A 32-Month Follow-Up Study of the Effect of APOE ε4 on the Whole Brain Connection in Young Healthy Individuals.

APOE ε4 is risk for cognitive decline even in normal aging, but its effect on the whole-brain functional connectivity (FC) among time in young adults remain elusive. This study aimed to validate the time-by-APOE ε4 interaction on brain FC of this specific population. Longitudinal changes in neuropsychological assessments and resting-state functional magnetic resonance imaging in 26 ε4 carriers and 26 matched non-ε4 carriers were measured for about 3 years. Whole-brain FC was calculated, and a full factorial design was used to compare the difference among groups. Two-sample t test was used for post-hoc analysis. Pearson's correlation analysis was conducted to investigate the relationships between FC and cognitive tests. Of 26 specially appointed ROIs, left superior temporal gyrus (TG) was most sensitive to the effect of time-by-gene interaction. Specifically, the alteration of FC was distributed between the left TG and right TG with GRF correction (voxel-P < 0.001, cluster-P < 0.05), and decreased in ε4 carriers while increased in non-ε4. The main effect of gene showed ε4 carriers has lower FC between left TG and right middle frontal gyrus as compared with non-ε4 both at baseline and follow-up study; ε4 carriers has lower FC between left TG and right supramarginal as compared with non-ε4 at baseline, but no difference in follow-up study. The time-by-APOE ε4 interaction on brain FC was demonstrated at a young age, and left TG was the earliest affected brain regions. The young adult ε4 carriers experience decreased FC among time in the absence overt clinical symptoms.

Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)-a protocol for a multicenter, double-blinded randomized controlled trial.

BACKGROUND: This multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneurysm detection in CT angiography (CTA) and its influence on patients' short-term and long-term outcomes. METHODS: Study design: Prospective, multicenter, double-blinded RCT. SETTINGS: The model was designed for the automatic detection of intracranial aneurysms from original CTA images. PARTICIPANTS: Adult inpatients and outpatients who are scheduled for head CTA scanning. Randomization groups: (1) Experimental Group: Head CTA interpreted by radiologists with the assistance of the True-AI-integrated intracranial aneurysm diagnosis strategy (True-AI arm). (2) Control Group: Head CTA interpreted by radiologists with the assistance of the Sham-AI-integrated intracranial aneurysm diagnosis strategy (Sham-AI arm). RANDOMIZATION: Block randomization, stratified by center, gender, and age group. PRIMARY OUTCOMES: Coprimary outcomes of superiority in patient-level sensitivity and noninferiority in specificity for the True-AI arm to the Sham-AI arm in intracranial aneurysms. SECONDARY OUTCOMES: Diagnostic performance for other intracranial lesions, detection rates, workload of CTA interpretation, resource utilization, treatment-related clinical events, aneurysm-related events, quality of life, and cost-effectiveness analysis. BLINDING: Study participants and participating radiologists will be blinded to the intervention. SAMPLE SIZE: Based on our pilot study, the patient-level sensitivity is assumed to be 0.65 for the Sham-AI arm and 0.75 for the True-AI arm, with specificities of 0.90 and 0.88, respectively. The prevalence of intracranial aneurysms for patients undergoing head CTA in the hospital is approximately 12%. To establish superiority in sensitivity and noninferiority in specificity with a margin of 5% using a one-sided α = 0.025 to ensure that the power of coprimary endpoint testing reached 0.80 and a 5% attrition rate, the sample size was determined to be 6450 in a 1:1 allocation to True-AI or Sham-AI arm. DISCUSSION: The study will determine the precise impact of the AI system on the detection performance for intracranial aneurysms in a double-blinded design and following the real-world effects on patients' short-term and long-term outcomes. TRIAL REGISTRATION: This trial has been registered with the NIH, U.S. National Library of Medicine at ClinicalTrials.gov, ID: NCT06118840 . Registered 11 November 2023.

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.

Coronary CTA-based Vascular Radiomics Predicts Atherosclerosis Development Proximal to LAD Myocardial Bridging.

BACKGROUND: Cardiac cycle morphological changes can accelerate plaque growth proximal to myocardial bridging (MB) in the left anterior descending artery (LAD). OBJECTIVE: To assess coronary CT angiography (CCTA)-based vascular radiomics for predicting proximal plaque development in LAD MB. METHODS: Patients with repeated CCTA scans showing LAD MB without proximal plaque in index CCTA were included from Jinling Hospital as development set. They were divided into training and internal testing in an 8:2 ratio. Patients from 4 other tertiary hospitals were set as external validation set. The endpoint was proximal plaque development of LAD MB in follow-up CCTA. Four vascular radiomics models were built: MB centerline (MB CL), proximal MB CL (pMB CL), MB cross section (MB CS), and proximal MB CS (pMB CS), whose performances were evaluated using area under the curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI). RESULTS: 295 patients were included in the development (n=192; median age, 54±11 years; 137 men) and external validation sets (n=103; median age, 57±9 years; 57 men). The pMB CS vascular radiomics model exhibited higher AUCs in training, internal test, and external sets (AUC=0.78, 0.75, 0.75) than the clinical and anatomical model (all p<0.05). Integration of the pMB CS vascular radiomics model significantly raised the AUC of the clinical and anatomical model from 0.56 to 0.75 (p=0.002), along with enhanced NRI (0.76 [0.37-1.14], p<0.001) and IDI (0.17 [0.07-0.26], p<0.001) in the external validation set. CONCLUSION: The CCTA-based pMB CS vascular radiomics model can predict plaque development in LAD MB.

Light-Chain Cardiac Amyloidosis: Cardiac Magnetic Resonance for Assessing Response to Chemotherapy.

OBJECTIVE: Cardiac magnetic resonance (CMR) is a diagnostic tool that provides precise and reproducible information about cardiac structure, function, and tissue characterization, aiding in the monitoring of chemotherapy response in patients with light-chain cardiac amyloidosis (AL-CA). This study aimed to evaluate the feasibility of CMR in monitoring responses to chemotherapy in patients with AL-CA. MATERIALS AND METHODS: In this prospective study, we enrolled 111 patients with AL-CA (50.5% male; median age, 54 [interquartile range, 49-63] years). Patients underwent longitudinal monitoring using biomarkers and CMR imaging. At follow-up after chemotherapy, patients were categorized into superior and inferior response groups based on their hematological and cardiac laboratory responses to chemotherapy. Changes in CMR findings across therapies and differences between response groups were analyzed. RESULTS: Following chemotherapy (before vs. after), there were significant increases in myocardial T2 (43.6 ± 3.5 ms vs. 44.6 ± 4.1 ms; P = 0.008), recovery in right ventricular (RV) longitudinal strain (median of -9.6% vs. -11.7%; P = 0.031), and decrease in RV extracellular volume fraction (ECV) (median of 53.9% vs. 51.6%; P = 0.048). These changes were more pronounced in the superior-response group. Patients with superior cardiac laboratory response showed significantly greater reductions in RV ECV (-2.9% [interquartile range, -8.7%-1.1%] vs. 1.7% [-5.5%-7.1%]; P = 0.017) and left ventricular ECV (-2.0% [-6.0%-1.3%] vs. 2.0% [-3.0%-5.0%]; P = 0.01) compared with those with inferior response. CONCLUSION: Cardiac amyloid deposition can regress following chemotherapy in patients with AL-CA, particularly showing more prominent regression, possibly earlier, in the RV. CMR emerges as an effective tool for monitoring associated tissue characteristics and ventricular functional recovery in patients with AL-CA undergoing chemotherapy, thereby supporting its utility in treatment response assessment.

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study.

BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performance, and validate its application in real-world clinical implementation. METHODS: We developed a deep-learning model using 16 546 head and neck CTA examination images from 14 517 patients at eight Chinese hospitals. Using an adapted, stepwise implementation and evaluation, 120 certified clinicians from 15 geographically different hospitals were recruited. Initially, the AI model was externally validated with images of 900 digital subtraction angiography-verified CTA cases (examinations) and compared with the performance of 24 clinicians who each viewed 300 of these cases (stage 1). Next, as a further external validation a multi-reader multi-case study enrolled 48 clinicians to individually review 298 digital subtraction angiography-verified CTA cases (stage 2). The clinicians reviewed each CTA examination twice (ie, with and without the AI model), separated by a 4-week washout period. Then, a randomised open-label comparison study enrolled 48 clinicians to assess the acceptance and performance of this AI model (stage 3). Finally, the model was prospectively deployed and validated in 1562 real-world clinical CTA cases. FINDINGS: The AI model in the internal dataset achieved a patient-level diagnostic sensitivity of 0·957 (95% CI 0·939-0·971) and a higher patient-level diagnostic sensitivity than clinicians (0·943 [0·921-0·961] vs 0·658 [0·644-0·672]; p<0·0001) in the external dataset. In the multi-reader multi-case study, the AI-assisted strategy improved clinicians' diagnostic performance both on a per-patient basis (the area under the receiver operating characteristic curves [AUCs]; 0·795 [0·761-0·830] without AI vs 0·878 [0·850-0·906] with AI; p<0·0001) and a per-aneurysm basis (the area under the weighted alternative free-response receiver operating characteristic curves; 0·765 [0·732-0·799] vs 0·865 [0·839-0·891]; p<0·0001). Reading time decreased with the aid of the AI model (87·5 s vs 82·7 s, p<0·0001). In the randomised open-label comparison study, clinicians in the AI-assisted group had a high acceptance of the AI model (92·6% adoption rate), and a higher AUC when compared with the control group (0·858 [95% CI 0·850-0·866] vs 0·789 [0·780-0·799]; p<0·0001). In the prospective study, the AI model had a 0·51% (8/1570) error rate due to poor-quality CTA images and recognition failure. The model had a high negative predictive value of 0·998 (0·994-1·000) and significantly improved the diagnostic performance of clinicians; AUC improved from 0·787 (95% CI 0·766-0·808) to 0·909 (0·894-0·923; p<0·0001) and patient-level sensitivity improved from 0·590 (0·511-0·666) to 0·825 (0·759-0·880; p<0·0001). INTERPRETATION: This AI model demonstrated strong clinical potential for intracranial aneurysm detection with improved clinician diagnostic performance, high acceptance, and practical implementation in real-world clinical cases. FUNDING: National Natural Science Foundation of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Coronary chronic total occlusion on coronary CT angiography: what radiologists should know?

Coronary chronic total occlusion (CTO) often occurs in patients with obstructive coronary artery disease, which remains one of the greatest challenges for interventional cardiologists. Coronary computed tomography angiography (CCTA) with its emerging post-processing techniques can provide a detailed assessment of CTO lesions before percutaneous coronary intervention (PCI), playing an important role in the clinical management of CTO PCI, from early diagnosis, pre-procedural outcome prediction, the crossing algorithm planning, intraprocedural guidance, and finally post-procedural assessment and follow-up. In addition, the feasibility of CT perfusion (CTP) in patients with CTO has been validated. Combined CCTA and CTP have the great potential to be the one-stop-shop imaging modality for assessing both anatomy and function of CTO lesions. This review aims to make radiologists understand the role of CCTA in the diagnosis and assessment of CTO lesions, thus assisting interventionalists in optimizing CTO PCI crossing strategies with the expertise of radiologists.Critical relevance statement The anatomical features of CTO on CCTA can reveal the complexity of CTO lesions and are associated with CTO PCI outcome, thus helping interventionalists optimize CTO PCI crossing strategies.Key points • CTO is the common lesion in invasive coronary angiography, and CTO PCI is technically difficult and its success rate is relatively low.• Length, collaterals, and attenuation-related signs can help distinguish CTO from subtotal occlusion.• The anatomical features of CTO lesions can help grade the difficulty of CTO PCI and predict procedural outcomes and long-term outcomes of CTO PCI.• The real-time fusion of CCTA with fluoroscopic angiography can be applied in highly complicated CTO lesions.• After CTO PCI, CCTA can help guide a second CTO PCI re-entry or follow up stent patency.

Multiparametric Cardiovascular Magnetic Resonance in Nonhospitalized COVID-19 Infection Subjects: An Intraindividual Comparison Study.

PURPOSE: To investigate intraindividual cardiac structural and functional changes before and after COVID-19 infection in a previously healthy population with a 3T cardiac magnetic resonance (CMR). MATERIALS AND METHODS: A total of 39 unhospitalized patients with COVID-19 were recruited. They participated in our previous study as non-COVID-19 healthy volunteers undergoing baseline CMR examination and were recruited to perform a repeated CMR examination after confirmed COVID-19 infection in December 2022. The CMR parameters were measured and compared between before and after COVID-19 infection with paired t tests. The laboratory measures including myocardial enzymes and inflammatory indicators were also collected when performing repeated CMR. RESULTS: The median duration was 393 days from the first to second CMR and 26 days from clinical symptoms onset to the second CMR. Four patients (10.3%, 4/39) had the same late gadolinium enhancement pattern at baseline and repeated CMR and 5 female patients (12.8%, 5/39) had myocardial T2 ratio >2 (2.07 to 2.27) but with normal T2 value in post-COVID-19 CMR. All other CMR parameters were in normal ranges before and after COVID-19 infection. Between before and after the COVID-19 infection, there were no significant differences in cardiac structure, function, and tissue characterization, no matter with or without symptoms (fatigue, chest discomfort, palpitations, shortness of breath, and insomnia/sleep disorders) (all P >0.05). The laboratory measures at repeated CMR were in normal ranges in all participants. CONCLUSIONS: These intraindividual CMR studies showed unhospitalized patients with COVID-19 with normal myocardial enzymes had no measurable CMR abnormalities, which can help alleviate wide social concerns about COVID-19-related myocarditis.

CT-derived fractional flow reserve in intracranial arterial stenosis: A pilot study based on computational fluid dynamics.

BACKGROUND: CT-derived fractional flow reserve (CT-FFR) has been widely applied in coronary hemodynamic assessment. However, the feasieablity and standardization measurement in intracranial artery stenosis (ICAS) remains to be defined. PURPOSE: To demonstrate the feasibility of CT-FFR in ICAS functional assessment and explore the optimal CT-FFR measurement position with invasive FFR as reference standard. MATERIALS AND METHODS: Nineteen patients (mean age, 58.6 years ± 1.9 [SD]; 13 men) with moderate to severe (≥50 %) ICAS undergoing guidewire-based pressure measurement and preoperative head CT angiography (CTA) were retrospectively enrolled. CT-FFR was measured in the following standard measurement positions, including the end of stenosis (D0), 1 cm distal to the stenosis (D1) and 2 cm distal to the stenosis (D2). Diagnostic performance of CT-FFR was assessed by the area under the curve (AUC) of receiver operating characteristic curves by assuming invasive FFR ≤ 0.80 or 0.75 as hemodynamically significant stenosis. RESULTS: Excellent intra- and inter-observer agreement (ICC range, 0.930-0.992) was observed for CT-FFR measurement in different positions. Under different FFR thresholds, the diagnostic performance of CT-FFRD1 showed perfect prediction with AUC values of 1.000 (95 % CI: 0.824, 1.000). The sensitivity, specificity and AUC of CT-FFRD1 ≤ 0.80 in detecting FFR ≤ 0.80 was 0.94 (95 % CI: 0.68, 1.00), 1.00 (95 % CI: 0.31, 1.00) and 0.969 (95 % CI: 0.772, 1.000), respectively. Similar performance of CT-FFRD1 ≤ 0.75 was obtained for identifying FFR ≤ 0.75 with the AUC of 0.964. The strongest correlation (r = 0.915, p < 0.001) and agreement (mean difference: 0.02, 95 % limits of agreement: -0.16 to 0.19) were observed between CT-FFRD1 and FFR. CONCLUSION: Cerebral CT-derived fractional flow reserve (CT-FFR) measured 1 cm distal to stenosis achieved the most comparable results with invasive FFR, which indicated its potentially promising clinical application for evaluating the functional relevance of intracranial artery stenosis.

FFR CT and Static Computed Tomography Myocardial Perfusion Imaging for Therapeutic Decision-making and Prognosis in Patients With Coronary Artery Disease.

PURPOSE: The purpose of this study was to investigate the effect of integrated evaluation of resting static computed tomography perfusion (CTP) and coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFR CT ) on therapeutic decision-making and predicting major adverse cardiovascular events (MACEs) in patients with suspected coronary artery disease. MATERIALS AND METHODS: In this post hoc analysis of a prospective trial of CCTA in patients assigned to either CCTA or CCTA plus FFR CT arms, 500 patients in the CCTA plus FFR CT arm were analyzed. Both resting static CTP and FFR CT were evaluated by using the conventional CCTA. Perfusion defects in the myocardial segments with ≥50% degree of stenosis in the supplying vessels were defined as resting static CTP positive, and any vessel with an FFR CT value of ≤0.80 was considered positive. Patients were divided into 3 groups: (1) negative CTP-FFR CT match group (resting static CTP-negative and FFR CT -negative group); (2) mismatch CTP-FFR CT group (resting static CTP-positive and FFR CT -negative or resting static CTP-negative and FFR CT -positive group); and (3) positive CTP-FFR CT match group (resting static CTP-positive and FFR CT -positive group). We compared the revascularization-to-invasive coronary angiography ratio and the MACE rate among 3 subgroups at 1- and 3-year follow-ups. The adjusted Cox hazard proportional model was used to assess the prognostic value of FFR CT and resting static CTP to determine patients at risk of MACE. RESULTS: Patients in the positive CTP-FFR CT match group were more likely to undergo revascularization at the time of invasive coronary angiography compared with those in the mismatch CTP-FFR CT group (81.4% vs 57.7%, P =0.033) and the negative CTP-FFR CT match group (81.4% vs 33.3%, P= 0.001). At 1- and 3-year follow-ups, patients in the positive CTP-FFR CT match group were more likely to have MACE than those in the mismatch CTP-FFR CT group (10.5% vs 4.2%, P= 0.046; 35.6% vs 9.4%, P <0.001) and the negative CTP-FFR CT match group (10.5% vs 0.9%, P <0.001; 35.6% vs 5.4%, P <0.001). A positive CTP-FFR CT match was strongly related to MACE at 1-year (hazard ratio=8.06, P= 0.003) and 3-year (hazard ratio=6.23, P <0.001) follow-ups. CONCLUSION: In patients with suspected coronary artery disease, the combination of FFR CT with resting static CTP could guide therapeutic decisions and have a better prognosis with fewer MACE in a real-world scenario.

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.

Machine learning based ischemia-specific stenosis prediction: A Chinese multicenter coronary CT angiography study.

OBJECTIVES: To evaluate the performance of coronary computed tomography angiography (CCTA) derived characteristics including CT derived fractional flow reserve (CT-FFR) with FFR as a reference standard in identifying the lesion-specific ischemia by machine learning (ML) algorithms. METHODS: The retrospective analysis enrolled 596 vessels in 462 patients (mean age, 61 years ± 11 [SD]; 71.4 % men) with suspected coronary artery disease who underwent CCTA and invasive FFR. The data were divided into training cohort, internal validation cohort, external validation cohorts 1 and 2 according to participating centers. All CCTA-derived parameters, which contained 10 qualitative and 33 quantitative plaque parameters, were collected to establish ML model. The Boruta and unsupervised clustering algorithm were implemented to select important and non-redundant parameters. Finally, the eight features with the highest mean importance were included for further ML model establishment and decision tree building. Five models were built to predict lesion-specific ischemia: stenosis degree from CCTA, CT-FFR, ΔCT-FFR, ML model and nested model. RESULTS: Low-attenuation plaque, bend and lesion length were the main predictors of ischemia-specific lesions. Of 5 models, the ML model showed favorable discrimination for ischemia-specific lesions in the training and three validation sets (area under the curve [95 % confidence interval], 0.93 [0.90-0.96], 0.86 [0.79-0.94], 0.88 [0.83-0.94], and 0.90 [0.84-0.96], respectively). The nested model which combined the ML model and CT-FFR showed better diagnostic efficacy (AUC [95 %CI], 0.96 [0.94-0.99], 0.92 [0.86-0.99], 0.92 [0.86-0.99] and 0.94 [0.91-0.98], respectively; all P < 0.05), and net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were significantly higher than CT-FFR alone. CONCLUSIONS: Comprehensive CCTA-derived multiparameter model could better predict the ischemia-specific lesions by ML algorithms compared to stenosis degree from CTA, CT-FFR and ΔCT-FFR. Decision tree can be used to predict myocardial ischemia effectively.

Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression.

BACKGROUND: Rapid plaque progression (RPP) is associated with a higher risk of acute coronary syndromes compared with gradual plaque progression. We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODS: A total of 214 patients who underwent serial CCTA examinations from 2 tertiary hospitals (development group, 137 patients with 164 lesions; validation group, 77 patients with 101 lesions) were retrospectively enrolled. Conventional CCTA-defined morphological parameters (eg, high-risk plaque characteristics and plaque burden) and radiomics features of plaques were analyzed. RPP was defined as an annual progression of plaque burden ≥1.0% on lesion-level at follow-up CCTA. RS was built to predict RPP using XGBoost method. RESULTS: RS significantly outperformed morphological parameters for predicting RPP in both the development group (area under the receiver operating characteristic curve, 0.82 versus 0.74; P=0.04) and validation group (area under the receiver operating characteristic curve, 0.81 versus 0.69; P=0.04). Multivariable analysis identified RS (odds ratio, 2.35 [95% CI, 1.32-4.46]; P=0.005) as an independent predictor of subsequent RPP in the validation group after adjustment of morphological confounders. Unlike unchanged RS in the non-RPP group, RS increased significantly in the RPP group at follow-up in the whole dataset (P<0.001). CONCLUSIONS: The proposed CCTA-based RS had a better discriminative value to identify plaques at risk of rapid progression compared with conventional morphological plaque parameters. These data suggest the promising utility of radiomics for predicting RPP in a low-risk group on CCTA.

Burden and distribution of monosodium urate deposition in patients with hyperuricemia and gout: a cross-sectional Chinese population-based dual-energy CT study.

Background: To investigate the distribution and burden of monosodium urate (MSU) deposition in hyperuricemia and gout patients with dual-energy computed tomography (DECT). Methods: A total of 1,936 consecutive patients from January 1, 2009, to September 15, 2017, underwent DECT examinations in Jinling Hospital. Of these, 1,294 patients were excluded due to other clinical diagnoses (n=1,041), inappropriate locations (n=82), poor-quality images (n=105), training cases (n=30) and duplicated data (n=36). Finally, 642 patients were included in this study. We retrospectively analyzed 1,127 DECT examinations in 642 consecutive patients (hyperuricemia group, n=121; gout group, n=521) and recorded the volume and number of MSU deposits. For each anatomical location, we recorded MSU deposition in the soft tissue and joint cavity. MSU deposition was analyzed and compared between groups. For normally distributed data, independent sample t-tests were used for comparison between the two groups. The independent samples nonparametric test was used to analyze nonnormally distributed data. Results: (I) The burden of MSU deposition in the gout group {volume [0.14 (0.04-1.36)] and numbers [10.00 (5.00-19.00)]} was significantly higher than that {volume [0.08 (0.02-0.47), P=0.003] and numbers [9.50 (2.00-16.00), P=0.01]} in the hyperuricemia group. (II) The burden of MSU deposition in the knees {volume [0.24 (0.01-1.79), P=0.002] and quantity [6.00 (2.00-12.00), P=0.04]} and feet {volume [0.10 (0.04-0.66)] and number [9.00 (5.00-15.00)]} was significantly higher in the gout group than those {knees: the volume [0.03 (0.00-0.27), P=0.002] and the quantity [4.00 (0.00-9.00), P=0.04]; feet: the volume [0.07 (0.02-0.19), P=0.003)] and number [8.00 (2.25-12.00), P=0.04]} in the hyperuricemia group, respectively. (III) In the hyperuricemia group, the volume of MSU deposition was significantly higher in the soft tissues of the knee (0.022±0.042) and ankle (0.062±0.305) than in those (knee: 0.001±0.005, P=0.02; ankle: 0.027±0.234, P=0.02) in the joint cavity. Conclusions: Although subclinical urate deposition can occur in patients with asymptomatic hyperuricemia, the burden of urate deposition is greater in patients with symptomatic gout, and the distribution is more pronounced in the foot/knee. Thus, more effective patient management and monitoring can be achieved by measuring the burden of MSU deposits in the patient's feet/knees. These data suggest that a threshold for urate crystal volume at typical sites may be required before symptomatic disease develops.

Multiparametric cardiac magnetic resonance reveals persistent myocardial inflammation in patients with exertional heat illness.

OBJECTIVES: To explore the clinical potential of multiparametric cardiac magnetic resonance (CMR) in evaluating myocardial inflammation in patients with exertional heat illness (EHI). METHODS: This prospective study enrolled 28 males with EHI (18 patients with exertional heat exhaustion (EHE) and 10 with exertional heat stroke (EHS)) and 18 age-matched male healthy controls (HC). All subjects underwent multiparametric CMR, and 9 patients had follow-up CMR measurements 3 months after recovery from EHI. CMR-derived left ventricular geometry, function, strain, native T1, extracellular volume (ECV), T2, T2*, and late gadolinium enhancement (LGE) were obtained and compared among different groups. RESULTS: Compared with HC, EHI patients showed increased global ECV, T2, and T2* values (22.6% ± 4.1 vs. 19.7% ± 1.7; 46.8 ms ± 3.4 vs. 45.1 ms ± 1.2; 25.5 ms ± 2.2 vs. 23.8 ms ± 1.7; all p < 0.05). Subgroup analysis showed that ECV was higher in the EHS patients than those in EHE and HC groups (24.7% ± 4.9 vs. 21.4% ± 3.2, 24.7% ± 4.9 vs. 19.7% ± 1.7; both p < 0.05). Repeated CMR measurements at 3 months after baseline CMR showed persistently higher ECV than HC (p = 0.042). CONCLUSIONS: With multiparametric CMR, EHI patients demonstrated increased global ECV, T2, and persistent myocardial inflammation at 3-month follow-up after EHI episode. Therefore, multiparametric CMR might be an effective method in evaluating myocardial inflammation in patients with EHI. CLINICAL RELEVANCE STATEMENT: This study showed persistent myocardial inflammation after an exertional heat illness (EHI) episode demonstrated by multiparametric CMR, which is a potential promising method to evaluate the severity of myocardial inflammation and guide return to work, play, or duty in EHI patients. KEY POINTS: • EHI patients showed an increased global extracellular volume (ECV), late gadolinium enhancement, and T2 value, indicating myocardial edema and fibrosis. • ECV was higher in the exertional heat stroke patients than exertional heat exhaustion and healthy control groups (24.7% ± 4.9 vs. 21.4% ± 3.2, 24.7% ± 4.9 vs. 19.7% ± 1.7; both p < 0.05). • EHI patients showed persistent myocardial inflammation with higher ECV than healthy controls 3 months after index CMR (22.3% ± 2.4 vs. 19.7% ± 1.7, p = 0.042).

Image Improved Intravoxel Incoherent Motion MRI With Optimized Trigger Delays Based on Strain Curve Analysis to Evaluate Myocardial Microvascular Dysfunction of Exertional Heat Illness.

BACKGROUND: Intravoxel incoherent motion (IVIM) MRI has not been widely used and its role in evaluating exertional heat illness (EHI)-related myocardial involvement remains unknown. PURPOSE: To investigate the feasibility of strain curve-derived trigger delay (TD) IVIM-MRI and its role in assessing myocardial diffusion and microvascular perfusion of EHI patients. STUDY TYPE: Prospective. SUBJECTS: A total of 42 male EHI patients (median age: 21 years) and 22 age- and sex-matched healthy controls (HC). FIELD STRENGTH/SEQUENCE: A 3-T, diffusion-weighted spin-echo echo-planar-imaging sequence. ASSESSMENT: IVIM-MRI was acquired by conventional TD method (group A) or strain curve-based TD method (group B) in random order. IVIM image quality was evaluated on a 3-point Likert scale (1, nondiagnostic; 2, moderate; 3, good). Technical success was defined as image quality score = 3. IVIM-MRI-derived parameters (pseudo diffusion in the capillaries [D*], perfusion fraction [f], and slow apparent diffusion coefficient [D]) were compared between EHI and HC. STATISTICAL TESTS: Student's t-tests, chi-square tests, one-way analysis of variance, receiver operating characteristic (ROC) curve analysis, Pearson's correlation coefficient (r). The statistical significance level was set at P < 0.05. RESULTS: IVIM-MRI image quality score (median [interquartile range]: 3 [2, 3] vs. 2 [1-3]) and technical success rate (61.9%[13/21] vs. 28.6%[6/21]) were significantly improved in group B. EHI patients showed significantly decreased D* (118.1 ± 23.3 × 10-3  mm2 /sec vs. 142.7 ± 42.6 × 10-3  mm2 /sec) and f values (0.42 ± 0.12 vs. 0.51 ± 0.11) and significantly higher D values (3.0 ± 0.9 × 10-3  mm2 /sec vs. 2.5 ± 0.6 × 10-3  mm2 /sec) compared to HC. Relative to D and D*, f showed the most robust efficacy for detecting EHI-related myocardial injury with the highest area under the ROC curve (0.906: 95% confidence interval, 0.799, 0.967) and sensitivity of 88.5% and specificity of 85.6%. CONCLUSION: The strain curve-based TD method significantly improved image quality and technical success rate of IVIM-MRI, and f value may be an effective biomarker to assess myocardial microcirculation abnormalities of EHI patients. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

A Coronary CT Angiography Radiomics Model to Identify Vulnerable Plaque and Predict Cardiovascular Events.

Background A noninvasive coronary CT angiography (CCTA)-based radiomics technique may facilitate the identification of vulnerable plaques and patients at risk for future adverse events. Purpose To assess whether a CCTA-based radiomic signature (RS) of vulnerable plaques defined with intravascular US was associated with increased risk for future major adverse cardiac events (MACE). Materials and Methods In a retrospective study, an RS of vulnerable plaques was developed and validated using intravascular US as the reference standard. The RS development data set included patients first undergoing CCTA and then intravascular US within 3 months between June 2013 and December 2020 at one tertiary hospital. The development set was randomly assigned to training and validation sets at a 7:3 ratio. Diagnostic performance was assessed internally and externally from three tertiary hospitals using the area under the curve (AUC). The prognostic value of the RS for predicting MACE was evaluated in a prospective cohort with suspected coronary artery disease between April 2018 and March 2019. Multivariable Cox regression analysis was used to evaluate the RS and conventional anatomic plaque features (eg, segment involvement score) for predicting MACE. Results The RS development data set included 419 lesions from 225 patients (mean age, 64 years ± 10 [SD]; 68 men), while the prognostic cohort included 1020 lesions from 708 patients (mean age, 62 years ± 11; 498 men). Sixteen radiomic features, including two shape features and 14 textural features, were selected to build the RS. The RS yielded a moderate to good AUC in the training, validation, internal, and external test sets (AUC = 0.81, 0.75, 0.80, and 0.77, respectively). A high RS (≥1.07) was independently associated with MACE over a median 3-year follow-up (hazard ratio, 2.01; P = .005). Conclusion A coronary CT angiography-derived radiomic signature of coronary plaque enabled the detection of vulnerable plaques that were associated with increased risk for future adverse cardiac outcomes. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by De Cecco and van Assen in this issue.

Cardiovascular magnetic resonance imaging in myocardial involvement of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder that primarily affects young women. Myocardial involvement in SLE frequently occurs and it is rather challenging to make the diagnosis in current clinical settings, mainly due to the extensive clinical presentation of signs and symptoms. As a noninvasive imaging reference in diagnosing cardiomyopathy and myocarditis, cardiovascular magnetic resonance (CMR) imaging can provide new insight into myocardial abnormalities including inflammation, fibrosis, and microcirculation. Therefore, the main aim of this work was to systematically review the pathology, clinical features, and diagnosis, while illustrating the clinical role of CMR on myocardial involvement of SLE.