Aberrant cortical morphology patterns are associated with cognitive impairment in patients with chronic heart failure.

A mounting body of evidences suggests that patients with chronic heart failure (HF) frequently experience cognitive impairments, but the neuroanatomical mechanism underlying these impairments remains elusive. In this retrospective study, 49 chronic HF patients and 49 healthy controls (HCs) underwent brain structural MRI scans and cognitive assessments. Cortical morphology index (cortical thickness, complexity, sulcal depth and gyrification) were evaluated. Correlations between cortical morphology and cognitive scores and clinical variables were explored. Logistic regression analysis was employed to identify risk factors for predicting 3-year major adverse cardiovascular events. Compared with HCs, patients with chronic HF exhibited decreased cognitive scores (p < .001) and decreased cortical thickness, sulcal depth and gyrification in brain regions involved cognition, sensorimotor, autonomic nervous system (family-wise error correction, all p values <.05). Notably, HF duration and New York Heart Association (NYHA) demonstrated negative correlations with abnormal cortex morphology, particularly HF duration and thickness in left precentral gyrus (r = -.387, p = .006). Cortical morphology characteristics exhibited positive associations with global cognition, particularly cortical thickness in left pars opercularis (r = .476, p < .001). NYHA class is an independent risk factor for adverse outcome (p = .001). The observed correlation between abnormal cortical morphology and global cognition suggested that cortical morphology may serve as a promising imaging biomarker and provide insights into neuroanatomical underpinnings of cognitive impairment in patients with chronic HF.

Clinical Effectiveness of Automated Coronary CT-derived Fractional Flow Reserve: A Chinese Randomized Controlled Trial.

Background Coronary CT-derived fractional flow reserve (CT-FFR) has been used in patients with suspected coronary artery disease (CAD); however, whether it decreases invasive coronary angiography (ICA) use and affects prognosis remains insufficiently evidenced. Purpose To explore the effectiveness of adding CT-FFR to routine coronary CT angiography (CCTA) on short-term ICA rate and major adverse cardiovascular events (MACE) in a Chinese setting. Materials and Methods A multicenter randomized controlled trial was conducted in 17 Chinese centers, with patient inclusion from May 2021 to September 2021. Eligible individuals with 25%-99% stenosis at CCTA were randomly assigned 1:1 to a strategy of CCTA plus automated CT-FFR or CCTA alone for guiding downstream care. The primary end point was the ICA rate 90 days after enrollment. Secondary end points included 90-day and 1-year MACE rates (comprised of all-cause mortality, nonfatal myocardial infarction, and urgent revascularization) and 1-year cardiac events (comprised of cardiac death, nonfatal myocardial infarction, and urgent revascularization). The Cox proportional hazards model with center effect adjustment was used for survival comparisons. Results A total of 5297 participants (mean age, 63.5 years ± 10.8 [SD]; 3178 male) were included. During the 90-day follow-up, ICA was performed in 263 of 2633 participants (10.0%) in the CCTA plus CT-FFR group and 327 of 2640 participants (12.4%) in the CCTA-alone group (absolute rate difference: -2.40%; 95% CI: -4.10, -0.70; P = .006). The MACE rates at 90 days (0.5% [12 of 2633 participants] vs 0.8% [21 of 2640 participants]; P = .12) and 1 year (2.9% [74 of 2546 participants] vs 2.8% [72 of 2531 participants]; P = .90) were similar for both groups. At 1-year follow-up, fewer cardiac events were observed in the CCTA plus CT-FFR group compared with the CCTA-alone group (0.5% vs 1.1%; adjusted hazard ratio: 0.52; 95% CI: 0.27, 0.99; P = .047). Conclusion CT-FFR added to CCTA led to a lower 90-day ICA rate and similar 1-year MACE rate in a Chinese real-world setting. Further follow-up is warranted to demonstrate the long-term prognostic value of this management approach. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Pundziute-do Prado in this issue.

Advances in Artificial Intelligence-Assisted Coronary Computed Tomographic Angiography for Atherosclerotic Plaque Characterization.

Coronary artery disease is a leading cause of death worldwide. Major adverse cardiac events are associated not only with coronary luminal stenosis but also with atherosclerotic plaque components. Coronary computed tomography angiography (CCTA) enables non-invasive evaluation of atherosclerotic plaque along the entire coronary tree. However, precise and efficient assessment of plaque features on CCTA is still a challenge for physicians in daily practice. Artificial intelligence (AI) refers to algorithms that can simulate intelligent human behavior to improve clinical work efficiency. Recently, cardiovascular imaging has seen remarkable advancements with the use of AI. AI-assisted CCTA has the potential to facilitate the clinical workflow, offer objective and repeatable quantitative results, accelerate the interpretation of reports, and guide subsequent treatment. Several AI algorithms have been developed to provide a comprehensive assessment of atherosclerotic plaques. This review serves to highlight the cutting-edge applications of AI-assisted CCTA in atherosclerosis plaque characterization, including detecting obstructive plaques, assessing plaque volumes and vulnerability, monitoring plaque progression, and providing risk assessment. Finally, this paper discusses the current problems and future directions for implementing AI in real-world clinical settings.

Late gadolinium enhanced cardiac MR derived radiomics approach for predicting all-cause mortality in cardiac amyloidosis: a multicenter study.

OBJECTIVES: To evaluate the prognostic value of radiomics features based on late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) images in patients with cardiac amyloidosis (CA). METHODS: This retrospective study included 120 CA patients undergoing CMR at three institutions. Radiomics features were extracted from global and three different segments (base, mid-ventricular, and apex) of left ventricular (LV) on short-axis LGE images. Primary endpoint was all-cause mortality. The predictive performance of the radiomics features and semi-quantitative and quantitative LGE parameters were compared by ROC. The AUC was used to observe whether Rad-score had an incremental value for clinical stage. The Kaplan-Meier curve was used to further stratify the risk of CA patients. RESULTS: During a median follow-up of 12.9 months, 30% (40/120) patients died. There was no significant difference in the predictive performance of the radiomics model in different LV sections in the validation set (AUCs of the global, basal, middle, and apical radiomics model were 0.75, 0.77, 0.76, and 0.77, respectively; all p > 0.05). The predictive performance of the Rad-score of the base-LV was better than that of the LGE total enhancement mass (AUC:0.77 vs. 0.54, p < 0.001) and LGE extent (AUC: 0.77 vs. 0.53, p = 0.004). Rad-score combined with Mayo stage had better predictive performance than Mayo stage alone (AUC: 0.86 vs. 0.81, p = 0.03). Rad-score (≥ 0.66) contributed to the risk stratification of all-cause mortality in CA. CONCLUSIONS: Compared to quantitative LGE parameters, radiomics can better predict all-cause mortality in CA, while the combination of radiomics and Mayo stage could provide higher predictive accuracy. CLINICAL RELEVANCE STATEMENT: Radiomics analysis provides incremental value and improved risk stratification for all-cause mortality in patients with cardiac amyloidosis. KEY POINTS: • Radiomics in LV-base was superior to LGE semi-quantitative and quantitative parameters for predicting all-cause mortality in CA. • Rad-score combined with Mayo stage had better predictive performance than Mayo stage alone or radiomics alone. • Rad-score ≥ 0.66 was associated with a significantly increased risk of all-cause mortality in CA patients.

The prognostic value of CT-derived fractional flow reserve in coronary artery bypass graft: a retrospective multicenter study.

OBJECTIVES: To investigate the predictive value of CT-derived fractional flow reserve (FFRCT) in anastomosis occlusion after coronary artery bypass graft (CABG) surgery. METHODS: Patients undergoing CABG with both pre- and post-operative coronary computed tomographic angiography (CCTA) were retrospectively included. Preoperative CCTA studies were used to evaluate anatomical and FFRCT information of target vessels. A diameter stenosis (DS) ≥ 70% or left main > 50% was considered to be anatomically severe, while FFRCT value ≤ 0.80 be functionally significant. The primary endpoint was anastomosis occlusion evaluated on post-operative CCTA during follow-up. Predictors of anastomosis occlusion were assessed by the multivariate binary logistic regression with generalized estimating equations. RESULTS: A total of 270 anastomoses were identified in 88 enrolled patients. Forty-one anastomoses from 30 patients exhibited occlusion during a follow-up of 15.3 months after CABG. The occluded group had significantly increased prevalence of non-severe DS (58.5% vs. 40.2%; p = 0.023) and non-significant FFRCT (48.8% vs. 10.0%; p < 0.001). Multivariable analysis indicated FFRCT ≤ 0.80 (odds ratio [OR]: 0.10, 95% CI: 0.03-0.33; p < 0.001) and older age (OR: 0.92, 95% CI: 0.87-0.97; p = 0.001) were predictors for bypass patency during follow-up, while myocardial infarction history and anastomosis to a local lesion or bifurcation (all p value < 0.05) were predictors of occlusion. Adding FFRCT into the model based on the clinical and anatomical predictors had an improved AUC of 0.848 (p = 0.005). CONCLUSIONS: FFRCT ≤ 0.80 was associated with a significant risk reduction of anastomosis occlusion after CABG. Preoperative judgment of the hemodynamic significance may improve the CABG surgery strategy and reduce graft failure. KEY POINTS: • FFRCT ≤ 0.80 was associated with a significant risk reduction of anastomosis occlusion after CABG. • The addition of FFRCT into the integrated model including clinical (age and history of myocardial infarction) and anatomical CCTA indicators (local lesion and bifurcation) significantly improved the model performance with an AUC of 0.848 (p = 0.005). • Preoperative judgment of the hemodynamic significance may help improve the decision-making and surgery planning in patients indicated for CABG and significantly reduce graft failure, without an extra radiation exposure and risk of invasive procedure.

Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study.

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.

One-year outcomes of CCTA alone versus machine learning-based FFRCT for coronary artery disease: a single-center, prospective study.

OBJECTIVES: To explore downstream management and outcomes of machine learning (ML)-based CT derived fractional flow reserve (FFRCT) strategy compared with an anatomical coronary computed tomography angiography (CCTA) alone assessment in participants with intermediate coronary artery stenosis. METHODS: In this prospective study conducted from April 2018 to March 2019, participants were assigned to either the CCTA or FFRCT group. The primary endpoint was the rate of invasive coronary angiography (ICA) that demonstrated non-obstructive disease at 90 days. Secondary endpoints included coronary revascularization and major adverse cardiovascular events (MACE) at 1-year follow-up. RESULTS: In total, 567 participants were allocated to the CCTA group and 566 to the FFRCT group. At 90 days, the rate of ICA without obstructive disease was higher in the CCTA group (33.3%, 39/117) than that (19.8%, 19/96) in the FFRCT group (risk difference [RD] = 13.5%, 95% confidence interval [CI]: 8.4%, 18.6%; p = 0.03). The ICA referral rate was higher in the CCTA group (27.5%, 156/567) than in the FFRCT group (20.3%, 115/566) (RD = 7.2%, 95% CI: 2.3%, 12.1%; p = 0.003). The revascularization-to-ICA ratio was lower in the CCTA group than that in the FFRCT group (RD = 19.8%, 95% CI: 14.1%, 25.5%, p = 0.002). MACE was more common in the CCTA group than that in the FFRCT group at 1 year (HR: 1.73; 95% CI: 1.01, 2.95; p = 0.04). CONCLUSION: In patients with intermediate stenosis, the FFRCT strategy appears to be associated with a lower rate of referral for ICA, ICA without obstructive disease, and 1-year MACE when compared to the anatomical CCTA alone strategy. KEY POINTS: • In stable patients with intermediate stenosis, ML-based FFRCT strategy was associated with a lower referral ICA rate, a lower normalcy rate of ICA, and higher revascularization-to-ICA ratio than the CCTA strategy. • Compared with the CCTA strategy, ML-based FFRCTshows superior outcome prediction value which appears to be associated with a lower rate of 1-year MACE. • ML-based FFRCT strategy as a non-invasive "one-stop-shop" modality may be the potential to change diagnostic workflows in patients with suspected coronary artery disease.

Functional CAD-RADS using FFRCT on therapeutic management and prognosis in patients with coronary artery disease.

OBJECTIVES: To propose a novel functional Coronary Artery Disease-Reporting and Data System (CAD-RADS) category system integrated with coronary CT angiography (CCTA)-derived fractional flow reserve (FFRCT) and to validate its effect on therapeutic decision and prognosis in patients with coronary artery disease (CAD). METHODS: Firstly, we proposed a novel functional CAD-RADS and evaluated the performance of functional CAD-RADS for guiding treatment strategies with actual clinical treatment as a reference standard in a retrospective multicenter cohort with CCTA and invasive FFR performed in all patients (n = 466). Net reclassification improvement (NRI) of functional CAD-RADS over anatomical CAD-RADS was calculated. Secondly, the prognostic value of functional CAD-RADS in a prospective two-arm cohort (566 [FFRCT arm] vs. 567 [CCTA arm]) was calculated, after a 1-year follow-up, functional CAD-RADS in FFRCT arm (n = 513) and anatomical CAD-RADS in CCTA arm (n = 511) to determine patients at risk of adverse outcomes were compared with a Cox hazard proportional model. RESULTS: Functional CAD-RADS demonstrated superior value over anatomical CAD-RADS (AUC: 0.828 vs. 0.681, p < 0.001) and comparable performance to FFR (AUC: 0.828 vs. 0.848, p = 0.253) in guiding therapeutic decisions. Functional CAD-RADS resulted in the revision of management plan as determined by anatomical CAD-RADS in 30.0% of patients (n = 140) (NRI = 0.369, p < 0.001). Functional CAD-RADS was an independent predictor for 1-year outcomes with indexes of concordance of 0.795 and the corresponding value was 0.751 in anatomical CAD-RADS. CONCLUSION: The novel functional CAD-RADS gained incremental value in guiding therapeutic decision-making compared with anatomical CAD-RADS and comparable power in 1-year prognosis with anatomical CAD-RADS in a real-world scenario. KEY POINTS: • The novel functional CAD-RADS category system with FFRCT integrated into the anatomical CAD-RADS categories was originally proposed. • The novel functional CAD-RADS category system was validated superior value over anatomical CAD-RADS (AUC: 0.828 vs. 0.681, p < 0.001) in guiding therapeutic decisions and revised management plan in 30.0% of patients as determined by anatomical CAD-RADS (net reclassification improvement index = 0.369, p < 0.001). • Functional CAD-RADS was an independent predictor with an index of concordance of 0.795 and 0.751 in anatomical CAD-RADS for 1-year prognosis of adverse outcomes.

Feasibility and prognostic role of machine learning-based FFRCT in patients with stent implantation.

OBJECTIVES: To investigate the feasibility and prognostic implications of coronary CT angiography (CCTA) derived fractional flow reserve (FFRCT) in patients who have undergone stents implantation. METHODS: Firstly, the feasibility of FFRCT in stented vessels was validated. The diagnostic performance of FFRCT in identifying hemodynamically in-stent restenosis (ISR) in 33 patients with invasive FFR ≤ 0.88 as reference standard, intra-group correlation coefficient (ICC) between FFRCT and FFR was calculated. Secondly, prognostic value was assessed with 115 patients with serial CCTA scans after PCI. Stent characteristics (location, diameter, length, etc.), CCTA measurements (minimum lumen diameter [MLD], minimum lumen area [MLA], ISR), and FFRCT measurements (FFRCT, ΔFFRCT, ΔFFRCT/stent length) both at baseline and follow-up were recorded. Longitudinal analysis included changes of MLD, MLA, ISR, and FFRCT. The primary endpoint was major adverse cardiovascular events (MACE). RESULTS: Per-patient accuracy of FFRCT was 0.85 in identifying hemodynamically ISR. FFRCT had a good correlation with FFR (ICC = 0.84). 15.7% (18/115) developed MACE during 25 months since follow-up CCTA. Lasso regression identified age and follow-up ΔFFRCT/length as candidate variables. In the Cox proportional hazards model, age (hazard ratio [HR], 1.102 [95% CI, 1.032-1.177]; p = 0.004) and follow-up ΔFFRCT/length (HR, 1.014 [95% CI, 1.006-1.023]; p = 0.001) were independently associated with MACE (c-index = 0.856). Time-dependent ROC analysis showed AUC was 0.787 (95% CI, 0.594-0.980) at 25 months to predict adverse outcome. After bootstrap validation with 1000 resamplings, the bias-corrected c-index was 0.846. CONCLUSIONS: Noninvasive ML-based FFRCT is feasible in patients following stents implantation and shows prognostic value in predicting adverse events after stents implantation in low-moderate risk patients. KEY POINTS: • Machine-learning-based FFRCT is feasible to evaluate the functional significance of in-stent restenosis in patients with stent implantation. • Follow-up △FFRCT along with the stent length might have prognostic implication in patients with stent implantation and low-to-moderate risk after 2 years follow-up. The prognostic role of FFRCT in patients with moderate-to-high or high risk needs to be further studied. • FFRCT might refine the clinical pathway of patients with stent implantation to invasive catheterization.

Serial coronary CT angiography-derived fractional flow reserve and plaque progression can predict long-term outcomes of coronary artery disease.

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.

The effect of coronary calcification on diagnostic performance of machine learning-based CT-FFR: a Chinese multicenter study.

OBJECTIVE: To investigate the effect of coronary calcification morphology and severity on the diagnostic performance of machine learning (ML)-based coronary CT angiography (CCTA)-derived fractional flow reserve (CT-FFR) with FFR as a reference standard. METHODS: A total of 442 patients (61.2 ± 9.1 years, 70% men) with 544 vessels who underwent CCTA, ML-based CT-FFR, and invasive FFR from China multicenter CT-FFR study were enrolled. The effect of calcification arc, calcification remodeling index (CRI), and Agatston score (AS) on the diagnostic performance of CT-FFR was investigated. CT-FFR ≤ 0.80 and lumen reduction ≥ 50% determined by CCTA were identified as vessel-specific ischemia with invasive FFR as a reference standard. RESULTS: Compared with invasive FFR, ML-based CT-FFR yielded an overall sensitivity of 0.84, specificity of 0.94, and accuracy of 0.90 in a total of 344 calcification lesions. There was no statistical difference in diagnostic accuracy, sensitivity, or specificity of CT-FFR across different calcification arc, CRI, or AS levels. CT-FFR exhibited improved discrimination of ischemia compared with CCTA alone in lesions with mild-to-moderate calcification (AUC, 0.89 vs. 0.69, p < 0.001) and lesions with CRI ≥ 1 (AUC, 0.89 vs. 0.71, p < 0.001). The diagnostic accuracy and specificity of CT-FFR were higher than CCTA alone in patients and vessels with mid (100 to 299) or high (≥ 300) AS. CONCLUSION: Coronary calcification morphology and severity did not influence diagnostic performance of CT-FFR in ischemia detection, and CT-FFR showed marked improved discrimination of ischemia compared with CCTA alone in the setting of calcification. KEY POINTS: • CT-FFR provides superior diagnostic performance than CCTA alone regardless of coronary calcification. • No significant differences in the diagnostic performance of CT-FFR were observed in coronary arteries with different coronary calcification arcs and calcified remodeling indexes. • No significant differences in the diagnostic accuracy of CT-FFR were observed in coronary arteries with different coronary calcification score levels.

Impact of machine learning-based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease.

OBJECTIVES: This study investigated the impact of machine learning (ML)-based fractional flow reserve derived from computed tomography (FFRCT) compared to invasive coronary angiography (ICA) for therapeutic decision-making and patient outcome in patients with suspected coronary artery disease (CAD). METHODS: One thousand one hundred twenty-one consecutive patients with stable chest pain who underwent coronary computed tomography angiography (CCTA) followed ICA within 90 days between January 2007 and December 2016 were included in this retrospective study. Medical records were reviewed for the endpoint of major adverse cardiac events (MACEs). FFRCT values were calculated using an artificial intelligence (AI) ML platform. Disagreements between hemodynamic significant stenosis via FFRCT and severe stenosis on qualitative CCTA and ICA were also evaluated. RESULTS: After FFRCT results were revealed, a change in the proposed treatment regimen chosen based on ICA results was seen in 167 patients (14.9%). Over a median follow-up time of 26 months (4-48 months), FFRCT ≤ 0.80 was associated with MACE (HR, 6.84 (95% CI, 3.57 to 13.11); p < 0.001), with superior prognostic value compared to severe stenosis on ICA (HR, 1.84 (95% CI, 1.24 to 2.73), p = 0.002) and CCTA (HR, 1.47 (95% CI, 1.01 to 2.14, p = 0.045). Reserving ICA and revascularization for vessels with positive FFRCT could have reduced the rate of ICA by 54.5% and lead to 4.4% fewer percutaneous interventions. CONCLUSIONS: This study indicated ML-based FFRCT had superior prognostic value when compared to severe anatomic stenosis on CCTA and adding FFRCT may direct therapeutic decision-making with the potential to improve efficiency of ICA. KEY POINTS: • ML-based FFRCT shows superior outcome prediction value when compared to severe anatomic stenosis on CCTA. • FFRCT noninvasively informs therapeutic decision-making with potential to change diagnostic workflows and enhance efficiencies in patients with suspected CAD. • Reserving ICA and revascularization for vessels with positive FFRCT may reduce the normalcy rate of ICA and improve its efficiency.

The influence of image quality on diagnostic performance of a machine learning-based fractional flow reserve derived from coronary CT angiography.

OBJECTIVE: To investigate the effect of image quality of coronary CT angiography (CCTA) on the diagnostic performance of a machine learning-based CT-derived fractional flow reserve (FFRCT). METHODS: This nationwide retrospective study enrolled participants from 10 individual centers across China. FFRCT analysis was performed in 570 vessels in 437 patients. Invasive FFR and FFRCT values ≤ 0.80 were considered ischemia-specific. Four-score subjective assessment based on image quality and objective measurement of vessel enhancement was performed on a per-vessel basis. The effects of body mass index (BMI), sex, heart rate, and coronary calcium score on the diagnostic performance of FFRCT were studied. RESULTS: Among 570 vessels, 216 were considered ischemia-specific by invasive FFR and 198 by FFRCT. Sensitivity and specificity of FFRCT for detecting lesion-specific ischemia were 0.82 and 0.93, respectively. Area under the curve (AUC) of high-quality images (0.93, n = 159) was found to be superior to low-quality images (0.80, n = 92, p = 0.02). Objective image quality and heart rate were also associated with diagnostic performance of FFRCT, whereas there was no statistical difference in diagnostic performance among different BMI, sex, and calcium score groups (all p > 0.05, Bonferroni correction). CONCLUSIONS: This retrospective multicenter study supported the FFRCT as a noninvasive test in evaluating lesion-specific ischemia. Subjective image quality, vessel enhancement, and heart rate affect the diagnostic performance of FFRCT. KEY POINTS: • FFRCTcan be used to evaluate lesion-specific ischemia. • Poor image quality negatively affects the diagnostic performance of FFRCT. • CCTA with ≥ score 3, intracoronary enhancement degree of 300-400 HU, and heart rate below 70 bpm at scanning could be of great benefit to more accurate FFRCTanalysis.

Fractional flow reserve derived from CCTA may have a prognostic role in myocardial bridging.

PURPOSE: To evaluate the feasibility of fractional flow reserve (cFFR) derivation from coronary CT angiography (CCTA) in patients with myocardial bridging (MB), its relationship with MB anatomical features, and clinical relevance. METHODS: This retrospective study included 120 patients with MB of the left anterior descending artery (LAD) and 41 controls. MB location, length, depth, muscle index, instance, and stenosis rate were measured. cFFR values were compared between superficial MB (≤ 2 mm), deep MB (> 2 mm), and control groups. Factors associated with abnormal cFFR values (≤ 0.80) were analyzed. RESULTS: MB patients demonstrated lower cFFR values in MB and distal segments than controls (all p < 0.05). A significant cFFR difference was only found in the MB segment during systole between superficial (0.94, 0.90-0.96) and deep MB (0.91, 0.83-0.95) (p = 0.018). Abnormal cFFR values were found in 69 (57.5%) MB patients (29 [49.2%] superficial vs. 40 [65.6%] deep; p = 0.069). MB length (OR = 1.06, 95% CI 1.03-1.10; p = 0.001) and systolic stenosis (OR = 1.04, 95% CI 1.01-1.07; p = 0.021) were the main predictors for abnormal cFFR, with an area under the curve of 0.774 (95% CI 0.689-0.858; p < 0.001). MB patients with abnormal cFFR reported more typical angina (18.8% vs 3.9%, p = 0.023) than patients with normal values. CONCLUSION: MB patients showed lower cFFR values than controls. Abnormal cFFR values have a positive association with symptoms of typical angina. MB length and systolic stenosis demonstrate moderate predictive value for an abnormal cFFR value. KEY POINTS: • MB patients showed lower cFFR values than controls. • Abnormal cFFR values have a positive association with typical angina symptoms. • MB length and systolic stenosis demonstrate moderate predictive value for an abnormal cFFR value .

Detection of pulmonary fat embolism with dual-energy CT: an experimental study in rabbits.

OBJECTIVES: To evaluate the use of dual-energy CT imaging of the lung perfused blood volume (PBV) for the detection of pulmonary fat embolism (PFE). METHODS: Dual-energy CT was performed in 24 rabbits before and 1 hour, 1 day, 4 days and 7 days after artificial induction of PFE via the right ear vein. CT pulmonary angiography (CTPA) and lung PBV images were evaluated by two radiologists, who recorded the presence, number, and location of PFE on a per-lobe basis. Sensitivity, specificity, and accuracy of CTPA and lung PBV for detecting PFE were calculated using histopathological evaluation as the reference standard. RESULTS: A total of 144 lung lobes in 24 rabbits were evaluated and 70 fat emboli were detected on histopathological analysis. The overall sensitivity, specificity and accuracy were 25.4 %, 98.6 %, and 62.5 % for CTPA, and 82.6 %, 76.0 %, and 79.2 % for lung PBV. Higher sensitivity (p < 0.001) and accuracy (p < 0.01), but lower specificity (p < 0.001), were found for lung PBV compared with CTPA. Dual-energy CT can detect PFE earlier than CTPA (all p < 0.01). CONCLUSION: Dual-energy CT provided higher sensitivity and accuracy in the detection of PFE as well as earlier detection compared with conventional CTPA in this animal model study. KEY POINTS: • Fat embolism occurs commonly in patients with traumatic bone injury. • Dual-energy CT improves diagnostic performance for pulmonary fat embolism detection. • Dual-energy CT can detect pulmonary fat embolism earlier than CTPA.

Non-Electrocardiogram-Triggered 70-kVp High-Pitch Computed Tomography Angiography of the Whole Aorta With Iterative Reconstruction: Initial Results.

OBJECTIVES: To evaluate the feasibility of non-electrocardiogram (ECG)-triggered 70-kVp high-pitch aortic computed tomography angiography (CTA) with iterative reconstruction (IR) and reduced contrast agent using second-generation dual-source CT (DSCT). METHODS: Seventy-seven patients were examined: group A (n = 21), 70-kVp high-pitch (3.2) CTA, 60 mL contrast agent and IR on second-generation DSCT; group B (n = 29), standard-pitch (1.2) CTA, automatic tube voltage selection, filtered back projection and 80 mL contrast agent on second-generation DSCT; group C (n = 27), 120-kVp standard-pitch (1.2) CTA, filtered back projection, and 80 mL contrast agent on first-generation DSCT. Computed tomography values, noise, signal-to-noise ratio, contrast-to-noise ratio, and subjective image quality were compared. RESULTS: Computed tomography values and noise of all aortic segments in group A were increased compared with groups B and C (P < 0.05). Group B showed the highest signal-to-noise ratio and contrast-to-noise ratio for all aortic segments (P < 0.05), whereas no significant differences were found between groups A and C (P > 0.05). Mean effective dose was 0.88 ± 0.08 mSv for group A, reduced by 93% compared to group C and by 90% compared to group B. CONCLUSIONS: Non-ECG-triggered 70-kVp high-pitch aortic CTA with IR provides equivalent diagnostic image quality with 90% reduction of radiation dose and 25% reduction of contrast volume compared with standard 120-kVp CTA.

Multidetector computed tomography pulmonary angiography in childhood acute pulmonary embolism.

Pulmonary embolism is a life-threatening condition affecting people of all ages. Multidetector row CT pulmonary angiography has improved the imaging of pulmonary embolism in both adults and children and is now regarded as the routine modality for detection of pulmonary embolism. Advanced CT pulmonary angiography techniques developed in recent years, such as dual-energy CT, have been applied as a one-stop modality for pulmonary embolism diagnosis in children, as they can simultaneously provide anatomical and functional information. We discuss CT pulmonary angiography techniques, common and uncommon findings of pulmonary embolism in both conventional and dual-energy CT pulmonary angiography, and radiation dose considerations.

Feasibility of prospectively ECG-triggered high-pitch coronary CT angiography with 30 mL iodinated contrast agent at 70 kVp: initial experience.

OBJECTIVES: To evaluate the feasibility, image quality and radiation dose of prospectively ECG-triggered high-pitch coronary CT angiography (CCTA) with 30 mL contrast agent at 70 kVp. METHODS: Fifty-eight patients with suspected coronary artery disease, a body mass index (BMI) of less than 25 kg/m(2), sinus rhythm and a heart rate (HR) of less than 70 beats per minute (bpm) were prospectively enrolled in this study. Thirty mL of 370 mg I/mL iodinated contrast agent was administrated at a flow rate of 5 mL/s. All patients underwent prospectively ECG-triggered high-pitch CCTA on a second-generation dual-source CT system at 70 kVp using automated tube current modulation. RESULTS: Fifty-six patients (96.6%) had diagnostic CCTA images and two patients (3.4%) had one vessel with poor image quality each rated as non-diagnostic. No significant effects of HR, HR variability and BMI on CCTA image quality were observed (all P > 0.05). Effective dose was 0.17 ± 0.02 mSv and the size-specific dose estimate was 1.03 ± 0.13 mGy. CONCLUSION: Prospectively ECG-triggered high-pitch CCTA at 70 kVp with 30 mL of contrast agent can provide diagnostic image quality at a radiation dose of less than 0.2 mSv in patients with a BMI of less than 25 kg/m(2) and an HR of less than 70 bpm. KEY POINTS: • Prospectively ECG-triggered high-pitch CCTA at 70 kVp/30 mL contrast agent is feasible. • Diagnostic image quality can be obtained at a radiation dose of less than 0.2 mSv. • This protocol is suitable for normal-weight patients with slow heart rate.