Network-based functional imaging output for evaluating multiple sclerosis
AssigneesBoard of Regents, The University of Texas System, Texas State University
InventorsFlorence Yi Yi Ling Chiang, Peter T. Fox, Rebecca S. Romero, Larry Price
Life of this patent
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Abstract
Provided here are non-invasive methods for evaluating functional connectivity patterns in localized brain regions of a patient involving application of a MS-specific functional meta-analytic connectivity model in resting-state functional magnetic resonance imaging (rsfMRI) data to provide patients with appropriate medical care in response to output from the model.
Claims19
A method for diagnosing and addressing multiple sclerosis (MS), the method comprising:
- acquiring an input including functional MRI (rsfMRI) data, of a brain of a subject;
- preprocessing the input via one or more of motion correction, B0 warping, slice timing correction, and spatial smoothing to thereby form a preprocessed input including gradient-echo fieldmap data of the rsfMRI data or T1-weighted data;
- applying the preprocessed input to an atrophy-based functional network (AFN) model, the AFN model comprising nodes defined by regions of grey matter atrophy in MS, and edges defined by healthy functional connectivity involving the nodes of the regions of grey matter atrophy in MS;
- computing, by a processor using the AFN model, an output based on the preprocessed input, the output including network-based functional imaging output in MS (NETFIO-MS) indices indicating a progression of MS;
- and
- based on the output, providing a diagnosis of MS in response to presence of altered functional connectivity involving localized brain regions in the subject based on the application of the preprocessed input to the AFN model.
A system to select a treatment regimen for diagnosing and addressing multiple sclerosis (MS) of a subject, the system comprising:
- a magnetic resonance imaging (MRI) device to provide an input including resting-state functional MRI (rsfMRI) data, of a brain of a subject;
- and
- a Network-based Functional Imaging Output in Multiple Sclerosis (NETFIO-MS) device connected to and in signal communication with the MRI device, wherein the NETFIO-MS device is configured to:
- receive the input from the MRI device,
- preprocess the input via one or more of motion correction, B0 warping, slice timing correction, and spatial smoothing to thereby form a preprocessed input including one or more of gradient-echo fieldmap data of the rsfMRI data and T1-weighted data,
- apply the input to an atrophy-based functional network (AFN) model, the AFN model comprising nodes defined by regions of grey matter atrophy in MS, and edges defined by healthy functional connectivity involving the nodes of the regions of grey matter atrophy in MS,
- based on application of the preprocessed input to the AFN model, compute, by a processor of the NETFIO-MS device, an output including metrics of functional connectivity, the metrics of functional connectivity indicating diagnosis of MS in a subject and including NETFIO-MS indices indicating a progression of MS in the subject,
- determine a treatment regimen or treatment effectiveness corresponding to the output for the subject, and
- transmit the output and the treatment regimen or the treatment effectiveness to a user.
A non-transitory machine-readable storage medium storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to:
- in response to receipt of an input including resting-state functional MRI (rsfMRI) data preprocess the input to produce a preprocessed input include gradient-echo fieldmap data of the rsfMRI data and T1-weighted data, of a brain of a subject;
- apply the preprocessed input to an atrophy-based functional network (AFN) model to produce an output, wherein the AFN model comprises nodes defined by regions of grey matter atrophy in MS, and edges defined by healthy functional connectivity involving the nodes of the regions of grey matter atrophy in MS;
- and wherein the output includes metrics of functional connectivity and NETFIO-MS indices indicating a progression of MS in the subject;
- in response to the output produced by application of the input to the AFN model, determine whether the subject exhibits MS and duration of MS in the subject;
- in response to a determination that the subject exhibits MS, determine a treatment regimen or treatment effectiveness based on the duration of MS in the subject;
- and
- transmit the treatment regimen or the treatment effectiveness to a user.
Dependencies are inferred from the claim text.