Plan quality in radiotherapy treatment planning – Review of the factors and challenges

Hansen, Christian Rønn; Hussein, Mohammad; Bernchou, U.; Zukauskaite, Ruta; Thwaites, David

doi:10.1111/1754-9485.13374

“…The hybrid planning performed significantly better than manual planning in OAR sparing (Additional file 1: Table S1), except for left femur head D 25 , which showed no significant difference. This result is similar to the conclusion proposed by Hansen et al [22], who concluded that, on average, automated planning reduces the OAR dose compared to manual planning.…”

Section: Discussionsupporting

confidence: 91%

Evaluation of a hybrid automatic planning solution for rectal cancer

Peng

¹

,

Yu

²

,

Xia

³

et al. 2022

Radiat Oncol

2

0

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Background Script-based planning and knowledge-based planning are two kinds of automatic planning solutions. Hybrid automatic planning may integrate the advantages of both solutions and provide a more robust automatic planning solution in the clinic. In this study, we evaluated and compared a commercially available hybrid planning solution with manual planning and script-based planning. Methods In total, 51 rectal cancer patients in our institution were enrolled in this study. Each patient generated 7 plans: one clinically accepted manual plan ($${plan}_{manual}$$ plan manual ), three script-based plans and three hybrid plans generated with the volumetric-modulated arc therapy technique and 3 different clinical goal settings: easy, moderate and hard ($${plan}_{hybrid}^{easy}$$ plan hybrid easy , $${plan}_{hybrid}^{moderate}$$ plan hybrid moderate , $${plan}_{hybrid}^{hard}$$ plan hybrid hard , $${plan}_{script}^{easy}$$ plan script easy , $${plan}_{script}^{moderate}$$ plan script moderate and $${plan}_{script}^{hard}$$ plan script hard ). Planning goals included planning target volume (PTV) Dmax, bladder Dmean and femur head Dmean. The PTV prescription was the same (50.00 Gy) for the 3 goal settings. The hard setting required a lower PTV Dmax and stricter organ at risk (OAR) dose, while the easy setting was the opposite. Plans were compared using dose metrics and plan quality metric (PQM) scores, including bladder D15 and D50, left and right femur head D25 and D40, PTV D2, D98, CI (conformity index) and HI (homogeneity index). Results Compared to manual planning, hybrid planning with all settings significantly reduced the OAR dose (p < 0.05, paired t-test or Wilcoxon signed rank test) for all dose-volume indices, except D25 of the left femur head. For script-based planning, $${plan}_{script}^{easy}$$ plan script easy significantly increased the OAR dose for the femur head and D2 and the PTV homogeneity index (p < 0.05, paired t-test or Wilcoxon signed rank test). Meanwhile, the maximum dose of the PTV was largely increased with hard script-based planning (D2 = 56.06 ± 7.57 Gy). For all three settings, the comparison of PQM between hybrid planning and script-based planning showed significant differences, except for D25 of the left femur head and PTV D2. The total PQM showed that hybrid planning could provide a better and more robust plan quality than script-based planning. Conclusions The hybrid planning solution was manual-planning comparable for rectal cancer. Hybrid planning can provide a better and more robust plan quality than script-based planning.

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“…It is also important to note that the quality of treatment delivery is intrinsically linked to other upstream activities such as treatment planning and simulation which are covered in a separate article in the present special issue of JMIRO 29 …”

Section: Treatment Delivery: Technology and Techniquesmentioning

confidence: 99%

“…It is also important to note that the quality of treatment delivery is intrinsically linked to other upstream activities such as treatment planning and simulation which are covered in a separate article in the present special issue of JMIRO. 29 A system to ensure fitness of purpose for radiotherapy delivery equipment Quality considerations for equipment used for patient treatment can be associated with a few distinct activities…”

Section: Risk Managementmentioning

confidence: 99%

Quality management in radiotherapy treatment delivery

Kron

¹

,

Fox

²

,

Ebert

³

et al. 2022

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Radiation Oncology continues to rely on accurate delivery of radiation, in particular where patients can benefit from more modulated and hypofractioned treatments that can deliver higher dose to the target while optimising dose to normal structures. These deliveries are more complex, and the treatment units are more computerised, leading to a re-evaluation of quality assurance (QA) to test a larger range of options with more stringent criteria without becoming too time and resource consuming. This review explores how modern approaches of risk management and automation can be used to develop and maintain an effective and efficient QA programme. It considers various tools to control and guide radiation delivery including image guidance and motion management. Links with typical maintenance and repair activities are discussed, as well as patient-specific quality control activities. It is demonstrated that a quality management programme applied to treatment delivery can have an impact on individual patients but also on the quality of treatment techniques and future planning. Developing and customising a QA programme for treatment delivery is an important part of radiotherapy. Using modern multidisciplinary approaches can make this also a useful tool for department management.

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“…Once a treatment plan is created, the next important step in the radiotherapy workflow is to evaluate the plan quality to determine if it is clinically acceptable and safe [3,4]. The quality of a plan is evaluated using several qualitative and quantitative metrics [2,3].…”

Section: Introductionmentioning

confidence: 99%

Phase I quality control framework for monitoring organ-at-risk dose

Sivabhaskar,

Buatti,

Yeh

et al. 2024

Biomed. Phys. Eng. Express

0

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Objective: The aim of this work was to develop a Phase I control chart framework for the recently proposed multivariate risk-adjusted Hotelling’s T^2 chart. Although this control chart alone can identify most patients receiving extreme organ-at-risk (OAR) dose, it is restricted by underlying distributional assumptions, making it sensitive to extreme observations in the sample, as is typically found in radiotherapy plan quality data such as dose-volume histogram (DVH) points. This can lead to slightly poor-quality plans that should have been identified as out-of-control (OC) to be signaled in-control (IC). Approach: We develop a robust iterative control chart framework to identify all OC patients with abnormally high OAR dose and improve them via re-optimization to achieve an IC sample prior to establishing the Phase I control chart, which can be used to monitor future treatment plans. Main Results: Eighty head-and-neck patients were used in this study. After the first iteration, P14, P67, and P68 were detected as OC for high brainstem dose, warranting re-optimization aimed to reduce brainstem dose without worsening other planning criteria. The DVH and control chart were updated after re-optimization. On the second iteration, P14, P67, and P68 were IC, but P40 was identified as OC. After re-optimizing P40’s plan and updating the DVH and control chart, P40 was IC, but P14* (P14’s re-optimized plan) and P62 were flagged as OC. P14* could not be re-optimized without worsening target coverage, so only P62 was re-optimized. Ultimately, a fully IC sample was achieved. Multiple iterations were needed to identify and improve all OC patients, and to establish a more robust control limit to monitor future treatment plans.Significance: The iterative procedure resulted in a fully IC sample of patients. With this sample, a more robust Phase I control chart that can monitor OAR doses of new plans was established.

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Plan quality in radiotherapy treatment planning – Review of the factors and challenges

Cited by 16 publications

References 114 publications

Evaluation of a hybrid automatic planning solution for rectal cancer

Evaluation of a hybrid automatic planning solution for rectal cancer

Quality management in radiotherapy treatment delivery

Phase I quality control framework for monitoring organ-at-risk dose

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