Fast automatic segmentation of thalamic nuclei from MP2RAGE acquisition at 7 Tesla

Purpose: Thalamic nuclei are largely invisible in conventional MRI due to poor contrast. Thalamus Optimized Multi-Atlas Segmentation (THOMAS) provides automatic segmentation of 12 thalamic nuclei using white-matter-nulled (WMn) MPRAGE sequence at 7T. Application of THOMAS to Magnetization Prepared 2 Rapid Gradient Echo (MP2RAGE) sequence acquired at 7T has been investigated in this study. Methods: 8 healthy volunteers and 5 pediatric-onset multiple sclerosis patients were recruited at the Children's Hospital of Philadelphia and scanned at Siemens 7T with WMn-MPRAGE and multi-echo MP2RAGE (ME-MP2RAGE) sequences. White-matter-nulled contrast was synthesized (MP2-SYN) from T1 maps from ME-MP2RAGE sequence. Thalamic nuclei were segmented using THOMAS joint label fusion algorithm from WMn-MPRAGE and MP2-SYN datasets. THOMAS pipeline was modified to use majority voting to segment the bias corrected MP2-UNI images. Thalamic nuclei from MP2-SYN and MP2-UNI images were evaluated against corresponding nuclei obtained from WMn-MPRAGE images using dice coefficients, volume similarity indices (VSI) and distance between centroids. Results: For MP2-SYN, dice > 0.85 and VSI > 0.95 was achieved for the 5 larger nuclei and dice > 0.6 and VSI > 0.7 was achieved for the 7 smaller nuclei. The dice and VSI were slightly higher whilst the distance between centroids were smaller for MP2-SYN compared to MP2-UNI, indicating improved performance using the synthesized WMn image. Discussion: THOMAS algorithm can successfully segment thalamic nuclei in routinely acquired bias-free MP2RAGE images with essentially equivalent quality when evaluated against WMn-MPRAGE, hence has wider applicability in studies focused on thalamic involvement in aging and disease.