EP-1922: Standardisation of VMAT frameless SRS/SRT planning using ensemble mapped knowledge based planning

Sarkar, Biplab; Ganesh, T; Manikandan, A.; Munshi, Anusheel; Mohanti, B.K.

doi:10.1016/s0167-8140(18)32231-x

Cited by 2 publications

(4 citation statements)

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“…Our technique is free from any complex mathematics or computer programming; hence can be implemented easily. 48 Our study is the second of its kind for a statistical Monte Carlo calculation engine, with earlier one found for prostate VMAT KBP. 22 The advantage of our technique is that it reduces the total planning time by mostly eliminating the iterative processes of finding most suitable optimization parameters, arc angles, and completes the stereotactic radiosurgery (SRS)/radiotherapy (SRS/SRT) plans in 1.5 runs.…”

Section: Discussionmentioning

confidence: 72%

“…These two are averting factors for KBP to be implemented in the routine clinical practice. Our technique is free from any complex mathematics or computer programming; hence can be implemented easily . Our study is the second of its kind for a statistical Monte Carlo calculation engine, with earlier one found for prostate VMAT KBP …”

Section: Discussionmentioning

confidence: 94%

“…used mutual information to identify the most anatomically similar library patient to new patients and used the treatment parameters from the matched library patient to develop new plan . This technique is somewhat similar to our methodology …”

Section: Discussionmentioning

confidence: 99%

“…22 This technique is somewhat similar to our methodology. 48,49 All the KBP techniques described so far by numerous research groups are complex in mathematics. For example, implementation of UCSD KBP algorithm [14][15][16][17] required proficiency in the use of ANN and MatLab programming, which may not be frequent among the clinical users.…”

Section: Discussionmentioning

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: 72%

Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%