Prediction of Metastasis-Free Survival in Patients with Localized Prostate Adenocarcinoma Using Delta Radiomics from Pre-Treatment PSMA-PET/CT Scans and Dosiomics
Year: 2026
Type: article
Study design: Observational Study
Abstract: 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 < 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.
Source: Cancers
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,499
Awards: Integrating bioinformatics into multiscale models for hepatocellular carcinoma, Hybrid virtual-MRI/CBCT: A new paradigm for image guidance in liver SBRT, W81XWH-21-1-0296/NOVEL BIOMARKERS TO DIRECT STEREOTACTIC ABLATIVE RADIOTHERAPY IN CASTRATION-SENSITIVE OLIGOMETASTATIC PROSTATE CANCER., Bioinformatic-Chemical Approach to Credential Molecular Targets to Combat Rapid Chemo-Radiation Resistance in SCLC, Tumor-barcoding coupled with high-throughput sequencing for quantitative radiogenomics of the abscopal response in NSCLC, Radiation Oncology-Biology Integration Network on Oligometastasis (ROBIN OligoMET) Center, 3D In vivo dosimetry for FLASH proton therapy, 3-dimensional prompt gamma imaging for online proton beam dose verification, eXtended Modular ANthropomorphic (XMAN) phantom for Imaging and Treatment Optimization in Radiotherapy.
OpenAlex ID: W7130506511