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AlJaroudi WA, Hage FG. Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2022: single photon emission computed tomography. J Nucl Cardiol 2023; 30:452-478. [PMID: 36797458 DOI: 10.1007/s12350-023-03216-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 01/11/2023] [Indexed: 02/18/2023]
Abstract
In this review, we will summarize a selection of articles on single-photon emission computed tomography published in the Journal of Nuclear Cardiology in 2022. The aim of this review is to concisely recap major advancements in the field to provide the reader a glimpse of the research published in the journal over the last year. This review will place emphasis on myocardial perfusion imaging using single-photon emission computed tomography summarizing advances in the field including in prognosis, non-perfusion variables, attenuation compensation, machine learning and camera design. It will also review nuclear imaging advances in amyloidosis, left ventricular mechanical dyssynchrony, cardiac innervation, and lung perfusion. We encourage interested readers to go back to the original articles, and editorials, for a comprehensive read as necessary but hope that this yearly review will be helpful in reminding readers of articles they have seen and attracting their attentions to ones they have missed.
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Affiliation(s)
- Wael A AlJaroudi
- Division of Cardiovascular Medicine, Augusta University, Augusta, GA, USA
| | - Fadi G Hage
- Division of Cardiovascular Disease, Department of Medicine, University of Alabama at Birmingham, GSB 446, 1900 University BLVD, Birmingham, AL, 35294, USA.
- Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA.
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Xu Z, Tang H, Malhotra S, Dong M, Zhao C, Ye Z, Zhou Y, Xu S, Li D, Wang C, Zhou W. Three-dimensional Fusion of Myocardial Perfusion SPECT and Invasive Coronary Angiography Guides Coronary Revascularization. J Nucl Cardiol 2022; 29:3267-3277. [PMID: 35194752 DOI: 10.1007/s12350-022-02907-8] [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: 11/20/2021] [Accepted: 01/06/2022] [Indexed: 01/18/2023]
Abstract
BACKGROUND SPECT myocardial perfusion imaging (SPECT MPI) and invasive coronary angiography (ICA) provide complementary clinical information in the diagnosis of coronary artery disease (CAD). We have developed an approach for 3D fusion of perfusion data from SPECT MPI and coronary anatomy from ICA. In this study, we aimed to evaluate its clinical value when compared to the traditional side-by-side readings. METHODS Thirty-six CAD patients who had at least one stenosis ≥ 50% were retrospectively enrolled. Based on the presence of a perfusion defect in a territory subtended by a coronary vessel, all vessels were classified as matched, unmatched, or normal groups via both the fusion and side-by-side analysis. The treatments recommended by the fusion and side-by-side analysis were compared with those that the patients received. Major adverse cardiac events (MACE), defined as all-cause death, myocardial infarction, unstable angina requiring hospitalization, and unplanned revascularization, were assessed. RESULTS The overall vessel-based concordance was 78.7% between the fusion and side-by-side analysis. Compared with the side-by-side analysis, 23 coronary arteries (29 equivocal segments) of 19 patients were reclassified via fusion of data. In the matched, unmatched, and normal groups, the numbers of vessels with hemodynamically significant stenosis which caused reversible defect were 37 vs 53, 28 vs 14, and 43 vs 41 (P < .01) when comparing the side-by-side analysis with the fusion, and the revascularization ratios per vessel were 69% vs 88%, 29% vs 10%, and 2% vs 2% between them. During the five-year follow-up, 8 patients (22.2%) experienced MACE. Patients who received the same treatment as the guidance of 3D fusion results (n = 22) had superior outcomes when compared with those who did not (n = 14) (P < .01). CONCLUSIONS Compared with the side-by-side analysis, the 3D fusion of SPECT MPI and ICA provided incremental diagnostic and prognostic value.
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Affiliation(s)
- Zhihui Xu
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Gulou, Nanjing, 210000, China
| | - Haipeng Tang
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
| | - Saurabh Malhotra
- Division of Cardiology, Cook County Health and Hospitals System, Chicago, IL, 60612, USA
- Division of Cardiology, Rush Medical College, Chicago, IL, 60612, USA
| | - Minghao Dong
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, Henan, China
| | - Chen Zhao
- Department of Applied Computing, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA
| | - Zekang Ye
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Gulou, Nanjing, 210000, China
| | - Ying Zhou
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Gulou, Nanjing, 210000, China
| | - Shun Xu
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Gulou, Nanjing, 210000, China
| | - Dianfu Li
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Gulou, Nanjing, 210000, China
| | - Cheng Wang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Gulou, Nanjing, 210000, China.
| | - Weihua Zhou
- Department of Applied Computing, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA.
- Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, Houghton, MI, 49931, USA.
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