Quantification with normal limits: New cameras and low-dose imaging

Impact of non-specific normal databases on perfusion quantification of low-dose myocardial SPECT studies

AIM

To evaluate the impact of non-specific normal databases on the percent summed rest score (SR%) and stress score (SS%) from simulated low-dose SPECT studies by shortening the acquisition time/projection.

METHODS

Forty normal-weight and 40 overweight/obese patients underwent myocardial studies with a conventional gamma-camera (BrightView, Philips) using three different acquisition times/projection: 30, 15, and 8 s (100%-counts, 50%-counts, and 25%-counts scan, respectively) and reconstructed using the iterative algorithm with resolution recovery (IRR) AstonishTM (Philips). Three sets of normal databases were used: (1) full-counts IRR; (2) half-counts IRR; and (3) full-counts traditional reconstruction algorithm database (TRAD). The impact of these databases and the acquired count statistics on the SR% and SS% was assessed by ANOVA analysis and Tukey test (P < 0.05).

RESULTS

Significantly higher SR% and SS% values (> 40%) were found for the full-counts TRAD databases respect to the IRR databases. For overweight/obese patients, significantly higher SS% values for 25%-counts scans (+19%) are confirmed compared to those of 50%-counts scan, independently of using the half-counts or the full-counts IRR databases.

CONCLUSIONS

AstonishTM requires the adoption of the own specific normal databases in order to prevent very high overestimation of both stress and rest perfusion scores. Conversely, the count statistics of the normal databases seems not to influence the quantification scores.

Recent advances in cardiac SPECT instrumentation and imaging methods

Cardiac SPECT continues to play a critical role in detecting and managing cardiovascular disease, in particularly coronary artery disease (CAD) (Jaarsma et al 2012 J. Am. Coll. Cardiol. 59 1719-28), (Agostini et al 2016 Eur. J. Nucl. Med. Mol. Imaging 43 2423-32). While conventional dual-head SPECT scanners using parallel-hole collimators and scintillation crystals with photomultiplier tubes are still the workhorse of cardiac SPECT, they have the limitations of low photon sensitivity (~130 count s^-1 MBq^-1), poor image resolution (~15 mm) (Imbert et al 2012 J. Nucl. Med. 53 1897-903), relatively long acquisition time, inefficient use of the detector, high radiation dose, etc. Recently our field observed an exciting growth of new developments of dedicated cardiac scanners and collimators, as well as novel imaging algorithms for quantitative cardiac SPECT. These developments have opened doors to new applications with potential clinical impact, including ultra-low-dose imaging, absolute quantification of myocardial blood flow (MBF) and coronary flow reserve (CFR), multi-radionuclide imaging, and improved image quality as a result of attenuation, scatter, motion, and partial volume corrections (PVCs). In this article, we review the recent advances in cardiac SPECT instrumentation and imaging methods. This review mainly focuses on the most recent developments published since 2012 and points to the future of cardiac SPECT from an imaging physics perspective.

Novel SPECT Technologies and Approaches in Cardiac Imaging

Recent novel approaches in myocardial perfusion single photon emission CT (SPECT) have been facilitated by new dedicated high-efficiency hardware with solid-state detectors and optimized collimators. New protocols include very low-dose (1 mSv) stress-only, two-position imaging to mitigate attenuation artifacts, and simultaneous dual-isotope imaging. Attenuation correction can be performed by specialized low-dose systems or by previously obtained CT coronary calcium scans. Hybrid protocols using CT angiography have been proposed. Image quality improvements have been demonstrated by novel reconstructions and motion correction. Fast SPECT acquisition facilitates dynamic flow and early function measurements. Image processing algorithms have become automated with virtually unsupervised extraction of quantitative imaging variables. This automation facilitates integration with clinical variables derived by machine learning to predict patient outcome or diagnosis. In this review, we describe new imaging protocols made possible by the new hardware developments. We also discuss several novel software approaches for the quantification and interpretation of myocardial perfusion SPECT scans.