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Richtsmeier D, Rodesch PA, Iniewski K, Bazalova-Carter M. Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging. Phys Med Biol 2024; 69:055001. [PMID: 38306974 DOI: 10.1088/1361-6560/ad25c8] [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: 03/30/2023] [Accepted: 02/01/2024] [Indexed: 02/04/2024]
Abstract
Objective.Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident x-ray beam. With this, K-edge imaging becomes possible, allowing high atomic number (high-Z) contrast materials to be distinguished and quantified. In this study, we demonstrated that DECT methods can be converted to PCD-CT systems by extending the method of Bourqueet al(2014). We optimized the energy bins of the PCD for this purpose and expanded the capabilities by employing K-edge subtraction imaging to separate a high-atomic number contrast material.Approach.The method decomposes materials into their effective atomic number (Zeff) and electron density relative to water (ρe). The model was calibrated and evaluated using tissue-equivalent materials from the RMI Gammex electron density phantom with knownρevalues and elemental compositions. TheoreticalZeffvalues were found for the appropriate energy ranges using the elemental composition of the materials.Zeffvaried slightly with energy but was considered a systematic error. Anex vivobovine tissue sample was decomposed to evaluate the model further and was injected with gold chloride to demonstrate the separation of a K-edge contrast agent.Main results.The mean root mean squared percent errors on the extractedZeffandρefor PCD-CT were 0.76% and 0.72%, respectively and 1.77% and 1.98% for DECT. The tissue types in theex vivobovine tissue sample were also correctly identified after decomposition. Additionally, gold chloride was separated from theex vivotissue sample with K-edge imaging.Significance.PCD-CT offers the ability to employ DECT material decomposition methods, along with providing additional capabilities such as K-edge imaging.
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Affiliation(s)
- Devon Richtsmeier
- Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada
| | - Pierre-Antoine Rodesch
- Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada
| | - Kris Iniewski
- Redlen Techologies, 1763 Sean Heights, Saanichton, British Columbia V8M 1X6, Canada
| | - Magdalena Bazalova-Carter
- Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2, Canada
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2
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Pettersson E, Thilander-Klang A, Bäck A. Prediction of proton stopping power ratios using dual-energy CT basis material decomposition. Med Phys 2024; 51:881-897. [PMID: 38194501 DOI: 10.1002/mp.16929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 12/04/2023] [Accepted: 12/15/2023] [Indexed: 01/11/2024] Open
Abstract
BACKGROUND Proton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single-energy computed tomography (SECT). Various studies have shown that multi-energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age-related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection-based MECT systems for SPR prediction. PURPOSE To present and evaluate a novel proton SPR prediction method based on MD images from dual-energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy. METHODS A theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non-tissue materials, by minimizing the root-mean-square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD-SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data-fitting. The goodness of fit of the MD-SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head- and an abdomen-sized phantom setup, were acquired with a clinical projection-based fast-kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non-tissue materials in the phantoms, as well as used for input to the MD-SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image-based consecutive scan DECT for the same phantom setups. RESULTS The predicted SPRs of the tissue surrogates were similar for MD-SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non-adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between -0.7% and -1.8%. The SPRs of the non-tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD-SPR images, compared to 6.8% for DirectSPR. CONCLUSIONS The MD-SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non-tissue materials.
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Affiliation(s)
- Erik Pettersson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Therapeutic Radiation Physics, Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anne Thilander-Klang
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Diagnostic Radiation Physics, Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anna Bäck
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Therapeutic Radiation Physics, Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
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Zhu L, Du Y, Peng Y, Xiang X, Wang X. Investigation on the proton range uncertainty with spectral CT-based virtual monoenergetic images. J Appl Clin Med Phys 2023; 24:e14062. [PMID: 37312288 PMCID: PMC10562040 DOI: 10.1002/acm2.14062] [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: 11/08/2022] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/15/2023] Open
Abstract
OBJECTIVE The stopping power ratio (SPR) prediction error will contribute to the range uncertainty of proton therapy. Spectral CT is promising in reducing the uncertainty in SPR estimation. The purpose of this research is to determine the optimal energy pairs of SPR prediction for each tissue and to evaluate the dose distribution and range difference between the spectral CT with the optimal energy pairs method and the single energy CT (SECT) method. METHODS A new method was proposed based on image segmentation to calculate the proton dose with spectral CT images for the head and body phantom. CT number of each organ region were converted to SPR with the optimal energy pairs of each organ. The CT images were segmented into different organ parts with thresholding method. Virtual monoenergetic (VM) images from 70 keV to 140 keV were investigated to determine the optimal energy pairs for each organ based on Gammex 1467 phantom. The beam data of Shanghai Advanced Proton Therapy facility (SAPT) was employed in matRad (an open-source software for radiation treatment planning) for the dose calculation. RESULTS The optimal energy pairs were obtained for each tissue. The dose distribution of two tumor sites (brain and lung) were calculated with the aforementioned optimal energy pairs. The maximum dose deviation between spectral CT and SECT at the target region was 2.57% and 0.84% for the lung tumor and brain tumor respectively. The range difference between spectral and SECT was significant with 1.8411 mm for the lung tumor. γ passing rate was 85.95% and 95.49% for the lung tumor and brain tumor with the criterion 2%/2 mm. CONCLUSIONS This work presents a way to determine the optimal energy pairs for each organ and to calculate the dose distribution based on the more accurate SPR prediction.
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Affiliation(s)
- Libing Zhu
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, PR China
| | - Yi Du
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiotherapy, Peking University Cancer Hospital & Institute, Beijing, PR China
| | - Yahui Peng
- School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, PR China
| | - Xincheng Xiang
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, PR China
| | - Xiangang Wang
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, PR China
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4
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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: 7] [Impact Index Per Article: 7.0] [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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5
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Greffier J, Villani N, Defez D, Dabli D, Si-Mohamed S. Spectral CT imaging: Technical principles of dual-energy CT and multi-energy photon-counting CT. Diagn Interv Imaging 2022; 104:167-177. [PMID: 36414506 DOI: 10.1016/j.diii.2022.11.003] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 11/11/2022] [Indexed: 11/21/2022]
Abstract
Spectral computed tomography (CT) imaging encompasses a unique generation of CT systems based on a simple principle that makes use of the energy-dependent information present in CT images. Over the past two decades this principle has been expanded with the introduction of dual-energy CT systems. The first generation of spectral CT systems, represented either by dual-source or dual-layer technology, opened up a new imaging approach in the radiology community with their ability to overcome the limitations of tissue characterization encountered with conventional CT. Its expansion worldwide can also be considered as an important leverage for the recent groundbreaking technology based on a new chain of detection available on photon counting CT systems, which holds great promise for extending CT towards multi-energy CT imaging. The purpose of this article was to detail the basic principles and techniques of spectral CT with a particular emphasis on the newest technical developments of dual-energy and multi-energy CT systems.
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6
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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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7
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Longarino FK, Kowalewski A, Tessonnier T, Mein S, Ackermann B, Debus J, Mairani A, Stiller W. Potential of a Second-Generation Dual-Layer Spectral CT for Dose Calculation in Particle Therapy Treatment Planning. Front Oncol 2022; 12:853495. [PMID: 35530308 PMCID: PMC9069208 DOI: 10.3389/fonc.2022.853495] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 03/14/2022] [Indexed: 11/20/2022] Open
Abstract
In particle therapy treatment planning, dose calculation is conducted using patient-specific maps of tissue ion stopping power ratio (SPR) to predict beam ranges. Improving patient-specific SPR prediction is therefore essential for accurate dose calculation. In this study, we investigated the use of the Spectral CT 7500, a second-generation dual-layer spectral computed tomography (DLCT) system, as an alternative to conventional single-energy CT (SECT) for patient-specific SPR prediction. This dual-energy CT (DECT)-based method allows for the direct prediction of SPR from quantitative measurements of relative electron density and effective atomic number using the Bethe equation, whereas the conventional SECT-based method consists of indirect image data-based prediction through the conversion of calibrated CT numbers to SPR. The performance of the Spectral CT 7500 in particle therapy treatment planning was characterized by conducting a thorough analysis of its SPR prediction accuracy for both tissue-equivalent materials and common non-tissue implant materials. In both instances, DLCT was found to reduce uncertainty in SPR predictions compared to SECT. Mean deviations of 0.7% and 1.6% from measured SPR values were found for DLCT- and SECT-based predictions, respectively, in tissue-equivalent materials. Furthermore, end-to-end analyses of DLCT-based treatment planning were performed for proton, helium, and carbon ion therapies with anthropomorphic head and pelvic phantoms. 3D gamma analysis was performed with ionization chamber array measurements as the reference. DLCT-predicted dose distributions revealed higher passing rates compared to SECT-predicted dose distributions. In the DLCT-based treatment plans, measured distal-edge evaluation layers were within 1 mm of their predicted positions, demonstrating the accuracy of DLCT-based particle range prediction. This study demonstrated that the use of the Spectral CT 7500 in particle therapy treatment planning may lead to better agreement between planned and delivered dose compared to current clinical SECT systems.
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Affiliation(s)
- Friderike K Longarino
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.,Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Antonia Kowalewski
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.,Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Physics, Simon Fraser University, Burnaby, BC, Canada
| | | | - Stewart Mein
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.,Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Heidelberg Ion Beam Therapy Center (HIT), Heidelberg, Germany.,Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | | | - Jürgen Debus
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.,Heidelberg Ion Beam Therapy Center (HIT), Heidelberg, Germany.,Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,National Center for Tumor Diseases (NCT), Heidelberg, Germany.,German Cancer Consortium (DKTK), Core Center Heidelberg, Heidelberg, Germany
| | - Andrea Mairani
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.,Heidelberg Ion Beam Therapy Center (HIT), Heidelberg, Germany.,National Center for Tumor Diseases (NCT), Heidelberg, Germany.,Medical Physics, National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Wolfram Stiller
- Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Heidelberg, Germany
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8
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Moskvin VP, Pirlepesov F, Yan Y, Ates O, Myers WJ, Uh J, Zhao L, Shapira N, Yagil Y, Merchant TE, Hua CH. Accuracy of stopping power ratio calculation and experimental validation of proton range with dual-layer computed tomography. Acta Oncol 2022; 61:864-868. [PMID: 35502150 DOI: 10.1080/0284186x.2022.2069477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Vadim P. Moskvin
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Fakhriddin Pirlepesov
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Yue Yan
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Ozgur Ates
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - William J. Myers
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA
| | - Jinsoo Uh
- 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
- 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
| | - Chia-ho Hua
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA
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9
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Dedes G, Drosten H, Götz S, Dickmann J, Sarosiek C, Pankuch M, Krah N, Rit S, Bashkirov V, Schulte RW, Johnson RP, Parodi K, DeJongh E, Landry G. Comparative accuracy and resolution assessment of two prototype proton computed tomography scanners. Med Phys 2022; 49:4671-4681. [PMID: 35396739 DOI: 10.1002/mp.15657] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 02/14/2022] [Accepted: 03/07/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Improving the accuracy of relative stopping power (RSP) in proton therapy may allow reducing range margins. Proton computed tomography (pCT) has been shown to provide state-of-the-art RSP accuracy estimation, and various scanner prototypes have recently been built. The different approaches used in scanner design are expected to impact spatial resolution and RSP accuracy. PURPOSE The goal of this study was to perform the first direct comparison, in terms of spatial resolution and RSP accuracy, of two pCT prototype scanners installed at the same facility and by using the same image reconstruction algorithm. METHODS A phantom containing cylindrical inserts of known RSP was scanned at the phase-II pCT prototype of the U.S. pCT collaboration and at the commercially oriented ProtonVDA scanner. Following distance-driven binning filtered backprojection reconstruction, the radial edge spread function of high-density inserts was used to estimate the spatial resolution. RSP accuracy was evaluated by the mean absolute percent error (MAPE) over the inserts. No direct imaging dose estimation was possible, which prevented a comparison of the two scanners in terms of RSP noise. RESULTS In terms of RSP accuracy, both scanners achieved the same MAPE of 0.72% when excluding the porous sinus insert from the evaluation. The ProtonVDA scanner reached a better overall MAPE when all inserts and the body of the phantom were accounted for (0.81%), compared to the phase-II scanner (1.14%). The spatial resolution with the phase-II scanner was found to be 0.61 lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46 lp/mm. CONCLUSIONS The comparison between two prototype pCT scanners operated in the same clinical facility showed that they both fulfill the requirement of an RSP accuracy of about 1%. Their spatial resolution performance reflects the different design choices of either a scanner with full tracking capabilities (phase-II) or of a more compact tracker system which only provides the positions of protons but not their directions (ProtonVDA). This article is protected by copyright. All rights reserved.
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Affiliation(s)
- G Dedes
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching b. München, 85748, Germany
| | - H Drosten
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching b. München, 85748, Germany
| | - S Götz
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching b. München, 85748, Germany
| | - J Dickmann
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching b. München, 85748, Germany
| | - C Sarosiek
- Department of Physics, Northern Illinois University, 1425 W. Lincoln Highway DeKalb, Illinois, IL, 60115, United States of America
| | - M Pankuch
- Northwestern Medicine Chicago Proton Center, 4455 Weaver Parkway, Warrenville, Illinois, IL, 60555, United States of America
| | - N Krah
- University of Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, LYON, F-69373, France
| | - S Rit
- University of Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, LYON, F-69373, France
| | - V Bashkirov
- Division of Biomedical Engineering Sciences, Loma Linda University, Loma Linda, California, CA 92354, United States of America
| | - R W Schulte
- Division of Biomedical Engineering Sciences, Loma Linda University, Loma Linda, California, CA 92354, United States of America
| | - R P Johnson
- Department of Physics, U.C. Santa Cruz, 1156 High Street Santa Cruz, California, CA, 95064, United States of America
| | - K Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching b. München, 85748, Germany
| | - E DeJongh
- ProtonVDA LLC, 1700 Park Street STE 208, Naperville, Illinois, IL, 60563, United States of America
| | - G Landry
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching b. München, 85748, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, 81377, Germany.,German Cancer Consortium (DKTK), Munich, 81377, Germany
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10
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Liu Y, Zhou L, Peng H. Machine learning based oxygen and carbon concentration derivation using dual-energy CT for PET-based dose verification in proton therapy. Med Phys 2022; 49:3347-3360. [PMID: 35246842 DOI: 10.1002/mp.15581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 02/02/2022] [Accepted: 02/20/2022] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Online dose verification based on proton-induced positron emitters requires high accuracy in the assignment of elemental composition (e.g. C and O). We developed a machine learning framework for deriving oxygen and carbon concentration based on dual-energy CT (DECT). METHODS Digital phantoms at the head site were constructed based on single-energy CT (SECT) and stoichiometric calibration. DECT images (80 kVp and 140 kVp) were synthesized using two methods: 1) theoretical CT numbers with Gaussian noise (method 1) and 2) forward/backward image reconstruction with poly-energetic energy spectrum and Poisson noise modeled (method 2). Two architectures of convolutional neural networks, UNet and ResNet, were investigated to map from DECT images to C/O weights. Four cases (UNet-1: Method 1+UNet, ResNet-1: Method 1+ResNet, UNet-2: Method 2+UNet, and ResNet-2: Method 2 +ResNet) were tested for different tissue types and different noise levels. Monte-Carlo simulation was employed to identify the impact of fluctuation in oxygen and carbon concentration on activity/dose distribution. RESULTS When no noise present, all four cases are able to obtain <2% mean absolute errors (MAE) and <4% root mean square error (RMSE). For the worst image quality (e.g. lowest image SNR), the RMSE for O among all tissue types is 3.02% (UNet-1), 4.46% (ResNet-1), 4.38% (UNet-2) and 6.31% (ResNet-2), respectively. For UNet-1 and ResNet-1, the model performed slightly better in terms of RMSE for skeletal tissue than soft tissues. Such trend is not observed for UNet-2 and ResNet-2. With regard to the comparison between UNet and ResNet, different accuracy and noise immunity are observed. The activity profiles exhibit 3-5% difference in terms of mean relative error (MRE) between the ground truth and machine learning outcome. CONCLUSION We explored the feasibility of a machine learning framework to derive elemental concentration of oxygen and carbon based on DECT images. Two machine learning models, UNet and ResNet, are able to utilize spatial correlation and obtain accurate carbon and oxygen concentration. This study lays a foundation for us to apply the proposed approach to clinical DECT images. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yuxiang Liu
- Department of Medical Physics, Wuhan University, Wuhan, 430072, China
| | - Long Zhou
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hao Peng
- Department of Medical Physics, Wuhan University, Wuhan, 430072, China.,ProtonSmart Ltd, Wuhan, 430072, China
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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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Näsmark T, Andersson J. Proton stopping power prediction based on dual-energy CT-generated virtual monoenergetic images. Med Phys 2021; 48:5232-5243. [PMID: 34213768 DOI: 10.1002/mp.15066] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE The purpose of this work was to assess a proof of concept for a novel method for predicting proton stopping power ratios (SPRs) based on a pair of dual-energy CT generated virtual monoenergetic (VM) images. MATERIALS AND METHODS A rapid kV-switching dual-energy CT scanner was used to acquire Gemstone Spectral Imaging (GSI) and 120 kV conventional single-energy CT (SECT) image data of the CIRS 062M phantom. The proposed method was applied to every possible pairing of VM images between 40 and 140 keV to find the optimal energy pairs for SPR prediction in lung tissue, soft tissue, and bone. The predicted SPRs were compared against SPRs predicted from the SECT data using the conventional SECT-based method. The impact of different scan and reconstruction parameters was also investigated. RESULTS The SPR residual root mean square errors (RMSE) yielded by the optimal pairs were 7.2% for lung tissue, 0.4% for soft tissue, and 0.8% for bone. While no direct comparison could be made to other DECT-based methods for SPR prediction, as these methods could not be directly implemented on a fast kV-switching system, the SPR RMSEs for soft tissue and bone in Table 4 are comparable to RMSEs reported in the literature. For the conventional SECT-based method, the SPR RMSEs were 5.9% for lung tissue, 0.9% for soft tissue, and 5.1% for bone. CONCLUSIONS The proposed method is a valid alternative to, and has the potential to improve upon, the conventional SECT-based method for predicting SPRs. The formalism used in the method is applied directly, with no approximations made on our part, and requires neither prior knowledge of the spectra nor calibration with a phantom. This work presents a way of optimizing the proposed method for a specific scanner by determining the optimal energy pairs to use as input and demonstrates the method's robustness to different levels of ASiR-V, reconstruction kernels, and dose levels.
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Affiliation(s)
- Torbjörn Näsmark
- Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden
| | - Jonas Andersson
- Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden
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Yingying L, Zhe Z, Xiaochen W, Xiaomei L, Nan J, Shengjun S. Dual-layer detector spectral CT-a new supplementary method for preoperative evaluation of glioma. Eur J Radiol 2021; 138:109649. [PMID: 33730659 DOI: 10.1016/j.ejrad.2021.109649] [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: 11/13/2020] [Revised: 02/27/2021] [Accepted: 03/09/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To investigate the value of the iodine concentration (IC) measured by dual-layer detector spectral CT (DLDSCT) in evaluating the factors related to the treatment scheme and survival prognosis of patients with glioma. METHODS From 2018 to 2019, we prospectively collected the data of 99 patients with glioma. The degree of CT enhancement and the IC of low grade gliomas (LGGs, II), high grade gliomas (HGGs, III and IV), grade II and III gliomas, were compared. The predictive performance of the degree of CT enhancement and IC was examined via receiver operating characteristic (ROC) analysis. The correlations between IC and Ki-67 labeling index, isocitrate dehydrogenase (IDH) mutation, chromosome 1p/19q deletion status of the tumor were examined. RESULTS Both IC and the degree of CT enhancement of patients with HGG were significantly higher than those of patients with LGG (p < 0.001; χ2 =41.707, p < 0.001); IC had large area under the ROC curve for diagnostic HGG (0.931; 95 % CI: 0.882-0.979; p < 0.001). The IC in the grade III gliomas was significantly higher than that in grade II gliomas (p < 0.001); IC had a large area under the ROC curve for diagnostic grade III gliomas (0.865; 95 % CI: 0.779-0.952; p < 0.001). There was a significant positive correlation between IC and Ki-67 LI (r = 0.679; p < 0.001). CONCLUSIONS The DLDSCT technology can be used as a supplementary method to provide more information for preoperative grading of the gliomas and the prognosis assessment of the patients.
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Affiliation(s)
- Li Yingying
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100024, China
| | - Zhang Zhe
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Wang Xiaochen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 Fanyang Road, Fengtai District, Beijing, 100070, China
| | - Lu Xiaomei
- CT Clinical Science, Philips Healthcare, Shenyang, 110016, China
| | - Ji Nan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China; Advanced Innovation Center for Big Data-Based Precision Medicine, China.
| | - Sun Shengjun
- Department of Neuroradiology, Beijing Neurosurgical Institute, No.119 Fanyang Road, Fengtai District, Beijing, 100070, China.
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Faller FK, Mein S, Ackermann B, Debus J, Stiller W, Mairani A. Pre-clinical evaluation of dual-layer spectral computed tomography-based stopping power prediction for particle therapy planning at the Heidelberg Ion Beam Therapy Center. ACTA ACUST UNITED AC 2020; 65:095007. [DOI: 10.1088/1361-6560/ab735e] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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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: 34] [Impact Index Per Article: 8.5] [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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