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Generation and evaluation of anatomy-preserving virtual CT for online adaptive proton therapy
Stockholm University, Faculty of Science, Department of Physics. RaySearch Laboratories AB (Publ), Sweden; Karolinska Institutet, Sweden.ORCID iD: 0000-0002-8441-3595
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Number of Authors: 52024 (English)In: Medical Physics, ISSN 0094-2405, E-ISSN 2473-4209, Vol. 51, no 3, p. 1536-1546Article in journal (Refereed) Published
Abstract [en]

Background: Daily CTs generated by CBCT correction are required for daily replanning in online-adaptive proton therapy (APT) to effectively deal with inter-fractional changes. Out of the currently available methods, the suitability of a daily CT generation method for proton dose calculation also depends on the anatomical site.

Purpose: We propose an anatomy-preserving virtual CT (APvCT) method as a hybrid method of CBCT correction, which is especially suitable for large anatomy deformations. The accuracy of the hybrid method was assessed by comparison with the corrected CBCT (cCBCT) and virtual CT (vCT) methods in the context of online APT.

Methods: Seventy-one daily CBCTs of four prostate cancer patients treated with intensity modulated proton therapy (IMPT) were converted to daily CTs using cCBCT, vCT, and the newly proposed APvCT method. In APvCT, planning CT (pCT) were mapped to CBCT geometry using deformable image registration with boundary conditions on controlling regions of interest (ROIs) created with deep learning segmentation on cCBCT. The relative frequency distribution (RFD) of HU, mass density and stopping power ratio (SPR) values were assessed and compared with the pCT. The ROIs in the APvCT and vCT were compared with cCBCT in terms of Dice similarity coefficient (DSC) and mean distance-to-agreement (mDTA). For each patient, a robustly optimized IMPT plan was created on the pCT and subsequent daily adaptive plans on daily CTs. For dose distribution comparison on the same anatomy, the daily adaptive plans on cCBCT and vCT were recalculated on the corresponding APvCT. The dose distributions were compared in terms of isodose volumes and 3D global gamma-index passing rate (GPR) at γ(2%, 2 mm) criterion.

Results: For all patients, no noticeable difference in RFDs was observed amongst APvCT, vCT, and pCT except in cCBCT, which showed a noticeable difference. The minimum DSC value was 0.96 and 0.39 for contours in APvCT and vCT respectively. The average value of mDTA for APvCT was 0.01 cm for clinical target volume and ≤0.01 cm for organs at risk, which increased to 0.18 cm and ≤0.52 cm for vCT. The mean GPR value was 90.9%, 64.5%, and 67.0% for APvCT versus cCBCT, vCT versus cCBCT, and APvCT versus vCT, respectively. When recalculated on APvCT, the adaptive cCBCT and vCT plans resulted in mean GPRs of 89.5 ± 5.1% and 65.9 ± 19.1%, respectively. The mean DSC values for 80.0%, 90.0%, 95.0%, 98.0%, and 100.0% isodose volumes were 0.97, 0.97, 0.97, 0.95, and 0.91 for recalculated cCBCT plans, and 0.89, 0.88, 0.87, 0.85, and 0.81 for recalculated vCT plans. Hausdorff distance for the 100.0% isodose volume in some cases of recalculated cCBCT plans on APvCT exceeded 1.00 cm.

Conclusions: APvCT contours showed good agreement with reference contours of cCBCT which indicates anatomy preservation in APvCT. A vCT with erroneous anatomy can result in an incorrect adaptive plan. Further, slightly lower values of GPR between the APvCT and cCBCT-based adaptive plans can be explained by the difference in the cCBCT's SPR RFD from the pCT.

Place, publisher, year, edition, pages
2024. Vol. 51, no 3, p. 1536-1546
Keywords [en]
adaptive proton therapy, virtual/synthetic CT | daily anatomical variation
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:su:diva-226118DOI: 10.1002/mp.16941ISI: 001143329900001PubMedID: 38230803Scopus ID: 2-s2.0-85182451194OAI: oai:DiVA.org:su-226118DiVA, id: diva2:1835526
Available from: 2024-02-06 Created: 2024-02-06 Last updated: 2026-01-19
In thesis
1. Robust optimization considering uncertainties in adaptive proton therapy.
Open this publication in new window or tab >>Robust optimization considering uncertainties in adaptive proton therapy.
2024 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Proton therapy, a promising alternative to conventional photon therapy, has gained widespread acceptance in clinical practice. This is attributed to its superior depth-dose curve that has a negligible dose beyond the maximum range of the proton. A proton treatment planning requires a multitude of parameters and are either manually selected or optimized using mathematical formulation. However, a proton treatment plan is also subject to various systematic and random uncertainties that must be taken into account during optimization. Robust optimization is a commonly used method for integrating the setup and range uncertainties in proton therapy.

In addition to the uncertainties accounted for during the treatment planning phase, others can arise during the course of treatment and are often hard to predict. Changes in the patient's anatomy represent uncertainties that can significantly affect planned dose delivery. Therefore, adaptive planning is typically performed intermittently or regularly, depending on the changes in anatomy. Paper II included in this thesis proposed a method of adaptive planning that takes into account the impact of the patient's respiratory motion at the treatment site, such as the lungs and abdomen for 4D robust optimization. This method uses dose mimicking to reproduce the results as initially planned.  

This additional stage of adaptive planning can introduce new complexities and uncertainties into the treatment process. One such uncertainty arise from daily cone beam computed tomography (CBCT) images which are required for treatment plan adaptation. Several strategies have been proposed in the past to improve the quality of these images, but each strategy has its advantages and disadvantages, depending on the site of treatment. In Paper I, a method was proposed that combined the advantages of other frequently used methods to create an improved method for generating daily images with CT-like image quality. This can contribute towards the goal of online adaptive in the near future with reduced uncertainties.

This thesis will provide a brief introduction and an in-depth chapter to elucidate the background, better understand the physics of proton therapy, the process of treatment planning, and the need for adaptive planning.

Place, publisher, year, edition, pages
Stockholm: Department of Physics, Stockholm University, 2024
Keywords
Proton therapy, Robust optimization, Adaptive radiation therapy
National Category
Physical Sciences
Research subject
Medical Radiation Physics
Identifiers
urn:nbn:se:su:diva-229129 (URN)
Presentation
2024-06-03, CCK Lecture Hall, Cancer Center Karolinska (CCK), Karolinska Universitetssjukhuset, 171 76 Solna, Solna, 09:00 (English)
Opponent
Supervisors
Projects
European Union’s Horizon 2020 Marie Skłodowska-Curie Actions under Grant Agreement No. 955956
Funder
EU, Horizon 2020, 955956
Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2024-05-13Bibliographically approved

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