Evaluation of a new commercial automated planning software for tangential breast intensity-modulated radiation therapy

Mizuno, Norifumi; Yamauchi, Ryouhei; Kawamori, Jiro; Itazawa, Tomoko; Shimbo, Munefumi; Nishimura, Keiichiro; Yamano, Takafumi; Hatanaka, Shin–ichi; Hariu, Masatsugu; Takahashi, Tetsuya

doi:10.1007/s12194-019-00515-9

Cited by 9 publications

(22 citation statements)

References 29 publications

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“…A timing study of four individual planners showed that on average, it took ~ 6 min to create an acceptable EZF plan, not including the time spent on setting up the fields and MLC blocks. This is comparable to what several others reported for other automated solutions, although included in their time estimate was automatic field setup as well 10,13 . Inability to automatically set the fields is the most significant shortcoming of EZF.…”

Section: Discussionsupporting

confidence: 87%

“…Each iteration proceeds in a trial‐and‐error fashion, with the planner editing the fluence, calculating 3D dose, and evaluating the dose until “optimal” dosimetry is achieved. There are several published studies on automated treatment planning algorithms being implemented for various anatomical sites, including breast 8–16 . Many institutions use in‐house developed software for plan automation, and while that is a feasible solution for those that already have it or have the resources to develop, maintain,and validate in‐house solutions, such an approach may not be accessible for many nonacademic clinics.…”

Section: Discussionmentioning

confidence: 99%

“…There are several published studies on automated treatment planning algorithms being implemented for various anatomical sites, including breast. [8][9][10][11][12][13][14][15][16] Many institutions use in-house developed software for plan automation, and while that is a feasible solution for those that already have it or have the resources to develop, maintain,and validate in-house solutions, such an approach may not be accessible for many nonacademic clinics. Commercially available software such as EZF, therefore can provide an ideal solution for those that have limited time and resources.…”

Section: Discussionmentioning

confidence: 99%

“…This is comparable to what several others reported for other automated solutions, although included in their time estimate was automatic field setup as well. 10,13 Inability to automatically set the fields is the most significant shortcoming of EZF. Since the most time-consuming step in manual breast treatment planning is fluence editing, this shortcoming does not significantly affect the workflow.…”

Section: Discussionmentioning

confidence: 99%

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Assessing the performance of an automated breast treatment planning software

Dragojević

Hoisak

Mansy

et al. 2021

J Applied Clin Med Phys

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Purpose To assess the dosimetric performance of an automated breast planning software. Methods We retrospectively reviewed 15 breast cancer patients treated with tangent fields according to the RTOG 1005 protocol and 30 patients treated off‐protocol. Planning with electronic compensators (eComps) via manual, iterative fluence editing was compared to an automated planning program called EZFluence (EZF) (Radformation, Inc.). We compared the minimum dose received by 95% of the volume (D95%), D90%, the volume receiving at least 105% of prescription (V105%), V95%, the conformity index of the V95% and PTV volumes (CI95%), and total monitor units (MUs). The PTV_Eval structure generated by EZF was compared to the RTOG 1005 breast PTV_Eval structure. Results The average D95% was significantly greater for the EZF plans, 95.0%, vs. the original plans 93.2% (P = 0.022). CI95% was less for the EZF plans, 1.18, than the original plans, 1.48 (P = 0.09). D90% was only slightly greater for EZF, averaging at 98.3% for EZF plans and 97.3% for the original plans (P = 0.0483). V105% (cc) was, on average, 27.8cc less in the EZF breast plans, which was significantly less than for those manually planned. The average number of MUs for the EZF plans, 453, was significantly less than original protocol plans, 500 (P = 8 × 10−6). The average difference between the protocol PTV volume and the EZF PTV volume was 196 cc, with all but two cases having a larger EZF PTV volume (P = 0.020). Conclusion EZF improved dose homogeneity, coverage, and MU efficiency vs. manually produced eComp plans. The EZF‐generated PTV eval is based on the volume encompassed by the tangents, and is not appropriate for dosimetric comparison to constraints for RTOG 1005 PTV eval. EZF produced dosimetrically similar or superior plans to manual, iteratively derived plans and may also offer time and efficiency benefits.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing the performance of an automated breast treatment planning software

Dragojević

Hoisak

Mansy

et al. 2021

J Applied Clin Med Phys

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“…Two general-purpose autoplanning approaches have been implemented in commercial TPSs and extensively tested, based on knowledge-based planning [14][15][16], and protocol-based automatic iterative optimization [17][18][19]. A dedicated application for breast autoplanning was also implemented in a commercial TPS [20,21]. Scripting in commercial TPS has also resulted in several clinical autoplanning applications [22,23].…”

mentioning

confidence: 99%

Pre-clinical validation of a novel system for fully-automated treatment planning

Bijman¹,

Sharfo²,

Rossi³

et al. 2021

Radiotherapy and Oncology

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Introduction: Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to 'manual' trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs). We performed a pre-clinical validation of a new system ('NovelATP') that is based on fully-automated multi-criterial optimization (MCO). The aim of NovelATP is to automatically generate for each patient a single high-quality, Pareto-optimal plan without manual Pareto navigation. Material and methods: Validation was performed by generating VMAT/IMRT plans for conventional treatment of prostate cancer (101 pts), prostate SBRT (20 pts), bilateral head-and-neck cancer (50 pts) and rectal cancer treated at an MR-Linac (23 pts). NovelATP autoplans were compared to plans that were generated with our in-house autoplanning system. In many previous validation studies, the latter system consistently showed enhanced plan quality when compared to manual planning. Results: Dosimetrical differences between NovelATP and benchmark plans were on average small and presumably not clinically relevant, pointing at high NovelATP dosimetric plan quality. MUs were 11-19% higher with NovelATP. NovelATP delivery times were up to 12% longer. Overall, there was a slight disadvantage for NovelATP regarding gamma analyses. Calculation times for NovelATP plans were between 29 and 151 min with no overall differences with the benchmark plans. Conclusion:The new autoplanning system was able to produce high-quality plans for four highly different planning protocols/treatment sites with a total of 194 patients investigated.

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

Zaratim,

dos Reis,

dos Santos

et al. 2024

J Applied Clin Med Phys

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PurposesThis 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 MethodsWe 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.ResultsOverall, 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.ConclusionsAlthough 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.

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Evaluation of a new commercial automated planning software for tangential breast intensity-modulated radiation therapy

Cited by 9 publications

References 29 publications

Assessing the performance of an automated breast treatment planning software

Assessing the performance of an automated breast treatment planning software

Pre-clinical validation of a novel system for fully-automated treatment planning

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

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