Multi-layer imager design for mega-voltage spectral imaging

Myronakis, Marios; Hu, Yue‐Houng; Fueglistaller, Rony; Wang, Adam; Baturin, Paul; Huber, Pascal; Morf, Daniel; Star‐Lack, Josh; Berbeco, R.

doi:10.1088/1361-6560/aabe21

Cited by 6 publications

(8 citation statements)

References 23 publications

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“…However, DE image contrast may be inferior using this approach since the mean energy separation between the two images is small. [79][80][81] More recently, there has been interest in the use of photon counting detectors to provide spectral separation which may be used to remove overlaying bone on kV-projections. [82][83][84][85][86] Furthermore, machine learning approaches, especially deep learning approaches, have been applied to segment kVprojections.…”

Section: F I G U R Ementioning

confidence: 99%

The markerless lung target tracking AAPM Grand Challenge (MATCH) results

et al. 2021

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Purpose: Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology. This knowledge gap motivated the MArkerless lung target Tracking CHallenge (MATCH). The aim was to localize lung targets accurately and precisely in a retrospective in silico study and a prospective experimental study. Methods: MATCH was an American Association of Physicists in Medicine sponsored Grand Challenge. Common materials for the in silico and experimental studies were the experiment setup including an anthropomorphic thorax phantom with two targets within the lungs, and a lung SABR planning protocol. The phantom was moved rigidly with patient-measured lung target motion traces, which also acted as ground truth motion. In the retrospective in silico study a volumetric modulated arc therapy treatment was simulated and a dataset consisting of treatment planning data and intra-treatment kilovoltage (kV) and megavoltage (MV) images for four blinded lung motion traces was provided to the participants. The participants used their MLTT approach to localize the moving target based on the dataset. In the experimental study, the participants received the phantom experiment setup and five patient-measured lung motion traces. The participants used their MLTT approach to localize the moving target during an experimental SABR phantom treatment. The challenge was open to any participant, and participants could complete either one or both parts of the challenge. For both the in silico and experimental studies the MLTT results were

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Section: F I G U R Ementioning

confidence: 99%

The markerless lung target tracking AAPM Grand Challenge (MATCH) results

et al. 2021

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“…47,48 There is no published data on kV CBCT dual-layer detector systems. However, a series of works [49][50][51][52][53][54][55][56][57] have reported the development of multilayer imagers (MLI) for MV CBCT imaging. These works present various aspects such as the 1) framework for analysis and design of MLIs, 50 2) a comprehensive computational model for MLI optimization, 52 3) task specific optimization 53 such as bone separation, 54 and 4) configurations to achieve superresolution imaging 55 and improved image quality by stacking and shifting multiple layers relatively to each other.…”

Section: Dual-layer Detectormentioning

confidence: 99%

Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy

Sajja

Lee

Eriksson

et al. 2020

Advances in Radiation Oncology

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Medical imaging is an indispensable tool in radiotherapy for dose planning, image guidance and treatment monitoring. Cone beam CT (CBCT) is a low dose imaging technique with high spatial resolution capability as a direct by-product of using flat-panel detectors. However, certain issues such as x-ray scatter, beam hardening and other artifacts limit its utility to the verification of patient positioning using image-guided radiotherapy.Methods and Materials: Dual-energy (DE)-CBCT has recently demonstrated promise as an improved tool for tumor visualization in benchtop applications. It has the potential to improve soft-tissue contrast and reduce artifacts caused by beam hardening and metal. In this review, the practical aspects of developing a DE-CBCT based clinical and technical workflow are presented based on existing DE-CBCT literature and concepts adapted from the well-established library of work in DE-CT. Furthermore, the potential applications of DE-CBCT on its future role in radiotherapy are discussed.Results and Conclusions: Based on current literature and an investigation of future applications, there is a clear potential for DE-CBCT technologies to be incorporated into radiotherapy. The applications of DE-CBCT include (but are not limited to): adaptive radiotherapy, brachytherapy, proton therapy, radiomics and theranostics.

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“…[2][3][4] Previously published work with the MLI included quantitative image metric evaluation on planar images, 1,5 theoretical design optimization studies for MVCBCT, [2][3][4] and feasibility and optimization of MV spectral imaging. 6,7 Low-dose MVCBCT has been a goal for image-guided radiotherapy. [8][9][10][11][12][13][14][15] However, MVCBCT with conventional electronic portal imagers (EPIDs) suffers from low image contrast as a result of the higher beam energy used to form the image and the limited detection efficiency of the EPID.…”

Section: Introductionmentioning

confidence: 99%

“…This novel design can benefit task‐specific imaging in radiotherapy such as portal imaging, motion‐tracking, and MV cone‐beam computed tomography (CBCT) by improving image contrast and noise characteristics . Previously published work with the MLI included quantitative image metric evaluation on planar images, theoretical design optimization studies for MVCBCT, and feasibility and optimization of MV spectral imaging …”

Section: Introductionmentioning

confidence: 99%

Low‐dose megavoltage cone‐beam computed tomography using a novel multi‐layer imager (MLI)

et al. 2020

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Purpose: The feasibility of low-dose megavoltage cone-beam acquisition (MVCBCT) using a novel, high detective quantum efficiency (DQE) multi-layer imager (MLI) was investigated. The aim of this work was to reconstruct MVCBCT images using the MLI at different total dose levels, and assess Hounsfield Unit (HU) accuracy, noise and contrast-to-noise ratio (CNR) for low-dose megavoltage cone-beam acquisition. Methods: The MLI has four stacked layers; each layer contains a combination of copper filter/converter, gadolinium oxysulfide (GOS) scintillator and a-Si detector array. In total, 720 projections of a CATPHAN â phantom were acquired over 360°at 2.5, 6, and 6 MV flattening filter free (FFF) beam energies on a Varian TrueBeam LINAC. The dose per projection was 0.01, 0.0167, and 0.05 MU for 2.5, 6, and 6 MV FFF, respectively. MVCBCT images were reconstructed with varying numbers of projections to provide a range of doses for evaluation. Hounsfield Unit uniformity, accuracy, noise and CNR were estimated. Improvements were quantified relative to the standard AS1200 single-layer imager. Results: Average HU uniformity for the MLI reconstructions was within a range of 95%-99% for all of the energies studied. Relative electron density estimation from HU values was within 0.4% AE 1.8% from nominal values. The CNR for MVCBCT based on MLI projections was 2-49 greater than from AS1200 projections. The 2.5 MV beam acquisition with the MLI exhibited the lowest noise and the best balance between CNR and dose for low-dose reconstructions. Conclusions: Megavoltage cone-beam acquisition imaging with a novel MLI prototype mounted on a clinical linear accelerator demonstrated substantial improvement over the standard AS1200 EPID. Further optimization of MVCBCT reconstruction, particularly for 2.5 MV acquisitions, will improve image metrics. Overall, the MLI improves CNR at substantially lower doses than currently required by conventional detectors. This new high DQE detector could provide high-quality MVCBCT at

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Multi-layer imager design for mega-voltage spectral imaging

Cited by 6 publications

References 23 publications

The markerless lung target tracking AAPM Grand Challenge (MATCH) results

The markerless lung target tracking AAPM Grand Challenge (MATCH) results

Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy

Low‐dose megavoltage cone‐beam computed tomography using a novel multi‐layer imager (MLI)

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