{"id":"https://openalex.org/W4405812285","doi":"https://doi.org/10.1101/2024.12.23.24319468","title":"Radiomics with super-voxel segmentation improves HPV prediction accuracy significantly in oropharyngeal cancer","display_name":"Radiomics with super-voxel segmentation improves HPV prediction accuracy significantly in oropharyngeal cancer","publication_year":2024,"publication_date":"2024-12-26","ids":{"openalex":"https://openalex.org/W4405812285","doi":"https://doi.org/10.1101/2024.12.23.24319468"},"language":"en","primary_location":{"id":"doi:10.1101/2024.12.23.24319468","doi":"https://doi.org/10.1101/2024.12.23.24319468","is_oa":true,"landing_page_url":"https://doi.org/10.1101/2024.12.23.24319468","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2024/12/26/2024.12.23.24319468.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"volume":null,"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.medrxiv.org/content/medrxiv/early/2024/12/26/2024.12.23.24319468.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008004574","display_name":"Oya Altinok","orcid":"https://orcid.org/0000-0002-8713-0697","observed_orcids":["https://orcid.org/0000-0002-8713-0697"]},"institutions":[{"id":"https://openalex.org/I125454184","display_name":"Tekirda\u011f Nam\u0131k Kemal University","ror":"https://ror.org/01a0mk874","country_code":"TR","type":"education","lineage":["https://openalex.org/I125454184"]},{"id":"https://openalex.org/I3019308854","display_name":"Moffitt Cancer Center","ror":"https://ror.org/01xf75524","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I3019308854"]},{"id":"https://openalex.org/I4405392","display_name":"Bo\u011fazi\u00e7i University","ror":"https://ror.org/03z9tma90","country_code":"TR","type":"education","lineage":["https://openalex.org/I4405392"]}],"countries":["TR","US"],"is_corresponding":true,"raw_author_name":"Oya Altinok","raw_affiliation_strings":["Biomedical Engineering, Namik Kemal University, Tekirdag, Turkiye","Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA","Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkiye","H. Lee Moffitt Cancer Center & Research Institute,Tampa,FL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Biomedical Engineering, Namik Kemal University, Tekirdag, Turkiye","institution_ids":["https://openalex.org/I125454184"]},{"raw_affiliation_string":"Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA","institution_ids":["https://openalex.org/I3019308854"]},{"raw_affiliation_string":"Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkiye","institution_ids":["https://openalex.org/I4405392"]},{"raw_affiliation_string":"H. Lee Moffitt Cancer Center & Research Institute,Tampa,FL,USA","institution_ids":["https://openalex.org/I3019308854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066835564","display_name":"Matthew B. Schabath","orcid":"https://orcid.org/0000-0003-3241-3216","observed_orcids":["https://orcid.org/0000-0003-3241-3216"]},"institutions":[{"id":"https://openalex.org/I3019308854","display_name":"Moffitt Cancer Center","ror":"https://ror.org/01xf75524","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I3019308854"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew B. Schabath","raw_affiliation_strings":["Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA","H. Lee Moffitt Cancer Center & Research Institute,Tampa, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA","institution_ids":["https://openalex.org/I3019308854"]},{"raw_affiliation_string":"H. Lee Moffitt Cancer Center & Research Institute,Tampa, FL, USA","institution_ids":["https://openalex.org/I3019308854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081304792","display_name":"Albert G\u00fcveni\u015f","orcid":"https://orcid.org/0000-0003-0490-5184","observed_orcids":["https://orcid.org/0000-0003-0490-5184"]},"institutions":[{"id":"https://openalex.org/I4405392","display_name":"Bo\u011fazi\u00e7i University","ror":"https://ror.org/03z9tma90","country_code":"TR","type":"education","lineage":["https://openalex.org/I4405392"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Albert Guvenis","raw_affiliation_strings":["Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkiye","institution_ids":["https://openalex.org/I4405392"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008004574"],"corresponding_institution_ids":["https://openalex.org/I125454184","https://openalex.org/I3019308854","https://openalex.org/I4405392"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10307","display_name":"Head and Neck Cancer Studies","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2733","display_name":"Otorhinolaryngology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/oropharyngeal-cancer","display_name":"oropharyngeal cancer","score":0.9039999842643738},{"id":"https://openalex.org/keywords/intratumor-heterogeneity","display_name":"intratumoral heterogeneity","score":0.9279999732971191},{"id":"https://openalex.org/keywords/radiomics","display_name":"radiomics","score":0.878000020980835},{"id":"https://openalex.org/keywords/tumor-subregions","display_name":"tumor subregions","score":0.847000002861023},{"id":"https://openalex.org/keywords/heterogeneity-measures","display_name":"heterogeneity measures","score":0.6159999966621399},{"id":"https://openalex.org/keywords/hpv-positive-tumors","display_name":"HPV-positive tumors","score":0.5479999780654907}],"concepts":[{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.9097772240638733},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.657280683517456},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.538236677646637},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4962223172187805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39407867193222046},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.33684512972831726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.26431959867477417}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1101/2024.12.23.24319468","doi":"https://doi.org/10.1101/2024.12.23.24319468","is_oa":true,"landing_page_url":"https://doi.org/10.1101/2024.12.23.24319468","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2024/12/26/2024.12.23.24319468.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.1101/2024.12.23.24319468","doi":"https://doi.org/10.1101/2024.12.23.24319468","is_oa":true,"landing_page_url":"https://doi.org/10.1101/2024.12.23.24319468","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2024/12/26/2024.12.23.24319468.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.9789000153541565}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405812285.pdf","grobid_xml":"https://content.openalex.org/works/W4405812285.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1965170884","https://openalex.org/W1976078521","https://openalex.org/W2024046085","https://openalex.org/W2032518018","https://openalex.org/W2083927153","https://openalex.org/W2103004421","https://openalex.org/W2106199488","https://openalex.org/W2110664940","https://openalex.org/W2118246710","https://openalex.org/W2142159058","https://openalex.org/W2150575159","https://openalex.org/W2156490355","https://openalex.org/W2162871445","https://openalex.org/W2174661749","https://openalex.org/W2298622237","https://openalex.org/W2307308593","https://openalex.org/W2624753657","https://openalex.org/W2724559516","https://openalex.org/W2767988301","https://openalex.org/W2788079077","https://openalex.org/W2802241248","https://openalex.org/W2910993836","https://openalex.org/W2921444773","https://openalex.org/W2938964227","https://openalex.org/W2942293875","https://openalex.org/W2945153923","https://openalex.org/W2968769168","https://openalex.org/W2982326328","https://openalex.org/W2996127486","https://openalex.org/W3025878800","https://openalex.org/W3175084466","https://openalex.org/W4238521078","https://openalex.org/W4367316054","https://openalex.org/W4386646026","https://openalex.org/W4390574788","https://openalex.org/W6940760203"],"related_works":["https://openalex.org/W4390574788","https://openalex.org/W2996127486","https://openalex.org/W2766461702","https://openalex.org/W3092492831","https://openalex.org/W2788899656","https://openalex.org/W7148973341","https://openalex.org/W4389326659","https://openalex.org/W4286696755","https://openalex.org/W7116630765","https://openalex.org/W4285728609"],"abstract_inverted_index":{"Abstract":[0],"Human":[1],"papillomavirus":[2],"(HPV)":[3],"status":[4,94,176,220],"has":[5],"been":[6],"shown":[7],"to":[8,29,32,65,91,146,173,208,217],"be":[9,37],"prognostic":[10],"among":[11],"patients":[12,18,82],"with":[13,19,86,204],"oropharyngeal":[14,267],"cancer":[15,268],"(OPC);":[16],"Specifically,":[17],"HPV-positive":[20],"tumors":[21,34],"often":[22],"have":[23],"a":[24,66,96,101,185,201,272],"superior":[25],"prognosis":[26],"and":[27,59,100,142,189,212,237,251,263],"response":[28],"treatment":[30],"compared":[31,64],"HPV-negative":[33],"which":[35,243,270],"may":[36],"attributed":[38],"greater":[39],"tumor":[40,47,103,120,152,163,215,246],"heterogeneity.":[41,148],"This":[42],"study":[43],"assessed":[44],"if":[45],"analyzing":[46],"subregions":[48],"(i.e.,":[49],"habitats)":[50],"using":[51,144],"super-voxel":[52,97,264],"segmentation":[53,98,265],"can":[54],"effectively":[55],"capture":[56],"intratumor":[57],"heterogeneity":[58,261],"improve":[60],"predicting":[61],"HPV":[62,84,93,175,219,279],"positivity":[63],"conventional":[67],"whole-tumor":[68],"approach.":[69,104],"Using":[70],"publicly":[71],"available":[72],"data":[73],"from":[74,134,221],"The":[75,180,224],"Cancer":[76],"Imaging":[77],"Archive":[78],"(TCIA)":[79],"of":[80,111,231,249,259,277],"192":[81],"(85%":[83],"positive)":[85],"OPC,":[87],"we":[88],"utilized":[89,172],"radiomics":[90,222],"predict":[92,174,218],"comparing":[95],"approach":[99,227],"whole":[102,151,214,245],"For":[105,149],"the":[106,109,150,154,161,210,213,234,240,257,278],"subregion":[107,211],"approach,":[108,153],"number":[110],"supervoxels":[112],"(subregions)":[113],"generated":[114,159],"per":[115],"patient":[116],"varied":[117],"based":[118,137,199],"on":[119,138,200],"size":[121],"(mean":[122],"=":[123,127],"30":[124],"supervoxels/patient":[125],"[SD":[126],"10]).":[128],"18":[129,168],"radiomic":[130,156,169],"features":[131,157,170],"were":[132,158,171],"extracted":[133],"each":[135],"supervoxel":[136],"gray-level":[139],"frequency":[140],"distribution":[141],"aggregated":[143],"variance":[145],"summarize":[147],"same":[155],"across":[160],"entire":[162],"without":[164],"sub-segmentation.":[165],"As":[166],"such,":[167],"in":[177,233,239,266],"both":[178,209],"models.":[179],"dataset":[181],"was":[182,206],"divided":[183],"into":[184],"training":[186,235],"set":[187,193,236,242],"(70%)":[188],"an":[190,229],"independent":[191],"test":[192,241],"(30%).":[194],"An":[195],"optimizable":[196],"ensemble":[197],"model":[198],"decision":[202],"tree":[203],"GentleBoost":[205],"applied":[207],"models":[216],"features.":[223],"proposed":[225],"super-voxel-based":[226],"yielded":[228],"AUC":[230],"0.94":[232],"0.91":[238],"outperformed":[244],"analysis":[247],"(AUC":[248],"0.77":[250],"0.75,":[252],"respectively).":[253],"These":[254],"findings":[255],"demonstrate":[256],"value":[258],"incorporating":[260],"measure":[262],"radiomics,":[269],"enable":[271],"significantly":[273],"more":[274],"accurate":[275],"prediction":[276],"Status.":[280]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2024-12-27T00:00:00"}