Abstract: A system for assessing cancer includes a memory configured to store one or more images of tissue of a patient, where the one or more images originate from a magnetic resonance imaging (MRI) machine. The system also includes a processor operatively coupled to the memory and configured to determine a composition of the tissue. The processor is also configured to determine, based at least in part on the composition of the tissue, an apparent diffusion constant of the tissue. The processor is also configured to identify a region of cancer based at least in part on the apparent diffusion constant. The processor is further configured to generate a map that identifies the region of cancer in the tissue.

Abstract: Disclosed are approaches to non-invasively characterize a tumor or other lesion in a region of interest (ROI) based on various analyses of magnetic resonance imaging (MRI) data. The MRI data may correspond to ultrafast dynamic contrast enhanced MRI (DCE-MRI) and high spatial resolution DCE-MRI scans, and diffusion-weighted MRI (DW-MRI) scans of the ROI. Vasculature metrics may be determined, and tumor-associated blood flow velocity and/or tumor interstitial pressure may be obtained using the vasculature metrics as inputs to a computational fluid dynamics model. A combination of morphological vascular metrics and functional vascular metrics may be used to characterize the tumor. Malignancy, aggressiveness, treatment response, and other features of tumors or other lesions, in the breast or other regions of a patient, may be characterized through disclosed analyses of MRI data.

Abstract: Disclosed are approaches to non-invasively characterize a tumor or other lesion in a region of interest (ROI) based on various analyses of magnetic resonance imaging (MRI) data. The MRI data may correspond to ultrafast dynamic contrast enhanced MRI (DCE-MRI) and high spatial resolution DCE-MRI scans, and diffusion-weighted MRI (DW-MRI) scans of the ROI. Vasculature metrics may be determined, and tumor-associated blood flow velocity and/or tumor interstitial pressure may be obtained using the vasculature metrics as inputs to a computational fluid dynamics model. A combination of morphological vascular metrics and functional vascular metrics may be used to characterize the tumor. Malignancy, aggressiveness, treatment response, and other features of tumors or other lesions, in the breast or other regions of a patient, may be characterized through disclosed analyses of MRI data.

Abstract: A non-transitory storage medium stores instructions readable and executable by at least one electronic processor to perform an imaging method). The method includes: obtaining multi-parametric magnetic resonance (MR) imaging data parameterized by a diffusion weighting or perfusion weighting parameter and a magnetization relaxation parameter for a region of interest (ROI) of a patient; determining volume fraction maps of the ROI for each of a plurality of tissue types from the multi-parametric MR imaging data; and controlling a display device to display a tissue composition map comprising or generated from the determined volume fraction maps.

Abstract: A diagnostic system to analyze imaging data includes a memory configured to store hybrid imaging data of a tissue sample. The system also includes a processor operatively coupled to the memory and configured to generate a four quadrant plot based on the hybrid imaging data. Each point in the four quadrant plot corresponds to an image voxel of the tissue sample. The processor is also configured to determine one or more angle values and one or more distance values for image voxels in the four quadrant plot. The processor is further configured to identify one or more characteristics of the tissue sample based at least in part on the one or more angle values and the one or more distance values. The processor is further configured to perform a matrix analysis of the data, which can be used to identify the one or more characteristics of the tissue sample.

Abstract: A non-transitory storage medium stores instructions readable and executable by at least one electronic processor (20) to perform an imaging method (100). The method includes: obtaining multi-parametric magnetic resonance (MR) imaging data parameterized by a diffusion weighting or perfusion weighting parameter and a magnetization relaxation parameter for a region of interest (ROI) of a patient; determining volume fraction maps of the ROI for each of a plurality of tissue types from the multi-parametric MR imaging data; and controlling a display device (24) to display a tissue composition map comprising or generated from the determined volume fraction maps.