{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T10:13:46Z","timestamp":1771496026481,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NIH\/NCI","award":["U01CA288351"],"award-info":[{"award-number":["U01CA288351"]}]},{"name":"NIH\/NCI","award":["U01CA231776"],"award-info":[{"award-number":["U01CA231776"]}]},{"name":"NIH\/NCI","award":["R01CA271540"],"award-info":[{"award-number":["R01CA271540"]}]},{"name":"NIH\/NCI","award":["R01EB028324"],"award-info":[{"award-number":["R01EB028324"]}]},{"name":"NIH\/NCI","award":["R01EB032680"],"award-info":[{"award-number":["R01EB032680"]}]},{"name":"NIH\/NCI","award":["R01CA279013"],"award-info":[{"award-number":["R01CA279013"]}]},{"name":"NIH\/NCI","award":["U54CA273956"],"award-info":[{"award-number":["U54CA273956"]}]},{"DOI":"10.13039\/100000005","name":"DoD","doi-asserted-by":"publisher","award":["W81XWH-21-1-0296"],"award-info":[{"award-number":["W81XWH-21-1-0296"]}],"id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Purpose: To develop prognostic models integrating delta radiomics from prostate-specific membrane antigen positron emission tomography\/computed tomography (PSMA-PET\/CT) and dosiomics with clinical variables to predict metastasis-free survival (MFS) in patients with localized prostate adenocarcinoma treated with androgen deprivation therapy and external-beam radiotherapy. Materials\/Methods: Delta-radiomics analysis included 43 patients. Radiomics features were extracted from the primary tumor on pre- and post-treatment PSMA-PET\/CT, and delta features were calculated as relative changes. Eight high-variance features were selected and combined with clinical variables (age, Gleason score, initial PSA, and a binary variable, indicating the occurrence of PSA relapse). Data was split 70:30 with training-set imbalance correction. Predictors that were significant in univariate Cox regression (p &lt; 0.05) were entered into multivariate Cox models, and five-year MFS was classified using a quadratic support vector machine. Dosiomics analysis included 48 patients. Dosiomics features were extracted from the planning target volume receiving 86 Gy and combined with pre-treatment radiomics and clinical variables using the same framework. Results: For delta radiomics, Model 1 (delta radiomics + pre-treatment radiomics + clinical) achieved the best performance (test c-score 0.58; AUC 0.70), exceeding Model 2 (pre-treatment radiomics + clinical; c-score 0.56; AUC 0.65) and Model 3 (clinical only; c-score 0.51; AUC 0.56). For dosiomics, Model 1 showed the highest performance (test c-score 0.56; AUC 0.67) compared with Model 2 (c-score 0.55; AUC 0.62) and Model 3 (c-score 0.50; AUC 0.54). Conclusions: Integrating delta radiomics or dosiomics with pre-treatment imaging and clinical variables improves MFS prediction and supports their role as non-invasive biomarkers for individualized radiotherapy in localized prostate cancer.<\/jats:p>","DOI":"10.3390\/cancers18040677","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T08:51:09Z","timestamp":1771491069000},"page":"677","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of Metastasis-Free Survival in Patients with Localized Prostate Adenocarcinoma Using Delta Radiomics from Pre-Treatment PSMA-PET\/CT Scans and Dosiomics"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9569-3513","authenticated-orcid":false,"given":"Apurva","family":"Singh","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William Silva","family":"Mendes","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7257-0350","authenticated-orcid":false,"given":"Sang-Bo","family":"Oh","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"},{"name":"Department of Internal Medicine, Division of Medical Oncology and Hematology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan 50612, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ozan Cem","family":"Guler","sequence":"additional","affiliation":[{"name":"Adana Dr Turgut Noyan Research and Treatment Center, Department of Radiation Oncology, Baskent University Faculty of Medicine, Adana 01250, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aysenur","family":"Elmali","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Baskent University Faculty of Medicine, Ankara 06490, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Birhan","family":"Demirhan","sequence":"additional","affiliation":[{"name":"Adana Dr Turgut Noyan Research and Treatment Center, Department of Radiation Oncology, Baskent University Faculty of Medicine, Adana 01250, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amit","family":"Sawant","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Phuoc","family":"Tran","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"},{"name":"Department of Genitourinary Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cem","family":"Onal","sequence":"additional","affiliation":[{"name":"Adana Dr Turgut Noyan Research and Treatment Center, Department of Radiation Oncology, Baskent University Faculty of Medicine, Adana 01250, Turkey"},{"name":"Department of Radiation Oncology, Baskent University Faculty of Medicine, Ankara 06490, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2384-5676","authenticated-orcid":false,"given":"Lei","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1001\/jamaoncol.2019.0096","article-title":"Assessment of 68Ga PSMA-11 PET Accuracy in Localizing Recurrent Prostate Cancer: A Prospective Single-Arm Clinical Trial","volume":"5","author":"Fendler","year":"2019","journal-title":"JAMA Oncol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.cpet.2024.03.001","article-title":"Prostate-specific Membrane Antigen: Diagnostics","volume":"19","author":"Alberts","year":"2024","journal-title":"PET Clin."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1007\/s00259-024-06847-y","article-title":"The association of quantitative PSMA PET parameters with pathologic ISUP grade: An international multicenter analysis","volume":"52","author":"Soeterik","year":"2024","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2537","DOI":"10.1007\/s00259-023-06195-3","article-title":"Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy","volume":"50","author":"Spohn","year":"2023","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111119","DOI":"10.1016\/j.radonc.2025.111119","article-title":"Prediction of metastasis-free survival in patients with localized prostate adenocarcinoma using primary tumor and lymph node radiomics from pre-treatment PSMA-PET\/CT scans","volume":"212","author":"Singh","year":"2025","journal-title":"Radiother. Oncol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: Images Are More than Pictures, They Are Data","volume":"278","author":"Gillies","year":"2016","journal-title":"Radiology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1007\/s00066-020-01679-9","article-title":"The role of radiomics in prostate cancer radiotherapy","volume":"196","author":"Delgadillo","year":"2020","journal-title":"Strahlenther. Onkol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1038\/s41598-017-00665-z","article-title":"Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer","volume":"7","author":"Fave","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"106987","DOI":"10.1016\/j.oraloncology.2024.106987","article-title":"Delta magnetic resonance imaging radiomics features-based nomogram predicts long-term efficacy after induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma","volume":"157","author":"Pan","year":"2024","journal-title":"Oral Oncol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1007\/s11547-022-01482-9","article-title":"Radiomics-based prediction of two-year clinical outcome in locally advanced cervical cancer patients undergoing neoadjuvant chemoradiotherapy","volume":"127","author":"Autorino","year":"2022","journal-title":"Radiol. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"111842","DOI":"10.1016\/j.apradiso.2025.111842","article-title":"MRI radiomics combined with delta-radiomics model for predicting pathological complete response in locally advanced rectal cancer patients after neoadjuvant chemoradiotherapy: A multi-institutional study","volume":"222","author":"Tian","year":"2025","journal-title":"Appl. Radiat. Isot."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Liang, B., Yan, H., Tian, Y., Chen, X., Yan, L., Zhang, T., Zhou, Z., Wang, L., and Dai, J. (2019). Dosiomics: Extracting 3D Spatial Features From Dose Distribution to Predict Incidence of Radiation Pneumonitis. Front. Oncol., 9.","DOI":"10.3389\/fonc.2019.00269"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e269","DOI":"10.1016\/j.clon.2024.03.003","article-title":"Radiomics for clinical decision support in radiation oncology","volume":"36","author":"Russo","year":"2024","journal-title":"Clin. Oncol. (R. Coll. Radiol.)"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"109983","DOI":"10.1016\/j.radonc.2023.109983","article-title":"Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non- small cell lung cancer patients treated with stereotactic radiation","volume":"190","author":"Thor","year":"2024","journal-title":"Radiother. Oncol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/s41698-019-0096-z","article-title":"A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer","volume":"3","author":"Nasief","year":"2019","journal-title":"NPJ Precis. Oncol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Cousin, F., Louis, T., Dheur, S., Aboubakar, F., Ghaye, B., Occhipinti, M., Vos, W., Bottari, F., Paulus, A., and Sibille, A. (2023). Radiomics and Delta-Radiomics Signatures to Predict Response and Survival in Patients with Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors. Cancers, 15.","DOI":"10.3390\/cancers15071968"},{"key":"ref_17","first-page":"e0800","article-title":"Radiomics Analysis for the Identification of Invasive Pulmonary Subsolid Nodules From Longitudinal Presurgical CT Scans","volume":"40","author":"Singh","year":"2025","journal-title":"J. Thorac. Imaging"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"20130617","DOI":"10.1259\/bjr.20130617","article-title":"Simultaneous integrated boost to intraprostatic lesions using different energy levels of intensity-modulated radiotherapy and volumetric-arc therapy","volume":"87","author":"Onal","year":"2014","journal-title":"Br. J. Radiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1158","DOI":"10.1002\/pros.24558","article-title":"Treatment outcomes of simultaneous integrated boost to intraprostatic lesions with external beam radiotherapy in localized prostate cancer patients","volume":"83","author":"Onal","year":"2023","journal-title":"Prostate"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","article-title":"Computational Radiomics System to Decode the Radiographic Phenotype","volume":"77","author":"Fedorov","year":"2017","journal-title":"Cancer Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Telecan, T., Chiorean, A., Sipos-Lascu, R., Caraiani, C., Boca, B., Hendea, R.M., Buliga, T., Andras, I., Crisan, N., and Lupsor-Platon, M. (2025). ISUP Grade Prediction of Prostate Nodules on T2WI Acquisitions Using Clinical Features, Textural Parameters and Machine Learning-Based Algorithms. Cancers, 17.","DOI":"10.3390\/cancers17122035"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"110443","DOI":"10.1016\/j.radonc.2024.110443","article-title":"Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics","volume":"199","author":"Cao","year":"2024","journal-title":"Radiother. Oncol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2806","DOI":"10.1007\/s00259-024-06734-6","article-title":"Development and validation of [18 F]- PSMA-1007 PET-based radiomics model to predict biochemical recurrence-free survival following radical prostatectomy","volume":"51","author":"Li","year":"2024","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1007\/s12149-025-02026-7","article-title":"The prognostic role of staging [18F]PSMA-1007 PET\/CT volumetric and dissemination features in prostate cancer","volume":"39","author":"Albano","year":"2025","journal-title":"Ann. Nucl. Med."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Flaiban, E., Orhan, K., Gon\u00e7alves, B.C., Lopes, S.L., and Costa, A.L. (2025). Radiomics in Action: Multimodal Synergies for Imaging Biomarkers. Bioengineering, 12.","DOI":"10.3390\/bioengineering12111139"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Jafari, E., Zarei, A., Dadgar, H., Keshavarz, A., Abdollahi, H., Samimi, R., Manafi-Farid, R., Nikkholgh, B., Fallahi, B., and Amini, H. (2025). Efficacy of PSMA PET\/CT radiomics analysis for risk stratification in newly diagnosed prostate cancer: A multicenter study. BMC Med. Imaging, 25.","DOI":"10.1186\/s12880-025-01914-8"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1177\/1724600819899665","article-title":"Correlating imaging parameters with molecular data: An integrated approach to improve the management of breast cancer patients","volume":"35","author":"Incoronato","year":"2020","journal-title":"Int. J. Biol. Markers"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Avanzo, M., Pirrone, G., Vinante, L., Caroli, A., Stancanello, J., Drigo, A., Massarut, S., Mileto, M., Urbani, M., and Trovo, M. (2020). Electron Density and Biologically Effective Dose (BED) Radiomics-Based Machine Learning Models to Predict Late Radiation-Induced Subcutaneous Fibrosis. Front. Oncol., 10.","DOI":"10.3389\/fonc.2020.00490"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Placidi, L., Gioscio, E., Garibaldi, C., Rancati, T., Fanizzi, A., Maestri, D., Massafra, R., Menghi, E., Mirandola, A., and Reggiori, G. (2021). A Multicentre Evaluation of Dosiomics Features Reproducibility, Stability and Sensitivity. Cancers, 13.","DOI":"10.3390\/cancers13153835"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lee, T.F., Chang, C.H., Chi, C.H., Liu, Y.H., Shao, J.C., Hsieh, Y.W., Yang, P.Y., Tseng, C.D., Chiu, C.L., and Hu, Y.C. (2024). Utilizing radiomics and dosiomics with AI for precision prediction of radiation dermatitis in breast cancer patients. BMC Cancer, 24.","DOI":"10.1186\/s12885-024-12753-1"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1038\/s41523-023-00574-7","article-title":"Radiomic predicts early response to CDK4\/6 inhibitors in hormone receptor positive metastatic breast cancer","volume":"9","author":"Khorrami","year":"2023","journal-title":"NPJ Breast Cancer"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1007\/s11547-024-01853-4","article-title":"Delta radiomics: An updated systematic review","volume":"129","author":"Nardone","year":"2024","journal-title":"Radiol. Med."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Midya, A., Hiremath, A., Huber, J., Sankar Viswanathan, V., Omil-Lima, D., Mahran, A., Bittencourt, L.K., Harsha Tirumani, S., Ponsky, L., and Shiradkar, R. (2023). Delta radiomic patterns on serial bi-parametric MRI are associated with pathologic upgrading in prostate cancer patients on active surveillance: Preliminary findings. Front. Oncol., 13.","DOI":"10.3389\/fonc.2023.1166047"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"20136","DOI":"10.1038\/s41598-022-24435-8","article-title":"Cone-beam CT delta-radiomics to predict genitourinary toxicities and international prostate symptom of prostate cancer patients: A pilot study","volume":"12","author":"Delgadillo","year":"2022","journal-title":"Sci. Rep."}],"container-title":["Cancers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6694\/18\/4\/677\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T08:57:20Z","timestamp":1771491440000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6694\/18\/4\/677"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,19]]},"references-count":34,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["cancers18040677"],"URL":"https:\/\/doi.org\/10.3390\/cancers18040677","relation":{},"ISSN":["2072-6694"],"issn-type":[{"value":"2072-6694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,19]]}}}