{"689483":{"#nid":"689483","#data":{"type":"event","title":"MS Defense by Khushi Shah","body":[{"value":"\u003Cp\u003EKhushi Shah\u003Cbr\u003EBME MS Thesis Defense Presentation\u003Cbr\u003E\u003Cstrong\u003EDate\u003C\/strong\u003E: 2026-04-14\u003Cbr\u003E\u003Cstrong\u003ETime\u003C\/strong\u003E: 9:00AM - 10:30AM\u003Cbr\u003E\u003Cstrong\u003ELocation \/ Meeting Link\u003C\/strong\u003E: Conference Room N657 HSRB II, Emory University, Atlanta, GA Zoom Link: \u003Ca href=\u0022https:\/\/emory.zoom.us\/j\/94212657259\u0022\u003Ehttps:\/\/emory.zoom.us\/j\/94212657259\u003C\/a\u003E\u003Cbr\u003E\u003Cbr\u003E\u003Cstrong\u003ECommittee Members:\u003C\/strong\u003E\u003Cbr\u003EDr. Anant Madabhushi (advisor); Dr. Laxmi Prasad Dasi; Dr. Hanjoong Jo; Dr. Puja Kiran Mehta\u003Cbr\u003E\u003Cbr\u003E\u003Cbr\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: Multi-Organ Fat quantification from Whole-Body MRI for longitudinal prediction of Major Adverse Cardiovascular Events (MACE)\u0026nbsp;\u003Cbr\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003Cbr\u003EIntroduction: Multi-organ fat quantification can improve longitudinal cardiovascular risk stratification by capturing tissue-level metabolic heterogeneity beyond what conventional adiposity measures and clinical risk scores provide. In this work, we propose a population-scale radiomic framework to understand inter-organ fat dynamics using whole-body MRI for cardiovascular diseases. Methods: We integrate automated deep learning organ segmentation to extract voxel-wise signals across five organs- heart, liver, pancreas, kidneys, and intestine. Fat fraction maps were partitioned into population-anchored density-stratified subregions, from which morphological and intensity radiomic features were derived per subject and reduced via LASSO bootstrap stability selection. Organ-specific and multi-organ Cox Proportional Hazards models were trained on a geographically stratified split and evaluated for 10-year incident MACE prediction, benchmarked against conventional adiposity measures and established clinical risk factors. Results: Combined multi-organ risk score yielded the highest discrimination for 10-year MACE (C-index = 0.636; HR = 1.76, p \u0026lt; 0.001), exceeding the performance of individual organ models (heart C-index= 0.635, pancreas C-index= 0.605, liver C-index= 0.598, kidney C-index= 0.590, intestine C-index= 0.585) and consistently outperforming visceral adipose tissue alone (C-index= 0.602) and subcutaneous fat alone (C-index= 0.50) model. Integrated model (inter-organ fat + clinical model), improved discrimination to C-index= 0.772 (\u0394C-index= +0.7%), over the clinical alone model. The dominant selected features across organs were morphological and the fat subregion volume. These results establish that shape-based characterization of focal high-density ectopic fat deposits, rather than scalar fat fraction, is the primary imaging determinant of cardiovascular risk, and motivate integration of multi-organ fat radiomics into population imaging pipelines for personalized preventive cardiology.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EMulti-Organ Fat quantification from Whole-Body MRI for longitudinal prediction of Major Adverse Cardiovascular Events (MACE)\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Multi-Organ Fat quantification from Whole-Body MRI for longitudinal prediction of Major Adverse Cardiovascular Events (MACE) "}],"uid":"27707","created_gmt":"2026-04-06 19:31:01","changed_gmt":"2026-04-06 19:31:41","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-04-14T09:00:00-04:00","event_time_end":"2026-04-14T10:30:00-04:00","event_time_end_last":"2026-04-14T10:30:00-04:00","gmt_time_start":"2026-04-14 13:00:00","gmt_time_end":"2026-04-14 14:30:00","gmt_time_end_last":"2026-04-14 14:30:00","rrule":null,"timezone":"America\/New_York"},"location":"Conference Room N657 HSRB II, Emory University, Atlanta, GA ","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"111531","name":"ms defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}