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Rojo-Santiago J, Habraken SJM, Unipan M, Both S, Bosmans G, Perkó Z, Korevaar E, Hoogeman MS. A probabilistic evaluation of the Dutch robustness and model-based selection protocols for Head-and-Neck IMPT: A multi-institutional study. Radiother Oncol 2024; 199:110441. [PMID: 39069084 DOI: 10.1016/j.radonc.2024.110441] [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: 03/21/2024] [Revised: 07/12/2024] [Accepted: 07/15/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND AND PURPOSE In the Netherlands, 2 protocols have been standardized for PT among the 3 proton centers: a robustness evaluation (RE) to ensure adequate CTV dose and a model-based selection (MBS) approach for IMPT patient-selection. This multi-institutional study investigates (i) inter-patient and inter-center variation of target dose from the RE protocol and (ii) the robustness of the MBS protocol against treatment errors for a cohort of head-and-neck cancer (HNC) patients treated in the 3 Dutch proton centers. MATERIALS AND METHODS Clinical treatment plans of 100 HNC patients were evaluated. Polynomial Chaos Expansion (PCE) was used to perform a comprehensive robustness evaluation per plan, enabling the probabilistic evaluation of 100,000 complete fractionated treatments. PCE allowed to derive scenario distributions of clinically relevant dosimetric parameters to assess CTV dose (D99.8%/D0.2%, based on a prior photon plan calibration) and tumour control probabilities (TCP) as well as the evaluation of the dose to OARs and normal tissue complication probabilities (NTCP) per center. RESULTS For the CTV70.00, doses from the RE protocol were consistent with the clinical plan evaluation metrics used in the 3 centers. For the CTV54.25, D99.8% were consistent with the clinical plan evaluation metrics at center 1 and 2 while, for center 3, a reduction of 1 GyRBE was found on average. This difference did not impact modelled TCP at center 3. Differences between expected and nominal NTCP were below 0.3 percentage point for most patients. CONCLUSION The standardization of the RE and MBS protocol lead to comparable results in terms of TCP and the NTCPs. Still, significant inter-patient and inter-center variation in dosimetric parameters remained due to clinical practice differences at each institution. The MBS approach is a robust protocol to qualify patients for PT.
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Affiliation(s)
- Jesús Rojo-Santiago
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, the Netherlands; HollandPTC, Delft, the Netherlands.
| | - Steven J M Habraken
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, the Netherlands; HollandPTC, Delft, the Netherlands
| | - Mirko Unipan
- GROW School for Oncology, Maastricht University Medical Center, Department of Radiation Oncology (Maastro), Maastricht, the Netherlands
| | - Stefan Both
- Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Geert Bosmans
- GROW School for Oncology, Maastricht University Medical Center, Department of Radiation Oncology (Maastro), Maastricht, the Netherlands
| | - Zoltán Perkó
- Delft University of Technology, Department of Radiation Science and Technology, Delft, the Netherlands
| | - Erik Korevaar
- Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Mischa S Hoogeman
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, the Netherlands; HollandPTC, Delft, the Netherlands
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Oud M, Breedveld S, Giżyńska M, Chen YH, Habraken S, Perkó Z, Heijmen B, Hoogeman M. Dosimetric advantages of adaptive IMPT vs. Enhanced workload and treatment time - A need for automation. Radiother Oncol 2024; 201:110548. [PMID: 39343389 DOI: 10.1016/j.radonc.2024.110548] [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: 04/25/2024] [Revised: 09/19/2024] [Accepted: 09/23/2024] [Indexed: 10/01/2024]
Abstract
INTRODUCTION In head-and-neck IMPT, trigger-based offline plan adaptation (Offlinetrigger-based) is often used. Our goal was to compare this to four alternative adaptive strategies for dosimetry, workload and treatment time, considering also foreseen further technological advancements, including anticipated automation. MATERIALS AND METHODS Alternative strategies included weekly offline re-planning (Offlineweekly), daily plan selection from a library (Librarystatic and Libraryprogsressive) and a fast, approximate daily online re-optimization approach (Onlinere-opt). Impact on CTV coverage and NTCPs was assessed by simulations based on repeat-CTs from 15 patients. Full daily re-planning was used as dosimetric benchmark. Increases in workload and treatment time were estimated. RESULTS Both for coverage and NTCPs, fast Onlinere-opt performed as well as full re-planning. Compared to current practice, Onlinere-opt showed enhanced probabilities for high coverage, and resulted in reductions in grade ≥ II NTCPs of 4.6 ± 1.7 %-point for xerostomia and 4.2 ± 2.3 %-point for dysphagia. Offlineweekly and library strategies did not show coverage enhancements and resulted in smaller NTCP improvements. Further automation can largely limit workload and treatment time increases. With anticipated further automation, adaptation-related workload of Offlineweekly, Librarystatic, Libraryprogressive, and Onlinere-opt was expected to increase by 3, 8, 21, and 66 h for 35 fraction treatment courses compared to Offlinetrigger-based. The corresponding adaptation-related prolonged treatment times were estimated to be 0, 4, 6, and 29 min/fraction. CONCLUSION Online adaptive strategies could approach dosimetric quality of full re-planning at the cost of additional workload and prolonged treatment time compared to the current offline adaptive strategy. Automation needs to play a key role in making more complex adaptive approaches feasible.
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Affiliation(s)
- Michelle Oud
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, Netherlands; HollandPTC, Delft, Netherlands.
| | - Sebastiaan Breedveld
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, Netherlands
| | | | - Yi Hsuan Chen
- Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Netherlands
| | - Steven Habraken
- HollandPTC, Delft, Netherlands; Leiden University Medical Center, Department of Radiation Oncology, Leiden, Netherlands
| | - Zoltán Perkó
- Delft University of Technology, Faculty of Applied Sciences, Department of Radiation Science and Technology, Netherlands
| | - Ben Heijmen
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, Netherlands
| | - Mischa Hoogeman
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, Netherlands; HollandPTC, Delft, Netherlands
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Fogazzi E, Hu G, Bruzzi M, Farace P, Kröncke T, Niepel K, Ricke J, Risch F, Sabel B, Scaringella M, Schwarz F, Tommasino F, Landry G, Civinini C, Parodi K. A direct comparison of multi-energy x-ray and proton CT for imaging and relative stopping power estimation of plastic and ex-vivophantoms. Phys Med Biol 2024; 69:175021. [PMID: 39159669 DOI: 10.1088/1361-6560/ad70ef] [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: 05/14/2024] [Accepted: 08/19/2024] [Indexed: 08/21/2024]
Abstract
Objective.Proton therapy administers a highly conformal dose to the tumour region, necessitating accurate prediction of the patient's 3D map of proton relative stopping power (RSP) compared to water. This remains challenging due to inaccuracies inherent in single-energy computed tomography (SECT) calibration. Recent advancements in spectral x-ray CT (xCT) and proton CT (pCT) have shown improved RSP estimation compared to traditional SECT methods. This study aims to provide the first comparison of the imaging and RSP estimation performance among dual-energy CT (DECT) and photon-counting CT (PCCT) scanners, and a pCT system prototype.Approach.Two phantoms were scanned with the three systems for their performance characterisation: a plastic phantom, filled with water and containing four plastic inserts and a wood insert, and a heterogeneous biological phantom, containing a formalin-stabilised bovine specimen. RSP maps were generated by converting CT numbers to RSP using a calibration based on low- and high-energy xCT images, while pCT utilised a distance-driven filtered back projection algorithm for RSP reconstruction. Spatial resolution, noise, and RSP accuracy were compared across the resulting images.Main results.All three systems exhibited similar spatial resolution of around 0.54 lp/mm for the plastic phantom. The PCCT images were less noisy than the DECT images at the same dose level. The lowest mean absolute percentage error (MAPE) of RSP,(0.28±0.07)%, was obtained with the pCT system, compared to MAPE values of(0.51±0.08)%and(0.80±0.08)%for the DECT- and PCCT-based methods, respectively. For the biological phantom, the xCT-based methods resulted in higher RSP values in most of the voxels compared to pCT.Significance.The pCT system yielded the most accurate estimation of RSP values for the plastic materials, and was thus used to benchmark the xCT calibration performance on the biological phantom. This study underlined the potential benefits and constraints of utilising such a novelex-vivophantom for inter-centre surveys in future.
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Affiliation(s)
- Elena Fogazzi
- Physics Department, University of Trento, Trento, TN, Italy
- Trento Institute for Fundamental Physics and Applications (TIFPA), Italian National Institute of Nuclear Physics (INFN), Trento, TN, Italy
| | - Guyue Hu
- Department of Medical Physics, Faculty of Physics, LMU Munich, Garching, Germany
| | - Mara Bruzzi
- Italian National Institute of Nuclear Physics (INFN), Florence section, Sesto Fiorentino, FI, Italy
- Physics and Astronomy Department, University of Florence, Sesto Fiorentino, FI, Italy
| | - Paolo Farace
- Trento Institute for Fundamental Physics and Applications (TIFPA), Italian National Institute of Nuclear Physics (INFN), Trento, TN, Italy
- Medical Physics Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - Thomas Kröncke
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
| | - Katharina Niepel
- Department of Medical Physics, Faculty of Physics, LMU Munich, Garching, Germany
| | - Jens Ricke
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Franka Risch
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
| | - Bastian Sabel
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Monica Scaringella
- Italian National Institute of Nuclear Physics (INFN), Florence section, Sesto Fiorentino, FI, Italy
| | - Florian Schwarz
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
| | - Francesco Tommasino
- Physics Department, University of Trento, Trento, TN, Italy
- Trento Institute for Fundamental Physics and Applications (TIFPA), Italian National Institute of Nuclear Physics (INFN), Trento, TN, Italy
| | - Guillaume Landry
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Bavarian Cancer Research Centre (BZKF), Munich, Germany
| | - Carlo Civinini
- Italian National Institute of Nuclear Physics (INFN), Florence section, Sesto Fiorentino, FI, Italy
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, LMU Munich, Garching, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
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Tarp IS, Taasti VT, Jensen MF, Vestergaard A, Jensen K. Benefit of range uncertainty reduction in robust optimisation for proton therapy of brain, head-and-neck and breast cancer patients. Phys Imaging Radiat Oncol 2024; 31:100632. [PMID: 39257572 PMCID: PMC11386293 DOI: 10.1016/j.phro.2024.100632] [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: 04/16/2024] [Revised: 08/14/2024] [Accepted: 08/18/2024] [Indexed: 09/12/2024] Open
Abstract
Background and Purpose The primary cause of range uncertainty in proton therapy is inaccuracy in estimating the stopping-power ratio from computed tomography. This study examined the impact on dose-volume metrics by reducing range uncertainty in robust optimisation for a diverse patient cohort and determined the level of range uncertainty that resulted in a relevant reduction in doses to organs-at-risk (OARs). Materials and Methods The effect of reducing range uncertainty on OAR doses was evaluated by robustly optimising six proton plans with varying range uncertainty levels (ranging from 3.5% in the original plan to 1.0%), keeping setup uncertainty fixed. All plans used the initial clinical treatment plan's beam directions and optimisation objectives and were optimised until a clinically acceptable plan was achieved across all setup and range scenarios. The effect of reduced range uncertainty on dose-volume metrics for OARs near the target was evaluated. This study included 30 brain cancer patients, as well as five head-and-neck and five breast cancer patients, investigating the relevance of reducing range uncertainty when different setup uncertainties were used. Results Lowering range uncertainty slightly reduced the nominal dose to surrounding tissue. For body volume receiving 80% of the prescribed dose, reducing range uncertainty from 3.5% to 2.0% resulted in a median decrease of 4 cm3 for the brain, 17 cm3 for head-and-neck, and 27 cm3 for breast cancer patients. Conclusions Reducing range uncertainty in robust optimisation showed a reduction in dose to OARs. The clinical relevance depends on the affected organs and the clinical dose constraints.
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Affiliation(s)
- Ivanka Sojat Tarp
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
| | - Vicki Trier Taasti
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
| | | | - Anne Vestergaard
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
| | - Kenneth Jensen
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
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Koh CWY, Lew KS, Wibawa A, Master Z, Yeap PL, Chua CGA, Lee JCL, Tan HQ, Park SY. First clinical experience following the consensus guide for calibrating a proton stopping power ratio curve in a new proton centre. Phys Med 2024; 120:103341. [PMID: 38554639 DOI: 10.1016/j.ejmp.2024.103341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 03/07/2024] [Accepted: 03/25/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND AND PURPOSE This work introduces the first assessment of CT calibration following the ESTRO's consensus guidelines and validating the HLUT through the irradiation of biological material. METHODS Two electron density phantoms were scanned with two CT scanners using two CT scan energies. The stopping power ratio (SPR) and mass density (MD) HLUTs for different CT scan energies were derived using Schneider's and ESTRO's methods. The comparison metric in this work is based on the Water-Equivalent Thickness (WET) difference between the treatment planning system and biological irradiation measurement. The SPR HLUTs were compared between the two calibration methods. To assess the accuracy of using MD HLUT for dose calculation in the treatment planning system, MD vs SPR HLUT was compared. Lastly, the feasibility of using a single SPR HLUT to replace two different energy CT scans was explored. RESULTS The results show a WET difference of less than 3.5% except for the result in the Bone region between Schneider's and ESTRO's methods. Comparing MD and SPR HLUT, the results from MD HLUT show less than a 3.5% difference except for the Bone region. However, the SPR HLUT shows a lower mean absolute percentage difference as compared to MD HLUT between the measured and calculated WET difference. Lastly, it is possible to use a single SPR HLUT for two different CT scan energies since both WET differences are within 3.5%. CONCLUSION This is the first report on calibrating an HLUT following the ESTRO's guidelines. While our result shows incremental improvement in range uncertainty using the ESTRO's guideline, the prescriptional approach of the guideline does promote harmonization of CT calibration protocols between different centres.
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Affiliation(s)
| | - Kah Seng Lew
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore; Nanyang Technological University Singapore, Singapore
| | - Andrew Wibawa
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore
| | - Zubin Master
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore
| | - Ping Lin Yeap
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore; Department of Oncology, University of Cambridge, United Kingdom
| | | | - James Cheow Lei Lee
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore; Nanyang Technological University Singapore, Singapore
| | - Hong Qi Tan
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore; Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore.
| | - Sung Yong Park
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore; Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore
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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.
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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
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Viar-Hernández D, Vera-Sánchez JA, Schmidt-Santiago L, Rodriguez-Vila B, Lorenzo-Villanueva I, Canals-de-Las-Casas E, Castro-Novais J, Maria Perez-Moreno J, Cerrón-Campoo F, Malpica N, Torrado-Carvajal A, Mazal A. Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study. Phys Med Biol 2024; 69:045018. [PMID: 38237181 DOI: 10.1088/1361-6560/ad2015] [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: 07/16/2023] [Accepted: 01/18/2024] [Indexed: 02/10/2024]
Abstract
We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation. The calibration process involves several steps. First, we tested the ability of MD values to reproduce Hounsfield unit (HU) values of single energy CT (SECT) acquisitions and it was found that the errors were below 1%, validating their use for HU reproduction. Next, the different definitions of computedZvalues were compared and the robustness of the approach based on the materials' composition was confirmed. Finally, the calibration method was compared with a previous method by Bourqueet al, providing a similar level of accuracy and superior performance in terms of precision. Overall, this novel DECT calibration method offers improved accuracy and reliability in determining tissue-specific physical properties. The resulting maps can be valuable for proton therapy treatments, where precise dose calculations and accurate tissue differentiation are crucial for optimal treatment planning and delivery.
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Affiliation(s)
- David Viar-Hernández
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| | | | - Lucia Schmidt-Santiago
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| | - Borja Rodriguez-Vila
- Universidad Rey Juan Carlos, Medical Image Analysis and Biometry Laboratory, Madrid, Spain
| | | | | | - Juan Castro-Novais
- Centro de Protonterapia Quironsalud, Servicio de Física Médica, 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
| | - Alejandro Mazal
- Centro de Protonterapia Quironsalud, Servicio de Física Médica, Madrid, Spain
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Broder BA, Aulwes EF, Espy M, Merrill FE, Sidebottom RB, Tupa D, Freeman MS. A TOPAS model for lens-based proton radiography. Biomed Phys Eng Express 2023; 9:065026. [PMID: 37812911 DOI: 10.1088/2057-1976/ad015b] [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: 08/11/2023] [Accepted: 10/09/2023] [Indexed: 10/11/2023]
Abstract
Objective.Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging.Approach.The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230-930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according toβγ,the inverse product of particle relativistic velocity and particle momentum.Main results.Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV.Significance.Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.
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Affiliation(s)
- Brittany A Broder
- The University of Chicago, 5841 South Ellis Avenue, Chicago, IL 60637, United States of America
| | - Ethan F Aulwes
- Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America
| | - Michelle Espy
- Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America
| | - Frank E Merrill
- Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America
| | - Rachel B Sidebottom
- The University of New Mexico, Albuquerque, NM 87131, United States of America
| | - Dale Tupa
- Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America
| | - Matthew S Freeman
- Los Alamos National Laboratory, Los Alamos, NM, 87545, United States of America
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Caron J, Gonzalez G, Pandey PK, Wang S, Prather K, Ahmad S, Xiang L, Chen Y. Single pulse protoacoustic range verification using a clinical synchrocyclotron. Phys Med Biol 2023; 68:10.1088/1361-6560/acb2ae. [PMID: 36634371 PMCID: PMC10567060 DOI: 10.1088/1361-6560/acb2ae] [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: 08/12/2022] [Accepted: 01/12/2023] [Indexed: 01/14/2023]
Abstract
Objective.Proton therapy as the next generation radiation-based cancer therapy offers dominant advantages over conventional radiation therapy due to the utilization of the Bragg peak; however, range uncertainty in beam delivery substantially mitigates the advantages of proton therapy. This work reports using protoacoustic measurements to determine the location of proton Bragg peak deposition within a water phantom in real time during beam delivery.Approach.In protoacoustics, proton beams have a definitive range, depositing a majority of the dose at the Bragg peak; this dose is then converted to heat. The resulting thermoelastic expansion generates a 3D acoustic wave, which can be detected by acoustic detectors to localize the Bragg peak.Main results.Protoacoustic measurements were performed with a synchrocyclotron proton machine over the exhaustive energy range from 45.5 to 227.15 MeV in clinic. It was found that the amplitude of the acoustic waves is proportional to proton dose deposition, and therefore encodes dosimetric information. With the guidance of protoacoustics, each individual proton beam (7 pC/pulse) can be directly visualized with sub-millimeter (<0.7 mm) resolution using single beam pulse for the first time.Significance.The ability to localize the Bragg peak in real-time and obtain acoustic signals proportional to dose within tumors could enable precision proton therapy and hope to progress towardsin vivomeasurements.
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Affiliation(s)
- Joseph Caron
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, United States of America
| | - Gilberto Gonzalez
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, United States of America
| | - Prabodh Kumar Pandey
- Department of Radiological Sciences, University of California at Irvine, Irvine, CA 92697, United States of America
| | - Siqi Wang
- The Department of Biomedical Engineering, University of California, Irvine, CA 92617, United States of America
| | - Kiana Prather
- University of Oklahoma College of Medicine, Oklahoma City, OK, 73104, United States of America
| | - Salahuddin Ahmad
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, United States of America
| | - Liangzhong Xiang
- Department of Radiological Sciences, University of California at Irvine, Irvine, CA 92697, United States of America
- The Department of Biomedical Engineering, University of California, Irvine, CA 92617, United States of America
- Beckman Laser Institute & Medical Clinic, University of California, Irvine, Irvine, CA 92612, United States of America
| | - Yong Chen
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, United States of America
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10
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Yang M, Wohlfahrt P, Shen C, Bouchard H. Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential. Phys Med Biol 2023; 68. [PMID: 36595276 DOI: 10.1088/1361-6560/acabfa] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power (ρs) within patients. Currently, theρsdistribution in a patient is derived from a single-energy CT (SECT) scan acquired for treatment planning by converting CT number expressed in Hounsfield units (HU) of each voxel toρsusing a Hounsfield look-up table (HLUT), also known as the CT calibration curve. HU andρsshare a linear relationship with electron density but differ in their additional dependence on elemental composition through different physical properties, i.e. effective atomic number and mean excitation energy, respectively. Because of that, the HLUT approach is particularly sensitive to differences in elemental composition between real human tissues and tissue surrogates as well as tissue variations within and among individual patients. The use of dual-energy CT (DECT) forρsprediction has been shown to be effective in reducing the uncertainty inρsestimation compared to SECT. The acquisition of CT data over different x-ray spectra yields additional information on the material elemental composition. Recently, multi-energy CT (MECT) has been explored to deduct material-specific information with higher dimensionality, which has the potential to further improve the accuracy ofρsestimation. Even though various DECT and MECT methods have been proposed and evaluated over the years, these approaches are still only scarcely implemented in routine clinical practice. In this topical review, we aim at accelerating this translation process by providing: (1) a comprehensive review of the existing DECT/MECT methods forρsestimation with their respective strengths and weaknesses; (2) a general review of uncertainties associated with DECT/MECT methods; (3) a general review of different aspects related to clinical implementation of DECT/MECT methods; (4) other potential advanced DECT/MECT applications beyondρsestimation.
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Affiliation(s)
- Ming Yang
- The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, 1515 Holcombe Blvd Houston, TX 77030, United States of America
| | - Patrick Wohlfahrt
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Boston, MA 02115, United States of America
| | - Chenyang Shen
- University of Texas Southwestern Medical Center, Department of Radiation Oncology, 2280 Inwood Rd Dallas, TX 75235, United States of America
| | - Hugo Bouchard
- Département de physique, Université de Montréal, Complexe des sciences, 1375 Avenue Thérèse-Lavoie-Roux, Montréal, Québec H2V0B3, Canada.,Centre de recherche du Centre hospitalier de l'Université de Montréal, 900 Rue Saint-Denis, Montréal, Québec, H2X 0A9, Canada.,Département de radio-oncologie, Centre hospitalier de l'Université de Montréal, 1051 Rue Sanguinet, Montréal, Québec H2X 3E4, Canada
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11
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An online adaptive plan library approach for intensity modulated proton therapy for head and neck cancer. Radiother Oncol 2022; 176:68-75. [PMID: 36150418 DOI: 10.1016/j.radonc.2022.09.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 08/25/2022] [Accepted: 09/13/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE In intensity modulated proton therapy (IMPT), the impact of setup errors and anatomical changes is commonly mitigated by robust optimization with population-based setup robustness (SR) settings and offline replanning. In this study we propose and evaluate an alternative approach based on daily plan selection from patient-specific pre-treatment established plan libraries (PLs). Clinical implementation of the PL strategy would be rather straightforward compared to daily online re-planning. MATERIALS AND METHODS For 15 head-and-neck cancer patients, the planning CT was used to generate a PL with 5 plans, robustly optimized for increasing SR: 0, 1, 2, 3, 5 mm, and 3% range robustness. Repeat CTs (rCTs) and realistic setup and range uncertainty distributions were used for simulation of treatment courses for the PL approach, treatments with fixed SR (fSR3) and a trigger-based offline adaptive schedule for 3 mm SR (fSR3OfA). Daily plan selection in the PL approach was based only on recomputed dose to the CTV on the rCT. RESULTS Compared to using fSR3 and fSR3OfA, the risk of xerostomia grade ≥ II & III and dysphagia ≥ grade III were significantly reduced with the PL. For 6/15 patients the risk of xerostomia and/or dysphagia ≥ grade II could be reduced by > 2% by using PL. For the other patients, adherence to target coverage constraints was often improved. fSR3OfA resulted in significantly improved coverage compared to PL for selected patients. CONCLUSION The proposed PL approach resulted in overall reduced NTCPs compared to fSR3 and fSR3OfA at limited cost in target coverage.
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12
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Hu G, Niepel K, Risch F, Kurz C, Würl M, Kröncke T, Schwarz F, Parodi K, Landry G. Assessment of quantitative information for radiation therapy at a first-generation clinical photon-counting computed tomography scanner. Front Oncol 2022; 12:970299. [PMID: 36185297 PMCID: PMC9515409 DOI: 10.3389/fonc.2022.970299] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 08/17/2022] [Indexed: 11/28/2022] Open
Abstract
As one of the latest developments in X-ray computed tomography (CT), photon-counting technology allows spectral detection, demonstrating considerable advantages as compared to conventional CT. In this study, we investigated the use of a first-generation clinical photon-counting computed tomography (PCCT) scanner and estimated proton relative (to water) stopping power (RSP) of tissue-equivalent materials from virtual monoenergetic reconstructions provided by the scanner. A set of calibration and evaluation tissue-equivalent inserts were scanned at 120 kVp. Maps of relative electron density (RED) and effective atomic number (EAN) were estimated from the reconstructed virtual monoenergetic images (VMI) using an approach previously applied to a spectral CT scanner with dual-layer detector technology, which allows direct calculation of RSP using the Bethe-Bloch formula. The accuracy of RED, EAN, and RSP was evaluated by root-mean-square errors (RMSE) averaged over the phantom inserts. The reference RSP values were obtained experimentally using a water column in an ion beam. For RED and EAN, the reference values were calculated based on the mass density and the chemical composition of the inserts. Different combinations of low- and high-energy VMIs were investigated in this study, ranging from 40 to 190 keV. The overall lowest error was achieved using VMIs at 60 and 180 keV, with an RSP accuracy of 1.27% and 0.71% for the calibration and the evaluation phantom, respectively.
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Affiliation(s)
- Guyue Hu
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU), Garching bei München, Germany
- *Correspondence: Guyue Hu,
| | - Katharina Niepel
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU), Garching bei München, Germany
| | - Franka Risch
- Department of Diagnostic and Interventional Radiology, Universitätsklinikum Augsburg, Augsburg, Germany
| | | | - Matthias Würl
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU), Garching bei München, Germany
| | - Thomas Kröncke
- Department of Diagnostic and Interventional Radiology, Universitätsklinikum Augsburg, Augsburg, Germany
| | - Florian Schwarz
- Department of Diagnostic and Interventional Radiology, Universitätsklinikum Augsburg, Augsburg, Germany
- Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU), Garching bei München, Germany
| | - Guillaume Landry
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU), Garching bei München, Germany
- Department of Radiation Oncology, LMU Klinikum, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
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13
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Longarino FK, Tessonnier T, Mein S, Harrabi SB, Debus J, Stiller W, Mairani A. Dual-layer spectral CT for proton, helium, and carbon ion beam therapy planning of brain tumors. J Appl Clin Med Phys 2022; 23:e13465. [PMID: 34724327 PMCID: PMC8803296 DOI: 10.1002/acm2.13465] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 08/23/2021] [Accepted: 10/14/2021] [Indexed: 01/21/2023] Open
Abstract
Pretreatment computed tomography (CT) imaging is an essential component of the particle therapy treatment planning chain. Treatment planning and optimization with charged particles require accurate and precise estimations of ion beam range in tissues, characterized by the stopping power ratio (SPR). Reduction of range uncertainties arising from conventional CT-number-to-SPR conversion based on single-energy CT (SECT) imaging is of importance for improving clinical practice. Here, the application of a novel imaging and computational methodology using dual-layer spectral CT (DLCT) was performed toward refining patient-specific SPR estimates. A workflow for DLCT-based treatment planning was devised to evaluate SPR prediction for proton, helium, and carbon ion beam therapy planning in the brain. DLCT- and SECT-based SPR predictions were compared in homogeneous and heterogeneous anatomical regions. This study included eight patients scanned for diagnostic purposes with a DLCT scanner. For each patient, four different treatment plans were created, simulating tumors in different parts of the brain. For homogeneous anatomical regions, mean SPR differences of about 1% between the DLCT- and SECT-based approaches were found. In plans of heterogeneous anatomies, relative (absolute) proton range shifts of 0.6% (0.4 mm) in the mean and up to 4.4% (2.1 mm) at the distal fall-off were observed. In the investigated cohort, 12% of the evaluated organs-at-risk (OARs) presented differences in mean or maximum dose of more than 0.5 Gy (RBE) and up to 6.8 Gy (RBE) over the entire treatment. Range shifts and dose differences in OARs between DLCT and SECT in helium and carbon ion treatment plans were similar to protons. In the majority of investigated cases (75th percentile), SECT- and DLCT-based range estimations were within 0.6 mm. Nonetheless, the magnitude of patient-specific range deviations between SECT and DLCT was clinically relevant in heterogeneous anatomical sites, suggesting further study in larger, more diverse cohorts. Results indicate that patients with brain tumors may benefit from DLCT-based treatment planning.
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Affiliation(s)
- Friderike K. Longarino
- German Cancer Research Center (DKFZ)Clinical Cooperation Unit Radiation OncologyHeidelbergGermany
- Department of Radiation OncologyHeidelberg University HospitalHeidelbergGermany
- Department of Physics and AstronomyHeidelberg UniversityHeidelbergGermany
| | | | - Stewart Mein
- Department of Radiation OncologyHeidelberg University HospitalHeidelbergGermany
- Heidelberg Ion Beam Therapy Center (HIT)HeidelbergGermany
- German Cancer Research Center (DKFZ)Translational Radiation OncologyHeidelbergGermany
- National Center for Radiation Research in Oncology (NCRO)Heidelberg Institute of Radiation Oncology (HIRO)HeidelbergGermany
- National Center for Tumor Diseases (NCT)HeidelbergGermany
| | - Semi B. Harrabi
- Department of Radiation OncologyHeidelberg University HospitalHeidelbergGermany
- Heidelberg Ion Beam Therapy Center (HIT)HeidelbergGermany
- National Center for Radiation Research in Oncology (NCRO)Heidelberg Institute of Radiation Oncology (HIRO)HeidelbergGermany
- National Center for Tumor Diseases (NCT)HeidelbergGermany
| | - Jürgen Debus
- German Cancer Research Center (DKFZ)Clinical Cooperation Unit Radiation OncologyHeidelbergGermany
- Department of Radiation OncologyHeidelberg University HospitalHeidelbergGermany
- Heidelberg Ion Beam Therapy Center (HIT)HeidelbergGermany
- National Center for Radiation Research in Oncology (NCRO)Heidelberg Institute of Radiation Oncology (HIRO)HeidelbergGermany
- National Center for Tumor Diseases (NCT)HeidelbergGermany
- Partner Site HeidelbergGerman Cancer Consortium (DKTK)HeidelbergGermany
| | - Wolfram Stiller
- Diagnostic and Interventional Radiology (DIR)Heidelberg University HospitalHeidelbergGermany
| | - Andrea Mairani
- Department of Radiation OncologyHeidelberg University HospitalHeidelbergGermany
- Heidelberg Ion Beam Therapy Center (HIT)HeidelbergGermany
- National Center for Tumor Diseases (NCT)HeidelbergGermany
- Medical PhysicsNational Centre of Oncological Hadrontherapy (CNAO)PaviaItaly
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14
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Charyyev S, Wang T, Lei Y, Ghavidel B, Beitler JJ, McDonald M, Curran WJ, Liu T, Zhou J, Yang X. Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy. Br J Radiol 2022; 95:20210644. [PMID: 34709948 PMCID: PMC8722254 DOI: 10.1259/bjr.20210644] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based method to synthesize DECT images from SECT image for proton radiotherapy. METHODS The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model to focus on the difference between DECT images and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 70 head-and-neck cancer patients whose DECT and SECT scans were acquired simultaneously. The model was trained to generate both a high and low energy DECT image based on a SECT image. The generated synthetic low and high DECT images were evaluated against the true DECT images using leave-one-out cross-validation. To evaluate our method in the context of a practical application, we generated SPR maps from synthetic DECT (sDECT) using a dual-energy based stoichiometric method and compared the SPR maps to those generated from DECT. A dosimetric comparison for dose obtained from DECT was performed against that derived from sDECT. RESULTS The mean of mean absolute error, peak signal-to-noise ratio and normalized cross-correlation for the synthetic high and low energy CT images was 36.9 HU, 29.3 dB, 0.96 and 35.8 HU, 29.2 dB, and 0.96, respectively. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square deviation of about 1% with reduced noise level and artifacts than those from original DECT. Dose-volume histogram (DVH) metrics for the clinical target volume agree within 1% between the DECT and sDECT calculated dose. CONCLUSION Our method synthesized accurate DECT images and showed a potential feasibility for proton SPR map generation. ADVANCES IN KNOWLEDGE This study investigated a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.
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Affiliation(s)
- Serdar Charyyev
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Tonghe Wang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Yang Lei
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Beth Ghavidel
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Jonathan J Beitler
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Mark McDonald
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Walter J Curran
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Tian Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Jun Zhou
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA
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15
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Tattenberg S, Madden TM, Gorissen BL, Bortfeld T, Parodi K, Verburg J. Proton range uncertainty reduction benefits for skull base tumors in terms of normal tissue complication probability (NTCP) and healthy tissue doses. Med Phys 2021; 48:5356-5366. [PMID: 34260085 DOI: 10.1002/mp.15097] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 07/04/2021] [Accepted: 07/07/2021] [Indexed: 01/11/2023] Open
Abstract
PURPOSE Proton therapy allows for more conformal dose distributions and lower organ at risk and healthy tissue doses than conventional photon-based radiotherapy, but uncertainties in the proton range currently prevent proton therapy from making full use of these advantages. Numerous developments therefore aim to reduce such range uncertainties. In this work, we quantify the benefits of reductions in range uncertainty for treatments of skull base tumors. METHODS The study encompassed 10 skull base patients with clival tumors. For every patient, six treatment plans robust to setup errors of 2 mm and range errors from 0% to 5% were created. The determined metrics included the brainstem and optic chiasm normal tissue complication probability (NTCP) with the endpoints of necrosis and blindness, respectively, as well as the healthy tissue volume receiving at least 70% of the prescription dose. RESULTS A range uncertainty reduction from the current level of 4% to a potentially achievable level of 1% reduced the probability of brainstem necrosis by up to 1.3 percentage points in the nominal scenario in which neither setup nor range errors occur and by up to 2.9 percentage points in the worst-case scenario. Such a range uncertainty reduction also reduced the optic chiasm NTCP with the endpoint of blindness by up to 0.9 percentage points in the nominal scenario and by up to 2.2 percentage points in the worst-case scenario. The decrease in the healthy tissue volume receiving at least 70% of the prescription dose ranged from -7.8 to 24.1 cc in the nominal scenario and from -3.4 to 38.4 cc in the worst-case scenario. CONCLUSION The benefits quantified as part of this study serve as a guideline of the OAR and healthy tissue dose benefits that range monitoring techniques may be able to achieve. Benefits were observed between all levels of range uncertainty. Even smaller range uncertainty reductions may therefore be beneficial.
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Affiliation(s)
- Sebastian Tattenberg
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching, Germany
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Thomas M Madden
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Bram L Gorissen
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Thomas Bortfeld
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching, Germany
| | - Joost Verburg
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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16
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kV-kV and kV-MV DECT based estimation of proton stopping power ratio - a simulation study. Phys Med 2021; 89:182-192. [PMID: 34390901 DOI: 10.1016/j.ejmp.2021.07.038] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 07/30/2021] [Accepted: 07/31/2021] [Indexed: 12/23/2022] Open
Abstract
PURPOSE This study aims to estimate the proton stopping power ratio (SPR) by using 80-120 kV and 120 kV-6 MV dual-energy CT (DECT) in a fully simulation-based approach for proton therapy dose calculations. METHODS Based on a virtual CT system, a two-step approach is applied to obtain the reference attenuation coefficient for image reconstruction. The effective atomic number (EAN) and electron density ratio (EDR) are estimated from two CT scans. The SPR is estimated using a calibration based on known materials to obtain a piecewise linear relationship between the EAN and the logarithm of the mean excitation energy, lnIm. The calibration phantoms are constructed from reference tissue materials taken from ICRU Report 44. Our approach is evaluated through using the ICRP110 human phantom. The respective influences of noise and beam hardening effects are studied. RESULTS With the beam hardening correction applied, the results of 120 kV-6 MV DECT are comparable to those of 80-120 kV DECT in predicting the EAN, but the former demonstrated a clear improvement in predicting the EDR and SPR. The 120 kV-6 MV DECT is able to predict the SPR within an accuracy of 10% for lung tissue and 5% for pelvis tissue, thereby outperforming the 80-120 kV DECT. CONCLUSIONS The 120 kV-6 MV DECT is less sensitive to noise but more susceptible to beam hardening effects. By applying beam hardening correction, the 120 kV-6 MV DECT can predict the SPR more accurately than the 80-120 kV DECT. To utilize our DECT approach most effectively, high-quality reconstructed images are required.
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17
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Ates O, Hua CH, Zhao L, Shapira N, Yagil Y, Merchant TE, Krasin M. Feasibility of using post-contrast dual-energy CT for pediatric radiation treatment planning and dose calculation. Br J Radiol 2021; 94:20200170. [PMID: 33201728 DOI: 10.1259/bjr.20200170] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES When iodinated contrast is administered during CT simulation, standard practice requires a separate non-contrast CT for dose calculation. The objective of this study is to validate our hypothesis that since iodine affects Hounsfield units (HUs) more than electron density (ED), the information from post-contrast dual-layer CT (DLCT) would be sufficient for accurate dose calculation for both photon and proton therapy. METHODS AND MATERIALS 10 pediatric patients with abdominal tumors underwent DLCT scans before and after iodinated contrast administration for radiotherapy planning. Dose distributions with these DLCT-based methods were compared to those with conventional calibration-curve methods that map HU images to ED and stopping-power ratio (SPR) images. RESULTS For photon plans, conventional and DLCT approaches based on post-contrast scans underestimated the PTV D99 by 0.87 ± 0.70% (p = 0.18) and 0.36 ± 0.31% (p = 0.34), respectively, comparing to their non-contrast optimization plans. Renal iodine concentration was weakly associated with D99 deviation for both conventional (R2 = 0.10) and DLCT (R2 = 0.02) approaches. For proton plans, the clinical target volume D99 errors were 3.67 ± 2.43% (p = 0.0001) and 0.30 ± 0.25% (p = 0.40) for conventional and DLCT approaches, respectively. The proton beam range changed noticeably with the conventional approach. Renal iodine concentration was highly associated with D99 deviation for the conventional approach (R2 = 0.83) but not for DLCT (R2 = 0.007). CONCLUSION Conventional CT with iodine contrast resulted in a large dosimetric error for proton therapy, compared to true non-contrast plans, but the error was less for photon therapy. These errors can be greatly reduced in the case of the proton plans if DLCT is used, raising the possibility of using only a single post-contrast CT for radiotherapy dose calculation, thus reducing the time and imaging dose required. ADVANCES IN KNOWLEDGE This study is the first to compare directly the differences in the calculated dose distributions between pre- and post-contrast CT images generated by single-energy CT and dual-energy CT methods for photon and proton therapy.
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Affiliation(s)
- Ozgur Ates
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Li Zhao
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Nadav Shapira
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.,Global Advanced Technology, Philips Medical Systems, Haifa, Israel
| | - Yoad Yagil
- Global Advanced Technology, Philips Medical Systems, Haifa, Israel
| | - Thomas E Merchant
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Matthew Krasin
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
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18
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Mossahebi S, Sabouri P, Chen H, Mundis M, O'Neil M, Maggi P, Polf JC. Initial Validation of Proton Dose Calculations on SPR Images from DECT in Treatment Planning System. Int J Part Ther 2020; 7:51-61. [PMID: 33274257 PMCID: PMC7707325 DOI: 10.14338/ijpt-xx-000xx.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
PURPOSE To investigate and quantify the potential benefits associated with the use of stopping-power-ratio (SPR) images created from dual-energy computed tomography (DECT) images for proton dose calculation in a clinical proton treatment planning system (TPS). MATERIALS AND METHODS The DECT and single-energy computed tomography (SECT) scans obtained for 26 plastic tissue surrogate plugs were placed individually in a tissue-equivalent plastic phantom. Relative-electron density (ρe) and effective atomic number (Z eff) images were reconstructed from the DECT scans and used to create an SPR image set for each plug. Next, the SPR for each plug was measured in a clinical proton beam for comparison of the calculated values in the SPR images. The SPR images and SECTs were then imported into a clinical TPS, and treatment plans were developed consisting of a single field delivering a 10 × 10 × 10-cm3 spread-out Bragg peak to a clinical target volume that contained the plugs. To verify the accuracy of the TPS dose calculated from the SPR images and SECTs, treatment plans were delivered to the phantom containing each plug, and comparisons of point-dose measurements and 2-dimensional γ-analysis were performed. RESULTS For all 26 plugs considered in this study, SPR values for each plug from the SPR images were within 2% agreement with measurements. Additionally, treatment plans developed with the SPR images agreed with the measured point dose to within 2%, whereas a 3% agreement was observed for SECT-based plans. γ-Index pass rates were > 90% for all SECT plans and > 97% for all SPR image-based plans. CONCLUSION Treatment plans created in a TPS with SPR images obtained from DECT scans are accurate to within guidelines set for validation of clinical treatment plans at our center. The calculated doses from the SPR image-based treatment plans showed better agreement to measured doses than identical plans created with standard SECT scans.
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Affiliation(s)
- Sina Mossahebi
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA
- Maryland Proton Treatment Center, Baltimore, MD, USA
| | - Pouya Sabouri
- Department of Radiation Oncology, Miami Cancer Institute, Miami, FL, USA
| | - Haijian Chen
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA
| | | | | | - Paul Maggi
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA
- Maryland Proton Treatment Center, Baltimore, MD, USA
| | - Jerimy C. Polf
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA
- Maryland Proton Treatment Center, Baltimore, MD, USA
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19
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Rajiah P, Parakh A, Kay F, Baruah D, Kambadakone AR, Leng S. Update on Multienergy CT: Physics, Principles, and Applications. Radiographics 2020; 40:1284-1308. [DOI: 10.1148/rg.2020200038] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Prabhakar Rajiah
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.)
| | - Anushri Parakh
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.)
| | - Fernando Kay
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.)
| | - Dhiraj Baruah
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.)
| | - Avinash R. Kambadakone
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.)
| | - Shuai Leng
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.)
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Harms J, Lei Y, Wang T, McDonald M, Ghavidel B, Stokes W, Curran WJ, Zhou J, Liu T, Yang X. Cone-beam CT-derived relative stopping power map generation via deep learning for proton radiotherapy. Med Phys 2020; 47:4416-4427. [PMID: 32579710 DOI: 10.1002/mp.14347] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 05/17/2020] [Accepted: 06/17/2020] [Indexed: 11/09/2022] Open
Abstract
PURPOSE In intensity-modulated proton therapy (IMPT), protons are used to deliver highly conformal dose distributions, targeting tumors, and sparing organs-at-risk. However, due to uncertainties in both patient setup and relative stopping power (RSP) calculation, margins are added to the treatment volume during treatment planning, leading to higher doses to normal tissues. Cone-beam computed tomography (CBCT) images are taken daily before treatment; however, the poor image quality of CBCT limits the use of these images for online dose calculation. In this work, we use a deep-learning-based method to predict RSP maps from daily CBCT images, allowing for online dose calculation in a step toward adaptive radiation therapy. METHODS Twenty-three head-and-neck cancer patients were simulated using a Siemens TwinBeam dual-energy CT (DECT) scanner. Mixed-energy scans (equivalent to a 120 kVp single-energy CT scan) were converted to RSP maps for treatment planning. Cone-beam computed tomography images were taken on the first day of treatment, and the planning RSP maps were registered to these images. A deep learning network based on a cycle-GAN architecture, relying on a compound loss function designed for structural and contrast preservation, was then trained to create an RSP map from a CBCT image. Leave-one-out and holdout cross validations were used for evaluation, and mean absolute error (MAE), mean error (ME), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were used to quantify the differences between the CT-based and CBCT-based RSP maps. The proposed method was compared to a deformable image registration-based method which was taken as the ground truth and two other deep learning methods. For one patient who underwent resimulation, the new planning RSP maps and CBCT images were used for further evaluation and validation. RESULTS The CBCT-based RSP generation method was evaluated on 23 head-and-neck cancer patients. From leave-one-out testing, the MAE between CT-based and CBCT-based RSP was 0.06 ± 0.01 and the ME was -0.01 ± 0.01. The proposed method statistically outperformed the comparison DL methods in terms of MAE and ME when compared to the planning CT. In terms of dose comparison, the mean gamma passing rate at 3%/3 mm was 94% when three-dimensional (3D) gamma index was calculated per plan and 96% when gamma index was calculated per field. CONCLUSIONS The proposed method provides sufficiently accurate RSP map generation from CBCT images, allowing for evaluation of daily dose based on CBCT and possibly allowing for CBCT-guided adaptive treatment planning for IMPT.
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Affiliation(s)
- Joseph Harms
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Yang Lei
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Tonghe Wang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Mark McDonald
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Beth Ghavidel
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - William Stokes
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Walter J Curran
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Jun Zhou
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Tian Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA
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Wohlfahrt P, Richter C. Status and innovations in pre-treatment CT imaging for proton therapy. Br J Radiol 2020; 93:20190590. [PMID: 31642709 PMCID: PMC7066941 DOI: 10.1259/bjr.20190590] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 10/04/2019] [Accepted: 10/21/2019] [Indexed: 12/19/2022] Open
Abstract
Pre-treatment CT imaging is a topic of growing importance in particle therapy. Improvements in the accuracy of stopping-power prediction are demanded to allow for a dose conformality that is not inferior to state-of-the-art image-guided photon therapy. Although range uncertainty has been kept practically constant over the last decades, recent technological and methodological developments, like the clinical application of dual-energy CT, have been introduced or arise at least on the horizon to improve the accuracy and precision of range prediction. This review gives an overview of the current status, summarizes the innovations in dual-energy CT and its potential impact on the field as well as potential alternative technologies for stopping-power prediction.
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Affiliation(s)
- Patrick Wohlfahrt
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Je E, Lee HHC, Duan X, Li B, Jia X, Yang M. Optimal energy selection for proton stopping-power-ratio estimation using dual-energy CT-based monoenergetic imaging. ACTA ACUST UNITED AC 2019; 64:195015. [DOI: 10.1088/1361-6560/ab3dec] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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23
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Thorwarth D. Imaging science and development in modern high-precision radiotherapy. Phys Imaging Radiat Oncol 2019; 12:63-66. [PMID: 33458297 PMCID: PMC7807660 DOI: 10.1016/j.phro.2019.11.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
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Darne CD, Alsanea F, Robertson DG, Guan F, Pan T, Grosshans D, Beddar S. A proton imaging system using a volumetric liquid scintillator: a preliminary study. Biomed Phys Eng Express 2019; 5:045032. [PMID: 32194988 PMCID: PMC7082085 DOI: 10.1088/2057-1976/ab2e4a] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
With the expansion of proton radiotherapy for cancer treatments, it has become important to explore proton-based imaging technologies to increase the accuracy of proton treatment planning, alignment, and verification. The purpose of this study is to demonstrate the feasibility of using a volumetric liquid scintillator to generate proton radiographs at a clinically relevant energy (180 MeV) using an integrating detector approach. The volumetric scintillator detector is capable of capturing a wide distribution of residual proton beam energies from a single beam irradiation. It has the potential to reduce acquisition time and imaging dose compared to other proton radiography methods. The imaging system design is comprised of a volumetric (20 × 20 × 20 cm3) organic liquid scintillator working as a residual-range detector and a charge-coupled device (CCD) placed along the beams'-eye-view for capturing radiographic projections. The scintillation light produced within the scintillator volume in response to a 3-dimensional distribution of residual proton beam energies is captured by the CCD as a 2-dimensional grayscale image. A light intensity-to-water equivalent thickness (WET) curve provided WET values based on measured light intensities. The imaging properties of the system, including its contrast, signal-to-noise ratio, and spatial resolution (0.19 line-pairs/mm) were determined. WET values for selected Gammex phantom inserts including solid water, acrylic, and cortical bone were calculated from the radiographs with a relative accuracy of -0.82%, 0.91%, and -2.43%, respectively. Image blurring introduced by system optics was accounted for, resulting in sharper image features. Finally, the system's ability to reconstruct proton CT images from radiographic projections was demonstrated using a filtered back-projection algorithm. The WET retrieved from the reconstructed CT slice was within 0.3% of the WET obtained from MC. In this work, the viability of a cumulative approach to proton imaging using a volumetric liquid scintillator detector and at a clinically-relevant energy was demonstrated.
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Affiliation(s)
- Chinmay D Darne
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Fahed Alsanea
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
| | | | - Fada Guan
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Tinsu Pan
- The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - David Grosshans
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sam Beddar
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
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Simard M, Lapointe A, Lalonde A, Bahig H, Bouchard H. The potential of photon-counting CT for quantitative contrast-enhanced imaging in radiotherapy. ACTA ACUST UNITED AC 2019; 64:115020. [DOI: 10.1088/1361-6560/ab1af1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Polf JC, Mille MM, Mossahebi S, Chen H, Maggi P, Chen-Mayer H. Determination of proton stopping power ratio with dual-energy CT in 3D-printed tissue/air cavity surrogates. Med Phys 2019; 46:3245-3253. [PMID: 31081542 DOI: 10.1002/mp.13587] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 05/07/2019] [Accepted: 05/08/2019] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To study the accuracy with which proton stopping power ratio (SPR) can be determined with dual-energy computed tomography (DECT) for small structures and bone-tissue-air interfaces like those found in the head or in the neck. METHODS Hollow cylindrical polylactic acid (PLA) plugs (3 cm diameter, 5 cm height) were 3D printed containing either one or three septa with thicknesses tsepta = 0.8, 1.6, 3.2, and 6.4 mm running along the length of the plug. The cylinders were inserted individually into a tissue-equivalent head phantom (16 cm diameter, 5 cm height). First, DECT scans were obtained using a Siemens SOMATOM Definition Edge CT scanner. Effective atomic number (Zeff ) and electron density (ρe ) images were reconstructed from the DECT to produce SPR-CT images of each plug. Second, independent elemental composition analysis of the PLA plastic was used to determine the Zeff and ρe for calculating the theoretical SPR (SPR-TH) using the Bethe-Bloch equation. Finally, for each plug, a direct measurement of SPR (SPR-DM) was obtained in a clinical proton beam. The values of SPR-CT, SPR-TH, and SPR-DM were compared. RESULTS The SPR-CT for PLA agreed with SPR-DM for tsepta ≥ 3 mm (for CT slice thicknesses of 0.5, 1.0, and 3.0 mm). The density of PLA was found to decrease with thickness when tsepta < 3 mm. As tsepta (and density) decreased, the SPR-CT values also decreased, in good agreement with SPR-DM and SPR-TH. CONCLUSION Overall, the DECT-based SPR-CT was within 3% of SPR-TH and SPR-DM in the high-density gradient regions of the 3D-printed plugs for septa greater than ~ 3mm in thickness.
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Affiliation(s)
- Jerimy C Polf
- Department of Radiation Oncology, University of Maryland School of Medicine, 22 S Green St, Baltimore, MD, 21201, USA
| | - Matthew M Mille
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sina Mossahebi
- Department of Radiation Oncology, University of Maryland School of Medicine, 22 S Green St, Baltimore, MD, 21201, USA
| | - Haijian Chen
- Department of Radiation Oncology, University of Maryland School of Medicine, 22 S Green St, Baltimore, MD, 21201, USA
| | - Paul Maggi
- Department of Radiation Oncology, University of Maryland School of Medicine, 22 S Green St, Baltimore, MD, 21201, USA
| | - Huaiyu Chen-Mayer
- Chemical Process and Nuclear Measurement Group, National Institute of Standards and Technology, Gaithersburg, MD, USA
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Lee HHC, Li B, Duan X, Zhou L, Jia X, Yang M. Systematic analysis of the impact of imaging noise on dual-energy CT-based proton stopping power ratio estimation. Med Phys 2019; 46:2251-2263. [PMID: 30883827 DOI: 10.1002/mp.13493] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 02/25/2019] [Accepted: 03/06/2019] [Indexed: 11/06/2022] Open
Abstract
PURPOSE Dual-energy CT (DECT) has been shown to have a great potential in reducing the uncertainty in proton stopping power ratio (SPR) estimation, when compared to current standard method - the stoichiometric method based on single-energy CT (SECT). However, a few recent studies indicated that imaging noise may have a substantial impact on the performance of the DECT-based approach, especially at a high noise level. The goal of this study is to quantify the uncertainty in SPR and range estimation caused by noise in the DECT-based approach under various conditions. METHODS Two widely referred parametric DECT methods were studied: the Hünemohr-Saito (HS) method and the Bourque method. Both methods were calibrated using Gammex tissue substitute inserts scanned on the Siemens Force DECT scanner. An energy pair of 80 and 150 kVp with a tin filter was chosen to maximize the spectral separation. After calibrating the model with the Gammex phantom, CT numbers were synthesized using the density and elemental composition from ICRU 44 human tissues to be used as a reference, in order to evaluate the impact of noise alone while putting aside other sources of uncertainty. Gaussian noise was introduced to the reference CT numbers and its impact was measured with the difference between estimated SPR and its noiseless reference SPR. The uncertainty caused by noise was divided into two independent categories: shift of the mean SPR and variation of SPR. Their overall impact on range uncertainty was evaluated on homogeneous and heterogeneous tissue samples of various water equivalent path lengths (WEPL). RESULTS Due to the algorithms being nonlinear and/or having hard thresholds in the CT number to SPR mapping, noise in the CT numbers induced a shift in the mean SPR from its noiseless reference SPR. The degree of the mean shift was dependent on the algorithm and tissue type, but its impact on the SPR uncertainty was mostly small compared to the variation. All mean shifts observed in this study were within 0.5% at a noise level of 2%. The ratio of the influence of variation to mean shift was mostly greater than 1, indicating that variation more likely determined the uncertainty caused by noise. Overall, the range uncertainty (95th percentile) caused by noise was within 1.2% and 1.0% for soft and bone tissues, respectively, at 2% noise with 50 voxels. This value can be considered an upper limit as more voxels and lower noise level rapidly decreased the uncertainty. CONCLUSIONS We have systematically evaluated the impact of noise to the DECT-based SPR estimation and identified under various conditions that the variation caused by noise is the dominant uncertainty-contributing component. We conclude that, based on the noise level and tumor depth, it is important to estimate and include the uncertainty due to noise in estimating the overall range uncertainty before implementing a small margin in the range of 1%.
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Affiliation(s)
- Hugh H C Lee
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Bin Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Xinhui Duan
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Linghong Zhou
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, 510515, China
| | - Xun Jia
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Ming Yang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
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Taasti VT, Hansen DC, Michalak GJ, Deisher AJ, Kruse JJ, Muren LP, Petersen JBB, McCollough CH. Theoretical and experimental analysis of photon counting detector CT for proton stopping power prediction. Med Phys 2018; 45:5186-5196. [PMID: 30191573 DOI: 10.1002/mp.13173] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 07/25/2018] [Accepted: 08/31/2018] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Photon counting detectors (PCDs) are being introduced in advanced x-ray computed tomography (CT) scanners. From a single PCD-CT acquisition, multiple images can be reconstructed, each based on only a part of the original x-ray spectrum. In this study, we investigated whether PCD-CT can be used to estimate stopping power ratios (SPRs) for proton therapy treatment planning, both by comparing to other SPR methods proposed for single energy CT (SECT) and dual energy CT (DECT) as well as to experimental measurements. METHODS A previously developed DECT-based SPR estimation method was adapted to PCD-CT data, by adjusting the estimation equations to allow for more energy spectra. The method was calibrated directly on noisy data to increase the robustness toward image noise. The new PCD SPR estimation method was tested in theoretical calculations as well as in an experimental setup, using both four and two energy bin PCD-CT images, and through comparison to two other SPR methods proposed for SECT and DECT. These two methods were also evaluated on PCD-CT images, full spectrum (one-bin) or two-bin images, respectively. In a theoretical framework, we evaluated the effect of patient-specific tissue variations (density and elemental composition) and image noise on the SPR accuracy; the latter effect was assessed by applying three different noise levels (low, medium, and high noise). SPR estimates derived using real PCD-CT images were compared to experimentally measured SPRs in nine organic tissue samples, including fat, muscle, and bone tissues. RESULTS For the theoretical calculations, the root-mean-square error (RMSE) of the SPR estimation was 0.1% for the new PCD method using both two and four energy bins, compared to 0.2% and 0.7% for the DECT- and SECT-based method, respectively. The PCD method was found to be very robust toward CT image noise, with a RMSE of 2.7% when high noise was added to the CT numbers. Introducing tissue variations, the RMSE only increased to 0.5%; even when adding high image noise to the changed tissues, the RMSE stayed within 3.1%. In the experimental measurements, the RMSE over the nine tissue samples was 0.8% when using two energy bins, and 1.0% for the four-bin images. CONCLUSIONS In all tested cases, the new PCD method produced similar or better results than the SECT- and DECT-based methods, showing an overall improvement of the SPR accuracy. This study thus demonstrated that PCD-CT scans will be a qualified candidate for SPR estimations.
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Affiliation(s)
- Vicki T Taasti
- Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - David C Hansen
- Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | | | - Amanda J Deisher
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Jon J Kruse
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Ludvig P Muren
- Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark
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Wohlfahrt P, Troost EGC, Hofmann C, Richter C, Jakobi A. Clinical Feasibility of Single-Source Dual-spiral 4D Dual-Energy CT for Proton Treatment Planning Within the Thoracic Region. Int J Radiat Oncol Biol Phys 2018; 102:830-840. [PMID: 30003998 DOI: 10.1016/j.ijrobp.2018.06.044] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 06/17/2018] [Accepted: 06/27/2018] [Indexed: 11/30/2022]
Abstract
PURPOSE Single-source dual-spiral dual-energy computed tomography (DECT) provides additional patient information but is prone to motion between the 2 consecutively acquired computed tomography (CT) scans. Here, the clinical applicability of dual-spiral time-resolved DECT (4D-DECT) for proton treatment planning within the thoracic region was evaluated. METHODS AND MATERIALS Dual-spiral 4D-DECT scans of 3 patients with lung cancer were acquired. For time-averaged datasets and 4 breathing phases, the geometric conformity of 80 kVp and 140 kVp 4D-DECT scans before image post-processing was assessed by normalized cross correlation (NCC). Additionally, the conformity of the corresponding DECT-derived 58 keV and 79 keV pseudo-monoenergetic CT datasets after image post-processing, including deformable image registration (DIR), was determined. To analyze the reliability of proton dose calculation, clinical (PlanClin) and artificial worst-case (PlanWorstCase, targeting the diaphragm) treatment plans were calculated on 140 kVp and 79 keV datasets and compared with gamma analyses (0.1% dose-difference and 1 mm distance-to-agreement criterion). The applicability of a patient-specific DECT-based prediction of stopping-power ratio (SPR) was investigated and proton range shifts compared with the clinical heuristic CT-number-to-SPR conversion were assessed. Finally, the delineation variability of an experienced radiation oncologist was quantified. RESULTS Dual-spiral 4D-DECT scans without DIR showed a high geometric conformity, with an average NCC ± standard deviation of 98.7% ± 1.0% when including all patient voxels or 88.2% ± 7.8% when considering only lung. DIR improved the conformity, leading to an average NCC of 99.9% ± 0.1% and 99.6% ± 0.5%, respectively. PlanClin dose distributions on 140 kVp and 79 keV datasets were similar, with an average gamma passing rate of 99.9% (99.2%-100%). The worst-case evaluation still revealed high passing rates (99.3% on average, 92.4% as minimum). Clinically relevant mean range shifts of 2.2% ± 1.2% were determined between patient-specific DECT-based SPR prediction and clinical heuristic CT-number-to-SPR conversion. The intra-observer delineation variability was slightly reduced using additional DECT-derived datasets. CONCLUSIONS The 79 keV pseudo-monoenergetic CT datasets can be consistently obtained from dual-spiral 4D-DECT and are applicable for dose calculation. Patient-specific DECT-based SPR prediction performed well and potentially reduces range uncertainty in proton therapy of patients with lung cancer.
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Affiliation(s)
- Patrick Wohlfahrt
- 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.
| | - Esther G C Troost
- 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; National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany; German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, 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, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Annika Jakobi
- 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
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van Elmpt W. Quantitative computed tomography in radiation therapy: A mature technology with a bright future. Phys Imaging Radiat Oncol 2018; 6:12-13. [PMID: 33458382 PMCID: PMC7807762 DOI: 10.1016/j.phro.2018.04.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Wouter van Elmpt
- Department of Radiation Oncology (MAASTRO), GROW – School for Oncology and Developmental Biology, Maastricht University Medical Centre, Dr. Tanslaan 12, NL-6229 ET Maastricht, The Netherlands
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