{"id":"https://openalex.org/W7160854233","doi":"https://doi.org/10.48550/arxiv.2605.07156","title":"Hierarchical Perfusion Graphs for Tumor Heterogeneity Modeling in Glioma Molecular Subtyping","display_name":"Hierarchical Perfusion Graphs for Tumor Heterogeneity Modeling in Glioma Molecular Subtyping","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160854233","doi":"https://doi.org/10.48550/arxiv.2605.07156"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07156","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07156","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.07156","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135832809","display_name":"Han Jang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jang, Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135882998","display_name":"Junhyeok Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Junhyeok","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128715726","display_name":"Heeseong Eum","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eum, Heeseong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107913288","display_name":"Joon Jang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jang, Joon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027171928","display_name":"Yoseob Han","orcid":"https://orcid.org/0000-0002-0382-7826"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Yoseob","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135892144","display_name":"Seung Hong Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Seung Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006749140","display_name":"Kyu Sung Choi","orcid":"https://orcid.org/0000-0002-5175-3307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Kyu Sung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10129","display_name":"Glioma Diagnosis and Treatment","score":0.7421000003814697,"subfield":{"id":"https://openalex.org/subfields/2716","display_name":"Genetics"},"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/T10129","display_name":"Glioma Diagnosis and Treatment","score":0.7421000003814697,"subfield":{"id":"https://openalex.org/subfields/2716","display_name":"Genetics"},"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":0.17550000548362732,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.012400000356137753,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subtyping","display_name":"Subtyping","score":0.8176000118255615},{"id":"https://openalex.org/keywords/glioma","display_name":"Glioma","score":0.6586999893188477},{"id":"https://openalex.org/keywords/isocitrate-dehydrogenase","display_name":"Isocitrate dehydrogenase","score":0.6055999994277954},{"id":"https://openalex.org/keywords/radiogenomics","display_name":"Radiogenomics","score":0.4578000009059906},{"id":"https://openalex.org/keywords/idh1","display_name":"IDH1","score":0.41659998893737793},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3935999870300293},{"id":"https://openalex.org/keywords/glioblastoma","display_name":"Glioblastoma","score":0.37279999256134033},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3580999970436096}],"concepts":[{"id":"https://openalex.org/C83852419","wikidata":"https://www.wikidata.org/wiki/Q2713292","display_name":"Subtyping","level":2,"score":0.8176000118255615},{"id":"https://openalex.org/C2778227246","wikidata":"https://www.wikidata.org/wiki/Q1365309","display_name":"Glioma","level":2,"score":0.6586999893188477},{"id":"https://openalex.org/C2777150147","wikidata":"https://www.wikidata.org/wiki/Q261968","display_name":"Isocitrate dehydrogenase","level":3,"score":0.6055999994277954},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.6035000085830688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5796999931335449},{"id":"https://openalex.org/C163500349","wikidata":"https://www.wikidata.org/wiki/Q7281263","display_name":"Radiogenomics","level":3,"score":0.4578000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44190001487731934},{"id":"https://openalex.org/C127848430","wikidata":"https://www.wikidata.org/wiki/Q18027543","display_name":"IDH1","level":4,"score":0.41659998893737793},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C2776194525","wikidata":"https://www.wikidata.org/wiki/Q282142","display_name":"Glioblastoma","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.3197000026702881},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.29499998688697815},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C59593255","wikidata":"https://www.wikidata.org/wiki/Q901663","display_name":"Molecular dynamics","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26429998874664307},{"id":"https://openalex.org/C136339569","wikidata":"https://www.wikidata.org/wiki/Q1142297","display_name":"Molecular imaging","level":3,"score":0.2615000009536743},{"id":"https://openalex.org/C2777727622","wikidata":"https://www.wikidata.org/wiki/Q5251772","display_name":"Degeneracy (biology)","level":2,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07156","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07156","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.07156","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07156","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Precise":[0],"molecular":[1,47,64,138,201],"subtyping":[2],"of":[3,78,115,149,192],"gliomas,":[4],"including":[5],"isocitrate":[6],"dehydrogenase":[7],"(IDH)":[8],"mutation":[9],"and":[10,16,75,154,158],"1p/19q":[11],"codeletion,":[12],"directly":[13],"guides":[14],"surgical":[15],"therapeutic":[17],"decisions,":[18],"yet":[19,66],"currently":[20],"relies":[21],"on":[22,28,51,165],"invasive":[23],"tissue":[24],"sampling.":[25],"Deep":[26],"learning":[27],"structural":[29,125],"MRI":[30,56],"has":[31,69],"emerged":[32],"as":[33],"a":[34,84,97],"non-invasive":[35],"alternative,":[36],"but":[37],"anatomy-only":[38],"approaches":[39],"cannot":[40],"capture":[41],"the":[42,76,145,189],"hemodynamic":[43,90],"signatures":[44],"that":[45,86],"distinguish":[46],"subtypes.":[48],"Radiogenomics":[49],"based":[50],"dynamic":[52],"susceptibility":[53],"contrast":[54],"(DSC)":[55],"holds":[57],"immense":[58],"potential":[59],"for":[60,137,199],"non-invasively":[61],"characterizing":[62],"glioma":[63,184,200],"subtypes,":[65],"clinical":[67],"deployment":[68],"been":[70],"hindered":[71],"by":[72,124],"inter-site":[73],"variability":[74],"limitations":[77],"voxel-wise":[79],"analysis.":[80],"We":[81],"introduce":[82],"HiPerfGNN,":[83],"framework":[85],"first":[87],"learns":[88],"discrete":[89],"representations":[91],"from":[92],"raw":[93],"time-intensity":[94],"curves":[95],"using":[96],"vector-quantized":[98],"variational":[99],"autoencoder":[100],"(VQ-VAE).":[101],"These":[102],"quantized":[103],"perfusion":[104,194],"codes":[105],"define":[106],"coarse-level":[107],"graph":[108,129],"nodes":[109],"representing":[110],"functional":[111],"tumor":[112],"habitats,":[113],"each":[114],"which":[116],"is":[117,204],"hierarchically":[118],"subdivided":[119],"into":[120,196],"fine-level":[121],"subregions":[122],"guided":[123],"MRI.":[126],"A":[127],"hierarchical":[128],"neural":[130],"network":[131],"then":[132],"propagates":[133],"information":[134],"across":[135],"scales":[136],"prediction.":[139],"On":[140],"an":[141,166],"internal":[142],"cohort":[143,169],"(n=475),":[144],"model":[146],"achieved":[147],"AUCs":[148],"0.96":[150],"(IDH),":[151],"0.89":[152],"(1p/19q),":[153],"0.84":[155],"(WHO":[156],"grade),":[157],"maintained":[159],"robust":[160],"IDH":[161],"performance":[162],"(AUC":[163],"0.89)":[164],"independent":[167],"external":[168],"(n=397)":[170],"without":[171],"recalibration.":[172],"Gradient-based":[173],"saliency":[174],"analysis":[175],"confirms":[176],"biologically":[177],"grounded":[178],"attention":[179],"patterns":[180],"aligned":[181],"with":[182],"known":[183],"pathophysiology.":[185],"Our":[186],"results":[187],"demonstrate":[188],"added":[190],"value":[191],"integrating":[193],"dynamics":[195],"radiogenomic":[197],"pipelines":[198],"subtyping.":[202],"Code":[203],"available":[205],"at":[206],"https://github.com/janghana/HiPerfGNN.":[207]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-12T00:00:00"}