Improving Quality and Consistency in NRG Oncology Radiation Therapy Oncology Group 0631 for Spine Radiosurgery via Knowledge-Based Planning

Younge, K. C.; Marsh, Richard L.; Owen, Dawn; Geng, H.; Xiao, Ying; Spratt, Daniel E.; Foy, Joseph J.; Suresh, Krithika; Wu, Qiuwen; Yin, Fang; Ryu, Samuel; Matuszak, Martha M.

doi:10.1016/j.ijrobp.2017.12.276

Cited by 39 publications

(43 citation statements)

References 26 publications

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“…Most of the researchers and all commercial KBP algorithms use predictive dose volume technique . The issue with the predictive dose volume method is the bandwidth of the predicted DVH is too wide at the mid portion of the curve, sometimes as high as 20% error in the dose and/or volume.…”

Section: Discussionmentioning

confidence: 99%

“…All the KBP techniques described so far by numerous research groups are complex in mathematics. For example, implementation of UCSD KBP algorithm required proficiency in the use of ANN and MatLab programming, which may not be frequent among the clinical users.…”

Section: Discussionmentioning

confidence: 99%

“…Optimal treatment plans can be generated by grossly reducing any subjectivity introduced by the treatment planner. Recently, knowledge‐based planning (KBP) helped the treatment planner standardize the treatment plans for different sites like brain, esophagus, prostate, head and neck, spine SBRT, and pancreas …”

Section: Introductionmentioning

confidence: 99%

“…Knowledge‐based planning was developed at Duke University and Washington University and is presently commercially available with the Varian planning system, known as RapidPlan (Eclipse, Varian medical System, Polo Alto, CA) . Similar atlas‐based techniques are available from Elekta (Erasmus‐iCycle), and from Philips Pinnacle 3 planning system as ideal dose distribution estimation (PlanIQ) using template‐based optimization for Auto Planning (AP) …”

Section: Introductionmentioning

confidence: 99%

“…The predicted DVH technique is the one described by many authors and used in all commercially available planning systems. It uses database DVH averaging approach . The assumption is that any DVH can be represented as a combination of the average DVH over a population plus a sum of weighted principal components and a residual.…”

Section: Introductionmentioning

confidence: 99%

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Standardization of volumetric modulated arc therapy‐based frameless stereotactic technique using a multidimensional ensemble‐aided knowledge‐based planning

et al. 2019

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Purpose Aim of this article is to describe a new knowledge‐based planning (KBP) methodology using volumetric modulated arc therapy (VMAT) for stereotactic radiosurgery (SRS) and radiotherapy (SRT) assisted by an ensemble mapping technique for use in a Monte Carlo planning system. Methods Libraries of 121 stereotactic patients were assembled on the basis of eight different parameters (a) tumor laterality, (b) whether planning target volume (PTV) dose coverage challenged by the presence of the organ at risk (OAR), (c) prescription dose and number of fractions, (d) number of PTVs, (e) tumor volume, (f) shortest distance between OAR and PTV (edge to edge distance, or EED), (g) center to center distance between OARs and PTV (CCD), and (h) lateral dimension of external contour (brain). For new patients, the most appropriate library plan was selected on the basis of the above categorization. A KBP plan was created based on this selected library plan with all parameters unchanged keeping the isocenter at the center of PTV. Using the same beam configuration, another independent treatment plan (IP) was generated by an experienced dosimetrist for comparison. IP and KBP were compared for 76 new patients. Results Of 197 patients (121 library and 76 new), 103 (52.3%) were placed in the OAR‐challenged category and 94 were placed in the OAR unchallenged category. The ensemble mapping technique shows that, for an OAR‐challenged patient, picking up the library plan is appropriate. IP was marginally better than KBP in PTV coverage and dose conformity (PCI). Library plans, IP, and KBP offer a mean PCI of 0.77 ± 0.2, 0.79 ± 0.2, and 0.78 ± 0.4, mean PTV‐V99% of 97.3 ± 22.0%, 98.9 ± 14.1%, and 98.2 ± 13.2%, and mean MU of 2403.8 ± 2403.8, 2344.0 ± 2423.6, and 2473.6 ± 2296.8, respectively. Statistically significant differences were observed in the planning time between the IP and KBP plans for both OAR‐challenged (P < 0.001) and ‐unchallenged (P < 0.002) categories. Comparison of optimization and dose calculation time showed a much lower average planning time of 111.0 ± 84.1 min for KBP as against 248.2 ± 96.6 min for IP. Conclusion Validation results for KBP plans indicate the multidimensional ensemble mapping mechanism can accurately pick up the most appropriate library plan. KBP plans, although slightly inferior in their dosimetric quality, fulfill all the required clinical conditions and dose constraints. KBP plans save considerable planning time and are nearly independent of the skill and knowledge of the treatment planner. KBP works well with a Monte Carlo planning system like Monaco.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Standardization of volumetric modulated arc therapy‐based frameless stereotactic technique using a multidimensional ensemble‐aided knowledge‐based planning

et al. 2019

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An Automated knowledge‐based planning routine for stereotactic body radiotherapy of peripheral lung tumors via DCA‐based volumetric modulated arc therapy

Visak

McGarry

et al. 2020

J Applied Clin Med Phys

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PurposeTo develop a knowledge‐based planning (KBP) routine for stereotactic body radiotherapy (SBRT) of peripherally located early‐stage non‐small‐cell lung cancer (NSCLC) tumors via dynamic conformal arc (DCA)‐based volumetric modulated arc therapy (VMAT) using the commercially available RapidPlanTM software. This proposed technique potentially improves plan quality, reduces complexity, and minimizes interplay effect and small‐field dosimetry errors associated with treatment delivery.MethodsKBP model was developed and validated using 70 clinically treated high quality non‐coplanar VMAT lung SBRT plans for training and 20 independent plans for validation. All patients were treated with 54 Gy in three treatments. Additionally, a novel k‐DCA planning routine was deployed to create plans incorporating historical three‐dimensional‐conformal SBRT planning practices via DCA‐based approach prior to VMAT optimization in an automated planning engine. Conventional KBPs and k‐DCA plans were compared with clinically treated plans per RTOG‐0618 requirements for target conformity, tumor dose heterogeneity, intermediate dose fall‐off and organs‐at‐risk (OAR) sparing. Treatment planning time, treatment delivery efficiency, and accuracy were recorded.ResultsKBPs and k‐DCA plans were similar or better than clinical plans. Average planning target volume for validation was 22.4 ± 14.1 cc (7.1–62.3 cc). KBPs and k‐DCA plans provided similar conformity to clinical plans with average absolute differences of 0.01 and 0.01, respectively. Maximal doses to OAR were lowered in both KBPs and k‐DCA plans. KBPs increased monitor units (MU) on average 1316 (P < 0.001) while k‐DCA reduced total MU on average by 1114 (P < 0.001). This routine can create k‐DCA plan in less than 30 min. Independent Monte Carlo calculation demonstrated that k‐DCA plans showed better agreement with planned dose distribution.ConclusionA k‐DCA planning routine was developed in concurrence with a knowledge‐based approach for the treatment of peripherally located lung tumors. This method minimizes plan complexity associated with model‐based KBP techniques and improve plan quality and treatment planning efficiency.

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Development and clinical validation of a robust knowledge‐based planning model for stereotactic body radiotherapy treatment of centrally located lung tumors

Visak

McGarry

Randall

et al. 2020

J Applied Clin Med Phys

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PurposeTo develop a robust and adaptable knowledge‐based planning (KBP) model with commercially available RapidPlanTM for early stage, centrally located non‐small‐cell lung tumors (NSCLC) treated with stereotactic body radiotherapy (SBRT) and improve a patient's“simulation to treatment” time.MethodsThe KBP model was trained using 86 clinically treated high‐quality non‐coplanar volumetric modulated arc therapy (n‐VMAT) lung SBRT plans with delivered prescriptions of 50 or 55 Gy in 5 fractions. Another 20 independent clinical n‐VMAT plans were used for validation of the model. KBP and n‐VMAT plans were compared via Radiation Therapy Oncology Group (RTOG)–0813 protocol compliance criteria for conformity (CI), gradient index (GI), maximal dose 2 cm away from the target in any direction (D2cm), dose to organs‐at‐risk (OAR), treatment delivery efficiency, and accuracy. KBP plans were re‐optimized with larger calculation grid size (CGS) of 2.5 mm to assess feasibility of rapid adaptive re‐planning.ResultsKnowledge‐based plans were similar or better than n‐VMAT plans based on a range of target coverage and OAR metrics. Planning target volume (PTV) for validation cases was 30.5 ± 19.1 cc (range 7.0–71.7 cc). KBPs provided an average CI of 1.04 ± 0.04 (0.97–1.11) vs. n‐VMAT plan'saverage CI of 1.01 ± 0.04 (0.97–1.17) (P < 0.05) with slightly improved GI with KBPs (P < 0.05). D2cm was similar between the KBPs and n‐VMAT plans. KBPs provided lower lung V10Gy (P = 0.003), V20Gy (P = 0.007), and mean lung dose (P < 0.001). KBPs had overall better sparing of OAR at the minimal increased of average total monitor units and beam‐on time by 460 (P < 0.05) and 19.2 s, respectively. Quality assurance phantom measurement showed similar treatment delivery accuracy. Utilizing a CGS of 2.5 mm in the final optimization improved planning time (mean, 5 min) with minimal or no cost to the plan quality.ConclusionThe RTOG‐compliant adaptable RapidPlan model for early stage SBRT treatment of centrally located lung tumors was developed. All plans met RTOG dosimetric requirements in less than 30 min of planning time, potentially offering shorter “simulation to treatment” times. OAR sparing via KBPs may permit tumorcidal dose escalation with minimal penalties. Same day adaptive re‐planning is plausible with a 2.5‐mm CGS optimizer setting.

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Improving Quality and Consistency in NRG Oncology Radiation Therapy Oncology Group 0631 for Spine Radiosurgery via Knowledge-Based Planning

Abstract: Incorporation of KBP models into the clinical trial setting may have a profound impact on the quality of trial results, owing to the increase in consistency and standardization of planning, especially for treatment sites or techniques that are nonstandard.

Cited by 39 publications

References 26 publications

Standardization of volumetric modulated arc therapy‐based frameless stereotactic technique using a multidimensional ensemble‐aided knowledge‐based planning

Standardization of volumetric modulated arc therapy‐based frameless stereotactic technique using a multidimensional ensemble‐aided knowledge‐based planning

An Automated knowledge‐based planning routine for stereotactic body radiotherapy of peripheral lung tumors via DCA‐based volumetric modulated arc therapy

Development and clinical validation of a robust knowledge‐based planning model for stereotactic body radiotherapy treatment of centrally located lung tumors

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