Optimizing irradiation protocols for pregnant women is challenging, because there are few cases and a dearth of fetal dosimetry data. We cared for a 36-year-old pregnant woman with tongue cancer. Prior to treatment, we compared three intensity-modulated radiation therapy (IMRT) techniques, including helical tomotherapy, volumetric arc therapy (VMAT), and flattening-filter free VMAT (FFF-VMAT) using treatment planning software. FFF-VMAT achieved the minimum fetal exposure and was selected as the optimal modality. We prescribed 66 Gy to the involved nodes, 60 Gy to the tumor bed and ipsilateral neck, and 54 Gy to the contralateral neck over 33 fractions. To confirm the out-of-field exposure per fraction, surface doses and the rectal dose were measured during FFF-VMAT delivery. Postoperative chemoradiotherapy was delivered using IMRT and a cisplatin regimen. Without any shielding, the total fetal dose was 0.03 Gy, within the limits established by the ICRP. A healthy girl was born vaginally at 37 weeks' gestation.
The purpose of this study was to predict the survival time of patients with malignant glioma after radiotherapy with high accuracy by considering additional clinical factors and optimize the prescription dose and treatment duration for individual patient by using a machine learning model. A total of 35 patients with malignant glioma were included in this study. The candidate features included 12 clinical features and 192 dose-volume histogram (DVH) features. The appropriate input features and parameters of the support vector machine (SVM) were selected using the genetic algorithm based on Akaike's information criterion, i.e. clinical, DVH, and both clinical and DVH features. The prediction accuracy of the SVM models was evaluated through a leave-one-out cross-validation test with residual error, which was defined as the absolute difference between the actual and predicted survival times after radiotherapy. Moreover, the influences of various values of prescription dose and treatment duration on the predicted survival time were evaluated. The prediction accuracy was significantly improved with the combined use of clinical and DVH features compared with the separate use of both features (P < 0.01, Wilcoxon signed rank test). Mean ± standard deviation of the leave-one-out cross-validation using the combined clinical and DVH features, only clinical features and only DVH features were 104.7 ± 96.5, 144.2 ± 126.1 and 204.5 ± 186.0 days, respectively. The prediction accuracy could be improved with the combination of clinical and DVH features, and our results show the potential to optimize the treatment strategy for individual patients based on a machine learning model.
The present study sought to evaluate the impact of the flattening filter-free (FFF) technique in volumetric modulated arc therapy for lung stereotactic body radiotherapy. Its clinical safety and availability were compared with the flattening filter (FF) method. The cases of 65 patients who underwent lung volumetric modulated arc therapy-stereotactic body radiotherapy (VMAT-SBRT) using FF or FFF techniques were reviewed. A total of 55 Gy/4 fractions (fr) was prescribed for peripheral lesions or 56 Gy/7 fr for central lesions. The total monitor units (MU), treatment time, dose to tumors, dose to organs at risk, tumor control (local control rate, overall survival, progression-free survival) and adverse events between cases treated with FF and cases treated with the FFF technique were compared. A total of 35 patients were treated with conventional FF techniques prior to November 2014 and 30 patients were treated with FFF techniques after this date. It was revealed that the beam-on time was significantly shortened by the FFF technique (P<0.01). Other factors were similar for FFF and FF plans in respect to conformity (P=0.95), homogeneity (P=0.20) and other dosimetric values, including total MU and planning target volume/internal target volume coverage. The median follow-up period was 18 months (range, 2-35). One-year local control rates were 97.1 and 90.0% in the FF group and FFF groups, respectively (P=0.33). Grade 3 pneumonitis was observed in 5.8% of FF patients and 3.4% of FFF patients (P=1.00). No other adverse events ≥grade 3 were observed. The results of the study suggest that VMAT-SBRT using the FFF technique shortens the treatment time for lung SBRT while maintaining a high local control rate with low toxicity.
Background: Postoperative irradiation for brain tumor in pregnant women is a matter of concern. Aim: We aimed to assess the safety of radiotherapy for brain tumors in pregnancy. We here report a successful treatment for anaplastic astrocytoma during pregnancy: surgery + postoperative irradiation. We wish to emphasize how we devised irradiation procedure to achieve both therapeutic effectiveness and safety to the fetus/infant. Case Presentation: A 34-year-old pregnant woman suffered with brain anaplastic astrocytoma. Tumor resection under craniotomy was performed with success. We decided to conduct postoperative radiotherapy at 25 weeks of gestation to reduce the risk of recurrence. We used a flattening filter-free volumetric arc therapy (FFF-VMAT) technique, which can achieve lower out-of-field dose than VMAT with a flattening filter or helical tomotherapy. We prescribed 60 Gy over 30 fractions. During actual beam delivery, surface and rectal dose to the patient (mother) were measured. The total fetal dose was estimated at 0.006 - 0.018 Gy, which is under the threshold set by the ICRP. A male healthy infant was born vaginally at the 37th week of pregnancy. The patient (mother) and the infant are healthy at the time of writing. Conclusion: FFF-VMAT is a good choice for brain tumors during pregnancy.
Abstract Using a plane‐parallel advanced Markus ionization chamber and a stack of water‐equivalent solid phantom blocks, percentage surface and build‐up doses of Elekta 6 MV flattening filter (FF) and flattening‐filter‐free (FFF) beams were measured as a function of the phantom depth for field sizes ranging from 2 × 2 to 10 × 10 cm 2 . It was found that the dose difference between the FF and the FFF beams was relatively small. The maximum dose difference between the FF and the FFF beams was 4.4% at a depth of 1 mm for a field size of 2 × 2 cm 2 . The dose difference was gradually decreased while the field size was increased up to 10 × 10 cm 2 . The measured data were also compared to published Varian FF and FFF data, suggesting that the percentage surface and build‐up doses as well as the percentage dose difference between FF and FFF beams by our Elekta linac were smaller than those by the Varian linac.
AbstractBackground We compared the dosimetric and clinical outcomes of VMAT and 3D-CRT in breast cancer patients undergoing regional nodal irradiation (RNI) to determine the effectiveness of VMAT. Methods This retrospective cohort study included breast cancer patients who underwent adjuvant radiotherapy with RNI between July 2016 and September 2022. Patients were assigned to receive either 3D-CRT or VMAT based on the laterality of their cancer. Right-sided breast cancer received 3D-CRT, while left-sided breast cancer received VMAT. Radiotherapy consisted of a dose of 50 Gy/25 fr to the chest wall or breast and the regional nodes. Dosimetric parameters, adverse events, and survival were compared between 3D-CRT and VMAT. Results A total of 126 patients were included in the analysis, with 64 in the 3D-CRT group and 62 in the VMAT group. VMAT showed better coverage of the clinical target volume (P < 0.01). Among patients who received internal mammary node irradiation, VMAT resulted in a lower total lung V20 Gy compared to 3D-CRT (17% vs. 11%, P < 0.01), whereas total lung V5 Gy was higher for VMAT (27% vs. 34%, P < 0.01). The incidence of grade 2 acute dermatitis was lower in the VMAT group (27%) than in the 3D-CRT group (47%) (P= 0.02). The 5-year overall survival and breast cancer-specific survival rates were 87% and 90% in the 3D-CRT group and 100% and 100% in the VMAT group, respectively (P = 0.06 and 0.09). Conclusions VMAT showed better target coverage and less acute radiation dermatitis compared to 3D-CRT.
Abstract Background The breath‐hold radiotherapy has been increasingly used to mitigate interfractional and intrafractional breathing impact on treatment planning and beam delivery. Previous techniques include body surface measurements or radiopaque metal markers, each having known disadvantages. Purpose We recently proposed a new markerless technique without the disadvantages, where diaphragm was registered between DRR and fluoroscopic x‐ray projection images every 180 ms during VMAT delivery. An initial validation of the proposed diaphragm tracking system (DiaTrak) was performed using a chest phantom to evaluate its characteristics. Methods Diaphragm registration was performed between DRR and projection streaming kV x‐ray images of a chest phantom during VMAT delivery. Streaming data including the projection images and the beam angles were transferred from a linac system to an external PC, where the diaphragm registration accuracy and beam‐off latency were measured based on image cross correlation between the DRR and the projection images every 180 ms. Results It was shown that the average of the beam‐off latency was 249.5 ms and the average of the diaphragm registration error was 0.84 mm Conclusions Initial validation of the proposed DiaTrak system for multiple breath‐hold VMAT of abdominal tumors has been successfully completed with a chest phantom. The resulting beam‐off latency and the diaphragm registration error were regarded clinically acceptable.
Statistical iterative reconstruction is expected to improve the image quality of megavoltage computed tomography (MVCT). However, one of the challenges of iterative reconstruction is its large computational cost. The purpose of this work is to develop a fast iterative reconstruction algorithm by combining several iterative techniques and by optimizing reconstruction parameters. Megavolt projection data was acquired from a TomoTherapy system and reconstructed using our statistical iterative reconstruction. Total variation was used as the regularization term and the weight of the regularization term was determined by evaluating signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and visual assessment of spatial resolution using Gammex and Cheese phantoms. Gradient decent with an adaptive convergence parameter, ordered subset expectation maximization (OSEM), and CPU/GPU parallelization were applied in order to accelerate the present reconstruction algorithm. The SNR and CNR of the iterative reconstruction were several times better than that of filtered back projection (FBP). The GPU parallelization code combined with the OSEM algorithm reconstructed an image several hundred times faster than a CPU calculation. With 500 iterations, which provided good convergence, our method produced a 512$\times$512 pixel image within a few seconds. The image quality of the present algorithm was much better than that of FBP for patient data. An image from the iterative reconstruction in TomoTherapy can be obtained within few seconds by fine-tuning the parameters. The iterative reconstruction with GPU was fast enough for clinical use, and largely improve the MVCT images.
