Pareto Fronts in Clinical Practice for Pinnacle

Janssen, Tomas; Kesteren, Z. van; Franssen, Gijs; Damen, E.; Vliet, Corine van

doi:10.1016/j.ijrobp.2012.05.045

Cited by 19 publications

(12 citation statements)

References 17 publications

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“…To definitively verify this claim, one needs to formally demonstrate that the resulting plans are Pareto‐optimal (i.e., no objective can be improved upon without simultaneously sacrificing at least one other) (27) . This task is formidable (28) even with the proposed reduction in the number of evaluated plans, 29 , 30 and typically five or fewer dose objectives were considered in the cited references. Therefore Pareto analysis, particularly exhaustive in terms of the structures, was beyond the scope of the current practical study.…”

Section: Discussionmentioning

confidence: 99%

Initial evaluation of automated treatment planning software

Gintz

Latifi

Caudell

et al. 2016

J Applied Clin Med Phys

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Even with advanced inverse‐planning techniques, radiation treatment plan optimization remains a very time‐consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to progressively guide the traditional optimization process with automatically created regions of interest and associated dose‐volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post‐treatment autoplanning (AP) were compared to the original human‐driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed‐rank test p=0.027). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands (p<0.001) and the inferior pharyngeal constrictor (p=0.016), as well as for the maximum doses to the spinal cord (p=0.018) and brainstem (p=0.040). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing.PACS number(s): 87.55.D

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Section: Discussionmentioning

confidence: 99%

Initial evaluation of automated treatment planning software

Gintz

Latifi

Caudell

et al. 2016

J Applied Clin Med Phys

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“…Comparing PFs for the evaluation of different planning techniques, such as OF gEUD -and OF NTCP -based optimisations, is superior to the comparison of two single plans. In this study, plans were automatically generated using the method described by Janssen et al [27].…”

Section: Treatment Planningmentioning

confidence: 99%

“…For the first plan the planning parameters (gEUD dose thresholds and corresponding objective weights k) were set manually, as described above. For each subsequent plan the objective parameters were varied according to adapted Gaussian distributions [27]. Moreover, the gEUD parameter a remained fixed (a = 1) during the optimisation process.…”

Section: Treatment Planningmentioning

confidence: 99%

Direct use of multivariable normal tissue complication probability models in treatment plan optimisation for individualised head and neck cancer radiotherapy produces clinically acceptable treatment plans

Kierkels¹,

Korevaar²,

Steenbakkers³

et al. 2014

Radiotherapy and Oncology

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“…Pareto front evaluation studies can be performed for multiple evaluation criteria, i.e. in n-dimensions (nD) [3][4][5], but are mostly used for treatment technique comparison in two dimensions (2D), exploring the trade-off between two important evaluation parameters (e.g. target coverage vs. mean dose to an organ at risk (OAR)) [6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A clinical distance measure for evaluating treatment plan quality difference with Pareto fronts in radiotherapy

Petersson

Kyroudi

Bourhis

et al. 2017

Physics and Imaging in Radiation Oncology

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A B S T R A C TWe present a clinical distance measure for Pareto front evaluation studies in radiotherapy, which we show strongly correlates (r = 0.74 and 0.90) with clinical plan quality evaluation. For five prostate cases, sub-optimal treatment plans located at a clinical distance value of > 0.32 (0.28-0.35) from fronts of Pareto optimal plans, were assessed to be of lower plan quality by our (12) observers (p < .05). In conclusion, the clinical distance measure can be used to determine if the difference between a front and a given plan (or between different fronts) corresponds to a clinically significant plan quality difference.

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Pareto Fronts in Clinical Practice for Pinnacle

Cited by 19 publications

References 17 publications

Initial evaluation of automated treatment planning software

Initial evaluation of automated treatment planning software

Direct use of multivariable normal tissue complication probability models in treatment plan optimisation for individualised head and neck cancer radiotherapy produces clinically acceptable treatment plans

A clinical distance measure for evaluating treatment plan quality difference with Pareto fronts in radiotherapy

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