NODDI in clinical research

In the paper

“A longitudinal follow-up of patients with orthopedic trauma revealed increased f fw and decreased NDI in WM compared with controls at 2 weeks post-injury”

What the sources say

• Disputed

  The Discussion identifies orthopedic trauma patients as the control group, not the group with these changes. It reports decreased NDI and increased free-water fraction (FISO) in patients with mTBI versus trauma controls at the early, 2-week time point. The supplied passages do not give page numbers. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  cites Palacios et al., 2018 sourceExperimental — accuracy not yet measured

In the paper

“Care is needed in the interpretation of results provided by these biophysical models, because to achieve and prove specificity is extremely challenging (for recent reviews, see (Jelescu and Budde, 2017;Novikov et al., 2018a); and Jelescu et al. in this special issue).”

What the sources say

• Supported

  Section 2.3 cautions that even a strong correlation with microscopy does not prove parameter specificity. The Summary adds that diffusion MRI is an indirect measure of microstructure and that some model parameters are particularly difficult to validate independently. Together, these passages support the citing sentence’s caution about achieving and demonstrating specificity. (LLM, conf=0.91)

  cites Jelescu and Budde, 2017 source
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Novikov et al., 2018a

In the paper

“NDI of the parieto-occipital WM was also correlated with visuospatial and visuoperceptual cognitive performance, a marker of parietal cortex function.”

What the sources say

• Supported

  The Results section reports significant positive correlations in patients between NDI in white-matter projections from both parieto-occipital lobes and visuospatial and visuoperceptual task performance. The Discussion identifies that performance as a marker of parietal cortex function, and the paper identifies the patient group as having young-onset Alzheimer’s disease. (LLM, conf=0.94)

  cites Slattery et al., 2017 source

In the paper

“However, as with DTI, care should be taken when comparing data from different scanners: field strength has significant effects on NODDI parameters (Chung et al., 2016;De Santis et al., 2019), and interscanner reproducibility has been shown to be lower than intra-scanner reproducibility, even at the same field strength (3 T) (Andica et al., 2019b).”

What the sources say

• Supported

  The Discussion states that magnetic field strength has a significant effect on estimated NODDI parameters. The Conclusion reports significant changes in intracellular volume fraction and orientation distribution index in specific white and grey matter regions and advises care when interpreting data acquired at different field strengths. (LLM, conf=0.94)

  cites Chung et al., 2016 source
• Partly supported

  The Statistical analysis section compares 3 T and 7 T protocols for the NODDI measures. Table 3 (DISCUSSION; page unavailable) reports a significant protocol effect for FR NODDI (p < 0.05), but not for ODI. The claim is therefore supported for one NODDI parameter, not NODDI parameters generally. (LLM, conf=0.88)

  cites De Santis et al., 2019 sourceExperimental — accuracy not yet measured

In the paper

“Several studies have reported non-monotonic behavior of dMRI metrics in relation to amyloid deposition in both GM (Montal et al., 2018) and WM (Dong et al., 2020;Wolf et al., 2015) in human Alzheimer's disease, as well as in a rat model of Alzheimer's disease (Fick et al., 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Montal et al., 2018 source
• Supported

  Dong et al.’s Results (ROI Analysis: Group comparisons; page not provided) report nonmonotonic white-matter diffusion metric changes across groups with increasing amyloid burden. The Abstract likewise reports a nonmonotonic trend in human participants. This citation supports the white-matter portion of the sentence; the gray-matter and rat-model portions are attributed to other sources. (LLM, conf=0.94)

  cites Dong et al., 2020 source
• ?Not checked — no full text of the sourcecites Wolf et al., 2015 source

In the paper

“ODI has shown a stronger correlation than has FA with orientation dispersion measured by histology (Grussu et al., 2017;Schilling et al., 2018), indicating that NODDI has the ability, at least partly, to disentangle the effect of orientation dispersion.”

What the sources say

• Supported

  The Results (Statistical analysis; page not supplied) report a strong correlation between ODI and histological orientation dispersion (CV). In the control samples, regression models show a stronger association with CV for ODI than for FA; the paper also describes ODI–CV as the strongest and most consistent association across controls and multiple sclerosis cases. (LLM, conf=0.90)

  cites Grussu et al., 2017 source
• Supported

  In Results §3.1 (Fig. 7E–F), the paper reports a moderate negative correlation between DTI FA and histological ODI, while describing NODDI’s correlation with histological ODI as much stronger overall. The passage supports the comparison in the citing sentence; the paper notes that NODDI overestimated ODI in its ex vivo experiments. (LLM, conf=0.86)

  cites Schilling et al., 2018 source

In the paper

“Similarly, in another mouse model of Alzheimer's disease, greater NDI and ODI than controls were observed in WM and hippocampus (Colon-Perez et al., 2019).”

What the sources say

• Supported

  The Results report higher intracellular volume fraction (ICVF), the paper’s neurite-density measure, in the cerebral peduncle (white matter) and hippocampus of TgCRND8 mice, and higher ODI in white-matter regions and the hippocampus. The Discussion explicitly describes increases in both measures relative to non-transgenic controls. The supplied passages do not give page numbers. (LLM, conf=0.93)

  cites Colon-Perez et al., 2019 source

In the paper

“Scan-rescan studies have reported excellent repeatability of NODDI in the brain, with the intra-subject coefficients of variation (CoV) for NDI and ODI mostly below 5% (Andica et al., 2019b;Chang et al., 2015;Chung et al., 2016;Granberg et al., 2017;Huber et al., 2019;Tariq et al., 2012), which is comparable with that of DTI, although (Chung et al., 2016) have reported a greater CoV than for FA in”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Andica et al., 2019b
• Supported

  Results §3.5 reports that test–retest CoVs for ODI and NDI were below 5% in every examined white matter group. Discussion §4.3 calls the reproducibility excellent and notes that repeat scans were limited to adults in their 20s. (LLM, conf=0.93)

  cites Chang et al., 2015 source
• Partly supported

  The Methods and Results describe repeated acquisitions within a session in healthy subjects and report within-subject CVs for NODDI measures. The Discussion gives a range of 0.6%–7.3% (excluding νiso), but does not establish that NDI and ODI values were mostly below 5%; this was within-session reproducibility, not a separate-session scan–rescan test. (LLM, conf=0.84)

  cites Chung et al., 2016 sourceExperimental — accuracy not yet measured

In the paper

“(Lampinen et al., 2019) clarified the risk of biases introduced by fixing parameters, where different constraints led to different rankings of neurite density among brain regions.”

What the sources say

• Supported

  The Results section, under “Brain region rankings by the ‘stick’ fractions of constrained biophysical models,” reports that six constraint sets produced significantly different regional rankings (p = 0.025). The paper treats these model-derived ‘stick’ fractions as indices of neurite density, which is the sense in which the citing sentence is supported. (LLM, conf=0.91)

  cites Lampinen et al., 2019 source

In the paper

“In a longitudinal follow-up, ODI in the posterior limb of the internal capsule at the first hospital visit predicted upper extremity motor function at 5-week follow-up (Hodgson et al., 2019).”

What the sources say

• Supported

  The Conclusions report that baseline ODI asymmetry in the posterior limb of the internal capsule (PLIC) predicted upper-extremity motor outcomes approximately five weeks after stroke. The Abstract specifies that the baseline MRI was obtained 3–12 days after stroke and that the follow-up outcome was an upper-extremity Fugl-Meyer score. The measured predictor was ODI-based asymmetry between the two sides of the PLIC, rather than ODI alone. (LLM, conf=0.91)

  cites Hodgson et al., 2019 source

In the paper

“Within the CST distal to the lesion, increased ODI has been observed in the subacute phase and this increase persisted in the chronic phase (Mastropietro et al., 2019).”

What the sources say

• Supported

  The Discussion reports significantly higher ODI in the ipsilesional PLIC and CP regions of the CST in the subacute phase. The chronic-phase Results report persistently higher ODI in both regions, including the more distal CP (p = 0.014). (LLM, conf=0.94)

  cites Mastropietro et al., 2019 source

In the paper

“indicating that NODDI's assumptions of fixed diffusivity and tortuosity constraints are most likely broken.”

What the sources say

• Partly supported

  In “Mechanism for the Water ADC Decrease That Accompanies Brain Injury” (page unavailable), the paper challenges an older model’s assumption that compartmental diffusivities remain unchanged after injury and suggests intracellular diffusivity decreases. It does not discuss NODDI or establish that NODDI’s tortuosity constraint is broken in acute cerebral ischemia. (LLM, conf=0.83)

  cites Ackerman and Neil, 2010 sourceExperimental — accuracy not yet measured

In the paper

“preclinical studies in acute cerebral ischemia using compartment-specific tracers have shown a profound decrease of diffusivities in both intra-and extra-cellular spaces (Ackerman and Neil, 2010)”

What the sources say

• Supported

  The “Changes in ADC Following Brain Injury” section reports that, after global ischemia, the compartment-specific FDG-6-P tracer’s ADC fell from 0.16 to 0.10 μm²/ms intracellularly and from 0.14 to 0.09 μm²/ms extracellularly. These substantial decreases support the claim about tracer-measured diffusivity in both spaces; the supplied passage has no page number. (LLM, conf=0.92)

  cites Ackerman and Neil, 2010 source

In the paper

“They also found that patients with secondary progressive MS showed more widespread NDI reduction than those with relapsing-remitting MS, suggesting the potential utility of NODDI for predicting transition from relapsing-remitting MS to secondary progressive MS.”

What the sources say

• Supported

  The Discussion reports a widespread decrease in NDI in patients with secondary progressive MS and says neurite abnormalities were less extensive in those with relapsing-remitting MS. The Abstract Results likewise describe more widespread abnormalities in the secondary progressive group. Page numbers were not available in our copy. (LLM, conf=0.94)

  cites Spanò et al., 2018 source

In the paper

“The study of postmortem spinal cord by (Grussu et al., 2017) also revealed that NDI should be interpreted in relation to both neurite density and myelin density.”

What the sources say

• Supported

  The Discussion (Statistical analysis) says NDI is sensitive to local axon and dendrite density but is also strongly influenced by myelination, limiting its interpretation without myelin mapping. The Discussion (Limitations) likewise cautions that myelin can affect NDI. This supports interpreting NDI in relation to both neurite and myelin density. (LLM, conf=0.94)

  cites Grussu et al., 2017 source

In the paper

“and that reduced ODI within the precentral gyrus was correlated with disease duration, presumably representing reduced dendritic density and branching.”

What the sources say

• Supported

  The Results section ('Correlation of NODDI parameters with disease severity'; page unavailable) reports that ODI correlated with disease duration predominantly in the right precentral gyrus, with a smaller region in the left. The Discussion (page unavailable) interprets reduced ODI in this region as compatible with loss of dendritic density and reduced dendritic branching. (LLM, conf=0.94)

  cites Broad et al., 2019 source

In the paper

“Recently, (Taoka et al., 2020) applied NODDI in 11 cases of tuberous sclerosis and confirmed reduced NDI in tubers.”

What the sources say

• Supported

  The Abstract reports NODDI imaging in 11 tuberous sclerosis cases. The Discussion identifies Ficv as a measure of neurite density and reports decreased Ficv in quantitative measurements of tubers. Page numbers are not provided in our copy. (LLM, conf=0.91)

  cites Taoka et al., 2020 source

In the paper

“In WM, along-tract analysis of the nigro-striatal pathway (Andica et al., 2018) demonstrated reduced NDI in the tract portion proximal to the striatum, which is consistent with histological evidence of retrograde axonal degeneration ('dying back') (Tagliaferro and Burke, 2016).”

What the sources say

• ?Not checked — no full text of the sourcecites Andica et al., 2018 source
• Supported

  The cited paper supports the sentence’s interpretation, not the NDI finding, which the sentence attributes to Andica et al. In “Evidence from postmortem and imaging studies in humans” (page unavailable), it reports postmortem evidence of early striatal axon-terminal involvement and describes findings suggesting degeneration begins in distal axons and proceeds retrogradely. The paper presents this as evidence consistent with ‘dying back,’ rather than definitive proof of that pattern in the nigrostriatal tract. (LLM, conf=0.90)

  cites Tagliaferro and Burke, 2016 source

In the paper

“Using NODDI, (Broad et al., 2019) found reduced NDI along the corticospinal tract (CST) and the transcallosal fiber between the primary motor cortices, which is consistent with histological studies reporting axonal degeneration within these regions (Brownell et al., 1970;Swash et al., 2020).”

What the sources say

• Supported

  The Results section (‘Neurite orientation dispersion and density imaging’) reports reduced NDI in the ALS group along a large continuous region of the corticospinal tract and in the transcallosal connection fibres between the primary motor cortices. This directly supports the finding attributed to Broad et al. (LLM, conf=0.95)

  cites Broad et al., 2019 source
• Supported

  Brownell et al. are cited for the histological finding, not the NODDI result. The passage on corticospinal degeneration reports a band of degeneration in the corpus callosum in case 18, presumed to affect fibres connecting the left and right Rolandic areas; it also traces degeneration along the pyramidal tract. The callosal observation is limited to that case. (LLM, conf=0.90)

  cites Brownell et al., 1970 source
• Partly supported

  Swash et al. are cited for the histological consistency of the finding, not for Broad et al.’s NODDI result. The Neuropathology section reports pathological evidence of corticospinal-tract axonal degeneration, while the Imaging section says interhemispheric motor fibres are involved in ALS. Our copy does not clearly establish histological axonal degeneration specifically in those transcallosal fibres, and it does not report reduced NDI. (LLM, conf=0.82)

  cites Swash et al., 2020 sourceExperimental — accuracy not yet measured

In the paper

“Using a model almost identical to NODDI, (Surova et al., 2016) observed only small differences between patients with Parkinson's disease and healthy controls.”

What the sources say

• Supported

  The Methods describe the study’s neurite density imaging (NDI) analysis as a simplification of the NODDI model. The Results report small differences in NDI measures between Parkinson’s disease patients and healthy controls, with no significant age- and gender-adjusted differences in the examined deep grey-matter regions. The claim accurately summarizes those model-based findings. (LLM, conf=0.90)

  cites Surova et al., 2016 source

In the paper

“Using NODDI parameters from tractograms as weights for a brain network in a connectomics study, (Lemkaddem et al., 2014) found different patterns of network alterations between left and right TLE.”

What the sources say

• Supported

  The Introduction says the study averaged the NODDI parameters ICVF and ODI along tracts to construct structural connectivity matrices for graph analysis. The Discussion section “Different structural connectivity alterations in RTLE and LTLE” explicitly reports different patterns of changes in right versus left TLE. Page numbers were not available in our copy. (LLM, conf=0.93)

  cites Lemkaddem et al., 2014 source

In the paper

“Increased NDI and ODI and decreased f fw have been reported in acute infarction lesions (Adluru et al., 2014;Z. Wang et al., 2019b).”

What the sources say

• Partly supported

  The Results report higher neurite density (NDI/ND) and ODI and a lower CSF fraction in stroke lesions than in contralesional regions. Methods §II.B says the two patients were scanned 7 and 9 days after stroke, consistent with an acute setting, but our copy does not identify their lesions specifically as infarctions. (LLM, conf=0.82)

  cites Adluru et al., 2014 sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Z. Wang et al., 2019b

In the paper

“Furthermore, (Broad et al., 2019) found that NDI was reduced to a greater spatial extent in patients with both limb and bulbar involvement compared with those with limb involvement alone.”

What the sources say

• Supported

  The Results (Subgroup analysis using the NODDI parameters) report significantly reduced NDI in the right corona radiata and subcortical white matter in patients with both bulbar and limb involvement compared with those with limb-only involvement. The Discussion describes this as more extensive microstructural damage in the group with more widespread clinical involvement. (LLM, conf=0.88)

  cites Broad et al., 2019 source

In the paper

“Patients with neurocognitive and psychiatric symptoms have a smaller NDI in the cerebral WM than those without neurocognitive and psychiatric symptoms (Andica et al., 2020).”

What the sources say

• Supported

  The Results (TBSS analysis; page unavailable) report significantly lower intracellular volume fraction (ICVF) in cerebral white matter among Parkinson’s patients with neurocognitive and psychiatric symptoms than among those without. The Discussion identifies ICVF as a measure of neurite density, matching the claim’s NDI terminology. (LLM, conf=0.93)

  cites Andica et al., 2020 source

In the paper

“In GM, (Spanò et al., 2018) observed a correlation between clinical disability and NODDI parameters.”

What the sources say

• Supported

  The Results (ODI correlations; page not provided) report significant associations between clinical disability scores and the NODDI measure ODI in several gray-matter regions, including the cingulate gyrus, caudate nucleus, and thalamus. The Discussion also states that gray-matter abnormalities correlate with patients’ clinical disability. (LLM, conf=0.94)

  cites Spanò et al., 2018 source

In the paper

“In children with cerebral palsy caused by perinatal stroke, NDI and ODI in lesioned CST were both decreased compared with in contralateral CST”

What the sources say

• Supported

  The Results (NODDI metrics; page unavailable) report significantly lower intracellular volume fraction (ICVF, the paper’s neurite-density measure) and ODI in the lesioned than the nonlesioned CST. The paper frames these findings in relation to perinatal stroke, although its sample also included one participant with periventricular leukomalacia. (LLM, conf=0.90)

  cites Nemanich et al., 2019 source

In the paper

“Studies in athletes with repetitive head impact found increased NDI, ODI, and f fw in both GM and WM compared with in non-athletes and non-contact athletes (Caron et al., 2020;Mayer et al., 2017).”

What the sources say

• Partly supported

  The paper’s opening summary says it mapped NODDI measures in cortical and subcortical structures and white-matter tracts, and found athletes to have higher microstructural measures than non-athlete controls. The passages do not establish that NDI, ODI, and f_fw were each increased in both gray and white matter specifically in the head-impact group, or that this group had higher values than non-contact athletes. (LLM, conf=0.75)

  cites Caron et al., 2020 sourceExperimental — accuracy not yet measured
• Partly supported

  The Results (dMRI results; page unavailable) report increased ODI and intracellular water fraction (Vic) in some gray- and white-matter regions of mixed-martial artists, and increased free-water fraction (Viso) in some regions. But Viso was reduced in other regions, so the findings do not establish a uniform increase in all three measures across both tissue types. The Methods (Participants; page unavailable) describe one physically active healthy-control group with no regular contact-sport history, not separate non-athlete and non-contact-athlete comparison groups. (LLM, conf=0.86)

  cites Mayer et al., 2017 sourceExperimental — accuracy not yet measured

In the paper

“Using NODDI in combination with multi-exponential T2 relaxometry, (Billiet et al., 2014) showed decreased NDI and prolonged T2 in the cellular water compartment (encompassing both intra-and extra-cellular water) compared with in normal-appearing WM.”

What the sources say

• Supported

  The Discussion reports decreased NDI and increased T2 relaxation of intra- and extracellular water in UBOs compared with contralateral normal-appearing white matter (cNAWM). The Introduction identifies that T2 component as combined intra- and extracellular water. (LLM, conf=0.94)

  cites Billiet et al., 2014 source

In the paper

“Moreover, smaller NDI within the cingulum was associated with greater genetic risk for schizophrenia (Drakesmith et al., 2019).”

What the sources say

• Supported

  The Results (White-matter microstructure; page not provided) report that intracellular volume fraction (ICVF) in the left cingulum decreases as the schizophrenia penetrance score increases. The Methods identify ICVF as a NODDI microstructural measure, and the Discussion interprets its reduction as reflecting lower axon density. The association was specifically observed in the left cingulum of people carrying risk-associated copy number variants. (LLM, conf=0.88)

  cites Drakesmith et al., 2019 source

In the paper

“with greater effects observed among those imaged after a longer period of time since their last concussion (Churchill et al., 2017).”

What the sources say

• Supported

  The Abstract states that NODDI-related effects were greater among athletes imaged longer after their last concussion. The Multivariate Analysis of Clinical History specifies the direction: longer intervals were associated with higher intracellular volume fraction (a neurite-density measure) and lower ODI. (LLM, conf=0.93)

  cites Churchill et al., 2017 source

In the paper

“suggesting that NODDI is sensitive to the damage caused by chronic ischemia (Hara et al., 2019(Hara et al., , 2018) ) (Fig. 6).”

What the sources say

• ?Not checked — no full text of the sourcecites Hara et al., 2019 source
• Supported

  The Conclusions (page not specified) state that NODDI revealed microstructural ischemic damage in normal-appearing brain tissue in adults with moyamoya disease. The Discussion also links the measured microstructural changes to chronic ischemia. (LLM, conf=0.93)

  cites Hara et al., 2018 source

In the paper

“A smaller NDI in WM was also found in patients with first-episode psychosis (Rae et al., 2017).”

What the sources say

• Supported

  The Conclusions state that neurite density is reduced across white matter tracts in first-episode psychosis. The NODDI methods passage identifies the intracellular volume fraction as an index of neurite density, supporting the claim about smaller NDI in white matter. (LLM, conf=0.94)

  cites Rae et al., 2017 source

In the paper

“and decreased NDI and f fw over time from 2 weeks to 6 months (Palacios et al., 2018).”

What the sources say

• Partly supported

  The ‘Longitudinal analysis of mTBI patients at 2 weeks vs 6 months’ section reports decreases in NDI and FISO over that interval, but those results are for patients with mild traumatic brain injury. The Participants section identifies orthopedic trauma patients as controls; the paper does not report the claimed longitudinal decreases for them. Page numbers are unavailable in our copy. (LLM, conf=0.88)

  cites Palacios et al., 2018 sourceExperimental — accuracy not yet measured

In the paper

“Decreased NDI and ODI and increased f fw were associated with more severe ischemic burden and cognitive impairments (Hara et al., 2019(Hara et al., , 2018)).”

What the sources say

• ?Not checked — no full text of the sourcecites Hara et al., 2019 source
• Partly supported

  The Conclusions and figure captions (page not given) report lower intracellular volume fraction (Vic, corresponding to NDI) and orientation dispersion (OD, corresponding to ODI) in adults with moyamoya disease, and correlations of these measures with neuropsychological performance. The Discussion links those changes to chronic ischemia, but our copy does not report increased f_fw or show that all three measures track greater ischemic burden. It also notes that some cognitive correlations weakened when patients and controls were analyzed separately. (LLM, conf=0.86)

  cites Hara et al., 2018 sourceExperimental — accuracy not yet measured

In the paper

“and greater NDI was associated with greater grip strength (Nemanich et al., 2019).”

What the sources say

• Partly supported

  The Results section (Hand function and relationship to diffusion metrics; page unavailable) reports that greater grip strength correlated with asymmetry indices for ICVF, a NODDI density metric. It does not establish that greater NDI itself was associated with greater grip strength. The Participants section (page unavailable) also includes children with periventricular leukomalacia, so the finding is not specific to cerebral palsy caused by perinatal stroke. (LLM, conf=0.86)

  cites Nemanich et al., 2019 sourceExperimental — accuracy not yet measured

In the paper

“indicating the effect of orientation prevails and hides the putative effect of axonal degeneration resulting in greater FA (Kamiya et al., 2017).”

What the sources say

• Partly supported

  The Introduction hypothesizes that increased FA in the corticospinal tract reflects an increase from axon stretching mixed with a decrease from neurodegeneration. The Results (Human data) find increased orientational coherence and lower axon density in patients, but FA was only nonsignificantly higher. The claim overstates the evidence by saying the orientation effect definitively prevails and hides degeneration. (LLM, conf=0.86)

  cites Kamiya et al., 2017 sourceExperimental — accuracy not yet measured

In the paper

“Although there is no established imaging tool capable of detecting the neuronal damage in TBI (Eierud et al., 2014)”

What the sources say

• Partly supported

  The Discussion says neuroimaging lacks the patient-level sensitivity and specificity to diagnose mild TBI, and the Introduction describes microscopic injury as difficult to detect in an individual. That supports the absence of an established diagnostic imaging tool for mild TBI, but not the broader claim that no imaging tool can detect neuronal damage in TBI generally; the Results describe CT detection of some trauma-related abnormalities. (LLM, conf=0.85)

  cites Eierud et al., 2014 sourceExperimental — accuracy not yet measured

In the paper

“The work of Nemanich et al. (2019) also showed that individuals with greater asymmetry of CST dMRI metrics experienced greater improvements following neuromodulatory/motor training intervention.”

What the sources say

• Supported

  The Results section (‘Hand function and relationship to diffusion metrics’) reports that greater improvement in AHA after the intervention was strongly correlated with asymmetry indices for several CST diffusion metrics. The Discussion (‘Relationship to hand function and response to intervention’) explicitly says participants with greater CST asymmetry showed greater AHA improvement. The Methods (‘Intervention’) identifies the treatment as motor training paired with real or sham tDCS. (LLM, conf=0.94)

  cites Nemanich et al., 2019 source

In the paper

“In GM, decreased ODI in the neocortex with increasing age has been reported (Nazeri et al., 2015)”

What the sources say

• Supported

  The ‘Aging pattern of GM microstructure’ section reports a widespread decrease in neocortical ODI with advancing age in 45 healthy adults aged 21–84. Its cortical ROI analysis also found significant declines in 27 of 48 regions. (LLM, conf=0.95)

  cites Nazeri et al., 2015 source

In the paper

“which is in line with histology showing age-related decreases of dendritic complexity and density (Dickstein et al., 2007).”

What the sources say

• Supported

  The Introduction describes dendritic and spine loss or regression during normal aging. The section “Dendrite and dendritic spine changes during aging” reports regression of cortical dendritic arbors and reduced spine density in aged animals, supporting the histological comparison. The citation does not attribute the cortical ODI measurement itself to this paper. (LLM, conf=0.91)

  cites Dickstein et al., 2007 source

In the paper

“In contrast, ODI in WM remains almost stable during the first two decades of life (Genc et al., 2017;Jelescu et al., 2015;Lynch et al., 2020;Mah et al., 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Genc et al., 2017 source
• Partly supported

  The Results (§4.1) state that NODDI showed no trend in orientation dispersion with age across the three white-matter regions studied. However, the subjects were aged only 1 day to 2 years and 9 months (§3.1.1), so this paper does not establish stability throughout the first two decades of life. (LLM, conf=0.88)

  cites Jelescu et al., 2015 sourceExperimental — accuracy not yet measured
• Supported

  The Discussion reports that ODI was not significantly associated with age in the majority of white matter tracts studied from infancy through adolescence. The Results (‘Mean ODI changes with age’) note weak age-related correlations in three tracts, consistent with the claim’s ‘almost stable’ qualification. (LLM, conf=0.88)

  cites Lynch et al., 2020 source

In the paper

“In an unusually large data set, (Cox et al., 2016) confirmed NDI decrease from middle to old age.”

What the sources say

• Supported

  The Methods identify ICVF as a measure of neurite density, and the Discussion reports decreasing ICVF from middle to older age. The study’s 3,513 UK Biobank participants support the description of an unusually large data set. The finding is a cross-sectional age association, not a measured decline within individuals. (LLM, conf=0.92)

  cites Cox et al., 2016 source

In the paper

“In subjects with harmful alcohol use, ODI in the ventral striatum was positively correlated with binge score.”

What the sources say

• Partly supported

  The Results (Neurite orientation dispersion and density; page not available) report a positive correlation between ventral striatal ODI and binge score in binge drinkers. The Participants section identifies the studied group specifically as young adult binge drinkers, not subjects with harmful alcohol use generally; the claim broadens the population. (LLM, conf=0.84)

  cites Morris et al., 2018 sourceExperimental — accuracy not yet measured

In the paper

“Discrepancy between clinical severity and degree of spinal cord compression is often encountered (Baron and Young, 2007;Nouri et al., 2016).”

What the sources say

• ?Not checked — no full text of the sourcecites Baron and Young, 2007 source
• Partly supported

  The review’s discussion of spinal cord compression says it can occur in approximately 5% of asymptomatic patients, showing that compression and clinical symptoms do not always align. The Perspectives section also notes controversy about the association between cervical myelopathy and MRI findings. Neither passage establishes that discrepancies between clinical severity and the degree of compression are often encountered in patients with myelopathy. (LLM, conf=0.79)

  cites Nouri et al., 2016 sourceExperimental — accuracy not yet measured

In the paper

“(Cox et al., 2016) also found that dMRI parameters, including those of NODDI, become increasingly correlated across WM tracts in older age”

What the sources say

• Partly supported

  The Results section (‘Age de-differentiation of white matter microstructure’; page not provided) reports stronger covariation across tracts at older ages for several dMRI measures, including the NODDI measures ICVF and ISOVF. It explicitly excludes the NODDI measure OD, for which there was no appreciable age-related increase. The claim is therefore too broad if read to include NODDI parameters generally. (LLM, conf=0.88)

  cites Cox et al., 2016 sourceExperimental — accuracy not yet measured

In the paper

“ODI generally showed a nonlinear increase until around 60 years, followed by a decrease.”

What the sources say

• Supported

  The Discussion states that OD generally increased nonlinearly until around age 60, then decreased, with variation across tracts. This directly supports the attributed trajectory; the paper calls the measure OD rather than ODI. (LLM, conf=0.95)

  cites Cox et al., 2016 source

In the paper

“The performance of NODDI for tumor grading is comparable with that of mean kurtosis (Figini et al., 2018;Maximov et al., 2017)”

What the sources say

• Partly supported

  The section “Correlation of Diffusion MRI Metrics with Glioma Grade, Histotype, and Cell Proliferation Index” (p. 5) reports that both NODDI and diffusion-kurtosis metrics distinguished grade IV from grade II and III gliomas, while neither distinguished grade II from grade III. This supports a broad similarity, but the paper does not directly compare NODDI’s tumor-grading performance with that of mean kurtosis specifically. (LLM, conf=0.82)

  cites Figini et al., 2018 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Maximov et al., 2017 source

In the paper

“Greater NDI than controls was observed in subcortical WM adjacent to regions of reduced ODI.”

What the sources say

• Supported

  The Results (Neurite orientation dispersion and density) report higher white-matter neurite density adjacent to lower grey-matter ODI in binge drinkers, including in the right dorsolateral prefrontal cortex. The paper calls this adjacent tissue “cortical white matter”; the claim’s “subcortical WM” describes its location beneath the cortex. (LLM, conf=0.88)

  cites Morris et al., 2018 source

In the paper

“earlier studies were partly inconsistent regarding the changes of NDI and ODI (Billiet et al., 2015;Chang et al., 2015;Kodiweera et al., 2016;Merluzzi et al., 2016), possibly reflecting heterogeneity in the age ranges investigated in these studies.”

What the sources say

• ?Not checked — no full text of the sourcecites Billiet et al., 2015 source
• Partly supported

  The Results (section 3.2; page unavailable) report age-related NDI and ODI trajectories, so Chang et al. is an earlier study relevant to the comparison. The Discussion (section 4.4; page unavailable) says its smaller older group biases those trajectories toward development. The paper does not itself establish that the cited studies had inconsistent findings or that differences in their age ranges explain the inconsistency. (LLM, conf=0.78)

  cites Chang et al., 2015 sourceExperimental — accuracy not yet measured
• Supported

  In Discussion > Aging effects (page unavailable), the paper describes mixed findings for age-related ICVF changes in earlier studies, reports no significant ICVF change in its young-to-middle-aged cohort, and contrasts its ODI finding with Billiet et al. It suggests that population differences may help explain the ODI discrepancy, consistent with the citing sentence’s hedged explanation. (LLM, conf=0.86)

  cites Kodiweera et al., 2016 source

In the paper

“although neither NODDI nor DKI have shown a particular benefit over DTI in predicting isocitrate dehydrogenase-1 gene mutation status (Figini et al., 2018;Zhao et al., 2018).”

What the sources say

• Supported

  The Discussion (p. 5) says the benefit of advanced diffusion models was small and that DTI identified IDH status as well as multishell methods. The Summary (p. 2) likewise says advanced models did not add significant diagnostic accuracy. The Neuropathologic Examination (p. 3) specifies that IDH-1 mutation status was assessed. (LLM, conf=0.90)

  cites Figini et al., 2018 source
• Partly supported

  The Results section reports no significant overall difference in NODDI or DTI metrics between patients with and without IDH-1 mutations, supporting the limited claim about NODDI. But it also reports a significant NODDI finding in grade IV gliomas. The paper does not test whether DKI offers a benefit over DTI for predicting mutation status, so that part of the claim is unsupported by this source. (LLM, conf=0.88)

  cites Zhao et al., 2018 sourceExperimental — accuracy not yet measured

In the paper

“With NODDI applied postoperatively, NDI showed a positive correlation with neurological score at the time of MRI (Jiang et al., 2018;Ma et al., 2018).”

What the sources say

• Supported

  The Introduction identifies Vic (intracellular volume fraction) as the NODDI measure of neurite density. The Results report a positive correlation between postoperative Vic and the follow-up mJOA neurological score (r = 0.420, p = 0.001). The paper calls the score a follow-up measure rather than explicitly saying it was obtained at the time of MRI. (LLM, conf=0.90)

  cites Jiang et al., 2018 source
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Ma et al., 2018

In the paper

“Although an increase of f fw with age has been consistently observed”

What the sources say

• Partly supported

  The Results report higher ISOVF with older age, and the Discussion says this agrees with prior estimates from middle to older age. The paper describes ISOVF as a measure of extracellular water diffusion, but does not identify it as the specific f_fw measure or establish a consistent increase across all ages. No page numbers are available in our copy. (LLM, conf=0.82)

  cites Cox et al., 2016 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Guerreri et al., 2019 source
• Supported

  The Introduction defines Viso as the fraction of a voxel occupied by isotropically diffusing, CSF-like water. The Results report widespread age-related increases in Viso, and the Discussion says a previous study observed similar increases. The finding is regional rather than universal, but it supports the cited statement that an increase has been observed consistently. (LLM, conf=0.88)

  cites Merluzzi et al., 2016 source

In the paper

“With NODDI, the T2-weighted hyperintense lesion of gliomas exhibit a smaller NDI and greater f fw compared with normal-appearing WM (Lampinen et al., 2017;Maximov et al., 2017;Wen et al., 2015).”

What the sources say

• Partly supported

  The Fig. 5 caption reports generally higher free-water fractions and mostly lower anisotropic-water fractions in gliomas than in normal tissue. It also notes that NODDI’s f_IC parameter was elevated in parts of the tumors. The paper does not establish the claim specifically for T2-hyperintense lesions compared with normal-appearing white matter, and the unqualified lower-NDI statement omits those exceptions. (LLM, conf=0.85)

  cites Lampinen et al., 2017 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Maximov et al., 2017 source
• Supported

  The Results (Evaluation of NODDI parameters; page not supplied) report significantly decreased intra-neurite volume fraction (vic) and increased isotropic volume fraction (viso) in T2-weighted lesions compared with normal-appearing white matter. The Methods identify these as the restricted and free-water-related NODDI compartments, respectively. (LLM, conf=0.91)

  cites Wen et al., 2015 source

In the paper

“(Cox et al., 2016) and (Slater et al., 2019) have consistently found that among the dMRI parameters (FA, MD, NDI, ODI, and f fw ) MD is the most sensitive to the effect of aging.”

What the sources say

• Partly supported

  The Discussion reports that MD was the most sensitive conventional dMRI or NODDI parameter to age among the thalamic radiations and association fasciculi studied. The claim omits that tract-specific scope and the study’s middle-to-older-age population, making it broader than the finding in our copy. (LLM, conf=0.84)

  cites Cox et al., 2016 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Slater et al., 2019 source

In the paper

“In patients undergoing interferon alpha therapy, (Dowell et al., 2019) found that increased NDI in the left striatum compared with baseline was associated with the occurrence of fatigue.”

What the sources say

• Supported

  The Results section (‘Relationship with change in fatigue’) reports a significant positive correlation between acute changes in NDI and fatigue in the left striatum. The paper measured NDI at baseline and again four hours after the first IFN-α dose, matching the claim’s comparison. (LLM, conf=0.94)

  cites Dowell et al., 2019 source

In the paper

“Besides, accelerated computation via convex optimization (Daducci et al., 2015) is available for NODDI.”

What the sources say

• Supported

  The NODDI section states that the authors’ convex formulation provides estimates for the NODDI model. It reports that fitting the synthetic data took about 40 hours with the original algorithm versus 6 minutes with the convex NODDI amico approach, directly supporting accelerated computation via convex optimization. (LLM, conf=0.95)

  cites Daducci et al., 2015 source

In the paper

“In a rat model co-expressing TAR DNA-binding protein 43 and toxic variants of tau, none of the NODDI parameters showed significant differences from controls, despite pathological evidence of microglial activation (Moszczynski et al., 2019).”

What the sources say

• Supported

  The Results > Neuroimaging section reports no differences between groups in the corpus callosum or hippocampus for the NODDI measures ODI, NDI, and IsoVF. The Results > Tau pathology in rats section reports significantly increased IBA1 staining, a marker of microglial activation, in rats co-expressing TDP-43M337V and tauT175D relative to controls. The claim is supported for the brain regions and measures examined. (LLM, conf=0.94)

  cites Moszczynski et al., 2019 source

In the paper

“Several studies (Billiet et al., 2015(Billiet et al., , 2014;;Fenchel et al., 2020;Geeraert et al., 2019;Hara et al., 2019;Slater et al., 2019) have demonstrated the benefits of combining NODDI with other complementary imaging methods to allow for more specific inferences about the underlying microstructure.”

What the sources say

• ?Not checked — no full text of the sourcecites Billiet et al., 2015 source
• Partly supported

  The Image Processing and MSN Construction methods describe combining NODDI-derived measures with other diffusion and structural MRI measures. The Discussion says the combination captures information no single measure captures, but the paper demonstrates richer characterization of neonatal cortical patterns, not specifically more precise inferences about the underlying microstructure. Page numbers are not available in our copy. (LLM, conf=0.83)

  cites Fenchel et al., 2020 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Geeraert et al., 2019 source

In the paper

“Children born very preterm exhibit greater ODI throughout the WM at the age of 6-7 years compared with full-term children (Kelly et al., 2016;Young et al., 2019).”

What the sources say

• Partly supported

  The Methods (MRI acquisition; page unavailable) place the scans at age 7, and the Discussion (VPT children compared with controls; page unavailable) reports increased axon dispersion in many white-matter tracts in very preterm children. The paper does not establish greater dispersion throughout all white matter; that wording is broader than its reported finding. (LLM, conf=0.87)

  cites Kelly et al., 2016 sourceExperimental — accuracy not yet measured
• Supported

  The Discussion reports widespread increases in ODI in children born very preterm compared with term-born children at six years of age. In the citing sentence, Young et al. supports the six-year-old portion of the stated 6–7-year age range. (LLM, conf=0.90)

  cites Young et al., 2019 source

In the paper

“Recently, in a large cohort of term-born infants, both NDI and ODI in the cortex were found to be positively correlated with gestational age at 37-44 weeks (Fenchel et al., 2020).”

What the sources say

• Partly supported

  The Results (Age at Scan and Sex Effects) report positive associations of cortical NDI and ODI with age in a cohort of term-born infants. But the Subjects section defines the 37–44-week range as postmenstrual age at scanning, not gestational age at birth; infants were born at 37–42 weeks. (LLM, conf=0.89)

  cites Fenchel et al., 2020 sourceExperimental — accuracy not yet measured

In the paper

“Applications of NODDI in the presence of neuroinflammation have reported mixed results so care should be taken in interpreting the relationship between NODDI and neuroinflammation.”

What the sources say

• Partly supported

  The Results and Discussion (page not available in our copy) report mixed findings within this IFN-α study: no significant group-level change in NODDI metrics, but a positive correlation between striatal NDI changes and fatigue. The Discussion also cautions that factors other than inflammation can affect NDI. The paper does not establish that NODDI applications across neuroinflammatory settings have generally reported mixed results. (LLM, conf=0.83)

  cites Dowell et al., 2019 sourceExperimental — accuracy not yet measured
• Partly supported

  The Results (Tau pathology in rats; page unavailable) report increased hippocampal microglial activation in one rat group, while the Results (Neuroimaging; page unavailable) report no group differences in NODDI measures. This supports caution about interpreting NODDI alongside neuroinflammation, but the paper does not report mixed results across NODDI applications. (LLM, conf=0.78)

  cites Moszczynski et al., 2019 sourceExperimental — accuracy not yet measured

In the paper

“NODDI was also shown to be sensitive to individual variations of WM microstructure at 1 month of age that are associated with prenatal maternal depression and anxiety symptoms (Dean et al., 2018).”

What the sources say

• Supported

  The paper says it evaluated white matter microstructure in 1-month-old infants using NODDI. Its Results report that prenatal maternal depression and anxiety symptoms were associated with decreased neurite-density measures, particularly in frontal white matter. No page number is available in our copy. (LLM, conf=0.92)

  cites Dean et al., 2018 source

In the paper

“Also, NDI in the posterior callosal connections showed a negative correlation with reading skill (Huber et al., 2019).”

What the sources say

• Supported

  In Results (‘Biological underpinnings of reading-diffusion correlations’; page unavailable), NODDI ICVF significantly correlates with reading skill, and struggling readers tend to have higher ICVF throughout the posterior callosal tract. The paper calls this measure ICVF rather than NDI; its reported direction supports the claimed negative correlation. (LLM, conf=0.90)

  cites Huber et al., 2019 source

In the paper

“In children with developmental dyslexia, ODI and NDI in the language-related cortical regions were correlated with a measure of gyrification in opposite directions from typically developing controls”

What the sources say

• Supported

  The Results section (‘Relationship between gyrification, neurite density and fiber dispersion’; page not provided) reports opposite slopes for children with developmental dyslexia and typically developing controls: ODI versus local gyrification index (lGI) in the left rostral middle frontal gyrus, and NDI versus lGI in the left middle temporal gyrus. These are the language-related frontal and temporal regions described in the claim. (LLM, conf=0.94)

  cites Caverzasi et al., 2018 source

In the paper

“Widespread reduction of NDI in WM was also present in young adults born with congenital heart disease (Easson et al., 2020).”

What the sources say

• Supported

  The Conclusion (section 4.5) reports widespread NDI reductions in many white matter tracts in youth born with congenital heart disease compared with healthy controls. The study population was aged 16–24 years (Study design), consistent with the citing sentence’s description of young adults. (LLM, conf=0.93)

  cites Easson et al., 2020 source

In the paper

“Pathologies like axonal beading/swelling (Budde and Frank, 2010;Palombo et al., 2018) and demyelination (Chuhutin et al., 2020;Guglielmetti et al., 2016;Jelescu et al., 2016) also affect compartmental diffusivities.”

What the sources say

• ?Not checked — no full text of the sourcecites Budde and Frank, 2010 source
• ?Not checked — no full text of the sourcecites Palombo et al., 2018 source
• Partly supported

  The Discussion (page unavailable) reports that extra-axonal parallel diffusivity increased with EAE grade and proposes myelin loss as one possible explanation. It does not establish that demyelination itself caused the change; axonal damage and glial changes are also proposed. The axonal beading/swelling portion is attached to other citations, not this one. (LLM, conf=0.83)

  cites Chuhutin et al., 2020 sourceExperimental — accuracy not yet measured

In the paper

“Recently proposed extensions of NODDI to measurements with b-tensor encoding (Guerreri et al., 2020) and with multiple TE (Gong et al., 2020) showed capability of estimating compartmental diffusivities and T2s using clinical scanners, and we may see some confirmations and/or re-interpretations of the previously-reported NODDI findings in near future.”

What the sources say

• ?Not checked — no full text of the sourcecites Guerreri et al., 2020
• Supported

  Gong et al. is cited for the multiple-TE extension. The Introduction describes estimating compartment-specific T2 values from multiple-TE diffusion data, and Methods §3.1.1 reports an in vivo demonstration on a Siemens 3T scanner. The separate b-tensor citation, rather than Gong et al., is attached to the other extension in the sentence. (LLM, conf=0.88)

  cites Gong et al., 2020 source

In the paper

“An important limitation of MRI g-ratio is that any bias introduced by the individual participating models or by the procedure to compute the g-ratio is propagated into the final output in an unpredictable way (Campbell et al., 2018).”

What the sources say

• Supported

  Section 3.3.3 (pp. 11–12) says that inaccurate calibration of the myelin estimate makes the computed g-ratio incorrect and can introduce a misleading dependence on fiber density. Section 3.1 (p. 5) also describes preprocessing errors that produce artifactually high or otherwise incorrect g-ratios. These passages support the claim that biases in the component estimates or computation carry through to the final metric, with effects that depend on the source of error. (LLM, conf=0.87)

  cites Campbell et al., 2018 source

In the paper

“Disentangling these factors beyond NODDI is expected to further improve our understanding of the brain and diseases, just as NODDI revealed the putative neuronal damage beyond limitations of DTI in diseases like Alzheimer's disease (Slattery et al., 2017) and iNPH (Kamiya et al., 2017).”

What the sources say

• Supported

  The Introduction explains that DTI gives a composite view of tissue microstructure, whereas NODDI can distinguish neurite-density loss from changes in axonal organization. The Discussion reports that, in young-onset Alzheimer’s disease, NODDI enabled more specific inferences about damage and could reveal effects not observable as a DTI fractional-anisotropy change. The separate iNPH example is attributed to Kamiya et al., not to this source. (LLM, conf=0.92)

  cites Slattery et al., 2017 source
• Supported

  The Introduction says conventional DTI measures are not highly specific to individual microstructural properties. In the iNPH study, the Abstract and Conclusion report lower estimated axon density that persisted after surgery, suggesting a marker of irreversible neuronal damage. The paper attributes this finding to both NODDI and WMTI, consistent with the citing sentence’s claim about NODDI in iNPH. (LLM, conf=0.90)

  cites Kamiya et al., 2017 source

In the paper

“At present, consensus has not been reached even on the very basic assumptions such as the number of compartments.”

In the paper

“In contrast, biophysical models such as NODDI align with the second reason-to provide better explanations for observed abnormalities-by increasing specificity for certain clinically meaningful tissue properties.”

In the paper

“The choice of fixed parallel diffusivity value (1.7 µm /ms 2 ) was based on minimization of the fitting residuals for voxels in the corpus callosum (Alexander et al., 2010).”

What the sources say

• ?Not checked — no full text of the sourcecites Alexander et al., 2010 source

In the paper

“As shown in the original work by (Zhang et al., 2012), NODDI is more specific than fractional anisotropy (FA) in DTI, in that voxels with different sets of NODDI parameters can yield exactly the same FA value and therefore be indistinguishable by FA.”

What the sources say

• ?Not checked — no full text of the sourcecites Zhang et al., 2012 source

In the paper

“Although there is no easy answer (Novikov et al., 2018a), a simple reply is that it depends on purpose and that the specificity of NODDI is only relative.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Novikov et al., 2018a

In the paper

“Lower FA and NDI, and higher mean diffusivity (MD) and ODI, were associated with worse neuropsychological scores (Q.Wen et al., 2019b).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Q.Wen et al., 2019b

In the paper

“ODI in GM generally exhibits a greater CoV than it does in WM, which is expected because estimation of higher ODI values are less precise (Zhang et al., 2012).”

What the sources say

• ?Not checked — no full text of the sourcecites Zhang et al., 2012 source

In the paper

“suggests the presence of different microstructural mechanisms at the different disease stages (e.g., neuroinflammation occurs early, followed by neurodegeneration)”

In the paper

“This nonmonotonic course, which is characterized by a stronger diffusion restriction at an intermediate amyloid burden and a weaker diffusion restriction at a higher burden, suggests the presence of different microstructural mechanisms at the different disease stages (e.g., neuroinflammation occurs early, followed by neurodegeneration), and so future longitudinal studies with methods that allow”

In the paper

“and interscanner reproducibility has been shown to be lower than intra-scanner reproducibility, even at the same field strength (3 T) (Andica et al., 2019b).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Andica et al., 2019b

In the paper

“Also, assuming multiple Gaussian compartments means we neglect several potentially important factors, including inter-compartmental exchange and non-Gaussian effects within the compartments.”

In the paper

“indicating that NODDI has the ability, at least partly, to disentangle the effect of orientation dispersion.”

In the paper

“Despite that, NODDI can describe multi-shell dMRI data better than DTI, illustrating the benefit of well-crafted model suitable for acquisition.”

In the paper

“Reduced NDI in WM has also been reported in pre-symptomatic carriers of c9orf72 mutation, a major genetic cause of ALS (J.Wen et al., 2019a).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites J.Wen et al., 2019a

In the paper

“In addition, NDI and ODI in the putamen was negatively correlated with motor symptom severity and disease duration, which is in agreement with the clinico-pathological hypothesis that striatal dendrite degeneration contributes to late-stage motor symptoms in Parkinson's disease (Zaja-Milatovic et al., 2005).”

What the sources say

• ?Not checked — no full text of the sourcecites Kamagata et al., 2016 source
• ?Not checked — no full text of the sourcecites Zaja-Milatovic et al., 2005 source

In the paper

“In GM, decreased NDI and increased f fw within the striatum and the frontal, temporal, limbic, and paralimbic cortices have been identified before atrophy is evident (Kamagata et al., 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Kamagata et al., 2017 source

In the paper

“In contrast, changes in ODI have been reported in all directions-as increases, decreases, or as no significant changes.”

In the paper

“Later, a larger case series (Rostampour et al., 2018) also reported that NODDI was useful for the visual detection of FCDs.”

What the sources say

• ?Not checked — no full text of the sourcecites Rostampour et al., 2018 source

In the paper

“Animal studies have shown a progressive decrease of NDI in the brain (Gatto et al., 2019) and spinal cord (Gatto et al., 2018) of ALS mice, and these findings were in good agreement with histologically measured decreases of the intra-axonal space.”

What the sources say

• ?Not checked — no full text of the sourcecites Gatto et al., 2019 source
• ?Not checked — no full text of the sourcecites Gatto et al., 2018

In the paper

“Increases of ODI and f fw were also observed in these mice.”

What the sources say

• ?Not checked — no full text of the sourcecites Gatto et al., 2019 source
• ?Not checked — no full text of the sourcecites Gatto et al., 2018

In the paper

“Also, (Yasuno et al., 2019) found that ODI in the left posterior cingulate cortex was associated with the severity and recovery of post-stroke depression”

What the sources say

• ?Not checked — no full text of the sourcecites Yasuno et al., 2019 source

In the paper

“In DTI, patients with iNPH exhibit greater FA within the CST compared with controls (Hattingen et al., 2010)”

What the sources say

• ?Not checked — no full text of the sourcecites Hattingen et al., 2010 source

In the paper

“a higher ODI in the corpus callosum (Spray et al., 2018a) and lower ODI in the left superior temporal gyrus (Spray et al., 2018b) were reported to be associated with proneness to auditory hallucination.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Spray et al., 2018b

In the paper

“a higher ODI in the corpus callosum (Spray et al., 2018a) and lower ODI in the left superior temporal gyrus (Spray et al., 2018b) were reported to be associated with proneness to auditory hallucination.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Spray et al., 2018a

In the paper

“(Espay et al., 2017) pointed out that the initial diagnoses of iNPH were revised later in more than 25 % of the patients (revised diagnosis: Alzheimer's disease, dementia with Lewy bodies, or progressive supranuclear palsy).”

What the sources say

• ?Not checked — no full text of the sourcecites Espay et al., 2017 source

In the paper

“and a few studies have reported a trend of partial normalization after surgery (Jurcoane et al., 2014;Scheel et al., 2012).”

What the sources say

• ?Not checked — no full text of the sourcecites Jurcoane et al., 2014 source
• ?Not checked — no full text of the sourcecites Scheel et al., 2012 source

In the paper

“In auto-pedestrian accidents, a widespread reduction of NDI in WM shortly after trauma has been reported (Wu et al., 2018).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Wu et al., 2018

In the paper

“A smaller NDI in the frontotemporal cortices was linked with lower neurocognitive performance (Nazeri et al., 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Nazeri et al., 2017 source

In the paper

“During these processes, myelin plays important roles related to axon vulnerability (Armstrong et al., 2016).”

What the sources say

• ?Not checked — no full text of the sourcecites Armstrong et al., 2016 source

In the paper

“WM damage in TBI is histopathologically characterized by axonal swelling at the initial damage, followed by axonal degeneration, demyelination, and neuroinflammation with microglial activation (Armstrong et al., 2016).”

What the sources say

• ?Not checked — no full text of the sourcecites Armstrong et al., 2016 source

In the paper

“With NODDI, a smaller NDI was found in GM regions such as the temporal pole, anterior parahippocampal gyrus, and hippocampus in patients with schizophrenia compared with healthy controls (Nazeri et al., 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Nazeri et al., 2017 source

In the paper

“Although all imaging techniques are inevitably dependent on simplistic models and are limited in their specificity, combining complementary techniques allows us to deduce the biological underpinnings of diseases beyond the limitation of a single model.”

In the paper

“Recently, another large-sample life span study including participants aged 7-84 years (Slater et al., 2019) identified 'U-shaped' or 'inverted U-shaped' life span trajectories in NODDI parameters”

What the sources say

• ?Not checked — no full text of the sourcecites Slater et al., 2019 source

In the paper

“suggesting that the relationship between cortical ODI and neurocognitive decline with age is likely not straightforward.”

In the paper

“The trends observed by (Cox et al., 2016) and (Slater et al., 2019) agree with the 'last in, first out' hypothesis (Bartzokis, 2004)”

What the sources say

• ?Not checked — no full text of the sourcecites Bartzokis, 2004 source

In the paper

“Survivors of childhood bone and soft tissue sarcoma, on average at 10 years after chemotherapy, exhibited widespread areas with greater f fw compared with controls in central WM, presumably representing interstitial edema (Sleurs et al., 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Sleurs et al., 2018 source

In the paper

“DKI's mean kurtosis is known to correlate well with tumor grade (Raab et al., 2010;Van Cauter et al., 2012)”

What the sources say

• ?Not checked — no full text of the sourcecites Raab et al., 2010 source
• ?Not checked — no full text of the sourcecites Van Cauter et al., 2012 source

In the paper

“In preoperative evaluation, greater NDI at the level of strongest compression was associated with greater neurological recovery after surgery (Iwama et al., 2020;Okita et al., 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Iwama et al., 2020 source
• ?Not checked — no full text of the sourcecites Okita et al., 2018 source

In the paper

“Greater NDI in the frontal cortex was observed in patients undergoing lithium therapy compared with patients treated with other mood stabilizers (Sarrazin et al., 2019)”

What the sources say

• ?Not checked — no full text of the sourcecites Sarrazin et al., 2019 source

In the paper

“does not necessarily mean recovered axon density, as shown in a post-mortem case report where the pathological change of spinal cord persisted after surgery and did not coincide with the relief of symptoms (Someya et al., 2011).”

What the sources say

• ?Not checked — no full text of the sourcecites Someya et al., 2011 source

In the paper

“In contrast, in breast cancer survivors, no significant difference from healthy controls was observed at 3-4 years after the end of chemotherapy (Billiet et al., 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Billiet et al., 2018 source

In the paper

“It is unlikely that computational cost is the main reason, because current medical practice spends a long time on image processing, for example, during surgical planning.”

In the paper

“There are also many other factors that are not mathematically parameterized in NODDI but could be biologically meaningful.”

In the paper

“One of the major concerns about dMRI microstructure models is that they have not yet been adopted for clinical use.”

In the paper

“Interpretations of NODDI depend on the clinical condition under examination and our associated biological hypotheses.”

In the paper

“Compared with the case of apparent diffusion coefficient and dMRI tractography, the pace of dissemination has been relatively slow.”

In the paper

“In the presence of intercompartmental differences in the relaxation times, compartmental fractions estimated via NODDI can be influenced by alterations of both actual volumes and relaxation times.”

In the paper

“Although each study is meaningful as a proof-of-concept, at present it is difficult to draw general conclusions about the practical benefit of NODDI in individual patient care.”