R01AG067078

Model Based Deep Learning Framework for Ultra-High Resolution Multi-Contrast MRI

Sensitive imaging biomarkers are urgently needed for screening high-risk subjects, determining early disease progression, and assessing response to therapies in neurodegenerative disorders.

The atrophy of several brain regions is an established biomarker in AD, which strongly correlates with AD neuropathology. However, the accuracy of subfield volumes and cortical thickness estimated from current MRI methods is limited due to vulnerability to motion, low spatial resolution, low contrast between brain sub-structures, and dependence on image quality for current segmentation frameworks.

To address these limitations, short motion-compensated MRI protocols are needed to map the human brain at high spatial resolution with multiple contrasts, along with accurate and computationally efficient segmentation algorithms. These advancements are crucial for the early detection and management of subjects with neurodegenerative disorders.

In this study, 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 using several different inversion times on 7T. Additionally, we will develop segmentation algorithms that are robust to acceleration.

The key difference of this framework from current approaches, which rely on MRI data with 1 mm resolution, is the significant increase in spatial resolution to 0.2 mm, as well as the availability of multiple contrasts. This improvement is made possible 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), which enables the joint exploitation of 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 that are considerably less expensive than PET and do 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.

Rector & Visitors Of The University Of Virginia

TO ENCOURAGE BIOMEDICAL, SOCIAL, AND BEHAVIORAL RESEARCH AND RESEARCH TRAINING DIRECTED TOWARD GREATER UNDERSTANDING OF THE AGING PROCESS AND THE DISEASES, SPECIAL PROBLEMS, AND NEEDS OF PEOPLE AS THEY AGE. THE NATIONAL INSTITUTE ON AGING HAS ESTABLISHED PROGRAMS TO PURSUE THESE GOALS. THE DIVISION OF AGING BIOLOGY EMPHASIZES UNDERSTANDING THE BASIC BIOLOGICAL PROCESSES OF AGING. THE DIVISION OF GERIATRICS AND CLINICAL GERONTOLOGY SUPPORTS RESEARCH TO IMPROVE THE ABILITIES OF HEALTH CARE PRACTITIONERS TO RESPOND TO THE DISEASES AND OTHER CLINICAL PROBLEMS OF OLDER PEOPLE. THE DIVISION OF BEHAVIORAL AND SOCIAL RESEARCH SUPPORTS RESEARCH THAT WILL LEAD TO GREATER UNDERSTANDING OF THE SOCIAL, CULTURAL, ECONOMIC AND PSYCHOLOGICAL FACTORS THAT AFFECT BOTH THE PROCESS OF GROWING OLD AND THE PLACE OF OLDER PEOPLE IN SOCIETY. THE DIVISION OF NEUROSCIENCE FOSTERS RESEARCH CONCERNED WITH THE AGE-RELATED CHANGES IN THE NERVOUS SYSTEM AS WELL AS THE RELATED SENSORY, PERCEPTUAL, AND COGNITIVE PROCESSES ASSOCIATED WITH AGING AND HAS A SPECIAL EMPHASIS ON ALZHEIMER'S DISEASE. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.

93.866 - Aging Research

National Institute on Aging (NIA) [HHS - NIH]

Virginia United States

State-Wide

Change of Recipient Organization (Type 7 Parent Clinical Trial Optional) (PA-24-254)

Amendment Since initial award the total obligations have increased 371% from $727,486 to $3,428,569.