Improving workflow for adaptive proton therapy with predictive anatomical modelling: A proof of concept

Zhang, Ying; Alshaikhi, Jailan; Amos, Richard A.; Lowe, Matthew; Tan, Wenyong; Bär, Esther; Royle, G.

doi:10.1016/j.radonc.2022.05.036

Cited by 5 publications

(5 citation statements)

References 38 publications

(41 reference statements)

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“…While challenging, identifying the subset of patients that would benefit the most from OA would be clinically relevant, as this could allow for a more efficient allocation of resources. In that regard, methods based on anatomical modeling (Gurney-Champion et al 2018 , Zhang et al 2022 ), previously identified pre-treatment clinical factors (van Kranen et al 2013 ) or deep learning (Pakela et al 2021 ) should be investigated in the future.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

et al. 2023

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Objective: To evaluate the impact of setup uncertainty reduction (SUR) and adaptation to geometrical changes (AGC) on normal tissue complication probability (NTCP) when using online adaptive head and neck intensity modulated proton therapy (IMPT).Approach: A cohort of ten retrospective head and neck cancer patients with daily scatter corrected cone-beam CT (CBCT) was studied. For each patient, two IMPT treatment plans were created: one with a 3-mm setup uncertainty robustness setting and one with no explicit setup robustness. Both plans were recalculated on the daily CBCT considering three scenarios: the robust plan without adaptation, the non-robust plan without adaptation and the non-robust plan with daily online adaptation. Online-adaptation was simulated using an in-house developed workflow based on GPU-accelerated Monte Carlo dose calculation and partial spot-intensity re-optimization. Dose distributions associated with each scenario were accumulated on the planning CT, where NTCP models for six toxicities were applied. NTCP values from each scenario were intercompared to quantify the reduction in toxicity risk induced by SUR alone, AGC alone and SUR and AGC combined. Finally, a decision tree was implemented to assess the clinical significance of the toxicity reduction associated with each mechanism.Main results: For most patients, clinically meaningful NTCP reductions were only achieved when SUR and AGC were performed together. In these conditions, total reductions in NTCP of up to 30.48 pp were obtained, with noticeable NTCP reductions for aspiration, dysphagia and xerostomia (mean reductions of 8.25, 5.42 and 5.12 pp respectively). While SUR had a generally larger impact than AGC on NTCP reductions, SUR alone did not induce clinically meaningful toxicity reductions in any patient, compared to only one for AGC alone.Significance: Online adaptive head and neck proton therapy can only yield clinically significant reductions in the risk of long-term side effects when combining the benefits of SUR and AGC.

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Section: Discussionmentioning

confidence: 99%

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

et al. 2023

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“…OADR, OADEF, and OAML, increased target coverage compared to no adaptation while reducing the need for offline adaptation. Although efforts to expedite offline adaptation workflows have been made by triggering adaptation using deformed contours on weekly rCTs (Taasti et al 2022) or by anticipating anatomical changes to re-plan on predicted weekly rCTs (Zhang et al 2022), our proposed methods could enable a fully online adaptive approach based on daily corrCBCT. Daily-based OAPT would provide a quicker response to fast (or unexpected) inter-fractional anatomical changes while reducing the need for re-planning.…”

Section: Discussionmentioning

confidence: 99%

Dose mimicking based strategies for online adaptive proton therapy of head and neck cancer

et al. 2023

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Objective: To compare a not adapted (NA) robust planning strategy with three fully automated online adaptive proton therapy (OAPT) workflows based on the same optimization method: dose mimicking (DM). The added clinical value and limitations of the OAPT methods are investigated for head and neck cancer (HNC) patients.Approach: The three OAPT strategies aimed at compensating for inter-fractional anatomical changes by mimiking different dose distributions on corrected cone beam CT images (corrCBCTs). Order by complexity, the OAPTs were: (1) online adaptive dose restoration (OADR) where the approved clinical dose on the planning-CT (pCT) was mimicked, (2) online adaptation using DM of the deformed clinical dose from the pCT to corrCBCTs (OADEF), and (3) online adaptation applying DM to a predicted dose on corrCBCTs (OAML). Adaptation was only applied in fractions where the target coverage criteria were not met (D98% < 95% of the prescribed dose). For 10 HNC patients, the accumulated dose distributions over the 35 fractions were calculated for NA, OADR, OADEF, and OAML.Main results: Higher target coverage was observed for all OAPT strategies compared to no adaptation. OADEF and OAML outperformed both NA and OADR and were comparable in terms of target coverage to initial clinical plans. However, only OAML provided comparable NTCP values to those from the clinical dose without statistically significant differences. When the NA initial plan was evaluated on corrCBCTs, 51% of fractions needed adaptation. The adaptation rate decreased significantly to 25% when the last adapted plan with OADR was selected for delivery, to 16% with OADEF, and to 21% with OAML. The reduction was even greater when the best plan among previously generated adapted plans (instead of the last one) was selected.Significance: The implemented OAPT strategies provided superior target coverage compared to no adaptation, higher OAR sparing, and fewer required adaptations.

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“…Periodic QACT has been regarded as routine in the clinic. 10 , 11 , 12 , 13 , 14 Several methods have been published for predicting the time to replan based on the above-mentioned change variables. In-room CT and cone-beam CT (CBCT) range-based registrations, deformable image registrations, range-corrected dose distributions, intensity correction, gamma index, and water-equivalent thickness change on CBCT have been reported for adaptive proton therapy.…”

Section: Introductionmentioning

confidence: 99%

Cone-Beam CT Images as an Indicator of QACT During Adaptive Proton Therapy of Extremity Sarcomas

Biswal,

Zhang,

Nichols

et al. 2024

International Journal of Particle Therapy

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Improving workflow for adaptive proton therapy with predictive anatomical modelling: A proof of concept

Cited by 5 publications

References 38 publications

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

Dose mimicking based strategies for online adaptive proton therapy of head and neck cancer

Cone-Beam CT Images as an Indicator of QACT During Adaptive Proton Therapy of Extremity Sarcomas

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