Preliminary result of combined treatment with scanning carbon-ion radiotherapy and image-guided brachytherapy for locally advanced cervical adenocarcinoma.

Although there is growing evidence of the efficacy of carbon-ion radiotherapy (CIRT) for locally advanced cervical adenocarcinoma, reports on combined treatment with CIRT and image-guided brachytherapy (IGBT) are scarce. We retrospectively analyzed patients with International Federation of Gynecology and Obstetrics (2008) stage II-IVA locally advanced cervical adenocarcinoma who received combined scanning CIRT (sCIRT) and IGBT between April 2019 and March 2022. sCIRT consisted of whole-pelvic irradiation with 36 Gy (relative biological effectiveness [RBE]) in 12 fractions and subsequent local boost irradiation with 19.2 Gy (RBE) in 4 fractions. Three sessions of IGBT were administered after completion of sCIRT. Concurrent chemotherapy using weekly cisplatin (40 mg/m2/week) was also administered. Efficacy, toxicity and dose-volume parameters were analyzed. Fifteen patients were included in the analysis. The median follow-up period was 25 months. The 2-year overall survival, progression-free survival and local control rates were 92.3% (95% confidence interval [CI] = 77.8-100%), 52.5% (95% CI = 26.9-78.1%) and 84.8% (95% CI = 65.2-100%), respectively. Neither severe acute toxicity necessitating treatment cessation nor grade 3 or higher late toxicity were observed. The sigmoid D2cm3 of the patient who developed grade 2 late sigmoid hemorrhage was 65.6 Gy, which exceeded the standard deviation and target dose. The combination of sCIRT and IGBT for locally advanced cervical adenocarcinoma showed acceptable efficacy and safety. Further large-scale and long-term studies are warranted to confirm the efficacy and safety of this treatment.

Evaluation of prediction and classification performances in different machine learning models for patient-specific quality assurance of head-and-neck VMAT plans.

PURPOSE: The purpose of this study is to evaluate the prediction and classification performances of the gamma passing rate (GPR) for different machine learning models and to select the best model for achieving machine learning-based patient-specific quality assurance (PSQA). METHODS: The measurement verification of 356 head-and-neck volumetric modulated arc therapy plans was performed using a diode array phantom (Delta4 Phantom), and GPR values at 2%/2 mm with global normalization and 3%/2 mm with local normalization were calculated. Machine learning models, including ridge regression (RIDGE), random forest (RF), support vector regression (SVR), and stacked generalization (STACKING), were used to predict the GPR. Each machine learning model was trained using 260 plans, and the prediction accuracy was evaluated using the remaining 96 plans. The prediction error between the measured and predicted GPR was evaluated. For the classification evaluation, the lower control limit for the measured GPR and lower control limit for predicted GPR (LCLp ) was defined to identify whether the GPR values represent a "pass" or a "fail." LCLp values with 99% and 99.9% confidence levels were calculated as the upper prediction limits for the GPR estimated from the linear regression between the measured and predicted GPR. RESULTS: There was an overestimation trend of the low measured GPR. The maximum prediction errors for RIDGE, RF, SVR, and STACKING were 3.2%, 2.9%, 2.3%, and 2.2% at the global 2%/2 mm and 6.3%, 6.6%, 6.1%, and 5.5% at the local 3%/2 mm, respectively. In the global 2%/2 mm, the sensitivity was 100% for all the machine learning models except RIDGE when using 99% LCLp . The specificity was 76.1% for RIDGE, RF, and SVR and 66.3% for STACKING; however, the specificity decreased dramatically when 99.9% LCLp was used. In the local 3%/2 mm, however, only STACKING showed 100% sensitivity when using 99% LCLp . The decrease in the specificity using 99.9% LCLp was smaller than that in the global 2%/2 mm, and the specificity for RIDGE, RF, SVR, and STACKING was 61.3%, 61.3%, 72.0%, and 66.8%, respectively. CONCLUSIONS: STACKING had better prediction accuracy for low GPR values than other machine learning models. Applying LCLp to a regression model enabled the consistent evaluation of quantitative and qualitative GPR predictions. Adjusting the confidence level of the LCLp helped improve the balance between the sensitivity and specificity. We suggest that STACKING can assist the safe and efficient operation of PSQA.

Robust treatment planning in scanned carbon-ion radiotherapy for pancreatic cancer: Clinical verification using in-room computed tomography images.

Purpose: Carbon-ion beam (C-beam) has a sharp dose distribution called the Bragg peak. Carbon-ion radiation therapy, such as stereotactic body radiotherapy in photon radiotherapy, can be completed in a short period by concentrating the radiation dose on the tumor while minimizing the dose to organs at-risk. However, the stopping position of C-beam is sensitive to density variations along the beam path and such variations can lower the tumor dose as well as cause the delivery of an unexpectedly high dose to the organs at risk. We evaluated the clinical efficacy of a robust planning technique considering gastrointestinal gas (G-gas) to deliver accurate radiation doses in carbon-ion radiotherapy for pancreatic cancer. Materials and methods: We focused on the computed tomography (CT) value replacement method. Replacement signifies the overwriting of CT values in the CT images. The most effective replacement method for robust treatment planning was determined by verifying the effects of the three replacement patterns. We selected 10 consecutive patients. Pattern 1 replaces the CT value of the G-gas contours with the value of the region without G-gas (P1). This condition indicates a no-gas state. Pattern 2 replaces each gastrointestinal contour using the mean CT value of each contour (P2). The effect of G-gas was included in the replacement value. Pattern 3 indicates no replacement (P3). We analyzed variations in the target coverage (TC) and homogeneity index (HI) from the initial plan using in-room CT images. We then performed correlation analysis on the variations in G-gas, TC, and HI to evaluate the robustness against G-gas. Results: Analysis of variations in TC and HI revealed a significant difference between P1 and P3 and between P2 and P3. Although no statistically significant difference was observed between P1 and P2, variations, including the median, tended to be fewer in P2. The correlation analyses for G-gas, TC, and HI showed that P2 was less likely to be affected by G-gas. Conclusion: For a treatment plan that is robust to G-gas, P2 mean replacement method should be used. This method does not necessitate any particular software or equipment, and is convenient to implement in clinical practice.

Comparison of Moderate Hypofractionated Volumetric-Modulated Arc Therapy Plans With and Without Flattening Filter for Localized Prostate Cancer.

Background/Aim The aim of this study was to compare volumetric-modulated arc therapy (VMAT) radiation plans between conventional VMAT with flattening filter (cFF-VMAT) and flattening filter-free VMAT (FFF-VMAT) for localized prostate cancer. Materials and methods Ten patients with localized prostate cancer who underwent cFF-VMAT at Yokosuka General Hospital Uwamachi, Yokosuka, Japan, from July 2020 to October 2020 were enrolled. Dose-volume histogram (DVH) parameters of the target volume, normal organs, monitor units (MU), and beam-on time (BOT) were compared between cFF-VMAT and FFF-VMAT plans. Results No significant difference was observed for DVH parameters for the target volume. No significant difference was observed in all parameters for the bladder and rectum between the cFF-VMAT and FFF-VMAT groups. The mean values of MU were 686 ± 52 and 784 ± 80 in cFF-VMAT and FFF-VMAT, respectively (p < 0.001). The mean BOT was 97.0 ± 6.6 s and 72.9 ± 1.4 s for cFF-VMAT and FFF-VMAT, respectively (p < 0.001). Conclusion DVH parameters of the target volume and normal organs were not significantly different between the cFF-VMAT and FFF-VMAT plans. In FFF-VMAT, MU was significantly higher, and the BOT was significantly shorter than those in cFF-VMAT.

Comparison of Dose Distribution Between VMAT-SBRT and Scanning Carbon-ion Radiotherapy for Early-stage NSCLC.

BACKGROUND/AIM: The purpose of this study was to compare the dose distribution between scanning carbon-ion radiotherapy (sCIRT) and volumetric-modulated arc therapy with stereotactic body radiation therapy (VMAT-SBRT) for stage I non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: Fifteen patients with early-stage NSCLC who underwent sCIRT at Kanagawa Cancer Center between 2018-2020 were enrolled. Dose-volume histogram parameters of the planned target volume and normal organs for sCIRT and VMAT-SBRT were evaluated. RESULTS: The homogeneity index of the target volume of sCIRT was significantly lower than that of VMAT-SBRT. The dose of sCIRT was significantly lower than that of VMAT-SBRT at low volumes in the lung, heart, spinal cord, and esophagus. CONCLUSION: The dose distribution of sCIRT for early-stage NSCLC was better than that of VMAT-SBRT.

Dosimetric Comparison of Radiation Therapy Using Hybrid-VMAT Technique for Stage I Esophageal Cancer.

BACKGROUND/AIM: This study focused on the hybrid-volumetric modulated arc therapy (hVMAT) for stage I esophageal cancer and compared the effects on dose distribution induced by changes in the ratio of three-dimensional conformal radiotherapy (3DCRT) to VMAT. PATIENTS AND METHODS: Fifteen patients who underwent 3DCRT for cT1bN0M0 esophageal cancer at Kanagawa Cancer Center from January 2014 to April 2019 were included in the study. The dose-volume histogram (DVH) parameters of the target volume and normal organs were evaluated in the 3DCRT, hVMAT, and VMAT treatment plans. RESULTS: The homogeneity index of the target volume was significantly lower for hVMAT. In hVMAT, as the ratio of VMAT increased, the volume of low-dose region in the heart and lung increased, whereas the volume of the middle- to high-dose region decreased. As the ratio of VMAT increased, the mean dose in the heart decreased, whereas the mean dose in the lung increased. CONCLUSION: Favorable dose concentration was obtained for the target volume in hVMAT for stage I esophageal cancer. Altering the ratio of VMAT significantly changed the DVH parameters in normal organs.