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Updated: Jun 13, 2026
In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
An automatic method for quantification of myocardium at risk from myocardial perfusion SPECT in patients with acute
Helen Soneson1, Henrik Engblom, Erik Hedström
1Department of Clinical Physiology, Skåne University Hospital, Lund University, 221 85 Lund, Sweden.
Background:
In order to determine myocardial salvage, accurate quantification of myocardium at risk (MaR) is necessary. We present a validated novel automatic segmentation algorithm for quantification of MaR by myocardial perfusion SPECT (MPS) in patients with acute coronary occlusion.
Methods And Results:
Twenty-nine patients with coronary occlusion were injected with a perfusion tracer before reperfusion, and underwent rest MPS within 4 hours. The MaR was quantified using the proposed algorithm (Segment software), the software Quantitative Perfusion SPECT (QPS) and by manual segmentation. The Segment MaR algorithm used a threshold of 55% of maximal counts and an a priori model based on normal coronary artery perfusion territories. The MaR was 30 ± 10% left ventricular mass (%LVM) by manual segmentation, 31 ± 12%LVM by Segment, and 36 ± 14%LVM by QPS. There was a good agreement between automatic and manual segmentation for both of the algorithms with a lower bias for Segment (.8 ± 4.0%LVM) than for QPS (5.8 ± 5.8%LVM) when compared to manual segmentation.
Conclusions:
The Segment MaR algorithm can be used to correctly assess MaR from MPS images in patients with acute coronary occlusion without access to tracer-specific normal database. The MaR in relation to final infarct size enables determination of myocardial salvage.
Insights
A new automatic algorithm accurately quantifies myocardium at risk (MaR) using myocardial perfusion SPECT (MPS) in acute coronary occlusion patients. This method aids in determining myocardial salvage without needing tracer-specific databases.
Area of Science:
- Cardiology
- Nuclear Medicine
- Medical Imaging
Background:
- Accurate quantification of myocardium at risk (MaR) is crucial for determining myocardial salvage.
- Myocardial perfusion SPECT (MPS) is a key imaging modality in patients with acute coronary occlusion.
- Existing methods for MaR quantification may have limitations.
Purpose of the Study:
- To present and validate a novel automatic segmentation algorithm for MaR quantification using MPS.
- To assess the accuracy and agreement of the proposed algorithm compared to manual segmentation and another software (QPS).
- To evaluate the algorithm's utility in patients with acute coronary occlusion.
Main Methods:
- Developed and applied an automatic segmentation algorithm (Segment software) for MaR quantification in 29 patients with coronary occlusion.
- Patients underwent rest MPS within 4 hours of reperfusion.
- MaR was quantified using the Segment algorithm, QPS, and manual segmentation, with the Segment algorithm using a 55% threshold and an a priori model.
Main Results:
- The Segment MaR algorithm showed good agreement with manual segmentation, with a bias of 0.8 ± 4.0% LVM.
- Quantitative Perfusion SPECT (QPS) also showed agreement but with a higher bias of 5.8 ± 5.8% LVM compared to manual segmentation.
- The Segment algorithm provided MaR values (31 ± 12% LVM) comparable to manual segmentation (30 ± 10% LVM).
Conclusions:
- The Segment MaR algorithm reliably assesses MaR from MPS images in acute coronary occlusion.
- This automated method does not require a tracer-specific normal database.
- Accurate MaR assessment facilitates the determination of myocardial salvage by relating it to final infarct size.