Limiting treatment plan complexity by applying a novel commercial tool

Scaggion, A.; Fusella, M.; Agnello, G.; Bettinelli, Andrea; Pivato, N.; Roggio, A.; Rossato, M.A.; Sepulcri, Matteo; Paiusco, M.

doi:10.1002/acm2.12908

Cited by 27 publications

(18 citation statements)

References 31 publications

(43 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Some TPSs incorporate methods to restrict complexity during optimization, e.g. the aperture shape controller (ASC) tool in the Eclipse TPS [94] and the modulation factor (MF) in the TomoTherapy Hi-Art treatment system [95][96][97], but most TPSs still do not directly incorporate advanced complexity metrics [77]. Thus, unnecessary plan complexity is sometimes a consequence of inverse planning and better tools are needed to handle plan complexity [98].…”

Section: Plan Complexitymentioning

confidence: 99%

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans

Hernández

Hansen

Widesott³

et al. 2020

Radiotherapy and Oncology

Self Cite

132

114

View full text Add to dashboard Cite

Plan evaluation is a key step in the radiotherapy treatment workflow. Central to this step is the assessment of treatment plan quality. Hence, it is important to agree on what we mean by plan quality and to be fully aware of which parameters it depends on. We understand plan quality in radiotherapy as the clinical suitability of the delivered dose distribution that can be realistically expected from a treatment plan. Plan quality is commonly assessed by evaluating the dose distribution calculated by the treatment planning system (TPS). Evaluating the 3D dose distribution is not easy, however; it is hard to fully evaluate its spatial characteristics and we still lack the knowledge for personalising the prediction of the clinical outcome based on individual patient characteristics. This advocates for standardisation and systematic collection of clinical data and outcomes after radiotherapy. Additionally, the calculated dose distribution is not exactly the dose delivered to the patient due to uncertainties in the dose calculation and the treatment delivery, including variations in the patient set-up and anatomy. Consequently, plan quality also depends on the robustness and complexity of the treatment plan. We believe that future work and consensus on the best metrics for quality indices are required. Better tools are needed in TPSs for the evaluation of dose distributions, for the robust evaluation and optimisation of treatment plans, and for controlling and reporting plan complexity. Implementation of such tools and a better understanding of these concepts will facilitate the handling of these characteristics in clinical practice and be helpful to increase the overall quality of treatment plans in radiotherapy.

show abstract

Section: Plan Complexitymentioning

confidence: 99%

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans

Hernández

Hansen

Widesott³

et al. 2020

Radiotherapy and Oncology

Self Cite

132

114

View full text Add to dashboard Cite

show abstract

“…[ 14 42 ] On the other hand, the reduced MU ensures plan deliverability. [ 43 ] Thus, the increase of MU should be noted carefully when using KBP.…”

Section: Discussionmentioning

confidence: 99%

Dosimetric Evaluation of Simplified Knowledge-Based Plan with an Extensive Stepping Validation Approach in Volumetric-Modulated Arc Therapy-Stereotactic Body Radiotherapy for Lung Cancer

Wada

Monzen

Tamura

et al. 2021

Journal of Medical Physics

View full text Add to dashboard Cite

Purpose: We investigated the performance of the simplified knowledge-based plans (KBPs) in stereotactic body radiotherapy (SBRT) with volumetric-modulated arc therapy (VMAT) for lung cancer. Materials and Methods: For 50 cases who underwent SBRT, only three structures were registered into knowledge-based model: total lung, spinal cord, and planning target volume. We performed single auto-optimization on VMAT plans in two steps: 19 cases used for the model training (closed-loop validation) and 16 new cases outside of training set (open-loop validation) for TrueBeam (TB) and Halcyon (Hal) linacs. The dosimetric parameters were compared between clinical plans (CLPs) and KBPs: CLPclosed, KBPclosed-TB and KBPclosed-Hal in closed-loop validation, CLPopen, KBPopen-TB and KBPopen-Hal in open-loop validation. Results: All organs at risk were comparable between CLPs and KBPs except for contralateral lung: V5 of KBPs was approximately 3%–7% higher than that of CLPs. V20 of total lung for KBPs showed comparable to CLPs; CLPclosed vs. KBPclosed-TB and CLPclosed vs. KBPclosed-Hal: 4.36% ± 2.87% vs. 3.54% ± 1.95% and 4.36 ± 2.87% vs. 3.54% ± 1.94% (P = 0.54 and 0.54); CLPopen vs. KBPopen-TB and CLPopen vs. KBPopen-Hal: 4.18% ± 1.57% vs. 3.55% ± 1.27% and 4.18% ± 1.57% vs. 3.67% ± 1.26% (P = 0.19 and 0.27). CI95 of KBPs with both linacs was superior to that of the CLP in closed-loop validation: CLPclosed vs. KBPclosed-TB vs. KBPclosed-Hal: 1.32% ± 0.12% vs. 1.18% ± 0.09% vs. 1.17% ± 0.06% (P < 0.01); and open-loop validation: CLPopen vs. KBPopen-TB vs. KBPopen-Hal: 1.22% ± 0.09% vs. 1.14% ± 0.04% vs. 1.16% ± 0.05% (P ≤ 0.01). Conclusions: The simplified KBPs with limited number of structures and without planner intervention were clinically acceptable in the dosimetric parameters for lung VMAT-SBRT planning.

show abstract

“…Collimator angles were offset by 30° to reduce leakage dose in the same plane and were chosen to ensure that the MLCs can travel to the PTV locations. The new aperture shape controller (ACS) feature in the PO MLC algorithm was set to “very high” in order to reduce the total number of monitor units, reduce plan complexity, and improve plan quality as demonstrated by the previous researchers 16,17 . Briefly, m‐RESIST plans were created by fitting the MLCs to PTV1 and then calculating the dynamic conformal arc (DCA) dose for the respective plan.…”

Section: Methodsmentioning

confidence: 99%

“…Next, standard manual VMAT optimization began for PTV1 and GTV1 coverage. The jaw tracking option was employed to reduce leakage dose to normal lung as described above 16 . Once dose calculation was complete, the plan for PTV1 was used as a base‐dose plan before VMAT optimization in the plan for PTV2.…”

Section: Methodsmentioning

confidence: 99%

“…The new aperture shape controller (ACS) feature in the PO MLC algorithm was set to "very high" in order to reduce the total number of monitor units, reduce plan complexity, and improve plan quality as demonstrated by the previous researchers. 16,17 Briefly, m-RESIST plans were created by fitting the MLCs to PTV1 and then calculating the dynamic conformal arc (DCA) dose for the respective plan. Next, standard manual VMAT optimization began for PTV1 and GTV1 coverage.…”

Section: D | M-resist Vmat Plansmentioning

confidence: 99%

See 1 more Smart Citation

Automation and integration of a novel restricted single‐isocenter stereotactic body radiotherapy (a‐RESIST) method for synchronous two lung lesions

Critchfield

Visak

Bernard

et al. 2021

J Applied Clin Med Phys

View full text Add to dashboard Cite

Synchronous treatment of two lung lesions using a single-isocenter volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) plan can decrease treatment time and reduce the impact of intrafraction motion. However, alignment of both lesions on a single cone beam CT (CBCT) can prove difficult and may lead to setup errors and unacceptable target coverage loss. A Restricted Single-Isocenter Stereotactic Body Radiotherapy (RESIST) method was created to minimize setup uncertainties and provide treatment delivery flexibility. RESIST utilizes a single-isocenter placed at patient's midline and allows both lesions to be planned separately but treated in the same session. Herein is described a process of automation of this novel RESIST method. Automation of RESIST significantly reduced treatment planning time while maintaining the benefits of RESIST. To demonstrate feasibility, ten patients with two lung lesions previously treated with a singleisocenter clinical VMAT plan were replanned manually with RESIST (m-RESIST) and with automated RESIST (a-RESIST). a-RESIST method automatically sets isocenter, creates beam geometry, chooses appropriate dose calculation algorithms, and performs VMAT optimization using an in-house trained knowledge-based planning model for lung SBRT. Both m-RESIST and a-RESIST showed lower dose to normal tissues compared to manually planned clinical VMAT although a-RESIST provided slightly inferior, but still clinically acceptable, dose conformity and gradient indices.However, a-RESIST significantly reduced the treatment planning time to less than 20 min and provided a higher dose to the lung tumors. The a-RESIST method provides guidance for inexperienced planners by standardizing beam geometry and plan optimization using DVH estimates. It produces clinically acceptable two lesions VMAT lung SBRT plans efficiently. We have further validated a-RESIST on phantom measurement and independent pretreatment dose verification of another four selected 2-lesions lung SBRT patients and implemented clinically. Further development of a-RESIST for more than two lung lesions and refining this approach for extracranial oligometastastic abdominal/pelvic SBRT, including development of automated simulated collision detection algorithm, merits future investigation.

show abstract

Limiting treatment plan complexity by applying a novel commercial tool

Cited by 27 publications

References 31 publications

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans

Dosimetric Evaluation of Simplified Knowledge-Based Plan with an Extensive Stepping Validation Approach in Volumetric-Modulated Arc Therapy-Stereotactic Body Radiotherapy for Lung Cancer

Automation and integration of a novel restricted single‐isocenter stereotactic body radiotherapy (a‐RESIST) method for synchronous two lung lesions

Contact Info

Product

Resources

About