Abstract
The accurate segmentation of in vivo magnetic resonance imaging (MRI) data is a crucial prerequisite for the reliable assessment of disease progression, patient stratification or the establishment of putative imaging biomarkers. This is especially important for the hippocampal formation, a brain area involved in memory formation and often affected by neurodegenerative or psychiatric diseases. FreeSurfer, a widely used automated segmentation software, offers hippocampal subfield delineation with multiple input options. While a single T1-weighted (T1) sequence is regularly used by most studies, it is also possible and advised to use a high-resolution T2-weighted (T2H) sequence or multispectral information. In this investigation it was determined whether there are differences in volume estimations depending on the input images and which combination of these deliver the most reliable results in each hippocampal subfield. 41 healthy participants (age = 25.2 years ± 4.2 SD) underwent two structural MRIs at three Tesla (time between scans: 23 days ± 11 SD) using three different structural MRI sequences, to test five different input configurations (T1, T2, T2H, T1 and T2, and T1 and T2H). We compared the different processing pipelines in a cross-sectional manner and assessed reliability using test-retest variability (%TRV) and the dice coefficient. Our analyses showed pronounced significant differences and large effect sizes between the processing pipelines in several subfields, such as the molecular layer (head), CA1 (head), hippocampal fissure, CA3 (head and body), fimbria and CA4 (head). The longitudinal analysis revealed that T1 and multispectral analysis (T1 and T2H) showed overall higher reliability across all subfields than T2H alone. However, the specific subfields had a substantial influence on the performance of segmentation results, regardless of the processing pipeline. Although T1 showed good test-retest metrics, results must be interpreted with caution, as a standard T1 sequence relies heavily on prior information of the atlas and does not take the actual fine structures of the hippocampus into account. For the most accurate segmentation, we advise the use of multispectral information by using a combination of T1 and high-resolution T2-weighted sequences or a T2 high-resolution sequence alone.
Highlights
Following the seminal findings from Scoville and Milner studying the “patient H
The same is seen in temporal lobe epilepsy (TLE) with mesial temporal sclerosis (TLE-MTS) where an overall decline in the subfields is observed, but not in the subiculum, which is quite different to the pattern seen in Alzheimer’s disease (AD) or depression (West et al, 1994; Gomez-Isla et al, 1996; Posener et al, 2003; Ballmaier et al, 2008; Mueller et al, 2009; Small, 2014)
The Friedman tests with Wilcoxon post hoc tests conducted for the cross-sectional analysis comprising the five different processing pipelines (T1, T2, T2H, T1 and T2, and T1 and T2H) revealed vast significant differences in several subfields between the input configurations
Summary
Following the seminal findings from Scoville and Milner studying the “patient H. The same is seen in temporal lobe epilepsy (TLE) with mesial temporal sclerosis (TLE-MTS) where an overall decline in the subfields is observed, but not in the subiculum, which is quite different to the pattern seen in AD or depression (West et al, 1994; Gomez-Isla et al, 1996; Posener et al, 2003; Ballmaier et al, 2008; Mueller et al, 2009; Small, 2014) These findings grant valuable information to better monitor disease progression, onset and for the putative development of biomarkers or prognosis for treatment outcome, tailored for the respective disease. Reliable assessment of these hippocampal substructures and high reliability of processing strategies are of utmost importance for human in vivo neuroscientific investigations
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