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Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema
Open accessAbstract
The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA) and increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice.
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TL;DR
This study shows that increased extra-fiber cellularity and vasogenic edema confound conventional DTI-derived white matter metrics, whereas diffusion basis spectrum imaging (DBSI) separates and quantifies these components. A 25-direction DBSI scheme performed comparably to 99-direction DBSI for coherent tracts and detected axonal injury, demyelination, and inflammation in EAE mouse optic nerve with immunohistochemical validation.
Key findings
- In fixed normal mouse trigeminal nerve phantoms, DTI gave λ∥ = 0.77 ± 0.05 μm²/ms, λ⊥ = 0.18 ± 0.02 μm²/ms, and FA = 0.72 ± 0.04, while DBSI gave λ∥ = 1.09 ± 0.06 μm²/ms, λ⊥ = 0.15 ± 0.02 μm²/ms, and FA = 0.84 ± 0.02; DBSI estimated axonal fiber fraction 67 ± 3%, cellularity 14 ± 2%, and extra-axonal/extracellular space 20 ± 3%.
- Added 2% agar gel and Monte-Carlo simulations of vasogenic edema significantly decreased DTI FA and increased DTI radial diffusivity, with less consistent axial diffusivity effects, but did not affect DBSI-derived fiber FA, λ∥, or λ⊥. Increased simulated cellularity significantly decreased DTI FA and λ∥ with limited impact on λ⊥, while DBSI fiber parameters were largely unaffected.
- DBSI estimates from 25- vs. 99-direction schemes were comparable in simulation: axial diffusivity 1.80 ± 0.03 vs. 1.81 ± 0.05 μm²/ms, radial diffusivity 0.05 ± 0.01 vs. 0.04 ± 0.01 μm²/ms, and FA 0.96 ± 0.01 vs. 0.97 ± 0.01.
- In EAE vs. sham optic nerve, DBSI showed decreased λ∥ (1.73 ± 0.22 vs. 2.10 ± 0.04 μm²/ms, p = 0.020), increased λ⊥ (0.15 ± 0.03 vs. 0.11 ± 0.01 μm²/ms, p = 0.047), increased restricted isotropic fraction (0.10 ± 0.09 vs. 0.03 ± 0.01, p = 0.022), and increased non-restricted isotropic fraction (0.15 ± 0.03 vs. 0.03 ± 0.01, p < 0.0001); DAPI-positive nuclei correlated with DBSI cellularity (r = 0.65, p = 0.042).
Methods
- Monte-Carlo simulations and fixed mouse trigeminal nerve phantoms were used: 20 nerves, including single nerve only (n = 7) and nerve with varying amounts of 2% agar gel to mimic vasogenic edema (n = 13); simulations modeled axons, cells, and extra-axonal/extracellular space with varying fractions.
- Diffusion-weighted data were acquired with 99- and 25-direction encoding schemes and analyzed by conventional single-tensor DTI and DBSI, which fits anisotropic diffusion tensors plus a spectrum of isotropic diffusion tensors using nonnegative least-squares; restricted isotropic fraction was defined as ADC 0–0.3 μm²/ms and non-restricted as ADC > 0.3–3 μm²/ms.
- In vivo validation used five EAE mice at onset of acute optic neuritis and five age-matched sham controls, imaged at 4.7 T with a 25-direction scheme, followed by immunohistochemistry for SMI-31, MBP, and DAPI; statistical comparisons used t-tests, repeated-measures linear regression, Wilcoxon signed-rank tests, and Spearman correlations.
Limitations
- Stated: DBSI in its current form does not consider water exchange between intracellular and extracellular space, which may affect accuracy, especially under pathological conditions with altered membrane permeability.
- Stated: DBSI was developed for white matter tracts, and further generalization is needed for gray matter pathology in CNS disorders.
- Evident from the text: Monte-Carlo simulations neglected T1 and T2 decay; cellularity was difficult to control experimentally in fixed nerve phantoms, so simulations were used; sample sizes were small (n = 7 nerve-only, n = 13 gel phantoms, 5 EAE vs. 5 sham); and 25-direction DBSI metrics showed SNR-dependent bias, with restricted diffusion fraction overestimated at SNR ≤ 30 and non-restricted fraction underestimated at SNR = 20.
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Claims the paper makes
50 Own result · 15 Own interpretation · 7 Supported · 5 Partly supported · 3 No full text of the sources · 3 Not checked yet · 3 Own method · 3 No basis given · 1 Couldn’t confirm · 1 Sources not found · accuracy not yet measured
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In the paper
“However, such modification is insufficient to deal with coexisting CNS inflammation (increased cellularity and vasogenic edema) or tissue loss that may be seen in diseased tissues (Horsfield and Jones, 2002).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Partly supportedcites Horsfield and Jones, 2002 sourceExperimental — accuracy not yet measured
The Reduced diffusion anisotropy and Ischaemic leukoaraiosis sections describe how axonal loss and replacement or proliferation of glial cells affect diffusion measurements. The review does not assess whether adding an isotropic free-diffusion component is sufficient to account for inflammation, vasogenic edema, or tissue loss; that central modeling claim is unsupported. (LLM, conf=0.76)
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Although decreased DTI-derived fractional anisotropic (FA) has been demonstrated to reflect myelin damage in multiple sclerosis (MS) (Schmierer et al., 2007), it is not a marker specific to myelin damage since other pathological components may also contribute to diffusion anisotropy change (Werring et al., 1999, Assaf et al., 2002).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Introduction
What the sources say
- Not checked — no full text of the sourcecites Werring et al., 1999 source
- Partly supportedcites Assaf et al., 2002 sourceExperimental — accuracy not yet measured
The “High b-Value q-Space DWI vs. Conventional DTI” section (page unavailable) says FA can be affected by an incoherent arrangement of normal fibers, supporting the point that FA is not specific to myelin damage. The paper discusses demyelination, axonal loss, and inflammation in MS, but the passages do not establish that those other pathological components specifically cause changes in FA. (LLM, conf=0.83)
plainconditional- Asserted: passes — The authors put it forward as true.
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Every source the paper cites for this claim was checked and supports it.
In the paper
“These confounding effects were resolved and quantified by the recently developed DBSI analysis (Wang et al., 2011), as demonstrated herein using data generated by both Monte-Carlo simulation and tissue phantoms.”
- Also stated in: § Discussion · boosted
“In summary, we have demonstrated that DBSI removes confounding effects of increased cellularity and vasogenic edema on DTI derived λǁ, λ⊥, and FA.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Supportedcites Wang et al., 2011 source
In the trigeminal-nerve phantom results, added gel mimicking vasogenic oedema altered DTI-derived FA and axial and radial diffusivity, while DBSI separated the gel and produced comparable measurements with and without it. The Discussion reports that DBSI quantifies increased cellularity and oedema and improves axial and radial diffusivity measurements; its Figure 6 caption reports a correlation between DBSI-derived cell fraction and cell counts. The citing sentence describes Monte-Carlo simulations as a demonstration in the citing paper, not as a result attributed to Wang et al. (LLM, conf=0.90)
boosteddirect- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Discussion · boosted
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For example, inflammation associated vasogenic edema has been recognized to increase apparent diffusion coefficient (ADC) and underestimate the DTI-derived FA of fiber tracts (Pasternak et al., 2009, Naismith et al., 2010).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Introduction
What the sources say
- Not checked — no full text of the sourcecites Pasternak et al., 2009 source
- Partly supportedcites Naismith et al., 2010 sourceExperimental — accuracy not yet measured
The paper’s discussion (page unavailable in our copy) says diffusivity normalized in some acute MS lesions, perhaps as edema associated with an acute inflammatory infiltrate resolved. This supports a link between inflammation-associated edema and elevated diffusivity, but the paper does not specifically identify vasogenic edema or show that it increases ADC. (LLM, conf=0.82)
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For example, inflammation associated vasogenic edema has been recognized to increase apparent diffusion coefficient (ADC) and underestimate the DTI-derived FA of fiber tracts (Pasternak et al., 2009, Naismith et al., 2010).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Introduction
What the sources say
- Not checked — no full text of the sourcecites Pasternak et al., 2009 source
- Partly supportedcites Naismith et al., 2010 sourceExperimental — accuracy not yet measured
The “DTI parameters became altered during Gd enhancement” section (page unavailable) reports that FA decreased by 35% and mean diffusivity increased by 21% in acute MS lesions. The discussion suggests that normalization of diffusivity may reflect resolution of edema associated with inflammation, but the paper does not establish that vasogenic edema caused the lower FA or higher diffusivity in fiber tracts generally. (LLM, conf=0.86)
boosteddirect- Asserted: passes — The authors put it forward as true.
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Every source the paper cites for this claim was checked and supports it.
In the paper
“Similar to previous results on corpus callosum from cuprizone treated mice (Wang et al., 2011), in vivo DBSI derived restricted isotropic diffusion fraction map of optic nerve from EAE mice revealed a heterogeneous increase in cellularity, closely matching the pattern of DAPI-positive cell nuclei staining of the same nerve (Fig. 6e, k, and l).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Supportedcites Wang et al., 2011 source
The citation supports the comparison to earlier results in cuprizone-treated mouse corpus callosum, not the citing authors’ new optic-nerve finding. The Rostrocaudal analysis section (page not provided) reports that regional differences in DAPI nucleus counts were reflected by DBSI-estimated cell ratios; the Figure 6 caption reports a significant correlation between the two. (LLM, conf=0.92)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Rests on an assumption: Current MRI methods do not assess specific elements of CNS pathology.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The current results from fixed normal tissues and gel phantoms, and our previous in vivo mouse brain data (Wang et al., 2011) suggest that the DBSI approach allowed for an accurate estimation of white matter tract diffusion properties in the presence of increased cellularity and vasogenic edema.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Supportedcites Wang et al., 2011 source
The Discussion (page unavailable) says DBSI improves estimates of axial and radial diffusivity and can quantify increased cellularity and vasogenic oedema in phantoms and in vivo mouse corpus callosum. It also reports that DBSI correctly estimated fibre diffusion parameters despite added gel mimicking oedema. These findings support the citing sentence’s qualified claim. (LLM, conf=0.92)
hedgeddirect- Asserted: passes — The authors put it forward as true.
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- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DTI λ⊥ = 0.21 ± 0.04 vs. 0.11 ± 0.01 μm2/ms (p = 0.0046).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > In Vivo DBSI of EAE Mice at the Onset of Optic Neuritis
plaincorrelational- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DBSI-radial diffusivity was well-estimated at SNR ≥ 20 (Fig. 5B);”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effects of Noise on 25-Direction DBSI-Derived Parameters
boosted- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DTI λ∥ = 1.34 ± 0.37 vs. 1.89 ± 0.09 μm2/ms (p = 0.028);”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > In Vivo DBSI of EAE Mice at the Onset of Optic Neuritis
plain- Asserted: passes — The authors put it forward as true.
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- Probably not a substantial claim. 8
- It may state two separate claims as one. 18
- The quote only partly states this claim. 1
Every source the paper cites for this claim was checked and supports it.
In the paper
“Although decreased DTI-derived fractional anisotropic (FA) has been demonstrated to reflect myelin damage in multiple sclerosis (MS) (Schmierer et al., 2007), it is not a marker specific to myelin damage since other pathological components may also contribute to diffusion anisotropy change (Werring et al., 1999, Assaf et al., 2002).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Introduction
What the sources say
- Supportedcites Schmierer et al., 2007 source
The Discussion reports that lower FA in chronic post mortem MS brain is primarily associated with myelin loss. The Conclusion describes FA as a useful indicator of demyelination in the subjects studied. (LLM, conf=0.92)
boostedcorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The recently-developed diffusion basis spectrum imaging (DBSI) approach models white matter diffusion as the linear combination of multiple discrete anisotropic diffusion tensors describing axonal tracts and a spectrum of isotropic diffusion tensors describing restricted (reflecting cells), non-restricted (reflecting extra-axonal and extracellular space) diffusion components outside of axonal tr”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Introduction
What the sources say
- Supportedcites Wang et al., 2011 source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“This finding explains the difference of axial diffusivities derived by DTI and DBSI, and is consistent with our previously published results supported by immunohistochemistry (Wang et al., 2011).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effect of Vasogenic Edema on DTI/DBSI-Derived Parameters
What the sources say
- Supportedcites Wang et al., 2011 source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plaindirectn = 7- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one. The quote only partly states this claim.
- Supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“The inclusion of the isotropic component of free diffusion improved fiber diffusion measurements (Alexander et al., 2001, Papadakis et al., 2002).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Could not verifycites Alexander et al., 2001 sourceExperimental — accuracy not yet measured
The Discussion (page unavailable) reports improvements from reorienting diffusion tensors, particularly in regions of prolate diffusion. It does not say that including an isotropic component of free diffusion improved fiber diffusion measurements. Searches for that phrase and for a free-diffusion model found no supporting passage in our copy. (LLM, conf=0.76)
- Not checked — no full text of the sourcecites Papadakis et al., 2002 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim.
- Could not verify
Every source the paper cites for this claim was checked and supports it.
In the paper
“One advantage of using DBSI is its capability to resolve crossing fibers while still quantitatively deriving fiber associated anisotropic diffusion tensors to assess the axon and myelin integrity (Wang et al., 2011).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Supportedcites Wang et al., 2011 source
The Discussion states that DBSI resolves crossing fibres and quantifies the directional diffusivities of the resolved fibres. It also says that its axial and radial diffusivity measures reflect axonal versus myelin injury. The crossing-fibre phantom results provide further support for the first point; page numbers are not provided in our copy. (LLM, conf=0.94)
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
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The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Iron-oxide particles have been used to allow in vivo visualization of macrophages, but this method is insensitive to non-phagocytic cells involved in inflammation (Vellinga et al., 2008).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Partly supportedcites Vellinga et al., 2008 sourceExperimental — accuracy not yet measured
The Introduction (page unavailable) says that phagocytosis of iron-oxide particles by monocytes and macrophages enables visualization of cellular infiltration, supporting the first part of the claim. It does not establish that the method is insensitive to all non-phagocytic inflammatory cells; it also notes a report of particles in astrocytes. (LLM, conf=0.84)
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the restricted diffusion fraction was well-estimated at SNR ≥ 40 while overestimated at SNR ≤ 30 (Fig. 5C);”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effects of Noise on 25-Direction DBSI-Derived Parameters
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At SNR=100, DBSI axial diffusivity, radial diffusivity, restricted isotropic diffusion and non-restricted isotropic diffusion fractions were all estimated with high precision indicated by a small interquartile range and absence of outliers (Fig. 5).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effects of Noise on 25-Direction DBSI-Derived Parameters
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the SNR range readily achieved on typical animal and clinical scanner (SNR = 20 - 40), 25-direction DBSI-derived axial diffusivity was well-estimated (i.e., falls within the middle half of values at SNR=100) at SNR ≥ 30 while slightly underestimated at SNR = 20 (Fig. 5A);”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effects of Noise on 25-Direction DBSI-Derived Parameters
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For 99-direction diffusion weighted data (SNR = 40) from fixed trigeminal nerve only phantoms (N=7), DTI derived λ∥ = 0.77 ± 0.05 μm2/ms, λ⊥ = 0.18 ± 0.02 μm2/ms, and FA = 0.72 ± 0.04 were compared with those derived using DBSI where λ∥ = 1.09 ± 0.06 μm2/ms, λ⊥ = 0.15 ± 0.02 μm2/ms, FA = 0.84 ± 0.02 (n = 7, mean ± standard deviation).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effect of Vasogenic Edema on DTI/DBSI-Derived Parameters
plainn = 7- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DBSI estimated axonal fiber fraction to be 67 ± 3%, cellularity to be 14 ± 2%, and extra- axonal/extracellular space to be 20 ± 3% of the total signal intensity.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effect of Vasogenic Edema on DTI/DBSI-Derived Parameters
hedgedn = 7- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Qualitatively, axonal injury (decreased λ∥) and demyelination (increased λ⊥) occurred within the regions where increased cellularity (increased restricted isotropic diffusion fraction) was present (Figs. 6b, d, and e).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > In Vivo DBSI of EAE Mice at the Onset of Optic Neuritis
plaincorrelationalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For 99-direction diffusion weighted data (SNR = 40) from fixed trigeminal nerve only phantoms (N=7), DTI derived λ∥ = 0.77 ± 0.05 μm2/ms, λ⊥ = 0.18 ± 0.02 μm2/ms, and FA = 0.72 ± 0.04 were compared with those derived using DBSI where λ∥ = 1.09 ± 0.06 μm2/ms, λ⊥ = 0.15 ± 0.02 μm2/ms, FA = 0.84 ± 0.02 (n = 7, mean ± standard deviation).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effect of Vasogenic Edema on DTI/DBSI-Derived Parameters
plainn = 7- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and non-restricted diffusion fraction was well-estimated at SNR ≥ 30 while underestimated at SNR = 20 (Fig. 5D).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effects of Noise on 25-Direction DBSI-Derived Parameters
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Diffusion parameters derived by DTI were significantly affected with increasing cellularity, i.e., DTI derived λ∥, and FA significantly decreased with increasing cellularity while DBSI derived parameters were largely unaffected (Fig. 3).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effect of Increased Cellularity on DTI/DBSI-Derived Parameters
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The fixed trigeminal nerve phantom with 2% agar gel is a valid model of vasogenic edema.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The DAPI-positive nuclear counts increased in EAE optic nerves (6.6 × 103 ± 5.0 × 103 vs. 3.5 × 103 ± 0.7 × 103 counts/mm2) without reaching a statistical significance (p = 0.2).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > In Vivo DBSI of EAE Mice at the Onset of Optic Neuritis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Current MRI methods do not assess specific elements of CNS pathology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A comparable observation was seen in MC simulation data where DTI derived FA decreased while λ∥, λ⊥ increased with increasing vasogenic edema (i.e., extra-axonal/extracellular space, non-restricted isotropic diffusion component; Fig. 2B) with relatively stable DBSI derived FA, λ∥, and λ⊥.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Results > Effect of Vasogenic Edema on DTI/DBSI-Derived Parameters
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The Monte-Carlo simulation models using spheres and extra-axonal space accurately represent cellularity and vasogenic edema in tissue.
- Rests on an assumption: The fixed trigeminal nerve phantom with 2% agar gel is a valid model of vasogenic edema.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The partial volume effect of CSF, i.e., non-restricted (free) isotropic diffusion, on DTI indices has long been recognized, and limits DTI capability in regions abutting CSF, such as periventricular regions that are commonly affected by MS.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Matched sham control mice were randomly selected for in vivo DBSI acquisition whenever an EAE mouse was imaged.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Materials and Methods > Acute Optic Neuritis of EAE
plainn = 5- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The simulation was repeated 20 times for each SNR level.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Materials and Methods > Monte-Carlo Simulation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Unfortunately, this method is nonspecific, as a changed nerve cross-sectional size may reflect cell infiltration and/or edema and is further confounded by any tissue loss that may be present (Hickman et al., 2004a).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Not matchedcites Hickman et al., 2004a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“This is consistent with the pathogenesis of optic neuritis in EAE, i.e., nerve injury originates from the induced CNS inflammation but may not always occur with inflammation, and when it does occur axon injury may extend well outside the region of inflammation (Iglesias et al., 2001, Gold et al., 2006).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“DBSI in its current form does not consider the effect of water exchange between intracellular and extracellular space, which can potentially affect the accuracy of DBSI metrics, especially under pathological conditions where the permeability of cell membranes may be altered.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“An increased optic nerve area (swelling) has also been considered to reflect the severity of inflammation in acute optic neuritis (Hickman et al., 2004a, Boretius et al., 2008).”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Not matchedcites Hickman et al., 2004a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Boretius et al., 2008 source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“For example, gadolinium-enhanced T1W images reflect the leakage of blood-brain barrier (Guy et al., 1990, Hickman et al., 2004b, Qi et al., 2007) without information regarding the cellular infiltration.”
§ Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema > Discussion
What the sources say
- Not checked — no full text of the sourcecites Guy et al., 1990 source
- Not matchedcites Hickman et al., 2004b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Qi et al., 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
The impact of increased cellularity on diffusion anisotropy was unclear at the time of the study.
“However, its impact on diffusion anisotropy remains unclear.”
The authors state this as an assumption.
DTI assumes that diffusion of water molecules in CNS white matter follows mono-exponential diffusion-weighted signal decay and can be modeled by a single anisotropic tensor.
“DTI assumes that diffusion of water molecules in the CNS white matter follows mono-exponential diffusion weighted signal decay (typically at b-value < 1000 s/mm2), and was modeled by a single anisotropic tensor.”
The authors state this as an assumption.
The boundaries of axon and cell components in the Monte-Carlo simulation are impermeable.
“The boundaries of the axon and cell components were assumed to be impermeable.”
The authors state this as an assumption.
T1 and T2 decay effects for all spin trajectories in the Monte-Carlo simulation can be neglected.
“The effect of T1 and T2 decay for all spin trajectories were neglected (Liu et al., 2004).”
The authors state this as an assumption.
Intracellular water can be modeled as restricted isotropic diffusion due to hindrance of cell membranes and sub-cellular structures.
“To the first approximation, the intracellular water may be modeled as restricted isotropic diffusion due to the hindrance of cell membranes and sub-cellular structures.”
The paper relies on this without support.
A more comprehensive study was needed to investigate the effect of increased cellularity and vasogenic edema associated with inflammation.
“Although the effect of increased cell infiltration and edema on DTI-derived indices has been demonstrated previously using cuprizone treated mouse model and mouse trigeminal nerve phantoms (Wang, 2011), a more comprehensive study was needed to investigate the effect of increased cellularity and vasogenic edema associated with inflammation.”
The authors state this as an assumption.
Water spins in the Monte-Carlo simulation can move in or out of the imaging voxel without constraints, reflecting the real physical condition.
“During the simulation, water spins were allowed to walk in or out of the imaging voxel without constrains to reflect the real physical condition (Liu et al., 2004).”
The paper relies on this without support.
The non-restricted isotropic diffusion fraction measured by DBSI corresponds to vasogenic edema.
“The non-restricted isotropic diffusion fraction (i.e., the putative vasogenic edema) was also significantly higher in EAE optic nerves than that of the control (0.15 ± 0.03 vs. 0.03 ± 0.01, p < 0.0001).”
The paper relies on this without support.
The Monte-Carlo simulation models using spheres and extra-axonal space accurately represent cellularity and vasogenic edema in tissue.
“Since cellularity is difficult to change experimentally using the fixed nerve, MC simulation was performed with various extents of extra-fiber cells (i.e., spheres, restricted isotropic diffusion component) to mimic cellularity changes.”
The paper relies on this without support.
The fixed trigeminal nerve phantom with 2% agar gel is a valid model of vasogenic edema.
“With the addition of 2% agar gel, DTI derived λ⊥ or FA was significantly affected while DBSI derived parameters remained unchanged (Fig. 2A).”
The paper relies on this without support.
The EAE mouse model at the onset of optic neuritis is representative of human optic neuritis and CNS inflammation.
“In Vivo DBSI of EAE Mice at the Onset of Optic Neuritis”
The paper relies on this without support.
DAPI-positive nuclear counts represent cellularity.
“DAPI-positive nuclear counts correlated with DBSI estimated cellularity (r = 0.65, p = 0.042; Fig. 7E).”
The paper relies on this without support.
Current MRI methods do not assess specific elements of CNS pathology.
“MRI greatly aids CNS disease diagnosis, but current methods do not assess specific elements of CNS pathology.”
The paper relies on this without support.
Gd+ MRI is not sensitive to small inflammatory lesions or inflammation behind the intact blood-CNS barrier.
“However, Gd+ MRI is not sensitive to small inflammatory lesions or inflammation behind the intact BBB, underscoring the need to improve imaging sensitivity and specificity to identify new beneficial therapies.”
The paper relies on this without support.
99-direction human whole brain DBSI scans can be performed within 15 minutes on 3.0 T clinical scanners with fast diffusion-weighted EPI.
“With fast diffusion-weighted EPI sequence available on 3.0 T clinical scanners, 99-direction human whole brain DBSI scans can be performed within 15 minutes, making DBSI protocol feasible for routine clinical scanning of patients.”
Citations
Cites
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.072 · Cited by 3,288 · cited 2×
“…diffusion imaging (HARDI) acquisition scheme, NODDI assesses intra-cellular (assigned to space within neurites), extracellular (assigned to space around the neurites but occupied by glial cells), and CSF compartments for deriving neurite density and orientation dispersion (Zhang et al., 2012).”
MethodDysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582 · cited 1×
“…(λ║, parallel to white matter tract) and increased radial diffusivity (λ⊥, perpendicular to white matter tract) in animal models of central nervous system (CNS) diseases and injuries (DeBoy et al., 2007; Kim et al., 2006; Song et al., 2002; Campus Box 8227, Washington Ave, St Louis, MO 63110, USA.”
BackgroundSelf-citationJensen, J. H., Helpern, J. A., Ramani, A., Lu, H., & Kaczynski, K. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20508 · Cited by 2,488 · cited 1×
“…imaging (DKI) quantifies the non-Gaussian diffusion by estimating apparent diffusion kurtosis of diffusion displacement probability distribution (Jensen et al., 2005); generalized diffusion tensor imaging (gDTI) models the white matter tract via higher order tensors (Liu et al., 2004);…”
BackgroundMapping complex tissue architecture with diffusion spectrum magnetic resonance imaging
Wedeen, V. J., Hagmann, P., Tseng, W. I., Reese, T. G., & Weisskoff, R. M. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20642 · Cited by 1,339 · cited 4×
“The 99 diffusion-encoding directions were selected as prescribed in diffusion spectrum imaging (DSI) where the position vectors are the entire grid points (qx, qy, qz) over the 3-D q-space under the relationship that (qx(2) + qy(2) + qz(2)) ≤ r(2), where r = 3 for DBSI (Kuo et al., 2008; Wang et al., 2011; Wedeen et a…”
BackgroundMethodInfluentialFree water elimination and mapping from diffusion MRI
Pasternak, O., Sochen, N., Gur, Y., Intrator, N., & Assaf, Y. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22055 · Cited by 1,092
Gold, R. (2006) · Brain · doi:10.1093/brain/awl075 · Cited by 1,017 · cited 1×
“…is consistent with the pathogenesis of optic neuritis in EAE, i.e., nerve injury originates from the induced CNS inflammation but may not always occur with inflammation, and when it does occur axon injury may extend well outside the region of inflammation (Gold et al., 2006; Iglesias et al., 2001).”
BackgroundComposite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain
Assaf, Y., & Basser, P. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.03.042 · Cited by 856 · cited 2×
“, 2004); composite hindered and restricted model of diffusion (CHARMED) evaluates an extra-cellular compartment (assigned to hindered diffusion resulting from extra-axonal diffusion weighted signal) and intra-cellular compartments (assigned to restricted diffusion in a cylinder representing individual intra-axonal spa…”
BackgroundMethodOrientationally invariant indices of axon diameter and density from diffusion MRI
Alexander, D. C., Hubbard, P. L., Hall, M. G., Moore, E. A., Ptito, M., Parker, G. J. M., & Dyrby, T. B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.043 · Cited by 683
Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis
Werring, D. J., Clark, C. A., Barker, G. J., Thompson, A. J., & Miller, D. H. (1999) · Neurology · doi:10.1212/wnl.52.8.1626 · Cited by 621 · cited 2×
“, 2007), it is not a marker specific to myelin damage since other pathological components may also contribute to diffusion anisotropy change (Assaf et al., 2002; Werring et al., 1999).”
BackgroundSpatial transformations of diffusion tensor magnetic resonance images
Alexander, D. C., Pierpaoli, C., Basser, P. J., & Gee, J. C. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.963816 · Cited by 610 · cited 1×
“The inclusion of the isotropic component of free diffusion improved fiber diffusion measurements (Alexander et al., 2001; Papadakis et al., 2002).”
Background
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- Tu, 2010, Using absorption-mode images to improve in vivo DTI quality, Proc. Int. Soc. Magn. Reson. Med., 18, 4001
Cited by
Sorted by citations
Understanding the Physiopathology Behind Axial and Radial Diffusivity Changes—What Do We Know?
Winklewski, P. J., Sabisz, A., Naumczyk, P., Jodzio, K., Szurowska, E., & Szarmach, A. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00092 · Cited by 463
Design and Validation of Diffusion MRI Models of White Matter
Jelescu, I. O., & Budde, M. D. (2017) · Frontiers in Physics · doi:10.3389/fphy.2017.00061 · Cited by 240
“[67] demonstrated strong correlations between axial diffusivity (a DBSI parameter related to Da,‖) and axon integrity, radial diffusivity (a parameter related to De,⊥), and myelinated axons, and cell ratio (a parameter related to Diso) and histological cell counts, with similar findings reported in the experimental au…”
Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis
Granziera, C., Wuerfel, J. T., Barkhof, F., Calabrese, M., Stefano, N. D., Enzinger, C., Evangelou, N., Filippi, M., Geurts, J. J. G., Reich, D. S., et al. (2021) · Brain · doi:10.1093/brain/awab029 · Cited by 224
“Diffusion-based spectrum imaging (DBSI) models the diffusion signal as a linear combination of anisotropic diffusion tensors reflecting fibres, which are predominantly axon fibres in white matter, and a spectrum of isotropic diffusion tensors that encompass cells, oedema, and CSF.(101,102) Neurite orientation dispersi…”
BackgroundKodiweera, C., Alexander, A. L., Harezlak, J., McAllister, T. W., & Wu, Y.-C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.033 · Cited by 179
“…(Pasternak et al. 2009); three compartments of fast isotropic diffusion, restricted isotropic diffusion, and restrict anisotropic diffusion (Chiang et al. 2014); or three compartments of fast isotropic diffusion (e.g., cerebrospinal fluid (CSF)), anisotropic hindered diffusion (e.g.,…”
Wang, Y., Sun, P., Wang, Q., Trinkaus, K. M., Schmidt, R. E., Naismith, R. T., Cross, A. H., & Song, S. (2015) · Brain · doi:10.1093/brain/awv046 · Cited by 166
“We thus developed DBSI and have previously accurately captured the severity of axonal injury, demyelination, and inflammation in white matter tracts from mouse models of CNS inflammatory demyelination (Wang et al., 2011b, 2014; Chiang et al., 2014).”
InfluentialSelf-citationChallenges for biophysical modeling of microstructure
Jelescu, I., Palombo, M., Bagnato, F. R., & Schilling, K. G. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108861 · Cited by 166
“The key advantage of biophysical models is going beyond the Gaussian approximation regime, where really interesting and subtle features of microstructure become manifest.”
BackgroundApplication and evaluation of NODDI in the cervical spinal cord of multiple sclerosis patients
By, S., Xu, J., Box, B. A., Bagnato, F. R., & Smith, S. A. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.05.010 · Cited by 113
“…models in order to more accurately characterize the diffusion signal in the presence of multiple tissue compartments or milieu (Alexander, 2008; Assaf and Basser, 2005; Assaf et al., 2008; Behrens et al., 2003; Chiang et al., 2014; Stanisz et al., 1997; Xu et al., 2014; Zhang et al., 2012).”
Achievements and obstacles of remyelinating therapies in multiple sclerosis
Stangel, M., Kuhlmann, T., Matthews, P. M., & Kilpatrick, T. J. (2017) · Nature Reviews Neurology · doi:10.1038/nrneurol.2017.139 · Cited by 116
Samara, A., Murphy, T., Strain, J. F., Rutlin, J. R., Sun, P., Neyman, O., Sreevalsan, N., Shimony, J. S., Ances, B. M., Song, S., et al. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00464 · Cited by 88
Self-citationHarris, N. G., Verley, D. R., Gutman, B. A., & Sutton, R. L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.012 · Cited by 83
“…changes that result in alteration in diffusion characteristics is an ongoing process in many CNS diseases states, for example, multiple sclerosis (Budde et al., 2009; Chiang et al., 2014; Song et al., 2002) as well as TBI (Budde et al., 2011; Laitinen et al., 2010, 2015; MacDonald et al., 2007).”
BackgroundDance and music training have different effects on white matter diffusivity in sensorimotor pathways
Giacosa, C., Karpati, F. J., Foster, N. E. V., Penhune, V. B., & Hyde, K. L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.048 · Cited by 88
“Similarly, highly fanning tracts that make connections with broader, or even divergent (Kalil and Dent, 2014), cortical regions would have a less coherent orientation than more coherent tracts that connect narrower regions, potentially leading to lower FA and higher RD values (Budde and Annese, 2013; Chiang et al., 20…”
Weiss, C., Tursunova, I., Neuschmelting, V., Lockau, H., Nettekoven, C., Oros‐Peusquens, A., Stoffels, G., Rehme, A. K., Faymonville, A. M., Shah, N. J., et al. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.01.006 · Cited by 74
“FAT and MFL The FA is a useful indicator for the validity of reconstructed fibre tracts since it describes the degree of directionality of the diffusion process and, hence, is widely accepted as a measure for structural white matter integrity (Basser and Pierpaoli, 1996, 2011; Chiang et al., 2014; Dacosta-Aguayo et al…”
BackgroundZaninovich, O. A., Ávila, M. J., Kay, M. D., Becker, J., Hurlbert, R. J., & Martirosyan, N. L. (2019) · Neurosurgical FOCUS · doi:10.3171/2019.1.focus18591 · Cited by 69
Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature
Lindsey, H. M., Hodges, C. B., Greer, K. M., Wilde, E. A., & Merkley, T. L. (2021) · Neuropsychology Review · doi:10.1007/s11065-021-09485-5 · Cited by 65
Wang, Q., Wang, Y., Liu, J., Sutphen, C. L., Cruchaga, C., Blazey, T., Gordon, B. A., Su, Y., Chen, C., Shimony, J. S., et al. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101767 · Cited by 63
Self-citationErcan, E., Ingo, C., Tritanon, O., Magro‐Checa, C., Smith, A. K., Smith, S. A., Huizinga, T. W. J., van Buchem, M. A., & Ronen, I. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.05.002 · Cited by 59
“A recent investigation of the DTI correlates of vasogenic edema using both Monte-Carlo simulations and tissue phantom data showed that increased extent of vasogenic edema could result in decreased FA, increased RD and less significantly increased AD, similarly to the results in our study (Chiang et al., 2014).”
Result“A new imaging modality to non-invasively assess multiple sclerosis pathology”
Cross, A. H., & Song, S. (2016) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2016.10.002 · Cited by 56
“…25-direction sampling scheme as prescribed (Batchelor et al., 2003) with the addition of one extra non-diffusion (b = 0) weighted image can be sufficient for regions with more coherent non-crossing tracts, such as found in the spinal cord and optic nerve (Chiang et al., 2014; Murphy et al., 2016).”
Self-citationHybrid Diffusion Imaging in Mild Traumatic Brain Injury
Wu, Y., Mustafi, S. M., Harezlak, J., Kodiweera, C., Flashman, L. A., & McAllister, T. W. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2017.5566 · Cited by 62
Lucas, C. W., Tursunova, I., Neuschmelting, V., Nettekoven, C., Oros‐Peusquens, A., Stoffels, G., Faymonville, A. M., Jon, S. N., Langen, K., Lockau, H., et al. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.11.022 · Cited by 53
“The FA describes the degree of directionality of the diffusion process and therefore serves as a useful indicator for the integrity of reconstructed fibre tracts (Basser and Pierpaoli, 1996, 2011; Chiang et al., 2014; Dacosta-Aguayo et al., 2014; Holtrop et al., 2014; Van der Werff et al., 2014).”
BackgroundDeep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions
Ye, Z., George, A., Wu, A. T., Niu, X., Lin, J. Y.-Y., Adusumilli, G., Naismith, R. T., Cross, A. H., Sun, P., & Song, S. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51037 · Cited by 55
“3 μm(2)/ms ≤ ADC ≤3 μm(2)/ms) and free (ADC ≥ 3 μm(2)/ms) isotropic diffusion components represent water molecules in less densely packed environments, such as areas of tissue disintegration or edema, or contaminating cerebrospinal fluid (CSF).(12,19,20)”
BackgroundMethodSelf-citationHuang, S. Y., Tobyne, S. M., Nummenmaa, A. R., Witzel, T., Wald, L. L., McNab, J. A., & Klawiter, E. C. (2016) · Radiology · doi:10.1148/radiol.2016151582 · Cited by 46
Diffusion MRI quantifies early axonal loss in the presence of nerve swelling
Lin, T.-H., Chiang, C.-W., Perez-Torres, C. J., Sun, P., Wallendorf, M., Schmidt, R. E., Cross, A. H., & Song, S.-K. (2017) · Journal of Neuroinflammation · doi:10.1186/s12974-017-0852-3 · Cited by 42
Self-citationChan, K. C., Kancherla, S., Fan, S.-J., & Wu, E. X. (2014) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.14-14287 · Cited by 41
Sprooten, E., O’Halloran, R., Dinse, J., Lee, W. H., Moser, D. A., Doucet, G. E., Goodman, M. C., Krinsky, H., Paulino, A. J., Rasgon, A., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.023 · Cited by 40
Ye, Z., Price, R. L., Liu, X., Lin, J. Y.-Y., Yang, Q., Sun, P., Wu, A. T., Wang, L. Y., Han, R. H., Song, C., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-20-0736 · Cited by 41
Self-citationNon-invasive quantification of inflammation, axonal and myelin injury in multiple sclerosis
Schiavi, S., Petracca, M., Sun, P., Fleysher, L., Cocozza, S., Mendili, M. M. E., Signori, A., Babb, J. S., Podranski, K., Song, S., et al. (2020) · Brain · doi:10.1093/brain/awaa381 · Cited by 40
Self-citationDiffusion Assessment of Cortical Changes, Induced by Traumatic Spinal Cord Injury
Sun, P., Murphy, R. K. J., Gamble, P. G., George, A., Song, S., & Ray, W. Z. (2017) · Brain Sciences · doi:10.3390/brainsci7020021 · Cited by 36
“While providing a valuable tool to assess white matter integrity, unfortunately it is now recognized that DTI loses specificity and sensitivity with increasing pathological and anatomical complexity [4,16,17].”
MethodSelf-citationStrain, J. F., Burdo, T. H., Song, S., Sun, P., El-Ghazzawy, O., Nelson, B., Westerhaus, E. T., Baker, L., Vaida, F., & Ances, B. M. (2017) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0000000000001513 · Cited by 37
“In single diffusion models FA values reflect the diffusion signal (Figure 1 adapted from Chiang et al., 2014) but do not dissociate anisotropic from isotropic diffusion.”
BackgroundSelf-citationMagnetic Resonance Imaging Biomarker of Axon Loss Reflects Cervical Spondylotic Myelopathy Severity
Murphy, R. K. J., Sun, P., Xu, J., Wang, Y., Sullivan, S., Gamble, P. G., Wagner, J. M., Wright, N. N., Dorward, I. G., Riew, D. K., et al. (2015) · Spine · doi:10.1097/brs.0000000000001337 · Cited by 36
“Changes in these directional diffusivities derived from DTI have been demonstrated to reflect the white matter integrity.(12,13) Specifically, demyelination is thought to increase RD, presumably due to the loss of myelin integrity resulting in increased inter-axonal space.”
BackgroundSelf-citationSkinner, N. P., Kurpad, S. N., Schmit, B. D., & Budde, M. D. (2015) · NMR in Biomedicine · doi:10.1002/nbm.3405 · Cited by 35
“An increase in the intracellular volume fraction caused the measured diffusivity and kurtosis measured perpendicular to the fibers to decrease and increase, respectively, which recapitulates previous simulation studies (61,71).”
ResultWu, Y., Mustafi, S. M., Harezlak, J., Kodiweera, C., Randolph, J., Ford, J., & Wishart, H. A. (2018) · Neural Regeneration Research · doi:10.4103/1673-5374.243716 · Cited by 34
“…(Pasternak et al., 2009); three compartments of fast isotropic diffusion, slow restricted isotropic diffusion, and restricted anisotropic diffusion (Chiang et al., 2014); and three compartments of fast isotropic diffusion ( e.g ., CSF), anisotropic hindered diffusion ( e.g ., extracellular water),…”
Fan, C., Zhao, Y., Qian, Y., Yin, W., Liu, H., Lin, J., Yang, T., Fan, M., Gesang, L., & Zhang, J. (2016) · Scientific Reports · doi:10.1038/srep33596 · Cited by 35
Schiavi, S., Palombo, M., Zacà, D., Tazza, F., Lapucci, C., Castellan, L., Costagli, M., & Inglese, M. (2023) · Human Brain Mapping · doi:10.1002/hbm.26416 · Cited by 32
“…models based on geometrical assumptions have been proposed (Alexander et al., 2019; Chiang et al., 2014; Coelho et al., 2022; Jelescu et al., 2020; Jespersen et al., 2010; Novikov, Kiselev, et al., 2018; Novikov, Veraart, et al., 2018; Shemesh et al., 2015; Suh et al., 2003; Wang et al., 2014).”
MethodDiffusion basis spectrum imaging provides insights into MS pathology
Sun, P., George, A., Perantie, D. C., Trinkaus, K. M., Ye, Z., Naismith, R. T., Song, S., & Cross, A. H. (2019) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000000655 · Cited by 33
Self-citationAquaporin-4 Expression during Toxic and Autoimmune Demyelination
Rohr, S. O., Greiner, T., Joost, S., Amor, S., van der Valk, P., Schmitz, C., & Kipp, M. (2020) · Cells · doi:10.3390/cells9102187 · Cited by 30
“Edema formation, to a variable extent, has been demonstrated in MS [49–52] as well as the EAE [53,54] and cuprizone animal models [55,56].”
BackgroundObenaus, A., & Badaut, J. (2021) · Journal of Neuroscience Research · doi:10.1002/jnr.24837 · Cited by 32
“However the primary objective of the reported studies has not been to identify edema per se (Chiang et al., 2014; Hoefnagels et al., 2014).”
BackgroundWang, Q., Schindler, S. E., Chen, G., McKay, N. S., McCullough, A. A., Flores, S. E., Liu, J., Sun, Z., Wang, S., Wang, W., et al. (2024) · Neurology · doi:10.1212/wnl.0000000000208013 · Cited by 27
Self-citationYe, Z., Gary, S. E., Sun, P., Mustafi, S. M., Glenn, G. R., Yeh, F.-C. F., Merisaari, H., Song, C., Yang, R., Huang, G., et al. (2020) · NMR in Biomedicine · doi:10.1002/nbm.4414 · Cited by 30
“In our previous works,(22,34) we used a single fixed mouse trigeminal nerve juxtaposed with agar gel and demonstrated that DTI failed to accurately estimate axial diffusivity (AD), radial diffusivity (RD) and fractional anisotropy (FA), while DBSI could accurately calculate these metrics.(22,34) Additionally, DBSI was…”
BackgroundMethodInfluentialSelf-citationYoung consumers’ brain responses to pop music on Youtube
Cha, K. C., Suh, M., Kwon, G., Yang, S.-E., & Lee, E. (2019) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-04-2019-0247 · Cited by 26
Ly, M. J., Raji, C. A., Yu, G. Z., Wang, Q., Wang, Y., Schindler, S. E., An, H., Samara, A., Eisenstein, S. A., Hershey, T. G., et al. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-201242 · Cited by 26
“Briefly, this model incorporates voxel-wise diffusion tensors represent-ingarangeofpotentialpathologicalcomponentssuchasextracellularwater,thatisaconsideredmarkerof edemarelatedtoneuroinflammation[29,30].”
Self-citationTayebi, M., Holdsworth, S. J., Champagne, A. A., Cook, D. J., Nielsen, P. M. F., Lee, T., Wang, A., Fernandez, J., & Shim, V. (2021) · Brain Injury · doi:10.1080/02699052.2021.1895313 · Cited by 26
Vavasour, I. M., Sun, P., Graf, C., Yik, J. T., Kolind, S., Li, D. K. B., Tam, R. C., Sayao, A., Schabas, A. J., Devonshire, V. A., et al. (2021) · Multiple Sclerosis Journal · doi:10.1177/13524585211023345 · Cited by 28
Self-citationFerris, J. K., Greeley, B., Vavasour, I. M., Kraeutner, S. N., Rinat, S., Ramirez, J., Black, S. E., & Boyd, L. A. (2022) · Brain Communications · doi:10.1093/braincomms/fcac142 · Cited by 27
“However, while changes to DTI microstructure are often interpreted as reflecting demyelination, FA and MD are also impacted by multiple factors beyond damage to myelinated axons, such as underlying fibre architecture, the presence of glial cells, and changes in local fluid.(24,25) This is an important caveat in interp…”
BackgroundSanders, A. F. P., Tirado, B. A., Seider, N. A., Triplett, R. L., Lean, R. E., Neil, J. J., Miller, J. P., Tillman, R., Smyser, T. A., Barch, D. M., et al. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02782-6 · Cited by 27
Exploring experimental autoimmune optic neuritis using multimodal imaging
Manogaran, P., Walker-Egger, C., Samardzija, M., Waschkies, C. F., Grimm, C., Rudin, M., & Schippling, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.004 · Cited by 27
“Previous studies have observed similar diffusivity changes in the murine model of MS (Sun et al., 2007b; Chiang et al., 2014; Wu et al., 2007).”
InfluentialZhan, J., Lin, T., Libbey, J. E., Sun, P., Ye, Z., Song, C., Wallendorf, M., Gong, H., Fujinami, R. S., & Song, S. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00077 · Cited by 25
“…reflecting dendritic density in the hippocampal CA1 region, correlated positively with MAP2-positive staining, which is also consistent with previous findings that fiber density correlated with axonal density (Wang et al., 2011, 2013; Chiang et al., 2014; Cross and Song, 2017; Lin et al., 2017).”
BackgroundMethodResultInfluentialSelf-citationKim, J., Park, H., Jeong, M., & Kang, T. (2020) · Antioxidants · doi:10.3390/antiox9090854 · Cited by 25
Li, Z., Samara, A., Ray, M. K., Rutlin, J., Raji, C., Shimony, J., Sun, P., Song, S.-K., Hershey, T., & Eisenstein, S. A. (2022) · medRxiv · doi:10.1093/texcom/tgad007 · Cited by 24
“…true anatomy, have been histopathologically validated as neuroinflammationsensitive using rodent and human neural tissue in multiple sclerosis (Wang et al. 2011, 2015; Chiang et al. 2014; Wang et al. 2014), epilepsy (Zhan et al. 2018), and optic neuritis (Lin et al. 2017; Yang et al. 2021).”
BackgroundInfluentialSelf-citationWu, H., Wang, X., Gao, Y., Lin, F., Song, T., Zou, Y., Xu, L., & Lei, H. (2016) · Neuroscience · doi:10.1016/j.neuroscience.2016.02.043 · Cited by 24
Mozersky, J. T., Hartz, S. M., Linnenbringer, E. L., Levin, L., Streitz, M. L., Stock, K., Moulder, K. L., & Morris, J. C. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200993 · Cited by 24
“In our case, many of the research results being returned surpass clinical quality requirements [72-78], but they are not approved for clinical use.”
Diffusion kurtosis imaging study on temporal lobe after nasopharyngeal carcinoma radiotherapy
Wang, D., Li, Y., Jie, F., et al. (2016) · Brain Research · doi:10.1016/j.brainres.2016.07.041 · Cited by 22
Weber, A. M., Pukropski, A., Kames, C., Jarrett, M., Dadachanji, S. B., Taunton, J. A., Li, D. K. B., & Rauscher, A. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00575 · Cited by 24
“, an increase in extracellular fluid, such as vasogenic edema, should lead to increased radial diffusivity, and a partial increase in axial diffusivity (49).”
BackgroundSamara, A., Li, Z. A., Rutlin, J. R., Raji, C. A., Sun, P., Song, S., Hershey, T. G., & Eisenstein, S. A. (2021) · Obesity · doi:10.1002/oby.23201 · Cited by 20
Self-citationvan de Looij, Y., Dean, J. M., Gunn, A. J., Hüppi, P. S., & Sizonenko, S. V. (2015) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2015.03.009 · Cited by 21
“Furthermore, although DTI derived parameters reflecting the tissue microstructural integrity changes, they can also be modulated by other pathological states such as extra-fiber cellularity or edema associated with inflammation (Chiang et al., 2014).”
BackgroundYik, J. T., Becquart, P., Gill, J., Petkau, J., Traboulsee, A. L., Carruthers, R. L., Kolind, S., Devonshire, V. A., Sayao, A., Schabas, A. J., et al. (2021) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2021.103366 · Cited by 21
Lin, T., Sun, P., Hallman, M. J., Hwang, F. C., Wallendorf, M., Ray, W. Z., Spees, W. M., & Song, S. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2018.6016 · Cited by 20
“12,17,25,26 Regions of interest (ROIs) were manually drawn in ventral and lateral white matter tracts on the diffusion-weighted image, corresponding to the diffusion gradient direction perpendicular to white matter fiber tracts (with good gray-white matter contrast), to minimize partial volume…”
InfluentialSelf-citationSchmid, A. B., Campbell, J., Hurley, S. A., et al. (2018) · Investigative Radiology · doi:10.1097/rli.0000000000000492 · Cited by 19
Shirani, A., Sun, P., Schmidt, R. E., Trinkaus, K. M., Naismith, R. T., Song, S., & Cross, A. H. (2018) · Multiple Sclerosis Journal · doi:10.1177/1352458518786072 · Cited by 19
Self-citationMishra, A., Wang, F., Chen, L. M., & Gore, J. C. (2020) · Scientific Reports · doi:10.1038/s41598-020-74234-2 · Cited by 18
Sensitivity and specificity of diffusion MRI to neuroinflammatory processes
Jelescu, I., & Fieremans, E. (2023) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-323-91771-1.00010-1 · Cited by 18
Myelin water imaging of moderate to severe diffuse traumatic brain injury
Choi, J. Y., Hart, T., Whyte, J., Rabinowitz, A. R., Oh, S., Lee, J., & Kim, J. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101785 · Cited by 18
“Recent evidence suggests that DTI metrics may not be specific to myelin integrity (Chiang et al., 2014; Wang et al., 2014).”
Kancherla, S., Kohler, W. J., van der Merwe, Y., & Chan, K. C. (2016) · PLoS ONE · doi:10.1371/journal.pone.0165169 · Cited by 17
Zhu, F., Zeng, L., Gui, S., Liu, Y., Wang, Y., Cao, X., Lin, H., Yang, L., Kong, X., & Guo, X. (2021) · World Neurosurgery · doi:10.1016/j.wneu.2021.01.146 · Cited by 17
Self-citationBauer, C. M., & Merabet, L. B. (2024) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2301001 · Cited by 18
“However, changes in RD may not be specific to myelin integrity, but may also reflect changes in the extra-axonal water content [78,79].”
Zhang, J. K., Yakdan, S. M., Kaleem, M. I., et al. (2024) · Journal of Neurosurgery Spine · doi:10.3171/2024.4.spine24107 · Cited by 15
Self-citationLin, T., Zhan, J., Song, C., Wallendorf, M., Sun, P., Niu, X., Yang, R., Cross, A. H., & Song, S. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.592063 · Cited by 15
Self-citationDiffusion Basis Spectrum Imaging Provides Insights Into Cervical Spondylotic Myelopathy Pathology
Zhang, J. K., Jayasekera, D., Song, C., Greenberg, J. K., Javeed, S., Dibble, C. F., Blum, J., Sun, P., Song, S., & Ray, W. Z. (2022) · Neurosurgery · doi:10.1227/neu.0000000000002183 · Cited by 15
Self-citationMRI-based assessment of function and dysfunction in myelinated axons
Spees, W. M., Lin, T., Sun, P., Song, C., George, A., Gary, S. E., Yang, H.-C., & Song, S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801788115 · Cited by 15
“For samples with this type of tissue geometry, the 25-direction DW acquisition scheme has been shown to provide DBSI modeling results (fiber fractions, diffusivities, and isotropic diffusion components) in good agreement with those obtained using a more extensive 99-direction diffusion-weighting scheme when tested wit…”
MethodSelf-citationLongitudinal multiparametric MRI of traumatic spinal cord injury in animal models
Chen, L. M., Wang, F., Mishra, A., Yang, P., Sengupta, A., Reed, J. L., & Gore, J. C. (2023) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2023.06.007 · Cited by 15
Otte, W. M., van der Marel, K., van Meer, M. P. A., van Rijen, P. C., Gosselaar, P. H., Braun, K. P. J., & Dijkhuizen, R. M. (2015) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2015.101 · Cited by 15
Talbott, J. F., Nout‐Lomas, Y. S., Wendland, M. F., Mukherjee, P., Huie, J. R., Hess, C. P., Mabray, M. C., Bresnahan, J. C., & Beattie, M. S. (2015) · Journal of Neurotrauma · doi:10.1089/neu.2015.4102 · Cited by 14
Murphy, S. A., Furger, R., Kurpad, S. N., Arpinar, V. E., Nencka, A. S., Koch, K. M., & Budde, M. D. (2021) · American Journal of Neuroradiology · doi:10.3174/ajnr.a7295 · Cited by 13
Sun, Z., Wu, W., Zhao, P., Wang, Q., Woodard, P. K., Nelson, D. M., Odibo, A. O., Cahill, A. G., & Wang, Y. (2022) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.24959 · Cited by 13
Self-citationZhang, J. K., Jayasekera, D., Javeed, S., Greenberg, J. K., Blum, J., Dibble, C. F., Sun, P., Song, S., & Ray, W. Z. (2022) · The Spine Journal · doi:10.1016/j.spinee.2022.12.003 · Cited by 13
Self-citationVasogenic Brain Edema During Maintenance Hemodialysis
Schaier, M., Wolf, R. C., Kubera, K. M., Nagel, S., Bartsch, A., Zeier, M., Bendszus, M., & Herweh, C. (2019) · Clinical Neuroradiology · doi:10.1007/s00062-019-00865-2 · Cited by 13
Jayasekera, D., Zhang, J. K., Blum, J., Jakes, R. S., Sun, P., Javeed, S., Greenberg, J. K., Song, S., & Ray, W. Z. (2022) · Journal of Neurosurgery Spine · doi:10.3171/2022.3.spine2294 · Cited by 12
Self-citationHu, Z., Sun, P., George, A., Zeng, X., Li, M., Lin, T., Ye, Z., Wei, X., Jiang, X., Song, S., et al. (2023) · European Radiology · doi:10.1007/s00330-023-09780-0 · Cited by 12
“The increase of cellularity (leading to reduced DTI-AD) and vasogenic edema (resulting in increased DTI-AD) is associated with neuroinflammation that typically caused the decrease in DTI-FA [14].”
BackgroundInfluentialSelf-citationZhang, J. K., Javeed, S., Greenberg, J. K., Yakdan, S. M., Kaleem, M. I., Botterbush, K. S., Benedict, B. C., Dibble, C. F., Sun, P., Sherrod, B. A., et al. (2024) · Neurosurgery · doi:10.1227/neu.0000000000003037 · Cited by 11
Self-citationZhang, J. K., Sun, P., Jayasekera, D., et al. (2022) · Spine · doi:10.1097/brs.0000000000004456 · Cited by 11
Self-citationDiffusivity in the core of chronic multiple sclerosis lesions
Klistorner, A., Wang, C., Yiannikas, C., Parratt, J., Barton, J., You, Y., Graham, S. L., & Barnett, M. H. (2018) · PLOS ONE · doi:10.1371/journal.pone.0194142 · Cited by 11
Dolatshahi, M., Commean, P. K., Rahmani, F., Xu, Y., Liu, J., Kasani, S. H., Naghashzadeh, M., Lloyd, L., Nguyen, C., McBee‐Kemper, A., et al. (2024) · Obesity · doi:10.1002/oby.24188 · Cited by 10
“A 99-direction diffusion-encoding scheme adapted from the previously prescribed DBSI was employed [ 14, 26].”
Self-citationZhu, F., Wang, Y., Kong, X., et al. (2022) · European Spine Journal · doi:10.1007/s00586-022-07207-w · Cited by 10
Self-citationSevere central nervous system demyelination in Sanfilippo disease
Taherzadeh, M., Zhang, E., Londoño, I., Song, S., Wang, S., Cooper, J. D., Kennedy, T. E., Morales, C. R., Chen, Z., Lodygensky, G. A., et al. (2023) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2023.1323449 · Cited by 10
“It has been also applied to detect white matter injury with edema or tissue loss [56-58].”
MethodSelf-citationCortical-cerebellar circuits changes in preschool ASD children by multimodal MRI
Yi, T., Ji, C., Wei, W., Wu, G., Jin, K., & Jiang, G. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae090 · Cited by 8
Waters, A. B., Sawyer, K. S., & Gansler, D. A. (2019) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2019.107710 · Cited by 8
Han, R. H., Johanns, T. M., Roberts, K. F., Yu, T., Luo, J. R., Ye, Z., Sun, P., Blum, J., Lin, T., Song, S., et al. (2023) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdad050 · Cited by 7
Self-citationHeterogeneity Diffusion Imaging of gliomas: Initial experience and validation
Wang, Q., Guzmán, G., Ponisio, M. R., LaMontagne, P., Dahiya, S. M., Marcus, D. S., Milchenko, M. V., Shimony, J. S., Liu, J., Chen, G., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225093 · Cited by 7
Self-citationCriswell, S. R., Nielsen, S. S., Faust, I. M., Shimony, J. S., White, R. L., Lenox-Krug, J., & Racette, B. A. (2023) · NeuroToxicology · doi:10.1016/j.neuro.2023.04.013 · Cited by 7
“In comparison to conventional diffusion tensor imaging (DTI) modeling, DBSI modeling differentiates and quantifies multiple intravoxel pathological processes by assigning specific diffusion components to different pathologic mechanisms (Wang et al., 2011; Wang et al., 2014).”
InfluentialTherapeutic potential of COX-2 inhibitors in neuropsychiatric disorders
Sharma, V., Sharma, P., & Singh, T. G. (2025) · Journal of Neural Transmission · doi:10.1007/s00702-025-02932-0 · Cited by 8
“Changes in the levels of cytokines and an im-balance between immune responses were also detected (Chiang et al. 2014).”
Yang, R., Lin, T., Zhan, J., Lai, S., Song, C., Sun, P., Ye, Z., Wallendorf, M., George, A., Cross, A. H., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102732 · Cited by 7
Self-citationKim, J.-W., Andersson, J., Seifert, A. C., Sun, P., Song, S., Dula, C., Naismith, R. T., & Xu, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.058 · Cited by 7
“(iii) A 25 directional diffusion encoding table with different b values was used, which has been shown through simulation and small animal studies to provide reliable DBSI modeling results for single coherent fiber bundle, such as the optic nerve or spinal cord white matter (Chiang et al., 2014).”
MethodSelf-citationDiffusion basis spectrum imaging of white matter in schizophrenia and bipolar disorder
Mamah, D., Patel, A., Chen, S., Wang, Y., & Wang, Q. (2025) · Brain Imaging and Behavior · doi:10.1007/s11682-025-01021-w · Cited by 6
“( Wang et al., 2014) There has been increasing evidence for an inflammatory signature in the brain in schizophrenia, including overexpression of pro-inflammatory cytokines,(Fillman et al., 2014) changes to the blood–brain barrier with macrophage infiltration (Cai et al., 2020) and possible…”
Self-citationMyelin-weighted imaging derived from quantitative parameter mapping
Kanazawa, Y., Harada, M., Taniguchi, Y., Hayashi, H., Abe, T., Otomo, M., Matsumoto, Y., Ono, M., Ito, K. R., Bito, Y., et al. (2022) · European Journal of Radiology · doi:10.1016/j.ejrad.2022.110525 · Cited by 6
Zhang, J. K., Javeed, S., Greenberg, J. K., et al. (2023) · Clinical Spine Surgery A Spine Publication · doi:10.1097/bsd.0000000000001451 · Cited by 6
Self-citationYang, H.-C., Lavadi, R. S., Sauerbeck, A. D., Wallendorf, M., Kummer, T. T., Song, S., & Lin, T. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1269817 · Cited by 5
Self-citationKilgore, C. B., Strain, J. F., Nelson, B., Cooley, S. A., Rosenow, A., Glans, M., Cade, W. T., Reeds, D. N., Paul, R. H., & Ances, B. M. (2021) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0000000000002907 · Cited by 5
Psilocybin’s acute and persistent brain effects: a precision imaging drug trial
Subramanian, S., Reneau, T. R., Perry, D., Chacko, R. V., Laumann, T. O., Flavin, K., Horan, C., Schweiger, J. A., Metcalf, N. V., Lenze, E. J., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-05189-0 · Cited by 6
“DBSI models inflammation-associated cellularity (DBSI-restriction fraction, RF) and vasogenic edema (DBSI-hindered fraction, HF) while accounting for partial volume effects resulting from cerebrospinal fluid contamination and crossing fibers 45,46 .”
Zvenigorodsky, V., Gruenbaum, B. F., Shelef, I., et al. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26157333 · Cited by 4
“MD measures the overall magnitude of water diffusion and RD measures its perpendicular qualities of water diffusion; however, they can be affected by mechanisms besides axonal injury, such as demyelination, edema, and inflammation [31].”
Wooliscroft, L., Salter, A. R., Adusumilli, G., Levasseur, V. A., Sun, P., Lancia, S., Perantie, D. C., Trinkaus, K. M., Naismith, R. T., Song, S., et al. (2024) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2024.105494 · Cited by 5
Self-citationShah-abadi, M. E., Ariaei, A., Mohammadi, H., et al. (2023) · Journal of Advances in Medical and Biomedical Research · doi:10.30699/jambs.31.148.415 · Cited by 4
Metadata
- Authors
- Chiang, C.-W., Wang, Y., Sun, P., Lin, T.-H., Trinkaus, K., Cross, A. H., & Song, S.-K.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Song, Sheng-Kwei
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-11
- Volume
- 101
- Pages
- 310-319
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4165711
- OpenAlex
- W2027270401
- Cited by
- 134
- References
- 37
- Citations by year
- 2026: 13 · 2025: 8 · 2024: 12 · 2023: 13 · 2022: 8 · 2021: 16 · 2020: 13 · 2019: 10 · 2018: 12 · 2017: 7 · 2016: 10 · 2015: 10 · 2014: 2
- FWCI
- 6.97
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (submittedVersion)
- PubMed Central (submittedVersion)
- Funders
- National Institute of Health (R01-NS047592, P01-NS059560)
- National Multiple Sclerosis Society (NMSS) (RG 4549A4/1)
- Department of Defense Ideal Award (W81XWH-12-1-0457)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › NMR spectroscopy and applications
- Keywords
- diffusion basis spectrum imaging, vasogenic edema, white matter tracts, fractional anisotropy, axial and radial diffusivity, Monte Carlo simulation, tissue phantoms, experimental autoimmune encephalomyelitis, optic nerve, multiple sclerosis, demyelination, axonal injury, inflammation
- MeSH terms
- Animals, Computer Simulation, Edema, Female, Mice, Inbred C57BL, Monte Carlo Method, Nerve Fibers, Myelinated, Neuritis, Autoimmune, Experimental, Optic Nerve, Trigeminal Nerve, Phantoms, Imaging, Mice, Diffusion Tensor Imaging, White Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-13, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-13 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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