CoChat
Sign Up
Cited by 64Advanced Neuroimaging Techniques and ApplicationsDementia and Cognitive Impairment ResearchFunctional Brain Connectivity Studies

Mean diffusivity in cortical gray matter in Alzheimer's disease: The importance of partial volume correction

Open access
Henf, Judith, Grothe, Michel J., Brueggen, Katharina, Teipel, Stefan, Dyrba, Martin·2018·NeuroImage: Clinical
DOI 10.1016/j.nicl.2017.10.005PMC PMC5702878
Open this paper in CoChat — free accountOpen PDF

Abstract

Mean diffusivity (MD) measured by diffusion tensor imaging can reflect microstructural alterations of the brain's gray matter (GM). Therefore, GM MD may be a sensitive marker of neurodegeneration related to Alzheimer's Disease (AD). However, due to partial volume effects (PVE), differences in MD may be overestimated because of a higher degree of brain atrophy in AD patients and in cases with mild cognitive impairment (MCI). Here, we evaluated GM MD changes in AD and MCI compared with healthy controls, and the effect of partial volume correction (PVC) on diagnostic utility of MD. We determined region of interest (ROI) and voxel-wise group differences and diagnostic accuracy of MD and volume measures between matched samples of 39 AD, 39 MCI and 39 healthy subjects before and after PVC. Additionally, we assessed whether effects of GM MD values on diagnosis were mediated by volume. ROI and voxel-wise group differences were reduced after PVC. When using these ROIs for predicting group separation in logistic models, both PVE corrected and uncorrected GM MD values yielded a poorer diagnostic accuracy in single predictor models than regional volume. For the discrimination of AD patients and healthy controls, the effect of GM MD on diagnosis was significantly mediated by volume of hippocampus and posterior cingulate ROIs. Our results suggest that GM MD measurements are strongly confounded by PVE in the presence of brain atrophy, underlining the necessity of PVC when using these measurements as specific metrics of microstructural tissue degeneration. Independently of PVC, regional MD was not superior to regional volume in separating prodromal and clinical stages of AD from healthy controls.

AI snapshot

Written from the paper’s full text.

TL;DR

In matched samples of 39 AD, 39 MCI, and 39 healthy controls, cortical gray matter mean diffusivity (MD) differences were reduced after partial volume correction (PVC), and uncorrected MD was strongly confounded by atrophy. Regional MD was not superior to regional volume for separating prodromal or clinical AD from healthy controls.

Key findings

  • Voxel-wise analyses showed widespread cortical MD elevation in AD vs. healthy controls without PVC; MCI vs. controls showed increased MD in both hippocampi. After PVC, MCI vs. controls no longer differed significantly in GM MD, while AD vs. controls still showed elevated MD in both hippocampi and middle/posterior cingulate cortex.
  • ROI ANCOVA found diagnosis effects on MD in all three ROIs regardless of PVC, but effect sizes were larger for uncorrected MD (e.g., left hippocampus partial eta² = 0.21 uncorrected vs. 0.09 corrected; PCC = 0.26 vs. 0.22). Post hoc tests showed AD > HC and AD > MCI; MCI MD values were numerically higher than HC but not statistically significant.
  • Logistic regression AUCs were generally numerically greater for volume than MD. For AD vs. HC left hippocampus, AUC was 0.82 for uncorrected MD, 0.72 for PVC-corrected MD, and 0.90 for volume; uncorrected MD AUCs were significantly greater than PVC-corrected MD AUCs in AD vs. HC.
  • Mediation analysis showed significant indirect effects of regional volume on AD vs. HC diagnosis for all ROIs, with no significant direct MD effects; e.g., left hippocampus indirect effect β = −1.28 with PVC and −1.75 without PVC. MD–volume correlations were significantly higher in uncorrected than PVC-corrected data in all ROIs (all p < 0.001, Williams’ test).

Methods

  • Matched sample of 117 subjects: 39 AD, 39 MCI, and 39 healthy controls from the German Center for Neurodegenerative Diseases in Rostock; diagnoses used NINCDS-ADRDA for AD and Mayo criteria for MCI, matched by age, gender, education, and imaging protocol.
  • 3 T MRI/DTI data were processed with SPM8/VBM8 and DARTEL normalization to an aging/AD-specific template; DTI preprocessing used FSL. PVC used the Koo et al. CSF contamination model as adapted by Jeon et al., with ROIs in bilateral hippocampus and posterior cingulate cortex.
  • Analyses included voxel-wise and ROI ANCOVA, logistic regression with AUC comparisons, partial correlations, and mediation analysis, controlling for age, gender, education, and MRI protocol; sensitivity analyses used an alternative FSL segmentation/normalization pipeline.

Limitations

  • The paper states that the MCI subjects were not uniquely amnestic MCI, making the sample more heterogeneous than some prior MCI studies.
  • The paper states that PVC relied on the Koo et al. CSF contamination model; if FLAIR DTI or DTI with more than one non-zero b-value had been available, additional PVC would have been unnecessary, and results may be sensitive to the segmentation/normalization algorithm because PVC uses VBM8 segmented maps.
  • Evident from the text: the study is cross-sectional and does not provide longitudinal evidence for the assumed succession of microstructural before macrostructural changes; the mediation effect of volume persisted after PVC, which the authors suggest may reflect atrophy too advanced for sufficient correction, and one right hippocampus MCI correlation finding was not reproduced with the FSL pipeline and was assumed to be a VBM8 artefact.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.nicl.2017.10.005

Cites

37 of 37 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

14 of 40 cited sources checked · 7 supported · 1 flagged · accuracy not yet measured

  • Premisecitation

    Most studies using diffusion tensor imaging data of healthy older and Alzheimer's disease participants did not consider partial volume effects at all.

    “However, most of the studies using DTI data of healthy older and AD participants did not consider PVE at all (Cherubini et al., 2010, Douaud et al., 2013, Eustache et al., 2016, Müller et al., 2007).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Cherubini et al., 2010 source
    • cites Douaud et al., 2013 source

      In Materials and Methods (page unavailable), Douaud et al. explicitly identify partial-voluming bias as a pitfall of their grey-matter diffusion analysis and say they kept that caveat in mind. The paper therefore cannot serve as an example of a study that did not consider partial volume effects at all; it also does not establish what most other studies did. (LLM, conf=0.84)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites Eustache et al., 2016 source

      The Materials and Methods sections on imaging and voxel-based analysis describe how the paper processed DTI-derived maps, but do not state whether partial volume effects were considered. The Introduction discusses prior DTI studies without assessing how many accounted for those effects. Searches for “partial volume,” “PVE,” and related correction methods found no passage that settles the claim. (LLM, conf=0.68)

      Experimental — accuracy not yet measured
  • Premisecitation

    In older people and Alzheimer's disease patients, the probability of gray matter voxels to also contain cerebrospinal fluid signal increases due to brain atrophy.

    “In older people and AD patients, the probability of GM voxels to also contain CSF signal increases due to brain atrophy (Jeon et al., 2012).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Jeon et al., 2012 source
  • Premisecitation

    Jeon et al. (2012) successfully applied the cerebrospinal fluid contamination model to gray matter mean diffusivity data of young, older, and Alzheimer's disease participants to correct for partial volume effects.

    “Jeon et al. (2012) successfully applied this CSF contamination model to GM MD data of young and older participants and participants with AD to correct for partial volume effects.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Jeon et al. (2012) source
  • Premisecitation

    The fixed threshold in Rose et al. leads to an altered distribution of mean diffusivity values.

    “This fixed threshold, however, leads to an altered distribution of MD values (Weston et al., 2015).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Weston et al., 2015 source
  • Premisecitation

    Previous studies reported increases of mean diffusivity in mild cognitive impairment patients that converted to Alzheimer's disease compared to mild cognitive impairment subjects that remained stable over several years.

    “as well as in MCI patients that converted to AD compared to MCI subjects that remained stable over a period of several years (Douaud et al., 2013, Fellgiebel et al., 2006, Scola et al., 2010, van Uden et al., 2016).”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Douaud et al., 2013 source
    • cites Fellgiebel et al., 2006 source
    • cites Scola et al., 2010 source
  • Classified as probably not a substantial claim. 29
  • May combine two claims. 19

  • Classified as probably not a substantial claim.

    Premisecitation

    Jeon et al. did not examine the potential diagnostic value of corrected gray matter mean diffusivity for Alzheimer's disease.

    “They found that PVC stronger reduced GM MD in elder and AD participants than in younger participants, but they did not examine the potential diagnostic value of corrected GM MD for AD.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Jeon et al. (2012) source

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Previous studies reported increases of hippocampal mean diffusivity and whole brain gray matter mean diffusivity in subjects with mild cognitive impairment compared to healthy controls.

    “Previous studies on GM MD in AD reported increases of hippocampal MD and whole brain GM MD in subjects with mild cognitive impairment (MCI) as compared to healthy controls (Cherubini et al., 2010, Eustache et al., 2016, Fellgiebel et al., 2004, Müller et al., 2005, Scola et al., 2010)”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Cherubini et al., 2010 source
    • cites Eustache et al., 2016 source

      The Results (Region-based analysis and Voxel-based analyses; page not available) report higher hippocampal mean diffusivity in patients with MCI due to AD than in healthy controls. The whole-brain analysis found localized increases, mainly in the hippocampi and right amygdala; it does not establish an increase in mean diffusivity across the whole brain’s gray matter. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites Fellgiebel et al., 2004 source

  • Classified as probably not a substantial claim.

    Premisecitation

    Left and right hippocampi and the posterior cingulate cortex were chosen as regions of interest following the literature on peak differences in regional mean diffusivity and volumes in Alzheimer's disease.

    “Left and right hippocampi as well as the posterior cingulate cortex (PCC) were chosen as regions of interest following the literature on peak differences in regional MD and volumes in AD (Cherubini et al., 2010, Eustache et al., 2016, Rose et al., 2008).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Cherubini et al., 2010 source
    • cites Eustache et al., 2016 source

      The Results sections on mean diffusivity and volumetry report higher MD and reduced volume in both hippocampi in patients with MCI due to AD compared with controls. The paper’s region-based analysis examined seven segmented structures, but not the posterior cingulate cortex; it therefore supports the hippocampal rationale, not the PCC part of the claim. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites Rose et al., 2008 source

      The Results and Discussion (page not provided) report elevated mean diffusivity in the posterior cingulate in AD, with the largest number of affected voxels there. The paper also discusses elevated hippocampal diffusivity, including reports involving both hippocampi, but it does not report regional volume differences in these regions; it only notes earlier findings of reduced gray-matter density. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Jeon et al. found that partial volume correction more strongly reduced gray matter mean diffusivity in elder and Alzheimer's disease participants than in younger participants.

    “They found that PVC stronger reduced GM MD in elder and AD participants than in younger participants, but they did not examine the potential diagnostic value of corrected GM MD for AD.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Jeon et al. (2012) source

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductcitation

    Diagnosis of Alzheimer's disease was made in accordance with NINCDS-ADRCA criteria and mild cognitive impairment was diagnosed according to Mayo criteria.

    “Diagnosis of AD was made in accordance with the NINCDS-ADRCA criteria (McKhann et al., 2011) and MCI was diagnosed according to the Mayo criteria (Petersen et al., 1999).”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites McKhann et al., 2011 source

      The Introduction identifies the NINCDS–ADRDA criteria as the 1984 criteria for diagnosing AD and says this paper revises them. The paper therefore supports the criteria named in the AD portion of the sentence, but it is not the original NINCDS–ADRDA criteria publication. The separately cited Mayo criteria for MCI are not attributed to this source. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
    • cites Petersen et al., 1999 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Rose et al. (2008) proposed excluding all voxels exceeding a certain threshold of mean diffusivity of 1300 × 10−6 mm2/s.

    “First, Rose et al. (2008) proposed to exclude all voxels exceeding a certain threshold of MD (1300 × 10− 6 mm2/s).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Rose et al. (2008) source

      Data Processing and Analysis states that pixels with MD greater than 1300 × 10−6 mm²/s were removed, supporting the threshold and exclusion method. The exclusion applied to the gray-matter mask, however, not to all voxels generally; the white-matter mask was thresholded using FA instead. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Pasternak's approach has been found to reduce cerebrospinal fluid contamination and to improve diffusion measures in white matter fiber tracts.

    “Although Pasternak's approach has been found to reduce CSF contamination and to improve diffusion measures in white matter fiber tracts (Berlot et al., 2014, Metzler-Baddeley et al., 2012, Pasternak et al., 2009), a formal validation of this model is still missing.”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites Berlot et al., 2014 source
    • cites Metzler-Baddeley et al., 2012 source
    • cites Pasternak et al., 2009 source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The diagnostic subgroups did not differ in age and gender but slightly differed in years of education.

    “The diagnostic subgroups did not differ in age and gender but they did slightly differ in years of education (see Table 1).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Main effects for regional volume were found in all regions of interest and with similar effect sizes across regions of interest.

    “Main effects for regional volume were found in all ROIs and with similar effect sizes across ROIs.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    As indicated by bootstrapped CIs, the indirect effect of regional volume was significant for the discrimination of AD vs. HC, whereas none of the direct effects of MD were significantly different from zero.

    “As indicated by the bootstrapped CIs, the indirect effect of regional volume was significant for the discrimination of AD vs. HC, whereas none of the direct effects of MD were significantly different from zero.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Numerically, the indirect effects were greater for uncorrected MD than for corrected MD in the bilateral hippocampi, although the CIs clearly overlapped.

    “Numerically, the indirect effects were greater for uncorrected MD than for corrected MD in the bilateral hippocampi, although the CIs clearly overlapped.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Mean mean diffusivity values of the mild cognitive impairment group were numerically greater than in the healthy control group for all regions of interest, but none of these differences were statistically significant.

    “Even though mean MD values of the MCI group were numerically greater than in the HC group for all ROIs, none of these differences were statistically significant.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In the left hippocampus and PCC, the correlations between MD and volume were numerically higher in AD subjects than in MCI subjects and higher in MCI than in HC subjects, albeit not significantly.

    “In our study, in the left hippocampus as well as in the PCC, the correlations between MD and volume were numerically - albeit not significantly - higher in AD subjects than in MCI subjects and higher in MCI than in HC subjects.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The Pearson correlations of the MD and volume values were moderate to strong (r = 0.54 to 0.85) with the correlation being the lowest in the PVE corrected MD values.

    “In sum, the Pearson correlations of the MD and volume values were moderate to strong (r = 0.54 to 0.85) with the correlation being the lowest in the PVE corrected MD values (Table 5).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The correlations in the right hippocampus were lowest in MCI subjects.

    “However, the correlations in the right hippocampus were lowest in MCI subjects.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The right hippocampus correlation change in MCI is an artefact of the segmentation and normalization algorithm (VBM 8).

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The groups differed in MMSE scores with Alzheimer's disease patients having the lowest scores and healthy controls having the highest scores.

    “As expected, the groups differed in MMSE scores with AD patients having the lowest scores and healthy controls having the highest scores.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The comparison of Alzheimer's disease patients with healthy controls after partial volume correction still yielded significant results, with elevated mean diffusivity in both hippocampi and in the middle and posterior cingulate cortex.

    “The comparison of AD patients with healthy controls still yielded significant results, with elevated MD in both hippocampi, as well as in the middle and posterior cingulate cortex (Fig. 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    When discriminating mild cognitive impairment from healthy controls, models with bilateral hippocampal mean diffusivity or volume yielded areas under the curve above chance, whereas models containing mean diffusivity or volume of the posterior cingulate cortex did not exceed chance level.

    “When discriminating MCI from HC, the models with bilateral hippocampal MD or volume yielded AUCs above chance, whereas the AUCs of the models containing MD or volume of the PCC did not exceed chance level.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The AUCs for both volume and MD of the left hippocampus were greater than those of the right hippocampus and of the PCC.

    “Considering the different ROIs, we found that the AUCs for both volume and MD of the left hippocampus were greater than those of the right hippocampus and of the PCC.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In all diagnostic group comparisons, AUCs were numerically greater for models containing volume as a predictor than those with MD as a predictor, although AUCs mostly did not differ significantly.

    “In all diagnostic group comparisons, the AUCs were numerically greater for the models containing volume as a predictor than those with MD as a predictor, although the AUCs mostly did not differ significantly.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Koo et al. found high consistency of their partial volume correction approach with fluid-attenuated inversion recovery diffusion tensor imaging, corroborating the validity of this post-hoc data correction procedure.

    “They found a high consistency of their PVC approach with FLAIR DTI, corroborating the validity of this post-hoc data correction procedure.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Koo et al. (2009) source

  • May combine two claims.

    Study design and conductcitation

    Healthy controls were free of cognitive complaints and scored within one standard deviation of the age and education adjusted norm in all subtests of the CERAD cognitive battery.

    “Healthy controls were free of cognitive complaints and scored within one standard deviation of the age and education adjusted norm in all subtests of the Consortium to Establish a Registry of Alzheimer's Disease (CERAD) cognitive battery (Morris et al., 1987).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Morris et al., 1987

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

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    Pasternak's method suffers from computational challenges that require defining regularization parameters and constraints on tensor estimates to obtain a unique solution for model fitting.

    “However, this method suffers from computational challenges that require defining regularization parameters and constraints on tensor estimates to obtain a unique solution for model fitting.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Koo et al. (2009) proposed the cerebrospinal fluid contamination model.

    “Third, Koo et al. (2009) proposed the CSF contamination model.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Koo et al. (2009) source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In some studies, hippocampal diffusivity demonstrated higher diagnostic and prognostic accuracy than hippocampal volume.

    “In some studies, hippocampal diffusivity even demonstrated a higher diagnostic and prognostic accuracy than hippocampal volume (Fellgiebel et al., 2006, Kantarci et al., 2005, Müller et al., 2007).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Fellgiebel et al., 2006 source
    • cites Kantarci et al., 2005 source
    • cites Müller et al., 2007 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All diagnoses were made in an interdisciplinary team of an experienced neurologist, psychiatrist and neuropsychologist.

    “All diagnoses were made in an interdisciplinary team of an experienced neurologist, psychiatrist and neuropsychologist.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    A formal validation of Pasternak's model is still missing.

    “a formal validation of this model is still missing.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The subjects were matched according to age, gender, years of education and imaging protocol.

    “The subjects were matched according to age, gender, years of education and imaging protocol, given that two different sequences were used for MRI and DTI acquisition (Table S1 of the Supplementary material).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    Considering mild cognitive impairment a possibly prodromal phase of Alzheimer's disease, previous findings corroborate the potential utility of gray matter mean diffusivity as an earlier biomarker than volumetric changes.

    “Considering MCI a possibly prodromal phase of AD, these findings corroborate the potential utility of GM MD as an earlier biomarker than volumetric changes.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Mild cognitive impairment is a possibly prodromal phase of Alzheimer's disease.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Differences of permeability of cell bodies in gray matter compared to myelin sheets in white matter may make it necessary to adjust some model parameters when applying Pasternak's model to gray matter.

    “Additionally, differences of the permeability of the cell bodies in gray matter in comparison to the myelin sheets of the fiber bundles in white matter may make it necessary to adjust some of the model parameters when applying this model to gray matter (Pasternak et al., 2009).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Pasternak et al., 2009 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Pasternak et al. (2009) introduced the method of free water elimination, consisting of sub-voxel modeling of a tissue tensor and a cerebrospinal fluid tensor.

    “Second, Pasternak et al. (2009) introduced the method of free water elimination, consisting of sub-voxel modeling of two tensors: a tissue and a CSF tensor.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Pasternak et al. (2009) source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Whole-brain voxel-wise comparisons used analysis of covariance with diagnosis as factor and MRI protocol, age, gender and years of education as covariates.

    “Whole-brain voxel-wise comparisons were made using analysis of covariance (ANCOVA) models in SPM8, with diagnosis as factor and MRI protocol, age, gender and years of education as covariates.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Mediation analysis included age, years of education, gender and MRI protocol as covariates.

    “Age, years of education, gender and MRI protocol were included as covariates.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Sensitivity of imaging variables to the choice of segmentation and normalization algorithm was assessed by correlating SPM and FSL imaging measures.

    “To assess the sensitivity of our imaging variables (MD and volume) to the choice of segmentation and normalization algorithm, we correlated the imaging measures resulting from the SPM processing pipeline with the imaging measures resulting from the FSL pipeline.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Region-of-interest based analysis of mean diffusivity and volume used linear models with diagnosis as main outcome and the aforementioned covariates.

    “ROI based analysis of MD and volume was conducted using linear models in SPSS 21, with diagnosis as main outcome and the aforementioned covariates (ANCOVA).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Only scans that passed quality control by a trained expert evaluating ghosting effects, blurring, motion and susceptibility artifacts were included.

    “Only scans were included that passed quality control by a trained expert who evaluated ghosting effects, blurring, motion and susceptibility artifacts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    To verify the sensitivity of results to the choice of segmentation and normalization algorithm, an alternative FSL segmentation and normalization pipeline was applied with identical further analysis steps.

    “To verify the sensitivity of our results to the choice of segmentation and normalization algorithm, we also applied an alternative segmentation and normalization algorithm on our imaging data using FSL (Version 5.0.9, FMRIB, Oxford, UK, http://www.fmrib.ox.ac.uk/fsl/). All further analysis steps were identical in both processing pipelines.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Logistic regression models included MRI protocol, age, gender and years of education as covariates.

    “To compare the accuracy of group separation based on corrected and uncorrected regional MD and regional volume, logistic regression models including MRI protocol, age, gender and years of education as covariates were calculated using the glm function in R version 3.3.2 (R Development Core Team, 2008).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The fact that the mediating effect of volume persisted after PVC had been applied could be due to brain atrophy that was already too advanced in these subjects to allow for a sufficient PVE correction.

    “However, the fact that the mediating effect of volume persisted after PVC had been applied could be due to brain atrophy that was already too advanced in these subjects to allow for a sufficient PVE correction.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    The study applied the previously validated CSF contamination model by Koo et al. (2009).

    “we applied the previously validated CSF contamination model by Koo et al. (2009).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Koo et al. (2009) source

  • May combine two claims.

    Study design and conductreasoning

    The MCI subjects of the sample were not uniquely amnestic MCI, making the sample more heterogeneous than MCI subgroups in other studies.

    “As a limitation, the MCI subjects of our sample were not uniquely amnestic MCI. Thus, our sample is more heterogeneous than the MCI subgroups in other studies”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Cherubini et al., 2010 source
    • cites Fellgiebel et al., 2006 source
    • cites Müller et al., 2007 source
41 of 41

  • The authors state this as an assumption.

    Microstructural changes in Alzheimer's disease predate macrostructural volumetric changes observable with MRI.

    “During the course of Alzheimer's Disease (AD), these changes are assumed to predate the macrostructural changes that are observable using volumetric magnetic resonance imaging (Weston et al., 2015).”

  • The authors state this as an assumption.

    An increase of mean diffusivity in gray matter reflects breakdown of microstructural barriers to diffusion that predates volumetric changes.

    “An increase of MD in GM is assumed to reflect the breakdown of microstructural barriers to diffusion which would predate volumetric changes (Weston et al., 2015).”

  • The authors state this as an assumption.

    Mean diffusivity alterations in Alzheimer's disease subjects are partly confounded by increased brain atrophy.

    “As we assumed that MD alterations were partly confounded by increased brain atrophy in AD subjects, we expected that PVC would decrease group differences and diagnostic accuracy of MD and reduce the correlation between regional MD and volume measures.”

  • The paper relies on this without support.

    Mild cognitive impairment is a possibly prodromal phase of Alzheimer's disease.

    “Considering MCI a possibly prodromal phase of AD, these findings corroborate the potential utility of GM MD as an earlier biomarker than volumetric changes.”

  • The authors state this as an assumption.

    The right hippocampus correlation change in MCI is an artefact of the segmentation and normalization algorithm (VBM 8).

    “we assume that it is an artefact of the segmentation and normalization algorithm (VBM 8).”

  • The authors state this as an assumption.

    Alterations of both MD and volume are caused by the same neurodegenerative process.

    “assuming that alterations of both MD and volume are caused by the same neurodegenerative process.”
6 of 6

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • ConsistentF(2, 114) = 0.92reported p = .4 · recomputed p = .401

    “F(2,114) = 0.92, p = .4”

  • ConsistentF(2, 114) = 2.61reported p = .08 · recomputed p = .078

    “F(2,114) = 2.61, p = .08”

  • ConsistentF(2, 114) = 39.18reported p < .001 · recomputed p < .001

    “F(2,114) = 39.18, p < .001”

3 of 3

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Left hippocampus does not consistently have the highest AUC

    Minor

    In the AD-versus-MCI comparison, PCC volume has an AUC of 0.84, compared with 0.79 for left-hippocampal volume. The PCC corrected-MD AUC is likewise higher, at 0.75 versus 0.61.

  • Reported cross-pipeline correlation range omits 0.53

    Minor

    The stated range starts at 0.54, but Table 5 reports a correlation of 0.53 for PCC volume.

  • Post-hoc AD-MCI MD differences are described as significant despite trend labels

    Minor

    The results describe AD MD as significantly increased relative to MCI across the ROIs, but Table 2 marks the AD-MCI comparisons for corrected MD in both hippocampi with †, defined as a trend at p < 0.1 rather than significance at p < 0.05.

  • Volume AUC is not higher in every comparison

    Minor

    For MCI versus healthy controls, uncorrected right-hippocampal MD has an AUC of 0.71, exceeding the volume AUC of 0.68. The PCC MD AUC of 0.63 also exceeds its volume AUC of 0.62.

4 of 4

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Ly, 2014, 2054, 2044
  2. Salminen, 2016, 18, 5

Cited by

Sorted by citations

Related

Authors
Henf, J., Grothe, M. J., Brueggen, K., Teipel, S., & Dyrba, M.
Affiliations
German Center for Neurodegenerative Diseases (DE)
Corresponding author
Henf, Judith
ORCID
Venue
NeuroImage: Clinical
Publisher
Elsevier BV
Published
2018
Volume
17
Pages
579-586
ISSN
2213-1582 (ISSN-L)
DOI
10.1016/j.nicl.2017.10.005
PMC
PMC5702878
OpenAlex
W2763764317
Semantic Scholar
d921c86dcf9e4d56e3698c65925d69cc1af60004
Cited by
64
References
37
Citations by year
2026: 9 · 2025: 8 · 2024: 8 · 2023: 5 · 2022: 7 · 2021: 8 · 2020: 10 · 2019: 7 · 2018: 2
FWCI
3.60
Type
journal article
Language
en
Open access
Licence
Locations
  • NeuroImage Clinical (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DZNE Pub (submittedVersion, cc-by-nc-nd)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
mean diffusivity, partial volume correction, Alzheimer's disease, mild cognitive impairment, cortical gray matter, diffusion tensor imaging, brain atrophy, hippocampus, posterior cingulate cortex, gray matter volume, diagnostic accuracy, prodromal Alzheimer's disease
MeSH terms
Aged, Alzheimer Disease, Cerebral Cortex, Female, Humans, Image Interpretation, Computer-Assisted, Male, Diffusion Tensor Imaging, Gray 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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-24.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-24.

Cited sources are checked by 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 ›

Are you an author, or do you see a problem with this page? Request a review