{"id":"https://openalex.org/W7218838415","doi":"https://doi.org/10.7759/cureus.117386","title":"Artificial Intelligence for Automated Analysis and Interpretation of Intravascular Ultrasound in Coronary Artery Disease: A Systematic Review","display_name":"Artificial Intelligence for Automated Analysis and Interpretation of Intravascular Ultrasound in Coronary Artery Disease: A Systematic Review","publication_year":2026,"publication_date":"2026-10-03","ids":{"openalex":"https://openalex.org/W7218838415","doi":"https://doi.org/10.7759/cureus.117386","pmid":"https://pubmed.ncbi.nlm.nih.gov/42974402","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13725891"},"language":"en","primary_location":{"id":"doi:10.7759/cureus.117386","doi":"https://doi.org/10.7759/cureus.117386","is_oa":true,"landing_page_url":"https://doi.org/10.7759/cureus.117386","pdf_url":"https://www.cureus.com/articles/535230-artificial-intelligence-for-automated-analysis-and-interpretation-of-intravascular-ultrasound-in-coronary-artery-disease-a-systematic-review.pdf","source":{"id":"https://openalex.org/S2738950867","display_name":"Cureus","issn_l":"2168-8184","issn":["2168-8184"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","poland-20","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310316779","host_organization_name":"Cureus, Inc.","host_organization_lineage":["https://openalex.org/P4310316779"],"host_organization_lineage_names":["Cureus, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cureus","raw_type":"journal-article"},"volume":null,"type":"review","is_traditional":true,"indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.cureus.com/articles/535230-artificial-intelligence-for-automated-analysis-and-interpretation-of-intravascular-ultrasound-in-coronary-artery-disease-a-systematic-review.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139464524","display_name":"Ashwin Umasankar","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405263919","display_name":"Government Medical College and Hospital, Thiruvallur","ror":"https://ror.org/00dxacs38","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405263919"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashwin Umasankar","raw_affiliation_strings":["Medicine, Government Medical College, Thiruvallur, IND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medicine, Government Medical College, Thiruvallur, IND","institution_ids":["https://openalex.org/I4405263919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139490253","display_name":"Heramba Vigneshwar Sachithananthan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210147381","display_name":"Oxford University Hospitals NHS Trust","ror":"https://ror.org/03h2bh287","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210147381"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Heramba Vigneshwar Sachithananthan","raw_affiliation_strings":["Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, GBR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, GBR","institution_ids":["https://openalex.org/I4210147381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114523270","display_name":"Anusha Chitravanshi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anusha Chitravanshi","raw_affiliation_strings":["Medicine, Sir Seewoosagur Ramgoolam Medical College, Belle Rive, MUS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medicine, Sir Seewoosagur Ramgoolam Medical College, Belle Rive, MUS","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110805029","display_name":"Indrajit Banerjee","orcid":"https://orcid.org/0000-0003-2880-4695","observed_orcids":["https://orcid.org/0000-0003-2880-4695"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Indrajit Banerjee","raw_affiliation_strings":["Pharmacology, Sir Seewoosagur Ramgoolam Medical College, Belle Rive, MUS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pharmacology, Sir Seewoosagur Ramgoolam Medical College, Belle Rive, MUS","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110805029"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55882353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"10","first_page":"e117386","last_page":"e117386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.8223000168800354,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.8223000168800354,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.10350000113248825,"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/T10862","display_name":"AI in cancer detection","score":0.015599999576807022,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/intravascular-ultrasound","display_name":"intravascular ultrasound","score":0.949999988079071},{"id":"https://openalex.org/keywords/coronary-artery-disease","display_name":"coronary artery disease","score":0.9729999899864197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"artificial intelligence","score":0.9399999976158142},{"id":"https://openalex.org/keywords/automated-image-analysis","display_name":"automated image analysis","score":0.9290000200271606},{"id":"https://openalex.org/keywords/plaque-segmentation","display_name":"plaque segmentation","score":0.6499999761581421},{"id":"https://openalex.org/keywords/lumen-segmentation","display_name":"lumen segmentation","score":0.7509999871253967},{"id":"https://openalex.org/keywords/plaque-characterization","display_name":"plaque characterization","score":0.5770000219345093},{"id":"https://openalex.org/keywords/calcium-quantification","display_name":"calcium quantification","score":0.6679999828338623},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8669999837875366},{"id":"https://openalex.org/keywords/u-net","display_name":"U-Net","score":0.6729999780654907},{"id":"https://openalex.org/keywords/deeplabv3","display_name":"DeepLabV3+","score":0.9110000133514404},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"gradient boosting","score":0.9049999713897705},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"diagnostic accuracy","score":0.8180000185966492},{"id":"https://openalex.org/keywords/percutaneous-coronary-intervention","display_name":"percutaneous coronary intervention","score":0.8830000162124634},{"id":"https://openalex.org/keywords/risk-of-bias","display_name":"risk of bias","score":0.6269999742507935},{"id":"https://openalex.org/keywords/clinical-utility","display_name":"clinical utility","score":0.3790000081062317},{"id":"https://openalex.org/keywords/risk-stratification","display_name":"risk stratification","score":0.4480000138282776}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.9502999782562256},{"id":"https://openalex.org/C2776931568","wikidata":"https://www.wikidata.org/wiki/Q1671577","display_name":"Intravascular ultrasound","level":2,"score":0.7053999900817871},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.6018000245094299},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.5375000238418579},{"id":"https://openalex.org/C2778213512","wikidata":"https://www.wikidata.org/wiki/Q844935","display_name":"Coronary artery disease","level":2,"score":0.49709999561309814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4332999885082245},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C3019004856","wikidata":"https://www.wikidata.org/wiki/Q42297149","display_name":"Coronary angiography","level":3,"score":0.35910001397132874},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.3027999997138977},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C3019060180","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automated method","level":2,"score":0.25859999656677246}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.7759/cureus.117386","doi":"https://doi.org/10.7759/cureus.117386","is_oa":true,"landing_page_url":"https://doi.org/10.7759/cureus.117386","pdf_url":"https://www.cureus.com/articles/535230-artificial-intelligence-for-automated-analysis-and-interpretation-of-intravascular-ultrasound-in-coronary-artery-disease-a-systematic-review.pdf","source":{"id":"https://openalex.org/S2738950867","display_name":"Cureus","issn_l":"2168-8184","issn":["2168-8184"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","poland-20","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310316779","host_organization_name":"Cureus, Inc.","host_organization_lineage":["https://openalex.org/P4310316779"],"host_organization_lineage_names":["Cureus, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cureus","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13725891","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13725891/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13725891/pdf/cureus-0018-00000117386.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cureus","raw_type":"Text"},{"id":"pmid:42974402","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42974402","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cureus","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.7759/cureus.117386","doi":"https://doi.org/10.7759/cureus.117386","is_oa":true,"landing_page_url":"https://doi.org/10.7759/cureus.117386","pdf_url":"https://www.cureus.com/articles/535230-artificial-intelligence-for-automated-analysis-and-interpretation-of-intravascular-ultrasound-in-coronary-artery-disease-a-systematic-review.pdf","source":{"id":"https://openalex.org/S2738950867","display_name":"Cureus","issn_l":"2168-8184","issn":["2168-8184"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","poland-20","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310316779","host_organization_name":"Cureus, Inc.","host_organization_lineage":["https://openalex.org/P4310316779"],"host_organization_lineage_names":["Cureus, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cureus","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.979200005531311,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[{"display_name":"Systematic Review","id":"https://openalex.org/study-designs/systematic-review"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7218838415.pdf","grobid_xml":"https://content.openalex.org/works/W7218838415.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2098360288","https://openalex.org/W2107638293","https://openalex.org/W2165010366","https://openalex.org/W2803695296","https://openalex.org/W3022807913","https://openalex.org/W3029781328","https://openalex.org/W3092783089","https://openalex.org/W3118615836","https://openalex.org/W3124156453","https://openalex.org/W3137184258","https://openalex.org/W3149846123","https://openalex.org/W3190673750","https://openalex.org/W4317038729","https://openalex.org/W4386054423","https://openalex.org/W4388617801","https://openalex.org/W4406854920","https://openalex.org/W4412513137","https://openalex.org/W4413100702","https://openalex.org/W4416139320","https://openalex.org/W7123356162","https://openalex.org/W7125777822","https://openalex.org/W7143513549","https://openalex.org/W7169831878"],"related_works":["https://openalex.org/W7169831878","https://openalex.org/W7110008735","https://openalex.org/W4324286705","https://openalex.org/W4396601388","https://openalex.org/W7168152719","https://openalex.org/W4410393812","https://openalex.org/W3190673750","https://openalex.org/W7123347406","https://openalex.org/W7133484339","https://openalex.org/W4313458742"],"abstract_inverted_index":{"Coronary":[0],"artery":[1],"disease":[2],"(CAD)":[3],"leads":[4],"to":[5,18,55,171,236,251,276,280,286,300,332,387,405,422],"considerable":[6],"morbidity":[7],"and":[8,49,60,80,90,101,131,138,142,161,165,197,216,224,238,259,262,267,271,278,308,317,340,348,393,396,401],"mortality":[9],"worldwide.":[10],"Intravascular":[11],"ultrasound":[12],"(IVUS)":[13],"is":[14,42],"an":[15],"imaging":[16],"modality":[17],"guide":[19],"percutaneous":[20],"coronary":[21,70,121,227,369],"intervention;":[22],"however,":[23],"it":[24],"requires":[25],"time-consuming,":[26],"expert-dependent":[27],"manual":[28],"analysis.":[29],"Artificial":[30],"intelligence":[31],"(AI)":[32],"has":[33],"been":[34],"increasingly":[35],"used":[36,170],"for":[37,65,86,106,116,243,257,265,367,378],"IVUS":[38,67,370,380],"analysis,":[39],"but":[40],"there":[41],"limited":[43,421],"evidence":[44,352,359,411],"on":[45,205],"its":[46],"diagnostic":[47,58],"accuracy":[48],"clinical":[50,61,383],"utility.":[51],"This":[52],"review":[53],"aimed":[54],"evaluate":[56],"the":[57,82,117,144,166,173,178,194,206,239,254,263,284,293,309,320,336,349,406,424],"performance":[59,207,256],"usefulness":[62],"of":[63,69,120,125,128,148,156,175,208,295,305,314,319,329,351,410,426],"AI":[64],"automated":[66,118],"analysis":[68,119],"arteries.":[71],"The":[72,146,229,269,357],"research":[73],"protocol":[74],"was":[75,150,169,297,322,345,353],"prospectively":[76],"registered":[77],"(PROSPERO,":[78],"CRD420261454806)":[79],"followed":[81],"PRISMA":[83],"2020":[84],"guidelines":[85],"systematic":[87],"reviews.":[88],"PubMed/MEDLINE":[89],"Cochrane":[91,186],"CENTRAL":[92],"were":[93,198],"searched":[94],"from":[95,234,249,274,412],"inception":[96],"through":[97],"July":[98,102],"23,":[99],"2026,":[100,104],"26,":[103],"respectively,":[105,282],"publications":[107],"assessing":[108],"AI,":[109],"machine":[110],"learning,":[111],"or":[112],"deep":[113],"learning":[114],"algorithms":[115],"IVUS,":[122],"including":[123],"segmentation":[124,244,261],"structures,":[126],"identification":[127],"plaque":[129],"types,":[130],"quantitative":[132],"measurements.":[133],"Two":[134],"reviewers":[135],"independently":[136],"screened":[137],"selected":[139],"eligible":[140],"studies":[141,192,321],"extracted":[143],"data.":[145],"risk":[147,294,328],"bias":[149,296],"assessed":[151],"using":[152,163],"QUADAS-2":[153],"(Quality":[154],"Assessment":[155],"Diagnostic":[157],"Accuracy":[158],"Studies-2":[159],"(QUADAS-2)":[160],"visualized":[162],"robvis,":[164],"GRADE":[167],"approach":[168],"rate":[172],"certainty":[174,350,409],"evidence.":[176],"Of":[177],"802":[179],"records":[180],"identified":[181],"(PubMed,":[182],"n":[183,188],"=":[184,189],"216;":[185],"CENTRAL,":[187],"586),":[190],"eight":[191,306,315],"met":[193],"inclusion":[195],"criteria":[196],"included":[199],"in":[200,219,226,335,382,428],"this":[201],"review.":[202],"They":[203,385],"reported":[204],"convolutional":[209],"neural":[210],"networks,":[211],"U-Net/U-Net++,":[212],"Efficient-UNet,":[213],"DeepLabv3+-based":[214],"models,":[215],"gradient":[217],"boosting":[218],"segmenting":[220,391,399],"lumen,":[221],"vessel,":[222],"plaque,":[223],"stent":[225,266,400],"IVUS.":[228],"Dice":[230],"similarity":[231],"coefficient":[232],"ranged":[233,248,273],"0.67":[235],"0.97,":[237,252],"intersection":[240],"over":[241],"union":[242],"(including":[245],"Jaccard":[246],"similarity)":[247],"0.66":[250],"with":[253,283,371],"best":[255,389],"lumen":[258,392],"vessel":[260,394],"poorest":[264],"calcium.":[268,402],"sensitivity":[270],"specificity":[272],"62%":[275],"90%":[277],"88%":[279],"99%,":[281],"correlation":[285],"expert":[287],"assessment":[288],"generally":[289],"above":[290],"0.9.":[291],"Overall,":[292],"mainly":[298],"related":[299],"patient":[301],"selection":[302],"(five":[303],"out":[304,313],"studies)":[307],"reference":[310,338],"standard":[311],"(three":[312],"studies),":[316],"none":[318],"rated":[323,354],"as":[324,355],"having":[325],"a":[326,343],"high":[327],"bias.":[330],"Due":[331],"between-study":[333],"heterogeneity":[334],"tasks,":[337],"standards,":[339],"outcome":[341],"measures,":[342],"meta-analysis":[344],"not":[346],"performed,":[347],"low.":[356],"current":[358],"suggests":[360],"that":[361],"AI-based":[362],"methods":[363],"have":[364],"good":[365],"potential":[366],"analyzing":[368],"acceptable":[372],"accuracy,":[373],"which":[374],"could":[375],"be":[376,420],"helpful":[377],"high-throughput":[379],"interpretation":[381],"practice.":[384],"appear":[386],"perform":[388],"at":[390,398],"structures":[395],"worst":[397],"However,":[403],"due":[404],"overall":[407],"low":[408],"these":[413],"mostly":[414],"retrospective":[415],"studies,":[416],"their":[417],"use":[418],"should":[419],"complementing":[423],"work":[425],"experts":[427],"cardiovascular":[429],"medicine.":[430]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-04T00:00:00"}