Background: The diagnostic accuracy of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFR-CT) needs to be further improved despite promising results available in the literature. While an innovative myocardial computed tomographic perfusion (CTP)-derived fractional flow reserve (CTP-FFR) model has been initially established, the feasibility of CTP-FFR to detect coronary artery ischemia in patients with suspected coronary artery disease (CAD) has not been proven. Methods: This retrospective study included 93 patients (a total of 103 vessels) who received CCTA and CTP for suspected CAD. Invasive coronary angiography (ICA) was performed within 2 weeks after CCTA and CTP. CTP-FFR, CCTA (stenosis ≥ 50% and ≥70%), ICA, FFR-CT and CTP were assessed by independent laboratory experts. The diagnostic ability of the CTP-FFR grouped by quantitative coronary angiography (QCA) in mild (30–49%), moderate (50–69%) and severe stenosis (≥70%) was calculated. The effect of calcification of lesions, grouped by FFR on CTP-FFR measurements, was also assessed. Results: On the basis of per-vessel level, the AUCs for CTP-FFR, CTP, FFR-CT and CCTA were 0.953, 0.876, 0.873 and 0.830, respectively (all p < 0.001). The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of CTP-FFR for per-vessel level were 0.87, 0.88, 0.87, 0.85 and 0.89 respectively, compared with 0.87, 0.54, 0.69, 0.61, 0.83 and 0.75, 0.73, 0.74, 0.70, 0.77 for CCTA ≥ 50% and ≥70% stenosis, respectively. On the basis of per-vessel analysis, CTP-FFR had higher specificity, accuracy and AUC compared with CCTA and also higher AUC compared with FFR-CT or CTP (all p < 0.05). The sensitivity and accuracy of CTP-FFR + CTP + FFR-CT were also improved over FFR-CT alone (both p < 0.05). It also had improved specificity compared with FFR-CT or CTP alone (p < 0.01). A strong correlation between CTP-FFR and invasive FFR values was found on per-vessel analysis (Pearson’s correlation coefficient 0.89). The specificity of CTP-FFR was higher in the severe calcification group than in the low calcification group (p < 0.001). Conclusions: A novel CTP-FFR model has promising value to detect myocardial ischemia in CAD, particularly in mild-to-moderate stenotic lesions.

Type 2 diabetes mellitus (T2DM) is associated with a high prevalence of diastolic dysfunction and congestive heart failure. A potential contributing factor is the accelerated accumulation of diffuse myocardial fibrosis and stiffness. Novel cardiac magnetic resonance (CMR) imaging techniques can identify both myocardial fibrosis and contractility quantitatively. This study aimed to investigate the dynamic characteristics of the myocardial strain and altered extracellular volume (ECV) fraction as determined by 7.0 T CMR in T2DM mice. C57Bl/6J mice were randomly divided into T2DM (fed a high-fat diet) and control (fed a normal diet) groups. They were scanned on 7.0 T MRI every 4 weeks until the end of week 24. The CMR protocol included multi-slice cine imaging to assess left ventricle strain and strain rate, and pre- and post-contrast T1 mapping images to quantify ECV. The ECV in the T2DM mice was significantly higher (p < 0.05) than that in the control group since week 12 with significantly impaired myocardial strain (p < 0.05). A significant linear correlation was established between myocardial strain and ECV (p < 0.001) and left ventricular-ejection fraction and ECV (p = 0.003). The results suggested that CMR feature tracking-derived myocardial strain analysis can assess functional abnormalities that may be associated with ECM alterations in diabetic cardiomyopathy, contributing to the study of diabetic therapy effects.

With the growing demand for coronary artery visualization and the diagnosis of coronary artery disease, noninvasive coronary imaging modalities have gained significance. Coronary magnetic resonance angiography (CMRA) is a promising technique as it is noninvasive and does not involve ionizing radiation or iodinated contrast agents. Although certain limitations in this technology have prevented its application as a first-line clinical imaging modality, its immense developmental potential has positioned it as a focal point of research. This review discusses the advancements in CMRA across multiple technical domains—including motion correction, imaging acceleration, and integration with artificial intelligence—as well as its current clinical status and future prospects.