To our knowledge, this is the first study that directly compares myocardial perfusion in static CT-MPI and 82Rb PET-MPI using prospective ECG-triggered axial cardiac CT protocol with semi-quantitative visual assessment with a widely available 64-detector CT scanner. This study also provides in-depth information about the CT-MPI image quality and artifacts including their distribution. Our study shows a moderate agreement between static CT-MPI and 82Rb PET-MPI (weighted kappa of 0.49, 95% CI of 0.28 to 0.70) and demonstrates good diagnostic performance of CT-MPI on qualitative and quantitative analyses at a per-person (89% SS, 58% SP, 71% accuracy AC) and a per-territory level (73% SS, 65% SP, 67% AC).

Other prior studies have compared CT-MPI and PET-MPI albeit with differing CT and PET methodologies. Williams et al. (2017) compared static whole-heart coverage CT-MPI determined perfusion defects with oxygen-15 labelled water PET determined myocardial blood flow (MBF). The authors reported excellent correlation between CT attenuation density and PET determined MBF (r = 0.579, P < 0.001). Others have utilized either dynamic (Kikuchi et al. 2014) or multiphase (Dantas et al. 2018) CT-MPI protocols to calculate MBF and have shown good correlation with 82Rb PET determined MBF. Our study extends the available evidence by demonstrating a moderate agreement between static CT-MPI and 82Rb PET-MPI based on a semi-quantitative visual assessment of myocardial segments for reversible perfusion defects.

Our findings lend support to the use of static CT-MPI with a semi-quantitative visual assessment in identifying hemodynamically significant CAD. This is important as a static CT-MPI protocol with a semi-quantitative visual assessment can be easily integrated into a reporting practice and also doesn’t have limitations of a dynamic CT-MPI protocols such as increased radiation exposure (Danad et al. 2016), longer duration of breath hold, need for whole-heart coverage CT scanner, and the need for analytical software for absolute MBF quantification (Koo et al. 2016).

Our study demonstrated a per-patient SS of 88.9%, a SP of 57.7% and 70.5% AC for CT-MPI based on a semi-quantitative visual assessment when compared to 82Rb PET-MPI as the reference standard. The per-patient AUC of 0.73 demonstrates a good ability of CT-MPI to discriminate between those with and without myocardial perfusion defects. We found that CT-MPI overestimated perfusion defects in the myocardium as the visually derived SSS and the resultant iTPD from CT-MPI were significantly higher than those derived from 82Rb PET-MPI (p < 0.0001). While the SRS was not significantly different, the same trend of higher measures was also noted using CT-MPI. Similarly, the Bland–Altman analysis also showed that CT-MPI overestimated perfusion defects and the Passing–Bablok test revealed that this overestimation progressively increased with an increase in perfusion abnormalities as identified by 82Rb PET. The overestimation of perfusion defects by CT-MPI is unlikely to be secondary to false positive defects related to artifacts (Blankstein et al. 2009). Of note, artifacts were identified in 27% of patients in our study who underwent stress CT-MPI. Most of these were noise artifacts (11%), and only 6% of beam hardening artifacts, which are known to mimic abnormal myocardial perfusion. The Likert scores for image quality were lower in the stress phase (score 4 or 5 in 66% of stress phase vs 94% of rest phase images) as expected. It seems unlikely that the relatively low number of beam hardening artifacts and image quality limitations could explain the differences in the measures of perfusion defects, as this trend was also noted in the rest studies. It is possible that the CT-MPI stress phase identified an excess of myocardial perfusion defects compared to 82Rb PET-MPI because of inherent higher spatial resolution (approximately 0.4 mm of CT compared to 0.7–0.9 mm of PET), higher contrast resolution and dynamic range of CT compared to a nuclear based method. Similar findings were described by Meinel et al. (2013), in a study of 55 patients comparing first-pass (static) dual energy CT with SPECT as the reference standard. In this study, almost one-half of defects that were reversible at SPECT were classified as fixed, suggesting that the higher sensitivity of rest CT perfusion could be due to its ability to detect small subendocardial perfusion abnormalities. In fact, it is well described that the presence of perfusion abnormalities at rest CT-MPI that correlate with decreased myocardial flow and myocardial ischemia are probably secondary to the vasodilatory effects of nitroglycerin and iodine contrast inducing a mild hyperemic state (Williams et al. 2017; Meinel et al. 2013; Iwasaki and Matsumoto 2011; Kachenoura et al. 2009; Gupta et al. 2013; Osawa et al. 2014, 2016; Han et al. 2018). However, given a lack of invasive cardiac catheterization correlation in all cases, it is possible that some of these cases could be false positives. Therefore, it may be prudent in clinical practice to correlate CT-MPI findings with CCTA or FFRCT to offset the risk of false positives.

On a per-territory level, the current study demonstrated a good SS of 73.1%, 65.1% SP and 67.7% AC. Of note, this is a small increase in SP from the per-patient value (57.7%) and decrease compared to per-patient SS (88.9%). This is an important result which demonstrates a difference in the diagnostic performance of a semi-quantitative visual assessment of CT-MPI using a per-person or a per-territory methodology. Given the good per-patient SS (88.9%) and the moderately low negative likelihood ratio (0.19) relative to 82Rb PET, using CT-MPI with a semi-quantitative visual per-person assessment may be useful in ruling out functionally significant CAD, which would be especially valuable in those with a high pretest probability. On the other hand, a per-territory assessment may be useful in ruling in functionally significant CAD given the moderate SP (65.1%) and positive likelihood ratio (2.15), which would be valuable for those with low pretest probabilities.

It is interesting to note a moderate agreement (weighted kappa 0.49) and a markedly higher SS were recorded for CT-MPI reader A compared to reader B (88.9% vs 55.6%) on a per-patient basis for identification of myocardial perfusion defects. This highlights the issue of inter-reader variability in visual assessment of static CT-MPI. While this result could possibly be explained by the difference in experience of the two CT-MPI readers (Lubbers et al. 2011), it also highlights the need to further investigate visual assessment methods that would reduce inter-reader variability. Nonetheless, the inter-reader variability in our study is reflective of the “real-world” scenario with CT-MPI image readers of varying degrees of experience.

Static CT-MPI addresses a number of the limitations of other MPI modalities. The wide availability of CT scanners compared to PET and CMR, the higher spatial resolution compared to SPECT, and the ability of CT-MPI to simultaneously provide information regarding the functional significance and anatomical assessment of CAD in a short examination duration place CT-MPI favorably compared to the other modalities (Yang et al. 2017). Considering the relative ease with which a visual based semi-quantitative MPI assessment can be integrated into a routine clinical practice, the use of such methodology might prove beneficial to assess the functional significance of CAD. There is emerging data on the added value of integrating CT-MPI with CCTA and FFRCT to provide incremental diagnostic accuracy, specifically in borderline lesions with FFRCT between 0.7 and 0.8 (Coenen et al. 2017; Pontone et al. 2019b). As per the 2020 Society of Cardiovascular Computed Tomography expert consensus, the use of CT-MPI as an adjunct for patients having CCTA is recommended for those at high risk of obstructive CAD or if stenoses have indeterminate functional significance (Patel et al. 2020). Furthermore, stress CT-MPI may be combined with FFRCT, as theoretically the former may be more representative of the contribution of epicardial stenosis, microvascular disease and myocardial mass to ischemia.

Multiple studies have compared FFRCT with static CT-MPI in their ability to provide incremental diagnostic value to CCTA in detecting hemodynamically significant stenoses. These studies have shown conflicting results, possibly due to differing CT-MPI acquisition modalities, the type of scanners used and other study limitations including small sample sizes (Pontone et al. 2019a; Yang et al. 2017; Guo et al. 2021; Ihdayhid et al. 2018; Ko et al. 2019). Furthermore, a recent meta-analysis by Celeng et al. (2019), showed similar diagnostic performance of CT-MPI (SS 0.94, 95% CI 0.91–0.97; SP 0.48, 95% CI 0.37–0.59, n = 3101) and FFRCT (SS 0.83, 95% CI 0.71–0.92; SP 0.79, 95% CI 0.68–0.87, n = 697) on a per-patient basis. CT-MPI can overcome FFRCT limitations such as requirement for off-site interpretation, evaluation of coronary stents and epicardial vessels with complex plaque and anatomy. Furthermore, FFRCT uses CCTA images as boundary conditions for computation fluid dynamic analysis of the coronary tree, and therefore the technique is impaired with the presence of artifacts in the coronary artery images that limit coronary segmentation, such as motion, steps, severe calcification or bypass grafts, factors that do not affect the performance of CT-MPI. Thus, CCTA and CT-MPI can be performed using a 64-detector width MDCT with static low dose protocol, FFRCT evaluation for CCTA datasets may not be feasible in a substantial number of cases (Rochitte and Magalhães 2019).

This study was a single-center, prospective study with a limited sample size and hence, studies in larger cohorts are needed to validate our findings. The large patient size in the study (average BMI 30.8 ± 6.7), the use of 64-detector row CT scanner and a low radiation dose protocol using prospective ECG-gated rest and stress acquisitions may have affected CT results unfavorably. However, despite these technical limitations, our study shows that CT-MPI is feasible and has good accuracy. We used a “rest-first” protocol for CT-MPI which could preclude our ability to identify low-attenuation perfusion defects, since iodine contrast can be retained in small subendocardial infarcts (increasing myocardial density) and theoretically decrease the sensitivity to detect perfusion defects in the stress phase (Koo et al. 2016). However, contrast contamination is likely to affect results for short inter-scan intervals of less than approximately 20 min. In our study an interval of 20 min was used, which should have been sufficient to allow for adequate washout of most of the myocardial contrast. Furthermore, theophyllines were withheld for 24 h more for 82Rb PET-MPI than CT-MPI in our study. The difference in duration of withholding theophyllines prior to 82Rb PET-MPI and CT-MPI in our study was driven by our local protocol. As the duration in both cases was 24 h or more (i.e. minimum required), additional 24 h of theophylline free period prior to 82Rb PET-MPI would have not caused any significant effect on study results (Salcedo and Kern 2009). Metoprolol was given orally before the rest CT-MPI. This may have caused some reduction in CT-MPI sensitivity.

Lastly, our study used 82Rb tracer for PET, which has a lower image resolution, a lower myocardial extraction fraction compared to Oxygen-15 water tracer (Maddahi and Packard 2014). However, given the need for an onsite-cyclotron for producing Oxygen-15 water tracers, most PET-MPIs are performed using Rb tracers (Takx et al. 2015) thus, reiterating the value of our study for current clinical practice. To our knowledge, nitrogen-13-ammonia PET has not been compared to CT-MPI.

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