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Jacobson MW, Lehmann M, Huber P, Wang A, Myronakis M, Shi M, Ferguson D, Valencia-Lozano I, Hu YH, Baturin P, Harris T, Fueglistaller R, Williams C, Morf D, Berbeco R. Abbreviated on-treatment CBCT using roughness penalized mono-energization of kV-MV data and a multi-layer MV imager. Phys Med Biol 2021; 66:10.1088/1361-6560/abddd2. [PMID: 33472189 PMCID: PMC11103584 DOI: 10.1088/1361-6560/abddd2] [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: 05/18/2020] [Accepted: 01/20/2021] [Indexed: 11/11/2022]
Abstract
Simultaneous acquisition of cone beam CT (CBCT) projections using both the kV and MV imagers of an image guided radiotherapy system reduces set-up scan times-a benefit to lung cancer radiation oncology patients-but increases noise in the 3D reconstruction. In this article, we present a kV-MV scan time reduction technique that uses two noise-reducing measures to achieve superior performance. The first is a high-DQE multi-layer MV imager prototype. The second is a beam hardening correction algorithm which combines poly-energetic modeling with edge-preserving, regularized smoothing of the projections. Performance was tested in real acquisitions of the Catphan 604 and a thorax phantom. Percent noise was quantified from voxel values in a soft tissue volume of interest (VOI) while edge blur was quantified from a VOI straddling a boundary between air and soft material. Comparisons in noise/resolution performance trade-off were made between our proposed approach, a dose-equivalent kV-only scan, and a kV-MV reconstruction technique previously published by Yinet al(2005Med. Phys.329). The proposed technique demonstrated lower noise as a function of spatial resolution than the baseline kV-MV method, notably a 50% noise reduction at typical edge blur levels. Our proposed method also exhibited fainter non-uniformity artifacts and in some cases superior contrast. Overall, we find that the combination of a multi-layer MV imager, acquiring at a LINAC source energy of 2.5 MV, and a denoised beam hardening correction algorithm enables noise, resolution, and dose performance comparable to standard kV-imager only set-up CBCT, but with nearly half the gantry rotation time.
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Affiliation(s)
- Matthew W Jacobson
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | | | - Pascal Huber
- Varian Medical Systems, Baden-Dattwil, CH-5405, Switzerland
| | - Adam Wang
- Varian Medical Systems, Palo Alto, CA, 94304-1030, United States of America
| | - Marios Myronakis
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | - Mengying Shi
- Medical Physics Program, Department of Physics and Applied Physics, University of Massachusetts Lowell, Lowell, MA 01854, United States of America
| | - Dianne Ferguson
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | - Ingrid Valencia-Lozano
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | - Yue-Houng Hu
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | - Paul Baturin
- Varian Medical Systems, Palo Alto, CA, 94304-1030, United States of America
| | - Tom Harris
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | | | - Christopher Williams
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
| | - Daniel Morf
- Varian Medical Systems, Baden-Dattwil, CH-5405, Switzerland
| | - Ross Berbeco
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, 02115, United States of America
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Valencia Lozano I, Shi M, Myronakis M, Baturin P, Fueglistaller R, Huber P, Lehmann M, Morf D, Ferguson D, Jacobson MW, Harris T, Berbeco RI, Williams CL. Frequency-dependent optimal weighting approach for megavoltage multilayer imagers. Phys Med Biol 2021; 66. [PMID: 33503603 DOI: 10.1088/1361-6560/abe051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 01/27/2021] [Indexed: 11/12/2022]
Abstract
Multi-layer imaging (MLI) devices improve the detective quantum efficiency (DQE) while maintaining the spatial resolution of conventional mega-voltage (MV) x-ray detectors for applications in radiotherapy. To date, only MLIs with identical detector layers have been explored. However, it may be possible to instead use different scintillation materials in each layer to improve the final image quality. To this end, we developed and validated a method for optimally combining the individual images from each layer of MLI devices that are built with heterogeneous layers. Two configurations were modeled within the GATE Monte Carlo package by stacking different layers of a terbium doped gadolinium oxysulfide Gd2O2S:Tb (GOS) phosphor and a LKH-5 glass scintillator. Detector response was characterized in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE. Spatial frequency-dependent weighting factors were then analytically derived for each layer such that the total DQE of the summed combination image would be maximized across all spatial modes. The final image is obtained as the weighted sum of the sub-images from each layer. Optimal weighting factors that maximize the DQE were found to be the quotient of MTF and NNPS of each layer in the heterogeneous MLI detector. Results validated the improvement of the DQE across the entire frequency domain. For the LKH-5 slab configuration, DQE(0) increases between 2%-3% (absolute), while the corresponding improvement for the LKH-5 pixelated configuration was 7%. The performance of the weighting method was quantitatively evaluated with respect to spatial resolution, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated planar images of phantoms at 2.5 and 6 MV. The line pair phantom acquisition exhibited a twofold increase in CNR and SNR, however MTF was degraded at spatial frequencies greater than 0.2 lp mm-1. For the Las Vegas phantom, the weighting improved the CNR by around 30% depending on the contrast region while the SNR values are higher by a factor of 2.5. These results indicate that the imaging performance of MLI systems can be enhanced using the proposed frequency-dependent weighting scheme. The CNR and SNR of the weighted combined image are improved across all spatial scales independent of the detector combination or photon beam energy.
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Affiliation(s)
- Ingrid Valencia Lozano
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America
| | - Mengying Shi
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.,Department of Physics and Applied Physics, University of Massachusetts Lowell, Lowell, MA, United States of America
| | - Marios Myronakis
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America
| | - Paul Baturin
- Varian Medical Systems, Palo Alto, CA, United States of America
| | | | | | | | | | - Dianne Ferguson
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America
| | - Matthew W Jacobson
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America
| | - Thomas Harris
- Varian Medical Systems, Palo Alto, CA, United States of America
| | - Ross I Berbeco
- Varian Medical Systems, Palo Alto, CA, United States of America
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Shi M, Myronakis M, Jacobson M, Ferguson D, Williams C, Lehmann M, Baturin P, Huber P, Fueglistaller R, Lozano IV, Harris T, Morf D, Berbeco RI. GPU-accelerated Monte Carlo simulation of MV-CBCT. Phys Med Biol 2020; 65:235042. [PMID: 33263311 DOI: 10.1088/1361-6560/abaeba] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Monte Carlo simulation (MCS) is one of the most accurate computation methods for dose calculation and image formation in radiation therapy. However, the high computational complexity and long execution time of MCS limits its broad use. In this paper, we present a novel strategy to accelerate MCS using a graphic processing unit (GPU), and we demonstrate the application in mega-voltage (MV) cone-beam computed tomography (CBCT) simulation. A new framework that generates a series of MV projections from a single simulation run is designed specifically for MV-CBCT acquisition. A Geant4-based GPU code for photon simulation is incorporated into the framework for the simulation of photon transport through a phantom volume. The FastEPID method, which accelerates the simulation of MV images, is modified and integrated into the framework. The proposed GPU-based simulation strategy was tested for its accuracy and efficiency in a Catphan 604 phantom and an anthropomorphic pelvis phantom with beam energies at 2.5 MV, 6 MV, and 6 MV FFF. In all cases, the proposed GPU-based simulation demonstrated great simulation accuracy and excellent agreement with measurement and CPU-based simulation in terms of reconstructed image qualities. The MV-CBCT simulation was accelerated by factors of roughly 900-2300 using an NVIDIA Tesla V100 GPU card against a 2.5 GHz AMD Opteron™ Processor 6380.
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Affiliation(s)
- Mengying Shi
- Medical Physics Program, Department of Physics and Applied Physics, University of Massachusetts Lowell, Lowell, MA, United States of America. Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America
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