Personalized setting of plan parameters using feasibility dose volume histogram for auto-planning in Pinnacle system

Essentially unedited deep-learning-based OARs are suitable for rigorous oropharyngeal and laryngeal cancer treatment planning

Quality of organ at risk (OAR) autosegmentation is often judged by concordance metrics against the human-generated gold standard. However, the ultimate goal is the ability to use unedited autosegmented OARs in treatment planning, while maintaining the plan quality. We tested this approach with head and neck (HN) OARs generated by a prototype deep-learning (DL) model on patients previously treated for oropharyngeal and laryngeal cancer. Forty patients were selected, with all structures delineated by an experienced physician. For each patient, a set of 13 OARs were generated by the DL model. Each patient was re-planned based on original targets and unedited DL-produced OARs. The new dose distributions were then applied back to the manually delineated structures. The target coverage was evaluated with inhomogeneity index (II) and the relative volume of regret. For the OARs, Dice similarity coefficient (DSC) of areas under the DVH curves, individual DVH objectives, and composite continuous plan quality metric (PQM) were compared. The nearly identical primary target coverage for the original and re-generated plans was achieved, with the same II and relative volume of regret values. The average DSC of the areas under the corresponding pairs of DVH curves was 0.97 ± 0.06. The number of critical DVH points which met the clinical objectives with the dose optimized on autosegmented structures but failed when evaluated on the manual ones was 5 of 896 (0.6%). The average OAR PQM score with the re-planned dose distributions was essentially the same when evaluated either on the autosegmented or manual OARs. Thus, rigorous HN treatment planning is possible with OARs segmented by a prototype DL algorithm with minimal, if any, manual editing.

Comparing breath hold versus free breathing irradiation for left-sided breast radiotherapy by PlanIQ™

BACKGROUND

Breast cancer is the most widespread cancer in women and young women worldwide. Moving towards customised radiotherapy, balancing the use of the available technology with the best treatment modality may not be an easy task in the daily routine. This study aims to evaluate the effectiveness of introducing IQ-feasibility into clinical practice to support the decision of free-breathing (FB) versus breath-hold (BH) left-sided breast irradiations, in order to optimise the technology available and the effectiveness of the treatment.

METHODS

Thirty-five patients who received 3D radiotherapy treatment of the left breast in deep-inspiration BH were included in this retrospective study. Computed tomography scans in FB and BH were acquired for each patient; targets contoured in both imaging datasets by an experienced radiation oncologist, and organs at risk delineated using automatic segmentation software were exported to PlanIQ™ (Sun Nuclear Corp.) to generate feasibility dose volume histogram (FDVHs). The dosimetric parameter of BH versus FB FDVH, and BH clinical dataset versus BH FDVH were compared.

RESULTS

A total of 30 patients out of 35 patients analysed, presented for the BH treatments a significant reduction (p < 0.05) in the heart mean dose ([Formula: see text]), volume receiving 5 Gy ([Formula: see text]) and 20 Gy ([Formula: see text]), of 35.7%, 54.5%, and 2.1%, respectively; for the left lung, a lower reduction was registered and significant only for [Formula: see text] (21.4%, p = 0.046). For the remaining five patients, the FDVH cut-off points of heart and lung were superimposable with differences of less than 1%. Heart and left lung dosimetric parameters of the BH clinical plans are located in the difficult zone of the FDVH and differ significantly (p < 0.05) from the corresponding parameters of the FDVH curves delimiting this buffer area between the impossible and feasible zones, respectively.

CONCLUSION

The use of PlanIQTM as a decision-support tool for the FB versus BH treatment delivery modality allows customisation of the treatment technique using the most appropriate technology for each patient enabling accurate management of available technologies.

Automated treatment planning for liver cancer stereotactic body radiotherapy

PURPOSE

To evaluate the quality of fully automated stereotactic body radiation therapy (SBRT) planning based on volumetric modulated arc therapy, which can reduce the reliance on historical plans and the experience of dosimetrists.

METHODS

Fully automated re-planning was performed on twenty liver cancer patients, automated plans based on automated SBRT planning (ASP) program and manual plans were conducted and compared. One patient was randomly selected and evaluate the repeatability of ASP, ten automated and ten manual SBRT plans were generated based on the same initial optimization objectives. Then, ten SBRT plans were generated for another selected randomly patient with different initial optimization objectives to assess the reproducibility. All plans were clinically evaluated in a double-blinded manner by five experienced radiation oncologists.

RESULTS

Fully automated plans provided similar planning target volume dose coverage and statistically better organ at risk sparing compared to the manual plans. Notably, automated plans achieved significant dose reduction in spinal cord, stomach, kidney, duodenum, and colon, with a median dose of D2% reduction ranging from 0.64 to 2.85 Gy. R50% and Dmean of ten rings for automated plans were significantly lower than those of manual plans. The average planning time for automated and manual plans was 59.8 ± 7.9 min vs. 127.1 ± 16.8 min (- 67.3 min).

CONCLUSION

Automated planning for SBRT, without relying on historical data, can generate comparable or even better plan quality for liver cancer compared with manual planning, along with better reproducibility, and less clinically planning time.

Toward Systematic Assessment and Improvement of Radiation Therapy Plan Quality of Cooperative Group Trial Submissions: A Report From the Children's Oncology Group

PURPOSE

This study evaluates the quality of plans used for the treatment of patients in the Children's Oncology Group study ACNS1123. Plan quality is quantified based on a scoring system specific to the protocol. In this way, the distribution of plan quality scores is determined that can be used to identify plan quality issues for this study and for future plan quality improvement.

METHODS AND MATERIALS

ACNS1123 stratum 1 patients (70) were evaluated. This included 50 photon and 20 proton plans. Digital Imaging and Communications in Medicine (DICOM) structure and dose data were obtained from the Children's Oncology Group. A commercially available plan quality scoring algorithm was used to create a scoring system we designed using the protocol dosimetric requirements. The whole ventricle and boost planning target volumes (PTVs) could earn a maximum of 70 points, whereas the organs at risk could earn 30 points (total maximum score of 100 points). The scoring algorithm adjusted scores based on the difficulty in achieving the structure dose requirements, which depended on the proximity of the PTVs and the dose gradients achieved relative to the organs at risk. The distribution of plan scores was used to determine the mean, median, and range of scores.

RESULTS

The median adjusted plan quality scores for the 20 proton and 50 photon plans were 83.3 and 86.9, respectively. The range of adjusted scores (maximum to minimum) was 50 points. The average score adjustment was 7.4 points. Photon and proton plans performed almost equally. Average plan quality by individual structure revealed that the brain stem, PTV boost, and cochlea lost the most points.

CONCLUSIONS

This report is the first to systematically analyze overall radiation therapy plan quality scores for an entire cohort of patients treated in a cooperative group clinical trial. The methodology demonstrated a large variation in plan quality in this trial. Future clinical trials could potentially use this method to reduce plan quality variability, which may improve outcomes.

Multi-isocenter VMAT craniospinal irradiation using feasibility dose-volume histogram-guided auto-planning technique

This study aims to propose a novel treatment planning methodology for multi-isocenter volumetric modulated arc therapy (VMAT) craniospinal irradiation (CSI) using the special feasibility dose-volume histogram (FDVH)-guided auto-planning (AP) technique. Three different multi-isocenter VMAT -CSI plans were created, including manually based plans (MUPs), conventional AP plans (CAPs) and FDVH-guided AP plans (FAPs). The CAPs and FAPs were specially designed by combining multi-isocenter VMAT and AP techniques in the Pinnacle treatment planning system. Specially, the personalized optimization parameters for FAPs were generated using the FDVH function implemented in PlanIQ software, which provides the ideal organs at risk (OARs) sparing for the specific anatomical geometry based on the valuable assumption of the dose fall-off. Compared to MUPs, CAPs and FAPs significantly reduced the dose for most of the OARs. FAPs achieved the best homogeneity index (0.092 ± 0.013) and conformity index (0.980 ± 0.011), while CAPs were slightly inferior to the FAPs but superior to the MUPs. As opposed to MUPs, FAPs delivered a lower dose to OARs, whereas the difference between FAPs and CAPs was not statistically significant except for the optic chiasm and inner ear_L. The two AP approaches had similar MUs, which were significantly lower than the MUPs. The planning time of FAPs (145.00 ± 10.25 min) was slightly lower than that of CAPs (149.83 ± 14.37 min) and was substantially lower than that of MUPs (157.92 ± 16.11 min) with P < 0.0167. Overall, introducing the multi-isocenter AP technique into VMAT-CSI yielded positive outcomes and may play an important role in clinical CSI planning in the future.

Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning

The aim of this study was to improve the protection of organs at risk (OARs), decrease the total planning time and maintain sufficient target doses using scripting endometrial cancer external beam radiation therapy (EBRT) planning. Computed tomography (CT) data of 14 endometrial cancer patients were included in this study. Manual and automatic planning with scripting were performed for each CT. Scripts were created in the RayStation™ (RaySearch Laboratories AB, Stockholm, Sweden) planning system using a Python code. In scripting, seven additional contours were automatically created to reduce the OAR doses. The scripted and manual plans were compared to each other in terms of planning time, dose-volume histogram (DVH) parameters, and total monitor unit (MU) values. While the mean total planning time for manual planning was 368 ± 8 s, it was only 55 ± 2 s for the automatic planning with scripting (p < 0.001). The mean doses of OARs decreased with automatic planning (p < 0.001). In addition, the maximum doses (D2% and D1%) for bilateral femoral heads and the rectum were significantly reduced. It was observed that the total MU value increased from 1146 ± 126 (manual planning) to 1369 ± 95 (scripted planning). It is concluded that scripted planning has significant time and dosimetric advantages over manual planning for endometrial cancer EBRT planning.

Using feasibility dose-volume histograms to reduce intercampus plan quality variability for head-and-neck cancer

The purpose of this work is to objectively assess variability of intercampus plan quality for head-and-neck (HN) cancer and to test utility of a priori feasibility dose-volume histograms (FDVHs) as planning dose goals. In this study, 109 plans treated from 2017 to 2019 were selected, with 52 from the main campus and 57 from various regional centers. For each patient, the planning computed tomography images and contours were imported into a commercial program to generate FDVHs with a feasibility value (f-value) ranging from 0.0 to 0.5. For 10 selected organs-at-risk (OARs), we used the Dice similarity coefficient (DSC) to quantify the overlaps between FDVH and clinically achieved DVH of each OAR and determined the f-value associated with the maximum DSC (labeled as f-max). Subsequently, 10 HN plans from the regional centers were replanned with planning dose goals guided by FDVHs. The clinical and feasibility-guided auto-planning (FgAP) plans were evaluated using our institutional criteria. Among plans from the main campus and regional centers, the median f-max values were statistically significantly different (p < 0.05) for all OARs except for the left parotid (p = 0.622), oral cavity (p = 0.057), and mandible (p = 0.237). For the 10 FgAP plans, the median values of f-max were 0.21, compared to 0.37 from the clinical plans. With comparable dose coverage to the tumor volumes, the significant differences (p < 0.05) in the median f-max and corresponding dose reduction (shown in parenthesis) for the spinal cord, larynx, supraglottis, trachea, and esophagus were 0.27 (8.5 Gy), 0.3 (7.6 Gy), 0.19 (5.9 Gy), 0.19 (8.9 Gy), and 0.12 (4.0 Gy), respectively. In conclusion, the FDVH prediction is an objective quality assurance tool to evaluate the intercampus plan variability. This tool can also provide guideline in planning dose goals to further improve plan quality.

Evaluation of two independent dose prediction methods to personalize the automated radiotherapy planning process for prostate cancer

Background and purpose

Currently, automatic approaches for radiotherapy planning are widely used, however creation of high quality treatment plans is still challenging. In this study, two independent dose prediction methods were used to personalize the initial settings for the automated planning template for optimizing prostate cancer treatment plans. This study evaluated the dose metrics of these plans comparing both methods with the current clinical automated prostate cancer treatment plans.

Material and methods

Datasets of 20 high-risk prostate cancer treatment plans were taken from our clinical database. The prescription dose for these plans was 70 Gy given in fractions of 2.5 Gy. Plans were replanned using the current clinical automated treatment and compared with two personalized automated planning methods. The feasibility dose volume histogram (FDVH) and modified filter back projection (mFBP) methods were used to calculate independent dose predictions. Parameters for the initial objective values of the planning template were extracted from these predictions and used to personalize the optimization of the automated planning process.

Results

The current automated replanned clinical plans and the automated plans optimized with the personalized template methods fulfilled the clinical dose criteria. For both methods a reduction in the average mean dose of the rectal wall was found, from 22.5 to 20.1 Gy for the FDVH and from 22.5 to 19.6 Gy for the mFBP method.

Conclusions

With both dose-prediction methods the initial settings of the template could be personalized. Hereby, the average dose to the rectal wall was reduced compared to the standard template method.

Implementation of automatic plan optimization in Italy: Status and perspectives

PURPOSE

To investigate and report on the diffusion and clinical use of automated radiotherapy planning systems in Italy and to assess the perspectives of the community of Italian medical physicists involved in radiotherapy on the use of these tools.

MATERIALS AND METHODS

A survey of medical physicists (one per Institute) of 175 radiotherapy centers in Italy was conducted between February 21st and April 1st, 2021. The information collected included the institute's characteristics, plan activity, availability/use of automatic tools and related issues regarding satisfaction, criticisms, expectations, and perceived professional modifications. Responses were analysed, including the impact of a few variables such as the institute type and experience.

RESULTS

125 of the centers (71%) answered the survey, with regional variability (range: 47%-100%); among these, 49% have a TPS with some automatic option. Clinical use of automatic planning is present in 33% of the centers, with 13% applying it in >50% of their plans. Among the 125 responding centres the most used systems are Pinnacle (16%), Raystation (9%) and Eclipse (4%). The majority of participants consider the use of automated techniques to be beneficial, while only 1% do not see any advantage; 83% of respondents see the possibility of enriching their professional role as a potential benefit, while 3% see potential threats.

CONCLUSIONS

Our survey shows that 49% of the responding centres have an automatic planning solution although clinically used in only 33% of the cases. Most physicists consider the use of automated techniques to be beneficial and show a prevalently positive attitude.

Systematic quantitative evaluation of Plan-IQ for intensity-modulated radiation therapy after modified radical mastectomy

Radiotherapy (RT) is one of the main treatment strategies of breast cancer. It is challenging to design RT plans that can completely cover the target area while protecting organs at risk (OAR). The Plan-IQ feasibility tool can estimate the best sparing dose of OAR before optimizing the Plan. A systematic quantitative evaluation of the quality change of intensity-modulated radiation therapy (IMRT) using the Plan-IQ feasibility tool was performed for modified radical mastectomy in this study. We selected 50 patients with breast cancer treated with IMRT. All patients received the same dose in the planning target volume (PTV). The plans are categorized into two groups, with each patient having one plan in each group: the clinically accepted normal plan group (NP group) and the repeat plan group (RP group). An automated planning strategy was generated using a Plan-IQ feasibility dose volume histogram (FDVH) in RP group. These plans were assessed according to the dosimetry parameters. A detailed scoring strategy was based on the RTOG9804 report and 2018 National Comprehensive Cancer Network guidelines, combined with clinical experience. PTV coverage in both groups was achieved at 100% of the prescribed dose. Except for the thyroid coverage, the dose limit of organs at risk (OAR) in RP group was significantly better than that in NP group. In the scoring analysis, the total scores of RP group decreased compared to that of NP group (P < 0.05), and the individual scores of PTV and OAR significantly changed. PTV scores in RP group decreased (P < 0.01); however, OAR scores improved (P < 0.01). The Plan-IQ FDVH was useful for evaluating a class solution for IMRT planning. Plan-IQ can automatically help physicians design the best OAR protection plan, which sacrifices part of PTV, but still meets clinical requirements.

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.

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.

Characterization of automatic treatment planning approaches in radiotherapy

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Auto-Planning is widely used, yet creation of high quality treatment plans remains challenging.

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Systematic investigation of behavior and optimal use of Auto-Planning.

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Widely applicable solutions to create optimal plans.

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Auto-Planning outperforms manual plans in DVH metrics and blind comparisons.

Background and purpose

Automatic approaches are widely implemented to automate dose optimization in radiotherapy treatment planning. This study systematically investigates how to configure automatic planning in order to create the best possible plans.

Materials and methods

Automatic plans were generated using protocol based automatic iterative optimization. Starting from a simple automation protocol which consisted of the constraints for targets and organs at risk (OAR), the performance of the automatic approach was evaluated in terms of target coverage, OAR sparing, conformity, beam complexity, and plan quality. More complex protocols were systematically explored to improve the quality of the automatic plans. The protocols could be improved by adding a dose goal on the outer 2 mm of the PTV, by setting goals on strategically chosen subparts of OARs, by adding goals for conformity, and by limiting the leaf motion. For prostate plans, development of an automated post-optimization procedure was required to achieve precise control over the dose distribution. Automatic and manually optimized plans were compared for 20 head and neck (H&N), 20 prostate, and 20 rectum cancer patients.

Results

Based on simple automation protocols, the automatic optimizer was not always able to generate adequate treatment plans. For the improved final configurations for the three sites, the dose was lower in automatic plans compared to the manual plans in 12 out of 13 considered OARs. In blind tests, the automatic plans were preferred in 80% of cases.

Conclusions

With adequate, advanced, protocols the automatic planning approach is able to create high-quality treatment plans.

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 (PlanIQ^TM) 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 PlanIQ^TM assessment tool (Feasibility DVH^TM) 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 DVH^TM. The quality of each treatment plan was evaluated based on a scoring system implemented in PlanIQ^TM.

RESULTS

Of 5 patients included, 4 received improved treatment plans when Feasibility DVH^TM was used. Moreover, 4 of 5 treatment planners showed improvement in treatment planning using Feasibility DVH^TM.

CONCLUSIONS

The findings suggest that using the Feasibility DVH^TM 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.

Analysis of prostate intensity- and volumetric-modulated arc radiation therapy planning quality with PlanIQTM

Purpose

The purpose of this study was to assess the quality of treatment planning using the PlanIQ^TM software and to investigate whether it is possible to improve the quality of treatment planning using the “Feasibility dose‐volume histogram (DVH)^TM” implemented in the PlanIQ^TM software.

Methods

Using the PlanIQ^TM software, we retrospectively analyzed the learning curve regarding the quality of the treatment plans for 148 patients of prostate intensity‐modulated radiation therapy and volumetric‐modulated radiation therapy performed at our institution over the past eight years. We also sought to examine the possibility of improving treatment planning quality by re‐planning in 47 patients where the quality of the target dose and the dose limits for organs at risk (OARs) were inadequate. The re‐planning treatment plans referred to the Feasibility DVH^TM implemented in the PlanIQ^TM software and modified the treatment planning system based on the target dose and OAR constraints.

Results

Analysis of the learning curve of the treatment plans quality using PlanIQ^TM software retrospectively showed a trend of improvement in the treatment plan quality from year to year. The improvement in the treatment plans quality was more influenced by dose reduction in the OARs than by target coverage.

In all cases where re‐planning was performed, the improvement in the treatment plan's quality resulted in a better treatment plan than the one adopted for delivery to patients in the clinical plan.

Conclusions

The PlanIQ^TM provided insights into the quality of the treatment plans at our institution and identified problems and areas for improvement in the treatment plans, allowing for the development of appropriate treatment plans for specific patients.

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.