OBJECTIVES: To examine the diagnostic accuracy of machine learning-based coronary CT angiography-derived fractional flow reserve (FFRCT) in diabetes mellitus (DM) patients.; METHODS: In total, 484 patients with suspected or known coronary artery disease from 11 Chinese medical centers were retrospectively analyzed. All patients underwent CCTA, FFRCT, and invasive FFR. The patients were further grouped into mild (25~49 %), moderate (50~69 %), and severe (≥ 70 %) according to CCTA stenosis degree and Agatston score < 400 and Agatston score ≥ 400 groups according to coronary artery calcium severity. Propensity score matching (PSM) was used to match DM (n =112) and non-DM (n =214) groups. Sensitivity, specificity, accuracy, and area under the curve (AUC) with 95 % confidence interval (CI) were calculated and compared.; RESULTS: Sensitivity, specificity, accuracy, and AUC of FFRCT were 0.79, 0.96, 0.87, and 0.91 in DM patients and 0.82, 0.93, 0.89, and 0.89 in non-DM patients without significant difference (all p > 0.05) on a per-patient level. The accuracies of FFRCT had no significant difference among different coronary stenosis subgroups and between two coronary calcium subgroups (all p > 0.05) in the DM and non-DM groups. After PSM grouping, the accuracies of FFRCT were 0.88 in the DM group and 0.87 in the non-DM group without a statistical difference (p > 0.05).; CONCLUSIONS: DM has no negative impact on the diagnostic accuracy of machine learning-based FFRCT.; KEY POINTS: ML-based FFRCT has a high discriminative accuracy of hemodynamic ischemia, which is not affected by DM. FFRCT was superior to the CCTA alone for the detection of ischemia relevance of coronary artery stenosis in both DM and non-DM patients. Coronary calcification had no significant effect on the diagnostic accuracy of FFRCT to detect ischemia in DM patients. © 2022. The Author(s), under exclusive licence to European Society of Radiology.

OBJECTIVE: To investigate the utility of coronary CT angiography-derived fractional flow reserve (FFRCT) and plaque progression in patients undergoing serial coronary CT angiography for predicting major adverse cardiovascular events (MACE).; METHODS: This retrospective study evaluated patients suspected or known coronary artery disease who underwent serial coronary CT angiography examinations between January 2006 and December 2017 and followed up until June 2019. The primary endpoint was MACE, defined as acute coronary syndrome, rehospitalization due to progressive angina, percutaneous coronary intervention, or cardiac death. FFRCT and plaque parameters were analyzed on a per-vessel and per-patient basis. Univariable and multivariable COX regression analysis determined predictors of MACE. The prognostic value of FFRCT and plaque progression were assessed in nested models.; RESULTS: Two hundred eighty-four patients (median age, 61 years (interquartile range, 54-70); 202 males) were evaluated. MACE was observed in 45 patients (15.8%, 45/284). By Cox multivariable regression modeling, vessel-specific FFRCT ≤ 0.80 was associated with a 2.4-fold increased risk of MACE (HR (95% CI): 2.4 (1.3-4.4); p = 0.005) and plaque progression was associated with a 9-fold increased risk of MACE (HR (95% CI): 9 (3.5-23); p < 0.001) after adjusting for clinical and imaging risk factors. FFRCT and plaque progression improved the prediction of events over coronary artery calcium (CAC) score and high-risk plaques (HRP) in the receiver operating characteristics analysis (area under the curve: 0.70 to 0.86; p = 0.002).; CONCLUSIONS: Fractional flow reserve and plaque progression assessed by serial coronary CT angiography predicted the risk of future MACE.; KEY POINTS: Vessel-specific CT angiography-derived fractional flow reserve (FFRCT) ≤ 0.80 and plaque progression improved the prediction of events over current risk factors. Major adverse cardiovascular events (MACE) significantly increased with the presence of plaque progression at follow-up stratified by the FFRCT change group. © 2021. European Society of Radiology.

Coronavirus disease 2019 (COVID-19) is a transmissible respiratory disease that was initially reported in Wuhan, China in December 2019. With the alarming levels of COVID-19 spread worldwide, the World Health Organization characterized COVID-19 as a pandemic. Over the past several months, chest CT has played a vital role in early identification, disease severity assessment, and dynamic disease course monitoring of COVID-19. The published data has enriched our knowledge on the etiology, epidemiology, clinical manifestations, and pathologic findings of COVID-19. Additionally, as the imaging spectrum of the disease continues to be defined, extrapulmonary infections or other complications will require further attention. This review aims to provide an updated framework and essential knowledge with which radiologists can better understand COVID-19.

The ongoing outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly throughout China and other countries, and has been characterized as a pandemic. With the strict prevention and control measures implemented by the Chinese government, the spread of the epidemic in China has come under preliminary control by the end of February, 2020, whereas the situation of some countries outside China is not optimistic and raises great public concern. In fighting COVID-19, radiologic examinations played a critical role in the early diagnosis of COVID-19, and could also help assess disease course and severity. There is an urgent need to share useful experience and effective measures internationally. This article outlines the collaborative actions and efforts by the Chinese radiology field and the situation of front-line health care workers in radiology departments to present the world with experiences and examples of Chinese radiology during the COVID-19 outbreak.

Contrast-induced acute kidney injury (CI-AKI) is the third most common hospital-acquired AKI after AKI induced by renal perfusion insufficiency and nephrotoxic drugs, taking great adverse effects on the prognosis and increasing hospital stay and medical cost. Diabetes nephropathy (DN) is a common chronic complication of DM (diabetes mellitus), and DN is an independent risk factor for chronic kidney disease (CKD) and CI-AKI. The incidence of CI-AKI significantly increases in patients with renal injury, especially in DM-related nephropathy. The etiology of CI-AKI is not fully clear, and research studies on how DM becomes a facilitated factor of CI-AKI are limited. This review describes the mechanism from three aspects. (1) Pathophysiological changes of CI-AKI in kidney under high-glucose status (HGS). HGS can enhance the oxidative stress and increase ROS which next causes stronger vessel constriction and insufficient oxygen supply in kidney via vasoactive substances. HGS also aggravates some ion pump load and the latter increases oxygen consumption. CI-AKI and HGS are mutually causal, making the kidney function continue to decline. (2) Immunological changes of DM promoting CI-AKI. Some innate immune cells and pattern recognition receptors (PRRs) in DM and/or DN may respond to some damage-associated molecular patterns (DAMPs) formed by CI-AKI. These effects overlap with some pathophysiological changes in hyperglycemia.. Signaling pathways related to both CI-AKI and DM. These pathways involved in CI-AKI are closely associated with apoptosis, inflammation, and ROS production, and some studies suggest that these pathways may be potential targets for alleviating CI-AKI. In conclusion, the pathogenesis of CI-AKI and the mechanism of DM as a predisposing factor for CI-AKI, especially signaling pathways, need further investigation to provide new clinical approaches to prevent and treat CI-AKI.

Intracranial aneurysms with subarachnoid hemorrhage lead to high morbidity and mortality. It is of critical importance to detect aneurysms, identify risk factors of rupture, and predict treatment response of aneurysms to guide clinical interventions. Artificial intelligence has received worldwide attention for its impressive performance in image-based tasks. Artificial intelligence serves as an adjunct to physicians in a series of clinical settings, which substantially improves diagnostic accuracy while reducing physicians? workload. Computer-assisted diagnosis systems of aneurysms based on MRA and CTA using deep learning have been evaluated, and excellent performances have been reported. Artificial intelligence has also been used in automated morphologic calculation, rupture risk stratification, and outcomes prediction with the implementation of machine learning methods, which have exhibited incremental value. This review summarizes current advances of artificial intelligence in the management of aneurysms, including detection and prediction. The challenges and future directions of clinical implementations of artificial intelligence are briefly discussed.

Contrast-induced acute kidney injury (CI-AKI) is the third most common hospital-acquired AKI after AKI induced by renal perfusion insufficiency and nephrotoxic drugs, taking great adverse effects on the prognosis and increasing hospital stay and medical cost. Diabetes nephropathy (DN) is a common chronic complication of DM (diabetes mellitus), and DN is an independent risk factor for chronic kidney disease (CKD) and CI-AKI. The incidence of CI-AKI significantly increases in patients with renal injury, especially in DM-related nephropathy. The etiology of CI-AKI is not fully clear, and research studies on how DM becomes a facilitated factor of CI-AKI are limited. This review describes the mechanism from three aspects. (1) Pathophysiological changes of CI-AKI in kidney under high-glucose status (HGS). HGS can enhance the oxidative stress and increase ROS which next causes stronger vessel constriction and insufficient oxygen supply in kidney via vasoactive substances. HGS also aggravates some ion pump load and the latter increases oxygen consumption. CI-AKI and HGS are mutually causal, making the kidney function continue to decline. (2) Immunological changes of DM promoting CI-AKI. Some innate immune cells and pattern recognition receptors (PRRs) in DM and/or DN may respond to some damage-associated molecular patterns (DAMPs) formed by CI-AKI. These effects overlap with some pathophysiological changes in hyperglycemia.. Signaling pathways related to both CI-AKI and DM. These pathways involved in CI-AKI are closely associated with apoptosis, inflammation, and ROS production, and some studies suggest that these pathways may be potential targets for alleviating CI-AKI. In conclusion, the pathogenesis of CI-AKI and the mechanism of DM as a predisposing factor for CI-AKI, especially signaling pathways, need further investigation to provide new clinical approaches to prevent and treat CI-AKI.

The ongoing outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly throughout China and other countries, and has been characterized as a pandemic. With the strict prevention and control measures implemented by the Chinese government, the spread of the epidemic in China has come under preliminary control by the end of February, 2020, whereas the situation of some countries outside China is not optimistic and raises great public concern. In fighting COVID-19, radiologic examinations played a critical role in the early diagnosis of COVID-19, and could also help assess disease course and severity. There is an urgent need to share useful experience and effective measures internationally. This article outlines the collaborative actions and efforts by the Chinese radiology field and the situation of front-line health care workers in radiology departments to present the world with experiences and examples of Chinese radiology during the COVID-19 outbreak.