Systems and Methods for Generating Biomarkers Based on Multivariate MRI and Multimodality Classifiers for Disorder Diagnosis

Abstract

In some embodiments, the systems and methods of the disclosure can efficiently and accurately classify neurodegenerative disorder(s) and/or movement disorder(s) of a subject (e.g., a patient) using at least quantitative features associated with one or more regions of interest determined from one or more sets of image data of the subjects brain. The method may include processing one or more sets of MRI image data of the subjects brain to extract one or more quantitative features for one or more regions. The one or more quantitative features may include a first quantitative and a second quantitative feature. The method may further include classifying at least the one or more quantitative features into one or more classes associated with neurodegenerative dementia disorder, neurodegenerative movement disorder, non-neurodegenerative movement disorder and/or heathy control. The method may include generating a report including a classification of at least the one or more quantitative features.

1 . A computer-implemented method for classifying neurodegenerative disorder(s) and/or movement disorder(s) of a subject, the method comprising:
 receiving subject data of a subject, the subject data including one or more sets of MRI image data of a brain of the subject;   processing one or more sets of MRI image data to extract one or more quantitative features for one or more regions, the one or more quantitative features for the one or more regions includes a first quantitative feature for the one or more regions and a second quantitative feature for the one or more regions;   classifying at least the one or more quantitative features for the one or more regions into one or more classes associated with neurodegenerative dementia disorder, neurodegenerative movement disorder, non-neurodegenerative movement disorder, and/or heathy control; and   generating a report including a classification of at least the one or more quantitative features.   
     
     
         2 . The method according to  claim 1 , wherein the one or more classes associated with the neurodegenerative dementia disorder includes a parkinsonian class and a non-parkinsonian class, and/or the one or more classes associated with the neurodegenerative movement disorder include a parkinsonian class. 
     
     
         3 . The method according to  claim 2 , wherein:
 the parkinsonian class for the neurodegenerative dementia disorder includes one or more parkinsonian neurodegenerative dementia subclasses; and   the one or more parkinsonian neurodegenerative dementia subclasses includes Parkinson's disease dementia (PDD), dementia with Lewy bodies (DLB), and/or one or more other atypical parkinsonism dementia disorder subclasses.   
     
     
         4 . The method according to  claim 3 , wherein the other atypical parkinsonism dementia disorder subclass includes multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and/or corticobasal degeneration (CBD). 
     
     
         5 . The method according to  claim 1 , wherein:
 the one or more classes for the non-neurodegenerative movement disorder includes one or more non-neurodegenerative movement disorder subclasses; and   the one or more non-neurodegenerative movement disorder subclasses includes psychogenic, essential tremor, and drug-induced.   
     
     
         6 . The method according to  claim 2 , wherein:
 the parkinsonian class for the neurogenerative movement disorder includes one or more parkinsonian movement disorder subclasses; and   the one or more parkinsonian movement disorder subclasses includes Parkinson's Disease (PD) and/or one or more other atypical parkinsonism movement disorder subclasses.   
     
     
         7 . The method according to  claim 6 , wherein the one or more other atypical parkinsonism movement disorder subclasses includes MSA, PSP, and/or CBD. 
     
     
         8 . The method according to  claim 1 , wherein the MRI image data is acquired by one or more stored protocols. 
     
     
         9 . The method according to  claim 1 , wherein the one or more quantitative features include NM-MRI feature(s), R2* feature(s), QSM feature(s), diffusion MRI feature(s), and/or other sequence feature(s). 
     
     
         10 . The method according to  claim 9 , wherein the one or more regions includes one or more of the following: substantia nigra pars compacta (SNc), locus coeruleus (LC), subthalamic nucleus, red nucleus, globus pallidus (total, pars interna and/or pars externa), putamen (lateral, medial, and/or total), caudate, cerebellar dentate nucleus, substantia nigra pars reticulata, middle cerebellar peduncle, superior cerebellar peduncle, hippocampus (one or more individual subfields and/or total), entorhinal cortex, occipital cortex (primary visual cortext, visual association cortext, and/or total), parietal cortex, cingulate gyms, parahippocampal gyms, and/or frontal cortext (M1, premotor, supplementary motor area, Broca's area, prefrontal, orbitofrontal, inferolateral frontal, and/or total). 
     
     
         11 . The method according to  claim 1 , wherein the first quantitative feature and the second quantitative feature are based on different imaging protocols. 
     
     
         12 . The method according to  claim 1 , wherein first quantitative feature and the second quantitative feature are determined for different regions of the brain. 
     
     
         13 . The method according to  claim 1 , wherein:
 the subject data includes additional subject data that is different from the one or more sets of medical image data; and   the classifying is also based on one or more features extracted from the additional subject data.   
     
     
         14 . The method according to  claim 1 , wherein:
 the subject data includes clinical data;   the processing including processing the clinical data to determine one or more clinical features; and   the classifying includes classifying the one or more clinical features and the one or more quantitative features into the one or more classes.   
     
     
         15 . A system for classifying neurodegenerative disorder(s) and/or movement disorder(s) of a subject, the system comprising:
 at least one processor; and   a memory, wherein the processor is configured to cause:
 processing one or more sets of MRI image data of a brain of the subject to extract one or more quantitative features for one or more regions, the one or more quantitative features for the one or more regions includes a first quantitative feature for the one or more regions and a second quantitative feature for the one or more regions; 
 classifying at least the one or more quantitative features for the one or more regions into one or more classes associated with neurodegenerative dementia disorder, neurodegenerative movement disorder, non-neurogenerative movement disorder, and/or heathy control; and 
 generating a report including a classification of at least the one or more quantitative features. 
   
     
     
         16 . The system according to  claim 15 , wherein the one or more quantitative features include NM-MRI feature(s), R2* feature(s), QSM feature(s), diffusion MRI feature(s), and/or other sequence feature(s). 
     
     
         17 . The system according to  claim 15 , wherein the one or more classes associated with the neurodegenerative dementia disorder includes a parkinsonian class and a non-parkinsonian class, and/or the one or more classes associated with the neurodegenerative movement disorder include a parkinsonian class. 
     
     
         18 . The system according to  claim 17 , wherein:
 the parkinsonian class for the neurodegenerative dementia disorder includes one or more parkinsonian neurodegenerative dementia subclasses; and   the one or more parkinsonian neurodegenerative dementia subclasses includes Parkinson's disease dementia (PDD), dementia with Lewy bodies (DLB), and/or one or more other atypical parkinsonism dementia disorder subclasses.   
     
     
         19 . The system according to  claim 18 , wherein the one or more other atypical parkinsonism dementia disorder subclasses includes multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and/or corticobasal degeneration (CBD). 
     
     
         20 . The system according to  claim 16 , wherein the one or more regions includes one or more of the following: substantia nigra pars compacta (SNc), locus coeruleus (LC), subthalamic nucleus, red nucleus, globus pallidus (total, pars interna and/or pars externa), putamen (lateral, medial, and/or total), caudate, cerebellar dentate nucleus, substantia nigra pars reticulata, middle cerebellar peduncle, superior cerebellar peduncle, hippocampus (one or more individual subfields and/or total), entorhinal cortex, occipital cortex (primary visual cortext, visual association cortext, and/or total), parietal cortex, cingulate gyms, parahippocampal gyms, and/or frontal cortext (M1, premotor, supplementary motor area, Broca's area, prefrontal, orbitofrontal, inferolateral frontal, and/or total).