Caffeine consumption before adenosine stress myocardial perfusion imaging (MPI) is known to affect the hemodynamic response and, thus, reduce the stress myocardial blood flow (MBF) and myocardial flow reserve (MFR) assessments. However, it is not clear if any sex-specific differences in the hemodynamic response after caffeine consumption exist. This study aimed to evaluate if such differences exist and, if so, their impact on MBF and MFR assessments. Methods: This study comprised 40 healthy volunteers (19 women). All volunteers underwent 4 serial rest/stress MPI sessions using ⁸²Rb; 2 sessions were acquired without controlled caffeine consumption, and 2 sessions after oral ingestion of either 100 and 300 mg of caffeine or 200 and 400 mg of caffeine. For the caffeine imaging sessions, caffeine was ingested orally 1 h before the MPI scan. Results: Increase in plasma caffeine concentration (PCC) (mg/L) after consumption of caffeine was larger in women (MPI session without caffeine vs. MPI session with caffeine: women = 0.3 ± 0.2 vs. 5.4 ± 5.1, men = 0.1 ± 0.2 vs. 2.7 ± 2.6, both P < 0.001). Caffeine consumption led to reduced stress MBF and MFR assessments for men whereas no changes were reported for women (women [PCC < 1 mg/L vs. PCC ≥ 1 mg/L]: stress MBF = 3.3 ± 0.6 vs. 3.0 ± 0.8 mL/g/min, P = 0.07; MFR = 3.7 ± 0.6 vs. 3.5 ± 1.0, P = 0.35; men [PCC < 1 mg/L vs. PCC ≥ 1 mg/L]: stress MBF = 2.7 ± 0.7 vs. 2.1 ± 1.0 mL/g/min, P = 0.005; MFR = 3.8 ± 1.0 vs. 3.1 ± 1.4, P = 0.018). Significant differences in the stress MBF were observed for the 2 sexes (both P ≤ 0.001), whereas similar MFR was reported (both P ≥ 0.12). Conclusion: Associations between increases in PCC and reductions in stress MBF and MFR were observed for men, whereas women did not have the same hemodynamic response. Stress MBF was affected at lower PCCs in men than women. Visual Abstract

¹⁸F-sodium fluoride (¹⁸F-NaF) positron emission tomography (PET) has emerged as a promising noninvasive imaging tool for the assessment of active calcification processes in coronary artery disease. ¹⁸F-NaF uptake colocalizes to high-risk and ruptured atherosclerotic plaques. Most recently, ¹⁸F-NaF coronary uptake was shown to be a robust and independent predictor of myocardial infarction in patients with advanced coronary artery disease. In this review, we provide an overview of the advances in coronary ¹⁸F-NaF imaging. In particular, we discuss the recently developed and validated motion correction techniques which address heart contractions, tidal breathing, and patient repositioning during the prolonged PET acquisitions. Additionally, we discuss a novel quantification approach—the coronary microcalcification activity (which has been inspired by the widely employed method in oncology total active tumor volume measurement). This new method provides a single number encompassing ¹⁸F-NaF activity within the entire coronary vasculature rather than just information regarding a single area of most intense tracer uptake.

Background Left ventricular ejection fraction (LVEF) estimation using adenosine stress myocardial perfusion imaging (MPI) can be challenging. The short half-life of adenosine and the guideline-recommended adenosine infusion stop during Rubidium-82 acquisition protocol may affect the accuracy and repeatability of the LVEF measures. Methods This study comprised 25 healthy volunteers (median age 23 years) who underwent repeat myocardial perfusion imaging (MPI) sessions employing Rubidium-82 PET/CT. A guideline-recommended reconstruction protocol was used for both rest and adenosine stress MPI (150-360 s post-radiotracer injection, standard_recon). For the stress MPI protocol, two additional reconstruction protocols were considered; one was employing 60 seconds data (150-210 seconds, short_fixed) and the other a dynamic frame window based on the bolus arrival of Rubidium-82 in the heart until 210 seconds (x-210 seconds, short_individual). We report rest and stress LVEF, the LVEF reserve, and the LVEF reserve repeatability. Results Differences in the LVEF assessments were observed between the guideline recommended and alternative reconstruction protocol (LVEF stress MPI: standard_recon = 68 ± 7%, short_fixed = 71 ± 7% (P = .08), short_individual = 72 ± 7% (P = .04)), and the LVEF reserve was reduced for the guideline-recommended protocol (standard_recon = 7.8 ± 3.5, short_fixed = 10.1 ± 3.7, short_individual = 10.5 ± 3.6, all P < .001). The best repeatability measures were obtained for the short_individual protocol (repeatability: standard_recon = 45.3%, short_fixed = 41.2%, short_individual = 31.7%). Conclusion We recommend using the short_individual reconstruction protocol for improved LVEF repeatability and reserve assessment. Alternatively, in centers with limited technical support we recommend the use of the short_fixed protocol.

Aims This study aimed to investigate the potential of different markers to identify adequate stressing in subjects with and without caffeine intake prior to Rubidium-82 myocardial imaging. Methods and Results This study comprised 40 healthy subjects who underwent four serial Rubidium-82 rest/adenosine stress MPI; two with 0mg caffeine consumption (baseline MPIs) and two with controlled consumption of caffeine (arm 1: 100 and 300mg, or arm 2: 200 and 400mg). We report the sensitivity and specificity of seven markers ability to predict adequate adenosine-induced hyperemic response: (1) the splenic response ratio (SRR); (2) splenic stress-to-rest intensity ratios (SIR); (3) changes in heart rate (ΔHR); (4) percentwise change in heart rate (Δ%HR); (5) changes in the rate pressure product (ΔRPP); (6) changes in the systolic blood pressure (ΔSBP); and (7) changes in the cardiovascular resistance (ΔCVR). Adequate stressing was determined as stress myocardial blood flow > 3ml/g/min and a corresponding myocardial flow reserve >68% of the individual maximum myocardial flow reserve obtained in the baseline MPIs. Results 129 MPI sessions (obtained in 39 subjects) were considered for this study. The following sensitivities were obtained: SSR = 72.7%, SIR = 63.6%, ΔHR = 45.5%, Δ%HR = 77.3%, ΔRPP = 54.5%, ΔSBP = 47.7%, and ΔCVR =40.9%, while the specificities were SSR = 80.9%, SIR = 85.0%, ΔHR = 90.4%, Δ%HR = 81.6%, ΔRPP=81.1%, ΔSBP = 86.4%, and ΔCVR =90.4%. Conclusion The image-derived and physiological markers all provide acceptable sensitivities and specificities when patients follow the caffeine pausation before MPI. However, their use warrants great care when caffeine consumption cannot be ruled out.

The objectives of our study were to (a) evaluate the feasibility of using 3D printed phantoms in magnetic resonance imaging (MR) in assessing the robustness and repeatability of radiomic parameters and (b) to compare the results obtained from the 3D printed phantoms to metrics obtained in biological phantoms. To this end, three different 3D phantoms were printed: a Hilbert cube (5 × 5 × 5 cm³) and two cubic quick response (QR) code phantoms (a large phantom (large QR) (5 × 5 × 4 cm³) and a small phantom (small QR) (4 × 4 × 3 cm³)). All 3D printed and biological phantoms (kiwis, tomatoes, and onions) were scanned thrice on clinical 1.5 T and 3 T MR with 1 mm and 2 mm isotropic resolution. Subsequent analyses included analyses of several radiomics indices (RI), their repeatability and reliability were calculated using the coefficient of variation (CV), the relative percentage difference (RPD), and the interclass coefficient (ICC) parameters. Additionally, the readability of QR codes obtained from the MR images was examined with several mobile phones and algorithms. The best repeatability (CV ≤ 10%) is reported for the acquisition protocols with the highest spatial resolution. In general, the repeatability and reliability of RI were better in data obtained at 1.5 T (CV = 1.9) than at 3 T (CV = 2.11). Furthermore, we report good agreements between results obtained for the 3D phantoms and biological phantoms. Finally, analyses of the read-out rate of the QR code revealed better texture analyses for images with a spatial resolution of 1 mm than 2 mm. In conclusion, 3D printing techniques offer a unique solution to create textures for analyzing the reliability of radiomic data from MR scans.

The image quality and quantitative accuracy of ⁸²Rb myocardial perfusion imaging (MPI) using PET is challenged by the extensive positron range (PR) effects, with the PR of ⁸²Rb being about 7 mm in soft tissues. This study explored the feasibility of applying postacquisition PR correction (PRC) to routine ⁸²Rb PET/CT MPI acquisitions and assessed its impact on diagnostic accuracy and image quality. Methods: We implemented a PRC method adjusted to ⁸²Rb into a vendor-provided reconstruction toolbox, using tissue-specific corrections for soft tissue, bone, and air/lungs. The PRC was evaluated in 2 cohorts: the first comprised 25 healthy volunteers who underwent repeated ⁸²Rb MPI within 2 wk, and the second included 66 patients with known or suspected coronary artery disease. We measured the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for the volunteer cohort. In the patient cohort, the impact of PRC was evaluated as changes in the area under the receiver operating characteristic curve (AUC), using fractional flow reserve as the gold standard (values < 80% were considered significantly reduced). We calculated AUCs for stress and ischemic total perfusion deficits. Results: In the volunteer cohort, PRC-based reconstructions (standard reconstruction [STD] + PRC) demonstrated significantly improved SNR and CNR compared with STD, with median increases of 22% and 47% for SNR and CNR, respectively (P < 0.05). For the patient cohort, comparable AUCs were reported for STD- versus PRC-based reconstructions (stress total perfusion deficits, 0.84 vs. 0.83 [P = 0.49]; ischemic total perfusion deficits, 0.87 vs. 0.87 [P = 0.80]). Conclusion: PRC significantly enhances SNR and CNR compared with STD without affecting the diagnostic accuracy of the scans. Given the significantly improved image quality, PRC may be recommended for MPI using ⁸²Rb PET/CT clinical-routine-assessment interpretation of TPD. Visual Abstract