It is possible to obtain accurate estimates of myocardial blood flow and flow reserve with a one-compartment model of (82)Rb kinetics and a nonlinear extraction function.

(82)Rb MFR is an independent predictor of 3-vessel CAD and provided added value to relative MPI. Clinical integration of this approach should be considered to enhance detection and risk assessment of patients with known or suspected CAD.

Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AIbased algorithms that enhance outcomes, quality, and efficiency. Moreover, a more holistic perspective of applications, opportunities, and challenges from a programmatic perspective contributes to ethical and sustainable implementation of AI solutions.

Patient body motion can produce MBF estimation errors up to 500%. To reduce these errors, new motion correction algorithms must be effective in identifying motion in the left/right direction, and in the mid-to-late time-frames, since these conditions produce the largest errors in MBF, particularly for high resolution PET imaging. Ideally, motion correction should be done before or during image reconstruction to eliminate PET-CTAC misalignment artifacts.

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Objective To compare myocardial blood flow (MBF) and myocardial flow reserve (MFR) estimates from 82Rb PET data using ten software packages (SPs): Carimas, Corridor4DM, FlowQuant, HOQUTO, ImagenQ, MunichHeart, PMOD, QPET, syngo MBF, and UW-QPP. Background It is unknown how MBF and MFR values from existing SPs agree for 82Rb PET. Methods Rest and stress 82Rb PET scans of 48 patients with suspected or known coronary artery disease (CAD) were analyzed in 10 centers. Each center used one of the 10 SPs to analyze global and regional MBF using the different kinetic models implemented. Values were considered to agree if they simultaneously had an intraclass correlation coefficient (ICC) > 0.75 and a difference < 20% of the median across all programs. Results The most common model evaluated was the one-tissue compartment model (1TCM) by Lortie et al. (2007). MBF values from seven of the eight software packages implementing this model agreed best (Carimas, Corridor4DM, FlowQuant, PMOD, QPET, syngoMBF, and UW-QPP). Values from two other models (El Fakhri et al. in Corridor4DM and Alessio et al. in UW-QPP) also agreed well, with occasional differences. The MBF results from other models (Sitek et al. 1TCM in Corridor4DM, Katoh et al. 1TCM in HOQUTO, Herrero et al. 2TCM in PMOD, Yoshida et al. retention in ImagenQ, and Lautamäki et al. retention in MunichHeart) were less in agreement with Lortie 1TCM values. Conclusions SPs using the same kinetic model, as described in Lortie et al. (2007), provided consistent results in measuring global and regional MBF values, suggesting they may be used interchangeably to process data acquired with a common imaging protocol.

Absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR) provide incremental diagnostic and prognostic information over relative perfusion alone. Recent development of dedicated cardiac SPECT cameras with better sensitivity and temporal resolution make dynamic SPECT imaging more practical. In this study, we evaluate the measurement of MBF using a multipinhole dedicated cardiac SPECT camera in a pig model of rest and transient occlusion at stress using 3 common tracers: 201 Tl, 99m Tc-tetrofosmin, and 99m Tc-sestamibi. Methods: Animals (n 5 19) were injected at rest/stress with 99m Tc radiotracers (370/1,100 MBq) or 201 Tl (37/110 MBq) with a 1-h delay between rest and dipyridamole stress. With each tracer, microspheres were injected simultaneously as the gold standard measurement for MBF. Dynamic images were obtained for 11 min starting with each injection. Residual resting activity was subtracted from stress data and images reconstructed with CT-based attenuation correction and energy window-based scatter correction. Dynamic images were processed with kinetic analysis software using a 1-tissue-compartment model to obtain the uptake rate constant K 1 as a function of microsphere MBF. Results: Measured extraction fractions agree with those obtained previously using ex vivo techniques. Converting K 1 back to MBF using the measured extraction fractions produced accurate values and good correlations with microsphere MBF: r 5 0.75-0.90 (P , 0.01 for all). The correlation in the MFR was between r 5 0.57 and 0.94 (P , 0.01). Conclusion: Noninvasive measurement of absolute MBF with stationary dedicated cardiac SPECT is feasible using common perfusion tracers. St udies using PET have demonstrated that absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR 5 stress/ rest MBF) provide incremental diagnostic and prognostic information over relative perfusion alone (1-4). Imaging of myocardial perfusion is much more commonly performed with SPECT than with PET, but MBF measurements are not typically acquired.Measuring MBF is difficult with standard SPECT cameras because of the need for attenuation and scatter correction and the need to rotate around the patient for 3-dimensional imaging. Recent studies have shown that it is possible to obtain an index of the MFR without a direct measure of MBF using a combination of dynamic planar followed by static SPECT acquisitions (5) and that this can provide some prognostic information (6). Other studies have demonstrated that rapid camera rotation can provide dynamic tomographic data and hence a measure of MFR (7) and the arterial input function (8), suggesting that accurate measures of MBF could be possible (9). The practicality of measuring MBF has increased greatly, however, with the advent of dedicated cardiac cameras.Dedicated cardiac cameras such as the DSPECT system (Spectrum Dynamics Medical Inc.) or the Discovery NM 530c/ 570c cameras (GE Healthcare) have greatly improved sensitivity and do not rotate around the patient (10). These features allow d...

The proposed method results in low operator-dependent variability, suitable for routine use.