1
|
Miller RJH, Shanbhag A, Killekar A, Lemley M, Bednarski B, Kavanagh PB, Feher A, Miller EJ, Bateman T, Builoff V, Liang JX, Newby DE, Dey D, Berman DS, Slomka PJ. AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging. JACC Cardiovasc Imaging 2024; 17:780-791. [PMID: 38456877 PMCID: PMC11222053 DOI: 10.1016/j.jcmg.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/18/2023] [Accepted: 01/04/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Computed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features. OBJECTIVES The authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility. METHODS The authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization. RESULTS In total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR: 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%. CONCLUSIONS AI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging.
Collapse
Affiliation(s)
- Robert J H Miller
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Cardiac Sciences, University of Calgary, Calgary Alberta, Canada
| | - Aakash Shanbhag
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA
| | - Aditya Killekar
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Mark Lemley
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Bryan Bednarski
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Paul B Kavanagh
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Attila Feher
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Edward J Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Timothy Bateman
- Cardiovascular Imaging Technologies LLC, Kansas City, Missouri, USA
| | - Valerie Builoff
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Joanna X Liang
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - David E Newby
- British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Damini Dey
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Daniel S Berman
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Piotr J Slomka
- Department of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA.
| |
Collapse
|
2
|
Miller RJH, Shanbhag A, Killekar A, Lemley M, Bednarski B, Van Kriekinge SD, Kavanagh PB, Feher A, Miller EJ, Einstein AJ, Ruddy TD, Liang JX, Builoff V, Berman DS, Dey D, Slomka PJ. AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging. NPJ Digit Med 2024; 7:24. [PMID: 38310123 PMCID: PMC10838293 DOI: 10.1038/s41746-024-01020-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 01/18/2024] [Indexed: 02/05/2024] Open
Abstract
Epicardial adipose tissue (EAT) volume and attenuation are associated with cardiovascular risk, but manual annotation is time-consuming. We evaluated whether automated deep learning-based EAT measurements from ungated computed tomography (CT) are associated with death or myocardial infarction (MI). We included 8781 patients from 4 sites without known coronary artery disease who underwent hybrid myocardial perfusion imaging. Of those, 500 patients from one site were used for model training and validation, with the remaining patients held out for testing (n = 3511 internal testing, n = 4770 external testing). We modified an existing deep learning model to first identify the cardiac silhouette, then automatically segment EAT based on attenuation thresholds. Deep learning EAT measurements were obtained in <2 s compared to 15 min for expert annotations. There was excellent agreement between EAT attenuation (Spearman correlation 0.90 internal, 0.82 external) and volume (Spearman correlation 0.90 internal, 0.91 external) by deep learning and expert segmentation in all 3 sites (Spearman correlation 0.90-0.98). During median follow-up of 2.7 years (IQR 1.6-4.9), 565 patients experienced death or MI. Elevated EAT volume and attenuation were independently associated with an increased risk of death or MI after adjustment for relevant confounders. Deep learning can automatically measure EAT volume and attenuation from low-dose, ungated CT with excellent correlation with expert annotations, but in a fraction of the time. EAT measurements offer additional prognostic insights within the context of hybrid perfusion imaging.
Collapse
Affiliation(s)
- Robert J H Miller
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | - Aakash Shanbhag
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Aditya Killekar
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Mark Lemley
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Bryan Bednarski
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Serge D Van Kriekinge
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Paul B Kavanagh
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Attila Feher
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Edward J Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Andrew J Einstein
- Division of Cardiology, Department of Medicine, and Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, NY, USA
| | - Terrence D Ruddy
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, ON, Canada
| | - Joanna X Liang
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Valerie Builoff
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Berman
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Damini Dey
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Piotr J Slomka
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| |
Collapse
|
3
|
Usanase N, Uzun B, Ozsahin DU, Ozsahin I. A look at radiation detectors and their applications in medical imaging. Jpn J Radiol 2024; 42:145-157. [PMID: 37733205 DOI: 10.1007/s11604-023-01486-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/28/2023] [Indexed: 09/22/2023]
Abstract
The effectiveness and precision of disease diagnosis and treatment have increased, thanks to developments in clinical imaging over the past few decades. Science is developing and progressing steadily in imaging modalities, and effective outcomes are starting to show up as a result of the shorter scanning periods needed as well as the higher-resolution images generated. The choice of one clinical device over another is influenced by technical disparities among the equipment, such as detection medium, shorter scan time, patient comfort, cost-effectiveness, accessibility, greater sensitivity and specificity, and spatial resolution. Lately, computational algorithms, artificial intelligence (AI), in particular, have been incorporated with diagnostic and treatment techniques, including imaging systems. AI is a discipline comprised of multiple computational and mathematical models. Its applications aided in manipulating sophisticated data in imaging processes and increased imaging tests' accuracy and precision during diagnosis. Computed tomography (CT), positron emission tomography (PET), and Single Photon Emission Computed Tomography (SPECT) along with their corresponding radiation detectors have been reviewed in this study. This review will provide an in-depth explanation of the above-mentioned imaging modalities as well as the radiation detectors that are their essential components. From the early development of these medical instruments till now, various modifications and improvements have been done and more is yet to be established for better performance which calls for a necessity to capture the available information and record the gaps to be filled for better future advances.
Collapse
Affiliation(s)
- Natacha Usanase
- Operational Research Centre in Healthcare, Near East University, Mersin 10, Nicosia, Turkey.
| | - Berna Uzun
- Operational Research Centre in Healthcare, Near East University, Mersin 10, Nicosia, Turkey
- Department of Statistics, Carlos III Madrid University, Getafe, Madrid, Spain
| | - Dilber Uzun Ozsahin
- Operational Research Centre in Healthcare, Near East University, Mersin 10, Nicosia, Turkey
- Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Ilker Ozsahin
- Operational Research Centre in Healthcare, Near East University, Mersin 10, Nicosia, Turkey
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, 10065, USA
| |
Collapse
|
4
|
Huang Y, Zhang H, Hu X, Qin S, Hu F, Li Y, Cai H, Shi K, Yu F. The D-SPECT SH reconstruction protocol: improved quantification of small left ventricle volumes. EJNMMI Phys 2024; 11:5. [PMID: 38190088 PMCID: PMC10774323 DOI: 10.1186/s40658-023-00606-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 12/22/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Due to spatial resolution limitations, conventional NaI-SPECT typically overestimates the left ventricular (LV) ejection fraction (EF) in patients with small LV volumes. The purpose of this study was to explore the clinical application value of the small heart (SH) reconstruction protocol embedded in the postprocessing procedure of D-SPECT. METHODS We retrospectively analyzed patients who undergo both D-SPECT and echocardiography (Echo) within one week. Patients with small LV volume were defined as those with a rest end-systolic volume (rESV) ≤ 25 mL and underwent reconstruction using the standard (SD) reconstruction protocol. The SH protocol was deemed successful in correcting the LVEF value if it decreased by 5% or more compared to the SD protocol. The ROC curve was used to calculate the optimal cutoff value of the SH protocol. LVEF, ESV and EDV were computed with SD and SH, respectively. Echo was performed as a reference, and Echo-LVEF, ESV, and EDV were calculated using the Teichholz formula. One-way ANOVA was used to compare these parameters among the three groups. RESULTS The final study included 209 patients (73.21% female, age 67.34 ± 7.85 years). Compared with the SD protocol, the SH protocol significantly decreased LVEF (67.43 ± 7.38% vs. 71.30 ± 7.61%, p < 0.001). The optimal cutoff value for using the SH protocol was rESV > 17 mL (AUC = 0.651, sensitivity = 78.43%, specificity = 45.57%, p = 0.001). In the subgroup of rESV > 17 mL, there was no significant difference in LVEF (61.84 ± 4.67% vs. 62.83 ± 2.85%, p = 0.481) between the SH protocol and Echo, and no significant difference was observed in rESV (26.92 ± 3.25 mL vs. 27.94 ± 7.96 mL, p = 0.60) between the SH protocol and Echo. CONCLUSION This pilot study demonstrated that the SH reconstruction protocol was able to effectively correct the overestimation of LVEF in patients with small LV volumes. Particularly, in the rESV > 17 mL subgroup, the time and computing power waste could be reduced while still ensuring the accuracy of the LVEF value and image quality.
Collapse
Affiliation(s)
- Yan Huang
- Medical College, Anhui University of Science and Technology, Huainan, China
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Han Zhang
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Yanchang RD.301, Shanghai, 200072, China
| | - Xueping Hu
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Yanchang RD.301, Shanghai, 200072, China
| | - Shanshan Qin
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Yanchang RD.301, Shanghai, 200072, China
| | - Fan Hu
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Yanchang RD.301, Shanghai, 200072, China
| | - Yuchen Li
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Yanchang RD.301, Shanghai, 200072, China
| | - Haidong Cai
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Kuangyu Shi
- Department of Informatics, Technical University of Munich, Munich, Germany
- Department of Nuclear Medicine, University of Bern, Bern, Switzerland
| | - Fei Yu
- Department of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
- Institute of Nuclear Medicine, Tongji University School of Medicine, Yanchang RD.301, Shanghai, 200072, China.
| |
Collapse
|
5
|
Feher A, Pieszko K, Shanbhag A, Lemley M, Miller RJ, Huang C, Miras L, Liu YH, Gerber J, Sinusas AJ, Miller EJ, Slomka PJ. Comparison of the prognostic value between quantification and visual estimation of coronary calcification from attenuation CT in patients undergoing SPECT myocardial perfusion imaging. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:185-193. [PMID: 37845406 DOI: 10.1007/s10554-023-02980-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 09/29/2023] [Indexed: 10/18/2023]
Abstract
We investigated the prognostic utility of visually estimated coronary artery calcification (VECAC) from low dose computed tomography attenuation correction (CTAC) scans obtained during SPECT/CT myocardial perfusion imaging (MPI), and assessed how it compares to coronary artery calcifications (CAC) quantified by calcium score on CTACs (QCAC). From the REFINE SPECT Registry 4,236 patients without prior coronary stenting with SPECT/CT performed at a single center were included (age: 64 ± 12 years, 47% female). VECAC in each coronary artery (left main, left anterior descending, circumflex, and right) were scored separately as 0 (absent), 1 (mild), 2 (moderate), or 3 (severe), yielding a possible score of 0-12 for each patient (overall VECAC grade zero:0, mild:1-2, moderate: 3-5, severe: >5). CAC scoring of CTACs was performed at the REFINE SPECT core lab with dedicated software. VECAC was correlated with categorized QCAC (zero: 0, mild: 1-99, moderate: 100-399, severe: ≥400). A high degree of correlation was observed between VECAC and QCAC, with 73% of VECACs in the same category as QCAC and 98% within one category. There was substantial agreement between VECAC and QCAC (weighted kappa: 0.78 with 95% confidence interval: 0.76-0.79, p < 0.001). During a median follow-up of 25 months, 372 patients (9%) experienced major adverse cardiovascular events (MACE). In survival analysis, both VECAC and QCAC were associated with MACE. The area under the receiver operating characteristic curve for 2-year-MACE was similar for VECAC when compared to QCAC (0.694 versus 0.691, p = 0.70). In conclusion, visual assessment of CAC on low-dose CTAC scans provides good estimation of QCAC in patients undergoing SPECT/CT MPI. Visually assessed CAC has similar prognostic value for MACE in comparison to QCAC.
Collapse
Affiliation(s)
- Attila Feher
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA.
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
| | - Konrad Pieszko
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Aakash Shanbhag
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Mark Lemley
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Robert Jh Miller
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | - Cathleen Huang
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Leonidas Miras
- Division of Cardiology, Bridgeport Hospital, Yale University School of Medicine, Bridgeport, CT, USA
| | - Yi-Hwa Liu
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA
| | - Jamie Gerber
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA
| | - Albert J Sinusas
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Edward J Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, Dana 3, P.O. Box 208017, New Haven, CT, 06520, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Piotr J Slomka
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| |
Collapse
|
6
|
Hedeer F, Akil S, Oddstig J, Hindorf C, Arheden H, Carlsson M, Engblom H. Diagnostic accuracy for CZT gamma camera compared to conventional gamma camera technique with myocardial perfusion single-photon emission computed tomography: Assessment of myocardial infarction and function. J Nucl Cardiol 2023; 30:1935-1946. [PMID: 36913172 PMCID: PMC10558368 DOI: 10.1007/s12350-022-03185-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 11/23/2022] [Indexed: 03/14/2023]
Abstract
BACKGROUND The solid-state cadmium-zinc-telluride (CZT) gamma camera for myocardial perfusion single-photon emission computed tomography (MPS) has theoretical advantages compared to the conventional gamma camera technique. This includes more sensitive detectors and better energy resolution. We aimed to explore the diagnostic performance of gated MPS with a CZT gamma camera compared to a conventional gamma camera for detection of myocardial infarct (MI) and assessment of left ventricular (LV) volumes and ejection fraction (LVEF), using cardiac magnetic resonance (CMR) as the reference method. METHODS Seventy-three patients (26% female) with known or suspected chronic coronary syndrome were examined with gated MPS using both a CZT gamma camera and a conventional gamma camera as well as with CMR. Presence and extent of MI on MPS and late gadolinium enhancement (LGE) CMR was evaluated. For LV volumes, LVEF and LV mass, gated MPS images and cine CMR images were evaluated. RESULTS MI was found in 42 patients on CMR. The overall sensitivity, specificity, positive and negative predictive values for the CZT and the conventional gamma camera were the same (67%, 100%, 100% and 69%). For infarct size > 3% on CMR, the sensitivity was 82% for the CZT and 73% for the conventional gamma camera, respectively. LV volumes were significantly underestimated by MPS compared to CMR (P ≤ .002 for all measures). The underestimation was slightly less pronounced for the CZT compared to the conventional gamma camera (2-10 mL, P ≤ .03 for all measures). For LVEF, however, accuracy was high for both gamma cameras. CONCLUSION Differences between a CZT and a conventional gamma camera for detection of MI and assessment of LV volumes and LVEF are small and do not appear to be clinically significant.
Collapse
Affiliation(s)
- Fredrik Hedeer
- Department of Clinical Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Shahnaz Akil
- Department of Clinical Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Jenny Oddstig
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Cecilia Hindorf
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Håkan Arheden
- Department of Clinical Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Marcus Carlsson
- Department of Clinical Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Henrik Engblom
- Department of Clinical Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| |
Collapse
|
7
|
Sohlberg A, Kangasmaa T, Tikkakoski A. Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT. Biomed Phys Eng Express 2023; 9:065007. [PMID: 37666231 DOI: 10.1088/2057-1976/acf66c] [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: 06/28/2023] [Accepted: 09/04/2023] [Indexed: 09/06/2023]
Abstract
Objective. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the studies and in the worst case lead to erroneous diagnosis. Deep learning (DL)-based methods can be used to improve the quality of the low count studies. DL can be applied in several different methods, which might affect the outcome. The aim of this study was to investigate the differences between post reconstruction- and reconstruction-based denoising methods.Approach. A UNET-type network was trained using ordered subsets expectation maximization (OSEM) reconstructed MPS studies acquired with half, quarter and eighth of full-activity. The trained network was applied as a post reconstruction denoiser (OSEM+DL) and it was incorporated into a regularized reconstruction algorithm as a deep learning penalty (DLP). OSEM+DL and DLP were compared against each other and against OSEM images without DL denoising in terms of noise level, myocardium-ventricle contrast and defect detection performance with signal-to-noise ratio of a non-prewhitening matched filter (NPWMF-SNR) applied to artificial perfusion defects inserted into defect-free clinical MPS scans. Comparisons were made using half-, quarter- and eighth-activity data.Main results. OSEM+DL provided lower noise level at all activities than other methods. DLP's noise level was also always lower than matching activity OSEM's. In addition, OSEM+DL and DLP outperformed OSEM in defect detection performance, but contrary to noise level ranking DLP had higher NPWMF-SNR overall than OSEM+DL. The myocardium-ventricle contrast was highest with DLP and lowest with OSEM+DL. Both OSEM+DL and DLP offered better image quality than OSEM, but visually perfusion defects were deeper in OSEM images at low activities.Significance. Both post reconstruction- and reconstruction-based DL denoising methods have great potential for MPS. The preference between these methods is a trade-off between smoother images and better defect detection performance.
Collapse
Affiliation(s)
- Antti Sohlberg
- Department of Nuclear Medicine, Päijät-Häme Central Hospital, Lahti, Finland
- HERMES Medical Solutions, Stockholm, Sweden
| | - Tuija Kangasmaa
- Department of Clinical Physiology and Nuclear Medicine, Vaasa Central Hospital, Vaasa, Finland
| | - Antti Tikkakoski
- Clinical Physiology and Nuclear Medicine, Tampere University Hospital, Tampere, Finland
| |
Collapse
|
8
|
Ruddy TD, Tavoosi A, Taqueti VR. Role of nuclear cardiology in diagnosis and risk stratification of coronary microvascular disease. J Nucl Cardiol 2023; 30:1327-1340. [PMID: 35851643 DOI: 10.1007/s12350-022-03051-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 05/22/2022] [Indexed: 10/17/2022]
Abstract
Coronary flow reserve (CFR) with positron emission tomography/computed tomography (PET/CT) has an important role in the diagnosis of coronary microvascular disease (CMD), aids risk stratification and may be useful in monitoring therapy. CMD contributes to symptoms and a worse prognosis in patients with coronary artery disease (CAD), nonischemic cardiomyopathies, and heart failure. CFR measurements may improve our understanding of the role of CMD in symptoms and prognosis in CAD and other cardiovascular diseases. The clinical presentation of CAD has changed. The prevalence of nonobstructive CAD has increased to about 50% of patients with angina undergoing angiography. Ischemia with nonobstructive arteries (INOCA) is recognized as an important cause of symptoms and has an adverse prognosis. Patients with INOCA may have ischemia due to CMD, epicardial vasospasm or diffuse nonobstructive CAD. Reduced CFR in patients with INOCA identifies a high-risk group that may benefit from management strategies specific for CMD. Although measurement of CFR by PET/CT has excellent accuracy and repeatability, use is limited by cost and availability. CFR measurement with single-photon emission tomography (SPECT) is feasible, validated, and would increase availability and use of CFR. Patients with CMD can be identified by reduced CFR and selected for specific therapies.
Collapse
Affiliation(s)
- Terrence D Ruddy
- Division of Cardiology, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, K1Y 4W7, Canada.
| | - Anahita Tavoosi
- Division of Cardiology, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, K1Y 4W7, Canada
| | - Viviany R Taqueti
- Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
9
|
Degtiarova G, Garefa C, Boehm R, Ciancone D, Sepulcri D, Gebhard C, Giannopoulos AA, Pazhenkottil AP, Kaufmann PA, Buechel RR. Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography. J Nucl Cardiol 2023; 30:1474-1483. [PMID: 36600174 PMCID: PMC10371953 DOI: 10.1007/s12350-022-03179-y] [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: 04/18/2022] [Accepted: 11/28/2022] [Indexed: 01/06/2023]
Abstract
AIM The current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR). METHODS Data from 100 patients with normal retention 13N-ammonia PET scans were divided into two groups, according to global MFR (i.e., < 2 and ≥ 2), as derived from quantitative PET analysis. We extracted radiomic features from retention images at each of five different gray-level (GL) discretization (8, 16, 32, 64, and 128 bins). Outcome independent and dependent feature selection and subsequent univariate and multivariate analyses was performed to identify image features predicting reduced global MFR. RESULTS A total of 475 radiomic features were extracted per patient. Outcome independent and dependent feature selection resulted in a remainder of 35 features. Discretization at 16 bins (GL16) yielded the highest number of significant predictors of reduced MFR and was chosen for the final analysis. GLRLM_GLNU was the most robust parameter and at a cut-off of 948 yielded an accuracy, sensitivity, specificity, negative and positive predictive value of 67%, 74%, 58%, 64%, and 69%, respectively, to detect diffusely impaired myocardial perfusion. CONCLUSION A single radiomic feature (GLRLM_GLNU) extracted from visually normal 13N-ammonia PET retention images independently predicts reduced global MFR with moderate accuracy. This concept could potentially be applied to other myocardial perfusion imaging modalities based purely on relative distribution patterns to allow for better detection of diffuse disease.
Collapse
Affiliation(s)
- Ganna Degtiarova
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Chrysoula Garefa
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Reto Boehm
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Domenico Ciancone
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Daniel Sepulcri
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Catherine Gebhard
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Andreas A. Giannopoulos
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Aju P. Pazhenkottil
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Philipp A. Kaufmann
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| | - Ronny R. Buechel
- Department of Nuclear Medicine, Cardiac Imaging, University and University Hospital Zurich, Ramistrasse 100, 8091 Zurich, Switzerland
| |
Collapse
|
10
|
D'Antonio A, Assante R, Zampella E, Mannarino T, Buongiorno P, Cuocolo A, Acampa W. Myocardial blood flow evaluation with dynamic cadmium-zinc-telluride single-photon emission computed tomography: Bright and dark sides. Diagn Interv Imaging 2023; 104:323-329. [PMID: 36797156 DOI: 10.1016/j.diii.2023.02.001] [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: 12/15/2022] [Revised: 02/01/2023] [Accepted: 02/01/2023] [Indexed: 02/16/2023]
Abstract
Myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) assessment with non-invasive techniques represent an important tool to evaluate both coronary artery disease severity and extent. Currently, cardiac positron emission tomography-computed tomography (PET-CT) is the "gold standard" for the assessment of coronary function and provides accurate estimations of baseline and hyperemic MBF and MFR. Nevertheless, due to the high cost and complexity, PET-CT is not widely used in clinical practice. The introduction of cardiac-dedicated cadmium-zinc-telluride (CZT) cameras has renewed researchers' interest on MBF quantitation by single-photon emission computed tomography (SPECT). Indeed, many studies evaluated MPR and MBF measurements by dynamic CZT-SPECT in different cohorts of patients with suspected or overt coronary artery disease. As well, many others have compared the values obtained by CZT-SPECT to the ones by PET-CT, showing good correlations in detecting significant stenosis, although with different and non-standardized cut-off values. Nevertheless, the lack of standardized protocol for acquisition, reconstruction and elaboration makes more difficult to compare different studies and to further assess the real advantages of MBF quantitation by dynamic CZT-SPECT in clinical routine. Many are the issues involved in the bright and dark sides of dynamic CZT-SPECT. They include different type of CZT cameras, different execution protocols, different tracers with different myocardial extraction fraction and distribution, different software packages with different tools and algorithms, often requiring manual post-processing elaboration. This review article provides a clear summary of the state of the art on MBF and MPR evaluation by dynamic CZT-SPECT and outlines the major issues to solve to optimize this technique.
Collapse
Affiliation(s)
- Adriana D'Antonio
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Roberta Assante
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Emilia Zampella
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Teresa Mannarino
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Pietro Buongiorno
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| | - Wanda Acampa
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy
| |
Collapse
|
11
|
Shanbhag AD, Miller RJH, Pieszko K, Lemley M, Kavanagh P, Feher A, Miller EJ, Sinusas AJ, Kaufmann PA, Han D, Huang C, Liang JX, Berman DS, Dey D, Slomka PJ. Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT. J Nucl Med 2023; 64:472-478. [PMID: 36137759 PMCID: PMC10071806 DOI: 10.2967/jnumed.122.264429] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 09/16/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is not available for most SPECT systems in clinical use, increases radiation exposure, and is impacted by misregistration. We developed and externally validated a deep-learning model to generate simulated AC images directly from non-AC (NC) SPECT, without the need for CT. Methods: SPECT myocardial perfusion imaging was performed using 99mTc-sestamibi or 99mTc-tetrofosmin on contemporary scanners with solid-state detectors. We developed a conditional generative adversarial neural network that applies a deep learning model (DeepAC) to generate simulated AC SPECT images. The model was trained with short-axis NC and AC images performed at 1 site (n = 4,886) and was tested on patients from 2 separate external sites (n = 604). We assessed the diagnostic accuracy of the stress total perfusion deficit (TPD) obtained from NC, AC, and DeepAC images for obstructive coronary artery disease (CAD) with area under the receiver-operating-characteristic curve. We also quantified the direct count change among AC, NC, and DeepAC images on a per-voxel basis. Results: DeepAC could be obtained in less than 1 s from NC images; area under the receiver-operating-characteristic curve for obstructive CAD was higher for DeepAC TPD (0.79; 95% CI, 0.72-0.85) than for NC TPD (0.70; 95% CI, 0.63-0.78; P < 0.001) and similar to AC TPD (0.81; 95% CI, 0.75-0.87; P = 0.196). The normalcy rate in the low-likelihood-of-coronary-disease population was higher for DeepAC TPD (70.4%) and AC TPD (75.0%) than for NC TPD (54.6%, P < 0.001 for both). The positive count change (increase in counts) was significantly higher for AC versus NC (median, 9.4; interquartile range, 6.0-14.2; P < 0.001) than for AC versus DeepAC (median, 2.4; interquartile range, 1.3-4.2). Conclusion: In an independent external dataset, DeepAC provided improved diagnostic accuracy for obstructive CAD, as compared with NC images, and this accuracy was similar to that of actual AC. DeepAC simplifies the task of artifact identification for physicians, avoids misregistration artifacts, and can be performed rapidly without the need for CT hardware and additional acquisitions.
Collapse
Affiliation(s)
- Aakash D Shanbhag
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Robert J H Miller
- Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Konrad Pieszko
- Department of Interventional Cardiology and Cardiac Surgery, University of Zielona Góra, Zielona Góra, Poland
| | - Mark Lemley
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Paul Kavanagh
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Attila Feher
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
| | - Edward J Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
| | - Albert J Sinusas
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
| | - Philipp A Kaufmann
- Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Donghee Han
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Cathleen Huang
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Joanna X Liang
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Daniel S Berman
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Damini Dey
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Piotr J Slomka
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California;
| |
Collapse
|
12
|
Sohlberg A, Kangasmaa T, Constable C, Tikkakoski A. Comparison of deep learning-based denoising methods in cardiac SPECT. EJNMMI Phys 2023; 10:9. [PMID: 36752847 PMCID: PMC9908801 DOI: 10.1186/s40658-023-00531-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 02/01/2023] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Myocardial perfusion SPECT (MPS) images often suffer from artefacts caused by low-count statistics. Poor-quality images can lead to misinterpretations of perfusion defects. Deep learning (DL)-based methods have been proposed to overcome the noise artefacts. The aim of this study was to investigate the differences among several DL denoising models. METHODS Convolution neural network (CNN), residual neural network (RES), UNET and conditional generative adversarial neural network (cGAN) were generated and trained using ordered subsets expectation maximization (OSEM) reconstructed MPS studies acquired with full, half, three-eighths and quarter acquisition time. All DL methods were compared against each other and also against images without DL-based denoising. Comparisons were made using half and quarter time acquisition data. The methods were evaluated in terms of noise level (coefficient of variation of counts, CoV), structural similarity index measure (SSIM) in the myocardium of normal patients and receiver operating characteristic (ROC) analysis of realistic artificial perfusion defects inserted into normal MPS scans. Total perfusion deficit scores were used as observer rating for the presence of a perfusion defect. RESULTS All the DL denoising methods tested provided statistically significantly lower noise level than OSEM without DL-based denoising with the same acquisition time. CoV of the myocardium counts with the different DL noising methods was on average 7% (CNN), 8% (RES), 7% (UNET) and 14% (cGAN) lower than with OSEM. All DL methods also outperformed full time OSEM without DL-based denoising in terms of noise level with both half and quarter acquisition time, but this difference was not statistically significant. cGAN had the lowest CoV of the DL methods at all noise levels. Image quality and polar map uniformity of DL-denoised images were also better than reduced acquisition time OSEM's. SSIM of the reduced acquisition time OSEM was overall higher than with the DL methods. The defect detection performance of full time OSEM measured as area under the ROC curve (AUC) was on average 0.97. Half time OSEM, CNN, RES and UNET provided equal or nearly equal AUC. However, with quarter time data CNN, RES and UNET had an average AUC of 0.93, which was lower than full time OSEM's AUC, but equal to quarter acquisition time OSEM. cGAN did not achieve the defect detection performance of the other DL methods. Its average AUC with half time data was 0.94 and 0.91 with quarter time data. CONCLUSIONS DL-based denoising effectively improved noise level with slightly lower perfusion defect detection performance than full time reconstruction. cGAN achieved the lowest noise level, but at the same time the poorest defect detection performance among the studied DL methods.
Collapse
Affiliation(s)
- Antti Sohlberg
- Department of Clinical Physiology and Nuclear Medicine, Päijät-Häme Central Hospital, Lahti, Finland. .,HERMES Medical Solutions, Stockholm, Sweden.
| | - Tuija Kangasmaa
- grid.417201.10000 0004 0628 2299Department of Clinical Physiology and Nuclear Medicine, Vaasa Central Hospital, Vaasa, Finland
| | - Chris Constable
- grid.451682.c0000 0004 0581 1128HERMES Medical Solutions, Stockholm, Sweden
| | - Antti Tikkakoski
- grid.412330.70000 0004 0628 2985Clinical Physiology and Nuclear Medicine, Tampere University Hospital, Tampere, Finland
| |
Collapse
|
13
|
Myocardial Perfusion Single-Photon Emission Computed Tomography (SPECT) Image Denoising: A Comparative Study. Diagnostics (Basel) 2023; 13:diagnostics13040611. [PMID: 36832099 PMCID: PMC9954870 DOI: 10.3390/diagnostics13040611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/30/2023] [Accepted: 02/03/2023] [Indexed: 02/10/2023] Open
Abstract
The present study aimed to evaluate the effectiveness of different filters in improving the quality of myocardial perfusion single-photon emission computed tomography (SPECT) images. Data were collected using the Siemens Symbia T2 dual-head SPECT/Computed tomography (CT) scanner. Our dataset included more than 900 images from 30 patients. The quality of the SPECT was evaluated after applying filters such as the Butterworth, Hamming, Gaussian, Wiener, and median-modified Wiener filters with different kernel sizes, by calculating indicators such as the signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and contrast-to-noise ratio (CNR). SNR and CNR were highest with the Wiener filter with a kernel size of 5 × 5. Additionally, the Gaussian filter achieved the highest PSNR. The results revealed that the Wiener filter, with a kernel size of 5 × 5, outperformed the other filters for denoising images of our dataset. The novelty of this study includes comparison of different filters to improve the quality of myocardial perfusion SPECT. As far as we know, this is the first study to compare the mentioned filters on myocardial perfusion SPECT images, using our datasets with specific noise structures and mentioning all the elements necessary for its presentation within one document.
Collapse
|
14
|
Advances in Single-Photon Emission Computed Tomography. Cardiol Clin 2023; 41:117-127. [PMID: 37003670 DOI: 10.1016/j.ccl.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
The clinical presentation of coronary artery disease (CAD) has changed during the last 20 years with less ischemia on stress testing and more nonobstructive CAD on coronary angiography. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging should include the measurement of myocardial flow reserve and assessment of coronary calcium for the diagnosis of nonobstructive CAD and coronary microvascular disease. SPECT/CT systems provide reliable attenuation correction for better specificity and low-dose CT for coronary calcium evaluation. SPECT MFR measurement is accurate, well validated, and repeatable.
Collapse
|
15
|
Counseller Q, Aboelkassem Y. Recent technologies in cardiac imaging. FRONTIERS IN MEDICAL TECHNOLOGY 2023; 4:984492. [PMID: 36704232 PMCID: PMC9872125 DOI: 10.3389/fmedt.2022.984492] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 11/30/2022] [Indexed: 01/11/2023] Open
Abstract
Cardiac imaging allows physicians to view the structure and function of the heart to detect various heart abnormalities, ranging from inefficiencies in contraction, regulation of volumetric input and output of blood, deficits in valve function and structure, accumulation of plaque in arteries, and more. Commonly used cardiovascular imaging techniques include x-ray, computed tomography (CT), magnetic resonance imaging (MRI), echocardiogram, and positron emission tomography (PET)/single-photon emission computed tomography (SPECT). More recently, even more tools are at our disposal for investigating the heart's physiology, performance, structure, and function due to technological advancements. This review study summarizes cardiac imaging techniques with a particular interest in MRI and CT, noting each tool's origin, benefits, downfalls, clinical application, and advancement of cardiac imaging in the near future.
Collapse
Affiliation(s)
- Quinn Counseller
- College of Health Sciences, University of Michigan, Flint, MI, United States
| | - Yasser Aboelkassem
- College of Innovation and Technology, University of Michigan, Flint, MI, United States,Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI, United States,Correspondence: Yasser Aboelkassem
| |
Collapse
|
16
|
Pandey AK, Kaur G, Chaudhary J, Hemrom A, Jaleel J, Sharma PD, Patel C, Kumar R. 99m-Tc MDP Bone Scan Image Enhancement using Pipeline Application of Dynamic Stochastic Resonance Algorithm and Block-Matching 3D Filter. Indian J Nucl Med 2023; 38:8-15. [PMID: 37180179 PMCID: PMC10171760 DOI: 10.4103/ijnm.ijnm_78_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 02/25/2023] Open
Abstract
Introduction In this pilot study, we have proposed and evaluated pipelined application of the dynamic stochastic resonance (DSR) algorithm and block-matching 3D (BM3D) filter for the enhancement of nuclear medicine images. The enhanced images out of the pipeline were compared with the corresponding enhanced images obtained using individual applications of DSR and BM3D algorithm. Materials and Methods Twenty 99m-Tc MDP bone scan images acquired on SymbiaT6 SPECT/CT gamma camera system fitted with low-energy high-resolution collimators were exported in DICOM format to a personal computer and converted into PNG format. These PNG images were processed using the proposed algorithm in MATLAB. Two nuclear medicine physicians visually compared each input and its corresponding three enhanced images to select the best-enhanced image. The image quality metrics (Brightness, Global Contrast Factor (GCF), Contrast per pixel (CPP), and Blur) were used to assess the image quality objectively. The Wilcoxon signed test was applied to find a statistically significant difference in Brightness, GCF, CPP, and Blur of enhanced and its input images at a level of significance. Results Images enhanced using the pipelined application of SR and BM3D were selected as the best images by both nuclear medicine physicians. Based on Brightness, Global Contrast Factor (GCF), CPP, and Blur, the image quality of our proposed pipeline was significantly better than enhanced images obtained using individual applications of DSR and BM3D algorithm. The proposed method was found to be very successful in enhancing details in the low count region of input images. The enhanced images were bright, smooth, and had better target-to-background ratio compared to input images. Conclusion The pipelined application of DSR and BM3D algorithm produced enhancement in nuclear medicine images having following characteristics: bright, smooth, better target-to-background ratio, and improved visibility of details in the low count regions of the input image, as compared to individual enhancements by application of DSR or BM3D algorithm.
Collapse
Affiliation(s)
- Anil Kumar Pandey
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Gagandeep Kaur
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Jagrati Chaudhary
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Angel Hemrom
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Jasim Jaleel
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Param Dev Sharma
- Department of Computer Science, SGTB Khalsa College, University of Delhi, New Delhi, India
| | - Chetan Patel
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| |
Collapse
|
17
|
Rahimian A, Etehadtavakol M, Moslehi M, Ng EYK. Comparing Different Algorithms for the Pseudo-Coloring of Myocardial Perfusion Single-Photon Emission Computed Tomography Images. J Imaging 2022; 8:jimaging8120331. [PMID: 36547496 PMCID: PMC9783251 DOI: 10.3390/jimaging8120331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/14/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022] Open
Abstract
Single-photon emission computed tomography (SPECT) images can significantly help physicians in diagnosing patients with coronary artery or suspected coronary artery diseases. However, these images are grayscale with qualities that are not readily visible. The objective of this study was to evaluate the effectiveness of different pseudo-coloring algorithms of myocardial perfusion SPECT images. Data were collected using a Siemens Symbia T2 dual-head SPECT/computed tomography (CT) scanner. After pseudo-coloring, the images were assessed both qualitatively and quantitatively. The qualities of different pseudo-color images were examined by three experts, while the images were evaluated quantitatively by obtaining indices such as mean squared error (MSE), peak signal-to-noise ratio (PSNR), normalized color difference (NCD), and structure similarity index metric (SSIM). The qualitative evaluation demonstrated that the warm color map (WCM), followed by the jet color map, outperformed the remaining algorithms in terms of revealing the non-visible qualities of the images. Furthermore, the quantitative evaluation results demonstrated that the WCM had the highest PSNR and SSIM but the lowest MSE. Overall, the WCM could outperform the other color maps both qualitatively and quantitatively. The novelty of this study includes comparing different pseudo-coloring methods to improve the quality of myocardial perfusion SPECT images and utilizing our collected datasets.
Collapse
Affiliation(s)
- Abdurrahim Rahimian
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81745-33871, Iran
| | - Mahnaz Etehadtavakol
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81745-33871, Iran
| | - Masoud Moslehi
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81745-33871, Iran
| | - Eddie Y. K. Ng
- School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
- Correspondence:
| |
Collapse
|
18
|
Peix A, Mesquita CT, Gutiérrez C, Puente A, Dueñas-C KA, Massardo T, Berrocal I, Astesiano A, Agüero RN, Bañolas R, Hiplan E, Sánchez M, Barreda AM, Gómez VV, Fernández C, Portillo S, Herrera Y, Mendoza A, Kapitan M, Castellanos C, Rodríguez DI, Estrada E, Páez D. Current status of nuclear cardiology practice in Latin America and the Caribbean, in the era of multimodality cardiac imaging approach: 2022 update. Nucl Med Commun 2022; 43:1163-1170. [PMID: 36266992 PMCID: PMC9645550 DOI: 10.1097/mnm.0000000000001630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/20/2022] [Indexed: 11/26/2022]
Abstract
Cardiovascular diseases (CVDs) are the leading cause of mortality in Latin America and the Caribbean (LAC), with the risk in men being slightly higher than in women. The coronavirus disease 2019 (COVID-19) pandemic caused a significant reduction in the number of cardiac diagnostic procedures globally and in particular in LAC. Nuclear cardiology is available in the region, but there is variability in terms of existing technology, radiopharmaceuticals, and human resources. In the region, there are 2385 single photon emission computed tomography (SPECT) and 315 PET scanners, Argentina and Brazil have the largest number. There is an increasing number of new technologies such as cadmium-zinc-telluride (CZT) cardiac-dedicated gamma cameras, SPECT/computed tomography (CT), and PET/CT. All countries performed myocardial perfusion imaging studies, mainly gated-SPECT; the rest are multi-gated acquisition, mainly for cardiac toxicity; detection of viability; rest gated SPECT in patients with dilated cardiomyopathy, and bone-avid tracer cardiac scintigraphy for transthyretin cardiac amyloidosis diagnosis. Regarding other non-nuclear cardiac imaging modalities, Argentina, Colombia, and Chile have the highest ratio of CT scanners, while Brazil, Argentina, and Chile show the highest ratio of MRI scanners. The development of nuclear cardiology and other advanced imaging modalities is challenged by the high cost of equipment, lack of equipment maintenance and service, insufficient-specific training both for imaging specialists and referring clinicians, and lack of awareness of cardiologists or other referring physicians on the clinical applications of nuclear cardiology. Another important aspect to consider is the necessity of implementing cardiac imaging multimodality training. A joint work of nuclear medicine specialists, radiologists, cardiologists, and clinicians, in general, is mandatory to achieve this goal. National, regional, and international cooperation including support from scientific professional societies such as the American Society of Nuclear Cardiology and Latin American Association of Biology and Nuclear Medicine Societies, cardiological societies, and organizations such as the International Atomic Energy Agency, and Pan American Health Organization, as well as government commitment are key factors in the overall efforts to tackle the burden of cardiovascular diseases in the region.
Collapse
Affiliation(s)
- Amalia Peix
- Instituto de Cardiología y Cirugía Cardiovascular, La Habana, CubaHospital Santo Tomás, Ciudad de Panamá, Panamá
| | | | | | - Adriana Puente
- Centro Médico Nacional ‘20 de Noviembre’, ISSSTE, Ciudad de México, México
| | | | | | - Isabel Berrocal
- Hospital San Juan de Dios, Caja Costarricense de Seguro Social, San José, Costa Rica
| | | | - Roberto N. Agüero
- Fundación Centro Diagnostico Nuclear (FCDN), Buenos Aires, Argentina
| | - Ryenne Bañolas
- Hospital Universitario Antonio Pedro-Ebeserh UFF, Niteroi, Brazil
| | | | - Mayra Sánchez
- Hospital de Especialidades ‘Carlos Andrade Marín’, Quito, Ecuador
| | - Ana Ma. Barreda
- Instituto de Cardiología y Cirugía Cardiovascular, La Habana, CubaHospital Santo Tomás, Ciudad de Panamá, Panamá
| | | | | | | | | | | | | | | | - Diana I. Rodríguez
- Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, International Atomic Emery Agency, Vienna, Austria
| | - Enrique Estrada
- Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, International Atomic Emery Agency, Vienna, Austria
| | - Diana Páez
- Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, International Atomic Emery Agency, Vienna, Austria
| |
Collapse
|
19
|
Singh A, Miller RJH. Deep learning-based attenuation map generation and correction; could it be useful clinically? J Nucl Cardiol 2022; 29:2893-2895. [PMID: 34877640 DOI: 10.1007/s12350-021-02875-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 11/04/2021] [Indexed: 01/22/2023]
Affiliation(s)
- Ananya Singh
- Departments of Imaging, Medicine and Biomedical Sciences, Division of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Robert J H Miller
- Departments of Imaging, Medicine and Biomedical Sciences, Division of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiac Sciences, University of Calgary, GAA08, 3230 Hospital Drive NW, Calgary, AB, T2N 2T9, Canada
- Libin Cardiovascular Institute, Calgary, AB, Canada
| |
Collapse
|
20
|
Desmonts C, Aide N, Austins H, Jaudet C, Lasnon C. Feasibility of Imaging Small Animals on a 360° Whole-Body Cadmium Zinc Telluride SPECT Camera: a Phantom Study. Mol Imaging Biol 2022; 24:1018-1027. [PMID: 35835951 DOI: 10.1007/s11307-022-01753-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 06/03/2022] [Accepted: 07/01/2022] [Indexed: 12/29/2022]
Abstract
PURPOSE Single-photon emission computed tomography has found an important place in preclinical cancer research. Nevertheless, the cameras dedicated to small animals are not widely available. The present study aimed to assess the feasibility of imaging small animals by a newly released 360° cadmium zinc telluride camera (VERITON, Spectrum Dynamics, Israel) dedicated to human patients. PROCEDURES A cylindrical phantom containing hot spheres was used to evaluate the intrinsic performance of the camera first without the presence of background activity and then with two contrasts between background and hot spheres (1/4 and 1/10). Acquisitions were repeated with different scan durations (10 and 20 min), two tested radioisotopes (Tc-99 m and I-123), and a set of reconstruction parameters (10 iterations [i] 8 subsets [s], 10i16s, 10i32s). A 3D-printed phantom mimicking a rat with four subcutaneous tumours was then used to test the camera under preclinical conditions. RESULTS The results obtained from the micro-hollow sphere phantom showed that it was possible to visualize spheres with an inner diameter of 3.95 mm without background activity. Moreover, spheres with diameters of 4.95 mm can be seen in the condition of high contrast between background and spheres (1/10) and 7.86 mm with lower contrast (1/4). The rat-sized phantom acquisitions showed that 10- and 8-mm subcutaneous tumours were visible with a good contrast obtained for the two radioisotopes tested in this study. Both Tc-99 m and I-123 measurements demonstrated that a 10-min acquisition reconstructed with an ordered subset expectation maximization algorithm applying 10i32s was optimal to obtain sufficient image quality in terms of noise, resolution, and contrast. CONCLUSION Phantom results showed the ability of the system to detect sub-centimetre lesions for various radioisotopes. It seemed feasible to image small animals using a 360° cadmium zinc telluride gamma camera for preclinical cancer research purposes.
Collapse
Affiliation(s)
- Cedric Desmonts
- Nuclear Medicine Department, University Hospital of Caen, Avenue de la Côte de Nacre, 14033, Caen, Cedex 9, France. .,INSERM U1086 ANTICIPE, Normandy University, UNICAEN, Caen, France.
| | - Nicolas Aide
- Nuclear Medicine Department, University Hospital of Caen, Avenue de la Côte de Nacre, 14033, Caen, Cedex 9, France.,INSERM U1086 ANTICIPE, Normandy University, UNICAEN, Caen, France
| | - Henry Austins
- Biomedical Department, Comprehensive Cancer Center F. Baclesse, UNICANCER, Caen, France
| | - Cyril Jaudet
- Medical Physics Department, Comprehensive Cancer Center F. Baclesse, UNICANCER, Caen, France
| | - Charline Lasnon
- INSERM U1086 ANTICIPE, Normandy University, UNICAEN, Caen, France.,Nuclear Medicine Department, Comprehensive Cancer Center F. Baclesse, UNICANCER, Caen, France
| |
Collapse
|
21
|
Boehm E, Better N. Time is Myocardium, but Who Does Best? J Nucl Cardiol 2022; 29:2633-2636. [PMID: 34647282 DOI: 10.1007/s12350-021-02820-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 11/28/2022]
Affiliation(s)
- Emma Boehm
- Department of Nuclear Medicine, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Nathan Better
- Department of Nuclear Medicine, Royal Melbourne Hospital, Parkville, VIC, Australia.
- Department of Cardiology, Royal Melbourne Hospital, Parkville, VIC, Australia.
- Department of Nuclear Medicine, St Frances Xavier Cabrini Hospital, Malvern, VIC, Australia.
- Department of Medicine, University of Melbourne, Parkville, VIC, Australia.
| |
Collapse
|
22
|
Tavoosi AN, Kadoya Y, Ruddy TD. Added value to stress myocardial perfusion imaging studies with measurement of left ventricular mass. J Nucl Cardiol 2022; 29:2374-2377. [PMID: 34668151 DOI: 10.1007/s12350-021-02802-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 08/08/2021] [Indexed: 10/20/2022]
Affiliation(s)
- Anahita N Tavoosi
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Canada
| | - Yoshito Kadoya
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Canada
| | - Terrence D Ruddy
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Canada.
- University of Ottawa Heart Institute, 40 Ruskin Street, Room H-S407, Ottawa, ON, K1Y 4W7, Canada.
| |
Collapse
|
23
|
Renaud JM, Poitrasson-Rivière A, Hagio T, Moody JB, Arida-Moody L, Ficaro EP, Murthy VL. Myocardial flow reserve estimation with contemporary CZT-SPECT and 99mTc-tracers lacks precision for routine clinical application. J Nucl Cardiol 2022; 29:2078-2089. [PMID: 34426935 DOI: 10.1007/s12350-021-02761-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/17/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND PET myocardial flow reserve (MFR) has established diagnostic and prognostic value. Technological advances have now enabled SPECT MFR quantification. We investigated whether SPECT MFR precision is sufficient for clinical categorization of patients. METHODS Validation studies vs invasive flow measurements and PET MFR were reviewed to determine global SPECT MFR thresholds. Studies vs PET and a SPECT MFR repeatability study were used to establish imprecision in SPECT MFR measurements as the standard deviation of the difference between SPECT and PET MFR, or test-retest SPECT MFR. Simulations were used to evaluate the impact of SPECT MFR imprecision on confidence of clinically relevant categorization. RESULTS Based on validation studies, the typical PET MFR categories were used for SPECT MFR classification (< 1.5, 1.5-2.0, > 2.0). Imprecision vs PET MFR ranged from 0.556 to 0.829, and test-retest imprecision was 0.781-0.878. Simulations showed correct classification of up to only 34% of patients when 1.5 ≤ true MFR ≤ 2.0. Categorization with high confidence (> 80%) was only achieved for extreme MFR values (< 1.0 or > 2.5), with correct classification in only 15% of patients in a typical lab with MFR of 1.8 ± 0.5. CONCLUSIONS Current SPECT-derived estimates of MFR lack precision and require further optimization for clinical risk stratification.
Collapse
Affiliation(s)
- Jennifer M Renaud
- INVIA Medical Imaging Solutions, 3025 Boardwalk Dr., Suite 200, Ann Arbor, MI, 48108, USA.
| | | | - Tomoe Hagio
- INVIA Medical Imaging Solutions, 3025 Boardwalk Dr., Suite 200, Ann Arbor, MI, 48108, USA
| | - Jonathan B Moody
- INVIA Medical Imaging Solutions, 3025 Boardwalk Dr., Suite 200, Ann Arbor, MI, 48108, USA
| | - Liliana Arida-Moody
- Frankel Cardiovascular Center, Division of Cardiovascular Medicine (Department of Internal Medicine) and Division of Nuclear Medicine (Department of Radiology), University of Michigan, Ann Arbor, MI, USA
| | - Edward P Ficaro
- INVIA Medical Imaging Solutions, 3025 Boardwalk Dr., Suite 200, Ann Arbor, MI, 48108, USA
- Frankel Cardiovascular Center, Division of Cardiovascular Medicine (Department of Internal Medicine) and Division of Nuclear Medicine (Department of Radiology), University of Michigan, Ann Arbor, MI, USA
| | - Venkatesh L Murthy
- Frankel Cardiovascular Center, Division of Cardiovascular Medicine (Department of Internal Medicine) and Division of Nuclear Medicine (Department of Radiology), University of Michigan, Ann Arbor, MI, USA
| |
Collapse
|
24
|
A Multimodality Myocardial Perfusion Phantom: Initial Quantitative Imaging Results. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 9:bioengineering9090436. [PMID: 36134982 PMCID: PMC9495397 DOI: 10.3390/bioengineering9090436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/21/2022] [Accepted: 08/28/2022] [Indexed: 11/28/2022]
Abstract
This proof-of-concept study explores the multimodal application of a dedicated cardiac flow phantom for ground truth contrast measurements in dynamic myocardial perfusion imaging with CT, PET/CT, and MRI. A 3D-printed cardiac flow phantom and flow circuit mimics the shape of the left ventricular cavity (LVC) and three myocardial regions. The regions are filled with tissue-mimicking materials and the flow circuit regulates and measures contrast flow through LVC and myocardial regions. Normal tissue perfusion and perfusion deficits were simulated. Phantom measurements in PET/CT, CT, and MRI were evaluated with clinically used hardware and software. The reference arterial input flow was 4.0 L/min and myocardial flow 80 mL/min, corresponding to myocardial blood flow (MBF) of 1.6 mL/g/min. The phantom demonstrated successful completion of all processes involved in quantitative, multimodal myocardial perfusion imaging (MPI) applications. Contrast kinetics in time intensity curves were in line with expectations for a mimicked perfusion deficit (38 s vs. 32 s in normal tissue). Derived MBF in PET/CT and CT led to under- and overestimation of reference flow of 0.9 mL/g/min and 4.5 mL/g/min, respectively. Simulated perfusion deficit (0.8 mL/g/min) in CT resulted in MBF of 2.8 mL/g/min. We successfully performed initial, quantitative perfusion measurements with a dedicated phantom setup utilizing clinical hardware and software. These results showcase the multimodal phantom’s potential.
Collapse
|
25
|
Huh Y, Shrestha UM, Gullberg GT, Seo Y. Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition. Front Cardiovasc Med 2022; 9:871967. [PMID: 35911544 PMCID: PMC9326051 DOI: 10.3389/fcvm.2022.871967] [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: 02/08/2022] [Accepted: 06/16/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.
Collapse
Affiliation(s)
- Yoonsuk Huh
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Uttam M. Shrestha
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Grant T. Gullberg
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Youngho Seo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Department of Nuclear Engineering, University of California, Berkeley, Berkeley, CA, United States
- *Correspondence: Youngho Seo,
| |
Collapse
|
26
|
Otaki Y, Fish MB, Miller RJH, Lemley M, Slomka PJ. Prognostic value of early left ventricular ejection fraction reserve during regadenoson stress solid-state SPECT-MPI. J Nucl Cardiol 2022; 29:1219-1230. [PMID: 33389643 DOI: 10.1007/s12350-020-02420-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 10/09/2020] [Indexed: 11/25/2022]
Abstract
BACKGROUND We hypothesized early post-stress left ventricular ejection fraction reserve (EFR) on solid-state-SPECT is associated with major cardiac adverse events (MACE). METHODS 151 patients (70 ± 12 years, male 50%) undergoing same-day rest/regadenoson stress 99mTc-sestamibi solid-state SPECT were followed for MACE. Rest imaging was performed in the upright and supine positions. Early stress imaging was started 2 minutes after the regadenoson injection in the supine position and followed by late stress acquisition in the upright position. Total perfusion deficit (TPD) and functional parameters were quantified automatically. EFR, ∆end-diastolic volume (EDV), and end-systolic volume (ESV) were calculated as the difference between stress and rest values in the same position. EFR < 0%, ∆EDV ≥ 5 ml, or ∆ESV ≥ 5 ml was defined as abnormal. RESULTS During the follow-up (mean 3.2 years), 28 MACE occurred (19%). In Kaplan-Meier analysis, there was a significantly decreased event-free survival in patients with early EFR < 0% (P = 0.004). Similarly, there was a decreased event-free survival in patients with ∆ESV ≥ 5 ml at early stress (P = 0.003). However, EFR, ∆EDV, and ∆ESV at late stress were not associated with MACE-free survival. Cox proportional hazards model adjusting for clinical information and stress TPD demonstrated that EFR, ∆EDV, and ∆ESV at early stress were significantly associated with MACE (P < 0.05 for all). CONCLUSIONS Reduced early post-stress EFR on vasodilator stress solid-state SPECT is associated with MACE.
Collapse
Affiliation(s)
- Yuka Otaki
- Department of Imaging (Division of Nuclear Medicine) and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Metro 203, Los Angeles, CA, 90048, USA
| | - Mathews B Fish
- Oregon Heart and Vascular Institute, Sacred Heart Medical Center, 3311 Riverbend Drive, Springfield, OR, 97477, USA
| | - Robert J H Miller
- Department of Imaging (Division of Nuclear Medicine) and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Metro 203, Los Angeles, CA, 90048, USA
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | - Mark Lemley
- Oregon Heart and Vascular Institute, Sacred Heart Medical Center, 3311 Riverbend Drive, Springfield, OR, 97477, USA
| | - Piotr J Slomka
- Department of Imaging (Division of Nuclear Medicine) and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Metro 203, Los Angeles, CA, 90048, USA.
| |
Collapse
|
27
|
Fu B, Wei X, Lin Y, Chen J, Yu D. Pathophysiologic Basis and Diagnostic Approaches for Ischemia With Non-obstructive Coronary Arteries: A Literature Review. Front Cardiovasc Med 2022; 9:731059. [PMID: 35369287 PMCID: PMC8968033 DOI: 10.3389/fcvm.2022.731059] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 01/31/2022] [Indexed: 02/05/2023] Open
Abstract
Ischemia with non-obstructive coronary arteries (INOCA) has gained increasing attention due to its high prevalence, atypical clinical presentations, difficult diagnostic procedures, and poor prognosis. There are two endotypes of INOCA-one is coronary microvascular dysfunction and the other is vasospastic angina. Diagnosis of INOCA lies in evaluating coronary flow reserve, microcirculatory resistance, and vasoreactivity, which is usually obtained via invasive coronary interventional techniques. Non-invasive diagnostic approaches such as echocardiography, single-photon emission computed tomography, cardiac positron emission tomography, and cardiac magnetic resonance imaging are also valuable for assessing coronary blood flow. Some new techniques (e.g., continuous thermodilution and angiography-derived quantitative flow reserve) have been investigated to assist the diagnosis of INOCA. In this review, we aimed to discuss the pathophysiologic basis and contemporary and novel diagnostic approaches for INOCA, to construct a better understanding of INOCA evaluation.
Collapse
Affiliation(s)
- Bingqi Fu
- Shantou University Medical College, Shantou, China
- Division of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xuebiao Wei
- Division of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Division of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yingwen Lin
- Shantou University Medical College, Shantou, China
- Division of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jiyan Chen
- Division of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Danqing Yu
- Division of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| |
Collapse
|
28
|
Juarez-Orozco LE, Klén R, Niemi M, Ruijsink B, Daquarti G, van Es R, Benjamins JW, Yeung MW, van der Harst P, Knuuti J. Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies. Curr Cardiol Rep 2022; 24:307-316. [PMID: 35171443 PMCID: PMC8852880 DOI: 10.1007/s11886-022-01649-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/17/2021] [Indexed: 12/28/2022]
Abstract
Purpose of Review As machine learning-based artificial intelligence (AI) continues to revolutionize the way in which we analyze data, the field of nuclear cardiology provides fertile ground for the implementation of these complex analytics. This review summarizes and discusses the principles regarding nuclear cardiology techniques and AI, and the current evidence regarding its performance and contribution to the improvement of risk prediction in cardiovascular disease. Recent Findings and Summary There is a growing body of evidence on the experimentation with and implementation of machine learning-based AI on nuclear cardiology studies both concerning SPECT and PET technology for the improvement of risk-of-disease (classification of disease) and risk-of-events (prediction of adverse events) estimations. These publications still report objective divergence in methods either utilizing statistical machine learning approaches or deep learning with varying architectures, dataset sizes, and performance. Recent efforts have been placed into bringing standardization and quality to the experimentation and application of machine learning-based AI in cardiovascular imaging to generate standards in data harmonization and analysis through AI. Machine learning-based AI offers the possibility to improve risk evaluation in cardiovascular disease through its implementation on cardiac nuclear studies. Graphical Abstract AI in improving risk evaluation in nuclear cardiology. * Based on the 2019 ESC guidelines ![]()
Collapse
Affiliation(s)
- Luis Eduardo Juarez-Orozco
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.,Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Riku Klén
- Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland
| | - Mikael Niemi
- Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland
| | - Bram Ruijsink
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas' Hospital, London, UK
| | - Gustavo Daquarti
- Department of Artificial Intelligence, UMA-Health, Buenos Aires, Argentina
| | - Rene van Es
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Jan-Walter Benjamins
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ming Wai Yeung
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Juhani Knuuti
- Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| |
Collapse
|
29
|
Boschi A, Uccelli L, Marvelli L, Cittanti C, Giganti M, Martini P. Technetium-99m Radiopharmaceuticals for Ideal Myocardial Perfusion Imaging: Lost and Found Opportunities. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27041188. [PMID: 35208982 PMCID: PMC8877792 DOI: 10.3390/molecules27041188] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 02/06/2022] [Accepted: 02/08/2022] [Indexed: 02/07/2023]
Abstract
The favorable nuclear properties in combination with the rich coordination chemistry make technetium-99m the radioisotope of choice for the development of myocardial perfusion tracers. In the early 1980s, [99mTc]Tc-Sestamibi, [99mTc]Tc-Tetrofosmin, and [99mTc]Tc-Teboroxime were approved as commercial radiopharmaceuticals for myocardial perfusion imaging in nuclear cardiology. Despite its peculiar properties, the clinical use of [99mTc]Tc-Teboroxime was quickly abandoned due to its rapid myocardial washout. Despite their widespread clinical applications, both [99mTc]Tc-Sestamibi and [99mTc]Tc-Tetrofosmin do not meet the requirements of an ideal perfusion imaging agent due to their relatively low first-pass extraction fraction and high liver absorption. An ideal radiotracer for myocardial perfusion imaging should have a high myocardial uptake; a high and stable target-to-background ratio with low uptake in the lungs, liver, stomach during the image acquisition period; a high first-pass myocardial extraction fraction and very rapid blood clearance; and a linear relationship between radiotracer myocardial uptake and coronary blood flow. Although it is difficult to reconcile all these properties in a single tracer, scientific research in the field has always channeled its efforts in the development of molecules that are able to meet the characteristics of ideality as much as possible. This short review summarizes the developments in 99mTc myocardial perfusion tracers, which are able to fulfill hitherto unmet medical needs and serve a large population of patients with heart disease, and underlines their strengths and weaknesses, the lost and found opportunities thanks to the developments of the new ultrafast SPECT technologies.
Collapse
Affiliation(s)
- Alessandra Boschi
- Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Via L. Borsari, 46-44121 Ferrara, Italy;
- Correspondence: ; Tel.:+39-0532-455354
| | - Licia Uccelli
- Department of Translational Medicine, University of Ferrara, Via Fossato di Mortara, 70 c/o Viale Eliporto, 46-44121 Ferrara, Italy; (L.U.); (C.C.); (M.G.)
| | - Lorenza Marvelli
- Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Via L. Borsari, 46-44121 Ferrara, Italy;
| | - Corrado Cittanti
- Department of Translational Medicine, University of Ferrara, Via Fossato di Mortara, 70 c/o Viale Eliporto, 46-44121 Ferrara, Italy; (L.U.); (C.C.); (M.G.)
| | - Melchiore Giganti
- Department of Translational Medicine, University of Ferrara, Via Fossato di Mortara, 70 c/o Viale Eliporto, 46-44121 Ferrara, Italy; (L.U.); (C.C.); (M.G.)
| | - Petra Martini
- Department of Environmental and Prevention Sciences, University of Ferrara, Via L. Borsari, 46-44121 Ferrara, Italy;
| |
Collapse
|
30
|
Muscogiuri G, Guglielmo M, Serra A, Gatti M, Volpato V, Schoepf UJ, Saba L, Cau R, Faletti R, McGill LJ, De Cecco CN, Pontone G, Dell’Aversana S, Sironi S. Multimodality Imaging in Ischemic Chronic Cardiomyopathy. J Imaging 2022; 8:jimaging8020035. [PMID: 35200737 PMCID: PMC8877428 DOI: 10.3390/jimaging8020035] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 01/23/2022] [Accepted: 01/27/2022] [Indexed: 02/01/2023] Open
Abstract
Ischemic chronic cardiomyopathy (ICC) is still one of the most common cardiac diseases leading to the development of myocardial ischemia, infarction, or heart failure. The application of several imaging modalities can provide information regarding coronary anatomy, coronary artery disease, myocardial ischemia and tissue characterization. In particular, coronary computed tomography angiography (CCTA) can provide information regarding coronary plaque stenosis, its composition, and the possible evaluation of myocardial ischemia using fractional flow reserve CT or CT perfusion. Cardiac magnetic resonance (CMR) can be used to evaluate cardiac function as well as the presence of ischemia. In addition, CMR can be used to characterize the myocardial tissue of hibernated or infarcted myocardium. Echocardiography is the most widely used technique to achieve information regarding function and myocardial wall motion abnormalities during myocardial ischemia. Nuclear medicine can be used to evaluate perfusion in both qualitative and quantitative assessment. In this review we aim to provide an overview regarding the different noninvasive imaging techniques for the evaluation of ICC, providing information ranging from the anatomical assessment of coronary artery arteries to the assessment of ischemic myocardium and myocardial infarction. In particular this review is going to show the different noninvasive approaches based on the specific clinical history of patients with ICC.
Collapse
Affiliation(s)
- Giuseppe Muscogiuri
- Department of Radiology, Istituto Auxologico Italiano IRCCS, San Luca Hospital, University Milano Bicocca, 20149 Milan, Italy
- Correspondence: ; Tel.: +39-329-404-9840
| | - Marco Guglielmo
- Department of Cardiology, Division of Heart and Lungs, Utrecht University, Utrecht University Medical Center, 3584 Utrecht, The Netherlands;
| | - Alessandra Serra
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari-Polo di Monserrato, 09042 Cagliari, Italy; (A.S.); (L.S.); (R.C.)
| | - Marco Gatti
- Radiology Unit, Department of Surgical Sciences, University of Turin, 10124 Turin, Italy; (M.G.); (R.F.)
| | - Valentina Volpato
- Department of Cardiac, Neurological and Metabolic Sciences, Istituto Auxologico Italiano IRCCS, San Luca Hospital, University Milano Bicocca, 20149 Milan, Italy;
| | - Uwe Joseph Schoepf
- Department of Radiology and Radiological Science, MUSC Ashley River Tower, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA; (U.J.S.); (L.J.M.)
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari-Polo di Monserrato, 09042 Cagliari, Italy; (A.S.); (L.S.); (R.C.)
| | - Riccardo Cau
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari-Polo di Monserrato, 09042 Cagliari, Italy; (A.S.); (L.S.); (R.C.)
| | - Riccardo Faletti
- Radiology Unit, Department of Surgical Sciences, University of Turin, 10124 Turin, Italy; (M.G.); (R.F.)
| | - Liam J. McGill
- Department of Radiology and Radiological Science, MUSC Ashley River Tower, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA; (U.J.S.); (L.J.M.)
| | - Carlo Nicola De Cecco
- Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
| | | | - Serena Dell’Aversana
- Department of Radiology, Ospedale S. Maria Delle Grazie—ASL Napoli 2 Nord, 80078 Pozzuoli, Italy;
| | - Sandro Sironi
- School of Medicine and Post Graduate School of Diagnostic Radiology, University of Milano-Bicocca, 20126 Milan, Italy;
- Department of Radiology, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
| |
Collapse
|
31
|
Kamphuis ME, de Vries GJ, Kuipers H, Saaltink M, Verschoor J, Greuter MJW, Slart RHJA, Slump CH. Development of a dedicated 3D printed myocardial perfusion phantom: proof-of-concept in dynamic SPECT. Med Biol Eng Comput 2022; 60:1541-1550. [PMID: 35048275 PMCID: PMC9079041 DOI: 10.1007/s11517-021-02490-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 12/08/2021] [Indexed: 11/30/2022]
Abstract
We aim to facilitate phantom-based (ground truth) evaluation of dynamic, quantitative myocardial perfusion imaging (MPI) applications. Current MPI phantoms are static representations or lack clinical hard- and software evaluation capabilities. This proof-of-concept study demonstrates the design, realisation and testing of a dedicated cardiac flow phantom. The 3D printed phantom mimics flow through a left ventricular cavity (LVC) and three myocardial segments. In the accompanying fluid circuit, tap water is pumped through the LVC and thereafter partially directed to the segments using adjustable resistances. Regulation hereof mimics perfusion deficit, whereby flow sensors serve as reference standard. Seven phantom measurements were performed while varying injected activity of 99mTc-tetrofosmin (330–550 MBq), cardiac output (1.5–3.0 L/min) and myocardial segmental flows (50–150 mL/min). Image data from dynamic single photon emission computed tomography was analysed with clinical software. Derived time activity curves were reproducible, showing logical trends regarding selected input variables. A promising correlation was found between software computed myocardial flows and its reference (\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\rho$$\end{document}ρ= − 0.98; p = 0.003). This proof-of-concept paper demonstrates we have successfully measured first-pass LV flow and myocardial perfusion in SPECT-MPI using a novel, dedicated, myocardial perfusion phantom.
Collapse
Affiliation(s)
- Marije E Kamphuis
- Multi-Modality Medical Imaging (M3i) Group, Faculty of Science and Technology, Technical Medical Centre 2386, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands. .,Robotics and Mechatronics (RaM) Group, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
| | - Gijs J de Vries
- Robotics and Mechatronics (RaM) Group, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Henny Kuipers
- Robotics and Mechatronics (RaM) Group, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Marloes Saaltink
- Department of Nuclear Medicine, Ziekenhuis Groep Twente, Hengelo, The Netherlands
| | - Jacqueline Verschoor
- Department of Nuclear Medicine, Ziekenhuis Groep Twente, Hengelo, The Netherlands
| | - Marcel J W Greuter
- Robotics and Mechatronics (RaM) Group, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, The Netherlands.,Medical Imaging Centre, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Riemer H J A Slart
- Medical Imaging Centre, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Biomedical Photonic Imaging Group, Faculty of Science and Technology, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Cornelis H Slump
- Robotics and Mechatronics (RaM) Group, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| |
Collapse
|
32
|
Imbert L, Marie PY. Dedicated CZT gamma cameras for nuclear cardiology. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00080-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
|
33
|
Miller RJH, Han D, Rozanski A, Gransar H, Friedman JD, Hayes S, Thomson L, Tamarappoo B, Slomka PJ, Berman DS. CZT camera systems may provide better risk stratification for low-risk patients. J Nucl Cardiol 2021; 28:2927-2936. [PMID: 32500175 DOI: 10.1007/s12350-020-02128-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 03/10/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND The photon sensitivity and spatial resolution of single-photon emission-computed tomography (SPECT) has been significantly improved by solid-state camera systems using cadmium zinc telluride (CZT) detectors. While the diagnostic accuracy of these systems is well established, there is little evidence directly comparing the prognostic utility to conventional NaI cameras. METHODS AND RESULTS Retrospective analysis of patients undergoing SPECT between 2008 and 2012. Visual SPECT assessment was performed utilizing the 17-segment model to determine summed stress scores (SSS). We identified 12,830 consecutive patients, mean age 63.2 ± 13.7 and 56.1% male, 5072 of whom underwent CZT and 7758 NaI imaging. During a median follow-up duration of 7.0 years (IQR 5.5-8.2), a total of 2788 (21.7%) patients died. Compared to SSS 0, minimal perfusion abnormality (SSS 1-3) was associated with increased all-cause mortality with CZT camera (adjusted HR 1.32, P = .017) and NaI camera (adjusted HR 1.29, P = .001, interaction P = .803). Increasing stress abnormality was associated with a similar increase in risk with CZT or NaI imaging (interaction P > .500). In a propensity matched analysis, patients with normal perfusion stress perfusion assessed with a CZT was associated with decreased mortality compared to normal perfusion assessed by a NaI camera system (hazard ratio .88, 95% CI .78-.99, P = .040). CONCLUSIONS Increasing stress perfusion abnormality was associated with similar increase in all-cause mortality with CZT or NaI cameras. CZT and NaI camera systems provide similar risk stratification, however, normal myocardial perfusion may be associated with a more benign prognosis when assessed with a CZT camera system.
Collapse
Affiliation(s)
- Robert J H Miller
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | - Donghee Han
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alan Rozanski
- Division of Cardiology, Mount Sinai St. Luke's Hospital, Mount Sinai Heart, and the Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Heidi Gransar
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - John D Friedman
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sean Hayes
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Louise Thomson
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Balaji Tamarappoo
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Piotr J Slomka
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Berman
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- , Room 1258, 8700 Beverly Boulevard, Los Angeles, CA, 90048, USA.
| |
Collapse
|
34
|
Bailly M, Ribeiro MJ, Angoulvant D. Combining flow and reserve measurement during myocardial perfusion imaging: A new era for myocardial perfusion scintigraphy? Arch Cardiovasc Dis 2021; 114:818-827. [PMID: 34801410 DOI: 10.1016/j.acvd.2021.10.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 12/25/2022]
Abstract
Myocardial flow reserve represents the ratio of myocardial blood flow between stress and rest, giving functional information about both macrocirculation and microcirculation; it has been reported extensively in positron emission tomography, with an increase in diagnostic performance, providing important prognostic information and being a powerful tool to guide therapy. Advances in single photon emission computed tomography, with the widespread availability of "cadmium zinc telluride" single photon emission computed tomography cameras, raise the question of myocardial flow reserve use in daily clinical practice. In this article, we review the pathophysiology of myocardial blood flow and myocardial flow reserve, and the initial data available from single photon emission computed tomography myocardial blood flow and myocardial flow reserve evaluation; we also discuss potential limitations to the wider implementation of flow evaluation in single photon emission computed tomography.
Collapse
Affiliation(s)
- Matthieu Bailly
- Nuclear Medicine Department, CHR Orleans, 14, Avenue de l'Hôpital, 45100 Orleans, France; UMR 1253, iBrain, Université de Tours, Inserm, 37000 Tours, France.
| | - Maria Joao Ribeiro
- UMR 1253, iBrain, Université de Tours, Inserm, 37000 Tours, France; Nuclear Medicine Department, CHRU Tours, 37000 Tours, France
| | - Denis Angoulvant
- Cardiology Department, CHRU Tours, 37000 Tours, France; EA4245, T2i, Tours University, 37000 Tours, France
| |
Collapse
|
35
|
Zhang R, Wang M, Zhou Y, Wang S, Shen Y, Li N, Wang P, Tan J, Meng Z, Jia Q. Impacts of acquisition and reconstruction parameters on the absolute technetium quantification of the cadmium-zinc-telluride-based SPECT/CT system: a phantom study. EJNMMI Phys 2021; 8:66. [PMID: 34568990 PMCID: PMC8473509 DOI: 10.1186/s40658-021-00412-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 09/10/2021] [Indexed: 02/06/2023] Open
Abstract
Background The digital cadmium–zinc–telluride (CZT)-based SPECT system has many advantages, including better spatial and energy resolution. However, the impacts of different acquisition and reconstruction parameters on CZT SPECT quantification might still need to be validated. This study aimed to evaluate the impacts of acquisition parameters (the main energy window and acquisition time per frame) and reconstruction parameters (the number of iterations, subsets in iterative reconstruction, post-filter, and image correction methods) on the technetium quantification of CZT SPECT/CT. Methods A phantom (PET NEMA/IEC image quality, USA) was filled with four target-to-background (T/B) ratios (32:1, 16:1, 8:1, and 4:1) of technetium. Mean uptake values (the calculated mean concentrations for spheres) were measured to evaluate the recovery coefficient (RC) changes under different acquisition and reconstruction parameters. The corresponding standard deviations of mean uptake values were also measured to evaluate the quantification error. Image quality was evaluated using the National Electrical Manufacturers Association (NEMA) NU 2–2012 standard. Results For all T/B ratios, significant correlations were found between iterations and RCs (r = 0.62–0.96 for 1–35 iterations, r = 0.94–0.99 for 35–90 iterations) as well as between the full width at half maximum (FWHM) of the Gaussian filter and RCs (r = − 0.86 to − 1.00, all P values < 0.05). The regression coefficients of 1–35 iterations were higher than those of 35–90 iterations (0.51–1.60 vs. 0.02–0.19). RCs calculated with AC (attenuation correction) + SC (scatter correction) + RR (resolution recovery correction) combination were more accurate (53.82–106.70%) than those calculated with other combinations (all P values < 0.05). No significant statistical differences (all P values > 0.05) were found between the 15% and 20% energy windows except for the 32:1 T/B ratio (P value = 0.023) or between the 10 s/frame and 120 s/frame acquisition times except for the 4:1 T/B ratio (P value = 0.015) in terms of RCs. Conclusions CZT-SPECT/CT of technetium resulted in good quantification accuracy. The favourable acquisition parameters might be a 15% energy window and 40 s/frame of acquisition time. The favourable reconstruction parameters might be 35 iterations, 20 subsets, the AC + SC + RR correction combination, and no filter. Supplementary Information The online version contains supplementary material available at 10.1186/s40658-021-00412-4.
Collapse
Affiliation(s)
- Ruyi Zhang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Miao Wang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Yaqian Zhou
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Shen Wang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Yiming Shen
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Ning Li
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Peng Wang
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Jian Tan
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China
| | - Zhaowei Meng
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China.
| | - Qiang Jia
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Anshan Road No. 154, Heping District, Tianjin, 300052, People's Republic of China.
| |
Collapse
|
36
|
Brambilla M, Kuchcińska A, Matheoud R, Muni A. Cumulative radiation doses due to nuclear medicine examinations: a systematic review. Br J Radiol 2021; 94:20210444. [PMID: 34379454 DOI: 10.1259/bjr.20210444] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
OBJECTIVES To systematically review the published data regarding the cumulative exposure to radiation in selected cohorts of adults or paediatric patients due to diagnostic nuclear medicine examinations. METHODS We conducted PubMed/Medline searches of peer-reviewed papers on cumulated effective dose (CED) from diagnostic nuclear medicine procedures published between 01 January 2010 until 31 January 2021. Studies were considered eligible if the contribution of nuclear medicine examinations to total CED was >10%. Studies reporting cumulative doses in a single episode of care or in a limited time (≤1 year) were excluded. The main outcomes for which data were sought were the CED accrued by patients, the period in which the CED was accrued, the percentage of patients with CED > 100 mSv and the percentage contribution due to nuclear medicine procedures to the overall CED. RESULTS The studies included in the synthesis were 18 which enrolled a total of 1,76,371 patients. Eleven (1,757 patients), three (1,74,079 patients) and four (535 patients) were related to oncological, cardiologic and transplanted patients, respectively. All the studies were retrospective; some of the source materials referred to small number of patients and some of the patients were followed for a short time. Not many studies accurately quantified the contribution of nuclear medicine procedures to the overall radiation exposure due to medical imaging. Finally, most of the studies covered an observation period which extended mainly in the 2000-2010 decade. CONCLUSIONS There is a need of prospective, multicentric studies enrolling a greater number of patients, followed for longer period in selected groups of patients to fully capture the cumulative exposure to radiation in these settings. ADVANCES IN KNOWLEDGE This systematic review allows to identify selected group of patients with a specific health status in which the cumulated exposure to radiation may be of concern and where the contribution of nuclear medicine procedures to the total CED is significant.
Collapse
Affiliation(s)
- Marco Brambilla
- Department of Medical Physics, Azienda Ospedaliera "SS. Antonio e Biagio e C. Arrigo", Alessandria, Italy.,Department of Medical Physics, University Hospital "Maggiore della Carità", Novara, Italy
| | - Agnieszka Kuchcińska
- Department of Radiotherapy, Maria Skłodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Roberta Matheoud
- Department of Medical Physics, University Hospital "Maggiore della Carità", Novara, Italy
| | - Alfredo Muni
- Department of Nuclear Medicine, Azienda Ospedaliera "SS. Antonio e Biagio e C. Arrigo", Alessandria, Italy
| |
Collapse
|
37
|
Impact of selenium addition to the cadmium-zinc-telluride matrix for producing high energy resolution X-and gamma-ray detectors. Sci Rep 2021; 11:10338. [PMID: 33990654 PMCID: PMC8121847 DOI: 10.1038/s41598-021-89795-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 04/20/2021] [Indexed: 12/03/2022] Open
Abstract
Both material quality and detector performance have been steadily improving over the past few years for the leading room temperature radiation detector material cadmium-zinc-telluride (CdZnTe). However, although tremendous progress being made, CdZnTe still suffers from high concentrations of performance-limiting defects, such as Te inclusions, networks of sub-grain boundaries and compositional inhomogeneity due to the higher segregation coefficient of Zn. Adding as low as 2% (atomic) Se into CdZnTe matrix was found to successfully mitigate many performance-limiting defects and provide improved compositional homogeneity. Here we report record-high performance of Virtual Frisch Grid (VFG) detector fabricated from as-grown Cd0.9Zn0.1Te0.98Se0.02 ingot grown by the Traveling Heater Method (THM). Benefiting from superior material quality, we achieved superb energy resolution of 0.77% at 662 keV (as-measured without charge-loss correction algorithms) registered at room temperature. The absence of residual thermal stress in the detector was revealed from white beam X-ray topographic images, which was also confirmed by Infra-Red (IR) transmission imaging under cross polarizers. Furthermore, neither sub-grain boundaries nor their networks were observed from the X-ray topographic image. However, large concentrations of extrinsic impurities were revealed in as-grown materials, suggesting a high likelihood for further reduction in the energy resolution after improved purification of the starting material.
Collapse
|
38
|
Slomka PJ, Moody JB, Miller RJH, Renaud JM, Ficaro EP, Garcia EV. Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications. J Nucl Cardiol 2021; 28:115-127. [PMID: 33067750 DOI: 10.1007/s12350-020-02337-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 07/28/2020] [Indexed: 02/07/2023]
Abstract
Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation.
Collapse
Affiliation(s)
- Piotr J Slomka
- Department of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | | | - Robert J H Miller
- Department of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | | | - Edward P Ficaro
- INVIA Medical Imaging Solutions, Ann Arbor, MI, USA
- Division of Cardiology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Ernest V Garcia
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA
| |
Collapse
|
39
|
Miller RJH, Slomka PJ. Is SPECT LVEF assessment more accurate than CT at higher heart rates? More evidence for complementary information in multimodality imaging. J Nucl Cardiol 2021; 28:317-319. [PMID: 32383082 DOI: 10.1007/s12350-020-02130-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 02/24/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Robert J H Miller
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | - Piotr J Slomka
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| |
Collapse
|
40
|
SPECT and SPECT/CT. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00008-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
|
41
|
Slomka PJ, Moody JB, Miller RJH, Renaud JM, Ficaro EP, Garcia EV. Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications. J Nucl Med 2020; 62:168-176. [PMID: 33067339 DOI: 10.2967/jnumed.120.242537] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 07/28/2020] [Indexed: 01/15/2023] Open
Abstract
Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation. (J Nucl Cardiol 2020).
Collapse
Affiliation(s)
- Piotr J Slomka
- Department of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA
| | | | - Robert J H Miller
- Department of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA.,Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada
| | | | - Edward P Ficaro
- INVIA Medical Imaging Solutions, Ann Arbor, MI.,Division of Cardiology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI; and
| | - Ernest V Garcia
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| |
Collapse
|
42
|
Beyer T, Bidaut L, Dickson J, Kachelriess M, Kiessling F, Leitgeb R, Ma J, Shiyam Sundar LK, Theek B, Mawlawi O. What scans we will read: imaging instrumentation trends in clinical oncology. Cancer Imaging 2020; 20:38. [PMID: 32517801 PMCID: PMC7285725 DOI: 10.1186/s40644-020-00312-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 04/17/2020] [Indexed: 12/16/2022] Open
Abstract
Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.
Collapse
Affiliation(s)
- Thomas Beyer
- QIMP Team, Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Währinger Gürtel 18-20/4L, 1090, Vienna, Austria.
| | - Luc Bidaut
- College of Science, University of Lincoln, Lincoln, UK
| | - John Dickson
- Institute of Nuclear Medicine, University College London Hospital, London, UK
| | - Marc Kachelriess
- Division of X-ray imaging and CT, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, DE, Germany
| | - Fabian Kiessling
- Institute for Experimental Molecular Imaging, University Clinic and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, DE, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Am Fallturm 1, 28359, Bremen, DE, Germany
| | - Rainer Leitgeb
- Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, AT, Austria
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lalith Kumar Shiyam Sundar
- QIMP Team, Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Währinger Gürtel 18-20/4L, 1090, Vienna, Austria
| | - Benjamin Theek
- Institute for Experimental Molecular Imaging, University Clinic and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, DE, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Am Fallturm 1, 28359, Bremen, DE, Germany
| | - Osama Mawlawi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| |
Collapse
|
43
|
Chen YH, Chen HT, Lee MC, Liu SH, Wang LY, Lue KH, Chan SC. Preoperative F-18 fluorocholine PET/CT for the detection of hyperfunctioning parathyroid glands in patients with secondary or tertiary hyperparathyroidism: comparison with Tc-99m sestamibi scan and neck ultrasound. Ann Nucl Med 2020; 34:527-537. [PMID: 32436180 DOI: 10.1007/s12149-020-01479-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 05/09/2020] [Indexed: 12/28/2022]
Abstract
OBJECTIVES Currently, neck ultrasound is the preferred preoperative imaging in patients with secondary/tertiary hyperparathyroidism, and the use of Tc-99m sestamibi scan is limited in these patients. We conducted this study to compare the diagnostic utilities of F-18 fluorocholine PET/CT, Tc-99m sestamibi scintigraphy, and neck ultrasound for localizing hyperfunctioning parathyroid glands in secondary/tertiary hyperparathyroidism. METHODS We prospectively enrolled 30 dialysis patients with a diagnosis of secondary/tertiary hyperparathyroidism; of these, 27 participants underwent all three imaging modalities, including dual-phase F-18 fluorocholine PET/CT (PET acquired 5 and 60 min after tracer injection), dual-phase Tc-99 m sestamibi SPECT/CT, and neck ultrasound. All patients underwent parathyroidectomy after imaging. We compared the lesion-based sensitivity, specificity, and accuracy of the three image tools using histopathology as the reference. RESULTS A total of 27 patients (107 lesions) underwent all three imaging modalities and entered the final analysis. The lesion-based sensitivities of F-18 fluorocholine PET/CT, Tc-99m sestamibi, and ultrasound were 86%, 55%, and 62%, respectively (both p < 0.001, when comparing F-18 fluorocholine PET/CT to Tc-99 m sestamibi scan and to ultrasound). F-18 fluorocholine PET/CT, Tc-99m sestamibi, and ultrasound had similar specificities of 93%, 80%, and 87%, respectively. The accuracy of F-18 fluorocholine PET/CT (87%) was significantly higher than that of Tc-99m sestamibi (59%) and ultrasound (65%) (both p < 0.001). F-18 fluorocholine PET/CT identified more hyperplastic glands than ultrasound in 52% (14/27) patients. The sensitivity of F-18 fluorocholine PET/CT reached 95% for hyperplastic parathyroid masses as low as 200 mg. CONCLUSIONS F-18 fluorocholine PET/CT shows superior accuracy over the conventional imaging modalities in patients with secondary or tertiary hyperparathyroidism. The combination of F-18 fluorocholine PET/CT and neck ultrasound may enable better surgical planning in these patients. REGISTRATION IDENTIFICATION NUMBER NCT04316845.
Collapse
Affiliation(s)
- Yu-Hung Chen
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan
| | - Hwa-Tsung Chen
- Department of Surgery, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan
| | - Ming-Che Lee
- Department of Surgery, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan
| | - Shu-Hsin Liu
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.,Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, Hualien, Taiwan
| | - Ling-Yi Wang
- Epidemiology and Biostatistics Consulting Center, Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.,Department of Pharmacy, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan
| | - Kun-Han Lue
- Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, Hualien, Taiwan
| | - Sheng-Chieh Chan
- Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.
| |
Collapse
|
44
|
Duatti A. Review on 99mTc radiopharmaceuticals with emphasis on new advancements. Nucl Med Biol 2020; 92:202-216. [PMID: 32475681 DOI: 10.1016/j.nucmedbio.2020.05.005] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 05/07/2020] [Accepted: 05/18/2020] [Indexed: 02/06/2023]
Abstract
Rapid imaging acquisition, high spatial resolution and sensitivity, powered by advancements in solid-state detector technology, are significantly changing the perspective of single photon emission tomography (SPECT). In particular, this evolutionary step is fueling a rediscovery of technetium-99m, a still unique radionuclide within the nuclear medicine scenario because of its ideal nuclear properties and easy preparation of its radiopharmaceuticals that does not require a costly infrastructure and complex procedures. Scope of this review is to show that the arsenal of technetium-99m radiopharmaceuticals is already equipped with imaging agents that may complement and integrate the role played by analogous tracers developed for positron emission tomography (PET). These include, in particular, somatostatin (SST) and prostate-specific membrane antigen (PSMA) receptor targeting agents, and a number of peptide-derived radiopharmaceuticals. Additionally, these recent technological developments, combined with new myocardial perfusion tracers having more favorable biodistribution and pharmacokinetic properties as compared to current commercial agents, may also reinvigorate the prevailing position still hold by technetium-99m radiopharmaceuticals in nuclear cardiology.
Collapse
Affiliation(s)
- Adriano Duatti
- Department of Chemical and Pharmaceutical Sciences, University of Ferrara, Ferrara, Italy.
| |
Collapse
|
45
|
Werner RA, Thackeray JT, Diekmann J, Weiberg D, Bauersachs J, Bengel FM. The Changing Face of Nuclear Cardiology: Guiding Cardiovascular Care Toward Molecular Medicine. J Nucl Med 2020; 61:951-961. [PMID: 32303601 DOI: 10.2967/jnumed.119.240440] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 03/25/2020] [Indexed: 01/01/2023] Open
Abstract
Radionuclide imaging of myocardial perfusion, function, and viability has been established for decades and remains a robust, evidence-based and broadly available means for clinical workup and therapeutic guidance in ischemic heart disease. Yet, powerful alternative modalities have emerged for this purpose, and their growth has resulted in increasing competition. But the potential of the tracer principle goes beyond the assessment of physiology and function, toward the interrogation of biology and molecular pathways. This is a unique selling point of radionuclide imaging, which has been underrecognized in cardiovascular medicine until recently. Now, molecular imaging methods for the detection of myocardial infiltration, device infection, and cardiovascular inflammation are successfully gaining clinical acceptance. This is further strengthened by the symbiotic quest of cardiac imaging and therapy for an increasing implementation of molecule-targeted procedures, in which specific therapeutic interventions require specific diagnostic guidance toward the most suitable candidates. This review will summarize the current advent of clinical cardiovascular molecular imaging and highlight its transformative contribution to the evolution of cardiovascular therapy beyond mechanical interventions and broad blockbuster medication, toward a future of novel, individualized molecule-targeted and molecular imaging-guided therapies.
Collapse
Affiliation(s)
- Rudolf A Werner
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany; and
| | - James T Thackeray
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany; and
| | - Johanna Diekmann
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany; and
| | - Desiree Weiberg
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany; and
| | - Johann Bauersachs
- Department of Cardiology and Angiology, Hannover Medical School, Hannover, Germany
| | - Frank M Bengel
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany; and
| |
Collapse
|
46
|
Slomka P. Leveraging latest computer science tools to advance nuclear cardiology. J Nucl Cardiol 2019; 26:1501-1504. [PMID: 31489585 DOI: 10.1007/s12350-019-01873-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 08/19/2019] [Indexed: 12/23/2022]
Abstract
Nuclear cardiology has unique advantages compared to other modalities, since the image analysis is already much more automated compared to what is currently clinically performed for CT, MR, or echocardiography imaging. The diverse image and clinical data available to assess coronary disease function, perfusion, flow, and associated CT data provide new opportunities, but logistically these additional assessments increase the overall complexity of SPECT/PET reporting, necessitating additional expertise and time. The advances in artificial intelligence software can be leveraged to obtain comprehensive risk predictions and diagnoses from all available data. They will allow nuclear cardiology to retain competitive edge compared to other modalities and improve its overall clinical utility. These tools will enhance diagnosis and risk prediction beyond what is possible by subjective visual analysis and mental integration of data by physicians.
Collapse
Affiliation(s)
- Piotr Slomka
- Department of Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Ste. A047N, Los Angeles, CA, 90048, USA.
| |
Collapse
|