BACKGROUND:Gleason score (GS) 7 prostate cancer (PCa) encompasses biologically heterogeneous subgroups with differing prognoses. This study aimed to assess long-term oncologic outcomes and develop a predictive nomogram for patients with GS 7 PCa treated with definitive radiotherapy (RT) with or without androgen deprivation therapy (ADT). METHODS:We retrospectively analysed the data of 372 patients with GS 7 PCa treated with RT between 2010 and 2020. Kaplan- Meier analysis was used to estimate freedom from biochemical failure (FFBF) and prostate cancer-specific survival (PCSS). Prognostic factors were identified using Cox regression models. A nomogram was constructed to predict individualised risks of FFBF and PCSS. Model performance was evaluated using time-dependent area under the curve (AUC), calibration plots and decision curve analysis. RESULTS:At a median follow-up of 102.6 months, the 8-year FFBF and PCSS rates were 88.2% and 96.3%, respectively. Patients with GS 4+3 had significantly poorer outcomes than those with GS 3+4 (FFBF: 84.3% vs. 91.1%, p = 0.010; PCSS: 92.1% vs. 98.5%, p = 0.002). Multivariable analysis revealed that young age (hazard ratio (HR): 0.95, p = 0.002), prostate specific antigen (PSA) >10 ng/mL (HR: 2.95, p = 0.010), GS 4+3 (HR: 2.67, p = 0.002) and absence of ADT (HR: 5.77, p < 0.001) were independently associated with an increased risk of biochemical failure. The final nomogram incorporating age, PSA, GS pattern, T stage, risk group, RT field, simultaneous integrated boost (SIB) use and ADT status showed excellent predictive performance, with 8-year time-dependent AUCs of 0.773 for FFBF and 0.914 for PCSS. Threshold scores > 0.5 for FFBF and > 1.06 for PCSS were associated with an increased event risk. CONCLUSIONS:GS 4+3 emerged as the strongest predictor of poor outcomes, alongside elevated PSA, absence of ADT and young age. The proposed nomogram provides accurate individualised risk stratification and may assist in tailoring treatment intensity and follow-up in patients with GS 7 PCa undergoing definitive RT. External validation is warranted.

Purpose:To evaluate clinical outcomes, patterns of failure, local control (LC), and time to next systemic therapy (TTNT) in patients with bone-only oligometastatic bladder cancer treated with stereotactic body radiotherapy (SBRT). Materials and Methods:We retrospectively analyzed 26 patients with 41 bone metastases treated with SBRT between 2012 and 2020 across four institutions. All patients had ≤3 bone metastases and received metastasis-directed therapy to all lesions. Overall survival (OS), progression-free survival (PFS), TTNT, and LC were estimated using the Kaplan-Meier method. Results:After a median follow-up of 97.8 months, median OS was 8.9 months, with 1- and 2-year OS rates of 38.5% and 22.4%, respectively. Median PFS was 5.8 months, with 1- and 2-year PFS rates of 29.4% and 25.2%, respectively. Median TTNT was 4.4 months, and only 19.8% of patients remained free from systemic therapy at 1 year. Disease progression occurred in 46.2% of patients and was predominantly distant metastasis. In contrast, LC was excellent, with 1- and 2-year rates of 94.7% and 88.0%, respectively. No grade ≥ 3 toxicities were observed. Conclusion:SBRT achieved excellent LC with minimal toxicity. However, systemic progression remained common. These findings suggest that prospective studies are needed to determine the role of SBRT within multimodal treatment strategies for bone-only oligometastatic bladder cancer.

OBJECTIVE We analyzed the dosimetric performance of Helical Tomotherapy (HT) and Volumetric Modulated Arc Therapy (VMAT) for postmastectomy chest wall irradiation (CWI) in patients with left-sided breast cancer, with a particular focus on target volume coverage, organ-at-risk (OAR) sparing, and low-dose exposure to surrounding normal tissues. METHODS Twenty patients with left-sided breast cancer who received postmastectomy CWI and regional nodal irradiation were retrospectively evaluated. For each patient, HT and VMAT treatment plans were generated. Dosimetric parameters assessed included planning target volume (PTV) coverage, conformity index (CI), homogeneity index (HI), and dose-volume metrics for OARs. Low-dose exposure to normal tissues was quantified using V-10Gy and V-25Gy. Statistical comparisons were performed using the Mann-Whitney U test. RESULTS Both techniques achieved clinically acceptable PTV coverage and comparable HI. VMAT plans demonstrated significantly better CI than HT (CI: 0.79 +/- 0.04 vs. 0.64 +/- 0.03; p<0.001). VMAT was associated with significantly lower high-dose exposure to the ipsilateral lung (V-20Gy and V-30Gy) and heart, and reduced mean dose to the contralateral breast. The VMAT plans also resulted in significantly lower low-dose body volumes (V-10Gy and V-25Gy.) compared to HT. Additionally, VMAT required fewer monitor units and shorter treatment times. CONCLUSION Both HT and VMAT are effective for chest wall irradiation in left-sided breast cancer; however, VMAT provides superior dose conformity, improved OAR sparing, and reduced low-dose exposure. These findings support the preferential use of VMAT in clinical settings where minimization of normal tissue exposure and treatment efficiency are priorities.

Objective To explore the imaging biomarkers obtained from baseline multi-modality imaging PET/ CT before metastasis-directed therapy (MDT), which could offer early response prediction before MDT treatment, optimizing patient management and improving outcomes. Methods The study analyzed a multi-institutional cohort of 118 patients with oligometastatic castration-sensitive prostate cancer (omCSPC), including 34 from Johns Hopkins Hospital (JHH) and 84 from Baskent University (BU), all treated with stereotactic ablative radiation therapy SABR-MDT. Before MDT, all patients underwent PSMA PET and CT imaging. For radiomics analysis, the gross tumor volume (GTV) was defined as zone 1, with an additional 5 mm peritumoral expansion designated as zone 2. From these regions, 1308 radiomics features were extracted. Feature selection was performed using a mutual information function, identifying the five most informative radiomics features from prostate-specific membrane antigen (PSMA) PET and CT. These were combined with five key clinical parameters—age, Gleason score, total number of lesions, number of untreated lesions, ADT, and pre-MDT prostate-specific antigen (PSA)—as model inputs. Multiple machine-learning algorithms, including random forest, decision tree, support vector machine, and naïve Bayes, were applied to predict 2-year metastasis-free survival (MFS). Model performance was evaluated using both leave-one-out and cross-institution validation. Results In a leave-one-out test with 93 patients, random forest achieved 78% accuracy and an AUC of 0.80 in predicting 2-year MFS. In cross-institution validation with 61 BU and 32 JHH patients, random forest correctly predicted 2-year MFS for 69% and 71% of patients, with AUC values of 0.71 and 0.73, respectively. Kaplan Meier curve comparison shows statistically significant separation between “rapid progressors” and “non-rapid progressors” patients stratified by the model in both leave one out and cross-institution validation tests. Conclusion This study provides evidence that pre-treatment multi-modality imaging biomarkers derived from PSMA PET and CT can serve as valuable predictors of metastasis-free survival (MFS) in patients with omCSPC.

Metastasis-directed therapy (MDT) is an emerging treatment option for metachronous oligometastatic castration-sensitive prostate cancer (omCSPC) and can delay time to progression and the need to initiate androgen deprivation therapy (ADT). However, optimal ways to synergize MDT and ADT are not known, and better personalization of MDT is needed. We examined the role of combined ADT and MDT and the ability of genomic alterations to provide prognostic and predictive information regarding response to MDT. We found that high-risk (HiRi) mutations in TP53, BRCA1/2, ATM, and Rb1 are poor prognostic markers in omCSPC. In addition, patients harboring HiRi mutations experienced greater benefit from addition of ADT to MDT, indicating that these alterations are predictive biomarkers for treatment intensification. Our results suggest that genetic biomarkers might aid in treatment personalization for patients with omCSPC.

Purpose:Incidental pelvic nodal irradiation is an unavoidable consequence of bladder-only radiotherapy (RT) and may contribute to the irradiation of occult microscopic disease. We characterized incidental pelvic nodal dose and compared regional dose distributions between volumetric modulated arc therapy (VMAT) and step-and-shoot intensity-modulated RT (IMRT). Materials and Methods:Planning computed tomography datasets from 30 patients receiving bladder-only RT were used to generate paired VMAT and step-and-shoot IMRT plans. Pelvic nodal regions, including the common iliac, external iliac, internal iliac, obturator, and presacral basins, were contoured according to consensus guidelines. Composite and region-specific dose-volume histogram parameters were compared between techniques using paired analyses. Treatment delivery efficiency was evaluated by monitor units (MUs). Results:Both techniques achieved equivalent target coverage and comparable incidental pelvic nodal dose distributions. A consistent regional hierarchy of incidental nodal irradiation was observed, with the obturator, external iliac, internal iliac, and common iliac regions receiving approximately 75%, 45%, 25%, and < 5% of the prescribed dose, respectively. These patterns remained remarkably consistent regardless of delivery technique. Although small statistically significant differences were identified for selected regional dose-volume parameters, the magnitude of these differences was generally less than 1 Gy and was considered unlikely to be clinically meaningful. VMAT required significantly fewer MUs than step-and-shoot IMRT (median 914 vs. 1123, p < 0.001). Conclusions:Bladder-only RT produces a reproducible regional pattern of incidental pelvic nodal irradiation that is largely independent of delivery technique. The observed consistency across techniques suggests that incidental nodal exposure may be influenced more by target geometry than by the delivery technique.

BACKGROUND:Diffusion-weighted magnetic resonance imaging (MRI)-derived apparent diffusion coefficient (ADC) has been investigated as a biomarker in prostate cancer, yet its prognostic relevance after definitive radiotherapy remains uncertain. We evaluated the association of post-treatment ADC with long-term oncologic outcomes in patients treated with modern radiotherapy techniques, including focal dose escalation. PATIENTS AND METHODS:We retrospectively analyzed 337 intermediate- or high-risk prostate cancer patients treated with definitive radiotherapy plus androgen deprivation therapy. Post-treatment MRI was performed 3-6 months after radiotherapy. Progression-free survival (PFS) was analyzed using Cox regression, and prostate cancer-specific survival (PCSS) using Fine-Gray competing-risk regression. Prognostic performance of pretreatment ADC, post-treatment ADC, and percentage ADC change (ΔADC) was assessed using receiver operating characteristic analysis, Bayesian Information Criterion (BIC), calibration, and decision-curve analysis. RESULTS:After a median follow-up of 11.7 years, 63 patients (18.7%) experienced disease progression. Pretreatment ADC was not associated with outcomes. In contrast, low post-treatment ADC was independently associated with inferior PFS (P < 0.05). Incorporation of post-treatment ADC improved model fit (PFS BIC: 491.6 vs. 379.9) and enhanced early-term discrimination and clinical net benefit. Radiotherapy incorporating simultaneous integrated boost was associated with greater post-treatment ADC increases and improved oncologic outcomes. Post-treatment ADC did not retain independent prognostic significance for PCSS. CONCLUSIONS:Post-treatment ADC provides prognostic information beyond established clinical factors following definitive radiotherapy for prostate cancer. While not a standalone predictor, it may support imaging-informed post-treatment risk stratification pending prospective validation.

Objective::To compare dimensionality-reduction methods for building prognostic models predicting metastasis-free survival (MFS) in localized prostate adenocarcinoma (PCa) patients treated with androgen-deprivation therapy and external radiotherapy using clinical factors and prostate-specific membrane antigen (PSMA)-PET/CT radiomics from primary tumor and nodal volumes.Methods::A total of 134 localized PCa patients (28 with nodal involvement) were analyzed. Gross tumor volumes for primary tumors (GTVp) and nodes (GTVn) were segmented on CT and PET scans; a 5-mm peritumoral ring was defined. Radiomic features were normalized and reduced using three techniques: principal component analysis (PCA), supervised, and unsupervised feature selection. Model 1 combined tumor and nodal radiomics via volume-weighted averaging and consisted of 12 predictors including clinical variables (age, Gleason score, initial PSA, PSA relapse) and radiomics from primary, nodal, and ring regions. Data imbalance (24 metastasis, 110 no metastasis) was addressed using a 70:30 train-test split with imbalance correction applied to train set. Univariate Cox regression ( P < 0.05) identified top predictors from train set; multivariate Cox regression was performed on corrected training data and applied to test data. Model 2 used clinical variables and radiomics from GTVp + ring; Model 3 used clinical data alone. Binary classification for five-year MFS was also evaluated. Results::Supervised feature selection achieved highest performance. Model 1 test had c-score 0.71 (0.65-0.72). The five-year MFS test classification was sensitivity 80.1 %, specificity 85.4 %, and AUC 0.84. Unsupervised and PCA methods showed slightly lower results (test c-scores: 0.70 and 0.69, respectively). Model 1 consistently outperformed Model 2 with c-score 0.64 and AUC 0.79, as well as Model 3 with c-score 0.54 and AUC 0.68 across all dimensionality-reduction techniques.Conclusion::Supervised feature selection yielded the highest c-scores and AUCs for the models. Integrating PSMA-PET/CT radiomics from primary, nodal, and peritumoral regions with clinical factors significantly improved MFS prediction, highlighting multi-regional radiomics as a promising biomarker for personalized therapy in prostate cancer.

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.

Background/Objectives: Teriflunomide is an active metabolite of leflunomide and acts as a selective and reversible inhibitor of dihydroorotate dehydrogenase, a key enzyme in de novo pyrimidine biosynthesis. It exhibits immunomodulatory activity by reducing the proliferation of activated T and B lymphocytes and is widely used in the treatment of rheumatoid arthritis and relapsing multiple sclerosis. This study aimed to develop a rapid, accurate, and simple high-performance liquid chromatography (HPLC) method with fluorometric detection for quantifying teriflunomide in human plasma. Methods: Plasma samples were prepared by liquid–liquid extraction followed by pre-column derivatization with NBD-Cl. Teriflunomide was derivatized with 4-chloro-7-nitrobenzofurazan (NBD-Cl) and separated using a reversed-phase C18 column (5 µm, 4.6 × 150 mm) at 30 °C with isocratic elution. The mobile phase consisted of acetonitrile and 0.1% orthophosphoric acid (80:20, v/v) at a flow rate of 1.1 mL/min. Fluorescence detection was performed at λex = 465 nm and λem = 535 nm. The method meets European Medicines Agency (EMA) guidelines for bioanalytical validation and was successfully applied to pharmacokinetic studies, including AUC0–t, AUC0–∞, Cmax, Tmax, and t½. Results: Teriflunomide showed a retention time of 2.55 ± 0.01 min. The method exhibited linearity in the range of 0.01–30 ng/mL (r2 = 0.9998), with a limit of detection and quantification of 0.003 and 0.01 ng/mL, respectively. The relative standard deviation was 3.27%. Conclusions: This work introduces a novel, cost-effective, and highly sensitive HPLC with fluorescence detection (HPLC-FL) method for the determination of teriflunomide in human plasma, providing an efficient alternative to LC-MS/MS for routine pharmacokinetic and bioequivalence studies.

BACKGROUND:Unfavorable intermediate-risk prostate cancer (UIR-PCa) represents a biologically heterogeneous subgroup with a higher risk of recurrence compared with favorable intermediate-risk disease. Contemporary management frequently includes dose-escalated radiotherapy (RT) combined with short-term androgen deprivation therapy (ADT). Whether additional intraprostatic dose escalation using a simultaneous integrated boost (SIB) provides incremental oncologic benefit in this setting remains uncertain. METHODS:We retrospectively analyzed 194 patients with UIR-PCa treated at three institutions between 2010 and 2023. All patients received image-guided intensity-modulated or volumetric modulated arc RT to 78 Gy with short-term ADT. An MRI-guided intraprostatic SIB (up to 86 Gy) was delivered in 77 patients (39.7%) at clinician discretion. Primary endpoints were biochemical recurrence-free survival (bRFS), distant metastasis-free survival (DMFS), and prostate cancer-specific mortality (PCSM). Multivariable Cox and competing-risk regression models were used to assess predictors of outcome. RESULTS:After a median follow-up of 105 months, 8-year bRFS and DMFS rates for the entire cohort were 93.7% and 95.7%, respectively. Addition of SIB was not associated with improved bRFS (93.5% vs 93.6%, p = 0.36), DMFS (94.6% vs 96.7%, p = 0.15), or PCSM. Percent positive biopsy cores ≥ 50% was the only independent predictor of inferior bRFS on multivariable analysis. Treatment-related toxicity was low in both groups, with no significant differences in late grade ≥ 2 gastrointestinal or genitourinary toxicity. CONCLUSIONS:In patients with UIR-PCa uniformly treated with dose-escalated, image-guided RT and short-term ADT, long-term oncologic outcomes were excellent. The addition of an intraprostatic SIB was safe but did not confer measurable improvement in biochemical or distant disease control. These findings support a selective rather than routine use of focal intraprostatic dose escalation in contemporary UIR-PCa management.