Differences between professionals in treatment planning for patients with stage III lung cancer using treatment-planning QA software.

Background: The quality of treatment planning for stage III non-small cell lung cancer varies within and between facilities due to the different professions involved in planning. Dose estimation parameters were calculated using a feasibility dose-volume histogram (FDVH) implemented in the treatment planning quality assurance software PlanIQ. This study aimed to evaluate differences in treatment planning between occupations using manual FDVH-referenced treatment planning to identify their characteristics. Materials and methods: The study included ten patients with stage III non-small cell lung cancer, and volumetric-modulated arc therapy was used as the treatment planning technique. Fifteen planners, comprising five radiation oncologists, five medical physicists, and five radiological technologists, developed treatment strategies after referring to the FDVH. Results: Medical physicists had a higher mean dose at D98% of the planning target volume (PTV) and a lower mean dose at D2% of the PTV than those in other occupations. Medical physicists had the lowest irradiation lung volumes (V5 Gy and V13 Gy) compared to other professions, and radiation oncologists had the lowest V20 Gy and mean lung dose. Radiological technologists had the highest irradiation volumes for dose constraints at all indexes on the normal lung volume. Conclusions: The quality of the treatment plans developed in this study differed between occupations due to their background expertise, even when an FDVH was used as a reference. Therefore, discussing and sharing knowledge and treatment planning techniques among professionals is essential to determine the optimal treatment plan for each facility and patient.

Predicting the complexity of head-and-neck volumetric-modulated arc therapy planning using a radiation therapy planning quality assurance software.

Background/Aim: The more complex the treatment plan, the higher the possibility of errors in dose verification. Recently, a treatment planning quality assurance (QA) software (PlanIQ) with a function to objectively evaluate the quality of volumetric-modulated arc therapy (VMAT) treatment plans by scoring and calculating the ideal dose-volume histogram has been marketed. This study aimed to assess the association between the scores of ideal treatment plans identified using PlanIQ and the results of dose verification and to investigate whether the results of dose verification can be predicted based on the complexity of treatment plans. Materials and methods: Dose verification was performed using an ionization chamber dosimeter, a radiochromic film, and a three-dimensional dose verification system, Delta4 PT. Correlations between the ideal treatment plan scores obtained by PlanIQ and the results of the absolute dose verification and dose distribution verification were obtained, and it was examined whether dose verifications could be predicted from the complexity of the treatment plans. Results: Even when the score from the ideal treatment plan was high, the results of absolute dose verification and dose distribution verification were sometimes poor. However, even when the score from the ideal treatment plan was low, the absolute volume verification and dose distribution verification sometimes yielded good results. Conclusions: Treatment plan complexity can be determined in advance from the ideal treatment plan score calculated by PlanIQ. However, it is difficult to predict the results of dose verification using an ideal treatment plan.

A comparison of two methodologies for radiotherapy treatment plan optimization and QA for clinical trials.

BACKGROUND AND PURPOSE: The efficacy of clinical trials and the outcome of patient treatment are dependent on the quality assurance (QA) of radiation therapy (RT) plans. There are two widely utilized approaches that include plan optimization guidance created based on patient-specific anatomy. This study examined these two techniques for dose-volume histogram predictions, RT plan optimizations, and prospective QA processes, namely the knowledge-based planning (KBP) technique and another first principle (FP) technique. METHODS: This analysis included 60, 44, and 10 RT plans from three Radiation Therapy Oncology Group (RTOG) multi-institutional trials: RTOG 0631 (Spine SRS), RTOG 1308 (NSCLC), and RTOG 0522 (H&N), respectively. Both approaches were compared in terms of dose prediction and plan optimization. The dose predictions were also compared to the original plan submitted to the trials for the QA procedure. RESULTS: For the RTOG 0631 (Spine SRS) and RTOG 0522 (H&N) plans, the dose predictions from both techniques have correlation coefficients of >0.9. The RT plans that were re-optimized based on the predictions from both techniques showed similar quality, with no statistically significant differences in target coverage or organ-at-risk sparing. The predictions of mean lung and heart doses from both methods for RTOG1308 patients, on the other hand, have a discrepancy of up to 14 Gy. CONCLUSIONS: Both methods are valuable tools for optimization guidance of RT plans for Spine SRS and Head and Neck cases, as well as for QA purposes. On the other hand, the findings suggest that KBP may be more feasible in the case of inoperable lung cancer patients who are treated with IMRT plans that have spatially unevenly distributed beam angles.

Refining complex re-irradiation dosimetry through feasibility benchmarking and analysis for informed treatment planning.

PURPOSE/OBJECTIVES: The purpose of this study is to dually evaluate the effectiveness of PlanIQ in predicting the viability and outcome of dosimetric planning in cases of complex re-irradiation as well as generating an equivalent plan through Pinnacle integration. The study also postulates that a possible strength of PlanIQ lies in mitigating pre-optimization uncertainties tied directly to dose overlap regions where re-irradiation is necessary. METHODS: A retrospective patient selection (n = 20) included a diverse range of re-irradiation cases to be planned using Pinnacle auto-planning with PlanIQ integration. A consistent planning template was developed and applied across all cases. Direct plan comparisons of manual plans against feasibility-produced plans were performed by physician(s) with dosimetry recording relevant proximal OAR and planning timeline data. RESULTS AND DISCUSSION: All re-irradiation cases were successfully predicted to be achievable per PlanIQ analyses with three cases (3/20) necessitating 95% target coverage conditions, previously exhibited in the manually planned counterparts, and determined acceptable under institutional standards. At the same time, PlanIQ consistently produced plans of equal or greater quality to the previously manually planned re-irradiation across all (20/20) trials (P = 0.05). Proximal OAR exhibited similar to slightly improved maximum point doses from feasibility-based planning with the largest advantages gained found within the subset of cranial and spine overlap cases, where improvements upward of 10.9% were observed. Mean doses to proximal tissues were found to be a statistically significant (P < 0.05) 5.0% improvement across the entire study. Documented planning times were markedly less than or equal to the time contributed to manual planning across all cases. CONCLUSION: Initial findings indicate that PlanIQ effectively provides the user clear feasibility feedback capable of facilitating decision-making on whether re-irradiation dose objectives and prescription dose coverage are possible at the onset of treatment planning thus eliminating possible trial and error associated with some manual planning. Introducing model-based prediction tools into planning of complex re-irradiation cases yielded positive outcomes on the final treatment plans.

Evaluation of plan quality improvements in PlanIQ-guided Autoplanning.

AIM: Philips recently integrated PlanIQ with Autoplan® in Pinnacle3 TPS (V16.2). The objective of the present work is to quantitatively demonstrate how this integration improves the plan quality. BACKGROUND: Pinnacle3 Autoplan® is the tool that generates the treatment plans with clinically acceptable plan quality with less manual intervention. In the recent past, a new tool called PlanIQ (Sun Nuclear Corp.) was introduced for a priori estimation of the best possible sparing of an organ at risk (OAR) for a given patient anatomy. Philips has recently integrated PlanIQ tool with Autoplan® for a seamless and efficient planning workflow. MATERIALS AND METHODS: We have performed this evaluation in Pinnacle3 TPS (V.16.2) for the VMAT treatment technique. All plans were created using Varian True beam machine with the dual arc technique. Basically, we created two sets of VMAT plans using 6 MV photons. In the first set of VMAT plans (AP_RTOG), we used OAR goals from either RTOG guidelines to perform optimization using Autoplan®. Subsequently, we exported the same dataset to the PlanIQ system to perform feasibility analysis on the OAR goals. These newly obtained OAR goals from PlanIQ were used to generate the other set of plans (AP_PlanIQ plans). We compared the dosimetric results from these two sets of plans in five cases, such as brain, head & neck, lung, abdomen and prostate. RESULTS: We compared the dosimetric results for AP_RTOG and AP_PlanIQ plans. We used RTOG guidelines to evaluate the plans and observed that while both sets of plans were meeting the RTOG guidelines in terms of OAR sparing, the AP_PlanIQ plans were significantly better in terms of OAR sparing as compared to AP_RTOG plans without any compromise in the target coverage. CONCLUSION: The results indicate that, although Autoplan helps achieve the user-defined goals without much manual intervention, the plan quality (OAR sparing) can be significantly improved without taking many iterative steps when PlanIQ suggested clinical goals are used in the Autoplan-based optimization. ADVANCES IN KNOWLEDGE: At present, there are no published material available about the efficacy of the integration of PlanIQ with Autoplanning®. In the present work, our objective is to evaluate the improvements in plan quality resulting from this integration.

Assessment of PlanIQ Feasibility DVH for head and neck treatment planning.

INTRODUCTION: Designing a radiation plan that optimally delivers both target coverage and normal tissue sparing is challenging. There are limited tools to determine what is dosimetrically achievable and frequently the experience of the planner/physician is relied upon to make these determinations. PlanIQ software provides a tool that uses target and organ at risk (OAR) geometry to indicate the difficulty of achieving different points for organ dose-volume histograms (DVH). We hypothesized that PlanIQ Feasibility DVH may aid planners in reducing dose to OARs. METHODS AND MATERIALS: Clinically delivered head and neck treatments (clinical plan) were re-planned (re-plan) putting high emphasis on maximally sparing the contralateral parotid gland, contralateral submandibular gland, and larynx while maintaining routine clinical dosimetric objectives. The planner was blinded to the results of the clinically delivered plan as well as the Feasibility DVHs from PlanIQ. The re-plan treatments were designed using 3-arc VMAT in Raystation (RaySearch Laboratories, Sweden). The planner was then given the results from the PlanIQ Feasibility DVH analysis and developed an additional plan incorporating this information using 4-arc VMAT (IQ plan). The DVHs across the three treatment plans were compared with what was deemed "impossible" by PlanIQ's Feasibility DVH (Impossible DVH). The impossible DVH (red) is defined as the DVH generated using the minimal dose that any voxel outside the targets must receive given 100% target coverage. RESULTS: The re-plans performed blinded to PlanIQ Feasibilty DVH achieved superior sparing of aforementioned OARs compared to the clinically delivered plans and resulted in discrepancies from the impossible DVHs by an average of 200-700 cGy. Using the PlanIQ Feasibility DVH led to additionalOAR sparing compared to both the re-plans and clinical plans and reduced the discrepancies from the impossible DVHs to an average of approximately 100 cGy. The dose reduction from clinical to re-plan and re-plan to IQ plan were significantly different even when taking into account multiple hypothesis testing for both the contralateral parotid and the larynx (P < 0.004 for all comparisons). No significant differences were observed between the three plans for the contralateral parotid when considering multiple hypothesis testing. CONCLUSIONS: Clinical treatment plans and blinded re-plans were found to suboptimally spare OARs. PlanIQ could aid planners in generating treatment plans that push the limits of OAR sparing while maintaining routine clinical target coverage goals.

Knowledge-based model building for treatment planning for prostate cancer using commercial treatment planning quality assurance software tools.

This study devised a method to efficiently launch the RapidPlan model for volumetric-modulated arc therapy for prostate cancer in small- and medium-sized facilities using high-quality treatment plans with the PlanIQ software as a reference. Treatment plans were generated for 30 patients with prostate cancer to construct the RapidPlan model using PlanIQ as a reference. In the context of PlanIQ-referenced treatment planning, treatment plans were developed, such that the feasibility dose-volume histogram of each organ-at-risk fell within F ≤ 0.1. For validation of the RapidPlan model, treatment plans were formulated for 20 patients using both RapidPlan and PlanIQ, and the differences were evaluated. The results of RapidPlan model validity assessment revealed that the RapidPlan-produced treatment plans exhibited higher quality in 11 of 20 patients. No significant differences were found between the treatment plans. In conclusion, high-quality treatment plans formulated using PlanIQ as reference facilitated efficient implementation of RapidPlan modeling.

Comparative analysis of two dose-volume histogram prediction tools for treatment planning in volumetric-modulated arc therapy: A multi-planner study.

The increase in high-precision radiation therapy, particularly volumetric-modulated arc therapy (VMAT), has increased patient numbers and expanded treatment sites. However, a significant challenge in VMAT treatment planning is the inconsistent plan quality among different planners and facilities. This study explored the use of dose-volume histogram (DVH) prediction tools to address these disparities, specifically focusing on RapidPlan (Varian Medical Systems) and PlanIQ (Sun Nuclear). RapidPlan predicts achievable DVHs and automatically generates optimization objectives. While it has demonstrated organ-at-risk (OAR) dose reduction benefits, the quality of the plan used to build its model significantly affects its predictions. On the other hand, PlanIQ offers ease of use and does not require prior model-building. Five planners participated in this study, each creating two treatment plans: one referencing RapidPlan and the other using PlanIQ. The planners had the freedom to adjust parameters while referencing the DVH predictions. The plans were evaluated using "Plan Quality Metric" (PQM) scores to assess the planning target volume excluding the rectum and OARs. The results revealed that RapidPlan-referenced plans often outperformed PlanIQ-based plans, with less interplanner variability. PlanIQ played a pivotal role in the construction of the RapidPlan model. This study is the first to compare plans generated by multiple planners using both tools. This study provides insights into optimizing treatment planning by considering the characteristics of both RapidPlan and PlanIQ.

Level Ib CTV delineation in nasopharyngeal carcinoma based on lymph node distribution and topographic anatomy.

BACKGROUND AND PURPOSE: To analyze the distribution pattern of lymph nodes (LNs) metastasis of level Ib in nasopharyngeal cancer (NPC) and propose shrinkage of clinical target volume (CTV) boundaries to avoid unnecessary radiation for some space with very low-risk of involvement. MATERIALS AND METHODS: Pretreatment images of pathologically proven NPC patients were reviewed and those with positive level Ib LN metastasis was enrolled. The geometric center of each level Ib LN in the neck was marked on a template CT. The spatial relationship of nodes with key structures in level Ib was analyzed. Modified level Ib CTV according to the 2013 International CTV consensus was proposed based on the LN distribution pattern. A PlanIQ Feasibility DVH module was implemented to evaluate the feasibility analysis of the best possible sparing of organs at risk (OAR) with modified Ib CTV. RESULTS: A total of 1518 NPC patients were reviewed and 54 with positive level Ib nodes were enrolled. Four sub-level anatomical regions were defined within the gross area of level Ib. Of 106 positive nodes identified, none, one, 88, and 17 were found in the intraglandular (IG), medial mandibular (MM), supra perivascular (SP), and infra perivascular (IP) sub-level, respectively. This study proposes sparing the IG and MM sub-level and including the area within a specified distance from the submandibular gland (11 mm for SP, 17 mm for IP) for CTV coverage. Compared with planning based on CTV-consensus, planning based on CTV-proposed results in a significantly reduced CTV volume, and mean dose (Dmean) of both the ipsilateral SMG and bilateral SLG. CONCLUSIONS: Based on detailed analysis of the relationship between positive node distribution and several important anatomical structures, modified level Ib CTV for prophylactic irradiation was proposed to reduce the dose of OAR irradiation.

Impact of treatment planning quality assurance software on volumetric-modulated arc therapy plans for prostate cancer patients.

INTRODUCTION: Software that evaluates the quality of treatment plans (PlanIQTM) has become commercially available in recent years. It includes a feasibility assessment tool that provides the ideal dose volume histogram (DVH) for each organ at risk, based on the ideal dose falloff from the prescribed dose at the target boundary. It is important to investigate whether the PlanIQTM assessment tool (Feasibility DVHTM) can assist treatment planners who have limited to no experience in treatment planning. Therefore, the present study aimed to evaluate this tool's usefulness for improving the quality of treatment plans. MATERIALS & METHODS: This study included 5 patients with prostate cancer. The treatment planners were 2 graduate students, 2 undergraduate students, and one clinical planner. All students were radiological technology and medical physics students with no clinical experience. Two different volumetric-modulated arc therapy (VMAT) plans were developed before and after Feasibility DVHTM. The quality of each treatment plan was evaluated based on a scoring system implemented in PlanIQTM. RESULTS: Of 5 patients included, 4 received improved treatment plans when Feasibility DVHTM was used. Moreover, 4 of 5 treatment planners showed improvement in treatment planning using Feasibility DVHTM. CONCLUSIONS: The findings suggest that using the Feasibility DVHTM tool may improve treatment plans for different planners and patients. However, planners at any level of experience should be trained to check the dose distribution in addition to checking the DVH, which depends on the adequacy of the contours.

Lung dose reduction in patients with stage III non-small-cell lung cancer using software that estimates patient-specific dose reduction feasibility.

PURPOSE: In radiotherapy, the dose to organs-at-risk must be kept as low as possible to preserve their function. We aimed to determine the acceptable f-value upper bound of the Feasibility DVH in the PlanIQ software to achieve dose reduction to the normal lung in patients with stage III non-small cell lung cancer. METHODS: By using the Feasibility DVH, the f-values corresponding to the pulmonary dosimetric parameters of each treatment plan for 11 patients were calculated. The acceptable f-value upper bound was defined as the value that added one standard deviation of the f-value to the mean. Additionally, the treatment plan for additional fourteen patients was designed to evaluate the effectiveness of the acceptable f-value upper bound for the normal lung dose reduction. The value beyond the acceptable f-value upper bound was judged as inadequate dose reduction. RESULTS: The acceptable f-value upper bound was different for dosimetric parameters (range, 0.22-0.26). These values were < 0.5, which is typically used as the acceptable f-value upper bound. Evaluation by the treatment plan of fourteen patients detected that the f-value of the normal lung of five patients exceeded the acceptable f-value upper bound, and the replanning was able to reduce the dose of the normal lung. CONCLUSIONS: We could efficiently reduce the normal-lung dose using the acceptable f-value upper bound calculated in this study and provide an effective acceptable f-value upper bound of the normal lung dose in the lung cancer radiotherapy.

Quality re-optimization and assessment of radiotherapy plan for rectal cancer / 中国医学物理学杂志

Objective To evaluate the quality of treatment planning(TP)and re-optimization planning(RP)of radiotherapy for rectal cancer using PlanIQ software,thereby providing methods and tools for the screening and optimization of radiotherapy plans.Methods Twenty patients with rectal cancer who received radiotherapy were selected retrospectively,with 10 cases of intensity-modulated radiotherapy(IMRT)and 10 of volumetric modulated arc therapy(VMAT).(1)TP:IMRT plan involved 5-field irradiation,and VMAT plan involved two 360°arcs.The prescription doses were 50 Gy/25 f for PTV1 and 45 Gy/25 f for PTV2.All plans underwent direct machine parameter optimization and required 95%isodose lines to cover 100%of the target volume.Organs-at-risk(OAR)were limited by reference to tolerated dose standards.After the planning was completed,the plans were reviewed and confirmed by a physician,and the treatment was implemented after dose verification.(2)RP:a physicist with 10 years of experience re-optimized the 20 TP plans,with the irradiation technique and field setting unchanged.The re-optimization involved adjusting planning conditions and parameters based on individual experience until the dose to OAR was minimized while without affecting PTV coverage.The quality of TP plans and RP plans were quantitatively evaluated using PlanIQ software.Non-parametric Wilcoxon signed rank test was performed for dose-volume histogram parameters and plan quality index between two groups.Results The dose-volume histogram parameters in RP plans were superior to those in TP plans,and the differences in the Dmax of PTV1,the V45 Gy and Dmax of small intestine,and the V45 Gy of colon were statistically significant(P<0.05).The quality scores of RP plans for IMRT group,VMAT group and all patients were significantly higher than those of TP plans(P<0.05),with plan quality index of 88.55±3.35 vs 86.61±4.63(P=0.005),89.72±3.15 vs 87.21±3.04(P=0.028),and 89.14±3.22 vs 86.91±3.22(P=0.001),respectively.Conclusion RP can further improve the quality of radiotherapy plan for rectal cancer.PlanIQ software serves as an effective tool for quality control and screening of radiotherapy planning.