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Reymann MP, Vija AH, Maier A. Method for comparison of data driven gating algorithms in emission tomography. Phys Med Biol 2023; 68:185024. [PMID: 37619585 DOI: 10.1088/1361-6560/acf3ce] [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: 04/10/2023] [Accepted: 08/24/2023] [Indexed: 08/26/2023]
Abstract
Objective.Multiple algorithms have been proposed for data driven gating (DDG) in single photon emission computed tomography (SPECT) and have successfully been applied to myocardial perfusion imaging (MPI). Application of DDG to acquisition types other than SPECT MPI has not been demonstrated so far, as limitations and pitfalls of current methods are unknown.Approach.We create a comprehensive set of phantoms simulating the influence of different motion artifacts, view angles, moving objects, contrast, and count levels in SPECT. We perform Monte Carlo simulation of the phantoms, allowing the characterization of DDG algorithms using quantitative metrics derived from the data and evaluate the Center of Light (COL) and Laplacian Eigenmaps methods as sample DDG algorithms.Main results.View angle, object size, count rate density, and contrast influence the accuracy of both DDG methods. Moreover, the ability to extract the respiratory motion in the phantom was shown to correlate with the contrast of the moving feature to the background, the signal to noise ratio, and the noise in the data.Significance.We showed that reporting the average correlation to an external physical reference signal per acquisition is not sufficient to characterize DDG methods. Assessing DDG methods on a view-by-view basis using the simulations and metrics from this work could enable the identification of pitfalls of current methods, and extend their application to acquisitions beyond SPECT MPI.
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Affiliation(s)
- M P Reymann
- Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Siemens Healthcare GmbH, Forchheim, Germany
- Clinic for Nuclear Medicine, University Hospital Erlangen, Germany
| | - A H Vija
- Siemens Medical Solutions USA, Inc., Molecular Imaging, Hoffman Estates, IL, United States of America
| | - A Maier
- Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Lu Z, Chen G, Jiang H, Sun J, Lin KH, Mok GSP. SPECT and CT misregistration reduction in [ 99mTc]Tc-MAA SPECT/CT for precision liver radioembolization treatment planning. Eur J Nucl Med Mol Imaging 2023; 50:2319-2330. [PMID: 36877236 DOI: 10.1007/s00259-023-06149-9] [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: 10/20/2022] [Accepted: 02/12/2023] [Indexed: 03/07/2023]
Abstract
PURPOSE Respiration and body movement induce misregistration between static [99mTc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver ratio (TNR) errors for 90Y radioembolization planning. We aim to alleviate the misregistration between [99mTc]Tc-MAA SPECT and CT using two registration schemes on simulation and clinical data. METHODS In the simulation study, 70 XCAT phantoms were modeled. The SIMIND Monte Carlo program and OS-EM algorithm were used for projection generation and reconstruction, respectively. Low-dose CT (LDCT) at end-inspiration was simulated for attenuation correction (AC), lungs and liver segmentation, while contrast-enhanced CT (CECT) was simulated for tumor and perfused liver segmentation. In the clinical study, 16 patient data including [99mTc]Tc-MAA SPECT/LDCT and CECT with observed SPECT and CT mismatch were analyzed. Two liver-based registration schemes were studied: SPECT registered to LDCT/CECT and vice versa. Mean count density (MCD) of different volumes-of-interest (VOIs), normalized mutual information (NMI), LSF, TNR, and maximum injected activity (MIA) based on the partition model before and after registration were compared. Wilcoxon signed-rank test was performed. RESULTS In the simulation study, compared to before registration, registrations significantly reduced estimation errors of MCD of all VOIs, LSF (Scheme 1: - 100.28%, Scheme 2: - 101.59%), and TNR (Scheme 1: - 7.00%, Scheme 2: - 5.67%), as well as MIA (Scheme 1: - 3.22%, Scheme 2: - 2.40%). In the clinical study, Scheme 1 reduced 33.68% LSF and increased 14.75% TNR, while Scheme 2 reduced 38.88% LSF and increased 6.28% TNR compared to before registration. One patient may change from 90Y radioembolization untreatable to treatable and other patients may change the MIA up to 25% after registration. NMI between SPECT and CT was significantly increased after registrations in both studies. CONCLUSION Registration between static [99mTc]Tc-MAA SPECT and corresponding CTs is feasible to reduce their spatial mismatch and improve dosimetric estimation. The improvement of LSF is larger than TNR. Our method can potentially improve patient selection and personalized treatment planning for liver radioembolization.
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Affiliation(s)
- Zhonglin Lu
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau SAR, China
| | - Gefei Chen
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Han Jiang
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Jingzhang Sun
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Ko-Han Lin
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, 11217, Taiwan.
| | - Greta S P Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau SAR, China.
- Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Science, University of Macau, Taipa, Macau SAR, China.
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Yu Z, Rahman A, Laforest R, Schindler TH, Gropler RJ, Wahl RL, Siegel BA, Jha AK. Need for objective task-based evaluation of deep learning-based denoising methods: A study in the context of myocardial perfusion SPECT. Med Phys 2023; 50:4122-4137. [PMID: 37010001 PMCID: PMC10524194 DOI: 10.1002/mp.16407] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 01/20/2023] [Accepted: 03/01/2023] [Indexed: 04/04/2023] Open
Abstract
BACKGROUND Artificial intelligence-based methods have generated substantial interest in nuclear medicine. An area of significant interest has been the use of deep-learning (DL)-based approaches for denoising images acquired with lower doses, shorter acquisition times, or both. Objective evaluation of these approaches is essential for clinical application. PURPOSE DL-based approaches for denoising nuclear-medicine images have typically been evaluated using fidelity-based figures of merit (FoMs) such as root mean squared error (RMSE) and structural similarity index measure (SSIM). However, these images are acquired for clinical tasks and thus should be evaluated based on their performance in these tasks. Our objectives were to: (1) investigate whether evaluation with these FoMs is consistent with objective clinical-task-based evaluation; (2) provide a theoretical analysis for determining the impact of denoising on signal-detection tasks; and (3) demonstrate the utility of virtual imaging trials (VITs) to evaluate DL-based methods. METHODS A VIT to evaluate a DL-based method for denoising myocardial perfusion SPECT (MPS) images was conducted. To conduct this evaluation study, we followed the recently published best practices for the evaluation of AI algorithms for nuclear medicine (the RELAINCE guidelines). An anthropomorphic patient population modeling clinically relevant variability was simulated. Projection data for this patient population at normal and low-dose count levels (20%, 15%, 10%, 5%) were generated using well-validated Monte Carlo-based simulations. The images were reconstructed using a 3-D ordered-subsets expectation maximization-based approach. Next, the low-dose images were denoised using a commonly used convolutional neural network-based approach. The impact of DL-based denoising was evaluated using both fidelity-based FoMs and area under the receiver operating characteristic curve (AUC), which quantified performance on the clinical task of detecting perfusion defects in MPS images as obtained using a model observer with anthropomorphic channels. We then provide a mathematical treatment to probe the impact of post-processing operations on signal-detection tasks and use this treatment to analyze the findings of this study. RESULTS Based on fidelity-based FoMs, denoising using the considered DL-based method led to significantly superior performance. However, based on ROC analysis, denoising did not improve, and in fact, often degraded detection-task performance. This discordance between fidelity-based FoMs and task-based evaluation was observed at all the low-dose levels and for different cardiac-defect types. Our theoretical analysis revealed that the major reason for this degraded performance was that the denoising method reduced the difference in the means of the reconstructed images and of the channel operator-extracted feature vectors between the defect-absent and defect-present cases. CONCLUSIONS The results show the discrepancy between the evaluation of DL-based methods with fidelity-based metrics versus the evaluation on clinical tasks. This motivates the need for objective task-based evaluation of DL-based denoising approaches. Further, this study shows how VITs provide a mechanism to conduct such evaluations computationally, in a time and resource-efficient setting, and avoid risks such as radiation dose to the patient. Finally, our theoretical treatment reveals insights into the reasons for the limited performance of the denoising approach and may be used to probe the effect of other post-processing operations on signal-detection tasks.
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Affiliation(s)
- Zitong Yu
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ashequr Rahman
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Richard Laforest
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Thomas H. Schindler
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Robert J. Gropler
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Richard L. Wahl
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Barry A. Siegel
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Abhinav K. Jha
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
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Sun J, Jiang H, Du Y, Li CY, Wu TH, Liu YH, Yang BH, Mok GSP. Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT. J Nucl Cardiol 2023; 30:970-985. [PMID: 35982208 DOI: 10.1007/s12350-022-03045-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 06/13/2022] [Indexed: 10/15/2022]
Abstract
BACKGROUND Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN) in projection-domain (cGAN-prj) and reconstruction-domain (cGAN-recon). METHODS Sixty-four noisy SPECT projections were simulated for a population of 100 XCAT phantoms with different anatomical variations and 99mTc-sestamibi distributions. Series of LD projections were obtained by scaling the full dose (FD) count rate to be 1/20 to 1/2 of the original. Twenty patients with 99mTc-sestamibi stress SPECT/CT scans were retrospectively analyzed. For each patient, LD SPECT images (7/10 to 1/10 of FD) were generated from the FD list mode data. All projections were reconstructed by the quantitative OS-EM method. A 3D cGAN was implemented to predict FD images from their corresponding LD images in the projection- and reconstruction-domain. The denoised projections were reconstructed for analysis in various quantitative indices along with cGAN-recon, Gaussian, and Butterworth-filtered images. RESULTS cGAN denoising improves image quality as compared to LD and conventional post-reconstruction filtering. cGAN-prj can further reduce the dose level as compared to cGAN-recon without compromising the image quality. CONCLUSIONS Denoising based on cGAN-prj is superior to cGAN-recon for MP-SPECT.
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Affiliation(s)
- Jingzhang Sun
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau SAR, China
| | - Han Jiang
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau SAR, China
| | - Yu Du
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau SAR, China
| | - Chien-Ying Li
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Tung-Hsin Wu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
| | - Yi-Hwa Liu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Bang-Hung Yang
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC.
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, ROC.
| | - Greta S P Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau SAR, China.
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Du Y, Shang J, Sun J, Wang L, Liu YH, Xu H, Mok GSP. Deep-learning-based estimation of attenuation map improves attenuation correction performance over direct attenuation estimation for myocardial perfusion SPECT. J Nucl Cardiol 2023; 30:1022-1037. [PMID: 36097242 DOI: 10.1007/s12350-022-03092-4] [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: 06/03/2022] [Accepted: 07/31/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Deep learning (DL)-based attenuation correction (AC) is promising to improve myocardial perfusion (MP) SPECT. We aimed to optimize and compare the DL-based direct and indirect AC methods, with and without SPECT and CT mismatch. METHODS One hundred patients with different 99mTc-sestamibi activity distributions and anatomical variations were simulated by a population of XCAT phantoms. Additionally, 34 patients 99mTc-sestamibi stress/rest SPECT/CT scans were retrospectively recruited. Projections were reconstructed by OS-EM method with or without AC. Mismatch between SPECT and CT images was modeled. A 3D conditional generative adversarial network (cGAN) was optimized for two DL-based AC methods: (i) indirect approach, i.e., non-attenuation corrected (NAC) SPECT paired with the corresponding attenuation map for training. The projections were reconstructed with the DL-generated attenuation map for AC; (ii) direct approach, i.e., NAC SPECT paired with the corresponding AC SPECT for training to perform direct AC. RESULTS Mismatch between SPECT and CT degraded DL-based AC performance. The indirect approach is superior to direct approach for various physical and clinical indices, even with mismatch modeled. CONCLUSION DL-based estimation of attenuation map for AC is superior and more robust to direct generation of AC SPECT.
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Affiliation(s)
- Yu Du
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau SAR, China
| | - Jingjie Shang
- Department of Nuclear Medicine and PET/CT-MRI Centre, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Jingzhang Sun
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Lu Wang
- Department of Nuclear Medicine and PET/CT-MRI Centre, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Yi-Hwa Liu
- Department of Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, CT, USA
| | - Hao Xu
- Department of Nuclear Medicine and PET/CT-MRI Centre, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Greta S P Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau SAR, China.
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Salari S, Khorshidi A, Soltani-Nabipour J. Simulation and assessment of 99mTc absorbed dose into internal organs from cardiac perfusion scan. NUCLEAR ENGINEERING AND TECHNOLOGY 2022. [DOI: 10.1016/j.net.2022.08.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Sun J, Du Y, Li C, Wu TH, Yang B, Mok GSP. Pix2Pix generative adversarial network for low dose myocardial perfusion SPECT denoising. Quant Imaging Med Surg 2022; 12:3539-3555. [PMID: 35782241 PMCID: PMC9246746 DOI: 10.21037/qims-21-1042] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 02/18/2022] [Indexed: 11/12/2023]
Abstract
BACKGROUND Myocardial perfusion (MP) SPECT is a well-established method for diagnosing cardiac disease, yet its radiation risk poses safety concern. This study aims to apply and evaluate the use of Pix2Pix generative adversarial network (Pix2Pix GAN) in denoising low dose MP SPECT images. METHODS One hundred male and female patients with different 99mTc-sestamibi activity distributions, organ and body sizes were simulated by a population of digital 4D Extended Cardiac Torso (XCAT) phantoms. Realistic noisy SPECT projections of full dose of 987 MBq injection and 16 min acquisition, and low dose ranged from 1/20 to 1/2 of the full dose, were generated by an analytical projector from the right anterior oblique (RAO) to the left posterior oblique (LPO) positions. Additionally, twenty patients underwent ~1,184 MBq 99mTc-sestamibi stress SPECT/CT scan were also retrospectively recruited for the study. For each patient, low dose SPECT images (7/10 to 1/10 of full dose) were generated from the full dose list mode data. Our Pix2Pix GAN model was trained with full dose and low dose reconstructed SPECT image pairs. Normalized mean square error (NMSE), structural similarity index (SSIM), coefficient of variation (CV), full-width-at-half-maximum (FWHM) and relative defect size differences (RSD) of Pix2Pix GAN processed images were evaluated along with a reference convolutional auto encoder (CAE) network and post-reconstruction filters. RESULTS NMSE values of 0.0233±0.004 vs. 0.0249±0.004 and 0.0313±0.007 vs. 0.0579±0.016 were obtained on 1/2 and 1/20 dose level for Pix2Pix GAN and CAE in the simulation study, while they were 0.0376±0.010 vs. 0.0433±0.010 and 0.0907±0.020 vs. 0.1186±0.025 on 7/10 and 1/10 dose level in the clinical study. Similar results were also obtained from the SSIM, CV, FWHM and RSD values. Overall, the use of Pix2Pix GAN was superior to other denoising methods in all physical indices, particular in the lower dose levels in the simulation and clinical study. CONCLUSIONS The Pix2Pix GAN method is effective to reduce the noise level of low dose MP SPECT. Further studies on clinical performance are warranted to demonstrate its full clinical effectiveness.
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Affiliation(s)
- Jingzhang Sun
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
| | - Yu Du
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, China
| | - ChienYing Li
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei
| | - Tung-Hsin Wu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei
| | - BangHung Yang
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei
| | - Greta S. P. Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
- Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, China
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The Use of Digital Coronary Phantoms for the Validation of Arterial Geometry Reconstruction and Computation of Virtual FFR. FLUIDS 2022. [DOI: 10.3390/fluids7060201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
We present computational fluid dynamics (CFD) results of virtual fractional flow reserve (vFFR) calculations, performed on reconstructed arterial geometries derived from a digital phantom (DP). The latter provides a convenient and parsimonious description of the main vessels of the left and right coronary arterial trees, which, crucially, is CFD-compatible. Using our DP, we investigate the reconstruction error in what we deem to be the most relevant way—by evaluating the change in the computed value of vFFR, which results from varying (within representative clinical bounds) the selection of the virtual angiogram pair (defined by their viewing angles) used to segment the artery, the eccentricity and severity of the stenosis, and thereby, the CFD simulation’s luminal boundary. The DP is used to quantify reconstruction and computed haemodynamic error within the VIRTUheartTM software suite. However, our method and the associated digital phantom tool are readily transferable to equivalent, clinically oriented workflows. While we are able to conclude that error within the VIRTUheartTM workflow is suitably controlled, the principal outcomes of the work reported here are the demonstration and provision of a practical tool along with an exemplar methodology for evaluating error in a coronary segmentation process.
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Sun J, Zhang Q, Du Y, Zhang D, Pretorius PH, King MA, Mok GSP. Dual gating myocardial perfusion SPECT denoising using a conditional generative adversarial network. Med Phys 2022; 49:5093-5106. [DOI: 10.1002/mp.15707] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 04/29/2022] [Accepted: 05/01/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Jingzhang Sun
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
| | - Qi Zhang
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
- Department of Computer and Information Science Faculty of Science and Technology University of Macau Macau SAR China
| | - Yu Du
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
| | - Duo Zhang
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
- Research Center for Healthcare Data Science Zhejiang Lab Hangzhou Zhejiang China
| | - P. Hendrik Pretorius
- Department of Radiology University of Massachusetts Medical School Worcester USA
| | - Michael A. King
- Department of Radiology University of Massachusetts Medical School Worcester USA
| | - Greta S. P. Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
- Center for Cognitive and Brain Sciences Institute of Collaborative Innovation University of Macau Macau SAR China
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Lu Z, Chen G, Lyu Y, Chen Y, Mok GSP. Technical Note: Respiratory impacts on static and respiratory gated 99m Tc-MAA SPECT/CT for liver radioembolization- A simulation study. Med Phys 2022; 49:5330-5339. [PMID: 35446448 DOI: 10.1002/mp.15682] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 03/25/2022] [Accepted: 04/12/2022] [Indexed: 11/06/2022] Open
Abstract
PURPOSE We aimed to evaluate respiratory impacts on static and respiratory gated (RG) 99m Tc-MAA SPECT in terms of respiratory motion (RM) blur, attenuation correction (AC) and volume-of-interest (VOI) segmentation on lung shunt faction (LSF) and tumor-to-normal liver ratio (TNR) estimation for liver radioembolization therapy planning. METHODS The XCAT phantom was used to simulate a population of 300 phantoms, modelling various anatomical variations, tumor characteristics, respiratory motion amplitudes, LSFs and TNRs. One hundred and twenty noisy projections of average activity maps near end-expiration (End-EX) and whole respiratory cycle were simulated analytically, modeling attenuation and geometric collimator-detector-response (GCDR). The OS-EM algorithm was employed for reconstruction, modeling AC and GCDR. RM effect was evaluated for static SPECT, while AC and VOI mismatch effects were investigated independently and together for static and RG SPECT utilizing one gate, i.e., End-EX. LSF and TNR errors were measured based on the ground truth. Lesions with different characteristics were also investigated for static and RG SPECT. RESULTS RM overestimates LSF and underestimates TNR. The VOI mismatch caused the largest errors in both RG and static SPECT for LSF and TNR estimation, reaching 160% and -52% correspondingly with extremely mismatched VOIs for RG SPECT, even larger than those for static SPECT. With matched AC and VOIs, RG SPECT has better performance than static SPECT. Larger TNR errors are associated with tumors of smaller sizes and higher TNR for static SPECT. CONCLUSIONS The VOI segmentation mismatch has a stronger impact, followed by RM and AC in static 99m Tc-MAA SPECT/CT. This effect is more pronounced for RG SPECT. When VOI masks are derived from a matched CT, RG SPECT is generally superior to static SPECT for LSF and TNR estimation. The performance of RG SPECT could be worse than static SPECT when a mismatched CT is used for segmentation. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Zhonglin Lu
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Gefei Chen
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Yingqing Lyu
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Yue Chen
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
| | - Greta S P Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.,Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau SAR, China.,Ministry of Education Frontiers Science Center for Precision Oncology, Faculty of Health Science, University of Macau, Taipa, Macau SAR, China
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Rahman MA, Yu Z, Jha AK. Ideal-Observer Computation with anthropomorphic phantoms using Markov chain Monte Carlo. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2022; 2022:10.1109/isbi52829.2022.9761579. [PMID: 36388622 PMCID: PMC9648621 DOI: 10.1109/isbi52829.2022.9761579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
In medical imaging, it is widely recognized that image quality should be objectively evaluated based on performance in clinical tasks. To evaluate performance in signal-detection tasks, the ideal observer (IO) is optimal but also challenging to compute in clinically realistic settings. Markov Chain Monte Carlo (MCMC)-based strategies have demonstrated the ability to compute the IO using pre-computed projections of an anatomical database. To evaluate image quality in clinically realistic scenarios, the observer performance should be measured for a realistic patient distribution. This implies that the anatomical database should also be derived from a realistic population. In this manuscript, we propose to advance the MCMC-based approach towards achieving these goals. We then use the proposed approach to study the effect of anatomical database size on IO computation for the task of detecting perfusion defects in simulated myocardial perfusion SPECT images. Our preliminary results provide evidence that the size of the anatomical database affects the computation of the IO.
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Affiliation(s)
- Md Ashequr Rahman
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Zitong Yu
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Abhinav K Jha
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
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Akhavanallaf A, Fayad H, Salimi Y, Aly A, Kharita H, Al Naemi H, Zaidi H. An update on computational anthropomorphic anatomical models. Digit Health 2022; 8:20552076221111941. [PMID: 35847523 PMCID: PMC9277432 DOI: 10.1177/20552076221111941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/19/2022] [Indexed: 11/15/2022] Open
Abstract
The prevalent availability of high-performance computing coupled with validated
computerized simulation platforms as open-source packages have motivated
progress in the development of realistic anthropomorphic computational models of
the human anatomy. The main application of these advanced tools focused on
imaging physics and computational internal/external radiation dosimetry
research. This paper provides an updated review of state-of-the-art developments
and recent advances in the design of sophisticated computational models of the
human anatomy with a particular focus on their use in radiation dosimetry
calculations. The consolidation of flexible and realistic computational models
with biological data and accurate radiation transport modeling tools enables the
capability to produce dosimetric data reflecting actual setup in clinical
setting. These simulation methodologies and results are helpful resources for
the medical physics and medical imaging communities and are expected to impact
the fields of medical imaging and dosimetry calculations profoundly.
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Affiliation(s)
- Azadeh Akhavanallaf
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
| | - Hadi Fayad
- Hamad Medical Corporation, Doha, Qatar
- Weill Cornell Medicine, Doha, Qatar
| | - Yazdan Salimi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
| | - Antar Aly
- Hamad Medical Corporation, Doha, Qatar
- Weill Cornell Medicine, Doha, Qatar
| | | | - Huda Al Naemi
- Hamad Medical Corporation, Doha, Qatar
- Weill Cornell Medicine, Doha, Qatar
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
- Geneva University Neurocenter, Geneva University, Geneva, Switzerland
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark
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13
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Lu Z, Chen G, Lin KH, Wu TH, Mok GSP. Evaluation of different CT maps for attenuation correction and segmentation in static 99m Tc-MAA SPECT/CT for 90 Y radioembolization treatment planning: A simulation study. Med Phys 2021; 48:3842-3851. [PMID: 34013551 DOI: 10.1002/mp.14991] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 05/04/2021] [Accepted: 05/08/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Conventional 99m Tc-macroaggregated albumin (99m Tc-MAA) planar scintigraphy overestimates lung shunt fraction (LSF) compared to SPECT/CT. However, the respiratory motion artifact due to the temporal mismatch between static SPECT and helical CT (HCT) may compromise the SPECT quantitation accuracy by incorrect attenuation correction (AC) and volume-of-interest (VOI) segmentation. This study aims to evaluate AC and VOI segmentation effects systematically and to propose a CT map for LSF and tumor-to-normal liver ratio (TNR) estimation in static 99m Tc-MAA SPECT/CT. METHODS The 4D XCAT phantom was used to simulate a phantom population of 120 phantoms, modeling 10 different anatomical variations, nine TNRs (2-13.2), nine tumor sizes (2-6.7 cm diameter), eight tumor locations, three axial motion amplitudes of 1, 1.5, and 2 (cm), and four LSFs of 5%, 10%, 15%, and 20%. An analytical projector for low-energy high-resolution parallel-hole collimator was used to simulate 60 noisy projections over 360°, modeling attenuation and geometric collimator-detector response (GCDR). AC and VOI mismatch effects were investigated independently and together, using cine average CT (CACT), HCT at end-inspiration (HCT-IN), mid-respiration (HCT-MID), and end-expiration (HCT-EX) respectively as attenuation and segmentation maps. SPECT images without motion, AC, and VOI errors were also generated as reference. LSF and TNR errors were measured as compared to the ground truth. RESULTS HCT-MID has slightly better performance for AC effect compared with other CT maps in LSF and TNR estimation, while HCT-EX and HCT-MID perform better for VOI effect. For a respiratory motion amplitude of 1.5 cm and a LSF of 5%, the LSF errors are 19.56 ± 4.58%, -6.79 ± 1.74%, 77.29 ± 14.74%, and 111.25 ± 18.29% corresponding to HCT-MID, HCT-EX, HCT-IN, and CACT in static SPECT. The TNR errors are -12.38 ± 6.42%, -20.55 ± 11.25%, -20.89 ± 9.98%, and -22.89 ± 14.38% respectively. HCT-MID has the best performance for LSF estimation for LSF > 10% and TNR estimation, followed by HCT-EX, HCT-IN, and CACT. CONCLUSIONS The HCT-MID is recommended for AC and segmentation to alleviate respiratory artifacts and improve quantitation accuracy in 90 Y radioembolization treatment planning. HCT-EX would also be a recommended choice if HCT-MID is not available.
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Affiliation(s)
- Zhonglin Lu
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau SAR, China
| | - Gefei Chen
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau SAR, China
| | - Kuan-Heng Lin
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Industrial PhD Program of Biomedical Science and Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tung-Hsin Wu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Greta S P Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau SAR, China.,Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Avenida da Universidade, Taipa, Macau SAR, China
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14
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Yu Z, Rahman MA, Schindler T, Laforest R, Jha AK. A physics and learning-based transmission-less attenuation compensation method for SPECT. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2021; 11595. [PMID: 34658480 DOI: 10.1117/12.2582350] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Attenuation compensation (AC) is a pre-requisite for reliable quantification and beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT). Typical AC methods require the availability of an attenuation map, which is obtained using a transmission scan, such as a CT scan. This has several disadvantages such as increased radiation dose, higher costs, and possible misalignment between SPECT and CT scans. Also, often a CT scan is unavailable. In this context, we and others are showing that scattered photons in SPECT contain information to estimate the attenuation distribution. To exploit this observation, we propose a physics and learning-based method that uses the SPECT emission data in the photopeak and scatter windows to perform transmission-less AC in SPECT. The proposed method uses data acquired in the scatter window to reconstruct an initial estimate of the attenuation map using a physics-based approach. A convolutional neural network is then trained to segment this initial estimate into different regions. Pre-defined attenuation coefficients are assigned to these regions, yielding the reconstructed attenuation map, which is then used to reconstruct the activity distribution using an ordered subsets expectation maximization (OSEM)-based reconstruction approach. We objectively evaluated the performance of this method using highly realistic simulation studies conducted on the clinically relevant task of detecting perfusion defects in myocardial perfusion SPECT. Our results showed no statistically significant differences between the performance achieved using the proposed method and that with the true attenuation maps. Visually, the images reconstructed using the proposed method looked similar to those with the true attenuation map. Overall, these results provide evidence of the capability of the proposed method to perform transmission-less AC and motivate further evaluation.
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Affiliation(s)
- Zitong Yu
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA, 63130
| | - Md Ashequr Rahman
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA, 63130
| | - Thomas Schindler
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63110
| | - Richard Laforest
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63110
| | - Abhinav K Jha
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA, 63130.,Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63110
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15
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Zhang D, Pretorius PH, Ghaly M, Zhang Q, King MA, Mok GSP. Evaluation of different respiratory gating schemes for cardiac SPECT. J Nucl Cardiol 2020; 27:634-647. [PMID: 30088195 DOI: 10.1007/s12350-018-1392-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 07/17/2018] [Indexed: 11/26/2022]
Abstract
BACKGROUND Respiratory gating reduces motion blurring in cardiac SPECT. Here we aim to evaluate the performance of three respiratory gating strategies using a population of digital phantoms with known truth and clinical data. METHODS We analytically simulated 60 projections for 10 XCAT phantoms with 99mTc-sestamibi distributions using three gating schemes: equal amplitude gating (AG), equal count gating (CG), and equal time gating (TG). Clinical list-mode data for 10 patients who underwent 99mTc-sestamibi scans were also processed using the 3 gating schemes. Reconstructed images in each gate were registered to a reference gate, averaged and reoriented to generate the polar plots. For simulations, image noise, relative difference (RD) of averaged count for each of the 17 segment, and relative defect size difference (RSD) were analyzed. For clinical data, image intensity profile and FWHM were measured across the left ventricle wall. RESULTS For simulations, AG and CG methods showed significantly lower RD and RSD compared to TG, while noise variation was more non-uniform through different gates for AG. In the clinical study, AG and CG had smaller FWHM than TG. CONCLUSIONS AG and CG methods show better performance for motion reduction and are recommended for clinical respiratory gating SPECT implementation.
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Affiliation(s)
- Duo Zhang
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
- Department of Radiology, University of Massachusetts Medical School, Worcester, USA
| | - P Hendrik Pretorius
- Department of Radiology, University of Massachusetts Medical School, Worcester, USA
| | - Michael Ghaly
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- Radiopharmaceutical Imaging and Dosimetry (RAPID), LLC, Baltimore, MD, USA
| | - Qi Zhang
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - Michael A King
- Department of Radiology, University of Massachusetts Medical School, Worcester, USA
| | - Greta S P Mok
- Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.
- Department of Radiology, University of Massachusetts Medical School, Worcester, USA.
- Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China.
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16
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Zhang Q, Zhang D, Mok GSP. Comparison of Different Attenuation Correction Methods for Dual Gating Myocardial Perfusion SPECT/CT. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2019. [DOI: 10.1109/trpms.2019.2899066] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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17
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Zhang D, Ghaly M, Mok GSP. InterpolatedCTfor attenuation correction on respiratory gating cardiacSPECT/CT— A simulation study. Med Phys 2019; 46:2621-2628. [DOI: 10.1002/mp.13513] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 03/07/2019] [Accepted: 03/18/2019] [Indexed: 11/12/2022] Open
Affiliation(s)
- Duo Zhang
- Biomedical Imaging Laboratory (BIG) Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
| | - Michael Ghaly
- Russell H Morgan Department of Radiology and Radiological Science Johns Hopkins University Baltimore MD USA
- Radiopharmaceutical Imaging and Dosimetry (RAPID), LLC Baltimore MD USA
| | - Greta S. P. Mok
- Biomedical Imaging Laboratory (BIG) Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China
- Faculty of Health Sciences University of Macau Macau SAR China
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18
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Abstract
Cardiac SPECT continues to play a critical role in detecting and managing cardiovascular disease, in particularly coronary artery disease (CAD) (Jaarsma et al 2012 J. Am. Coll. Cardiol. 59 1719-28), (Agostini et al 2016 Eur. J. Nucl. Med. Mol. Imaging 43 2423-32). While conventional dual-head SPECT scanners using parallel-hole collimators and scintillation crystals with photomultiplier tubes are still the workhorse of cardiac SPECT, they have the limitations of low photon sensitivity (~130 count s-1 MBq-1), poor image resolution (~15 mm) (Imbert et al 2012 J. Nucl. Med. 53 1897-903), relatively long acquisition time, inefficient use of the detector, high radiation dose, etc. Recently our field observed an exciting growth of new developments of dedicated cardiac scanners and collimators, as well as novel imaging algorithms for quantitative cardiac SPECT. These developments have opened doors to new applications with potential clinical impact, including ultra-low-dose imaging, absolute quantification of myocardial blood flow (MBF) and coronary flow reserve (CFR), multi-radionuclide imaging, and improved image quality as a result of attenuation, scatter, motion, and partial volume corrections (PVCs). In this article, we review the recent advances in cardiac SPECT instrumentation and imaging methods. This review mainly focuses on the most recent developments published since 2012 and points to the future of cardiac SPECT from an imaging physics perspective.
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Affiliation(s)
- Jing Wu
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, United States of America
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19
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Abstract
Myocardial perfusion imaging (MPI) using rest/stress single photon emission computed tomography (SPECT) allows non-invasive assessment of reversible cardiac perfusion defects. Conventionally, reversible defects are identified using a difference image, called reversible map, obtained by subtracting the stress image from the rest image after registration and normalization of the two images. The identification of reversible defects using the conventional subtraction method is however limited by noise. We propose to jointly reconstruct rest and stress projection data to directly obtain the reversible map in a single reconstruction framework to improve the detectability of reversible defects. To evaluate the performance of the proposed method, we performed phantom studies to mimic reversible defects with different levels of severity and doses. As compared to the conventional subtraction method, the joint method yielded reversible maps with much lower noise and improved defect detectability. At a normal clinical dose level, the joint method improved the signal to noise ratio (SNR) of defect contrast in reversible maps from 13.2 to 66.4, 9.7 to 35.0, 6.1 to 13.2, and 3.1 to 6.5, for defect to normal myocardium concentration ratios of 0%, 25%, 50%, and 75%, respectively. The SNRs obtained using the joint method were improved from 6.1 to 13.2, 3.9 to 9.4, 3.0 to 8.0, and 2.1 to 7.1, for 100%, 75%, 50%, and 25% of the normal clinical dose as compared to the conventional subtraction method. To access clinical feasibility, we applied the joint method to a rest/stress SPECT MPI patient study. The joint method yielded a reversible map with much lower noise, translating into a much higher defect detectability as compared to the conventional subtraction method. Our results indicate that the joint method has the potential to improve radiologists' performance for assessing defects in rest/stress SPECT MPI. In addition, the joint method can be used to reduce dose or imaging time.
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Affiliation(s)
- X Lai
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States of America. Department of Radiology, Harvard Medical School, Boston, MA 02115, United States of America
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20
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Elshahaby FEA, Jha AK, Ghaly M, Frey EC. A comparison of resampling schemes for estimating model observer performance with small ensembles. Phys Med Biol 2017; 62:7300-7320. [PMID: 28829044 DOI: 10.1088/1361-6560/aa807a] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
In objective assessment of image quality, an ensemble of images is used to compute the 1st and 2nd order statistics of the data. Often, only a finite number of images is available, leading to the issue of statistical variability in numerical observer performance. Resampling-based strategies can help overcome this issue. In this paper, we compared different combinations of resampling schemes (the leave-one-out (LOO) and the half-train/half-test (HT/HT)) and model observers (the conventional channelized Hotelling observer (CHO), channelized linear discriminant (CLD) and channelized quadratic discriminant). Observer performance was quantified by the area under the ROC curve (AUC). For a binary classification task and for each observer, the AUC value for an ensemble size of 2000 samples per class served as a gold standard for that observer. Results indicated that each observer yielded a different performance depending on the ensemble size and the resampling scheme. For a small ensemble size, the combination [CHO, HT/HT] had more accurate rankings than the combination [CHO, LOO]. Using the LOO scheme, the CLD and CHO had similar performance for large ensembles. However, the CLD outperformed the CHO and gave more accurate rankings for smaller ensembles. As the ensemble size decreased, the performance of the [CHO, LOO] combination seriously deteriorated as opposed to the [CLD, LOO] combination. Thus, it might be desirable to use the CLD with the LOO scheme when smaller ensemble size is available.
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Affiliation(s)
- Fatma E A Elshahaby
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, United States of America. The Russell H Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD 21287, United States of America. Department of Computers and Systems, Electronics Research Institute, Cairo, Egypt
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Li X, Jha AK, Ghaly M, Elshahaby FEA, Links JM, Frey EC. Use of Sub-Ensembles and Multi-Template Observers to Evaluate Detection Task Performance for Data That are Not Multivariate Normal. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:917-929. [PMID: 28026757 PMCID: PMC5496770 DOI: 10.1109/tmi.2016.2643684] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
The Hotelling Observer (HO) is widely used to evaluate image quality in medical imaging. However, applying it to data that are not multivariate-normally (MVN) distributed is not optimal. In this paper, we apply two multi-template linear observer strategies to handle such data. First, the entire data ensemble is divided into sub-ensembles that are exactly or approximately MVN and homoscedastic. Next, a different linear observer template is estimated for and applied to each sub-ensemble. The first multi-template strategy, adapted from previous work, applies the HO to each sub-ensemble, calculates the area under the receiver operating characteristics curve (AUC) for each sub-ensemble, and averages the AUCs from all the sub-ensembles. The second strategy applies the Linear Discriminant (LD) to estimate test statistics for each sub-ensemble and calculates a single global AUC using the pooled test statistics from all the sub-ensembles. We show that this second strategy produces the maximum AUC when only shifting of the HO test statistics is allowed. We compared these strategies to the use of a single HO template for the entire data ensemble by applying them to the non-MVN data obtained from reconstructed images of a realistic simulated population of myocardial perfusion SPECT studies with the goal of optimizing the reconstruction parameters. Of the strategies investigated, the multi-template LD strategy yielded the highest AUC for any given set of reconstruction parameters. The optimal reconstruction parameters obtained by the two multi-template strategies were comparable and produced higher AUCs for each sub-ensemble than the single-template HO strategy.
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22
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Vicente EM, Lodge MA, Rowe SP, Wahl RL, Frey EC. Simplifying volumes-of-interest (VOIs) definition in quantitative SPECT: Beyond manual definition of 3D whole-organ VOIs. Med Phys 2017; 44:1707-1717. [PMID: 28207950 DOI: 10.1002/mp.12164] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 01/23/2017] [Accepted: 02/02/2017] [Indexed: 12/25/2022] Open
Abstract
PURPOSE We investigated the feasibility of using simpler methods than manual whole-organ volume-of-interest (VOI) definition to estimate the organ activity concentration in single photon emission computed tomography (SPECT) in cases where the activity in the organ can be assumed to be uniformly distributed on the scale of the voxel size. In particular, we investigated an anatomic region-of-interest (ROI) defined in a single transaxial slice, and a single sphere placed inside the organ boundaries. METHODS The evaluation was carried out using Monte Carlo simulations based on patient indium 111 In pentetreotide SPECT and computed tomography (CT) images. We modeled constant activity concentrations in each organ, validating this assumption by comparing the distribution of voxel values inside the organ VOIs of the simulated data with the patient data. We simulated projection data corresponding to 100, 50, and 25% of the clinical count level to study the effects of noise level due to shortened acquisition time. Images were reconstructed using a previously validated quantitative SPECT reconstruction method. The evaluation was performed in terms of the accuracy and precision of the activity concentration estimates. RESULTS The results demonstrated that the non-uniform image intensity observed in the reconstructed images in the organs with normal uptake was consistent with uniform activity concentration in the organs on the scale of the voxel size; observed non-uniformities in image intensity were due to a combination of partial-volume effects at the boundaries of the organ, artifacts in the reconstructed image due to collimator-detector response compensation, and noise. Using an ROI defined in a single transaxial slice produced similar biases compared to the three-dimensional (3D) whole-organ VOIs, provided that the transaxial slice was near the central plane of the organ and that the pixels from the organ boundaries were not included in the ROI. Although this slice method was sensitive to noise, biases were less than 10% for all the noise levels studied. The use of spherical VOIs was more sensitive to noise. The method was more accurate for larger spheres and larger organs such as the liver in comparison to the kidneys. Biases lower than 7% were found in the liver when using large enough spheres (radius ≥ 28 mm), regardless of the position, of the VOI inside the organ even with shortened acquisition times. The biases were more position-dependent for smaller organs. CONCLUSIONS Both of the simpler methods provided suitable surrogates in terms of accuracy and precision. The results suggested that a spherical VOI was more appropriate for estimating the activity concentration in larger organs such as the liver, regardless of the position of the sphere inside the organ. Larger spheres resulted in better estimates. A single-slice ROI was more suitable for activity estimation in smaller organs such as the kidneys, providing that the transaxial slice selected was near the central plane of the organ and that voxels from the organ boundaries were excluded. Under those conditions, activity concentrations with biases lower than 5% were observed for all the studied count levels and coefficients of variation were less than 9% and 5% for the 25% and 100% count levels, respectively.
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Affiliation(s)
- Esther M Vicente
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Martin A Lodge
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Steven P Rowe
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric C Frey
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, 21287, USA
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Denisova NV, Terekhov IN. A study of myocardial perfusion SPECT imaging with reduced radiation dose using maximum likelihood and entropy-based maximum
a posteriori
approaches. Biomed Phys Eng Express 2016. [DOI: 10.1088/2057-1976/2/5/055015] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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24
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Ghaly M, Links JM, Frey EC. Collimator optimization and collimator-detector response compensation in myocardial perfusion SPECT using the ideal observer with and without model mismatch and an anthropomorphic model observer. Phys Med Biol 2016; 61:2109-23. [PMID: 26894376 DOI: 10.1088/0031-9155/61/5/2109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The collimator is the primary factor that determines the spatial resolution and noise tradeoff in myocardial perfusion SPECT images. In this paper, the goal was to find the collimator that optimizes the image quality in terms of a perfusion defect detection task. Since the optimal collimator could depend on the level of approximation of the collimator-detector response (CDR) compensation modeled in reconstruction, we performed this optimization for the cases of modeling the full CDR (including geometric, septal penetration and septal scatter responses), the geometric CDR, or no model of the CDR. We evaluated the performance on the detection task using three model observers. Two observers operated on data in the projection domain: the Ideal Observer (IO) and IO with Model-Mismatch (IO-MM). The third observer was an anthropomorphic Channelized Hotelling Observer (CHO), which operated on reconstructed images. The projection-domain observers have the advantage that they are computationally less intensive. The IO has perfect knowledge of the image formation process, i.e. it has a perfect model of the CDR. The IO-MM takes into account the mismatch between the true (complete and accurate) model and an approximate model, e.g. one that might be used in reconstruction. We evaluated the utility of these projection domain observers in optimizing instrumentation parameters. We investigated a family of 8 parallel-hole collimators, spanning a wide range of resolution and sensitivity tradeoffs, using a population of simulated projection (for the IO and IO-MM) and reconstructed (for the CHO) images that included background variability. We simulated anterolateral and inferior perfusion defects with variable extents and severities. The area under the ROC curve was estimated from the IO, IO-MM, and CHO test statistics and served as the figure-of-merit. The optimal collimator for the IO had a resolution of 9-11 mm FWHM at 10 cm, which is poorer resolution than typical collimators used for MPS. When the IO-MM and CHO used a geometric or no model of the CDR, the optimal collimator shifted toward higher resolution than that obtained using the IO and the CHO with full CDR modeling. With the optimal collimator, the IO-MM and CHO using geometric modeling gave similar performance to full CDR modeling. Collimators with poorer resolution were optimal when CDR modeling was used. The agreement of rankings between the IO-MM and CHO confirmed that the IO-MM is useful for optimization tasks when model mismatch is present due to its substantially reduced computational burden compared to the CHO.
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Affiliation(s)
- Michael Ghaly
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21287, USA
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Ghaly M, Du Y, Links JM, Frey EC. Collimator optimization in myocardial perfusion SPECT using the ideal observer and realistic background variability for lesion detection and joint detection and localization tasks. Phys Med Biol 2016; 61:2048-66. [PMID: 26895287 DOI: 10.1088/0031-9155/61/5/2048] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
In SPECT imaging, collimators are a major factor limiting image quality and largely determine the noise and resolution of SPECT images. In this paper, we seek the collimator with the optimal tradeoff between image noise and resolution with respect to performance on two tasks related to myocardial perfusion SPECT: perfusion defect detection and joint detection and localization. We used the Ideal Observer (IO) operating on realistic background-known-statistically (BKS) and signal-known-exactly (SKE) data. The areas under the receiver operating characteristic (ROC) and localization ROC (LROC) curves (AUCd, AUCd+l), respectively, were used as the figures of merit for both tasks. We used a previously developed population of 54 phantoms based on the eXtended Cardiac Torso Phantom (XCAT) that included variations in gender, body size, heart size and subcutaneous adipose tissue level. For each phantom, organ uptakes were varied randomly based on distributions observed in patient data. We simulated perfusion defects at six different locations with extents and severities of 10% and 25%, respectively, which represented challenging but clinically relevant defects. The extent and severity are, respectively, the perfusion defect's fraction of the myocardial volume and reduction of uptake relative to the normal myocardium. Projection data were generated using an analytical projector that modeled attenuation, scatter, and collimator-detector response effects, a 9% energy resolution at 140 keV, and a 4 mm full-width at half maximum (FWHM) intrinsic spatial resolution. We investigated a family of eight parallel-hole collimators that spanned a large range of sensitivity-resolution tradeoffs. For each collimator and defect location, the IO test statistics were computed using a Markov Chain Monte Carlo (MCMC) method for an ensemble of 540 pairs of defect-present and -absent images that included the aforementioned anatomical and uptake variability. Sets of test statistics were computed for both tasks and analyzed using ROC and LROC analysis methodologies. The results of this study suggest that collimators with somewhat poorer resolution and higher sensitivity than those of a typical low-energy high-resolution (LEHR) collimator were optimal for both defect detection and joint detection and localization tasks in myocardial perfusion SPECT for the range of defect sizes investigated. This study also indicates that optimizing instrumentation for a detection task may provide near-optimal performance on the more challenging detection-localization task.
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Affiliation(s)
- Michael Ghaly
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21287, USA
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Elshahaby FEA, Ghaly M, Jha AK, Frey EC. Factors affecting the normality of channel outputs of channelized model observers: an investigation using realistic myocardial perfusion SPECT images. J Med Imaging (Bellingham) 2016; 3:015503. [PMID: 26839913 DOI: 10.1117/1.jmi.3.1.015503] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 12/10/2015] [Indexed: 11/14/2022] Open
Abstract
The channelized Hotelling observer (CHO) uses the first- and second-order statistics of channel outputs under both hypotheses to compute test statistics used in binary classification tasks. If these input data deviate from a multivariate normal (MVN) distribution, the classification performance will be suboptimal compared to an ideal observer operating on the same channel outputs. We conducted a comprehensive investigation to rigorously study the validity of the MVN assumption under various kinds of background and signal variability in a realistic population of phantoms. The study was performed in the context of myocardial perfusion SPECT imaging; anatomical, uptake (intensity), and signal variability were simulated. Quantitative measures and graphical approaches applied to the outputs of each channel were used to investigate the amount and type of deviation from normality. For some types of background and signal variations, the channel outputs, under both hypotheses, were non-normal (i.e., skewed or multimodal). This indicates that, for realistic medical images in cases where there is signal or background variability, the normality of the channel outputs should be evaluated before applying a CHO. Finally, the different degrees of departure from normality of the various channels are explained in terms of violations of the central limit theorem.
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Affiliation(s)
- Fatma E A Elshahaby
- Johns Hopkins University, Whiting School of Engineering, Department of Electrical and Computer Engineering, 3400 North Charles street, Baltimore, Maryland 21218, United States; Johns Hopkins Hospital, Russell H. Morgan Department of Radiology and Radiological Science, 601 North Caroline street, Baltimore, Maryland 21287, United States
| | - Michael Ghaly
- Johns Hopkins Hospital , Russell H. Morgan Department of Radiology and Radiological Science, 601 North Caroline street, Baltimore, Maryland 21287, United States
| | - Abhinav K Jha
- Johns Hopkins Hospital , Russell H. Morgan Department of Radiology and Radiological Science, 601 North Caroline street, Baltimore, Maryland 21287, United States
| | - Eric C Frey
- Johns Hopkins Hospital , Russell H. Morgan Department of Radiology and Radiological Science, 601 North Caroline street, Baltimore, Maryland 21287, United States
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Ghaly M, Links JM, Frey EC. Optimization and comparison of simultaneous and separate acquisition protocols for dual isotope myocardial perfusion SPECT. Phys Med Biol 2015; 60:5083-101. [PMID: 26083239 PMCID: PMC4685479 DOI: 10.1088/0031-9155/60/13/5083] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Dual-isotope simultaneous-acquisition (DISA) rest-stress myocardial perfusion SPECT (MPS) protocols offer a number of advantages over separate acquisition. However, crosstalk contamination due to scatter in the patient and interactions in the collimator degrade image quality. Compensation can reduce the effects of crosstalk, but does not entirely eliminate image degradations. Optimizing acquisition parameters could further reduce the impact of crosstalk. In this paper we investigate the optimization of the rest Tl-201 energy window width and relative injected activities using the ideal observer (IO), a realistic digital phantom population and Monte Carlo (MC) simulated Tc-99m and Tl-201 projections as a means to improve image quality. We compared performance on a perfusion defect detection task for Tl-201 acquisition energy window widths varying from 4 to 40 keV centered at 72 keV for a camera with a 9% energy resolution. We also investigated 7 different relative injected activities, defined as the ratio of Tc-99m and Tl-201 activities, while keeping the total effective dose constant at 13.5 mSv. For each energy window and relative injected activity, we computed the IO test statistics using a Markov chain Monte Carlo (MCMC) method for an ensemble of 1,620 triplets of fixed and reversible defect-present, and defect-absent noisy images modeling realistic background variations. The volume under the 3-class receiver operating characteristic (ROC) surface (VUS) was estimated and served as the figure of merit. For simultaneous acquisition, the IO suggested that relative Tc-to-Tl injected activity ratios of 2.6-5 and acquisition energy window widths of 16-22% were optimal. For separate acquisition, we observed a broad range of optimal relative injected activities from 2.6 to 12.1 and acquisition energy window of widths 16-22%. A negative correlation between Tl-201 injected activity and the width of the Tl-201 energy window was observed in these ranges. The results also suggested that DISA methods could potentially provide image quality as good as that obtained with separate acquisition protocols. We compared observer performance for the optimized protocols and the current clinical protocol using separate acquisition. The current clinical protocols provided better performance at a cost of injecting the patient with approximately double the injected activity of Tc-99m and Tl-201, resulting in substantially increased radiation dose.
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Affiliation(s)
- Michael Ghaly
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jonathan M Links
- Department of Environmental Health Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Eric C Frey
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
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Lee TS, Tsui BMW. The development and initial evaluation of a realistic simulated SPECT dataset with simultaneous respiratory and cardiac motion for gated myocardial perfusion SPECT. Phys Med Biol 2015; 60:1399-413. [PMID: 25612263 DOI: 10.1088/0031-9155/60/4/1399] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
We developed a realistic simulation dataset for simultaneous respiratory and cardiac (R&C) gated SPECT/CT using the 4D NURBS-based Cardiac-Torso (NCAT) Phantom and Monte Carlo simulation methods, and evaluated it for a sample application study. The 4D NCAT phantom included realistic respiratory motion and beating heart motion based on respiratory gated CT and cardiac tagged MRI data of normal human subjects. To model the respiratory motion, a set of 24 separate 3D NCAT phantoms excluding the heart was generated over a respiratory cycle. The beating heart motion was modeled separately with 48 frames per cardiac cycle for each of the 24 respiratory phases. The resultant set of 24 × 48 3D NCAT phantoms provides a realistic model of a normal human subject at different phases of combined R&C motions. An almost noise-free SPECT projection dataset for each of the 1152 3D NCAT phantoms was generated using Monte Carlo simulation techniques and the radioactivity uptake distribution of (99m)Tc sestamibi in different organs. By grouping and summing the separate projection datasets, separate or simultaneous R&C gated acquired data with different gating schemes could be simulated. In the initial evaluation, we combined the projection datasets into ungated, 6 respiratory-gates only, 8 cardiac-gates only, and combined 6 respiratory-gates & 8 cardiac-gates projection datasets. Each dataset was reconstructed using 3D OS-EM without and with attenuation correction using the averaged and respiratory-gated attenuation maps, and the resulting reconstructed images were compared. These results were used to demonstrate the effects of R&C motions and the reduction of image artifact due to R&C motions by gating and attenuation corrections. We concluded that the realistic 4D NCAT phantom and Monte Carlo simulated SPECT projection datasets with R&C motions are powerful tools in the study of the effects of R&C motions, as well as in the development of R&C gating schemes and motion correction methods for improved SPECT/CT imaging.
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Affiliation(s)
- Taek-Soo Lee
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
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Ekjeen T, Tocharoenchai C, Pusuwan P, Fung GSK, Ghaly M, Du Y, Frey EC. Optimization and evaluation of reconstruction-based compensation methods and reconstruction parameters for Tc-99m MIBI parathyroid SPECT. Phys Med 2015; 31:159-66. [PMID: 25555904 DOI: 10.1016/j.ejmp.2014.12.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Revised: 12/16/2014] [Accepted: 12/17/2014] [Indexed: 11/26/2022] Open
Abstract
The value of Tc-99m MIBI parathyroid SPECT for localizing parathyroid hyperplasia in chronic renal failure patients remains inconclusive due to limited image quality. Advanced reconstruction methods to improve image quality have been developed but require optimization and evaluation. The goal of this study was to optimize and evaluate compensation methods and reconstruction parameters for Tc-99m MIBI parathyroid SPECT. A phantom population and projection data that modelled clinically realistic variations found in patients were simulated. The 3D OS-EM reconstruction with compensation for attenuation, detector response and scatter in various combinations were studied. For each compensation, the number of updates for OS-EM and the cutoff frequency of a 3D Butterworth filter were optimized and evaluated using anthropomorphic model observer. With optimal parameters, the method with compensation for attenuation and detector response, with or without the addition of scatter compensation, provided the highest lesion detectability for Tc-99m MIBI parathyroid SPECT.
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Affiliation(s)
- Tawatchai Ekjeen
- Department of Radiological Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand.
| | - Chiraporn Tocharoenchai
- Department of Radiological Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand
| | - Pawana Pusuwan
- Department of Radiology, Siriraj Hospital, Bangkok, Thailand
| | - George S K Fung
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Ghaly
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Yong Du
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Eric C Frey
- The Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
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Ghaly M, Links JM, Frey E. Optimization of energy window and evaluation of scatter compensation methods in myocardial perfusion SPECT using the ideal observer with and without model mismatch and an anthropomorphic model observer. J Med Imaging (Bellingham) 2015; 2:015502. [PMID: 26029730 PMCID: PMC4447606 DOI: 10.1117/1.jmi.2.1.015502] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2014] [Accepted: 02/03/2015] [Indexed: 11/14/2022] Open
Abstract
We used the ideal observer (IO) and IO with model mismatch (IO-MM) applied in the projection domain and an anthropomorphic channelized Hotelling observer (CHO) applied to reconstructed images to optimize the acquisition energy window width and to evaluate various scatter compensation methods in the context of a myocardial perfusion single-photon emission computed tomography (SPECT) defect detection task. The IO has perfect knowledge of the image formation process and thus reflects the performance with perfect compensation for image-degrading factors. Thus, using the IO to optimize imaging systems could lead to suboptimal parameters compared with those optimized for humans interpreting SPECT images reconstructed with imperfect or no compensation. The IO-MM allows incorporating imperfect system models into the IO optimization process. We found that with near-perfect scatter compensation, the optimal energy window for the IO and CHO was similar; in its absence, the IO-MM gave a better prediction of the optimal energy window for the CHO using different scatter compensation methods. These data suggest that the IO-MM may be useful for projectiondomain optimization when MM is significant and that the IO is useful when followed by reconstruction with good models of the image formation process.
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Affiliation(s)
- Michael Ghaly
- Johns Hopkins University, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, United States
| | - Jonathan M. Links
- Johns Hopkins University, Department of Environmental Health Sciences, Baltimore, Maryland, United States
| | - Eric Frey
- Johns Hopkins University, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, United States
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