@inproceedings{
 title = {Identifying radiomic features associated with disease activity, patient outcomes, and serum phenotypes in pediatric Crohn's disease via MRI},
 type = {inproceedings},
 year = {2022},
 keywords = {Crohn's disease,Radiomics,prediction,prognosis,serum markers,small bowel},
 volume = {12034},
 id = {ada99740-2e0d-3a24-a15a-086490cca601},
 created = {2023-10-25T08:56:38.153Z},
 file_attached = {false},
 profile_id = {eaba325f-653b-3ee2-b960-0abd5146933e},
 last_modified = {2023-10-25T08:56:38.153Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {true},
 abstract = {Pediatric Crohn's disease (pCD) is a chronic relapsing-remitting inflammatory disease of the gastrointestinal tract, where there is a significant need for non-invasive comprehensive markers to accurately target clinical interventions. While Magnetic Resonance Enterography (MRE) is often used to localize pCD in vivo, it is still limited in predicting treatment response and capturing pCD phenotypes. The goal of this study was to identify radiomic features on baseline MRE associated with disease activity and treatment outcomes in pCD, as well as investigate potential associations of radiomics with serum-based pCD subtypes. Baseline MRE scans were acquired from 45 pediatric subjects (including healthy controls and pCD patients) where the latter was further sub-grouped into responders (stable after treatment) and non-responders (required surgery or had active disease 2+ years after treatment initiation). Radiomic features were extracted from the terminal ileum on a per-voxel basis from MRE and evaluated via a multi-stage feature selection scheme for identifying disease presence and patient outcomes separately. A Random Forest (RF) classifier achieved an area under the ROC curve (AUC) of 0.83 in distinguishing diseased patients from healthy subjects and an AUC of 0.85 in distinguishing nonresponders from responders; in leave-one-out cross-validation. Top-ranked Gabor and Laws radiomic features were found to be significantly correlated with serum pCD phenotypes including anemia, inflammation risk, vitamin deficiency, and immune activity. Radiomic features may therefore offer the ability to better characterize pCD phenotypes and predict patient outcomes, which could then be effectively treated via targeted interventions.},
 bibtype = {inproceedings},
 author = {Chirra, P. and Muchhala, A. and Amann, K. and Krishnan, K. and Kurowski, J.A. and Viswanath, S.E.},
 doi = {10.1117/12.2613599},
 booktitle = {Progress in Biomedical Optics and Imaging - Proceedings of SPIE}
}

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While Magnetic Resonance Enterography (MRE) is often used to localize pCD in vivo, it is still limited in predicting treatment response and capturing pCD phenotypes. The goal of this study was to identify radiomic features on baseline MRE associated with disease activity and treatment outcomes in pCD, as well as investigate potential associations of radiomics with serum-based pCD subtypes. Baseline MRE scans were acquired from 45 pediatric subjects (including healthy controls and pCD patients) where the latter was further sub-grouped into responders (stable after treatment) and non-responders (required surgery or had active disease 2+ years after treatment initiation). Radiomic features were extracted from the terminal ileum on a per-voxel basis from MRE and evaluated via a multi-stage feature selection scheme for identifying disease presence and patient outcomes separately. A Random Forest (RF) classifier achieved an area under the ROC curve (AUC) of 0.83 in distinguishing diseased patients from healthy subjects and an AUC of 0.85 in distinguishing nonresponders from responders; in leave-one-out cross-validation. Top-ranked Gabor and Laws radiomic features were found to be significantly correlated with serum pCD phenotypes including anemia, inflammation risk, vitamin deficiency, and immune activity. Radiomic features may therefore offer the ability to better characterize pCD phenotypes and predict patient outcomes, which could then be effectively treated via targeted interventions.","bibtype":"inproceedings","author":"Chirra, P. and Muchhala, A. and Amann, K. and Krishnan, K. and Kurowski, J.A. and Viswanath, S.E.","doi":"10.1117/12.2613599","booktitle":"Progress in Biomedical Optics and Imaging - Proceedings of SPIE","bibtex":"@inproceedings{\n title = {Identifying radiomic features associated with disease activity, patient outcomes, and serum phenotypes in pediatric Crohn's disease via MRI},\n type = {inproceedings},\n year = {2022},\n keywords = {Crohn's disease,Radiomics,prediction,prognosis,serum markers,small bowel},\n volume = {12034},\n id = {ada99740-2e0d-3a24-a15a-086490cca601},\n created = {2023-10-25T08:56:38.153Z},\n file_attached = {false},\n profile_id = {eaba325f-653b-3ee2-b960-0abd5146933e},\n last_modified = {2023-10-25T08:56:38.153Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {true},\n abstract = {Pediatric Crohn's disease (pCD) is a chronic relapsing-remitting inflammatory disease of the gastrointestinal tract, where there is a significant need for non-invasive comprehensive markers to accurately target clinical interventions. While Magnetic Resonance Enterography (MRE) is often used to localize pCD in vivo, it is still limited in predicting treatment response and capturing pCD phenotypes. The goal of this study was to identify radiomic features on baseline MRE associated with disease activity and treatment outcomes in pCD, as well as investigate potential associations of radiomics with serum-based pCD subtypes. Baseline MRE scans were acquired from 45 pediatric subjects (including healthy controls and pCD patients) where the latter was further sub-grouped into responders (stable after treatment) and non-responders (required surgery or had active disease 2+ years after treatment initiation). Radiomic features were extracted from the terminal ileum on a per-voxel basis from MRE and evaluated via a multi-stage feature selection scheme for identifying disease presence and patient outcomes separately. A Random Forest (RF) classifier achieved an area under the ROC curve (AUC) of 0.83 in distinguishing diseased patients from healthy subjects and an AUC of 0.85 in distinguishing nonresponders from responders; in leave-one-out cross-validation. Top-ranked Gabor and Laws radiomic features were found to be significantly correlated with serum pCD phenotypes including anemia, inflammation risk, vitamin deficiency, and immune activity. Radiomic features may therefore offer the ability to better characterize pCD phenotypes and predict patient outcomes, which could then be effectively treated via targeted interventions.},\n bibtype = {inproceedings},\n author = {Chirra, P. and Muchhala, A. and Amann, K. and Krishnan, K. and Kurowski, J.A. and Viswanath, S.E.},\n doi = {10.1117/12.2613599},\n booktitle = {Progress in Biomedical Optics and Imaging - Proceedings of SPIE}\n}","author_short":["Chirra, P.","Muchhala, A.","Amann, K.","Krishnan, K.","Kurowski, J.","Viswanath, S."],"biburl":"https://bibbase.org/service/mendeley/eaba325f-653b-3ee2-b960-0abd5146933e","bibbaseid":"chirra-muchhala-amann-krishnan-kurowski-viswanath-identifyingradiomicfeaturesassociatedwithdiseaseactivitypatientoutcomesandserumphenotypesinpediatriccrohnsdiseaseviamri-2022","role":"author","urls":{},"keyword":["Crohn's disease","Radiomics","prediction","prognosis","serum markers","small bowel"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/service/mendeley/eaba325f-653b-3ee2-b960-0abd5146933e","dataSources":["MFTLffJ4nzQec8k8n","ya2CyA73rpZseyrZ8","2252seNhipfTmjEBQ"],"keywords":["crohn's disease","radiomics","prediction","prognosis","serum markers","small bowel"],"search_terms":["identifying","radiomic","features","associated","disease","activity","patient","outcomes","serum","phenotypes","pediatric","crohn","disease","via","mri","chirra","muchhala","amann","krishnan","kurowski","viswanath"],"title":"Identifying radiomic features associated with disease activity, patient outcomes, and serum phenotypes in pediatric Crohn's disease via MRI","year":2022}