PT  - JOURNAL ARTICLE
AU  - L.E.M. Wisse
AU  - H.J. Kuijf
AU  - A.M. Honingh
AU  - H. Wang
AU  - J.B. Pluta
AU  - S.R. Das
AU  - D.A. Wolk
AU  - J.J.M. Zwanenburg
AU  - P.A. Yushkevich
AU  - M.I. Geerlings
TI  - Automated Hippocampal Subfield Segmentation at 7T MRI
AID  - 10.3174/ajnr.A4659
DP  - 2016 Jun 01
TA  - American Journal of Neuroradiology
PG  - 1050--1057
VI  - 37
IP  - 6
4099  - http://www.ajnr.org/content/37/6/1050.short
4100  - http://www.ajnr.org/content/37/6/1050.full
SO  - Am. J. Neuroradiol.2016 Jun 01; 37
AB  - BACKGROUND AND PURPOSE: High resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI.MATERIALS AND METHODS: The cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal cortex were manually segmented, covering most of the long axis of the hippocampus on 0.70-mm3 T2-weighted 7T images of 26 participants (59 ± 9 years, 46% men). The automated segmentation of hippocampal subfields approach was applied and evaluated by using leave-one-out cross-validation.RESULTS: Comparison of automated segmentations with corresponding manual segmentations yielded a Dice similarity coefficient of >0.75 for CA1, the dentate gyrus, subiculum, and entorhinal cortex and >0.54 for CA2 and CA3. Intraclass correlation coefficients were >0.74 for CA1, the dentate gyrus, and subiculum; and >0.43 for CA2, CA3, and the entorhinal cortex. Restricting the comparison of the entorhinal cortex segmentation to a smaller range along the anteroposterior axis improved both intraclass correlation coefficients (left: 0.71; right: 0.82) and Dice similarity coefficients (left: 0.78; right: 0.77). The accuracy of the automated segmentation versus a manual rater was lower, though only slightly for most subfields, than the intrarater reliability of an expert manual rater, but it was similar to or slightly higher than the accuracy of an expert-versus-manual rater with ∼170 hours of training for almost all subfields.CONCLUSIONS: This work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields that is competitive with the labor-intensive manual segmentation. The software and atlas are publicly available: http://www.nitrc.org/projects/ashs/.ASHSautomated segmentation of hippocampal subfieldsCAcornu ammonisDSCDice similarity coefficientDGdentate gyrusERCentorhinal cortexICCintraclass correlation coefficientSUBsubiculum