  A cascaded multi-planar scheme with a modified residual U-Net architecture
was used to segment thalamic nuclei on conventional and white-matter-nulled
(WMn) magnetization prepared rapid gradient echo (MPRAGE) data. A single
network was optimized to work with images from healthy controls and patients
with multiple sclerosis (MS) and essential tremor (ET), acquired at both 3T and
7T field strengths. Dice similarity coefficient and volume similarity index
(VSI) were used to evaluate performance. Clinical utility was demonstrated by
applying this method to study the effect of MS on thalamic nuclei atrophy.
Segmentation of each thalamus into twelve nuclei was achieved in under a
minute. For 7T WMn-MPRAGE, the proposed method outperforms current
state-of-the-art on patients with ET with statistically significant
improvements in Dice for five nuclei (increase in the range of 0.05-0.18) and
VSI for four nuclei (increase in the range of 0.05-0.19), while performing
comparably for healthy and MS subjects. Dice and VSI achieved using 7T
WMn-MPRAGE data are comparable to those using 3T WMn-MPRAGE data. For
conventional MPRAGE, the proposed method shows a statistically significant Dice
improvement in the range of 0.14-0.63 over FreeSurfer for all nuclei and
disease types. Effect of noise on network performance shows robustness to
images with SNR as low as half the baseline SNR. Atrophy of four thalamic
nuclei and whole thalamus was observed for MS patients compared to healthy
control subjects, after controlling for the effect of parallel imaging,
intracranial volume, gender, and age (p<0.004). The proposed segmentation
method is fast, accurate, performs well across disease types and field
strengths, and shows great potential for improving our understanding of
thalamic nuclei involvement in neurological diseases.
