Method and system for quantitative renal assessment
AssigneeChildren's Hospital Los Angeles
InventorsRex Moats, Yang Tang, Priyank Sharma, Hollie Jackson
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Abstract
Method and system embodiments of the present invention employ computational analysis tools running on one or more computer systems to quantitatively analyze MRI data from patients in order to both assess various functional parameters and characteristics of a patient's kidney, as well as to provide an electronic display device interconnected with the one or more computer systems, and accessible visualization of the quantitative assessment to facilitate diagnosis of various types of kidney abnormalities and pathologies.
Claims11
A computer implemented method for quantitative-organ-assessment comprising:
- (a) obtaining a time series of MRI images in a subject comprising:
- (i) acquiring pre-contrast MRI images of the organ;
- (ii) introducing an MRI contrast-enhancing agent into the subject;
- and
- (iii) obtaining a time-series of MRI images;
- (b) storing the MRI images obtained in the absence and presence of an MRI contrast-enhancing substance as a dataset, wherein the dataset comprises intensities associated with voxels at each time point in the time series of MRI images;
- (c) partitioning voxels within the dataset into clusters, each cluster containing voxels with similar time-intensity curves by using a Gaussian-mixture-model on principle component space;
- (d) distinguishing the organ clusters from background clusters by using a knowledge-based framework comprising applying fuzzy logic based on organ specific standards;
- (e) distinguishing the cluster into different inner compartments of the organ by using a physiological spatial model comprising transformation from time-intensity space into the physiological space, wherein the transformation is performed by using the function:
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- to solve for the parameters P2, P3, P4 and P5;
- wherein P2 is related to the magnitude of baseline and peak signal, P3 is the approximate time of the maximum rate of increase, P4 denotes the slope of the enhancement and P5 describe the trends of excretion, for inner compartments recognition, and
- (f) computing functional characteristics and parameters of the organ from aggregate intensity-versus-time characteristics of the voxels within the clusters.
Dependencies are inferred from the claim text.