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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×
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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
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“…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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Cited by
Sorted by citations
Items 101–134 of 134
Kurniawan, N. D. (2021) · Open Access Journal of Biomedical Science · doi:10.38125/oajbs.000263 · Cited by 3
“To-date, there are minimal reports of DTI changes in the EAE mouse brain [9], with most studies focussing on the spinal cord [22] or optical nerve [23-24].”
BackgroundISMRM Clinical Focus Meeting 2023: “Imaging the Fire in the Brain”
Agarwal, N., Fan, A. P., Huang, X., Dehkharghani, S., & van der Kolk, A. G. (2024) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29587 · Cited by 3
“27,28 However, the effect size of these changes may be reduced by the presence of vasogenic edema and demyelination in the same tissues during disease, both of which increase MD. 29 Cytotoxic edema has the same effect (reduced MD, increased MK) as microgliosis and therefore can be confused with…”
Zhang, J. K., Javeed, S., Greenberg, J. K., et al. (2023) · Neurosurgical FOCUS · doi:10.3171/2023.6.focus23273 · Cited by 3
Self-citationNoninvasive Imaging Techniques for Brain Edema
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Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline
Flaherty, R., Sui, Y. V., Masurkar, A. V., Betensky, R. A., Rusinek, H., & Lazar, M. (2024) · Frontiers in Neurology · doi:10.3389/fneur.2024.1360273 · Cited by 3
Hartz, S. M., Goswami, S., Oliver, A. I., Evans, A., Jackson, S., Linnenbringer, E. L., Moulder, K. L., Morris, J. C., & Mozersky, J. T. (2026) · BMJ Open · doi:10.1136/bmjopen-2025-099970 · Cited by 5
Cordano, C., Ramos, C., Arnow, S., Cruz-Herranz, A., Guglielmetti, C., Iester, M., & Bandini, F. (2020) · Neuroimmunology and Neuroinflammation · doi:10.20517/2347-8659.2020.54 · Cited by 2
“DTI-derived λ || and diffusion basis spectrum imaging have both shown high potential to detect axonal damage in the acute phase of EAE [144,146] , while changes in λ⊥ are usually detectable at a later stage of the disease (4 weeks onward) [92,140,145] .”
The Role of the Glymphatic System in Cervical Spondylotic Myelopathy
Zhang, J. K., Javeed, S., Greenberg, J. K., Yakdan, S. M., Gilandehi, S. N., Shah, L. M., Iyer, R. R., Dailey, A. T., Bisson, E. F., Mahan, M. A., et al. (2025) · Clinical Spine Surgery A Spine Publication · doi:10.1097/bsd.0000000000001763 · Cited by 1
“3,4 In this study, we focus on cervical spondylotic myelopathy (CSM), the most common form of chronic spinal cord injury in the world.”
Self-citationYu, Q., Kothe, K., Kwiatek, R. A., Fante, P. D., Bonner, A., Calhoun, V. D., & Shan, Z. (2026) · Human Brain Mapping · doi:10.1002/hbm.70505 · Cited by 2
“…(Wang et al. 2014; Zhan et al. 2018) approach is the diffusion-based neuroinflammation imaging (NII) model (Wang et al. 2011, 2015, 2019, 2024; Chiang et al. 2014; Samara et al. 2020), which estimates multiple biologically informed indices to quantify inflammation-related processes, including…”
Diffusion tensor imaging in chronic tension-type headache
Teepker, M., Vacik, L., Hermsen, A. M., Menzler, K., Mylius, V., Timmermann, L., Knake, S., & Belke, M. (2026) · Frontiers in Pain Research · doi:10.3389/fpain.2026.1850836 · Cited by 1
“Another explanation is an increase of the amount of free water in the interstitial space (60) due to glial cell activation (61) which may occur in neuroinflammation or injury (59) or due to neural plasticity (62).”
Zhu, N., Mazu, L., Xia, Z., et al. (2026) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.70573 · Cited by 1
Simulated Diffusion in Realistic Imaging Features of Tissue (Sim-DRIFT)
Blum, J., & Utt, K. (2023) · The Journal of Open Source Software · doi:10.21105/joss.05621 · Cited by 1
Microstructural abnormalities of the right hemisphere in preschool autism spectrum disorders
Yi, T., Liu, Y., Wei, W., He, S., & Jin, K. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.10.020 · Cited by 1
Yi, T., Li, W., Wei, W., Wu, G., Jiang, G., Gao, X., & Jin, K. (2024) · European Journal of Neuroscience · doi:10.1111/ejn.16615 · Cited by 1
“Although DBSI has been widely used in the diagnosis and subtype classification of autoimmune encephalomyelitis (Chiang et al., 2014), multiple sclerosis (Schiavi et al., 2021; Vavasour et al., 2022) and Parkinson ’ s disease (Hu et al., 2023), but not in preschool ASD.”
Neurophysiological Correlates of Fatigue in Multiple Sclerosis
Newland, P., Chen, L., Sun, P., & Zempel, J. M. (2021) · The Journal for Nurse Practitioners · doi:10.1016/j.nurpra.2021.02.012 · Cited by 1
Self-citationNoninvasive Detection and Differentiation of Axonal Injury/Loss, Demyelination, and Inflammation
Song, S., Spees, W. M., Sun, P., Wang, Y., & Cross, A. H. (2014) · Defense Technical Information Center (DTIC) · doi:10.21236/ada613483
Self-citationDisease in Patients with Multiple s clerosis Using high-gradient- Diffusion M
Huang, S. Y., Tobyne, S. M., Witzel, T., Wald, L. L., McNab, J. A., & Klawiter, E. C. (2016)
In Vivo Diffusion Tensor Imaging of the Rat Spinal Cord - Pilot Study
Dvořáková, L., Jiřík, R., Burian, M., et al. (2015) · ASEP
Current Challenges and Future Directions in Diffusion MRI: From Model- to Data- Driven Analysis
Schilling, K. G., Rogers, B., Anderson, A. W., & Landman, B. A. (2020) · Mathematics and visualization · doi:10.1007/978-3-030-52893-5_6
Optimal Fiber Diffusion Model Restoration
Greene, C. A., Revill, K. P., Buetefisch, C. M., et al. (2020) · Mathematics and visualization · doi:10.1007/978-3-030-52893-5_4
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“It has been successfully applied in animal models and translated to various CNS diseases (24, 27, 50).”
MethodSelf-citationPehlivan, E., Mwangi, M. K., Abraham, V., Mange, U., Song, S., Sun, P., & Mar, S. (2025) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2025.02.012
Self-citationDense Longitudinal Precision Neuroimaging of Recovery from Traumatic Brain InjuryPreprint
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Rajesh, A., Laumann, T. O., Wang, Q., Jiang, M., Wang, Y., Barch, D. M., Kay, B. P., Meyer, A., Dosenbach, N. U. F., & Gordon, E. M. (2025) · Research Square · doi:10.21203/rs.3.rs-7682138/v1
Self-citationBrain tissue polarimetry under simulated intraoperative conditions: Effects of edema and temperature
Gros, E., Sakiri, A., Moriconi, S., Jankauskas, A., Hasler, D., Lucas, T., McKinley, R. I., Maragkou, T., Novikova, T., Schucht, P., et al. (2026) · Journal of Innovative Optical Health Sciences · doi:10.1142/s1793545826500045
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“The complete diffusion-encoding scheme, including the distribution of gradient directions across the diffusion shells, was described previously (Chiang et al., 2014).”
Wang, Q. L., Jiang, M., Luna, A., Niu, X., Yuan, N., Sun, Q., Perrin, R. J., Franklin, E. E., Cruchaga, C., Flores, S. E., et al. (2026) · medRxiv · doi:10.64898/2026.06.11.26354743 · Cited by 1
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Xing, Y., Li, T., Zhang, Y. X., et al. (2026) · BMC Medical Imaging · doi:10.1186/s12880-026-02565-z
“In contrast, our study showed that MD, AD, and RD were all significantly increased within the first month after RT, a profile [32].”
Diffusion Weighted Imaging: Principles and Applications
Fischi-Gómez, E., Girard, G., & Estéban, O. (2026) · Neuromethods · doi:10.1007/978-1-0716-5340-1_11
Drottar, M., Kim, C. M., Cabral, H., & Bauer, C. M. (2026) · Behavioural Neurology · doi:10.1155/bn/3687804
“However, RD is a nonspecific measure [84, 85] and diffusion perpendicular to the fiber orientation reflects not only myelination, but is also influenced by edema [86, 87], axonal packing [88, 89], and chronic axonal loss [90].”
Taoka, T. (2026) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.70565
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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