Purpose
We propose a robust treatment planning model that simultaneously considers proton range and patient setup uncertainties and reduces high linear energy transfer (LET) exposure in organs at ...risk (OARs) to minimize the relative biological effectiveness (RBE) dose in OARs for intensity‐modulated proton therapy (IMPT). Our method could potentially reduce the unwanted damage to OARs.
Methods
We retrospectively generated plans for 10 patients including two prostate, four head and neck, and four lung cancer patients. The “worst‐case robust optimization” model was applied. One additional term as a “biological surrogate (BS)” of OARs due to the high LET‐related biological effects was added in the objective function. The biological surrogate was defined as the sum of the physical dose and extra biological effects caused by the dose‐averaged LET. We generated nine uncertainty scenarios that considered proton range and patient setup uncertainty. Corresponding to each uncertainty scenario, LET was obtained by a fast LET calculation method developed in‐house and based on Monte Carlo simulations. In each optimization iteration, the model used the worst‐case BS among all scenarios and then penalized overly high BS to organs. The model was solved by an efficient algorithm (limited‐memory Broyden–Fletcher–Goldfarb–Shanno) in a parallel computing environment. Our new model was benchmarked with the conventional robust planning model without considering BS. Dose–volume histograms (DVHs) of the dose assuming a fixed RBE of 1.1 and BS for tumor and organs under nominal and uncertainty scenarios were compared to assess the plan quality between the two methods.
Results
For the 10 cases, our model outperformed the conventional robust model in avoidance of high LET in OARs. At the same time, our method could achieve dose distributions and plan robustness of tumors assuming a fixed RBE of 1.1 almost the same as those of the conventional robust model.
Conclusions
Explicitly considering LET in IMPT robust treatment planning can reduce the high LET to OARs and minimize the possible toxicity of high RBE dose to OARs without sacrificing plan quality. We believe this will allow one to design and deliver safer proton therapy.
Some patients with unresectable or incompletely resected head-and-neck cancer (SCCHN) cannot tolerate radiochemotherapy. Alternatives are needed that are more effective than conventional radiotherapy ...alone.
This retrospective study investigated patients irradiated for non-metastatic stage IV SCCHN who could not receive concurrent chemotherapy. Eight patients received accelerated radiotherapy with concomitant boost (group A) and 31 patients conventionally fractionated radiotherapy (group B). Groups were matched for tumor site, gender, age, performance score and histologic grade.
Two-year PFS-rates were 63% in group A vs. 41% in group B, and median PFS-times were 36 vs. 10 months (p=0.48). Two-year OS-rates were 88% vs. 37%, and median OS-times were 44 vs. 14 months (p=0.19). Grade ≥2 radiation dermatitis was significantly (p=0.040) more common in group B; other toxicities were similar.
Accelerated fractionation with concomitant boost appeared superior to conventional fractionation and can be considered for patients with stage IV SCCHN not suitable for radiochemotherapy. Larger studies are needed to confirm these findings.
Background/Aim: Cutaneous squamous cell carcinoma (cSCC) is a common type of skin cancer. Options for palliative treatment include systemic agents and radiotherapy. Selection of a radiation regimen ...should consider the patient’s survival prognosis. This study aimed to identify prognostic factors of survival after palliative radiotherapy for cSCC of the head-and-neck. Patients and Methods: Ten factors were analyzed for survival in 12 patients including age, gender, tumor site, histological grade, primary tumor stage, lymph node involvement, distant metastases, upfront surgery, radiation dose and completion of radiotherapy. Results: On univariate analysis, improved survival was significantly associated with lower histological grade (better differentiation) (p=0.022), no distant metastases (p=0.040) and completion of radiotherapy (p=0.014). In the multivariate analysis, lower histological grade (risk ratio=6.05, p=0.100) and completion of radiotherapy (risk ratio=4.87, p=0.115) showed trends. Conclusion: Predictors of survival were identified that can help design individual treatments. Patients require optimal supportive care as completion of radiotherapy was associated with better survival.
Very elderly patients irradiated for bone metastases likely benefit from individualized treatments. A specific survival score was created for this group and compared to existing instruments.
...Ninety-six patients aged 80+ irradiated for bone metastases were retrospectively evaluated. Dose-fractionation regimen plus twelve characteristics were evaluated for survival.
In the Cox regression model, performance status and tumor type were significant and used for the score, which included three groups (5-7, 8-12, and 14 points) with 6-month survival rates of 15%, 52%, and 90%. Positive predictive values (PPVs) regarding death ≤6 months were 85% (new score), 100% (previous 65+ score), and 84% (previous score for any age). The new instrument and the 65+ score were also very accurate regarding survival. Since PPV regarding death was calculated from only four patients for the 65+ score, this PPV may be less conclusive than that for the new instrument.
The new score appears useful for patients aged 80+ irradiated for bone metastases.
Background
Deep learning auto‐segmentation (DLAS) models have been adopted in the clinic; however, they suffer from performance deterioration owing to the clinical practice variability. Some ...commercial DLAS software provide an incremental retraining function that enables users to train a custom model using their institutional data to account for clinical practice variability.
Purpose
This study was performed to evaluate and implement the commercial DLAS software with the incremental retraining function for definitive treatment of patients with prostate cancer in a multi‐user environment.
Methods
CT‐based target organs and organs‐at‐risk (OAR) delineation of 215 prostate cancer patients were utilized. The performance of three commercial DLAS software built‐in models was validated with 20 patients. A retrained custom model was developed using 100 patients and evaluated on the remaining data (n = 115). Dice similarity coefficient (DSC), Hausdorff distance (HD), mean surface distance (MSD), and surface DSC (SDSC) were utilized for quantitative evaluation. A multi‐rater qualitative evaluation was blindly performed with a five‐level scale. Visual inspection was performed in consensus and non‐consensus unacceptable cases to identify the failure modes.
Results
Three commercial DLAS vendor built‐in models achieved sub‐optimal performance in 20 patients. The retrained custom model had a mean DSC of 0.82 for prostate, 0.48 for seminal vesicles (SV), and 0.92 for rectum, respectively. This represents a significant improvement over the built‐in model with DSC of 0.73, 0.37, and 0.81 for the corresponding structures. Compared to the acceptance rate of 96.5% and consensus unacceptable rate (i.e., both reviewers rated as unacceptable) of 3.5% achieved by manual contours, the custom model achieved a 91.3% acceptance rate and 8.7% consensus unacceptable rate. The failure modes of retrained custom model were attributed to the following: cystogram (n = 2), hip prosthesis (n = 2), low dose rate brachytherapy seeds (n = 2), air in endorectal balloon(n = 1), non‐iodinated spacer (n = 2), and giant bladder(n = 1).
Conclusion
The commercial DLAS software with the incremental retraining function was validated and clinically adopted for prostate patients in a multi‐user environment. AI‐based auto‐delineation of the prostate and OARs is shown to achieve improved physician acceptance, overall clinical utility, and accuracy.
Background/Aim: Very elderly patients may benefit from individualized treatment. A survival score was created for patients aged 80+ receiving radiosurgery or fractionated stereotactic radiotherapy ...for 1-2 brain metastases. Patients and Methods: Thirteen patients were retrospectively evaluated. Characteristics showing significant associations with survival or trends were used for analysis. Prognostic groups were calculated from scoring points of these characteristics (0=worse, 1=better survival) added for each patient. Results: Survival was significantly associated with performance score (p=0.010). Trends were found for histology (p=0.066) and diameter of lesions (p=0.071). Three groups were created (0, 1-2, 3 points) with 6-month survival rates of 0%, 56%, and 100% (p=0.025). Positive predictive values (PPVs) to predict death ≤6 months were 100% with the new score vs. not available and 50% with previous scores; PPVs regarding survival ≥6 were 100% vs. 75% and 67%. Conclusion: Given its limitations, the score was more precise than previous tools and can serve for orientation in patients aged 80+.
Although omitting whole-brain radiotherapy (WBRT) during the treatment of few brain metastases more popular, many patients receive local therapies plus WBRT. WBRT may be less reasonable for patients ...with poor overall survival (OS), particularly if they are older. This study aimed to identify predictors of OS in these patients.
One-hundred-and-two older patients receiving a local therapy (surgery, radiosurgery, simultaneous integrated boost) and WBRT for 1-3 brain metastases were evaluated. Type of local therapy, WBRT-regimen, age, gender, performance status, primary tumour type, number of brain metastases, extra-cerebral metastasis, and interval from tumour diagnosis to treatment of brain metastases were analysed for OS.
Absence of extra-cerebral metastasis was significantly associated with increased OS on univariate analysis (p=0.001) and Cox regression analysis (risk ratio=2.13, p=0.002).
Extra-cerebral metastasis is an independent predictor of OS and can be helpful when assigning a treatment to older patients with few brain metastases.
Purpose
The dose‐averaged linear energy transfer (LETd) for intensity‐modulated proton therapy (IMPT) calculated by one‐dimensional (1D) analytical models deviates from more accurate but ...time‐consuming Monte Carlo (MC) simulations. We developed a fast hybrid three‐dimensional (3D) analytical LETd calculation that is more accurate than 1D analytical model.
Methods
We used the Geant4 MC code to generate 3D LETd distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LETd lateral profiles at various depths to the MC simulation. The 3D LETd calculation kernel was a lookup table of these fitted coefficients, and LETd was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LETd distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank‐sum test.
Results
The passing rate of 3D Gamma analysis comparing LETd distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LETd simultaneously using an Intel Xeon E5‐2680 2.50 GHz workstation was approximately 2.5 min.
Conclusions
Our new method significantly improved the LETd calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU‐based fast MC code.
Purpose/objectives
This retrospective study demonstrates the long-term outcomes of treating prostate cancer using intensity modulated (IMRT) with incorporation of MRI-directed boost.
...Materials/methods
From February 2009 to February 2013, 78 men received image-guided IMRT delivering 77.4 Gy in 44 fractions with simultaneously integrated boost to 81–83 Gy to an MRI-identified lesion. Patients with intermediate-risk or high-risk prostate cancer were recommended to receive 6 and 24–36 months of adjuvant hormonal therapy, respectively.
Results
Median follow-up was 113 months (11–147). There were 18 low-risk, 43 intermediate-risk, and 17 high-risk patients per NCCN risk stratification included in this study. Adjuvant hormonal therapy was utilized in 32 patients (41%). The 10-year biochemical control rate for all patients was 77%. The 10-year biochemical control rates for low-risk, intermediate-risk, and high-risk diseases were 94%, 81%, and 88%, respectively (p = 0.35). The 10-year rates of local control, distant control, and survival were 99%, 88%, and 66%, respectively. Of 25 patients who died, only four (5%) died of prostate cancer. On univariate analysis, T-category and pretreatment PSA level were associated with distant failure rate (p = 0.02). There was no grade =3 genitourinary and gastrointestinal toxicities that persisted at the last follow-up.
Conclusions
This study demonstrated the long-term efficacy of using MRI to define an intra-prostatic lesion for SIB to 81–83Gy while treating the entire prostate gland to 77.4 Gy with IMRT. Our study confirms that modern MRI can be used to locally intensify dose to prostate tumors providing high long-term disease control while maintaining favorable long-term toxicity.
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