Quantification of Thalamic Volume in Multiple Sclerosis: From the Multicenter INNI Dataset Towards the Clinical Application

Thalamic atrophy has been found since the earliest phases of multiple sclerosis (MS). However, this measure is not included in clinical practice, due to the time-consuming manual segmentation and technical challenges. By comparing thalamic segmentations from three available automatic methods in a multicenter dataset, we found that the inclusion of fractional anisotropy maps facilitated the automatic identification of thalamic boundaries increasing robustness of the results. In particular, the multimodal approach (FSL-MIST) showed a better capability to detect small longitudinal variations of thalamic volumes in MS patients and a better correlation with another relevant MRI measure such as the lesion volume.