UNLABELLED: The anatomy of the thalamus and its connectivity with surrounding areas are known. Localized metabolic activities at the thalamic substructural level have not been measured in vivo in human brains because of limited resolution and contrast. METHODS: The energy metabolism and fine anatomic structures of the thalamus were measured simultaneously in 5 healthy subjects using a PET/MRI fusion imaging system. Measured metabolism in individual thalamic nuclei was quantified by corresponding PET/MRI images. RESULTS: Substructures of the thalamus were clearly distinguished in 7.0-T MRI images, and the corresponding metabolic activities measured by PET were integrated by the PET/MRI system. The medial dorsal thalamic nucleus consistently showed the highest glucose uptake among the thalamic nuclei. CONCLUSION: These results demonstrate that substructure-specific metabolic activities in the thalamus can be measured with a PET/MRI system consisting of an ultra-high-resolution PET component and an ultra-high-field MRI component.
UNLABELLED: The anatomy of the thalamus and its connectivity with surrounding areas are known. Localized metabolic activities at the thalamic substructural level have not been measured in vivo in human brains because of limited resolution and contrast. METHODS: The energy metabolism and fine anatomic structures of the thalamus were measured simultaneously in 5 healthy subjects using a PET/MRI fusion imaging system. Measured metabolism in individual thalamic nuclei was quantified by corresponding PET/MRI images. RESULTS: Substructures of the thalamus were clearly distinguished in 7.0-T MRI images, and the corresponding metabolic activities measured by PET were integrated by the PET/MRI system. The medial dorsal thalamic nucleus consistently showed the highest glucose uptake among the thalamic nuclei. CONCLUSION: These results demonstrate that substructure-specific metabolic activities in the thalamus can be measured with a PET/MRI system consisting of an ultra-high-resolution PET component and an ultra-high-field MRI component.
Authors: Natalia Chechko; Sebastian Vocke; Ute Habel; Timur Toygar; Lisa Kuckartz; Mark Berthold-Losleben; Zacharias G Laoutidis; Stelios Orfanos; Annette Wassenberg; Wölfram Karges; Frank Schneider; Nils Kohn Journal: Hum Brain Mapp Date: 2014-11-12 Impact factor: 5.038
Authors: Zang Hee Cho; Young Don Son; Eun Jung Choi; Hang Keun Kim; Jeong Hee Kim; Sang Yoon Lee; Seiji Ogawa; Young Bo Kim Journal: MAGMA Date: 2012-08-03 Impact factor: 2.310
Authors: Dima A Hammoud; Sanhita Sinharay; Sally Steinbach; Paul G Wakim; Katrina Geannopoulos; Katherine Traino; Amit K Dey; Edmund Tramont; Stanley I Rapoport; Joseph Snow; Nehal N Mehta; Bryan R Smith; Avindra Nath Journal: Neurology Date: 2018-09-26 Impact factor: 9.910