CCTA-Derived Fat Attenuation Index Predict Future Percutaneous Coronary Intervention.

OBJECTIVES: This study aims to investigate the differences in plaque characteristics and fat attenuation index (FAI) between in patients who received revascularization versus those who did not receive revascularization and examine whether the machine-learning (ML) based model constructed by plaque characteristics and FAI can predict revascularization. MATERIALS & METHODS: This study was a post hoc analysis of a prospective single-center registry of sequential patients undergoing CCTA, referred from inpatient and emergency department settings (n = 261, 63 years ± 8; 188 men). The primary outcome was revascularization by percutaneous coronary revascularization. The CTA images were analyzed by experienced radiologists using a dedicated workstation in a blinded fashion. The ML-based model was automatically computed. RESULTS: The study cohort consisted of 261 subjects. Revascularization was performed in 105 subjects. Patients receiving revascularization had higher FAI value (67.35±5.49 Hu vs -80.10±7.75 Hu, p < 0.001) as well as higher plaque length, calcified, lipid and fibrous plaque burden and volume. When FAI was incorporated into a ML risk model based on plaque characteristics to predict revascularization, the area under the curve increased from 0.84 (95% CI: 0.68-0.99) to 0.95 (95% CI: 0.88-1.00). CONCLUSION: ML-algorithms based on FAI and characteristics could help improve the prediction of future revascularization and identify patients likely to receive revascularization. ADVANCES IN KNOWLEDGE: Pre-procedural FAI could help guide revascularization in symptomatic CAD patients.

Correlation between cancer-related cognitive impairment and resting cerebral glucose metabolism in patients with ovarian cancer.

Background: An increasing number of research have applied neuroimaging techniques to explore the potential neurobiological mechanism of Cancer-related cognitive impairment (CRCI). Purpose: To explore the correlation between resting brain glucose metabolism and CRCI using 18F-FDG PET/CT in ovarian cancer (OC) patients. Methods: From December 2021 to March 2022, 38 patients with OC were selected as the study group, and 38 healthy women of the same age (±1 year) who underwent routine physical examination using PET/CT were selected as the control group. Patients received further assessment with the Montreal Cognitive Assessment Scale (MoCA) and Perceived Deficit Questionnaire (PDQ). Independent sample t-test and Spearman correlation were conducted for data analysis. Results: The resting brain glucose metabolism in the OC group was significantly lower than in the healthy controls. 60.52 % patients had neuropsychological impairment and retrospective memory were the most serious perceived cognitive impairments. The resting brain glucose metabolism in OC patients did not significantly correlate with neuropsychological performance but had significant positive correlation with subjective cognitive evaluation. Discussion: Resting glucose metabolism was low in OC patients and associated with subjective cognitive impairment but not objective neuropsychological test results. 18F-FDG PET/CT can be used to evaluate brain function in OC patients and provide reliable imaging indicators for early recognition of and intervention for changes in cognitive function.

Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease.

OBJECTIVES: To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis. METHODS: Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference. RESULTS: The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01). CONCLUSION: ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis. CLINICAL RELEVANCE STATEMENT: ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other. KEY POINTS: • Both machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.

PPARγ Agonist Rosiglitazone and Antagonist GW9662: Antihypertensive Effects on Chronic Intermittent Hypoxia-Induced Hypertension in Rats.

The increased incidence of hypertension associated with obstructive sleep apnea (OSA) presents significant physical, psychological, and economic challenges. Peroxisome proliferator-activated receptor gamma (PPARγ) plays a role in both OSA and hypertension, yet the therapeutic potential of PPARγ agonists and antagonists for OSA-related hypertension remains unexplored. Therefore, we constructed a chronic intermittent hypoxia (CIH)-induced hypertension rat model that mimics the pathogenesis of OSA-related hypertension in humans. The model involved administering PPARγ agonist rosiglitazone (RSG), PPARγ antagonist GW9662, or normal saline, followed by regular monitoring of blood pressure and thoracic aorta analysis using staining and electron microscopy. Intriguingly, our results indicated that both RSG and GW9662 appeared to potently counteract CIH-induced hypertension. In silico study suggested that GW9662's antihypertensive effect might mediated through angiotensin II receptor type 1 (AGTR1). Our findings provide insights into the mechanisms of OSA-related hypertension and propose novel therapeutic targets.