{"doi":"10.1117/12.2611587","title":"Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features","abstract":null,"journal":"Medical Imaging 2022: Computer-Aided Diagnosis","year":2022,"id":675949,"datarank":0.4752623790148025,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"self_citation_contribution":0.32958368660043297,"citation_network_contribution":0.14567869241436956,"self_endowment_contribution":0.32958368660043297,"citer_contribution":0.14567869241436956,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":7,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":794099,"name":"Maysam Shahedi","orcid":"0000-0001-9108-2010","position":1,"is_corresponding":false},{"id":270948,"name":"James D. Dormer","orcid":"0000-0002-0719-6697","position":2,"is_corresponding":false},{"id":1766164,"name":"Quyen N. Do","orcid":null,"position":3,"is_corresponding":false},{"id":480786,"name":"Yin Xi","orcid":"0000-0001-9743-3010","position":4,"is_corresponding":false},{"id":480787,"name":"Matthew A. Lewis","orcid":"0000-0002-3714-9031","position":5,"is_corresponding":false},{"id":802710,"name":"Christina L. Herrera","orcid":"0000-0002-6484-9850","position":6,"is_corresponding":false},{"id":544831,"name":"Catherine Y. Spong","orcid":null,"position":7,"is_corresponding":false},{"id":459563,"name":"Ananth J. Madhuranthakam","orcid":"0000-0002-5524-7962","position":8,"is_corresponding":false},{"id":802713,"name":"Diane M. Twickler","orcid":"0000-0001-5192-9782","position":9,"is_corresponding":false},{"id":254797,"name":"Baowei Fei","orcid":"0000-0002-9123-9484","position":10,"is_corresponding":false},{"id":1766163,"name":"Ka'Toria Leitch","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features","abstract":"In women with placenta accreta spectrum (PAS), patient management may involve cesarean hysterectomy at delivery. Magnetic resonance imaging (MRI) has been used for further evaluation of PAS and surgical planning. This work tackles two prediction problems: predicting presence of PAS and predicting hysterectomy using MR images of pregnant patients. First, we extracted approximately 2,500 radiomic features from MR images with two regions of interest: the placenta and the uterus. In addition to analyzing two regions of interest, we dilated the placenta and uterus masks by 5, 10, 15, and 20 mm to gain insights from the myometrium, where the uterus and placenta overlap in the case of PAS. This study cohort includes 241 pregnant women. Of these women, 89 underwent hysterectomy while 152 did not; 141 with suspected PAS, and 100 without suspected PAS. We obtained an accuracy of 0.88 for predicting hysterectomy and an accuracy of 0.92 for classifying suspected PAS. The radiomic analysis tool is further validated, it can be useful for aiding clinicians in decision making on the care of pregnant women.","is_dataset_classified":null,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"36844110","pmcid":"PMC9956938","openalex_id":"https://openalex.org/W4220973488","authors":[],"funders":[{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL140325","title":null},{"funder_name":"NICHD NIH HHS","grant_id":"K25 HD104004","title":null},{"funder_name":"NCI NIH HHS","grant_id":"R01 CA156775","title":null},{"funder_name":"NCI NIH HHS","grant_id":"R01 CA204254","title":null},{"funder_name":"NCI NIH HHS","grant_id":"R21 CA231911","title":null},{"funder_name":"National Institutes of Health","grant_id":"7R01CA156775-07","title":"MOLECULAR IMAGING DIRECTED, 3D ULTRASOUND-GUIDED, BIOPSY SYSTEM"},{"funder_name":"National Institutes of Health","grant_id":"5R01HL140325-04","title":"Image-guided Intravascular Robotic System for Mitral Valve Repair and Implants"},{"funder_name":"National Institutes of Health","grant_id":"5R21CA231911-02","title":"STAN-CT: Standardization and Normalization of CT images for Lung Cancer Patients"}],"total_grants":8,"fwci":15.0429,"citation_percentile":0.98653611,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":2},{"year":2025,"count":4},{"year":2026,"count":1}],"oa_status":"green","license":null,"oa_locations":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9956938","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9956938","host_type":"repository"},{"url":"https://doi.org/10.1117/12.2611587","host_type":"conference"},{"url":"https://pubmed.ncbi.nlm.nih.gov/36844110","host_type":"repository"}],"fields_of_study":["Maternal and fetal healthcare","Ultrasound in Clinical Applications","Uterine Myomas and Treatments","03 medical and health sciences","0302 clinical medicine"],"mesh_terms":[],"keywords":["Placenta accreta","Hysterectomy","Medicine","Placenta","Magnetic resonance imaging","Obstetrics","Myometrium","Uterus","Radiology","Pregnancy","Gynecology","Fetus","Internal medicine","Pregnant","Magnetic resonance imaging (MRI)","Machine Learning","Radiomics","Placenta Accreta Spectrum (Pas)"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-17T01:54:11.273163Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}