1
|
Quarz A, Volz L, Antink CH, Durante M, Graeff C. Deep learning-based voxel sampling for particle therapy treatment planning. Phys Med Biol 2024; 69:155014. [PMID: 38917844 DOI: 10.1088/1361-6560/ad5bba] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 06/25/2024] [Indexed: 06/27/2024]
Abstract
Objective.Scanned particle therapy often requires complex treatment plans, robust optimization, as well as treatment adaptation. Plan optimization is especially complicated for heavy ions due to the variable relative biological effectiveness. We present a novel deep-learning model to select a subset of voxels in the planning process thus reducing the planning problem size for improved computational efficiency.Approach.Using only a subset of the voxels in target and organs at risk (OARs) we produced high-quality treatment plans, but heuristic selection strategies require manual input. We designed a deep-learning model based onP-Net to obtain an optimal voxel sampling without relying on patient-specific user input. A cohort of 70 head and neck patients that received carbon ion therapy was used for model training (50), validation (10) and testing (10). For training, a total of 12 500 carbon ion plans were optimized, using a highly efficient artificial intelligence (AI) infrastructure implemented into a research treatment planning platform. A custom loss function increased sampling density in underdosed regions, while aiming to reduce the total number of voxels.Main results.On the test dataset, the number of voxels in the optimization could be reduced by 84.8% (median) at <1% median loss in plan quality. When the model was trained to reduce sampling in the target only while keeping all voxels in OARs, a median reduction up to 71.6% was achieved, with 0.5% loss in the plan quality. The optimization time was reduced by a factor of 7.5 for the total AI selection model and a factor of 3.7 for the model with only target selection.Significance.The novel deep-learning voxel sampling technique achieves a significant reduction in computational time with a negligible loss in the plan quality. The reduction in optimization time can be especially useful for future real-time adaptation strategies.
Collapse
Affiliation(s)
- A Quarz
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany
- Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany
| | - L Volz
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany
| | - C Hoog Antink
- Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany
| | - M Durante
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany
- Department of Condensed Matter Physics, Technische Universität Darmstadt, Darmstadt, Germany
- Department of Physics 'Ettore Pancini', University Federico II, Naples, Italy
| | - C Graeff
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany
- Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany
| |
Collapse
|
2
|
Lang Y, Jiang Z, Sun L, Tran P, Mossahebi S, Xiang L, Ren L. Patient-specific deep learning for 3D protoacoustic image reconstruction and dose verification in proton therapy. Med Phys 2024. [PMID: 38980065 DOI: 10.1002/mp.17294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/27/2024] [Accepted: 06/27/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND Protoacoustic (PA) imaging has the potential to provide real-time 3D dose verification of proton therapy. However, PA images are susceptible to severe distortion due to limited angle acquisition. Our previous studies showed the potential of using deep learning to enhance PA images. As the model was trained using a limited number of patients' data, its efficacy was limited when applied to individual patients. PURPOSE In this study, we developed a patient-specific deep learning method for protoacoustic imaging to improve the reconstruction quality of protoacoustic imaging and the accuracy of dose verification for individual patients. METHODS Our method consists of two stages: in the first stage, a group model is trained from a diverse training set containing all patients, where a novel deep learning network is employed to directly reconstruct the initial pressure maps from the radiofrequency (RF) signals; in the second stage, we apply transfer learning on the pre-trained group model using patient-specific dataset derived from a novel data augmentation method to tune it into a patient-specific model. Raw PA signals were simulated based on computed tomography (CT) images and the pressure map derived from the planned dose. The reconstructed PA images were evaluated against the ground truth by using the root mean squared errors (RMSE), structural similarity index measure (SSIM) and gamma index on 10 specific prostate cancer patients. The significance level was evaluated by t-test with the p-value threshold of 0.05 compared with the results from the group model. RESULTS The patient-specific model achieved an average RMSE of 0.014 (p < 0.05 ${{{p}}}<{0.05}$ ), and an average SSIM of 0.981 (p < 0.05 ${{{p}}}<{0.05}$ ), out-performing the group model. Qualitative results also demonstrated that our patient-specific approach acquired better imaging quality with more details reconstructed when comparing with the group model. Dose verification achieved an average RMSE of 0.011 (p < 0.05 ${{{p}}}<{0.05}$ ), and an average SSIM of 0.995 (p < 0.05 ${{{p}}}<{0.05}$ ). Gamma index evaluation demonstrated a high agreement (97.4% [p < 0.05 ${{{p}}}<{0.05}$ ] and 97.9% [p < 0.05 ${{{p}}}<{0.05}$ ] for 1%/3 and 1%/5 mm) between the predicted and the ground truth dose maps. Our approach approximately took 6 s to reconstruct PA images for each patient, demonstrating its feasibility for online 3D dose verification for prostate proton therapy. CONCLUSIONS Our method demonstrated the feasibility of achieving 3D high-precision PA-based dose verification using patient-specific deep-learning approaches, which can potentially be used to guide the treatment to mitigate the impact of range uncertainty and improve the precision. Further studies are needed to validate the clinical impact of the technique.
Collapse
Affiliation(s)
- Yankun Lang
- Department of Radiation Oncology Physics, University of Maryland, Baltimore, Maryland, USA
| | - Zhuoran Jiang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
| | - Leshan Sun
- Department of Biomedical Engineering and Radiology, University of California, Irnive, California, USA
| | - Phuoc Tran
- Department of Radiation Oncology Physics, University of Maryland, Baltimore, Maryland, USA
| | - Sina Mossahebi
- Department of Radiation Oncology Physics, University of Maryland, Baltimore, Maryland, USA
| | - Liangzhong Xiang
- Department of Biomedical Engineering and Radiology, University of California, Irnive, California, USA
| | - Lei Ren
- Department of Radiation Oncology Physics, University of Maryland, Baltimore, Maryland, USA
| |
Collapse
|
3
|
Fenwick JD, Mayhew C, Jolly S, Amos RA, Hawkins MA. Navigating the straits: realizing the potential of proton FLASH through physics advances and further pre-clinical characterization. Front Oncol 2024; 14:1420337. [PMID: 39022584 PMCID: PMC11252699 DOI: 10.3389/fonc.2024.1420337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 06/11/2024] [Indexed: 07/20/2024] Open
Abstract
Ultra-high dose-rate 'FLASH' radiotherapy may be a pivotal step forward for cancer treatment, widening the therapeutic window between radiation tumour killing and damage to neighbouring normal tissues. The extent of normal tissue sparing reported in pre-clinical FLASH studies typically corresponds to an increase in isotoxic dose-levels of 5-20%, though gains are larger at higher doses. Conditions currently thought necessary for FLASH normal tissue sparing are a dose-rate ≥40 Gy s-1, dose-per-fraction ≥5-10 Gy and irradiation duration ≤0.2-0.5 s. Cyclotron proton accelerators are the first clinical systems to be adapted to irradiate deep-seated tumours at FLASH dose-rates, but even using these machines it is challenging to meet the FLASH conditions. In this review we describe the challenges for delivering FLASH proton beam therapy, the compromises that ensue if these challenges are not addressed, and resulting dosimetric losses. Some of these losses are on the same scale as the gains from FLASH found pre-clinically. We therefore conclude that for FLASH to succeed clinically the challenges must be systematically overcome rather than accommodated, and we survey physical and pre-clinical routes for achieving this.
Collapse
Affiliation(s)
- John D. Fenwick
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Christopher Mayhew
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Simon Jolly
- Department of Physics and Astronomy, University College London, London, United Kingdom
| | - Richard A. Amos
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Maria A. Hawkins
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Clinical Oncology, Radiotherapy Department, University College London NHS Foundation Trust, London, United Kingdom
| |
Collapse
|
4
|
Viar-Hernandez D, Molina-Maza JM, Vera-Sánchez JA, Perez-Moreno JM, Mazal A, Rodriguez-Vila B, Malpica N, Torrado-Carvajal A. Enhancing adaptive proton therapy through CBCT images: Synthetic head and neck CT generation based on 3D vision transformers. Med Phys 2024; 51:4922-4935. [PMID: 38569141 DOI: 10.1002/mp.17057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 03/01/2024] [Accepted: 03/17/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Proton therapy is a form of radiotherapy commonly used to treat various cancers. Due to its high conformality, minor variations in patient anatomy can lead to significant alterations in dose distribution, making adaptation crucial. While cone-beam computed tomography (CBCT) is a well-established technique for adaptive radiation therapy (ART), it cannot be directly used for adaptive proton therapy (APT) treatments because the stopping power ratio (SPR) cannot be estimated from CBCT images. PURPOSE To address this limitation, Deep Learning methods have been suggested for converting pseudo-CT (pCT) images from CBCT images. In spite of convolutional neural networks (CNNs) have shown consistent improvement in pCT literature, there is still a need for further enhancements to make them suitable for clinical applications. METHODS The authors introduce the 3D vision transformer (ViT) block, studying its performance at various stages of the proposed architectures. Additionally, they conduct a retrospective analysis of a dataset that includes 259 image pairs from 59 patients who underwent treatment for head and neck cancer. The dataset is partitioned into 80% for training, 10% for validation, and 10% for testing purposes. RESULTS The SPR maps obtained from the pCT using the proposed method present an absolute relative error of less than 5% from those computed from the planning CT, thus improving the results of CBCT. CONCLUSIONS We introduce an enhanced ViT3D architecture for pCT image generation from CBCT images, reducing SPR error within clinical margins for APT workflows. The new method minimizes bias compared to CT-based SPR estimation and dose calculation, signaling a promising direction for future research in this field. However, further research is needed to assess the robustness and generalizability across different medical imaging applications.
Collapse
Affiliation(s)
- David Viar-Hernandez
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| | | | | | | | - Alejandro Mazal
- Centro de Protonterapia Quironsalud, Servicio de física médica, Madrid, Spain
| | - Borja Rodriguez-Vila
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| | - Norberto Malpica
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| | - Angel Torrado-Carvajal
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| |
Collapse
|
5
|
Qiu Z, Depauw N, Gorissen BL, Madden T, Ajdari A, den Hertog D, Bortfeld T. A reference-point-method-based online proton treatment plan re-optimization strategy and a novel solution to planning constraint infeasibility problem. Phys Med Biol 2024; 69:125001. [PMID: 38729194 DOI: 10.1088/1361-6560/ad4a00] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/10/2024] [Indexed: 05/12/2024]
Abstract
Objective. Propose a highly automated treatment plan re-optimization strategy suitable for online adaptive proton therapy. The strategy includes a rapid re-optimization method that generates quality replans and a novel solution that efficiently addresses the planning constraint infeasibility issue that can significantly prolong the re-optimization process.Approach. We propose a systematic reference point method (RPM) model that minimizes the l-infinity norm from the initial treatment plan in the daily objective space for online re-optimization. This model minimizes the largest objective value deviation among the objectives of the daily replan from their reference values, leading to a daily replan similar to the initial plan. Whether a set of planning constraints is feasible with respect to the daily anatomy cannot be known before solving the corresponding optimization problem. The conventional trial-and-error-based relaxation process can cost a significant amount of time. To that end, we propose an optimization problem that first estimates the magnitude of daily violation of each planning constraint. Guided by the violation magnitude and clinical importance of the constraints, the constraints are then iteratively converted into objectives based on their priority until the infeasibility issue is solved.Main results.The proposed RPM-based strategy generated replans similar to the offline manual replans within the online time requirement for six head and neck and four breast patients. The average targetD95and relevant organ at risk sparing parameter differences between the RPM replans and clinical offline replans were -0.23, -1.62 Gy for head and neck cases and 0.29, -0.39 Gy for breast cases. The proposed constraint relaxation solution made the RPM problem feasible after one round of relaxation for all four patients who encountered the infeasibility issue.Significance. We proposed a novel RPM-based re-optimization strategy and demonstrated its effectiveness on complex cases, regardless of whether constraint infeasibility is encountered.
Collapse
Affiliation(s)
- Zihang Qiu
- Department of Business Analytics, University of Amsterdam, Amsterdam, The Netherlands
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Nicolas Depauw
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Bram L Gorissen
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Boston, MA, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Thomas Madden
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Ali Ajdari
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Dick den Hertog
- Department of Business Analytics, University of Amsterdam, Amsterdam, The Netherlands
| | - Thomas Bortfeld
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| |
Collapse
|
6
|
Chang C, Bohannon D, Tian Z, Wang Y, Mcdonald MW, Yu DS, Liu T, Zhou J, Yang X. A retrospective study on the investigation of potential dosimetric benefits of online adaptive proton therapy for head and neck cancer. J Appl Clin Med Phys 2024; 25:e14308. [PMID: 38368614 PMCID: PMC11087169 DOI: 10.1002/acm2.14308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 10/28/2023] [Accepted: 02/06/2024] [Indexed: 02/20/2024] Open
Abstract
PURPOSE Proton therapy is sensitive to anatomical changes, often occurring in head-and-neck (HN) cancer patients. Although multiple studies have proposed online adaptive proton therapy (APT), there is still a concern in the radiotherapy community about the necessity of online APT. We have performed a retrospective study to investigate the potential dosimetric benefits of online APT for HN patients relative to the current offline APT. METHODS Our retrospective study has a patient cohort of 10 cases. To mimic online APT, we re-evaluated the dose of the in-use treatment plan on patients' actual treatment anatomy captured by cone-beam CT (CBCT) for each fraction and performed a templated-based automatic replanning if needed, assuming that these were performed online before treatment delivery. Cumulative dose of the simulated online APT course was calculated and compared with that of the actual offline APT course and the designed plan dose of the initial treatment plan (referred to as nominal plan). The ProKnow scoring system was employed and adapted for our study to quantify the actual quality of both courses against our planning goals. RESULTS The average score of the nominal plans over the 10 cases is 41.0, while those of the actual offline APT course and our simulated online course is 25.8 and 37.5, respectively. Compared to the offline APT course, our online course improved dose quality for all cases, with the score improvement ranging from 0.4 to 26.9 and an average improvement of 11.7. CONCLUSION The results of our retrospective study have demonstrated that online APT can better address anatomical changes for HN cancer patients than the current offline replanning practice. The advanced artificial intelligence based automatic replanning technology presents a promising avenue for extending potential benefits of online APT.
Collapse
Affiliation(s)
- Chih‐Wei Chang
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Duncan Bohannon
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Zhen Tian
- Department of Radiation and Cellular OncologyUniversity of ChicagoChicagoIllinoisUSA
| | - Yinan Wang
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Mark W. Mcdonald
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - David S. Yu
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Tian Liu
- Department of Radiation OncologyMount Sinai Medical CenterNew YorkNew YorkUSA
| | - Jun Zhou
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| |
Collapse
|
7
|
Kim JY, Tawk B, Knoll M, Hoegen-Saßmannshausen P, Liermann J, Huber PE, Lifferth M, Lang C, Häring P, Gnirs R, Jäkel O, Schlemmer HP, Debus J, Hörner-Rieber J, Weykamp F. Clinical Workflow of Cone Beam Computer Tomography-Based Daily Online Adaptive Radiotherapy with Offline Magnetic Resonance Guidance: The Modular Adaptive Radiotherapy System (MARS). Cancers (Basel) 2024; 16:1210. [PMID: 38539544 PMCID: PMC10969008 DOI: 10.3390/cancers16061210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/07/2024] [Accepted: 03/15/2024] [Indexed: 05/03/2024] Open
Abstract
PURPOSE The Ethos (Varian Medical Systems) radiotherapy device combines semi-automated anatomy detection and plan generation for cone beam computer tomography (CBCT)-based daily online adaptive radiotherapy (oART). However, CBCT offers less soft tissue contrast than magnetic resonance imaging (MRI). This work aims to present the clinical workflow of CBCT-based oART with shuttle-based offline MR guidance. METHODS From February to November 2023, 31 patients underwent radiotherapy on the Ethos (Varian, Palo Alto, CA, USA) system with machine learning (ML)-supported daily oART. Moreover, patients received weekly MRI in treatment position, which was utilized for daily plan adaptation, via a shuttle-based system. Initial and adapted treatment plans were generated using the Ethos treatment planning system. Patient clinical data, fractional session times (MRI + shuttle transport + positioning, adaptation, QA, RT delivery) and plan selection were assessed for all fractions in all patients. RESULTS In total, 737 oART fractions were applied and 118 MRIs for offline MR guidance were acquired. Primary sites of tumors were prostate (n = 16), lung (n = 7), cervix (n = 5), bladder (n = 1) and endometrium (n = 2). The treatment was completed in all patients. The median MRI acquisition time including shuttle transport and positioning to initiation of the Ethos adaptive session was 53.6 min (IQR 46.5-63.4). The median total treatment time without MRI was 30.7 min (IQR 24.7-39.2). Separately, median adaptation, plan QA and RT times were 24.3 min (IQR 18.6-32.2), 0.4 min (IQR 0.3-1,0) and 5.3 min (IQR 4.5-6.7), respectively. The adapted plan was chosen over the scheduled plan in 97.7% of cases. CONCLUSION This study describes the first workflow to date of a CBCT-based oART combined with a shuttle-based offline approach for MR guidance. The oART duration times reported resemble the range shown by previous publications for first clinical experiences with the Ethos system.
Collapse
Affiliation(s)
- Ji-Young Kim
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Bouchra Tawk
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Maximilian Knoll
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), Core Center Heidelberg, 69120 Heidelberg, Germany
| | - Philipp Hoegen-Saßmannshausen
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Jakob Liermann
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Peter E. Huber
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Molecular Radiooncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mona Lifferth
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Clemens Lang
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Peter Häring
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Regula Gnirs
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Oliver Jäkel
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Molecular Radiooncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Radiation Oncology, Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Department of Radiation Oncology, Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Juliane Hörner-Rieber
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Fabian Weykamp
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| |
Collapse
|
8
|
Oud M, Breedveld S, Rojo-Santiago J, Giżyńska MK, Kroesen M, Habraken S, Perkó Z, Heijmen B, Hoogeman M. A fast and robust constraint-based online re-optimization approach for automated online adaptive intensity modulated proton therapy in head and neck cancer. Phys Med Biol 2024; 69:075007. [PMID: 38373350 DOI: 10.1088/1361-6560/ad2a98] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/19/2024] [Indexed: 02/21/2024]
Abstract
Objective. In head-and-neck cancer intensity modulated proton therapy, adaptive radiotherapy is currently restricted to offline re-planning, mitigating the effect of slow changes in patient anatomies. Daily online adaptations can potentially improve dosimetry. Here, a new, fully automated online re-optimization strategy is presented. In a retrospective study, this online re-optimization approach was compared to our trigger-based offline re-planning (offlineTBre-planning) schedule, including extensive robustness analyses.Approach. The online re-optimization method employs automated multi-criterial re-optimization, using robust optimization with 1 mm setup-robustness settings (in contrast to 3 mm for offlineTBre-planning). Hard planning constraints and spot addition are used to enforce adequate target coverage, avoid prohibitively large maximum doses and minimize organ-at-risk doses. For 67 repeat-CTs from 15 patients, fraction doses of the two strategies were compared for the CTVs and organs-at-risk. Per repeat-CT, 10.000 fractions with different setup and range robustness settings were simulated using polynomial chaos expansion for fast and accurate dose calculations.Main results. For 14/67 repeat-CTs, offlineTBre-planning resulted in <50% probability ofD98%≥ 95% of the prescribed dose (Dpres) in one or both CTVs, which never happened with online re-optimization. With offlineTBre-planning, eight repeat-CTs had zero probability of obtainingD98%≥ 95%Dpresfor CTV7000, while the minimum probability with online re-optimization was 81%. Risks of xerostomia and dysphagia grade ≥ II were reduced by 3.5 ± 1.7 and 3.9 ± 2.8 percentage point [mean ± SD] (p< 10-5for both). In online re-optimization, adjustment of spot configuration followed by spot-intensity re-optimization took 3.4 min on average.Significance. The fast online re-optimization strategy always prevented substantial losses of target coverage caused by day-to-day anatomical variations, as opposed to the clinical trigger-based offline re-planning schedule. On top of this, online re-optimization could be performed with smaller setup robustness settings, contributing to improved organs-at-risk sparing.
Collapse
Affiliation(s)
- Michelle Oud
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| | - Sebastiaan Breedveld
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
| | - Jesús Rojo-Santiago
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| | | | - Michiel Kroesen
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Radiation Oncology, Delft, The Netherlands
| | - Steven Habraken
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| | - Zoltán Perkó
- Delft University of Technology, Faculty of Applied Sciences, Department of Radiation Science and Technology, The Netherlands
| | - Ben Heijmen
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
| | - Mischa Hoogeman
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| |
Collapse
|
9
|
Lundberg M, Meijers A, Souris K, Deffet S, Weber DC, Lomax A, Knopf A. Technical note: development of a simulation framework, enabling the investigation of locally tuned single energy proton radiography. Biomed Phys Eng Express 2024; 10:027002. [PMID: 38241732 DOI: 10.1088/2057-1976/ad20a8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/19/2024] [Indexed: 01/21/2024]
Abstract
Range uncertainties remain a limitation for the confined dose distribution that proton therapy can offer. The uncertainty stems from the ambiguity when translating CT Hounsfield Units (HU) into proton stopping powers. Proton Radiography (PR) can be used to verify the proton range. Specifically, PR can be used as a quality-control tool for CBCT-based synthetic CTs. An essential part of the work illustrating the potential of PR has been conducted using multi-layer ionization chamber (MLIC) detectors and mono-energetic PR. Due to the dimensions of commercially available MLICs, clinical adoption is cumbersome. Here, we present a simulation framework exploring locally-tuned single energy (LTSE) proton radiography and corresponding potential compact PR detector designs. Based on a planning CT data set, the presented framework models the water equivalent thickness. Subsequently, it analyses the proton energies required to pass through the geometry within a defined ROI. In the final step, an LTSE PR is simulated using the MCsquare Monte Carlo code. In an anatomical head phantom, we illustrate that LTSE PR allows for a significantly shorter longitudinal dimension of MLICs. We compared PR simulations for two exemplary 30 × 30 mm2proton fields passing the phantom at a 90° angle at an anterior and a posterior location in an iso-centric setup. The longitudinal distance over which all spots per field range out is significantly reduced for LTSE PR compared to mono-energetic PR. In addition, we illustrate the difference in shape of integral depth dose (IDD) when using constrained PR energies. Finally, we demonstrate the accordance of simulated and experimentally acquired IDDs for an LTSE PR acquisition. As the next steps, the framework will be used to investigate the sensitivity of LTSE PR to various sources of errors. Furthermore, we will use the framework to systematically explore the dimensions of an optimized MLIC design for daily clinical use.
Collapse
Affiliation(s)
- Måns Lundberg
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Arturs Meijers
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Kevin Souris
- Ion Beam Applications SA, Louvain-La-Neuve, Belgium
| | | | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Department of Radiation Oncology, University Hospital of Zürich, Zürich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Antony Lomax
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Department of Physics, ETH Zurich, Zurich, Switzerland
| | - Antje Knopf
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
| |
Collapse
|
10
|
Bobić M, Christensen JB, Lee H, Choulilitsa E, Czerska K, Togno M, Safai S, Yukihara EG, Winey BA, Lomax AJ, Paganetti H, Albertini F, Nesteruk KP. Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow. Front Oncol 2024; 13:1333039. [PMID: 38510267 PMCID: PMC10951997 DOI: 10.3389/fonc.2023.1333039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 12/18/2023] [Indexed: 03/22/2024] Open
Abstract
Purpose To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. Methods A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. Results The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. Conclusion The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.
Collapse
Affiliation(s)
- Mislav Bobić
- Department of Physics, ETH Zurich, Zurich, Switzerland
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Hoyeon Lee
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Evangelia Choulilitsa
- Department of Physics, ETH Zurich, Zurich, Switzerland
- Paul Scherrer Institute, Villigen, Switzerland
| | | | | | | | | | - Brian A. Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Antony J. Lomax
- Department of Physics, ETH Zurich, Zurich, Switzerland
- Paul Scherrer Institute, Villigen, Switzerland
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Konrad P. Nesteruk
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| |
Collapse
|
11
|
Knäusl B, Belotti G, Bertholet J, Daartz J, Flampouri S, Hoogeman M, Knopf AC, Lin H, Moerman A, Paganelli C, Rucinski A, Schulte R, Shimizu S, Stützer K, Zhang X, Zhang Y, Czerska K. A review of the clinical introduction of 4D particle therapy research concepts. Phys Imaging Radiat Oncol 2024; 29:100535. [PMID: 38298885 PMCID: PMC10828898 DOI: 10.1016/j.phro.2024.100535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/12/2023] [Accepted: 01/04/2024] [Indexed: 02/02/2024] Open
Abstract
Background and purpose Many 4D particle therapy research concepts have been recently translated into clinics, however, remaining substantial differences depend on the indication and institute-related aspects. This work aims to summarise current state-of-the-art 4D particle therapy technology and outline a roadmap for future research and developments. Material and methods This review focused on the clinical implementation of 4D approaches for imaging, treatment planning, delivery and evaluation based on the 2021 and 2022 4D Treatment Workshops for Particle Therapy as well as a review of the most recent surveys, guidelines and scientific papers dedicated to this topic. Results Available technological capabilities for motion surveillance and compensation determined the course of each 4D particle treatment. 4D motion management, delivery techniques and strategies including imaging were diverse and depended on many factors. These included aspects of motion amplitude, tumour location, as well as accelerator technology driving the necessity of centre-specific dosimetric validation. Novel methodologies for X-ray based image processing and MRI for real-time tumour tracking and motion management were shown to have a large potential for online and offline adaptation schemes compensating for potential anatomical changes over the treatment course. The latest research developments were dominated by particle imaging, artificial intelligence methods and FLASH adding another level of complexity but also opportunities in the context of 4D treatments. Conclusion This review showed that the rapid technological advances in radiation oncology together with the available intrafractional motion management and adaptive strategies paved the way towards clinical implementation.
Collapse
Affiliation(s)
- Barbara Knäusl
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Gabriele Belotti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Jenny Bertholet
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Juliane Daartz
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Mischa Hoogeman
- Department of Medical Physics & Informatics, HollandPTC, Delft, The Netherlands
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
| | - Antje C Knopf
- Institut für Medizintechnik und Medizininformatik Hochschule für Life Sciences FHNW, Muttenz, Switzerland
| | - Haibo Lin
- New York Proton Center, New York, NY, USA
| | - Astrid Moerman
- Department of Medical Physics & Informatics, HollandPTC, Delft, The Netherlands
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Antoni Rucinski
- Institute of Nuclear Physics Polish Academy of Sciences, PL-31342 Krakow, Poland
| | - Reinhard Schulte
- Division of Biomedical Engineering Sciences, School of Medicine, Loma Linda University
| | - Shing Shimizu
- Department of Carbon Ion Radiotherapy, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kristin Stützer
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Dresden, Germany
| | - Xiaodong Zhang
- Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Katarzyna Czerska
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| |
Collapse
|
12
|
Smolders A, Lomax A, Weber DC, Albertini F. Deep learning based uncertainty prediction of deformable image registration for contour propagation and dose accumulation in online adaptive radiotherapy. Phys Med Biol 2023; 68:245027. [PMID: 37820691 DOI: 10.1088/1361-6560/ad0282] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/11/2023] [Indexed: 10/13/2023]
Abstract
Objective.Online adaptive radiotherapy aims to fully leverage the advantages of highly conformal therapy by reducing anatomical and set-up uncertainty, thereby alleviating the need for robust treatments. This requires extensive automation, among which is the use of deformable image registration (DIR) for contour propagation and dose accumulation. However, inconsistencies in DIR solutions between different algorithms have caused distrust, hampering its direct clinical use. This work aims to enable the clinical use of DIR by developing deep learning methods to predict DIR uncertainty and propagating it into clinically usable metrics.Approach.Supervised and unsupervised neural networks were trained to predict the Gaussian uncertainty of a given deformable vector field (DVF). Since both methods rely on different assumptions, their predictions differ and were further merged into a combined model. The resulting normally distributed DVFs can be directly sampled to propagate the uncertainty into contour and accumulated dose uncertainty.Main results.The unsupervised and combined models can accurately predict the uncertainty in the manually annotated landmarks on the DIRLAB dataset. Furthermore, for 5 patients with lung cancer, the propagation of the predicted DVF uncertainty into contour uncertainty yielded for both methods anexpected calibration errorof less than 3%. Additionally, theprobabilisticly accumulated dose volume histograms(DVH) encompass well the accumulated proton therapy doses using 5 different DIR algorithms. It was additionally shown that the unsupervised model can be used for different DIR algorithms without the need for retraining.Significance.Our work presents first-of-a-kind deep learning methods to predict the uncertainty of the DIR process. The methods are fast, yield high-quality uncertainty estimates and are useable for different algorithms and applications. This allows clinics to use DIR uncertainty in their workflows without the need to change their DIR implementation.
Collapse
Affiliation(s)
- A Smolders
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - A Lomax
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - D C Weber
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Radiation Oncology, University Hospital Zurich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - F Albertini
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| |
Collapse
|
13
|
Berthold J, Pietsch J, Piplack N, Khamfongkhruea C, Thiele J, Hölscher T, Janssens G, Smeets J, Traneus E, Löck S, Stützer K, Richter C. Detectability of Anatomical Changes With Prompt-Gamma Imaging: First Systematic Evaluation of Clinical Application During Prostate-Cancer Proton Therapy. Int J Radiat Oncol Biol Phys 2023; 117:718-729. [PMID: 37160193 DOI: 10.1016/j.ijrobp.2023.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 04/02/2023] [Accepted: 05/02/2023] [Indexed: 05/11/2023]
Abstract
PURPOSE The development of online-adaptive proton therapy (PT) is essential to overcome limitations encountered by day-to-day variations of the patient's anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present the results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system. METHODS AND MATERIALS For 15 patients with prostate cancer, PGI measurements were performed during 105 fractions (201 fields) with in-room control computed tomography (CT)acquisitions. Field-wise doses on control CT scans were manually classified as whether showing relevant or non-relevant anatomical changes. This manual classification of the treatment fields was then used to establish an automatic field-wise ground truth based on spot-wise dosimetric range shifts, which were retrieved from integrated depth-dose (IDD) profiles. To determine the detection capability of anatomical changes with PGI, spot-wise PGI-based range shifts were initially compared with corresponding dosimetric IDD range shifts. As final endpoint, the agreement of a developed field-wise PGI classification model with the field-wise ground truth was determined. Therefore, the PGI model was optimized and tested for a subcohort of 131 and 70 treatment fields, respectively. RESULTS The correlation between PGI and IDD range shifts was high, ρpearson = 0.67 (p < 0.01). Field-wise binary PGI classification resulted in an area under the curve of 0.72 and 0.80 for training and test cohorts, respectively. The model detected relevant anatomical changes in the independent test cohort, with a sensitivity and specificity of 74% and 79%, respectively. CONCLUSIONS For the first time, evidence of the detection capability of anatomical changes in prostate-cancer PT from clinically acquired PGI data is shown. This emphasizes the benefit of PGI-based range verification and demonstrates its potential for online-adaptive PT.
Collapse
Affiliation(s)
- Jonathan Berthold
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany.
| | - Julian Pietsch
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany
| | - Nick Piplack
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Technische Universität Dresden, Faculty of Electrical and Computer Engineering, Dresden, Germany
| | - Chirasak Khamfongkhruea
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Princess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Julia Thiele
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Tobias Hölscher
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | | | | | | | - Steffen Löck
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; German Cancer Consortium (DKTK), partner site Dresden, Germany and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Kristin Stützer
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany
| | - Christian Richter
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; German Cancer Consortium (DKTK), partner site Dresden, Germany and German Cancer Research Center (DKFZ), Heidelberg, Germany
| |
Collapse
|
14
|
Brincker M, Jensen I, Rechner LA, Schut DA, Johansen TS, Nielsen M, Thomsen JB. Multi-center comparison between proton and photon plans for mediastinal lymphomas. Acta Oncol 2023; 62:1251-1255. [PMID: 37624751 DOI: 10.1080/0284186x.2023.2251089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023]
Affiliation(s)
- Mads Brincker
- Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg, Denmark
| | - Ingelise Jensen
- Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg, Denmark
| | - Laura Ann Rechner
- Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Oncology, Radiotherapy Research Unit, Herlev and Gentofte Hospital, University of Copenhagen, Herlev, Denmark
| | - Deborah Anne Schut
- Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | | | - Morten Nielsen
- Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark
| | - Jakob Borup Thomsen
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
| |
Collapse
|
15
|
Nenoff L, Sudhyadhom A, Lau J, Sharp GC, Paganetti H, Pursley J. Comparing Predicted Toxicities between Hypofractionated Proton and Photon Radiotherapy of Liver Cancer Patients with Different Adaptive Schemes. Cancers (Basel) 2023; 15:4592. [PMID: 37760560 PMCID: PMC10526201 DOI: 10.3390/cancers15184592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/30/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
With the availability of MRI linacs, online adaptive intensity modulated radiotherapy (IMRT) has become a treatment option for liver cancer patients, often combined with hypofractionation. Intensity modulated proton therapy (IMPT) has the potential to reduce the dose to healthy tissue, but it is particularly sensitive to changes in the beam path and might therefore benefit from online adaptation. This study compares the normal tissue complication probabilities (NTCPs) for liver and duodenal toxicity for adaptive and non-adaptive IMRT and IMPT treatments of liver cancer patients. Adaptive and non-adaptive IMRT and IMPT plans were optimized to 50 Gy (RBE = 1.1 for IMPT) in five fractions for 10 liver cancer patients, using the original MRI linac images and physician-drawn structures. Three liver NTCP models were used to predict radiation-induced liver disease, an increase in albumin-bilirubin level, and a Child-Pugh score increase of more than 2. Additionally, three duodenal NTCP models were used to predict gastric bleeding, gastrointestinal (GI) toxicity with grades >3, and duodenal toxicity grades 2-4. NTCPs were calculated for adaptive and non-adaptive IMRT and IMPT treatments. In general, IMRT showed higher NTCP values than IMPT and the differences were often significant. However, the differences between adaptive and non-adaptive treatment schemes were not significant, indicating that the NTCP benefit of adaptive treatment regimens is expected to be smaller than the expected difference between IMRT and IMPT.
Collapse
Affiliation(s)
- Lena Nenoff
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Atchar Sudhyadhom
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Radiation Oncology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Jackson Lau
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gregory C. Sharp
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Harald Paganetti
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jennifer Pursley
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| |
Collapse
|
16
|
Smolders A, Choulilitsa E, Czerska K, Bizzocchi N, Krcek R, Lomax A, Weber DC, Albertini F. Dosimetric comparison of autocontouring techniques for online adaptive proton therapy. Phys Med Biol 2023; 68:175006. [PMID: 37385266 DOI: 10.1088/1361-6560/ace307] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 06/29/2023] [Indexed: 07/01/2023]
Abstract
Objective.Anatomical and daily set-up uncertainties impede high precision delivery of proton therapy. With online adaptation, the daily plan is reoptimized on an image taken shortly before the treatment, reducing these uncertainties and, hence, allowing a more accurate delivery. This reoptimization requires target and organs-at-risk (OAR) contours on the daily image, which need to be delineated automatically since manual contouring is too slow. Whereas multiple methods for autocontouring exist, none of them are fully accurate, which affects the daily dose. This work aims to quantify the magnitude of this dosimetric effect for four contouring techniques.Approach.Plans reoptimized on automatic contours are compared with plans reoptimized on manual contours. The methods include rigid and deformable registration (DIR), deep-learning based segmentation and patient-specific segmentation.Main results.It was found that independently of the contouring method, the dosimetric influence of usingautomaticOARcontoursis small (<5% prescribed dose in most cases), with DIR yielding the best results. Contrarily, the dosimetric effect of using theautomatic target contourwas larger (>5% prescribed dose in most cases), indicating that manual verification of that contour remains necessary. However, when compared to non-adaptive therapy, the dose differences caused by automatically contouring the target were small and target coverage was improved, especially for DIR.Significance.The results show that manual adjustment of OARs is rarely necessary and that several autocontouring techniques are directly usable. Contrarily, manual adjustment of the target is important. This allows prioritizing tasks during time-critical online adaptive proton therapy and therefore supports its further clinical implementation.
Collapse
Affiliation(s)
- A Smolders
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - E Choulilitsa
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - K Czerska
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| | - N Bizzocchi
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| | - R Krcek
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - A Lomax
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - D C Weber
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Radiation Oncology, University Hospital Zurich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - F Albertini
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| |
Collapse
|
17
|
Knäusl B, Taasti VT, Poulsen P, Muren LP. Surveying the clinical practice of treatment adaptation and motion management in particle therapy. Phys Imaging Radiat Oncol 2023; 27:100457. [PMID: 37361612 PMCID: PMC10285555 DOI: 10.1016/j.phro.2023.100457] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023] Open
Affiliation(s)
- Barbara Knäusl
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Vicki T Taasti
- Department of Radiation Oncology (Maastro), GROW - School for Oncology and Reproduction, Maastricht, University Medical Centre+, Maastricht, The Netherlands
| | - Per Poulsen
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
- Department of Oncology, Aarhus University, Aarhus, Denmark
| | - Ludvig P Muren
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| |
Collapse
|
18
|
Graeff C, Volz L, Durante M. Emerging technologies for cancer therapy using accelerated particles. PROGRESS IN PARTICLE AND NUCLEAR PHYSICS 2023; 131:104046. [PMID: 37207092 PMCID: PMC7614547 DOI: 10.1016/j.ppnp.2023.104046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Cancer therapy with accelerated charged particles is one of the most valuable biomedical applications of nuclear physics. The technology has vastly evolved in the past 50 years, the number of clinical centers is exponentially growing, and recent clinical results support the physics and radiobiology rationale that particles should be less toxic and more effective than conventional X-rays for many cancer patients. Charged particles are also the most mature technology for clinical translation of ultra-high dose rate (FLASH) radiotherapy. However, the fraction of patients treated with accelerated particles is still very small and the therapy is only applied to a few solid cancer indications. The growth of particle therapy strongly depends on technological innovations aiming to make the therapy cheaper, more conformal and faster. The most promising solutions to reach these goals are superconductive magnets to build compact accelerators; gantryless beam delivery; online image-guidance and adaptive therapy with the support of machine learning algorithms; and high-intensity accelerators coupled to online imaging. Large international collaborations are needed to hasten the clinical translation of the research results.
Collapse
Affiliation(s)
- Christian Graeff
- GSI Helmholtzzentrum für Schwerionenforschung, Biophysics Department, Planckstraße 1, 64291 Darmstadt, Germany
- Technische Universität Darmstadt, Darmstadt, Germany
| | - Lennart Volz
- GSI Helmholtzzentrum für Schwerionenforschung, Biophysics Department, Planckstraße 1, 64291 Darmstadt, Germany
| | - Marco Durante
- GSI Helmholtzzentrum für Schwerionenforschung, Biophysics Department, Planckstraße 1, 64291 Darmstadt, Germany
- Technische Universität Darmstadt, Darmstadt, Germany
- Dipartimento di Fisica “Ettore Pancini”, University Federico II, Naples, Italy
| |
Collapse
|
19
|
He M, Cao Y, Chi C, Yang X, Ramin R, Wang S, Yang G, Mukhtorov O, Zhang L, Kazantsev A, Enikeev M, Hu K. Research progress on deep learning in magnetic resonance imaging-based diagnosis and treatment of prostate cancer: a review on the current status and perspectives. Front Oncol 2023; 13:1189370. [PMID: 37546423 PMCID: PMC10400334 DOI: 10.3389/fonc.2023.1189370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 05/30/2023] [Indexed: 08/08/2023] Open
Abstract
Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection and noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging and time-consuming, which may impact sensitivity and specificity. With recent technological advances, artificial intelligence (AI) in the form of computer-aided diagnosis (CAD) based on MRI data has been applied to prostate cancer diagnosis and treatment. Among AI techniques, deep learning involving convolutional neural networks contributes to detection, segmentation, scoring, grading, and prognostic evaluation of prostate cancer. CAD systems have automatic operation, rapid processing, and accuracy, incorporating multiple sequences of multiparametric MRI data of the prostate gland into the deep learning model. Thus, they have become a research direction of great interest, especially in smart healthcare. This review highlights the current progress of deep learning technology in MRI-based diagnosis and treatment of prostate cancer. The key elements of deep learning-based MRI image processing in CAD systems and radiotherapy of prostate cancer are briefly described, making it understandable not only for radiologists but also for general physicians without specialized imaging interpretation training. Deep learning technology enables lesion identification, detection, and segmentation, grading and scoring of prostate cancer, and prediction of postoperative recurrence and prognostic outcomes. The diagnostic accuracy of deep learning can be improved by optimizing models and algorithms, expanding medical database resources, and combining multi-omics data and comprehensive analysis of various morphological data. Deep learning has the potential to become the key diagnostic method in prostate cancer diagnosis and treatment in the future.
Collapse
Affiliation(s)
- Mingze He
- Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Yu Cao
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Changliang Chi
- Department of Urology, The First Hospital of Jilin University (Lequn Branch), Changchun, Jilin, China
| | - Xinyi Yang
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Rzayev Ramin
- Department of Radiology, The Second University Clinic, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Shuowen Wang
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Guodong Yang
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Otabek Mukhtorov
- Regional State Budgetary Health Care Institution, Kostroma Regional Clinical Hospital named after Korolev E.I. Avenue Mira, Kostroma, Russia
| | - Liqun Zhang
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, China
| | - Anton Kazantsev
- Regional State Budgetary Health Care Institution, Kostroma Regional Clinical Hospital named after Korolev E.I. Avenue Mira, Kostroma, Russia
| | - Mikhail Enikeev
- Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Kebang Hu
- Department of Urology, The First Hospital of Jilin University (Lequn Branch), Changchun, Jilin, China
| |
Collapse
|
20
|
Yan S, Ngoma TA, Ngwa W, Bortfeld TR. Global democratisation of proton radiotherapy. Lancet Oncol 2023; 24:e245-e254. [PMID: 37269856 DOI: 10.1016/s1470-2045(23)00184-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 04/05/2023] [Accepted: 04/19/2023] [Indexed: 06/05/2023]
Abstract
Proton radiotherapy is an advanced treatment option compared with conventional x-ray treatment, delivering much lower doses of radiation to healthy tissues surrounding the tumour. However, proton therapy is currently not widely available. In this Review, we summarise the evolution of proton therapy to date, together with the benefits to patients and society. These developments have led to an exponential growth in the number of hospitals using proton radiotherapy worldwide. However, the gap between the number of patients who should be treated with proton radiotherapy and those who have access to it remains large. We summarise the ongoing research and development that is contributing to closing this gap, including the improvement of treatment efficiency and efficacy, and advances in fixed-beam treatments that do not require an enormously large, heavy, and costly gantry. The ultimate goal of decreasing the size of proton therapy machines to fit into standard treatment rooms appears to be within reach, and we discuss future research and development opportunities to achieve this goal.
Collapse
Affiliation(s)
- Susu Yan
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Twalib A Ngoma
- Department Clinical Oncology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Wilfred Ngwa
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Information and Sciences, ICT University, Yaoundé, Cameroon
| | - Thomas R Bortfeld
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| |
Collapse
|
21
|
Lalonde A, Bobić M, Sharp GC, Chamseddine I, Winey B, Paganetti H. 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. Phys Med Biol 2023; 68:115018. [PMID: 37164020 PMCID: PMC10351361 DOI: 10.1088/1361-6560/acd433] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 05/03/2023] [Accepted: 05/10/2023] [Indexed: 05/12/2023]
Abstract
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.SignificanceOnline 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.
Collapse
Affiliation(s)
- Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- ETH Zürich, Zürich, Switzerland
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ibrahim Chamseddine
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Brian Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| |
Collapse
|
22
|
Zhang L, Holmes JM, Liu Z, Vora SA, Sio TT, Vargas CE, Yu NY, Keole SR, Schild SE, Bues M, Li S, Liu T, Shen J, Wong WW, Liu W. Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy. ARXIV 2023:arXiv:2305.18572v1. [PMID: 37396612 PMCID: PMC10312803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
PURPOSE To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent replanning. METHODS PBSPT plans of 103 prostate cancer patients and 83 lung cancer patients previously treated at our institution were included in the study, each with CTs, structure sets, and plan doses calculated by the in-house developed Monte-Carlo dose engine. For the ablation study, we designed three experiments corresponding to the following three methods: 1) Experiment 1, the conventional region of interest (ROI) method. 2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. 3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D-Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates, and dice coefficients for the structures enclosed by the iso-dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency. RESULTS Compared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices. For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method can improve the passing rates in these regions and the sliding window method further improved them. A similar trend was also observed for the dice coefficients. In fact, this trend was especially remarkable for relatively low prescription isodose lines. The dose predictions for all the testing cases were completed within 0.25s.
Collapse
Affiliation(s)
- Lian Zhang
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Jason M. Holmes
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Zhengliang Liu
- Department of Computer Science, University of Georgia, Athens, GA 30602, USA
| | - Sujay A. Vora
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Terence T. Sio
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Carlos E. Vargas
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Nathan Y. Yu
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Sameer R. Keole
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Steven E. Schild
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Martin Bues
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Sheng Li
- Department of Data Science, University of Virginia, Charlottesville, VA 22903, USA
| | - Tianming Liu
- Department of Computer Science, University of Georgia, Athens, GA 30602, USA
| | - Jiajian Shen
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - William W. Wong
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| | - Wei Liu
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ 85054, USA
| |
Collapse
|
23
|
Qiu Z, Olberg S, den Hertog D, Ajdari A, Bortfeld T, Pursley J. Online adaptive planning methods for intensity-modulated radiotherapy. Phys Med Biol 2023; 68:10.1088/1361-6560/accdb2. [PMID: 37068488 PMCID: PMC10637515 DOI: 10.1088/1361-6560/accdb2] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/17/2023] [Indexed: 04/19/2023]
Abstract
Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence's potential application to online adaptive planning.
Collapse
Affiliation(s)
- Zihang Qiu
- Department of Business Analytics, University of Amsterdam, The Netherlands
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Sven Olberg
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Dick den Hertog
- Department of Business Analytics, University of Amsterdam, The Netherlands
| | - Ali Ajdari
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Thomas Bortfeld
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Jennifer Pursley
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| |
Collapse
|
24
|
Yahya N, Manan HA. Quality of Life and Patient-Reported Outcomes Following Proton Therapy for Oropharyngeal Carcinoma: A Systematic Review. Cancers (Basel) 2023; 15:cancers15082252. [PMID: 37190180 DOI: 10.3390/cancers15082252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND Complex anatomy surrounding the oropharynx makes proton therapy (PT), especially intensity-modulated PT (IMPT), a potentially attractive option due to its ability to reduce the volume of irradiated healthy tissues. Dosimetric improvement may not translate to clinically relevant benefits. As outcome data are emerging, we aimed to evaluate the evidence of the quality of life (QOL) and patient-reported outcomes (PROs) following PT for oropharyngeal carcinoma (OC). MATERIALS AND METHODS We searched PubMed and Scopus electronic databases (date: 15 February 2023) to identify original studies on QOL and PROs following PT for OC. We employed a fluid strategy in the search strategy by tracking citations of the initially selected studies. Reports were extracted for information on demographics, main results, and clinical and dose factor correlates. Quality assessment was performed using the NIH's Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. The PRISMA guidelines were followed in the preparation of this report. RESULTS Seven reports were selected, including one from a recently published paper captured from citation tracking. Five compared PT and photon-based therapy, although none were randomized controlled trials. Most endpoints with significant differences favored PT, including xerostomia, cough, need for nutritional supplements, dysgeusia, food taste, appetite, and general symptoms. However, some endpoints favored photon-based therapy (sexual symptoms) or showed no significant difference (e.g., fatigue, pain, sleep, mouth sores). The PROs and QOL improve following PT but do not appear to return to baseline. CONCLUSION Evidence suggests that PT causes less QOL and PRO deterioration than photon-based therapy. Biases due to the non-randomized study design remain obstacles to a firm conclusion. Whether or not PT is cost-effective should be the subject of further investigation.
Collapse
Affiliation(s)
- Noorazrul Yahya
- Diagnostic Imaging and Radiotherapy, Center for Diagnostic, Therapeutic and Investigative Studies (CODTIS), Faculty of Health Sciences, National University of Malaysia, Jalan Raja Muda Aziz, Kuala Lumpur 50300, Malaysia
| | - Hanani Abdul Manan
- Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur 56000, Malaysia
| |
Collapse
|
25
|
Trnkova P, Zhang Y, Toshito T, Heijmen B, Richter C, Aznar MC, Albertini F, Bolsi A, Daartz J, Knopf AC, Bertholet J. A survey of practice patterns for adaptive particle therapy for interfractional changes. Phys Imaging Radiat Oncol 2023; 26:100442. [PMID: 37197154 PMCID: PMC10183663 DOI: 10.1016/j.phro.2023.100442] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/22/2023] [Accepted: 04/24/2023] [Indexed: 05/19/2023] Open
Abstract
Background and purpose Anatomical changes may compromise the planned target coverage and organs-at-risk dose in particle therapy. This study reports on the practice patterns for adaptive particle therapy (APT) to evaluate current clinical practice and wishes and barriers to further implementation. Materials and methods An institutional questionnaire was distributed to PT centres worldwide (7/2020-6/2021) asking which type of APT was used, details of the workflow, and what the wishes and barriers to implementation were. Seventy centres from 17 countries participated. A three-round Delphi consensus analysis (10/2022) among the authors followed to define recommendations on required actions and future vision. Results Out of the 68 clinically operational centres, 84% were users of APT for at least one treatment site with head and neck being most common. APT was mostly performed offline with only two online APT users (plan-library). No centre used online daily re-planning. Daily 3D imaging was used for APT by 19% of users. Sixty-eight percent of users had plans to increase their use or change their technique for APT. The main barrier was "lack of integrated and efficient workflows". Automation and speed, reliable dose deformation for dose accumulation and higher quality of in-room volumetric imaging were identified as the most urgent task for clinical implementation of online daily APT. Conclusion Offline APT was implemented by the majority of PT centres. Joint efforts between industry research and clinics are needed to translate innovations into efficient and clinically feasible workflows for broad-scale implementation of online APT.
Collapse
Affiliation(s)
- Petra Trnkova
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
- Corresponding author.
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Toshiyuki Toshito
- Nagoya Proton Therapy Center, Nagoya City University West Medical Center, Nagoya, Japan
| | - Ben Heijmen
- Department of Radiotherapy, Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands
| | - Christian Richter
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany
| | - Marianne C. Aznar
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | | | - Alessandra Bolsi
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Juliane Daartz
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, MA 02114, United States of America
| | - Antje C. Knopf
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
| | - Jenny Bertholet
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern, Switzerland
| |
Collapse
|
26
|
Bobić M, Lalonde A, Nesteruk KP, Lee H, Nenoff L, Gorissen BL, Bertolet A, Busse PM, Chan AW, Winey BA, Sharp GC, Verburg JM, Lomax AJ, Paganetti H. Large anatomical changes in head-and-neck cancers – a dosimetric comparison of online and offline adaptive proton therapy. Clin Transl Radiat Oncol 2023; 40:100625. [PMID: 37090849 PMCID: PMC10120292 DOI: 10.1016/j.ctro.2023.100625] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023] Open
Abstract
Purpose This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.
Collapse
|
27
|
Huiskes M, Astreinidou E, Kong W, Breedveld S, Heijmen B, Rasch C. Dosimetric impact of adaptive proton therapy in head and neck cancer - A review. Clin Transl Radiat Oncol 2023; 39:100598. [PMID: 36860581 PMCID: PMC9969246 DOI: 10.1016/j.ctro.2023.100598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/10/2023] [Accepted: 02/12/2023] [Indexed: 02/18/2023] Open
Abstract
Background Intensity Modulated Proton Therapy (IMPT) in head and neck cancer (HNC) is susceptible to anatomical changes and patient set-up inaccuracies during the radiotherapy course, which can cause discrepancies between planned and delivered dose. The discrepancies can be counteracted by adaptive replanning strategies. This article reviews the observed dosimetric impact of adaptive proton therapy (APT) and the timing to perform a plan adaptation in IMPT in HNC. Methods A literature search of articles published in PubMed/MEDLINE, EMBASE and Web of Science from January 2010 to March 2022 was performed. Among a total of 59 records assessed for possible eligibility, ten articles were included in this review. Results Included studies reported on target coverage deterioration in IMPT plans during the RT course, which was recovered with the application of an APT approach. All APT plans showed an average improved target coverage for the high- and low-dose targets as compared to the accumulated dose on the planned plans. Dose improvements up to 2.5 Gy (3.5 %) and up to 4.0 Gy (7.1 %) in the D98 of the high- and low dose targets were observed with APT. Doses to the organs at risk (OARs) remained equal or decreased slightly after APT was applied. In the included studies, APT was largely performed once, which resulted in the largest target coverage improvement, but eventual additional APT improved the target coverage further. There is no data showing what is the most appropriate timing for APT. Conclusion APT during IMPT for HNC patients improves target coverage. The largest improvement in target coverage was found with a single adaptive intervention, and an eventual second or more frequent APT application improved the target coverage further. Doses to the OARs remained equal or decreased slightly after applying APT. The most optimal timing for APT is yet to be determined.
Collapse
Affiliation(s)
- Merle Huiskes
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, the Netherlands,Corresponding author at: Department of Radiation Oncology, Leiden University Medical Centre, Albinusdreef 2, P.O. Box 9600, Postal zone K1-P, 2300 RC Leiden, the Netherlands.
| | - Eleftheria Astreinidou
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, the Netherlands
| | - Wens Kong
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, the Netherlands
| | - Sebastiaan Breedveld
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, the Netherlands
| | - Ben Heijmen
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, the Netherlands
| | - Coen Rasch
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, the Netherlands,HollandPTC, Delft, the Netherlands
| |
Collapse
|
28
|
Chang S, Liu G, Zhao L, Zheng W, Yan D, Chen P, Li X, Deraniyagala R, Stevens C, Grills I, Chinnaiyan P, Li X, Ding X. Introduce a rotational robust optimization framework for spot-scanning proton arc (SPArc) therapy. Phys Med Biol 2022; 68. [PMID: 36546347 DOI: 10.1088/1361-6560/aca874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 12/02/2022] [Indexed: 12/03/2022]
Abstract
Objective. Proton dosimetric uncertainties resulting from the patient's daily setup errors in rotational directions exist even with advanced image-guided radiotherapy techniques. Thus, we developed a new rotational robust optimization SPArc algorithm (SPArcrot) to mitigate the dosimetric impact of the rotational setup error in Raystation ver. 6.02 (RaySearch Laboratory AB, Stockholm, Sweden).Approach.The initial planning CT was rotated ±5° simulating the worst-case setup error in the roll direction. The SPArcrotuses a multi-CT robust optimization framework by taking into account of such rotational setup errors. Five cases representing different disease sites were evaluated. Both SPArcoriginaland SPArcrotplans were generated using the same translational robust optimized parameters. To quantitatively investigate the mitigation effect from the rotational setup errors, all plans were recalculated using a series of pseudo-CT with rotational setup error (±1°/±2°/±3°/±5°). Dosimetric metrics such as D98% of CTV, and 3D gamma analysis were used to assess the dose distribution changes in the target and OARs.Main results.The magnitudes of dosimetric changes in the targets due to rotational setup error were significantly reduced by the SPArcrotcompared to SPArc in all cases. The uncertainties of the max dose to the OARs, such as brainstem, spinal cord and esophagus were significantly reduced using SPArcrot. The uncertainties of the mean dose to the OARs such as liver and oral cavity, parotid were comparable between the two planning techniques. The gamma passing rate (3%/3 mm) was significantly improved for CTV of all tumor sites through SPArcrot.Significance.Rotational setup error is one of the major issues which could lead to significant dose perturbations. SPArcrotplanning approach can consider such rotational error from patient setup or gantry rotation error by effectively mitigating the dose uncertainties to the target and in the adjunct series OARs.
Collapse
Affiliation(s)
- Sheng Chang
- Department of Radiation Oncology, Wuhan University, Renmin Hospital, Wuhan, 430060 Hubei Province, People's Republic of China.,Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Gang Liu
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America.,Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430023, People's Republic of China
| | - Lewei Zhao
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Weili Zheng
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Di Yan
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Peter Chen
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Xiangpan Li
- Department of Radiation Oncology, Wuhan University, Renmin Hospital, Wuhan, 430060 Hubei Province, People's Republic of China
| | - Rohan Deraniyagala
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Craig Stevens
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Inga Grills
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Prakash Chinnaiyan
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Xiaoqiang Li
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| | - Xuanfeng Ding
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48074, United States of America
| |
Collapse
|
29
|
Yao W, Zhang B, Han D, Polf J, Vedam S, Lasio G, Yi B. Use of CBCT plus plan robustness for reducing QACT frequency in intensity-modulated proton therapy: Head-and-neck cases. Med Phys 2022; 49:6794-6801. [PMID: 35933322 DOI: 10.1002/mp.15915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 06/20/2022] [Accepted: 08/01/2022] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Anatomic variation has a significant dosimetric impact in intensity-modulated proton therapy. Weekly or biweekly computed tomography (CT) scans, called quality assurance CTs (QACTs), are used to monitor anatomic and resultant dose changes to determine whether adaptive plans are needed. Frequent CT scans result in unwanted QACT dose and increased clinical workloads. This study proposed utilizing patient setup cone-beam CTs (CBCTs) and treatment plan robustness to reduce the frequency of QACTs. METHODS We retrospectively analyzed data from 27 patients with head-and-neck cancer, including 594 CBCTs, 136 QACTs, and 19 adaptive plans. For each CBCT, water-equivalent thickness (WET) along the pencil-beam path was calculated. For each treatment plan, the WET of the first-day CBCT was used as the reference, and the mean WET changes (ΔWET) in each following CBCT was used as the surrogate of proton range change. Using CBCTs acquired prior to a QACT, we predicted the ΔWET on the QACT day by a linear regression model. The impact of range change on target dose was calculated as the predicted ΔWET weighted by the monitor units of each field. In addition, plan robustness was estimated from the robust dose-volume histograms (DVHs) and combined with ΔWET to reduce QACT frequency. Robustness was estimated from the distance between the DVH curves of the nominal and worst scenarios. RESULTS When the estimated mean ΔWET was <6.5 mm (or <7.5 mm if the robustness was >95%), the QACT could be skipped without missing any adaptive planning; otherwise a QACT was required. Overall, 41% of QACTs could be eliminated when ΔWET was <6.5 mm and 56% when ΔWET was <7.5 mm, and robustness was >95%. At least one QACT could have been omitted in 25 of the 27 cases under skipping thresholds at ΔWETs <7.5 mm and R > 95%. CONCLUSION This study suggests that the number of QACTs can be greatly reduced by calculating range change in patient setup CBCTs and can be further reduced by combining this information with analyses of plan robustness.
Collapse
Affiliation(s)
- Weiguang Yao
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Baoshe Zhang
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Dong Han
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Jerimy Polf
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Sastry Vedam
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Giovanni Lasio
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Byongyong Yi
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|
30
|
A plan verification platform for online adaptive proton therapy using deep learning-based Monte–Carlo denoising. Phys Med 2022; 103:18-25. [DOI: 10.1016/j.ejmp.2022.09.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 09/27/2022] [Accepted: 09/28/2022] [Indexed: 11/21/2022] Open
|
31
|
Nesteruk KP, Bobić M, Sharp GC, Lalonde A, Winey BA, Nenoff L, Lomax AJ, Paganetti H. Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers. Cancers (Basel) 2022; 14:cancers14205155. [PMID: 36291939 PMCID: PMC9600085 DOI: 10.3390/cancers14205155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/15/2022] [Accepted: 10/19/2022] [Indexed: 01/11/2023] Open
Abstract
PURPOSE To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients. METHODS We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDIvol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference. RESULTS The maximum differences in D98 between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%. CONCLUSION The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.
Collapse
Affiliation(s)
- Konrad P. Nesteruk
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Correspondence:
| | - Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland
| | - Gregory C. Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Brian A. Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Lena Nenoff
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Antony J. Lomax
- Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| |
Collapse
|
32
|
Moglioni M, Kraan AC, Baroni G, Battistoni G, Belcari N, Berti A, Carra P, Cerello P, Ciocca M, De Gregorio A, De Simoni M, Del Sarto D, Donetti M, Dong Y, Embriaco A, Fantacci ME, Ferrero V, Fiorina E, Fischetti M, Franciosini G, Giraudo G, Laruina F, Maestri D, Magi M, Magro G, Malekzadeh E, Marafini M, Mattei I, Mazzoni E, Mereu P, Mirandola A, Morrocchi M, Muraro S, Orlandi E, Patera V, Pennazio F, Pullia M, Retico A, Rivetti A, Da Rocha Rolo MD, Rosso V, Sarti A, Schiavi A, Sciubba A, Sportelli G, Tampellini S, Toppi M, Traini G, Trigilio A, Valle SM, Valvo F, Vischioni B, Vitolo V, Wheadon R, Bisogni MG. In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO. Front Oncol 2022; 12:929949. [PMID: 36226070 PMCID: PMC9549776 DOI: 10.3389/fonc.2022.929949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam’s Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan.
Collapse
Affiliation(s)
- Martina Moglioni
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Aafke Christine Kraan
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- *Correspondence: Aafke Christine Kraan,
| | - Guido Baroni
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
- Politecnico di Milano, Milano, Italy
| | | | - Nicola Belcari
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Andrea Berti
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
- Istituto di Scienza e Tecnologie dell’Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Pietro Carra
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | | | - Mario Ciocca
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Angelica De Gregorio
- Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
| | - Micol De Simoni
- Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
| | - Damiano Del Sarto
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Marco Donetti
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Yunsheng Dong
- Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Milano, Italy
- Dipartimento di Fisica, Università di Milano, Milano, Italy
| | - Alessia Embriaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Pavia, Pavia, Italy
| | - Maria Evelina Fantacci
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Veronica Ferrero
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | - Elisa Fiorina
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | - Marta Fischetti
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
| | - Gaia Franciosini
- Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
| | - Giuseppe Giraudo
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | - Francesco Laruina
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Davide Maestri
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Marco Magi
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
| | - Giuseppe Magro
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Etesam Malekzadeh
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
- Department of Medical Physics, Tarbiat Modares University, Teheran, Iran
| | - Michela Marafini
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
- Museo Storico della Fisica e Centro Studi e Ricerche “E. Fermi”, Roma, Italy
| | - Ilaria Mattei
- Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Milano, Italy
| | - Enrico Mazzoni
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
| | - Paolo Mereu
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | | | - Matteo Morrocchi
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Silvia Muraro
- Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Milano, Italy
| | - Ester Orlandi
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Vincenzo Patera
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
| | | | - Marco Pullia
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | | | - Angelo Rivetti
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | | | - Valeria Rosso
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | - Alessio Sarti
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
| | - Angelo Schiavi
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
| | - Adalberto Sciubba
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione dei Laboratori di Frascati, Frascati, Italy
| | - Giancarlo Sportelli
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| | | | - Marco Toppi
- Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Universit `a di Roma, Roma, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione dei Laboratori di Frascati, Frascati, Italy
| | - Giacomo Traini
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
- Museo Storico della Fisica e Centro Studi e Ricerche “E. Fermi”, Roma, Italy
| | - Antonio Trigilio
- Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Roma, Italy
| | | | | | | | - Viviana Vitolo
- Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Richard Wheadon
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | - Maria Giuseppina Bisogni
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy
- Dipartimento di Fisica, Università di Pisa, Pisa, Italy
| |
Collapse
|
33
|
Lin B, Huang D, Gao F, Yang Y, Wu D, Zhang Y, Feng G, Dai T, Du X. Mechanisms of FLASH effect. Front Oncol 2022; 12:995612. [PMID: 36212435 PMCID: PMC9537695 DOI: 10.3389/fonc.2022.995612] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
FLASH radiotherapy (FLASH-RT) is a novel radiotherapy technology defined as ultra-high dose rate (≥ 40 Gy/s) radiotherapy. The biological effects of FLASH-RT include two aspects: first, compared with conventional dose rate radiotherapy, FLASH-RT can reduce radiation-induced damage in healthy tissue, and second, FLASH-RT can retain antitumor effectiveness. Current research shows that mechanisms of the biological effects of FLASH-RT are related to oxygen. However, due to the short time of FLASH-RT, evidences related to the mechanisms are indirect, and the exact mechanisms of the biological effects of FLASH-RT are not completely clear and some are even contradictory. This review focuses on the mechanisms of the biological effects of FLASH-RT and proposes future research directions.
Collapse
Affiliation(s)
- Binwei Lin
- National Health Commission (NHC) Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Department of Oncology, Mianyang Central Hospital, Mianyang, China
- State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
| | - Dan Huang
- Department of Radiology Mianyang Central Hospital, Mianyang, China
| | - Feng Gao
- National Health Commission (NHC) Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Department of Oncology, Mianyang Central Hospital, Mianyang, China
| | - Yiwei Yang
- Institute of Applied Electronics, China Academy of Engineering Physics, Mianyang, China
| | - Dai Wu
- Institute of Applied Electronics, China Academy of Engineering Physics, Mianyang, China
| | - Yu Zhang
- National Health Commission (NHC) Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Department of Oncology, Mianyang Central Hospital, Mianyang, China
| | - Gang Feng
- National Health Commission (NHC) Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Department of Oncology, Mianyang Central Hospital, Mianyang, China
| | - Tangzhi Dai
- National Health Commission (NHC) Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Department of Oncology, Mianyang Central Hospital, Mianyang, China
| | - Xiaobo Du
- National Health Commission (NHC) Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Department of Oncology, Mianyang Central Hospital, Mianyang, China
| |
Collapse
|
34
|
Volz L, Sheng Y, Durante M, Graeff C. Considerations for Upright Particle Therapy Patient Positioning and Associated Image Guidance. Front Oncol 2022; 12:930850. [PMID: 35965576 PMCID: PMC9372451 DOI: 10.3389/fonc.2022.930850] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/17/2022] [Indexed: 11/16/2022] Open
Abstract
Particle therapy is a rapidly growing field in cancer therapy. Worldwide, over 100 centers are in operation, and more are currently in construction phase. The interest in particle therapy is founded in the superior target dose conformity and healthy tissue sparing achievable through the particles’ inverse depth dose profile. This physical advantage is, however, opposed by increased complexity and cost of particle therapy facilities. Particle therapy, especially with heavier ions, requires large and costly equipment to accelerate the particles to the desired treatment energy and steer the beam to the patient. A significant portion of the cost for a treatment facility is attributed to the gantry, used to enable different beam angles around the patient for optimal healthy tissue sparing. Instead of a gantry, a rotating chair positioning system paired with a fixed horizontal beam line presents a suitable cost-efficient alternative. Chair systems have been used already at the advent of particle therapy, but were soon dismissed due to increased setup uncertainty associated with the upright position stemming from the lack of dedicated image guidance systems. Recently, treatment chairs gained renewed interest due to the improvement in beam delivery, commercial availability of vertical patient CT imaging and improved image guidance systems to mitigate the problem of anatomical motion in seated treatments. In this review, economical and clinical reasons for an upright patient positioning system are discussed. Existing designs targeted for particle therapy are reviewed, and conclusions are drawn on the design and construction of chair systems and associated image guidance. Finally, the different aspects from literature are channeled into recommendations for potential upright treatment layouts, both for retrofitting and new facilities.
Collapse
Affiliation(s)
- Lennart Volz
- Biophysics, GSI Helmholtz Center for Heavy Ion Research GmbH, Darmstadt, Germany.,Department of Medical Physics, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Yinxiangzi Sheng
- Biophysics, GSI Helmholtz Center for Heavy Ion Research GmbH, Darmstadt, Germany.,Department of Medical Physics, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Marco Durante
- Biophysics, GSI Helmholtz Center for Heavy Ion Research GmbH, Darmstadt, Germany.,Institute of Condensed Matter Physics, Technical University of Darmstadt, Darmstadt, Germany
| | - Christian Graeff
- Biophysics, GSI Helmholtz Center for Heavy Ion Research GmbH, Darmstadt, Germany.,Institute of Electrical Engineering and Information Technology, Technical University of Darmstadt, Darmstadt, Germany
| |
Collapse
|
35
|
Nenoff L, Buti G, Bobić M, Lalonde A, Nesteruk KP, Winey B, Sharp GC, Sudhyadhom A, Paganetti H. Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans. Cancers (Basel) 2022; 14:cancers14163926. [PMID: 36010919 PMCID: PMC9406068 DOI: 10.3390/cancers14163926] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 08/10/2022] [Accepted: 08/12/2022] [Indexed: 01/11/2023] Open
Abstract
Currently, adaptive strategies require time- and resource-intensive manual structure corrections. This study compares different strategies: optimization without manual structure correction, adaptation with physician-drawn structures, and no adaptation. Strategies were compared for 16 patients with pancreas, liver, and head and neck (HN) cancer with 1-5 repeated images during treatment: 'reference adaptation', with structures drawn by a physician; 'single-DIR adaptation', using a single set of deformably propagated structures; 'multi-DIR adaptation', using robust planning with multiple deformed structure sets; 'conservative adaptation', using the intersection and union of all deformed structures; 'probabilistic adaptation', using the probability of a voxel belonging to the structure in the optimization weight; and 'no adaptation'. Plans were evaluated using reference structures and compared using a scoring system. The reference adaptation with physician-drawn structures performed best, and no adaptation performed the worst. For pancreas and liver patients, adaptation with a single DIR improved the plan quality over no adaptation. For HN patients, integrating structure uncertainties brought an additional benefit. If resources for manual structure corrections would prevent online adaptation, manual correction could be replaced by a fast 'plausibility check', and plans could be adapted with correction-free adaptation strategies. Including structure uncertainties in the optimization has the potential to make online adaptation more automatable.
Collapse
Affiliation(s)
- Lena Nenoff
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
- Correspondence:
| | - Gregory Buti
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
- Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Mislav Bobić
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Physics, ETH Zurich, 8092 Zurich, Switzerland
| | - Arthur Lalonde
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Konrad P. Nesteruk
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Brian Winey
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gregory Charles Sharp
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Atchar Sudhyadhom
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Harald Paganetti
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| |
Collapse
|
36
|
Cao W, Rocha H, Mohan R, Lim G, Goudarzi HM, Ferreira BC, Dias JM. Reflections on beam configuration optimization for intensity-modulated proton therapy. Phys Med Biol 2022; 67. [PMID: 35561700 DOI: 10.1088/1361-6560/ac6fac] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 05/13/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Presumably, intensity-modulated proton radiotherapy (IMPT) is the most powerful form of proton radiotherapy. In the current state of the art, IMPT beam configurations (i.e. the number of beams and their directions) are, in general, chosen subjectively based on prior experience and practicality. Beam configuration optimization (BCO) for IMPT could, in theory, significantly enhance IMPT’s therapeutic potential. However, BCO is complex and highly computer resource-intensive. Some algorithms for BCO have been developed for intensity-modulated photon therapy (IMRT). They are rarely used clinically mainly because the large number of beams typically employed in IMRT renders BCO essentially unnecessary. Moreover, in the newer form of IMRT, volumetric modulated arc therapy, there are no individual static beams. BCO is of greater importance for IMPT because it typically employs a very small number of beams (2-4) and, when the number of beams is small, BCO is critical for improving plan quality. However, the unique properties and requirements of protons, particularly in IMPT, make BCO challenging. Protons are more sensitive than photons to anatomic changes, exhibit variable relative biological effectiveness along their paths, and, as recently discovered, may spare the immune system. Such factors must be considered in IMPT BCO, though doing so would make BCO more resource intensive and make it more challenging to extend BCO algorithms developed for IMRT to IMPT. A limited amount of research in IMPT BCO has been conducted; however, considerable additional work is needed for its further development to make it truly effective and computationally practical. This article aims to provide a review of existing BCO algorithms, most of which were developed for IMRT, and addresses important requirements specific to BCO for IMPT optimization that necessitate the modification of existing approaches or the development of new effective and efficient ones.
Collapse
|
37
|
Bäumer C, Frakulli R, Kohl J, Nagaraja S, Steinmeier T, Worawongsakul R, Timmermann B. Adaptive Proton Therapy of Pediatric Head and Neck Cases Using MRI-Based Synthetic CTs: Initial Experience of the Prospective KiAPT Study. Cancers (Basel) 2022; 14:cancers14112616. [PMID: 35681594 PMCID: PMC9179385 DOI: 10.3390/cancers14112616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/20/2022] [Accepted: 05/20/2022] [Indexed: 12/07/2022] Open
Abstract
BACKGROUND AND PURPOSE Interfractional anatomical changes might affect the outcome of proton therapy (PT). We aimed to prospectively evaluate the role of Magnetic Resonance Imaging (MRI) based adaptive PT for children with tumors of the head and neck and base of skull. METHODS MRI verification images were acquired at half of the treatment course. A synthetic computed tomography (CT) image was created using this MRI and a deformable image registration (DIR) to the reference MRI. The methodology was verified with in-silico phantoms and validated using a clinical case with a shrinking cystic hygroma on the basis of dosimetric quantities of contoured structures. The dose distributions on the verification X-ray CT and on the synthetic CT were compared with a gamma-index test using global 2 mm/2% criteria. RESULTS Regarding the clinical validation case, the gamma-index pass rate was 98.3%. Eleven patients were included in the clinical study. The most common diagnosis was rhabdomyosarcoma (73%). Craniofacial tumor site was predominant in 64% of patients, followed by base of skull (18%). For one individual case the synthetic CT showed an increase in the median D2 and Dmax dose on the spinal cord from 20.5 GyRBE to 24.8 GyRBE and 14.7 GyRBE to 25.1 GyRBE, respectively. Otherwise, doses received by OARs remained relatively stable. Similarly, the target volume coverage seen by D95% and V95% remained unchanged. CONCLUSIONS The method of transferring anatomical changes from MRIs to a synthetic CTs was successfully implemented and validated with simple, commonly available tools. In the frame of our early results on a small cohort, no clinical relevant deterioration for neither PTV coverage nor an increased dose burden to OARs occurred. However, the study will be continued to identify a pediatric patient cohort, which benefits from adaptive treatment planning.
Collapse
Affiliation(s)
- Christian Bäumer
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Department of Physics, Technische Universität Dortmund, 44227 Dortmund, Germany
- Correspondence:
| | - Rezarta Frakulli
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
- Department of Particle Therapy, 45147 Essen, Germany
| | - Jessica Kohl
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
| | - Sindhu Nagaraja
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
- Department of Particle Therapy, 45147 Essen, Germany
| | - Theresa Steinmeier
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
- Department of Particle Therapy, 45147 Essen, Germany
| | - Rasin Worawongsakul
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
- Department of Particle Therapy, 45147 Essen, Germany
- Radiation Oncology Unit, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Nakhon 73170, Thailand
| | - Beate Timmermann
- West German Proton Therapy Centre Essen, 45147 Essen, Germany; (R.F.); (J.K.); (S.N.); (T.S.); (R.W.); (B.T.)
- University Hospital Essen, 45147 Essen, Germany
- West German Cancer Center (WTZ), 45147 Essen, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Department of Particle Therapy, 45147 Essen, Germany
| |
Collapse
|
38
|
Li H, Hrinivich WT, Chen H, Sheikh K, Ho MW, Ger R, Liu D, Hales RK, Voong KR, Halthore A, Deville C. Evaluating Proton Dose and Associated Range Uncertainty Using Daily Cone-Beam CT. Front Oncol 2022; 12:830981. [PMID: 35449577 PMCID: PMC9016186 DOI: 10.3389/fonc.2022.830981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose This study aimed to quantitatively evaluate the range uncertainties that arise from daily cone-beam CT (CBCT) images for proton dose calculation compared to CT using a measurement-based technique. Methods For head and thorax phantoms, wedge-shaped intensity-modulated proton therapy (IMPT) treatment plans were created such that the gradient of the wedge intersected and was measured with a 2D ion chamber array. The measured 2D dose distributions were compared with 2D dose planes extracted from the dose distributions using the IMPT plan calculated on CT and CBCT. Treatment plans of a thymoma cancer patient treated with breath-hold (BH) IMPT were recalculated on 28 CBCTs and 9 CTs, and the resulting dose distributions were compared. Results The range uncertainties for the head phantom were determined to be 1.2% with CBCT, compared to 0.5% for CT, whereas the range uncertainties for the thorax phantom were 2.1% with CBCT, compared to 0.8% for CT. The doses calculated on CBCT and CT were similar with similar anatomy changes. For the thymoma patient, the primary source of anatomy change was the BH uncertainty, which could be up to 8 mm in the superior-inferior (SI) direction. Conclusion We developed a measurement-based range uncertainty evaluation method with high sensitivity and used it to validate the accuracy of CBCT-based range and dose calculation. Our study demonstrated that the CBCT-based dose calculation could be used for daily dose validation in selected proton patients.
Collapse
Affiliation(s)
- Heng Li
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - William T Hrinivich
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Hao Chen
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Khadija Sheikh
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Meng Wei Ho
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Rachel Ger
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Dezhi Liu
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Russell Kenneth Hales
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Khinh Ranh Voong
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Aditya Halthore
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Curtiland Deville
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| |
Collapse
|
39
|
Post-Mastectomy Radiation Therapy: Applications and Advancements. CURRENT BREAST CANCER REPORTS 2022. [DOI: 10.1007/s12609-022-00449-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
40
|
Pakela JM, Knopf A, Dong L, Rucinski A, Zou W. Management of Motion and Anatomical Variations in Charged Particle Therapy: Past, Present, and Into the Future. Front Oncol 2022; 12:806153. [PMID: 35356213 PMCID: PMC8959592 DOI: 10.3389/fonc.2022.806153] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 02/04/2022] [Indexed: 12/14/2022] Open
Abstract
The major aim of radiation therapy is to provide curative or palliative treatment to cancerous malignancies while minimizing damage to healthy tissues. Charged particle radiotherapy utilizing carbon ions or protons is uniquely suited for this task due to its ability to achieve highly conformal dose distributions around the tumor volume. For these treatment modalities, uncertainties in the localization of patient anatomy due to inter- and intra-fractional motion present a heightened risk of undesired dose delivery. A diverse range of mitigation strategies have been developed and clinically implemented in various disease sites to monitor and correct for patient motion, but much work remains. This review provides an overview of current clinical practices for inter and intra-fractional motion management in charged particle therapy, including motion control, current imaging and motion tracking modalities, as well as treatment planning and delivery techniques. We also cover progress to date on emerging technologies including particle-based radiography imaging, novel treatment delivery methods such as tumor tracking and FLASH, and artificial intelligence and discuss their potential impact towards improving or increasing the challenge of motion mitigation in charged particle therapy.
Collapse
Affiliation(s)
- Julia M Pakela
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, United States
| | - Antje Knopf
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.,Department I of Internal Medicine, Center for Integrated Oncology Cologne, University Hospital of Cologne, Cologne, Germany
| | - Lei Dong
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, United States
| | - Antoni Rucinski
- Institute of Nuclear Physics, Polish Academy of Sciences, Krakow, Poland
| | - Wei Zou
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, United States
| |
Collapse
|