Evaluation of multiple-vendor AI autocontouring solutions.

BACKGROUND: Multiple artificial intelligence (AI)-based autocontouring solutions have become available, each promising high accuracy and time savings compared with manual contouring. Before implementing AI-driven autocontouring into clinical practice, three commercially available CT-based solutions were evaluated. MATERIALS AND METHODS: The following solutions were evaluated in this work: MIM-ProtégéAI+ (MIM), Radformation-AutoContour (RAD), and Siemens-DirectORGANS (SIE). Sixteen organs were identified that could be contoured by all solutions. For each organ, ten patients that had manually generated contours approved by the treating physician (AP) were identified, totaling forty-seven different patients. CT scans in the supine position were acquired using a Siemens-SOMATOMgo 64-slice helical scanner and used to generate autocontours. Physician scoring of contour accuracy was performed by at least three physicians using a five-point Likert scale. Dice similarity coefficient (DSC), Hausdorff distance (HD) and mean distance to agreement (MDA) were calculated comparing AI contours to "ground truth" AP contours. RESULTS: The average physician score ranged from 1.00, indicating that all physicians reviewed the contour as clinically acceptable with no modifications necessary, to 3.70, indicating changes are required and that the time taken to modify the structures would likely take as long or longer than manually generating the contour. When averaged across all sixteen structures, the AP contours had a physician score of 2.02, MIM 2.07, RAD 1.96 and SIE 1.99. DSC ranged from 0.37 to 0.98, with 41/48 (85.4%) contours having an average DSC ≥ 0.7. Average HD ranged from 2.9 to 43.3 mm. Average MDA ranged from 0.6 to 26.1 mm. CONCLUSIONS: The results of our comparison demonstrate that each vendor's AI contouring solution exhibited capabilities similar to those of manual contouring. There were a small number of cases where unusual anatomy led to poor scores with one or more of the solutions. The consistency and comparable performance of all three vendors' solutions suggest that radiation oncology centers can confidently choose any of the evaluated solutions based on individual preferences, resource availability, and compatibility with their existing clinical workflows. Although AI-based contouring may result in high-quality contours for the majority of patients, a minority of patients require manual contouring and more in-depth physician review.

Fertility-sparing uterine displacement for pelvic malignancies: surgical options and radiotherapy dosimetry on a human cadaver.

BACKGROUND: Radio(chemo)therapy is often required in pelvic malignancies (cancer of the anus, rectum, cervix). Direct irradiation adversely affects ovarian and endometrial function, compromising the fertility of women. While ovarian transposition is an established method to move the ovaries away from the radiation field, surgical procedures to displace the uterus are investigational. This study demonstrates the surgical options for uterine displacement in relation to the radiation dose received.  METHODS: The uterine displacement techniques were carried out sequentially in a human female cadaver to demonstrate each procedure step by step and assess the uterine positions with dosimetric CT scans in a hybrid operating room. Two treatment plans (anal and rectal cancer) were simulated on each of the four dosimetric scans (1. anatomical position, 2. uterine suspension of the round ligaments to the abdominal wall 3. ventrofixation of the uterine fundus at the umbilical level, 4. uterine transposition). Treatments were planned on Eclipse® System (Varian Medical Systems®,USA) using Volumetric Modulated Arc Therapy. Data about maximum (Dmax) and mean (Dmean) radiation dose received and the volume receiving 14 Gy (V14Gy) were collected. RESULTS: All procedures were completed without technical complications. In the rectal cancer simulation with delivery of 50 Gy to the tumor, Dmax, Dmean and V14Gy to the uterus were respectively 52,8 Gy, 34,3 Gy and 30,5cc (1), 31,8 Gy, 20,2 Gy and 22.0cc (2), 24,4 Gy, 6,8 Gy and 5,5cc (3), 1,8 Gy, 0,6 Gy and 0,0cc (4). For anal cancer, delivering 64 Gy to the tumor respectively 46,7 Gy, 34,8 Gy and 31,3cc (1), 34,3 Gy, 20,0 Gy and 21,5cc (2), 21,8 Gy, 5,9 Gy and 2,6cc (3), 1,4 Gy, 0,7 Gy and 0,0cc (4). CONCLUSIONS: The feasibility of several uterine displacement procedures was safely demonstrated. Increasing distance to the radiation field requires more complex surgical interventions to minimize radiation exposure. Surgical strategy needs to be tailored to the multidisciplinary treatment plan, and uterine transposition is the most technically complex with the least dose received.

Radiation Dose-Volume-Response Relationships for Adverse Events in Childhood Cancer Survivors: Introduction to the Scientific Issues in PENTEC.

At its very core, radiation oncology involves a trade-off between the benefits and risks of exposing tumors and normal tissue to relatively high doses of ionizing radiation. This trade-off is particularly critical in childhood cancer survivors (CCS), in whom both benefits and risks can be hugely consequential due to the long life expectancy if the primary cancer is controlled. Estimating the normal tissue-related risks of a specific radiation therapy plan in an individual patient relies on predictive mathematical modeling of empirical data on adverse events. The Pediatric Normal-Tissue Effects in the Clinic (PENTEC) collaborative network was formed to summarize and, when possible, to synthesize dose-volume-response relationships for a range of adverse events incident in CCS based on the literature. Normal-tissue clinical radiation biology in children is particularly challenging for many reasons: (1) Childhood malignancies are relatively uncommon-constituting approximately 1% of new incident cancers in the United States-and biologically heterogeneous, leading to many small series in the literature and large variability within and between series. This creates challenges in synthesizing data across series. (2) CCS are at an elevated risk for a range of adverse health events that are not specific to radiation therapy. Thus, excess relative or absolute risk compared with a reference population becomes the appropriate metric. (3) Various study designs and quantities to express risk are found in the literature, and these are summarized. (4) Adverse effects in CCS often occur 30, 50, or more years after therapy. This limits the information content of series with even very extended follow-up, and lifetime risk estimates are typically extrapolations that become dependent on the mathematical model used. (5) The long latent period means that retrospective dosimetry is required, as individual computed tomography-based radiation therapy plans gradually became available after 1980. (6) Many individual patient-level factors affect outcomes, including age at exposure, attained age, lifestyle exposures, health behaviors, other treatment modalities, dose, fractionation, and dose distribution. (7) Prospective databases with individual patient-level data and radiation dosimetry are being built and will facilitate advances in dose-volume-response modeling. We discuss these challenges and attempts to overcome them in the setting of PENTEC.

Reporting Standards for Complication Studies of Radiation Therapy for Pediatric Cancer: Lessons From PENTEC.

The major aim of Pediatric Normal Tissue Effects in the Clinic (PENTEC) was to synthesize quantitative published dose/-volume/toxicity data in pediatric radiation therapy. Such systematic reviews are often challenging because of the lack of standardization and difficulty of reporting outcomes, clinical factors, and treatment details in journal articles. This has clinical consequences: optimization of treatment plans must balance between the risks of toxicity and local failure; counseling patients and their parents requires knowledge of the excess risks encountered after a specific treatment. Studies addressing outcomes after pediatric radiation therapy are particularly challenging because: (a) survivors may live for decades after treatment, and the latency time to toxicity can be very long; (b) children's maturation can be affected by radiation, depending on the developmental status of the organs involved at time of treatment; and (c) treatment regimens frequently involve chemotherapies, possibly modifying and adding to the toxicity of radiation. Here we discuss: basic reporting strategies to account for the actuarial nature of the complications; the reporting of modeling of abnormal development; and the need for standardized, comprehensively reported data sets and multivariate models (ie, accounting for the simultaneous effects of radiation dose, age, developmental status at time of treatment, and chemotherapy dose). We encourage the use of tools that facilitate comprehensive reporting, for example, electronic supplements for journal articles. Finally, we stress the need for clinicians to be able to trust artificial intelligence models of outcome of radiation therapy, which requires transparency, rigor, reproducibility, and comprehensive reporting. Adopting the reporting methods discussed here and in the individual PENTEC articles will increase the clinical and scientific usefulness of individual reports and associated pooled analyses.

Deep Learning-Based Prediction of Radiation Therapy Dose Distributions in Nasopharyngeal Carcinomas: A Preliminary Study Incorporating Multiple Features Including Images, Structures, and Dosimetry.

Purpose: Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enhance prediction accuracy by incorporating dose information into a deep convolutional neural network (CNN) using a multichannel input method. Methods: A target conformal plan (TCP) was created based on the maximum planning target volume (PTV). Input data included TCP dose distribution, images, target structures, and organ-at-risk (OAR) information. The role of target conformal plan dose (TCPD) was assessed by comparing the TCPD-CNN (with dose information) and NonTCPD-CNN models (without dose information) using statistical analyses with the ranked Wilcoxon test (P < .05 considered significant). Results: The TCPD-CNN model showed no statistical differences in predicted target indices, except for PTV60, where differences in the D98% indicator were < 0.5%. For OARs, there were no significant differences in predicted results, except for some small-volume or closely located OARs. On comparing TCPD-CNN and NonTCPD-CNN models, TCPD-CNN's dose-volume histograms closely resembled clinical plans with higher similarity index. Mean dose differences for target structures (predicted TCPD-CNN and NonTCPD-CNN results) were within 3% of the maximum prescription dose for both models. TCPD-CNN and NonTCPD-CNN outcomes were 67.9% and 54.2%, respectively. 3D gamma pass rates of the target structures and the entire body were higher in TCPD-CNN than in the NonTCPD-CNN models (P < .05). Additional evaluation on previously unseen volumetric modulated arc therapy plans revealed that average 3D gamma pass rates of the target structures were larger than 90%. Conclusions: This study presents a novel framework for dose distribution prediction using deep learning and multichannel input, specifically incorporating TCPD information, enhancing prediction accuracy for IMRT in NPC treatment.

Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy.

Objective.To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Approach.Two 3D UNets were established to predict photon and proton doses. A dataset of 95 patients with localized prostate cancer was randomly partitioned into 55, 10, and 30 for training, validation, and testing, respectively. We selected NTCP models for late rectum bleeding and acute urinary urgency of grade 2 or higher to quantify the benefit of proton therapy. Propagated uncertainties of predicted ΔNTCPs resulting from the dose prediction errors were calculated. Patient selection accuracies for a single endpoint and a composite evaluation were assessed under different ΔNTCP thresholds.Main results.Our deep learning-based dose prediction technique can reduce the time spent on plan comparison from approximately 2 days to as little as 5 seconds. The expanded uncertainty of predicted ΔNTCPs for rectum and bladder endpoints propagated from the dose prediction error were 0.0042 and 0.0016, respectively, which is less than one-third of the acceptable tolerance. The averaged selection accuracies for rectum bleeding, urinary urgency, and composite evaluation were 90%, 93.5%, and 93.5%, respectively.Significance.Our study demonstrates that deep learning dose prediction and NTCP evaluation scheme could distinguish the NTCP differences between photon and proton treatment modalities. In addition, the dose prediction uncertainty does not significantly influence the decision accuracy of NTCP-based patient selection for proton therapy. Therefore, automated deep learning dose prediction and NTCP evaluation schemes can potentially be used to screen large patient populations and to avoid unnecessary delays in the start of prostate cancer radiotherapy in the future.

Biological optimization for hybrid proton-photon radiotherapy.

Objective.Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose.Approach.The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method.Main results.Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies.Significance.This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

Imaging Assessment of Radiation Therapy-Related Normal Tissue Injury in Children: A PENTEC Visionary Statement.

The Pediatric Normal Tissue Effects in the Clinic (PENTEC) consortium has made significant contributions to understanding and mitigating the adverse effects of childhood cancer therapy. This review addresses the role of diagnostic imaging in detecting, screening, and comprehending radiation therapy-related late effects in children, drawing insights from individual organ-specific PENTEC reports. We further explore how the development of imaging biomarkers for key organ systems, alongside technical advancements and translational imaging approaches, may enhance the systematic application of imaging evaluations in childhood cancer survivors. Moreover, the review critically examines knowledge gaps and identifies technical and practical limitations of existing imaging modalities in the pediatric population. Addressing these challenges may expand access to, minimize the risk of, and optimize the real-world application of, new imaging techniques. The PENTEC team envisions this document as a roadmap for the future development of imaging strategies in childhood cancer survivors, with the overarching goal of improving long-term health outcomes and quality of life for this vulnerable population.

The clinical practice and dosimetric outcome of the manual adaptive planning during definitive radiotherapy for cervical cancer.

PROPOSE: To evaluate the advantage of the manual adaptive plans comparing to the scheduled plans, and explored clinical factors predicting patients suitable for adaptive strategy. METHODS AND MATERIALS: Eighty two patients with weekly online cone-beam computed tomography (CBCT) were enrolled. The re-CT simulation was performed after 15 fractions and a manual adaptive plan was developed if a significant deviation of the planning target volume (PTV) was found. To evaluate the dosimetric benefit, D98, homogeneity index (HI) and conformity index (CI) for the planning target volume (PTV), as well as D2cc of the bowel, bladder, sigmoid and rectum were compared between manual adaptive plans and scheduled ones. The clinical factors influencing target motion during radiotherapy were analyzed by chi-square test and logistic regression analysis. RESULTS: The CI and HI of the manual adaptive plans were significantly superior to the scheduled ones (P = 0.0002, 0.003, respectively), demonstrating a better dose coverage of the target volume. Compared to the scheduled plans, D98 of the manual adaptive plans increased by 3.3% (P = 0.0002), the average of D2cc to the rectum, bladder decreased 0.358 Gy (P = 0.000034) and 0.240 Gy (P = 0.03), respectively. In addition, the chi-square test demonstrated that age, primary tumor volume, and parametrial infiltration were the clinical factors influencing target motion during radiotherapy. Multivariate analysis further identified the large tumor volume (≥ 50cm3, OR = 3.254, P = 0.039) and parametrial infiltration (OR = 3.376, P = 0.018) as the independent risk factors. CONCLUSION: We found the most significant organ motion happened after 15 fractions during treatment. The manual adaptive plans improved the dose coverage and decreased the OAR doses. Patients with bulky mass or with parametrial infiltration were highly suggested to adaptive strategy during definitive radiotherapy due to the significant organ motion.

Assessment of the Dosimetric Index from IMRT and Rapid arc Plan for Oropharyngeal Cancer with Simultaneous Integrated Boost (SIB) Technique in Combination with EUD-based NTCP and TCP Radiobiological Models.

PURPOSE: The current research compared radiobiological and dosimetric results for simultaneous integrated boost (SIB) plans employing RapidArc and IMRT planning procedures in oropharyngeal cancer from head-and-neck cancer (HNC) patients. MATERIALS AND METHODS: The indigenously developed Python-based software was used in this study for generation and analysis. Twelve patients with forty-eight total plans with SIB were planned using Rapid arc (2 and 3 arcs) and IMRT (7 and 9 fields) and compared with radiobiological models Lyman, Kutcher, Burman (LKB) and EUD (Equivalent Uniform Dose) along with physical index such as homogeneity index(HI), conformity index(CI) of target volumes. RESULTS: These models' inputs are the dose-volume histograms (DVHs) calculated by the treatment planning system (TPS). The values obtained vary from one model to the other for the same technique and patient. The maximum dose to the brainstem and spinal cord and the mean dose to the parotids were analysed both dosimetrically and radiobiologically, such as the LKB model effective volume, equivalent uniform dose, EUD-based normal tissue complication probability, and normal tissue integral dose. The mean and max dose to target volume with conformity, homogeneity index, tumor control probability compared with treatment times, and monitor units. CONCLUSION: Rapid arc (3 arcs) resulted in significantly better OAR sparing, dose homogeneity, and conformity. The findings indicate that the rapid arc plan has improved dose distribution in the target volume compared with IMRT, but the tumor control probability obtained for the two planning methods, Rapid arc (3 arcs) and IMRT (7 fields), are similar. The treatment time and monitor units for the Rapid arc (3 arcs) were superior to other planning methods and considered to be standard in head & neck radiotherapy.

Phase I quality control framework for monitoring organ-at-risk dose.

Objective.The aim of this work was to develop a Phase I control chart framework for the recently proposed multivariate risk-adjusted Hotelling'sT2chart. Although this control chart alone can identify most patients receiving extreme organ-at-risk (OAR) dose, it is restricted by underlying distributional assumptions, making it sensitive to extreme observations in the sample, as is typically found in radiotherapy plan quality data such as dose-volume histogram (DVH) points. This can lead to slightly poor-quality plans that should have been identified as out-of-control (OC) to be signaled in-control (IC).Approach. We develop a robust iterative control chart framework to identify all OC patients with abnormally high OAR dose and improve them via re-optimization to achieve an IC sample prior to establishing the Phase I control chart, which can be used to monitor future treatment plans.Main Results. Eighty head-and-neck patients were used in this study. After the first iteration, P14, P67, and P68 were detected as OC for high brainstem dose, warranting re-optimization aimed to reduce brainstem dose without worsening other planning criteria. The DVH and control chart were updated after re-optimization. On the second iteration, P14, P67, and P68 were IC, but P40 was identified as OC. After re-optimizing P40's plan and updating the DVH and control chart, P40 was IC, but P14* (P14's re-optimized plan) and P62 were flagged as OC. P14* could not be re-optimized without worsening target coverage, so only P62 was re-optimized. Ultimately, a fully IC sample was achieved. Multiple iterations were needed to identify and improve all OC patients, and to establish a more robust control limit to monitor future treatment plans.Significance. The iterative procedure resulted in a fully IC sample of patients. With this sample, a more robust Phase I control chart that can monitor OAR doses of new plans was established.

Effective timing of hyaluronate gel injection in image-guided adaptive brachytherapy for uterine cervical cancer: a proposal of the 'adjusted dose score'.

Hyaluronate gel injection (HGI) in the rectovaginal septum and vesicovaginal septum is effective in the setting of high-dose-rate image-guided adaptive brachytherapy (IGABT) for cervical cancer. We aimed to retrospectively investigate optimal conditions for HGI to achieve optimal dose distribution with a minimum number of HGI. We classified 50 IGABT plans of 13 patients with cervical cancer who received IGABT both with and without HGI in the rectovaginal septum and vesicovaginal septum into the following two groups: plan with (number of plans = 32) and plan without (number of plans = 18) HGI. The irradiation dose parameters of high-risk clinical target volume (CTVHR) and organs at risk per fraction were compared between these groups. We also developed the adjusted dose score (ADS), reflecting the overall irradiation dose status for four organs at risk and CTVHR in one IGABT plan and investigated its utility in determining the application of HGI. HGI reduced the maximum dose to the most exposed 2.0 cm3 (D2.0 cm3) of the bladder while increasing the minimum dose covering 90% of CTVHR and the percentage of CTVHR receiving 100% of the prescription dose in one IGABT plan without causing any associated complications. An ADS of ≥2.60 was the optimum cut-off value to decide whether to perform HGI. In conclusion, HGI is a useful procedure for improving target dose distribution while reducing D2.0 cm3 in the bladder in a single IGABT plan. The ADS can serve as a useful indicator for the implementation of HGI.

Functional imaging guided stereotactic ablative body radiotherapy (SABR) with focal dose escalation and bladder trigone sparing for intermediate and high-risk prostate cancer: study protocol for phase II safo trial.

BACKGROUND: Stereotactic ablative body radiotherapy (SABR) is an emerging treatment alternative for patients with localized low and intermediate risk prostate cancer patients. As already explored by some authors in the context of conventional moderate hypofractionated radiotherapy, focal boost of the index lesion defined by magnetic resonance imaging (MRI) is associated with an improved biochemical outcome. The objective of this phase II trial is to determine the effectiveness (in terms of biochemical, morphological and functional control), the safety and impact on quality of life, of prostate SABR with MRI guided focal dose intensification in males with intermediate and high-risk localized prostate cancer. METHODS: Patients with intermediate and high-risk prostate cancer according to NCCN definition will be treated with SABR 36.25 Gy in 5 fractions to the whole prostate gland with MRI guided simultaneous integrated focal boost (SIB) to the index lesion (IL) up to 50 Gy in 5 fractions, using a protocol of bladder trigone and urethra sparing. Intra-fractional motion will be monitored with daily cone beam computed tomography (CBCT) and intra-fractional tracking with intraprostatic gold fiducials. Androgen deprivation therapy (ADT) will be allowed. The primary endpoint will be efficacy in terms of biochemical and local control assessed by Phoenix criteria and post-treatment MRI respectively. The secondary endpoints will encompass acute and late toxicity, quality of life (QoL) and progression-free survival. Finally, the subgroup of high-risk patients will be involved in a prospective study focused on immuno-phenotyping. DISCUSSION: To the best of our knowledge, this is the first trial to evaluate the impact of post-treatment MRI on local control among patients with intermediate and high-risk prostate cancer undergoing SABR and MRI guided focal intensification. The results of this trial will enhance our understanding of treatment focal intensification through the employment of the SABR technique within this specific patient subgroup, particularly among those with high-risk disease, and will help to clarify the significance of MRI in monitoring local responses. Hopefully will also help to design more personalized biomarker-based phase III trials in this specific context. Additionally, this trial is expected to be incorporated into a prospective radiomics study focused on localized prostate cancer treated with radiotherapy. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT05919524; Registered 17 July 2023. TRIAL SPONSOR: IRAD/SEOR (Instituto de Investigación de Oncología Radioterápica / Sociedad Española de Oncología Radioterápica). STUDY SETTING: Clinicaltrials.gov identifier: NCT05919524; Registered 17 July 2023. TRIAL STATUS: Protocol version number and date: v. 5/ 17 May-2023. Date of recruitment start: August 8, 2023. Date of recruitment completion: July 1, 2024.

Comparative analysis of simultaneous integrated boost and sequential boost radiotherapy in node-positive cervical cancer: dosimetric and radiobiological considerations.

For locally advanced cervical cancer, the standard therapeutic approach involves concomitant chemoradiation therapy, supplemented by a brachytherapy boost. Moreover, an external beam radiotherapy (RT) boost should be considered for treating gross lymph node (LN) volumes. Two boost approaches exist with Volumetric Intensity Modulated Arc Therapy (VMAT): Sequential (SEQ) and Simultaneous Integrated Boost (SIB). This study undertakes a comprehensive dosimetric and radiobiological comparison between these two boost strategies. The study encompassed ten patients who underwent RT for cervical cancer with node-positive disease. Two sets of treatment plans were generated for each patient: SIB-VMAT and SEQ-VMAT. Dosimetric as well as radiobiological parameters including tumour control probability (TCP) and normal tissue complication probability (NTCP) were compared. Both techniques were analyzed for two different levels of LN involvement - only pelvic LNs and pelvic with para-aortic LNs. Statistical analysis was performed using SPSS software version 25.0. SIB-VMAT exhibited superior target coverage, yielding improved doses to the planning target volume (PTV) and gross tumour volume (GTV). Notably, SIB-VMAT plans displayed markedly superior dose conformity. While SEQ-VMAT displayed favorable organ sparing for femoral heads, SIB-VMAT appeared as the more efficient approach for mitigating bladder and bowel doses. TCP was significantly higher with SIB-VMAT, suggesting a higher likelihood of successful tumour control. Conversely, no statistically significant difference in NTCP was observed between the two techniques. This study's findings underscore the advantages of SIB-VMAT over SEQ-VMAT in terms of improved target coverage, dose conformity, and tumour control probability. In particular, SIB-VMAT demonstrated potential benefits for cases involving para-aortic nodes. It is concluded that SIB-VMAT should be the preferred approach in all cases of locally advanced cervical cancer.

Tubarial gland sparing with intensity modulated radiation therapy for oropharyngeal cancers: A pilot study of dosimetric feasibility.

BACKGROUND: Tubarial glands are a new organ at risk for head and neck cancer radiation therapy (RT). We aimed to study the feasibility of sparing them using intensity-modulated radiation therapy (IMRT). METHODS: Tubarial glands were delineated for 17 patients with oropharyngeal carcinoma receiving definitive RT, and treatment plans were re-optimized to spare dose to the tubarial glands while maintaining target coverage. A paired t test was performed to compare the mean dose of tubarial glands and target coverage. RESULTS: The difference in mean doses was 4.9 and 7.0 Gy for the ipsilateral and contralateral tubarial glands, respectively (p < 0.01). The mean dose to tubarial gland was ≤39 Gy in 35% versus 47% (ipsilateral) and 70% versus 100% (contralateral) in clinical and re-optimized plans, respectively. Re-optimized ipsilateral tubarial gland mean ≤39 Gy was achieved more commonly in patients with base of tongue versus tonsil primaries (86% vs. 20%, p = 0.02). CONCLUSION: This pilot study demonstrates the dosimetric feasibility of tubarial gland sparing with IMRT. Dosimetric constraints need to be determined with larger studies.

Automated treatment planning for whole breast irradiation with individualized tangential IMRT fields.

PURPOSES: This study aimed to develop and validate algorithms for automating intensity modulated radiation therapy (IMRT) planning in breast cancer patients, with a focus on patient anatomical characteristics. MATERIAL AND METHODS: We retrospectively selected 400 breast cancer patients without lymph node involvement for automated treatment planning. Automation was achieved using the Eclipse Scripting Application Programming Interface (ESAPI) integrated into the Eclipse Treatment Planning System. We employed three beam insertion geometries and three optimization strategies, resulting in 3600 plans, each delivering a 40.05 Gy dose in 15 fractions. Gantry angles in the tangent fields were selected based on a criterion involving the minimum intersection area between the Planning Target Volume (PTV) and the ipsilateral lung in the Beam's Eye View projection. ESAPI was also used to gather patient anatomical data, serving as input for Random Forest models to select the optimal plan. The Random Forest classification considered both beam insertion geometry and optimization strategy. Dosimetric data were evaluated in accordance with the Radiation Therapy Oncology Group (RTOG) 1005 protocol. RESULTS: Overall, all approaches generated high-quality plans, with approximately 94% meeting the acceptable dose criteria for organs at risk and/or target coverage as defined by RTOG guidelines. Average automated plan generation time ranged from 6 min and 37 s to 9 min and 22 s, with the mean time increasing with additional fields. The Random Forest approach did not successfully enable automatic planning strategy selection. Instead, our automated planning system allows users to choose from the tested geometry and strategy options. CONCLUSIONS: Although our attempt to correlate patient anatomical features with planning strategy using machine learning tools was unsuccessful, the resulting dosimetric outcomes proved satisfactory. Our algorithm consistently produced high-quality plans, offering significant time and efficiency advantages.

Feasibility of Customized Thermoplastic Patient-Specific Helmet Bolus for Scalp Irradiation Using Volumetric-Modulated Arc Therapy Planning.

Introduction: In this study, we sought to develop a thermoplastic patient-specific helmet bolus that could deliver a uniform therapeutic dose to the target and minimize the dose to the normal brain during whole-scalp treatment with a humanoid head phantom. Methods: The bolus material was a commercial thermoplastic used for patient immobilization, and the holes in the netting were filled with melted paraffin. We compared volumetric-modulated arc therapy treatment plans with and without the bolus for quantitative dose distribution analysis. We analyzed the dose distribution in the region of interest to compare dose differences between target and normal organs. For quantitative analysis of treatment dose, OSLD chips were attached at the vertex (VX), posterior occipital (PO), right (RT), and left temporal (LT) locations. Results: The average dose in the clinical target volume was 6553.8 cGy (99.3%) with bolus and 5874 cGy (89%) without bolus, differing by more than 10% from the prescribed dose (6600 cGy) to the scalp target. For the normal brain, it was 3747.8 cGy (56.8%) with bolus and 5484.6 cGy (83.1%) without bolus. These results show that while the dose to the treatment target decreased, the average dose to the normal brain, which is mostly inside the treatment target, increased by more than 25%. With the bolus, the OSLD measured dose was 102.5 ± 1.2% for VX and 101.5 ± 1.9%, 95.9 ± 1.9%, and 81.8 ± 2.1% for PO, RT, and LT, respectively. In addition, the average dose in the treatment plan was 102%, 101%, 93.6%, and 80.7% for VX, PO, RT, and LT. When no bolus was administered, 59.6 ± 2.4%, 112.6 ± 1.8%, 47.1 ± 1.6%, and 53.1 ± 2.3% were assessed as OSLD doses for VX, PO, RT, and LT, respectively. Conclusion: This study proposed a method to fabricate patient-specific boluses that are highly reproducible, accessible, and easy to fabricate for radiotherapy to the entire scalp and can effectively spare normal tissue while delivering sufficient surface dose.

Multi-institutional evaluation of a Pareto navigation guided automated radiotherapy planning solution for prostate cancer.

BACKGROUND: Current automated planning solutions are calibrated using trial and error or machine learning on historical datasets. Neither method allows for the intuitive exploration of differing trade-off options during calibration, which may aid in ensuring automated solutions align with clinical preference. Pareto navigation provides this functionality and offers a potential calibration alternative. The purpose of this study was to validate an automated radiotherapy planning solution with a novel multi-dimensional Pareto navigation calibration interface across two external institutions for prostate cancer. METHODS: The implemented 'Pareto Guided Automated Planning' (PGAP) methodology was developed in RayStation using scripting and consisted of a Pareto navigation calibration interface built upon a 'Protocol Based Automatic Iterative Optimisation' planning framework. 30 previous patients were randomly selected by each institution (IA and IB), 10 for calibration and 20 for validation. Utilising the Pareto navigation interface automated protocols were calibrated to the institutions' clinical preferences. A single automated plan (VMATAuto) was generated for each validation patient with plan quality compared against the previously treated clinical plan (VMATClinical) both quantitatively, using a range of DVH metrics, and qualitatively through blind review at the external institution. RESULTS: PGAP led to marked improvements across the majority of rectal dose metrics, with Dmean reduced by 3.7 Gy and 1.8 Gy for IA and IB respectively (p < 0.001). For bladder, results were mixed with low and intermediate dose metrics reduced for IB but increased for IA. Differences, whilst statistically significant (p < 0.05) were small and not considered clinically relevant. The reduction in rectum dose was not at the expense of PTV coverage (D98% was generally improved with VMATAuto), but was somewhat detrimental to PTV conformality. The prioritisation of rectum over conformality was however aligned with preferences expressed during calibration and was a key driver in both institutions demonstrating a clear preference towards VMATAuto, with 31/40 considered superior to VMATClinical upon blind review. CONCLUSIONS: PGAP enabled intuitive adaptation of automated protocols to an institution's planning aims and yielded plans more congruent with the institution's clinical preference than the locally produced manual clinical plans.

A Comparative Analysis of Implant-sparing Plan Versus Conventional Plans Utilizing Helical Tomotherapy in Breast Cancer Patients Undergoing Breast Reconstruction.

BACKGROUND/AIM: To compare implant sparing irradiation with conventional radiotherapy (RT) using helical (H) and TomoDirect (TD) techniques in breast cancer patients undergoing immediate breast reconstruction (IBR). PATIENTS AND METHODS: The dosimetric parameters of 40 patients with retropectoral implants receiving 50.4 Gy delivered in 28 fractions were analyzed. Three plans were created: H plan using conventional planning target volume (PTV) that included the chest wall, skin, and implant; TD plan using conventional PTV; and Hs plan using implant-sparing PTV. The H, TD, and Hs plans were compared for PTV doses, organ-at-risk (OAR) doses, and treatment times. RESULTS: Dose distribution in the Hs plan was less homogeneous and uniform than that in the H and TD plans. The TD plan had lower lung, heart, contralateral breast, spinal cord, liver, and esophagus doses than the Hs plan. Compared to the Hs plan, the H plan had lower lung volume receiving 5Gy (V5) (39.1±3.9 vs. 41.2±3.9 Gy; p<0.001), higher V20 (12.3±1.3 vs. 11.5±2.6 Gy; p=0.02), and higher V30 (7.5±1.6 vs. 4.4±1.7 Gy; p<0.001). H plan outperformed Hs plan in heart dosimetric parameters except V20. The Hs plan had significantly lower mean implant doses (43.4±2.1 Gy) than the H plan (51.4±0.5 Gy; p<0.001) and the TD plan (51.9±0.6 Gy; p<0.001). Implementing an implant sparing technique for silicone dose reduction decreases lung doses. CONCLUSION: Conventional H and TD plans outperform the implant sparing helical plan dosimetrically. Because capsular contracture during RT is unpredictable, long-term clinical outcomes are required to determine whether silicon should be spared.