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US 12,579,651 B2Granted
Impeded diffusion fraction for quantitative imaging diagnostic assay
AssigneeThe Regents of the University of Michigan
InventorsDariya I. Malyarenko, Scott D. Swanson, Thomas L. Chenevert
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Abstract
Methods and systems are provided for analyzing diffusion weighted images (DWI) using impeded diffusion fraction models for quantitative imaging diagnostic assay of cancer, such as glandular tissue cancers. The Impeded diffusion fraction models are tissue and cancer independent and generate a single score representative of multi-compartment diffusion fractions occurring within each voxel of a DWI image.
Claims19
A computer-implemented method of analyzing diffusion weighted images, the computer-implemented method comprising:
- receiving, at one or more processors, diffusion weighted image (DWI) data corresponding to a sample of an imaged tissue and identifying within the DWI data a region of interest comprising one or more voxels, the region of interest spanning at least partially a tissue region within the sample;
- applying, using the one or more processors, the DWI data corresponding to the region of interest to an impeded diffusion fraction model and, from applying the impeded diffusion fraction model, determining an impeded diffusion fraction for each of the one or more voxels in the region of interest, the impeded diffusion fraction model being a multi-compartment model of water coordination by macromolecules agnostic to tissue compartment origin and applicable across multiple tissue compartments using a fixed rate for free diffusion and order of magnitude scaling constraints for vascular diffusion and coordinated diffusion;
- from the impeded diffusion fraction of the one or more voxels, identifying the presence and/or severity of a pathology in the imaged tissue;
- and
- generating, using the one or more processors and the identified presence and/or severity of the pathology in the imaged tissue, a pathology determination image indicating a location of the presence and/or the severity of the pathology within the region of interest.
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Dependencies are inferred from the claim text.