Performance assessment of a new optimization system for robotic SBRT MLC-based plans

Comparison of two optimization algorithms (VOLOTM , SEQU) for CyberKnife® treatment of acoustic neuromas, lung metastases, and liver metastases

INTRODUCTION

Two optimization algorithms VOLO™ and sequential optimization algorithm (SEQU) are compared in the Precision® treatment planning system from Accuray® for stereotactic radiosurgery and stereotactic body radiotherapy (SBRT) treatment plans. The aim is to compare the two algorithms to assess if VOLO™ is better of SEQU in certain treatment site.

MATERIALS AND METHODS

Sixty clinical treatment cases were compared. Entities include Acoustic neuroma (AN), lung metastases, and liver metastases. In each entity, 10 SEQU and 10 VOLO™ treatment plans were optimized. The Ray-Tracing calculation algorithm was used for all treatment plans and the treatments were planned exclusively with fixed cones (5-50 mm). The number of nodes, beams, total MU, and treatment time were compared. Conformity index (CI), new conformity index (nCI), homogeneity index (HI), gradient index (GI), and target coverage were examined for agreement. Dmin , Dmean , Dmax , D100%, D98%, and D2% dose in the target volume as well as exposure to organs at risk was checked. To determine peripheral doses, the isodose volumes from V10% to V98% were evaluated.

RESULTS

AN treatment plans showed significant differences for the number of nodes, beams, total MU, treatment time, D98%, D100% for the target volume, and the doses for all organs at risk. VOLO™ achieved better results on average. Total MU, treatment time, coverage, and D98% are significantly better for VOLO™ for lung metastases. For liver metastases, a significant reduction in number of nodes, total MU, and treatment time was observed for VOLO™ plans. The mean target coverage increased slightly with VOLO™, while the mean CI deteriorated slightly. The averages of Dmin , Dmean , D98%, D100%, and V80% resulted in a significant increase for VOLO™.

CONCLUSION

The results of the present study indicate that VOLO™ should be used in place of SEQU as a standard for AN cases moving forward. Despite the lack of significance in the lung and liver cases, VOLO™ optimization is recommended because OAR sparing was similar, but coverage, Dmin , and Dmean were increased, and thus better tumor control can be expected.

Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol

PURPOSE

To extend the knowledge-based (KB) automatic planning approach to CyberKnife in the case of Stereotactic Body Radiation Therapy (SBRT) for prostate cancer.

METHODS

Seventy-two clinical plans of patients treated according to the RTOG0938 protocol (36.25 Gy/5fr) with CyberKnife were exported from the CyberKnife system to Eclipse to train a KB-model using the Rapid Plan tool. The KB approach provided dose-volume objectives for specific OARs only and not PTV. Bladder, rectum and femoral heads were considered in the model. The KB-model was successfully trained on 51 plans and then validated on 20 new patients. A KB-based template was tuned in the Precision system for both sequential optimization (SO) and VOLO optimization algorithms. Plans of the validation group were re-optimized (KB-TP) using both algorithms without any operator intervention and compared against the original plans (TP) in terms of OARs/PTV dose-volume parameters. Paired Wilcoxon signed-rank tests were performed to assess statistically significant differences (p < 0.05).

RESULTS

Regarding SO, automatic KB-TP plans were generally better than or equivalent to TP plans. PTVs V95% was slightly worse while OARs sparing for KB-TP was significantly improved. Regarding VOLO optimization, the PTVs coverage was significantly better for KB-TP while there was a limited worsening in the rectum. A significant improvement was observed in the bladder in the range of low-intermediate doses.

CONCLUSIONS

An extension of the KB optimization approach to the CyberKnife system has been successfully developed and validated in the case of SBRT prostate cancer.

Preoperative robotic radiosurgery for early breast cancer: Results of the phase II ROCK trial (NCT03520894)

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Preoperative partial breast irradiation treats well-defined target.

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Stereotactic body radiation therapy have been routinely implemented in clinical practice.

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No acute toxicity greater than grade 2 was recorded.

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A single 21 Gy dose preoperative robotic radiosurgery represents a feasible technique.

Background and purpose

Preoperative partial breast irradiation (PBI) has got the advantage of treating a well-defined target. We report the results of the phase II ROCK trial (NCT03520894), enrolling early breast cancer (BC) patients treated with preoperative robotic radiosurgery (prRS), in terms of acute and early late toxicity, disease control, and cosmesis.

Material and methods

The study recruited between 2018 and 2021 at our Radiation Oncology Unit. Eligible patients were 50 + years old BC, hormonal receptors positive/human epidermal growth factor receptor 2 negative (HR+/HER2-), sized up to 25 mm. The study aimed to prospectively assess the toxicity and feasibility of a robotic single 21 Gy-fraction prRS in preoperative setting.

Results

A total of 70 patients were recruited and 22 patients were successfully treated with pRS. Overall, three G1 adverse events (13.6 %) were recorded within 7 days from prRS. Three events (13.6 %) were recorded between 7 and 30 days, one G2 breast oedema and two G1 breast pain. No acute toxicity greater than G2 was recorded. Five patients experienced early late G1 toxicity. One patient reported G2 breast induration. No early late toxicity greater than G2 was observed. At a median follow up of 18 months (range 6–29.8), cosmetic results were scored excellent/good and fair in 14 and 5 patients, respectively, while 3 patients experienced a poor cosmetic outcome.

Conclusions

ROCK trial showed that a single 21 Gy dose prRS represents a feasible technique for selected patients affected by early BC, showing an acceptable preliminary toxicity profile.

Implementing and evaluating a high-resolution diode array for patient-specific quality assurance of robotic brain stereotactic radiosurgery/radiotherapy

The purpose of the study was to introduce and evaluate a high-resolution diode array for patient-specific quality assurance (PSQA) of CyberKnife brain stereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT). Thirty-three intracranial plans were retrospectively delivered on the SRS MapCHECK using fixed cone, Iris, and multileaf collimator (MLC). The plans were selected to cover a range of sites from large tumor bed, single/multiple small brain metastases (METs) to trigeminal neuralgia. Fiducial tracking using the four fiducials embedded around the detector plane was used as image guidance. Results were analyzed before and after registration based on absolute dose gamma criterion of 1 mm distance-to-agreement and 0.5%-3% dose-difference. Overall, the gamma passing rates (1 mm and 3% criterion) before registration for all the patients were above 90% for all three treatment modalities (96.8 ± 3.5%, the lowest passing rate of 90.4%), and were improved after registration (99.3 ± 1.5%). When tighter criteria (1 mm and 2%) were applied, the gamma passing rates after registration for all the cases dropped to 97.3 ± 3.2%. For trigeminal neuralgia cases, we applied 1 mm and 0.5% criterion and the passing rates dropped from 100 ± 0.0% to 98.5 ± 2.0%. The mean delivery time was 33.4 ± 11.7 min, 24.0 ± 4.9 min, and 17.1 ± 2.6 min for the fixed cone, Iris, and MLC, respectively. With superior gamma passing rates and reasonable quality assurance (QA) time, we believe the SRS MapCHECK could be a good option for routine PSQA for CyberKnife SRS/SRT.

TBS-BAO: fully automated beam angle optimization for IMRT guided by a total-beam-space reference plan

Properly selected beam angles contribute to the quality of radiotherapy treatment plans. However, the beam angle optimization (BAO) problem is difficult to solve to optimality due to its non-convex discrete nature with many local minima. In this study, we propose TBS-BAO, a novel approach for solving the BAO problem, and test it for non-coplanar robotic CyberKnife radiotherapy for prostate cancer. First, an ideal Pareto-optimal reference dose distribution is automatically generated usinga priorimulti-criterial fluence map optimization (FMO) to generate a plan that includes all candidate beams (total-beam-space, TBS). Then, this ideal dose distribution is reproduced as closely as possible in a subsequent segmentation/beam angle optimization step (SEG/BAO), while limiting the number of allowed beams to a user-selectable preset value. SEG/BAO aims at a close reproduction of the ideal dose distribution. For each of 33 prostate SBRT patients, 18 treatment plans with different pre-set numbers of allowed beams were automatically generated with the proposed TBS-BAO. For each patient, the TBS-BAO plans were then compared to a plan that was automatically generated with an alternative BAO method (Erasmus-iCycle) and to a high-quality manually generated plan. TBS-BAO was able to automatically generate plans with clinically feasible numbers of beams (∼25), with a quality highly similar to corresponding 91-beam ideal reference plans. Compared to the alternative Erasmus-iCycle BAO approach, similar plan quality was obtained for 25-beam segmented plans, while computation times were reduced from 10.7 hours to 4.8/1.5 hours, depending on the applied pencil-beam resolution in TBS-BAO. 25-beam TBS-BAO plans had similar quality as manually generated plans with on average 48 beams, while delivery times reduced from 22.3 to 18.4/18.1 min. TBS reference plans could effectively steer the discrete non-convex BAO.

Comparison of Daily Online Plan Adaptation Strategies for a Cohort of Pancreatic Cancer Patients Treated with SBRT

PURPOSE

To study the trade-offs of three online strategies to adapt treatment plans of patients with locally advanced pancreatic carcinoma (LAPC) treated using the CyberKnife with tumor tracking.

METHODS AND MATERIALS

A total of 35 planning computed tomography scans and 98 daily in-room computed tomography scans were collected from 35 patients with LAPC. Planned dose distributions, optimized with VOLO, were evaluated on manually contoured daily anatomies to collect daily doses. Three strategies were tested to adapt treatment plans: (1) unrestricted full replanning using a patient-specific plan template, (2) time-restricted replanning on organs at risk (OARs) within 3 cm from the planning target volume (PTV) structure, and (3) dose realignment optimization to stay within OAR constraints. Dose distributions resulting from each plan adaptation strategy were dosimetrically compared by means of gross tumor volume (GTV), PTV coverage, and OAR tolerances.

RESULTS

Planned doses did not result in dose-constraint violations for 28 of 98 daily anatomies. None of the suggested plan adaptation strategies improved planned doses significantly for this subset. For 70 of the 98 reported violations, the median (interquartile range) PTV coverage of the planned dose was 84% (76% to 86%). After plan adaptation, unrestricted replanning achieved clinically acceptable plans in 93% of these fractions, time-restricted replanning in 90%, and dose realignment in 74%, at median computational times of 8.5, 3, and 0.5 minutes. Over all 98 fractions, PTV coverage was reduced: -1% (-3% to 1%), -2% (-5% to 0%), and -2% (-8% to 0%) after each strategy, respectively. In 3 of 70 fractions, none of the suggested strategies achieved clinically acceptable OAR dose volumes.

CONCLUSIONS

Unrestricted replanning was the most time-consuming method but reached the highest number of successfully adapted plans. Time-restricted replanning and dose realignment resulted in a high number of plans within dose constraints. Depending on the resources available, an adaptive strategy can be selected for each patient to address the specific anatomic challenges on the treatment day. The increase in the complexity of the strategy corresponds with an increasing number of successfully adapted plans.

Fully automated treatment planning for MLC-based robotic radiotherapy

PURPOSE

To propose and validate a fully automated multicriterial treatment planning solution for a CyberKnife® equipped with an InCise^TM 2 multileaf collimator.

METHODS

The AUTO BAO plans are generated using fully automated prioritized multicriterial optimization (AUTO MCO) of pencil-beam fluence maps with integrated noncoplanar beam angle optimization (BAO), followed by MLC segment generation. Both the AUTO MCO and segmentation algorithms have been developed in-house. AUTO MCO generates for each patient a single, high-quality Pareto-optimal IMRT plan. The segmentation algorithm then accurately mimics the AUTO MCO 3D dose distribution, while considering all candidate beams simultaneously, rather than replicating the fluence maps. Pencil-beams, segment dose depositions, and final dose calculations are performed with a stand-alone version of the clinical dose calculation engine. For validation, AUTO BAO plans were generated for 33 prostate SBRT patients and compared to reference plans (REF) that were manually generated with the commercial treatment planning system (TPS), in absence of time pressure. REF plans were also compared to AUTO RB plans, for which fluence map optimization was performed for the beam angle configuration used in the REF plan, and the segmentation could use all these beams or only a subset, depending on the dosimetry.

RESULTS

AUTO BAO plans were clinically acceptable and dosimetrically similar to REF plans, but had on average reduced numbers of beams ((beams in AUTO BAO)/(beams in REF) (relative improvement): 24.7/48.3 (-49%)), segments (59.5/98.9 (-40%)), and delivery times (17.1/22.3 min. (-23%)). Dosimetry of AUTO RB and REF were also similar, but AUTO RB used on average fewer beams (38.0/48.3 (-21%)) and had on average shorter delivery times (18.6/22.3 min. (-17%)). Delivered Monitor Units (MU) were similar for all three planning approaches.

CONCLUSIONS

A new, vendor-independent optimization workflow for fully automated generation of deliverable high-quality CyberKnife® plans was proposed, including BAO. Compared to manual planning with the commercial TPS, fraction delivery times were reduced by 5.3 min. (-23%) due to large reductions in beam and segment numbers.

Largely reduced OAR doses, and planning and delivery times for challenging robotic SBRT cases, obtained with a novel optimizer

Recently, VOLO™ was introduced as a new optimizer for CyberKnife® planning. In this study, we investigated possibilities to improve treatment plans for MLC-based prostate SBRT with enhanced peripheral zone dose while sparing the urethra, and central lung tumors, compared to existing Sequential Optimization (SO). The primary focus was on reducing OAR doses. For 25 prostate and 25 lung patients treated with SO plans, replanning with VOLO™ was performed with the same planning constraints. For equal PTV coverage, almost all OAR plan parameters were improved with VOLO™. For prostate patients, mean rectum and bladder doses were reduced by 34.2% (P < 0.001) and 23.5% (P < 0.001), with reductions in D_0.03cc of 3.9%, 11.0% and 3.1% for rectum, mucosa and bladder (all P ≤ 0.01). Urethra D_5% and D_10% were 3.8% and 3.0% lower (P ≤ 0.002). For lung patients, esophagus, main bronchus, trachea, and spinal cord D_0.03cc was reduced by 18.9%, 11.1%, 16.1%, and 13.2%, respectively (all P ≤ 0.01). Apart from the dosimetric advantages of VOLO™ planning, average reductions in MU, numbers of beams and nodes for prostate/lung were 48.7/32.8%, 26.5/7.9% and 13.4/7.9%, respectively (P ≤ 0.003). VOLO™ also resulted in reduced delivery times with mean/max reductions of: 27/43% (prostate) and 15/41% (lung), P  < 0.001. Planning times reduced from 6 h to 1.1 h and from 3 h to 1.7 h for prostate and lung, respectively. The new VOLO™ planning was highly superior to SO planning in terms of dosimetric plan quality, and planning and delivery times.

Robotic MLC-based plans: A study of plan complexity

PURPOSE

The utility of complexity metrics has been assessed for IMRT and VMAT treatment plans, but this analysis has never been performed for CyberKnife (CK) plans. The purpose of this study is to perform a complexity analysis of CK MLC plans, adapting and computing complexity indices previously defined for IMRT plans. Metrics were used to compare the complexity of plans created by two optimization systems and to study correlations between plan complexity and patient-specific quality assurance (PSQA) results. Relationships between pairs of metrics were also analyzed to get insight into possible interdependencies.

METHODS

Two independent in-house software platforms were developed to compute six complexity metrics: modulation complexity score (MCS), edge metric (EM), plan irregularity (PI), plan modulation (PM), leaf gap (LG), and small aperture score (SAS10). MCS and PM definitions were adapted to account for CK plans characteristics. The computed metrics were used to compare the existing optimization algorithms (sequential and VOLO) in terms of plan complexity over 24 selected cases. Metrics were then computed over a large number (103) of VOLO SBRT clinical plans from different treatment sites, mainly liver, prostate, pancreas, and spine. Pearson's r was used to study relationships between each pair of metrics. Correlation between complexity indices and PSQA results expressed as gamma index passing rates (GPR) at (3%, 1 mm) and (2%, 1 mm) was finally analyzed. Correlation was regarded as weak for absolute Pearson's r values in the range 0.2-0.39, moderate 0.4-0.59, strong 0.6-0.79, and very strong 0.8-1.

RESULTS

When compared to VOLO, sequential plans exhibited a higher complexity degree, showing lower MCS and LG values and higher EM, PM and PI values. Differences were significant for 5/6 metrics (Wilcoxon P < 0.05). The analysis of VOLO clinical plans highlighted different degrees of complexity among plans from different treatment sites, increasing from liver to prostate, pancreas, and finally, spine. Analysis of dependencies between pairs of metrics showed a very strong significant negative correlation (P < 0.01), respectively, between MCS and PM (r = -0.97), and EM and LG (-0.82). Most of the remaining pairs showed moderate to strong correlations with the exception of PI, which showed weaker correlations with the other metrics. A moderate significant correlation was observed with GPR values both at (3%, 1 mm) and (2%, 1 mm) for all metrics except PI, which showed no correlation.

CONCLUSIONS

Modulation complexity metrics were computed for CK MLC-based plans for the first time and some metrics' definitions were adapted to CK plans peculiarities. The computed metrics proved a useful tool for comparing optimization algorithms and for characterizing CK clinical plans. Strong and very strong correlations were found between some pairs of metrics. Some significant correlations were found with PSQA GPR, indicating that some indices are promising for rationalizing and reducing PSQA workload. Our results set the basis for evaluating new optimization algorithms and TPS versions in the future, as well as for comparing the complexity of CK MLC-based plans in multicenter and multiplatform comparisons.