A reliable protocol for the manual segmentation of the human amygdala and its subregions using ultra-high resolution MRI

The measurement of the volume of the human amygdala in vivo has received increasing attention over the past decade, but existing methods face several challenges. First, due to the amorphous appearance of the amygdala and the difficulties in interpreting its boundaries, it is common for protocols to omit sizable sections of the rostral and dorsal regions of the amygdala comprising parts of the basolateral complex (BL) and central nucleus (Ce), respectively. Second, segmentation of the amgydaloid complex into separate subdivisions is challenging due to the resolution of routinely acquired images and the lack of standard protocols. Recent advances in technology have made ultra-high resolution MR images available, and in this study we provide a detailed segmentation protocol for manually tracing the whole amygdala that incorporates a greater portion of the rostral and dorsal sections with techniques illustrated in detail to maximize reproducibility. In addition, we propose a geometrically-based protocol for segmenting the amygdala into four component subregions of interest (sROI), which correspond largely to amygdala subnuclear divisions: the BL sROI, centromedial (CM) sROI, basomedial (BM) sROI, and the amygdaloid cortical (ACo) sROI. We performed an intra- and inter-rater reliability study of our methods in 10 adults (5 young adults and 5 older adults). The results indicate that both protocols can be implemented with a high degree of reliability (the majority of intra-rater and inter-rater correlations were > 0.81). This protocol should aid further research into the alterations in amygdala anatomy, connectivity, and function that accompany normal aging and pathology associated with neuropsychiatric disorders.

► We create protocols for whole amygdala and subnuclei segmentation in living humans. ► We use detail visible in high-resolution MRIs to demarcate boundaries. ► We test inter-rater and intra-rater reliabilities. ► Methods are precise and reliable.