{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T17:40:25Z","timestamp":1793727625324,"version":"4.6.1"},"reference-count":45,"publisher":"American Society of Hematology","issue":"21","content-domain":{"domain":["ashpublications.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,11,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Investigating prognostic factors in patients with relapsed or primary refractory classical Hodgkin lymphoma (R\/R cHL) is essential to optimize risk-adapted treatment strategies. We built a prognostic model using baseline quantitative 18F-fluorodeoxyglucose\u00a0positron emission tomography\u00a0(PET) radiomics features and clinical characteristics to predict the progression-free survival (PFS) among patients with R\/R cHL treated with salvage chemotherapy followed by autologous stem cell transplantation. Metabolic tumor volume and several novel radiomics dissemination features, representing interlesional differences in distance, volume, and standard uptake value, were extracted from the baseline PET. Machine learning using backward selection and logistic regression were applied to develop and train the model on a total of 113 patients from 2 clinical trials. The model was validated on an independent external cohort of 69 patients. In addition, we validated 4 different PET segmentation methods to calculate radiomics features. We identified a subset of patients at high risk for progression with significant inferior 3-year PFS outcomes of 38.1% vs 88.4% for patients in the low-risk group in the training cohort (P\u00a0&amp;lt; .001) and 38.5% vs 75.0% in the validation cohort (P\u00a0= .015), respectively. The overall survival was also significantly better in the low-risk group (P\u00a0= .022 and P\u00a0&amp;lt; .001). We provide a formula to calculate a risk score for individual patients based on the model. In conclusion, we developed a prognostic model for PFS combining radiomics and clinical features in a large cohort of patients with R\/R cHL. This model calculates a PET-based risk profile and can be applied to develop risk-stratified treatment strategies for patients with R\/R cHL. These trials were registered at www.clinicaltrials.gov as #NCT02280993,\u00a0#NCT00255723, and #NCT01508312.<\/jats:p>","DOI":"10.1182\/bloodadvances.2023010404","type":"journal-article","created":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T18:04:16Z","timestamp":1695060256000},"page":"6732-6743","update-policy":"https:\/\/doi.org\/10.1182\/blood.2019cm0000","source":"Crossref","is-referenced-by-count":24,"title":["Prognostic model using 18F-FDG PET radiomics predicts progression-free survival in relapsed\/refractory Hodgkin lymphoma"],"prefix":"10.1182","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9364-2501","authenticated-orcid":false,"given":"Julia","family":"Driessen","sequence":"first","affiliation":[{"name":"1Department of Hematology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands"},{"name":"2Division of Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, The Netherlands"},{"name":"3LYMMCARE, Lymphoma and Myeloma Center Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9571-9362","authenticated-orcid":false,"given":"Gerben J. C.","family":"Zwezerijnen","sequence":"additional","affiliation":[{"name":"2Division of Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, The Netherlands"},{"name":"4Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5170-4185","authenticated-orcid":false,"given":"Heiko","family":"Sch\u00f6der","sequence":"additional","affiliation":[{"name":"5Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8904-3802","authenticated-orcid":false,"given":"Marie Jos\u00e9","family":"Kersten","sequence":"additional","affiliation":[{"name":"1Department of Hematology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands"},{"name":"3LYMMCARE, Lymphoma and Myeloma Center Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3408-050X","authenticated-orcid":false,"given":"Alison J.","family":"Moskowitz","sequence":"additional","affiliation":[{"name":"6Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9189-3152","authenticated-orcid":false,"given":"Craig H.","family":"Moskowitz","sequence":"additional","affiliation":[{"name":"7Department of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6094-0016","authenticated-orcid":false,"given":"Jakoba J.","family":"Eertink","sequence":"additional","affiliation":[{"name":"2Division of Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, The Netherlands"},{"name":"8Department of Hematology, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3889-0921","authenticated-orcid":false,"given":"Martijn W.","family":"Heymans","sequence":"additional","affiliation":[{"name":"9Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0313-5686","authenticated-orcid":false,"given":"Ronald","family":"Boellaard","sequence":"additional","affiliation":[{"name":"2Division of Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, The Netherlands"},{"name":"4Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1074-5922","authenticated-orcid":false,"given":"Jos\u00e9e M.","family":"Zijlstra","sequence":"additional","affiliation":[{"name":"2Division of Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, The Netherlands"},{"name":"8Department of Hematology, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"234","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"issue":"2","key":"2023111415103477900_bib1","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1038\/s41375-020-0875-0","article-title":"Primary therapy and relative survival in classical Hodgkin lymphoma: a nationwide population-based study in the Netherlands, 1989-2017","volume":"35","author":"Driessen","year":"2021","journal-title":"Leukemia"},{"issue":"4","key":"2023111415103477900_bib2","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1002\/cncr.31114","article-title":"Long-term outcomes among 2-year survivors of autologous hematopoietic cell transplantation for Hodgkin and diffuse large b-cell lymphoma","volume":"124","author":"Myers","year":"2018","journal-title":"Cancer"},{"issue":"8","key":"2023111415103477900_bib3","doi-asserted-by":"crossref","first-page":"1922","DOI":"10.3109\/10428194.2013.854888","article-title":"Outcome and risk factors of patients with Hodgkin lymphoma who relapse or progress after autologous stem cell transplant","volume":"55","author":"von Tresckow","year":"2014","journal-title":"Leuk Lymphoma"},{"issue":"1","key":"2023111415103477900_bib4","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1182\/hematology.2021000311","article-title":"How to choose first salvage therapy in Hodgkin lymphoma: traditional chemotherapy vs novel agents","volume":"2021","author":"Driessen","year":"2021","journal-title":"Hematology Am Soc Hematol Educ Program"},{"issue":"16","key":"2023111415103477900_bib5","doi-asserted-by":"crossref","first-page":"1786","DOI":"10.1200\/JCO.2016.68.6394","article-title":"Early positron emission tomography response-adapted treatment in stage I and II Hodgkin lymphoma: final results of the randomized EORTC\/LYSA\/FIL H10 trial","volume":"35","author":"Andr\u00e9","year":"2017","journal-title":"J\u00a0Clin Oncol"},{"issue":"17","key":"2023111415103477900_bib6","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.1056\/NEJMoa1408648","article-title":"Results of a trial of PET-directed therapy for early-stage Hodgkin's lymphoma","volume":"372","author":"Radford","year":"2015","journal-title":"N\u00a0Engl J Med"},{"issue":"10114","key":"2023111415103477900_bib7","doi-asserted-by":"crossref","first-page":"2790","DOI":"10.1016\/S0140-6736(17)32134-7","article-title":"PET-guided treatment in patients with advanced-stage Hodgkin's lymphoma (HD18): final results of an open-label, international, randomised phase 3 trial by the German Hodgkin Study Group","volume":"390","author":"Borchmann","year":"2017","journal-title":"Lancet"},{"issue":"6","key":"2023111415103477900_bib8","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1093\/annonc\/mdx072","article-title":"Risk factors and a prognostic score for survival after autologous stem-cell transplantation for relapsed or refractory Hodgkin lymphoma","volume":"28","author":"Br\u00f6ckelmann","year":"2017","journal-title":"Ann Oncol"},{"issue":"20","key":"2023111415103477900_bib9","doi-asserted-by":"crossref","first-page":"2196","DOI":"10.1182\/blood-2017-06-788877","article-title":"Prognostic significance of baseline metabolic tumor volume in relapsed and refractory Hodgkin lymphoma","volume":"130","author":"Moskowitz","year":"2017","journal-title":"Blood"},{"issue":"12","key":"2023111415103477900_bib10","doi-asserted-by":"crossref","first-page":"2853","DOI":"10.1038\/s41375-022-01717-8","article-title":"Prognostic value of TARC and quantitative PET parameters in relapsed or refractory Hodgkin lymphoma patients treated with brentuximab vedotin and DHAP","volume":"36","author":"Driessen","year":"2022","journal-title":"Leukemia"},{"issue":"13","key":"2023111415103477900_bib11","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1182\/blood-2017-07-795476","article-title":"Prognostic value of baseline metabolic tumor volume in early-stage Hodgkin lymphoma in the standard arm of the H10 trial","volume":"131","author":"Cottereau","year":"2018","journal-title":"Blood"},{"issue":"12","key":"2023111415103477900_bib12","doi-asserted-by":"crossref","first-page":"1656","DOI":"10.1111\/cas.12282","article-title":"Metabolic tumor volume by positron emission tomography\/computed tomography as a clinical parameter to determine therapeutic modality for early stage Hodgkin's lymphoma","volume":"104","author":"Song","year":"2013","journal-title":"Cancer Sci"},{"key":"2023111415103477900_bib13","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.clinimag.2022.09.004","article-title":"(18)F-FDG PET\/CT prognostic role in predicting response to salvage therapy in relapsed\/refractory Hodgkin's lymphoma","volume":"92","author":"Eisazadeh","year":"2022","journal-title":"Clin Imaging"},{"issue":"1","key":"2023111415103477900_bib14","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1186\/s12885-022-09758-z","article-title":"Predictive value of baseline metabolic tumor volume in early-stage favorable Hodgkin lymphoma - data from the prospective, multicenter phase III HD16 trial","volume":"22","author":"van Heek","year":"2022","journal-title":"BMC Cancer"},{"issue":"12","key":"2023111415103477900_bib15","doi-asserted-by":"crossref","first-page":"2897","DOI":"10.3324\/haematol.2021.280004","article-title":"High-risk stage IIB Hodgkin lymphoma treated in the H10 and AHL2011 trials: total metabolic tumor volume is a useful risk factor to stratify patients at baseline","volume":"107","author":"Rossi","year":"2022","journal-title":"Haematologica"},{"issue":"9","key":"2023111415103477900_bib16","doi-asserted-by":"crossref","first-page":"e29212","DOI":"10.1002\/pbc.29212","article-title":"Prognostic value of baseline metabolic tumor volume in children and adolescents with intermediate-risk Hodgkin lymphoma treated with chemo-radiation therapy: FDG-PET parameter analysis in a subgroup from COG AHOD0031","volume":"68","author":"Milgrom","year":"2021","journal-title":"Pediatr Blood Cancer"},{"issue":"1","key":"2023111415103477900_bib17","doi-asserted-by":"crossref","first-page":"40","DOI":"10.2967\/jnumed.119.229450","article-title":"(18)F-FDG PET dissemination features in diffuse large B-cell lymphoma are predictive of outcome","volume":"61","author":"Cottereau","year":"2020","journal-title":"J\u00a0Nucl Med"},{"issue":"4","key":"2023111415103477900_bib18","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1002\/hon.3025","article-title":"Prognostic value of lesion dissemination in doxorubicin, bleomycin, vinblastine, and dacarbazine-treated, interimPET-negative classical Hodgkin lymphoma patients: a radio-genomic study","volume":"40","author":"Durmo","year":"2022","journal-title":"Hematol Oncol"},{"issue":"13","key":"2023111415103477900_bib19","doi-asserted-by":"crossref","first-page":"2307","DOI":"10.1007\/s00259-018-4100-6","article-title":"Radiomics analysis of pre-treatment [(18)F]FDG PET\/CT for patients with metastatic colorectal cancer undergoing palliative systemic treatment","volume":"45","author":"van Helden","year":"2018","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"12","key":"2023111415103477900_bib20","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","article-title":"Radiomics: the bridge between medical imaging and personalized medicine","volume":"14","author":"Lambin","year":"2017","journal-title":"Nat Rev Clin Oncol"},{"issue":"4","key":"2023111415103477900_bib21","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","article-title":"Radiomics: extracting more information from medical images using advanced feature analysis","volume":"48","author":"Lambin","year":"2012","journal-title":"Eur J Cancer"},{"issue":"1","key":"2023111415103477900_bib22","doi-asserted-by":"crossref","first-page":"3913","DOI":"10.1038\/s41598-018-22319-4","article-title":"Radiomics features differentiate between normal and tumoral high-FDG uptake","volume":"8","author":"Hsu","year":"2018","journal-title":"Sci Rep"},{"issue":"1","key":"2023111415103477900_bib23","doi-asserted-by":"crossref","first-page":"1322","DOI":"10.1038\/s41598-018-37197-z","article-title":"A\u00a0PET radiomics model to predict refractory mediastinal Hodgkin lymphoma","volume":"9","author":"Milgrom","year":"2019","journal-title":"Sci Rep"},{"issue":"8","key":"2023111415103477900_bib24","doi-asserted-by":"crossref","first-page":"e183","DOI":"10.1016\/j.acra.2019.10.015","article-title":"Intratumor heterogeneity assessed by (18)F-FDG PET\/CT predicts treatment response and survival outcomes in patients with Hodgkin lymphoma","volume":"27","author":"Lue","year":"2020","journal-title":"Acad Radiol"},{"issue":"2","key":"2023111415103477900_bib25","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1002\/mp.13322","article-title":"Repeatability of (18) F-FDG PET radiomic features: a phantom study to explore sensitivity to image reconstruction settings, noise, and delineation method","volume":"46","author":"Pfaehler","year":"2019","journal-title":"Med Phys"},{"issue":"9","key":"2023111415103477900_bib26","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.2967\/jnumed.121.263067","article-title":"The impact of semi-automatic segmentation methods on metabolic tumor volume, intensity and dissemination radiomics in (18)F-FDG PET scans of patients with classical Hodgkin lymphoma","volume":"63","author":"Driessen","year":"2022","journal-title":"J\u00a0Nucl Med"},{"issue":"32","key":"2023111415103477900_bib27","doi-asserted-by":"crossref","first-page":"3722","DOI":"10.1200\/JCO.2017.72.7925","article-title":"Prognostic model to predict post-autologous stem-cell transplantation outcomes in classical Hodgkin lymphoma","volume":"35","author":"Chan","year":"2017","journal-title":"J\u00a0Clin Oncol"},{"issue":"4","key":"2023111415103477900_bib28","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.3324\/haematol.2019.243238","article-title":"Combining brentuximab vedotin with dexamethasone, high-dose cytarabine and cisplatin as salvage treatment in relapsed or refractory Hodgkin lymphoma: the phase II HOVON\/LLPC Transplant BRaVE study","volume":"106","author":"Kersten","year":"2021","journal-title":"Haematologica"},{"issue":"3","key":"2023111415103477900_bib29","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/S1470-2045(15)70013-6","article-title":"PET-adapted sequential salvage therapy with brentuximab vedotin followed by augmented ifosamide, carboplatin, and etoposide for patients with relapsed and refractory Hodgkin's lymphoma: a non-randomised, open-label, single-centre, phase 2 study","volume":"16","author":"Moskowitz","year":"2015","journal-title":"Lancet Oncol"},{"issue":"7","key":"2023111415103477900_bib30","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1182\/blood-2011-10-388058","article-title":"Normalization of pre-ASCT, FDG-PET imaging with second-line, non-cross-resistant, chemotherapy programs improves event-free survival in patients with Hodgkin lymphoma","volume":"119","author":"Moskowitz","year":"2012","journal-title":"Blood"},{"issue":"1","key":"2023111415103477900_bib31","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s00259-009-1297-4","article-title":"FDG PET and PET\/CT: EANM procedure guidelines for tumour PET imaging: version 1.0","volume":"37","author":"Boellaard","year":"2010","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"2","key":"2023111415103477900_bib32","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1007\/s00259-014-2961-x","article-title":"FDG PET\/CT: EANM procedure guidelines for tumour imaging: version 2.0","volume":"42","author":"Boellaard","year":"2015","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"suppl 1","key":"2023111415103477900_bib33","first-page":"1753","article-title":"Quantitative oncology molecular analysis suite: ACCURATE","volume":"59","author":"Boellaard","year":"2018","journal-title":"J\u00a0Nucl Med"},{"issue":"2","key":"2023111415103477900_bib34","doi-asserted-by":"crossref","first-page":"e0212223","DOI":"10.1371\/journal.pone.0212223","article-title":"An open source and easy to use radiomics calculator tool","volume":"14","author":"Pfaehler","year":"2019","journal-title":"PLoS One"},{"issue":"suppl 1","key":"2023111415103477900_bib35","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/s00259-017-3690-8","article-title":"FDG PET for therapy monitoring in Hodgkin and non-Hodgkin lymphomas","volume":"44","author":"Barrington","year":"2017","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"5","key":"2023111415103477900_bib36","doi-asserted-by":"crossref","first-page":"677","DOI":"10.2967\/jnumed.112.108530","article-title":"Reference range for intrapatient variability in blood-pool and liver SUV for 18F-FDG PET","volume":"54","author":"Boktor","year":"2013","journal-title":"J\u00a0Nucl Med"},{"issue":"27","key":"2023111415103477900_bib37","doi-asserted-by":"crossref","first-page":"3059","DOI":"10.1200\/JCO.2013.54.8800","article-title":"Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification","volume":"32","author":"Cheson","year":"2014","journal-title":"J\u00a0Clin Oncol"},{"issue":"23","key":"2023111415103477900_bib38","doi-asserted-by":"crossref","first-page":"2577","DOI":"10.1002\/sim.5328","article-title":"Misuse of DeLong test to compare AUCs for nested models","volume":"31","author":"Demler","year":"2012","journal-title":"Stat Med"},{"issue":"12","key":"2023111415103477900_bib39","doi-asserted-by":"crossref","first-page":"1740","DOI":"10.1016\/j.bbmt.2013.09.018","article-title":"Simplified validated prognostic model for progression-free survival after autologous transplantation for hodgkin lymphoma","volume":"19","author":"Hahn","year":"2013","journal-title":"Biol Blood Marrow Transplant"},{"issue":"3","key":"2023111415103477900_bib40","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1093\/annonc\/mdx791","article-title":"Autologous stem-cell transplantation after second-line brentuximab vedotin in relapsed or refractory Hodgkin lymphoma","volume":"29","author":"Herrera","year":"2018","journal-title":"Ann Oncol"},{"issue":"28","key":"2023111415103477900_bib41","doi-asserted-by":"crossref","first-page":"3109","DOI":"10.1200\/JCO.21.01056","article-title":"Phase II trial of pembrolizumab plus gemcitabine, vinorelbine, and liposomal doxorubicin as second-line therapy for relapsed or refractory classical Hodgkin lymphoma","volume":"39","author":"Moskowitz","year":"2021","journal-title":"J\u00a0Clin Oncol"},{"issue":"1","key":"2023111415103477900_bib42","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1182\/hematology.2022000365","article-title":"Do all patients with primary refractory\/first relapse of HL need autologous stem cell transplant?","volume":"2022","author":"Moskowitz","year":"2022","journal-title":"Hematology Am Soc Hematol Educ Program"},{"issue":"1","key":"2023111415103477900_bib43","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1186\/s13550-020-00717-y","article-title":"Correlations between baseline (18)F-FDG PET tumour parameters and circulating DNA in diffuse large B cell lymphoma and Hodgkin lymphoma","volume":"10","author":"Decazes","year":"2020","journal-title":"EJNMMI Res"},{"issue":"10","key":"2023111415103477900_bib44","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1016\/j.medj.2021.09.002","article-title":"In-depth cell-free DNA sequencing reveals genomic landscape of Hodgkin\u2019s lymphoma and facilitates ultrasensitive residual disease detection","volume":"2","author":"Sobesky","year":"2021","journal-title":"Med"},{"issue":"1","key":"2023111415103477900_bib45","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s13550-020-00744-9","article-title":"Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET","volume":"11","author":"Pfaehler","year":"2021","journal-title":"EJNMMI Res"}],"container-title":["Blood Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ashpublications.org\/bloodadvances\/article-pdf\/7\/21\/6732\/2089291\/blooda_adv-2023-010404-main.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/ashpublications.org\/bloodadvances\/article-pdf\/7\/21\/6732\/2089291\/blooda_adv-2023-010404-main.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T10:11:15Z","timestamp":1699956675000},"score":1,"resource":{"primary":{"URL":"https:\/\/ashpublications.org\/bloodadvances\/article\/7\/21\/6732\/497949\/Prognostic-model-using-18F-FDG-PET-radiomics"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,2]]},"references-count":45,"journal-issue":{"issue":"21","published-print":{"date-parts":[[2023,11,14]]}},"URL":"https:\/\/doi.org\/10.1182\/bloodadvances.2023010404","relation":{},"ISSN":["2473-9529","2473-9537"],"issn-type":[{"value":"2473-9529","type":"print"},{"value":"2473-9537","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,2]]}}}