Automatic treatment planning improves the clinical quality of head and neck cancer treatment plans

Hansen, Christian Rønn; Bertelsen, Anders; Hazell, Irene; Zukauskaite, Ruta; Gyldenkerne, Niels; Johansen, Jørgen; Eriksen, Jesper Grau; Brink, Carsten

doi:10.1016/j.ctro.2016.08.001

Cited by 90 publications

(131 citation statements)

References 18 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%

“…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: 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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“…For treatment planning, Pinnacle3 Auto‐Planning (Philips Radiation Oncology Systems, Fitchburg, WI, USA) is an example of reducing the amount of user interaction required to achieve optimal intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans while RapidPlan™ (Varian Medical Systems, Palo Alto, USA) builds the knowledge of previously planned patients to achieve the same aim . With automated planning including knowledge‐based planning systems (KBPS), the time to create a treatment plan can be reduced in some cases by more than an hour while reducing variability in plan quality and producing comparable or better plans compared to manual planning . Many treatment planning systems supply tools for templating and/or scripting processes to enable further automation of the many steps required to design and check a treatment plan.…”

mentioning

confidence: 99%

Automation in radiation oncology – cautionary considerations in the push for planning efficiency

et al. 2018

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A knowledge‐based approach to automated planning for hepatocellular carcinoma

Zhang

Xiao

et al. 2017

J Applied Clin Med Phys

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PurposeTo build a knowledge‐based model of liver cancer for Auto‐Planning, a function in Pinnacle, which is used as an automated inverse intensity modulated radiation therapy (IMRT) planning system.Methods and MaterialsFifty Tomotherapy patients were enrolled to extract the dose–volume histograms (DVHs) information and construct the protocol for Auto‐Planning model. Twenty more patients were chosen additionally to test the model. Manual planning and automatic planning were performed blindly for all twenty test patients with the same machine and treatment planning system. The dose distributions of target and organs at risks (OARs), along with the working time for planning, were evaluated.ResultsStatistically significant results showed that automated plans performed better in target conformity index (CI) while mean target dose was 0.5 Gy higher than manual plans. The differences between target homogeneity indexes (HI) of the two methods were not statistically significant. Additionally, the doses of normal liver, left kidney, and small bowel were significantly reduced with automated plan. Particularly, mean dose and V15 of normal liver were 1.4 Gy and 40.5 cc lower with automated plans respectively. Mean doses of left kidney and small bowel were reduced with automated plans by 1.2 Gy and 2.1 Gy respectively. In contrast, working time was also significantly reduced with automated planning.ConclusionsAuto‐Planning shows availability and effectiveness in our knowledge‐based model for liver cancer.

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Automatic treatment planning improves the clinical quality of head and neck cancer treatment plans

Abstract: HighlightsAutoplan can produce clinically better VMAT radiotherapy plans for H&N cancer.Autoplan plans have similar target coverage with significant sparing of OAR.With a template the TPS can automatically create better plans than manually created plans.

Cited by 90 publications

References 18 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

Automation in radiation oncology – cautionary considerations in the push for planning efficiency

A knowledge‐based approach to automated planning for hepatocellular carcinoma

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