An effective calculation method for an overlap volume histogram descriptor and its application in IMRT plan retrieval

Application of dose-gradient function in reducing radiation induced lung injury in breast cancer radiotherapy

OBJECTIVE

Try to create a dose gradient function (DGF) and test its effectiveness in reducing radiation induced lung injury in breast cancer radiotherapy.

MATERIALS AND METHODS

Radiotherapy plans of 30 patients after breast-conserving surgery were included in the study. The dose gradient function was defined as DGH=VDVp3, then the area under the DGF curve of each plan was calculated in rectangular coordinate system, and the minimum area was used as the trigger factor, and other plans were triggered to optimize for area reduction. The dosimetric parameters of target area and organs at risk in 30 cases before and after re-optimization were compared.

RESULTS

On the premise of ensuring that the target dose met the clinical requirements, the trigger factor obtained based on DGF could further reduce the V5, V10, V20, V30 and mean lung dose (MLD) of the ipsilateral lung in breast cancer radiotherapy, P < 0.01. And the D2cc and mean heart dose (MHD) of the heart were also reduced, P < 0.01. Besides, the NTCPs of the ipsilateral lung and the heart were also reduced, P < 0.01.

CONCLUSION

The trigger factor obtained based on DGF is efficient in reducing radiation induced lung injury in breast cancer radiotherapy.

Application research on reducing radiation-induced lung injury with a trigger operator based on overlap volume histogram (OVH) in breast cancer postoperative radiotherapy

This study aims to develop a trigger operator based on the Overlap Volume Histogram (OVH) and examined its effectiveness in enhancing plan quality to minimize radiation-induced lung injury in postoperative radiotherapy for breast cancer. This trigger operator was applied for plan re-optimization to the previous Volumetric Modulated Arc Therapy (VMAT) plans of 16 left breast conserving surgery cases. These cases were categorized into a Contiguous Group (CG) and a Separated Group (SG) based on the relative position between the target and the Left-Lung (L-Lung). We investigated the changes in Vx, mean dose, and Normal Tissue Complication Probability (NTCP) values of organs-at-risk (OARs) before and after using the trigger operator. The Pairwise Sample T test was employed to evaluate the differences in indices between the two groups before and after optimizations. The trigger operator effectively initiated plan re-optimization. The values of V5, V10, V20, V30, and V40 of the L-Lung, as well as the mean dose of the heart, all decreased after re-optimization. The Pairwise Sample T test results showed statistically significant differences in the V20, V30, and V40 of the L-Lung in the CG (P < 0.01), and in the V5, V10, V20, V30, and V40 of the L-Lung in the SG (P < 0.01). Our findings suggest that the proposed trigger operator can improve plan quality, thereby reducing radiation-induced lung injury in postoperative radiotherapy for breast cancer.

Evaluation of Auto-Planning for Left-Side Breast Cancer After Breast-Conserving Surgery Based on Geometrical Relationship

PURPOSE

This study aimed to evaluate (1) the performance of the Auto-Planning module embedded in the Pinnacle treatment planning system (TPS) with 30 left-side breast cancer plans and (2) the dose-distance correlations between dose-based patients and overlap volume histogram-based (OVH) patients.

METHOD

A total of 30 patients with left-side breast cancer after breast-conserving surgery were enrolled in this study. The clinical manual-planning (MP) and the Auto-Planning (AP) plans were generated by Monaco and by the Auto-Planning module in Pinnacle respectively. The geometric information between organ at risk (OAR) and planning target volume (PTV) of each patient was described by the OVH. The AP and MP plans were ranked to compare with the geometry-based patients from OVH. The Pearson product-moment correlation coefficient (R) was used to describe the correlations between dose-based patients (APs and MPs) and geometry-based patients (OVH). Dosimetric differences between MP and AP plans were evaluated with statistical analysis.

RESULT

The correlation coefficient (mean R = 0.71) indicated that the AP plans have a high correlation with geometry-based patients from OVH, whereas the correlation coefficient (mean R = 0.48) shows a weak correlation between MP plans and geometry-based patients. The dosimetric comparison revealed a statistically significant improvement in the ipsilateral lung V_5Gy and V_10Gy, and in the heart V_5Gy of AP plans compared to MP plans, while statistical reduction was seen in PTV V_107% for MP plans compared to AP plans.

CONCLUSION

The overall results of AP plans were superior to MP plans. The dose distribution in AP plans was more consistent with the distance-dose relationship described by OVH. After eliminating the interference of human factors, the AP was able to provide more stable and objective plans for radiotherapy patients.

The status of medical physics in radiotherapy in China

PURPOSE

To present an overview of the status of medical physics in radiotherapy in China, including facilities and devices, occupation, education, research, etc. MATERIALS AND METHODS: The information about medical physics in clinics was obtained from the 9-th nationwide survey conducted by the China Society for Radiation Oncology in 2019. The data of medical physics in education and research was collected from the publications of the official and professional organizations.

RESULTS

By 2019, there were 1463 hospitals or institutes registered to practice radiotherapy and the number of accelerators per million population was 1.5. There were 4172 medical physicists working in clinics of radiation oncology. The ratio between the numbers of radiation oncologists and medical physicists is 3.51. Approximately, 95% of medical physicists have an undergraduate or graduate degrees in nuclear physics and biomedical engineering. 86% of medical physicists have certificates issued by the Chinese Society of Medical Physics. There has been a fast growth of publications by authors from mainland of China in the top international medical physics and radiotherapy journals since 2018.

CONCLUSIONS

Demand for medical physicists in radiotherapy increased quickly in the past decade. The distribution of radiotherapy facilities in China became more balanced. High quality continuing education and training programs for medical physicists are deficient in most areas. The role of medical physicists in the clinic has not been clearly defined and their contributions have not been fully recognized by the community.

Predictive performance of an OVH-based treatment planning quality assurance model for prostate VMAT: Assessing dependence on training cohort size and composition

Radiotherapy treatment planning quality assurance models are used to assess overall plan quality in terms of dose-volume characteristics, by predicting an optimal dosimetry based on a dataset of prior cases (the training cohort). In this study, a treatment planning quality assurance model for prostate cancer patients treated with volumetric modulated arc therapy was developed using the concept of the overlap volume histogram for geometric comparison to the training cohort. The model was developed on the publically available Erasmus iCycle dataset in order to remove the effect of plan quality/inter-planner variability on the model's predictive capabilities. The model was used to predict anus, rectum, and bladder dose volume histograms. Two versions were developed: the n = 114 case (leave-one-out method) which made predictions using the complete Erasmus dataset, and the similarity index (SI)-based model which used a smaller training cohort allocated in order of geometric similarity determined using an overlap volume histogram-derived SI. The difference in mean dose (predicted-achieved) of the SI model at cohort sizes of 10, 20, 30, 40, 50, 75, and 100 was compared to the leave-one-out method for 5 patients, in an attempt to determine the "optimum" cohort size for the SI-based model in this dataset. Performance of the optimized SI model was compared to the leave-one-out method for all patients using the following metrics: difference in mean and median dose, difference in V65Gy and V75Gy (rectum only), similarity of predicted and achieved mean dose, and mean dose volume histograms residual. The "optimum" cohort size for the SI-based model was determined to be 45. The SI-based model implementing this cohort size yielded slightly better outcomes in all performance metrics for the rectum and anus, but worse for the bladder. SI-based training cohort allocation can lead to better predictive efficacy, but the cohort size should be optimized for each individual organ.