{"id":"https://openalex.org/W2320193080","doi":"https://doi.org/10.1117/12.2217008","title":"Predicting response before initiation of neoadjuvant chemotherapy in breast cancer using new methods for the analysis of dynamic contrast enhanced MRI (DCE MRI) data","display_name":"Predicting response before initiation of neoadjuvant chemotherapy in breast cancer using new methods for the analysis of dynamic contrast enhanced MRI (DCE MRI) data","publication_year":2016,"publication_date":"2016-03-29","ids":{"openalex":"https://openalex.org/W2320193080","doi":"https://doi.org/10.1117/12.2217008","mag":"2320193080"},"language":"en","primary_location":{"id":"doi:10.1117/12.2217008","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2217008","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006032317","display_name":"Joseph B. DeGrandchamp","orcid":"https://orcid.org/0000-0003-2194-5495"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joseph B. DeGrandchamp","raw_affiliation_strings":["Univ. of Arizona (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Arizona (United States)","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075392197","display_name":"Jennifer G. Whisenant","orcid":"https://orcid.org/0000-0002-3435-2464"},"institutions":[{"id":"https://openalex.org/I4210150144","display_name":"LIG Science (United States)","ror":"https://ror.org/05035cc38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150144"]},{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer G. Whisenant","raw_affiliation_strings":["Vanderbilt Univ. Institute of Imaging Science (United States)"],"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. Institute of Imaging Science (United States)","institution_ids":["https://openalex.org/I200719446","https://openalex.org/I4210150144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073974051","display_name":"Lori R. Arlinghaus","orcid":"https://orcid.org/0000-0002-8582-1777"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]},{"id":"https://openalex.org/I4210150144","display_name":"LIG Science (United States)","ror":"https://ror.org/05035cc38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lori R. Arlinghaus","raw_affiliation_strings":["Vanderbilt Univ. Institute of Imaging Science (United States)"],"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. Institute of Imaging Science (United States)","institution_ids":["https://openalex.org/I200719446","https://openalex.org/I4210150144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075889627","display_name":"Vandana G. Abramson","orcid":"https://orcid.org/0000-0002-6855-1322"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"V. G. Abramson","raw_affiliation_strings":["Vanderbilt Univ. School of Medicine (United States)"],"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027619317","display_name":"Thomas E. Yankeelov","orcid":"https://orcid.org/0000-0001-6201-3913"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas E. Yankeelov","raw_affiliation_strings":["Univ. of Texas at Austin (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Texas at Austin (United States)","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071501649","display_name":"Julio C\u00e1rdenas\u2010Rodr\u00edguez","orcid":"https://orcid.org/0000-0003-4789-4630"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Julio C\u00e1rdenas-Rodr\u00edguez","raw_affiliation_strings":["Univ. of Arizona (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Arizona (United States)","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5006032317"],"corresponding_institution_ids":["https://openalex.org/I138006243"],"apc_list":null,"apc_paid":null,"fwci":1.1108,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77745862,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9788","issue":null,"first_page":"978811","last_page":"978811"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11885","display_name":"MRI in cancer diagnosis","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/T11885","display_name":"MRI in cancer diagnosis","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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9997000098228455,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9988999962806702,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.6383085250854492},{"id":"https://openalex.org/keywords/dynamic-contrast-enhanced-mri","display_name":"Dynamic contrast-enhanced MRI","score":0.5633542537689209},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.552191436290741},{"id":"https://openalex.org/keywords/neoadjuvant-therapy","display_name":"Neoadjuvant therapy","score":0.44865792989730835},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.44846612215042114},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.3974858820438385},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3938455283641815},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.385678768157959},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3677794933319092},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.31613150238990784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3029744029045105},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.24478942155838013},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.21813121438026428},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19780346751213074}],"concepts":[{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.6383085250854492},{"id":"https://openalex.org/C41727105","wikidata":"https://www.wikidata.org/wiki/Q17009718","display_name":"Dynamic contrast-enhanced MRI","level":3,"score":0.5633542537689209},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.552191436290741},{"id":"https://openalex.org/C2778292576","wikidata":"https://www.wikidata.org/wiki/Q6991934","display_name":"Neoadjuvant therapy","level":4,"score":0.44865792989730835},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.44846612215042114},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.3974858820438385},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3938455283641815},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.385678768157959},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3677794933319092},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.31613150238990784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3029744029045105},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.24478942155838013},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.21813121438026428},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19780346751213074}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2217008","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2217008","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W212537071","https://openalex.org/W1526651659","https://openalex.org/W1963844533","https://openalex.org/W1964357740","https://openalex.org/W1967484865","https://openalex.org/W2020712165","https://openalex.org/W2026223017","https://openalex.org/W2035808363","https://openalex.org/W2042184005","https://openalex.org/W2042436876","https://openalex.org/W2058710711","https://openalex.org/W2069009122","https://openalex.org/W2085512859","https://openalex.org/W2091633428","https://openalex.org/W2094259943","https://openalex.org/W2097666948","https://openalex.org/W2098981666","https://openalex.org/W2125981191","https://openalex.org/W2135046866","https://openalex.org/W2165932245","https://openalex.org/W2189916683","https://openalex.org/W4206679801","https://openalex.org/W4235807914","https://openalex.org/W6674618617","https://openalex.org/W6680156768"],"related_works":["https://openalex.org/W2970784617","https://openalex.org/W4385649027","https://openalex.org/W2217963778","https://openalex.org/W2129882004","https://openalex.org/W4303685026","https://openalex.org/W1980276147","https://openalex.org/W3187081201","https://openalex.org/W1995646291","https://openalex.org/W2140519023","https://openalex.org/W2314026259"],"abstract_inverted_index":{"The":[0,201],"pharmacokinetic":[1],"parameters":[2,160],"derived":[3],"from":[4,215],"dynamic":[5],"contrast":[6],"enhanced":[7],"(DCE)":[8],"MRI":[9,26],"have":[10],"shown":[11],"promise":[12],"as":[13,178],"biomarkers":[14,48,108],"for":[15,143,149,203],"tumor":[16,139,147],"response":[17,50,241],"to":[18,78,132,170,175,188,239,242],"therapy.":[19],"However,":[20],"standard":[21,97],"methods":[22,98],"of":[23,49,165,224],"analyzing":[24],"DCE":[25],"data":[27],"(Tofts":[28],"model)":[29],"require":[30],"high":[31,34],"temporal":[32,104],"resolution,":[33,105],"signal-to-noise":[35],"ratio":[36],"(SNR),":[37],"and":[38,94,102,125,138,145,161,220,228],"the":[39,60,69,71,83,89,114,134,141,146,162,197,210,216,234],"Arterial":[40],"Input":[41],"Function":[42],"(AIF).":[43],"Such":[44],"models":[45,174],"produce":[46],"reliable":[47],"only":[51],"when":[52],"a":[53,56,65],"therapy":[54],"has":[55],"large":[57],"effect":[58],"on":[59],"parameters.":[61],"We":[62],"recently":[63],"reported":[64],"method":[66],"that":[67,233],"solves":[68],"limitations,":[70],"Linear":[72,121],"Reference":[73,117],"Region":[74,118],"Model":[75,119,128,190],"(LRRM).":[76],"Similar":[77],"other":[79],"reference":[80],"region":[81],"models,":[82],"LRRM":[84,90,235],"needs":[85],"no":[86],"AIF.":[87],"Additionally,":[88],"is":[91],"more":[92],"accurate":[93],"precise":[95],"than":[96],"at":[99],"low":[100],"SNR":[101],"slow":[103],"suggesting":[106],"LRRM-derived":[107],"could":[109],"be":[110,237],"better":[111],"predictors.":[112],"Here,":[113],"LRRM,":[115,217],"Non-linear":[116,126],"(NRRM),":[120],"Tofts":[122,127],"model":[123],"(LTM),":[124],"(NLTM)":[129],"were":[130,168,222],"used":[131,169,238],"estimate":[133],"<i>R<sup>Ktrans</sup></i>":[135],"between":[136],"muscle":[137],"(or":[140],"<i>K<sup>trans</sup></i>":[142],"Tofts)":[144],"<i>k<sub>ep,TOI</sub></i>":[148],"39":[150],"breast":[151,245],"cancer":[152],"patients":[153,177],"who":[154],"received":[155],"neoadjuvant":[156],"chemotherapy":[157],"(NAC).":[158],"These":[159],"receptor":[163,204],"statuses":[164],"each":[166],"patient":[167],"construct":[171],"cross-validated":[172],"predictive":[173],"classify":[176],"complete":[179],"pathological":[180,185],"responders":[181,186],"(pCR)":[182],"or":[183],"non-complete":[184],"(non-pCR)":[187],"NAC.":[189],"performance":[191,212],"was":[192,207],"evaluated":[193],"using":[194,213],"area":[195],"under":[196],"ROC":[198],"curve":[199],"(AUC).":[200],"AUC":[202],"status":[205],"alone":[206],"0.62,":[208],"while":[209],"best":[211],"predictors":[214],"NRRM,":[218],"LTM,":[219],"NLTM":[221],"AUCs":[223],"0.79,":[225],"0.55,":[226],"0.60,":[227],"0.59":[229],"respectively.":[230],"This":[231],"suggests":[232],"can":[236],"predict":[240],"NAC":[243],"in":[244],"cancer.":[246]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}