Sensitive imaging biomarkers are urgently needed for screening of high?risk subjects, determine early disease progression, and assess response to therapies in neurodegenerative disorders. The atrophy of several brain regions is an established biomarker in AD, which strongly correlates with AD neuropathology. The accuracy of subfield volumes and cortical thickness estimated from current MRI methods is limited because of the vulnerability to motion, low spatial resolution, low contrast between brain sub?structures, and dependence of current segmentation frameworks on image quality. Short motion?compensated MRI protocols to map the human brain at high spatial resolution with multiple contrasts, along with accurate and computationally efficient segmentation algorithms, are urgently needed tor early detection and management of subjects with neurodegenerative disorders. We propose to introduce a 15?minute motion?robust 3?D acquisition and reconstruction scheme to recover whole?brain MRI data with 0.2 mm isotropic resolution with several different inversion times on 7T, along with segmentation algorithms that are robust to acceleration. The key difference of this framework from current approaches, which rely on MRI data 1 mm resolution, is the quite significant increase in spatial resolution to 0.2 mm as well as the availability of multiple conteasts. This improvement is enabled by innovations in all areas of the data?processing pipeline, including acquisition, reconstruction, and analysis. These innovations are facilitated and integrated by the model based deep learning framework (MoDL); this framework facilitates the joint exploitation the available prior information, including motion and models for magnetization evolution, with convolutional neural network blocks that learn anatomical information from exemplar data. The successful completion of this framework will yield sensitive biomarkers, which will be considerably less expensive than PET and does not involve radiation exposure. As 7T clinical scanners become more common, this framework can emerge as a screening tool for high?risk subjects (e.g. APOE, PSEN mutations) and assess progression in patients with short follow?up duration.
Alzheimer?s disease (AD) is now a major public health concern with life expectancy at an all-time high. In US alone, the number of affected patients is expected to triple to 13.8 million by the year 2050. This proposal focuses on the development of an ultra-high resolution multicontrast MRI protocol, with the objective of improving the accuracy of brain atrophy rates in early AD subjects. The successful completion of this proposal will yield a biomarker that is sensitive to early brain changes in AD, which can facilitate early detection in high risk population, measure progression, and quantify the efficacy of brain sparing drugs.
