Search

Background: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults., Methods: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session., Results: Significant MRI site and vendor effects (p ​< ​.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p ​< ​1.39E-36). In particular, volumes larger than 200 ​mm 3 (for amygdalar nuclei) and 300 ​mm 3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε ​< ​5% and DICE ​> ​0.80)., Conclusion: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials., Competing Interests: Declaration of competing interest None., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

NIA-AA diagnostic criteria include volumetric or visual rating measures of hippocampal atrophy (HA) as a diagnostic biomarker of Alzheimer's disease (AD). We aimed to determine its utility as a diagnostic biomarker for early onset Alzheimer's disease (EOAD) by assessing Medial Temporal Atrophy (MTA) and hippocampal volume (HV) determination. MTA score and HV quantified by FreeSurfer were assessed in 140 (aged ≤65) subjects with biomarker supported diagnosis: 38 amnesic (A-EOAD), 20 non-amnesic (NA-EOAD), 30 late onset AD (LOAD), 20 fronto-temporal dementia (FTD) and 32 healthy controls (HC). The results showed that the proportion of MTA ≥ 1.5 was higher on LOAD and FTD than EOAD and HC but none of the MTA thresholds (≥1, ≥1.5 and ≥ 2) showed acceptable diagnostic accuracy. LOAD had lower HV than the other groups. A-EOAD HV was lower than NA-EOAD and HC but equal to FTD. The 6258 mm3 cut-off showed good diagnostic accuracy between A-EOAD and HC. Both tools showed a moderate inverse correlation. In conclusion, MTA has a limited diagnostic utility as an EOAD biomarker as it does not discriminate AD from FTD or HC in initial symptomatic stages. HV may discriminate A-EOAD from HC but not from FTD., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

We assessed first-year hippocampal atrophy in stroke patients and healthy controls using manual and automated segmentations: AdaBoost, FIRST (fsl/v5.0.8), FreeSurfer/v5.3 and v6.0, and Subfields (in FreeSurfer/v6.0). We estimated hippocampal volumes in 39 healthy controls and 124 stroke participants at three months, and 38 controls and 113 stroke participants at one year. We used intra-class correlation, concordance, and reduced major axis regression to assess agreement between automated and 'Manual' estimations. A linear mixed-effect model was used to characterize hippocampal atrophy. Overall, hippocampal volumes were reduced by 3.9% in first-ever stroke and 9.2% in recurrent stroke at three months post-stroke, with comparable ipsi-and contra-lesional reductions in first-ever stroke. Mean atrophy rates between time points were 0.5% for controls and 1.0% for stroke patients (0.6% contra-lesionally, 1.4% ipsi-lesionally). Atrophy rates in left and right-hemisphere strokes were comparable. All methods revealed significant volume change in first-ever and ipsi-lesional stroke (p < 0.001). Hippocampal volume estimation was not impacted by hemisphere, study group, or scan time point, but rather, by the interaction between the automated segmentation method and hippocampal size. Compared to Manual, Subfields and FIRST recorded the lowest bias. FreeSurfer/v5.3 overestimated volumes the most for large hippocampi, while FIRST was the most accurate in estimating small volumes. AdaBoost performance was average. Our findings suggest that first-year ipsi-lesional hippocampal atrophy rate especially in first-ever stroke, is greater than atrophy rates in healthy controls and contra-lesional stroke. Subfields and FIRST can complementarily be effective in characterizing the hippocampal atrophy in healthy and stroke cohorts., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)