Biological effective dose in analysis of rectal dose in prostate cancer patients who underwent a combination therapy of VMAT and LDR with hydrogel spacer insertion

Rectal complications following SpaceOAR insertion after prior pelvic radiation

Treating prostate cancer with radiation therapy in patients with a history of prior pelvic radiation may be limited by rectal dose constraints and the risk of rectal toxicity. Rectal spacers have been shown to improve rectal dosimetry in the treatment of prostate cancer. This study aimed to evaluate the safety and outcomes of hydrogel spacer placement, specifically SpaceOAR, between the rectum and prostate in prostate cancer patients who had previously undergone radiation therapy. In this retrospective case series, we analysed the medical records of 8 sequential patients undergoing reirradiation in the setting or prior pelvic radiation, who had received transperineal SpaceOAR placement. We documented the incidence of complications after SpaceOAR placement, before and after undergoing radiation therapy. There was a spectrum of complications in this patient cohort, ranging from pelvic pain to more severe complications such as rectal perforation abscess and fistula. Severe complications occurred in 2 of the 8 patients. Re-irradiation may increase the risk of normal tissue complications; however, hydrogel spacer placement using SpaceOAR in prostate cancer patients with prior pelvic radiation was associated with a higher rate of rectal complications than expected in a small series of patients. We urge caution when using SpaceOAR in this patient group.

Proposal for a Method for Assessing the Quality of an Updated Deep Learning-Based Automatic Segmentation Program

This study aimed to verify whether a commercial deep learning-based automatic segmentation (DLS) method can maintain contour geometric accuracy post-update and to propose a streamlined validation method that minimizes the burden on clinical workflows. This study included 109 participants. Radiation oncologists used computed tomography (CT) imaging to identify 28 organs located in the head and neck, chest, abdomen, and pelvic regions. Contours were delineated on CT images using AI-Rad Companion Organs RT (AIRC; Siemens Healthineers, Erlangen, Germany) versions VA30, VA50, and VA50. The Dice similarity coefficient, maximum Hausdorff distance, and mean distance to agreement were calculated to identify contours with significant differences among versions. To evaluate the identified contours, the ground truth was defined as the contour delineated by radiation oncologists, and the geometric indices for VA30, VA50, and VA60 were recalculated. Statistical analysis was performed on the geometric indices to verify differences between each version. Among the 28 contours evaluated, nine organs did not satisfy the established criteria. Statistical analysis revealed that the brain, rectum, and bladder contours differed substantially across AIRC versions. In particular, the pre-update rectum contour had a mean (range) Hausdorff distance of 0.76 (0.40-1.16), whereas the post-update rectum contour exhibited lower quality, with a Hausdorff distance of 1.13 (0.24-5.68). Therefore, commercial DLS methods that undergo regular updates must be reassessed for quality in each region of interest. The proposed method can help reduce the burden on clinical workflows while appropriately evaluating post-update DLS performance.

Efficacy of hydrogel spacer compared with intensity-modulated radiotherapy for 3-dimensional conformal radiotherapy for prostate cancer

One major adverse effect of prostate radiotherapy is associated with the rectum. The SpaceOAR system has been developed to address this problem, as it enables treatment planning with a reduced dose to the rectum. This study aimed to evaluate and compare the treatment plans between three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT) for prostate cancer using the SpaceOAR system. Thirty-five patients treated with prostate cancer radiation using the SpaceOAR system received a total radiation dose of 60 Gy/20 fractions. The dose constraints and robustness of the plan for VMAT and 3D-CRT were compared. For 3D-CRT, 6-field conformal method and 2-arc conformal method were created and compared in 3 treatment plans together with VMAT. The dose-constraint evaluation was performed using the planning target volume (PTV), rectum (mean dose), bladder (mean dose), and femoral head (mean dose). One issue associated with prostate radiotherapy is the physiological movement of the target prostate gland, which reduces the accuracy of irradiation. The prostate moves several millimeters during irradiation due to physiological movements, and there are reports of a decrease in the PTV index due to this effect. This has a significant impact on the cure rate of prostate cancer. A comparative study of the 3 irradiation methods was conducted to investigate this issue. Each study item was analyzed using the Friedman test to determine the significance of the 3 irradiation methods. Our analysis showed that the dose constraint was statistically significant for VMAT, but 3D-CRT was also sufficient in achieving dose constraints. The hydrogel spacer reduced the rectal dose and improved the dose-constrained fulfillment rate in VMAT and 3D-CRT. In a study of prostate motion during irradiation, 3D-CRT, a robust plan, was superior in the PTV mean evaluation over VMAT, where the multileaf collimator moved in fine increments. VMAT is currently the standard treatment for prostate cancer; however, with the introduction of the SpaceOAR system using hydrogel spacers, 3D-CRT may also be a viable option for prostate cancer treatment.

A Comparative Study of Deep Learning Dose Prediction Models for Cervical Cancer Volumetric Modulated Arc Therapy

Purpose: Deep learning (DL) is widely used in dose prediction for radiation oncology, multiple DL techniques comparison is often lacking in the literature. To compare the performance of 4 state-of-the-art DL models in predicting the voxel-level dose distribution for cervical cancer volumetric modulated arc therapy (VMAT). Methods and Materials: A total of 261 patients' plans for cervical cancer were retrieved in this retrospective study. A three-channel feature map, consisting of a planning target volume (PTV) mask, organs at risk (OARs) mask, and CT image was fed into the three-dimensional (3D) U-Net and its 3 variants models. The data set was randomly divided into 80% as training-validation and 20% as testing set, respectively. The model performance was evaluated on the 52 testing patients by comparing the generated dose distributions against the clinical approved ground truth (GT) using mean absolute error (MAE), dose map difference (GT-predicted), clinical dosimetric indices, and dice similarity coefficients (DSC). Results: The 3D U-Net and its 3 variants DL models exhibited promising performance with a maximum MAE within the PTV 0.83% ± 0.67% in the UNETR model. The maximum MAE among the OARs is the left femoral head, which reached 6.95% ± 6.55%. For the body, the maximum MAE was observed in UNETR, which is 1.19 ± 0.86%, and the minimum MAE was 0.94 ± 0.85% for 3D U-Net. The average error of the Dmean difference for different OARs is within 2.5 Gy. The average error of V40 difference for the bladder and rectum is about 5%. The mean DSC under different isodose volumes was above 90%. Conclusions: DL models can predict the voxel-level dose distribution accurately for cervical cancer VMAT treatment plans. All models demonstrated almost analogous performance for voxel-wise dose prediction maps. Considering all voxels within the body, 3D U-Net showed the best performance. The state-of-the-art DL models are of great significance for further clinical applications of cervical cancer VMAT.