Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer – ASEG and SAMSEG

• Published in: NeuroImage (Orlando, Fla.) Vol. 237; p. 118113
• Main Authors: Sederevičius, Donatas, Vidal-Piñeiro, Didac, Sørensen, Øystein, van Leemput, Koen, Iglesias, Juan Eugenio, Dalca, Adrian V., Greve, Douglas N., Fischl, Bruce, Bjørnerud, Atle, Walhovd, Kristine B., Fjell, Anders M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.08.2021; Elsevier Limited; Elsevier
• Subjects: Accuracy; Adolescent; Adult; Age; Aged; Aged, 80 and over; Aging; Alzheimer Disease - diagnostic imaging; Alzheimer Disease - pathology; Alzheimer's disease; Amygdala; Atrophy; Automation; Bias; Brain; Brain - diagnostic imaging; Brain - pathology; Child; Child, Preschool; Cognitive ability; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - pathology; Comparative analysis; Datasets; Female; Globus pallidus; Hippocampus; Hippocampus - diagnostic imaging; Hippocampus - pathology; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Life span; Longitudinal Studies; Magnetic resonance imaging; Magnetic Resonance Imaging - standards; Male; Medical imaging; Middle Aged; Neurodegenerative diseases; Neuroimaging; Neuroimaging - standards; Nucleus accumbens; Putamen; Registration; Reproducibility of Results; Scanners; Segmentation; Sensitivity analysis; Sensitivity and Specificity; Thalamus; Ventricle (lateral); Young Adult; Germany
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2021.118113

Accurate and reliable whole-brain segmentation is critical to longitudinal neuroimaging studies. We undertake a comparative analysis of two subcortical segmentation methods, Automatic Segmentation (ASEG) and Sequence Adaptive Multimodal Segmentation (SAMSEG), recently provided in the open-source neuroimaging package FreeSurfer 7.1, with regard to reliability, bias, sensitivity to detect longitudinal change, and diagnostic sensitivity to Alzheimer’s disease. First, we assess intra- and inter-scanner reliability for eight bilateral subcortical structures: amygdala, caudate, hippocampus, lateral ventricles, nucleus accumbens, pallidum, putamen and thalamus. For intra-scanner analysis we use a large sample of participants (n = 1629) distributed across the lifespan (age range = 4–93 years) and acquired on a 1.5T Siemens Avanto (n = 774) and a 3T Siemens Skyra (n = 855) scanners. For inter-scanner analysis we use a sample of 24 participants scanned on the day with three models of Siemens scanners: 1.5T Avanto, 3T Skyra and 3T Prisma. Second, we test how each method detects volumetric age change using longitudinal follow up scans (n = 491 for Avanto and n = 245 for Skyra; interscan interval = 1–10 years). Finally, we test sensitivity to clinically relevant change. We compare annual rate of hippocampal atrophy in cognitively normal older adults (n = 20), patients with mild cognitive impairment (n = 20) and Alzheimer’s disease (n = 20). We find that both ASEG and SAMSEG are reliable and lead to the detection of within-person longitudinal change, although with notable differences between age-trajectories for most structures, including hippocampus and amygdala. In summary, SAMSEG yields significantly lower differences between repeated measures for intra- and inter-scanner analysis without compromising sensitivity to changes and demonstrating ability to detect clinically relevant longitudinal changes.