Cogswell, Petrice M.

AbstractBackgroundIn 2018 we presented the Computational DESH (CDESH) metric (DOI:10.1016/j.nicl.2018.11.015), a machine learning measure of abnormal CSF space patterns commonly observed on MRI in Disproportionately Enlarged Subarachnoid‐space Hydrocephalus (DESH‐type) NPH. We have shown that CDESH positive individuals often have discordant CSF and PET amyloid measures (DOI:10.1016/j.jalz.2019.06.4921). Positive CDESH scores are predictive of cognitive decline (DOI:10.1016/j.neuroimage.2021.117899, DOI: 10.1212/WNL.0000000000008616). The score is calculated from regional CSF volumes in a sulcal atlas and within the ventricles using a support vector machine (SVM). The Mayo Clinic Study of Aging (MCSA) changed scanner platforms (GE to Siemens) and T1‐weighted image resolution (1.2mm x 1.05mm x 1.05mm to 0.8mm isotropic) in 2017. We refer to these as “isotropic” or “anisotropic” scans. Our objective was to assess the dependence of a machine learning method (specifically CDESH) to image input variation and, if necessary, determine what needed corrections.MethodAll data considered is from the MCSA or Mayo Clinic ADRC. The SVM was trained on anisotropic images with laboriously labelled ground truth. We resampled the isotropic data from a crossover study (N=112, typically scanned same‐day with both platforms/resolutions) to match the anisotropic resolution. Two approaches to correction were evaluated (Figure 1). In Figure 2 we compare of the score with and without correction cross‐sectionally in 998 MCSA participants. In Figure 3 we present longitudinal series from 23 participants with multiple scans using the isotropic resolution protocol and at least one prior anisotropic image.ResultsComparisons of data from the crossover study are presented in Figure 1. Matching voxel resolution to the data used to train the SVM is critical and a subsequent mild linear score adjustment may be warranted. Cross‐sectional comparisons (Figure 2) confirm improvement matching voxel resolution with a possible mild linear score adjustment. After matching voxel resolution CDESH score trajectories (Figure 3) are markedly more stable across this scanner/protocol change.ConclusionThe SVM‐based CDESH score is sensitive to voxel resolution. Corrections are needed in image processing and possibly in the scalar output score to achieve stability across protocol and scanner changes. The resulting correction supports coherent long timeseries data and longitudinal extension of previous work.

AbstractBackgroundQuantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating the local tissue magnetic susceptibility of every voxel. Dysregulation of neuronal iron has been correlated with typical Alzheimer’s disease (tAD), but little is known about iron distribution in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA).MethodEleven PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five‐echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions‐of‐interest across the brain using the Mayo Clinic Adult Lifespan Template. Hierarchical models were fit per‐region and per‐hemisphere to compare PCA and LPA to each other, to 20 healthy controls, and to 20 patients with tAD recruited by the Alzheimer’s Disease Research Center.ResultStrong evidence (posterior probability>0.99) was observed for greater susceptibility in the left middle occipital gyrus and amygdala in both LPA and PCA, and in the right precuneus and inferior temporal gyrus in PCA compared to controls. Moderate evidence for greater susceptibility (posterior probability>0.90) was also observed in the left insula, inferior occipital gyrus, entorhinal cortex, and right inferior parietal gyrus and amygdala in both LPA and PCA, along with right angular gyrus and middle occipital gyrus in PCA and right insula and caudate in LPA, when compared to controls. Comparing between phenotypes, LPA showed moderate evidence for greater susceptibility in the caudate, hippocampus, substantia nigra, left supramarginal gyrus and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right precuneus compared to LPA. Both LPA and PCA showed moderate‐strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions.ConclusionUnique iron profiles were identified in LPA and PCA within cortical and subcortical structures. These changes are in line with disease‐related neurodegenerative changes in the clinical phenotypes, suggesting that QSM could be an informative marker to study iron deposition in these patients.

Background Phase-contrast cine magnetic resonance imaging (PC-MRI) has been used to measure cerebrospinal fluid (CSF) flow dynamics, but the influence of the area of the aqueduct and region of interest (ROI) on quantification of stroke volume (SV) has not been assessed. Purpose To assess the influence of the area of the ROI in quantifying the aqueductal SV measured with PC-MRI within the cerebral aqueduct. Material and Methods Nine healthy volunteers (mean age = 29.6 years) were enrolled in the study, and brain MRI examinations were performed on a 3.0-T system. Quantitative analysis of the aqueductal CSF flow was performed using manual ROI placement. ROIs were separately drawn for each of the 12 phases of the cardiac cycle, and changes in aqueduct size during the cardiac cycle were determined. The SV was calculated using 12 different aqueductal ROIs and compared with the SV calculated using a fixed ROI size. Results There was variation in the size of the aqueduct during the cardiac cycle. In addition, the measured SV increased with a greater area of the ROI. A significant difference in the calculated SVs with the 12 variable ROIs was observed compared with that using a fixed ROI throughout the cardiac cycle. Conclusion To establish reliable reference values for the SV in future studies, a variable ROI should be considered.

BackgroundFocally enlarged sulci (FES) are areas of proposed extraventricular fluid entrapment that may occur within idiopathic normal pressure hydrocephalus (iNPH) with radiographic evidence of disproportionately enlarged subarachnoid‐space hydrocephalus (DESH), and should be differentiated from atrophy.PurposeTo evaluate for change in FES size and pituitary height after shunt placement in iNPH.Study typeRetrospective.SubjectsA total of 125 iNPH patients who underwent shunt surgery and 40 age‐matched controls.Field Strength/Sequence1.5 T and 3 T. Axial T2w FLAIR, 3D T1w MPRAGE, 2D sagittal T1w.AssessmentFES were measured in three dimensions and volume was estimated by assuming an ellipsoid shape. Pituitary gland height was measured in the mid third of the gland in iNPH patients and controls.Statistical testsWilcoxon signed‐rank test for comparisons between MRI measurements; Wilcoxon rank sum test for comparison of cases/controls. Significance level was P < 0.05.ResultsFifty percent of the patients had FES. FES volume significantly decreased between the pre and first postshunt MRI by a median of 303 mm3 or 30.0%. Pituitary gland size significantly increased by 0.48 mm or 14.4%. FES decreased significantly by 190 mm3 or 23.1% and pituitary gland size increased significantly by 0.25 mm or 6% between the first and last postshunt MRI.Data ConclusionDecrease in size of FES after shunt placement provides further evidence that these regions are due to disordered cerebrospinal fluid (CSF) dynamics and should not be misinterpreted as atrophy. A relatively smaller pituitary gland in iNPH patients that normalizes after shunt is a less‐well recognized feature of altered CSF dynamics.Evidence Level3Technical EfficacyStage 2

BackgroundLocalized regions of left–right image intensity asymmetry (LRIA) were incidentally observed on T2‐weighted (T2‐w) and T1‐weighted (T1‐w) diagnostic magnetic resonance imaging (MRI) images. Suspicion of herpes encephalitis resulted in unnecessary follow‐up imaging. A nonbiological imaging artifact that can lead to diagnostic uncertainty was identified.PurposeTo investigate whether systematic LRIA exist for a range of scanner models and to determine if LRIA can introduce diagnostic uncertainty.Study TypeA retrospective study using the Alzheimer's Disease Neuroimaging Initiative (ADNI) data base.SubjectsOne thousand seven hundred fifty‐three (median age: 72, males/females: 878/875) unique participants with longitudinal data were included.Field Strength3T.SequencesT1‐w three‐dimensional inversion‐recovery spoiled gradient‐echo (IR‐SPGR) or magnetization‐prepared rapid gradient‐echo (MP‐RAGE) and T2‐w fluid‐attenuated inversion recovery (FLAIR) long tau fast spin echo inversion recovery (LT‐FSE‐IR). Only General Electric, Philips, and Siemens' product sequences were used.AssessmentLRIA was calculated as the left–right percent difference with respect to the mean intensity from automated anatomical atlas segmented regions. Three neuroradiologists with 37 (**), 32 (**), and 3 (**) years of experience rated the clinical impact of 30 T2‐w three‐dimensional FLAIR exams with LRIA to determine the diagnostic uncertainty. Statistical comparisons between retrospective intensity normalized T1m and original T1‐w images were made.Statistical TestsFor each image type, a linear mixed effects model was fit using LRIA scores from all scanners, regions, and participants as the outcome and age and sex as predictors. Statistical significance was defined as having a P‐value <0.05.ResultsLRIA scores were significantly different from zero on most scanners. All clinicians were uncertain or recommended definite diagnostic follow‐up in 62.5% of cases with LRIA >10%. Individuals with acute brain pathology or focal neurologic deficits are not enrolled in ADNI; therefore, focal signal abnormalities were considered false positives.Data ConclusionLRIA is system specific, systematic, creates diagnostic uncertainty, and impacts IR‐SPGR, MP‐RAGE, and LT‐FSE‐IR product sequences.Level of Evidence: 2Technical Efficacy Stage: 3

AbstractBackgroundAlzheimer’s disease biomarkers of tau pathology may be assessed by both CSF and PET. Cross‐sectional associations between CSF phosphorylated tau (p‐tau) and tau PET have been studied and regional tau PET SUVR has been shown to have similar diagnostic performance as CSF p‐tau. The association between CSF p‐tau and longitudinal tau PET has not been studied. CSF measures may be thought of as a result of the imbalance of influx vs efflux of soluble tau, whereas, tau PET reflects total tau accumulation into insoluble aggregates to date. We therefore hypothesize that baseline CSF p‐tau may be a leading indicator of future tau PET accumulation.MethodWe identified Mayo Clinic Study of Aging (MCSA) and Mayo Alzheimer’s Disease Research Center (ADRC) participants with diagnoses of cognitively unimpaired, mild cognitive impairment, and amnestic dementia who had CSF p‐tau (Elecsys p‐tau [181P]) and subsequent serial tau PET (flortaucipir) exams. The first tau PET scan was within 3 years of the CSF p‐tau collection. A longitudinal pipeline with two‐compartment partial volume correction was used to measure change in tau PET in a temporal‐lobe meta‐ROI (amygdala, fusiform, middle/inferior temporal, entorhinal, and parahippocampal regions) with a composite reference region (eroded supratentorial white matter, pons, and whole cerebellum). Spearman correlation was used to assess the association between CSF p‐tau and annual percent change in tau PET. A linear mixed effects model was fit to assess the association adjusting for age and sex.ResultThe study included 143 participants (76% cognitively unimpaired) (). CSF p‐tau was significantly associated with annual percent change in tau PET overall (Spearman R=0.19, p=0.023) () and after adjusting for age and sex (p<0.001) (). There was nonlinearity in the CSF p‐tau effect, with higher values (>20 pg/mL) having a greater association with annual change in tau PET than lower values.ConclusionIn a group of cognitively unimpaired and impaired participants, CSF p‐tau predicted subsequent tau PET accumulation rate. A threshold effect is suggested with subsequent tau PET accumulation primarily in participants with elevated CSF p‐tau levels near the Mayo threshold of 22 pg/mL.

BackgroundA low‐cryogen, compact 3T (C3T) MRI scanner with high‐performance gradients capable of simultaneously achieving 80 mT/m gradient amplitude and 700 T/m/second slew rate has been in use to study research patients since March 2016 but has not been implemented in the clinical practice.PurposeTo compare head MRI examinations obtained with the C3T system and a conventional whole‐body 3T (WB3T) scanner in seven parameters across five commonly used brain imaging sequences.Study TypeProspective.SubjectsThirty patients with a clinically indicated head MRI.Sequence 3T; T1 FLAIR, T1 MP‐RAGE, 3D T2 FLAIR, T2 FSE, and DWI.AssessmentAll patients tolerated the scans well. Three board‐certified neuroradiologists scored the comparative quality of C3T and WB3T images in blinded fashion using a five‐point Likert scale in terms of: signal‐to‐noise ratio, lesion conspicuity, motion artifact, gray/white matter contrast, cerebellar folia, susceptibility artifact, and overall quality.Statistical TestLeft‐sided, right‐sided, and two‐sided Wilcoxon signed rank test; Fisher's method. A P value <0.05 was considered statistically significant.ResultsThe C3T system performed better than the WB3T in virtually all comparisons, except for motion artifacts for the T1 FLAIR and T1 MP‐RAGE sequences, where the WB3T system was deemed better. When combining all sequences together, the C3T system outperformed the WB3T system in all image quality parameters evaluated, except for motion artifact (P = 0.13).Data ConclusionThe C3T scanner provided better overall image quality for all sequences, and performed better in all individual categories, except for motion artifact on the T1 FLAIR and T1 MP‐RAGE.Level of Evidence2Technical Efficacy Stage1

Introduction There is increased interest in the use of artificial intelligence-based (AI) software packages in the evaluation of neuroimaging studies for acute ischemic stroke. We studied whether, compared to standard image interpretation without AI, Brainomix e-ASPECTS software improved interobserver agreement and accuracy in detecting ASPECTS regions affected in anterior circulation LVO. Methods We included 60 consecutive patients with anterior circulation LVO who had TICI 3 revascularization within 60 minutes of their baseline CT. A total of 16 readers, including senior neuroradiologists, junior neuroradiologists and vascular neurologists participated. Readers interpreted CT scans on independent workstations and assessed final ASPECTS and evaluated whether each individual ASPECTS region was affected. Two months later, readers again evaluated the CT scans, but with assistance of e-ASPECTS software. We assessed interclass correlation coefficient for total ASPECTS and interobserver agreement with Fleiss’ Kappa for each ASPECTS region with and without assistance of the e-ASPECTS. We also assessed accuracy for the readers with and without e-ASPECTS assistance. In our assessment of accuracy, ground truth was the 24 hour CT in this cohort of patients who had prompt and complete revascularization. Results Interclass correlation coefficient for total ASPECTS without e-ASPECTS assistance was 0.395, indicating fair agreement compared, to 0.574 with e-ASPECTS assistance, indicating good agreement (P < 0.01). There was significant improvement in inter-rater agreement with e-ASPECTS assistance for each individual region with the exception of M6 and caudate. The e-ASPECTS software had higher accuracy than the overall cohort of readers (with and without e-ASPECTS assistance) for every region except the caudate. Conclusions Use of Brainomix e-ASPECTS software resulted in significant improvements in inter-rater agreement and accuracy of ASPECTS score evaluation in a large group of neuroradiologists and neurologists. e-ASPECTS software was more predictive of final infarct/ASPECTS than the overall group interpreting the CT scans with and without e-ASPECTS assistance.

Abstract Background: The relationship of the area of the aqueduct on quantification of the aqueductal stroke volume (SV) and max velocity need further investigation. Our aim was to assess the influence of the area of the aqueduct on quantification of the aqueductal SV and max velocity measured with phase contrast magnetic resonance imaging (PC-MRI) within the cerebral aqueduct at the level of the intercollicular sulcus.Materials and Methods: Nine healthy volunteers (mean age 29.6 yrs) were enrolled in the study and brain MRIs were performed on a 3.0T system. Quantitative analysis of aqueductal cerebrospinal fluid (CSF) flow was performed using manual regions of interest (ROI) placement. ROIs were separately drawn for each of 12 phases of the cardiac cycle, and changes in aqueduct size during the cardiac cycle were determined. Stroke volumes were calculated uses the first and ninth aqueductal ROIs and compared to each other. Max velocities at the 12 phases were also collected, and the relationship between the area and max velocity and the impact on SV were analyzed.Results: There was variation in the size of the aqueduct during the cardiac cycle, the first area（S1）was larger than the ninth（S9）. The first max velocity（Vmax1）was less than the ninth（Vmax9）. Additionally, there was a significant different between the stroke volume calculated using the first aqueductal ROI (SV1) and the ninth（SV9）. Conclusions: There is variation in the size of the cerebral aqueduct which is used to calculate stroke volume and other CSF flow parameters during the cardiac cycle. The maximum velocity may be inversely proportional to the area of ​​the aqueduct. In order to establish reliable reference values for CSF flow parameters in future studies, a variable ROI, to account for cardiac cycle variation, should be considered and incorporated.