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PurposeIn a randomized focal dose escalation radiation therapy trial for prostate cancer (FLAME), up to 95 Gy was prescribed to the tumor in the dose-escalated arm, with 77 Gy to the entire prostate in both arms. As dose constraints to organs at risk had priority over dose escalation and suboptimal planning could occur, we investigated how well the dose to the tumor was boosted. We developed an anatomy-based prediction model to identify plans with suboptimal tumor dose and performed replanning to validate our model.Methods and MaterialsWe derived dose-volume parameters from planned dose distributions of 539 FLAME trial patients in 4 institutions and compared them between both arms. In the dose-escalated arm, we determined overlap volume histograms and derived features representing patient anatomy. We predicted tumor D98% with a linear regression on anatomic features and performed replanning on 21 plans.ResultsIn the dose-escalated arm, the median tumor D50% and D98% were 93.0 and 84.7 Gy, and 99% of the tumors had a dose escalation greater than 82.4 Gy (107% of 77 Gy). In both arms organs at risk constraints were met. Five out of 73 anatomic features were found to be predictive for tumor D98%. Median predicted tumor D98% was 4.4 Gy higher than planned D98%. Upon replanning, median tumor D98% increased by 3.0 Gy. A strong correlation between predicted increase in D98% and realized increase upon replanning was found (ρ = 0.86).ConclusionsFocal dose escalation in prostate cancer was feasible with a dose escalation to 99% of the tumors. Replanning resulted in an increased tumor dose that correlated well with the prediction model. The model was able to identify tumors on which a higher boost dose could be planned. The model has potential as a quality assessment tool in focal dose escalated treatment plans.

Purpose For focal boost strategies in the prostate, the robustness of magnetic resonance imaging—based tumor delineations needs to be improved. To this end we developed a statistical model that predicts tumor presence on a voxel level (2.5×2.5×2.5 mm3) inside the peripheral zone. Furthermore, we show how this model can be used to derive a valuable input for radiotherapy treatment planning. Methods and Materials The model was created on 87 radiotherapy patients. For the validation of the voxelwise performance of the model, an independent group of 12 prostatectomy patients was used. After model validation, the model was stratified to create three different risk levels for tumor presence: gross tumor volume (GTV), high-risk clinical target volume (CTV), and low-risk CTV. Results The model gave an area under the receiver operating characteristic curve of 0.70 for the prediction of tumor presence in the prostatectomy group. When the registration error between magnetic resonance images and pathologic delineation was taken into account, the area under the curve further improved to 0.89. We propose that model outcome values with a high positive predictive value can be used to define the GTV. Model outcome values with a high negative predictive value can be used to define low-risk CTV regions. The intermediate outcome values can be used to define a high-risk CTV. Conclusions We developed a logistic regression with a high diagnostic performance for voxelwise prediction of tumor presence. The model output can be used to define different risk levels for tumor presence, which in turn could serve as an input for dose planning. In this way the robustness of tumor delineations for focal boost therapy can be greatly improved.

Purpose To investigate the association between prostate specific antigen (PSA) bounce and disease outcome after prostate brachytherapy. Methods and Materials We analyzed 975 patients treated with 125 I implantation monotherapy between 1992 and 2006. All patients had tumor Stage ≤2c, Gleason score ≤7 prostate cancer, a minimum follow-up of 2 years with at least four PSA measurements, and no biochemical failure in the first 2 years. Median follow-up was 6 years. Bounce was defined as a PSA elevation of +0.2 ng/mL with subsequent decrease to previous nadir. We used the Phoenix +2 ng/mL definition for biochemical failure. Additional endpoints were disease-specific and overall survival. Multivariate Cox regression analysis was performed to adjust for potential confounding factors. Results Bounce occurred in 32% of patients, with a median time to bounce of 1.6 years. More than 90% of bounces took place in the first 3 years after treatment and had disappeared within 2 years of onset. Ten-year freedom from biochemical failure, disease-specific survival, and overall survival rates were, respectively, 90%, 99%, and 88% for the bounce group and 70%, 93%, and 82% for the no-bounce group. Only 1 patient (0.3%) died of prostate cancer in the bounce group, compared with 40 patients (6.1%) in the no-bounce group. Adjusted for confounding, a 70% biochemical failure risk reduction was observed for patients experiencing a bounce (hazard ratio 0.31; 95% confidence interval 0.20–0.48). Conclusions A PSA bounce after prostate brachytherapy is strongly related to better outcome in terms of biochemical failure, disease-specific survival, and overall survival.

Acute urinary retention (AUR) after iodine-125 (I-125) prostate brachytherapy negatively influences long-term quality of life and therefore should be prevented. We aimed to develop a nomogram to preoperatively predict the risk of AUR.Using the preoperative data of 714 consecutive patients who underwent I-125 prostate brachytherapy between 2005 and 2008 at our department, we modeled the probability of AUR. Multivariate logistic regression analysis was used to assess the predictive ability of a set of pretreatment predictors and the additional value of a new risk factor (the extent of prostate protrusion into the bladder). The performance of the final model was assessed with calibration and discrimination measures.Of the 714 patients, 57 patients (8.0%) developed AUR after implantation. Multivariate analysis showed that the combination of prostate volume, IPSS score, neoadjuvant hormonal treatment and the extent of prostate protrusion contribute to the prediction of AUR. The discriminative value (receiver operator characteristic area, ROC) of the basic model (including prostate volume, International Prostate Symptom Score, and neoadjuvant hormonal treatment) to predict the development of AUR was 0.70. The addition of prostate protrusion significantly increased the discriminative power of the model (ROC 0.82). Calibration of this final model was good. The nomogram showed that among patients with a low sum score (18 points), the risk of AUR was only 0%-5%. However, in patients with a high sum score (35 points), the risk of AUR was more than 20%.This nomogram is a useful tool for physicians to predict the risk of AUR after I-125 prostate brachytherapy. The nomogram can aid in individualized treatment decision-making and patient counseling.

To assess the influence of dose in different prostate regions, and the influence of anatomic variation on the risk of acute urinary retention (AUR) after I-125 prostate brachytherapy.In this case-control study, dosimetry and anatomy were compared between 50 patients with AUR (cases) and 50 patients without AUR (controls). Cases and controls were randomly selected from our database. The following structures were delineated on magnetic resonance imaging: prostate, urethra, peripheral zone, transitional zone, apex, base, midprostate, lower sphincter, and bladder neck. The dosimetric parameters analyzed were D(10), D(50), D(90), V(100), V(150), and V(200). The anatomic parameters analyzed were prostate protrusion into the bladder, bladder overlap, urethra angle, and urethra-bladder angle. The delineator was blinded to the patient's AUR status. Logistic regression analysis was used to investigate the association of these factors with AUR.The dose delivered to different regions of the prostate was not significantly associated with the risk of AUR. Only dose to the bladder neck was significantly associated with AUR (odds ratio 1.13 per 10 Gy; 95% CI 1.02;1.26; p = 0.023). Mean bladder neck D(90) was 65 Gy in AUR cases vs. 56 Gy in controls (p = 0.016), and mean bladder neck D(10) was 128 Gy vs. 107 Gy, respectively (p = 0.018). Furthermore, on univariate analysis, a larger extent of both bladder overlap and of prostate protrusion were associated with a higher risk of AUR (odds ratio 1.16; 95% CI 1.04-1.28; p = 0.005, and odds ratio 1.83; 95% CI 1.37-2.45; p0.001, respectively). The mean extent of prostate protrusion was 3.5 mm in AUR cases vs. 1.0 mm in controls (p0.001). Odds ratios did not change substantially after adjustment for potential confounders. On multivariate analysis, the extent of prostate protrusion seemed to be a stronger risk factor for AUR than bladder overlap.The risk of AUR is not associated with dose delivered to different regions of the prostate. However, a higher dose to the bladder neck and a larger extent of prostate protrusion into the bladder are risk factors for the development of AUR after I-125 prostate brachytherapy.

Purpose: To assess the influence of dose on the risk of acute urinary retention (AUR) after iodine-125 prostate brachytherapy. Methods and Materials: Between January 2005 and December 2008, 714 consecutive patients with localized prostate cancer were treated with iodine-125 prostate brachytherapy at our department. All patients completed four imaging studies: magnetic resonance imaging before and 4 weeks after treatment and intraoperative three-dimensional transrectal ultrasonography before and after implantation. The development of AUR was prospectively recorded. The evaluated treatment and dosimetric parameters included prostate volume, number of needles and seeds used, intra- and postoperative prostate edema, percentage of prostate volume receiving 100%, 150%, and 200% of the prescribed dose to the prostate, minimal dose received by 90% of the prostate volume, and percentage of the urethra receiving 100%, 150%, and 200% of the prescribed dose. Logistic regression analysis was used to examine which factors were associated with AUR. Results: Of the 714 patients, 57 (8.0%) developed AUR. On univariate analysis, the following treatment and dosimetric factors were significantly associated with AUR: International Prostate Symptom Score (odds ratio [OR], 2.07, per 10-point increase), preimplant prostate volume (OR, 1.06), postimplant prostate volume (OR, 1.04), number of needles used (OR, 1.09), and number ofmore » seeds used (OR, 1.03). On multivariate analysis, the only independent predictive factors for AUR were pretreatment prostate volume (OR, 1.05) and International Prostate Symptom Score (OR, 1.76, per 10-point increase). Patients with a pretreatment prostate volume >35 cm{sup 3} had a 10.4% risk of developing AUR compared with 5.4% for those with a prostate volume of {

Purpose: To evaluate the impact of acute urinary retention (AUR) in patients treated with {sup 125}I prostate brachytherapy on short- and long-term health-related quality of life (HRQOL); and to assess whether pretreatment HRQOL has additional value in the prediction of AUR. Methods and Materials: For 127 patients treated with {sup 125}I brachytherapy for localized prostate cancer between December 2000 and June 2003, toxicity and HRQOL data were prospectively collected. Patients received a HRQOL questionnaire at five time points: before and 1 month, 6 months, 1 year, and 6 years after treatment. The questionnaire included the RAND-36 generic health survey, the cancer-specific European Organization for Research and Treatment of Cancer core questionnaire (EORTC QLQ-C30), the tumor-specific EORTC prostate cancer module (EORTC QLQ-PR25), and the American Urological Association (AUA) symptom index. Results: Of 127 patients, 13 (10.2%) developed AUR. Patients with AUR had a significantly worse urinary QOL at all time points compared with patients without AUR. The mean difference over time (6 years) between both groups for the EORTC QLQ-PR25 urinary symptom score was 13.0 points (p < 0.001) and for the AUA urinary symptom score was 15.7 points (p = 0.001). Global QOL scores (EORTC QLQ-C30) over time for patientsmore » who developed AUR were significantly worse compared with patients without AUR (mean difference 6.7 points; p = 0.043). In multivariate logistic regression analysis, pretreatment International Prostate Symptom Score (p = 0.004) and neoadjuvant hormonal treatment (p = 0.034) were predictors of AUR. Quality of life did not have added predictive value. Conclusion: Acute urinary retention after prostate brachytherapy has a significant negative impact on patient's HRQOL up to 6 years after treatment, in terms of both global QOL measures and urinary symptom scores. Furthermore, our results suggest limited value of pretreatment HRQOL measures for the prediction of AUR.« less