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Comparison and Reliability of Hippocampal Subfield Segmentations Within FreeSurfer Utilizing T1- and T2-Weighted Multispectral MRI Data.

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.

SUBMITTER: Seiger R

PROVIDER: S-EPMC8480394 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeStudies using magnetic resonance imaging to assess lumbar multifidus cross-sectional area frequently utilize T1 or T2-weighted sequences, but seldom provide the rationale for their sequence choice. However, technical considerations between their acquisition protocols could impact on the ability to assess lumbar multifidus anatomy or its fat/muscle distinction. Our objectives were to examine the concurrent validity of lumbar multifidus morphology measures of T2 compared to T1-weighted sequences, and to assess the reliability of repeated lumbar multifidus measures.MethodsThe lumbar multifidus total cross-sectional area of 45 patients was measured bilaterally at L4 and L5, with histogram analysis determining the muscle/fat threshold values per muscle. Images were later re-randomized and re-assessed for intra-rater reliability. Matched images were visually rated for consistency of outlining between both image sequences. Bland-Altman bias, limits of agreement, and plots were calculated for differences in total cross-sectional area and percentage fat between and within sequences, and intra-rater reliability analysed.ResultsT1-weighted total cross-sectional area measures were systematically larger than T2 (0.2 cm2), with limits of agreement <±10% at both spinal levels. For percentage fat, no systematic bias occurred, but limits of agreement approached ±15%. Visually, muscle outlining was consistent between sequences, with substantial mismatches occurring in <5% of cases. Intra-rater reliability was excellent (ICC: 0.981-0.998); with bias and limits of agreement less than 1% and ±5%, respectively.ConclusionTotal cross-sectional area measures and outlining of muscle boundaries were consistent between sequences, and intra-rater reliability for total cross-sectional area and percentage fat was high indicating that either MRI sequence could be used interchangeably for this purpose. However, further studies comparing the accuracy of various methods for distinguishing fat from muscle are recommended.

Dataset Information

Comparison and Reliability of Hippocampal Subfield Segmentations Within FreeSurfer Utilizing T1- and T2-Weighted Multispectral MRI Data.

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