Predictive value of thrombus enhancement sign for stroke subtype and recanalization in acute basilar-artery occlusion.

BACKGROUND: Thrombus enhancement sign (TES) is associated with cardioembolic stroke and first-pass angiographic failure in anterior ischemic stroke. However, the relationship between TES and stroke subtype and recanalization status after endovascular treatment (EVT) in basilar artery occlusion (BAO) remains unknown. METHODS: This retrospective study included consecutive patients with acute BAO who underwent EVT between January 2020 and September 2023. Each patient underwent baseline non-contrast computed tomography (CT) and CT angiography. Two independent readers assessed the presence of TES. Stroke types were classified according to the Trial of ORG 10172 for Acute Stroke Treatment. Successful recanalization was defined as a modified Thrombolysis in Cerebral Infarction score of 2b-3 after EVT. Clinical and interventional parameters, along with histopathological thrombi examination results, were compared between the TES-positive and TES-negative groups. The associations between TES and stroke subtype and recanalization status were analyzed using univariate and multivariate analyses. RESULTS: A total of 151 patients were included in the analysis, among whom 116 (77%) exhibited TES. TES showed a significant correlation with cardioembolic and cryptogenic strokes (odds ratio [OR]: 8.56; 95% confidence interval: 3.49-22.4; p < 0.001), whereas the TES-positive thrombi were characterized by a higher fibrin/platelet proportion (p = 0.002) and lower erythrocyte proportion (p = 0.044). The TES-positive group demonstrated favorable outcomes compared to the TES-negative group, including a shorter procedure time (p < 0.001), lower number of thrombectomy attempts (p = 0.010), higher incidence of first pass success (p = 0.022), and lower rate of requiring rescue angioplasty and/or stenting (p < 0.001). In multivariate analysis, TES remained independently associated with successful recanalization (OR: 9.63; 95% CI: 2.33, 47.7; p = 0.003) after adjusting for baseline confounders. CONCLUSIONS: Visualization of TES serves as a reliable and easily accessible marker for identifying cardioembolic and cryptogenic strokes and predicting recanalization success in thrombectomy for basilar artery occlusion.

Prognostic implications of pre-transcatheter aortic valve replacement computed tomography-derived coronary plaque characteristics and stenosis severity.

OBJECTIVES: The study aimed to investigate the prognostic value of pre-transcatheter aortic valve replacement (TAVR) computed tomography angiography (CTA) in assessing physiological stenosis severity (CTA-derived fractional flow reserve (CT-FFR)) and high-risk plaque characteristics (HRPC). MATERIALS AND METHODS: Among TAVR patients who underwent pre-procedure CTA, the presence and number of HRPCs (minimum lumen area of < 4 mm2, plaque burden ≥ 70%, low-attenuating plaques, positive remodeling, napkin-ring sign, or spotty calcification) as well as CT-FFR were assessed. The risk of vessel-oriented composite outcome (VOCO, a composite of vessel-related ischemia-driven revascularization, vessel-related myocardial infarction, or cardiac death) was compared according to the number of HRPC and CT-FFR categories. RESULTS: Four hundred and twenty-seven patients (68.4% were male) with 1072 vessels were included. Their mean age was 70.6 ± 10.6 years. Vessels with low CT-FFR (≤ 0.80) (41.7% vs. 15.8%, adjusted hazard ratio (HRadj) 1.96; 95% confidence interval (CI): 1.28-2.96; p = 0.001) or lesions with ≥ 3 HRPC (38.7% vs. 16.0%, HRadj 1.81; 95%CI 1.20-2.71; p = 0.005) demonstrated higher VOCO risk. In the CT-FFR (> 0.80) group, lesions with ≥ 3 HRPC showed a significantly higher risk of VOCO than those with < 3 HRPC (34.7% vs. 13.0%; HRadj 2.04; 95%CI 1.18-3.52; p = 0.011). However, this relative increase in risk was not observed in vessels with positive CT-FFR (≤ 0.80). CONCLUSIONS: In TAVR candidates, both CT-FFR and the presence of ≥ 3 HRPC were associated with an increased risk of adverse clinical events. However, the value of HRPC differed with the CT-FFR category, with more incremental predictability among vessels with negative CT-FFR but not among vessels with positive CT-FFR. CLINICAL RELEVANCE STATEMENT: In transcatheter aortic valve replacement (TAVR) candidates, pre-TAVR CTA provided the opportunity to assess coronary physiological stenosis severity and high-risk plaque characteristics, both of which are associated with worse clinical outcomes. KEY POINTS: • The current study investigated the prognostic value of coronary physiology significance and plaque characteristics in transcatheter aortic valve replacement patients. • The combination of coronary plaque vulnerability and physiological significance showed improved accuracy in predicting clinical outcomes in transcatheter aortic valve replacement patients. • Pre-transcatheter aortic valve replacement CT can be a one-stop-shop tool for coronary assessments in clinical practice.

Financial and clinical outcomes of CT myocardial perfusion imaging and coronary CT angiography-guided versus coronary CT angiography-guided strategy.

OBJECTIVES: To compare the financial and clinical outcomes of CT myocardial perfusion imaging (CT-MPI) + coronary CT angiography (CCTA)-guided versus CCTA-guided strategy in patients suspected of chronic coronary syndrome (CCS). MATERIALS AND METHODS: This study retrospectively included consecutive patients suspected of CCS and referred for CT-MPI+CCTA-guided and CCTA-guided treatment. The details of medical costs within 3 months after index imaging, including downstream invasive procedures, hospitalization, and medications, were recorded. All patients were followed up for major adverse cardiac events (MACE) at a median time of 22 months. RESULTS: A total of 1335 patients (559 in the CT-MPI+CCTA group and 776 in the CCTA group) were finally included. In the CT-MPI+CCTA group, 129 patients (23.1%) underwent ICA and 95 patients (17.0%) received revascularization. In the CCTA group, 325 patients (41.9%) underwent ICA whereas 194 patients (25.0%) received revascularization. An addition of CT-MPI in the evaluation strategy remarkably reduced the healthcare expenditure, compared with CCTA-guided strategy (USD 1441.36 vs. USD 232.91, p < 0.001). After adjustment for potential cofounders after inverse probability weighting, the CT-MPI+CCTA strategy was significantly associated with lower medical expenditure [adjusted cost ratio (95% CI) for total costs: 0.77 (0.65-0.91), p < 0.001]. In addition, there was no significant difference regarding the clinical outcome between the two groups (adjusted HR= 0.97; p = 0.878). CONCLUSIONS: CT-MPI+CCTA considerably reduced medical expenditures in patients suspected of CCS, compared to the CCTA strategy alone. Moreover, CT-MPI+CCTA led to a lower rate of invasive procedures with a similar long-term prognosis. CLINICAL RELEVANCE STATEMENT: CT myocardial perfusion imaging + coronary CT angiography-guided strategy reduced medical expenditure and invasive procedure rate. KEY POINTS: • CT-MPI+CCTA strategy yielded significantly lower medical expenditure than did the CCTA strategy alone in patients with suspected CCS. • After adjustment for potential confounders, the CT-MPI+CCTA strategy was significantly associated with lower medical expenditure. • No significant difference was observed regarding the long-term clinical outcome between the two groups.

CT-derived fractional flow reserve for prediction of major adverse cardiovascular events in diabetic patients.

OBJECTIVES: To investigate the prognostic value of computed tomography fractional flow reserve (CT-FFR) in patients with diabetes and to establish a risk stratification model for major adverse cardiac event (MACE). METHODS: Diabetic patients with intermediate pre-test probability of coronary artery disease were prospectively enrolled. All patients were referred for coronary computed tomography angiography and followed up for at least 2 years. In the training cohort comprising of 957 patients, two models were developed: model1 with the inclusion of clinical and conventional imaging parameters, model2 incorporating the above parameters + CT-FFR. An internal validation cohort comprising 411 patients and an independent external test cohort of 429 patients were used to validate the proposed models. RESULTS: 1797 patients (mean age: 61.0 ± 7.0 years, 1031 males) were finally included in the present study. MACE occurred in 7.18% (129/1797) of the current cohort during follow- up. Multivariate Cox regression analysis revealed that CT-FFR ≤ 0.80 (hazard ratio [HR] = 4.534, p < 0.001), HbA1c (HR = 1.142, p = 0.015) and low attenuation plaque (LAP) (HR = 3.973, p = 0.041) were the independent predictors for MACE. In the training cohort, the Log-likelihood test showed statistical significance between model1 and model2 (p < 0.001). The C-index of model2 was significantly larger than that of model1 (C-index = 0.82 [0.77-0.87] vs. 0.80 [0.75-0.85], p = 0.021). Similar findings were found in internal validation and external test cohorts. CONCLUSION: CT-FFR was a strong independent predictor for MACE in diabetic cohort. The model incorporating CT-FFR, LAP and HbA1c yielded excellent performance in predicting MACE.

Computed Tomography Radiomics Model Predicts Procedure Success of Coronary Chronic Total Occlusions.

BACKGROUND: Coronary computed tomography (CT) angiography imaging is useful for the preprocedural evaluation of chronic total occlusion (CTO). However, the predictive value of CT radiomics model for successful percutaneous coronary intervention (PCI) has not been studied. We aimed to develop and validate a CT radiomics model for predicting PCI success of CTOs. METHODS: In this retrospective study, a radiomics-based model for predicting PCI success was developed on the training and internal validation sets of 202 and 98 patients with CTO, collected from 1 tertiary hospital. The proposed model was validated on an external test set of 75 CTO patients enrolled from another tertiary hospital. CT radiomics features of each CTO lesion were manually labeled and extracted. Other anatomical parameters, including occlusion length, entry morphology, tortuosity, and calcification burden, were also measured. Fifteen radiomics features, 2 quantitative plaque features, and CT-derived Multicenter CTO Registry of Japan score were used to train different models. The predictive values of each model were evaluated for predicting revascularization success. RESULTS: In the external test set, 75 patients (60 men; 65 years [58.5, 71.5]) with 83 CTO lesions were assessed. Occlusion length was shorter (13.00 mm versus 29.30 mm, P=0.007) in PCI success group whereas the presence of tortuous course was more commonly presented in PCI failure group (1.49% versus 25.00%, P=0.004). The radiomics score was significantly smaller in PCI success group (0.10 versus 0.55, P<0.001). The area under the curve of CT radiomics-based model was significantly higher than that of CT-derived Multicenter CTO Registry of Japan score for predicting PCI success (area under the curve=0.920 versus 0.752, P=0.008). The proposed radiomics model accurately identified 89.16% (74/83) CTO lesions with procedure success. CONCLUSIONS: CT radiomics-based model outperformed CT-derived Multicenter CTO Registry of Japan score for predicting PCI success. The proposed model is more accurate than the conventional anatomical parameters to identify CTO lesions with PCI success.

Deep Learning Segmentation and Reconstruction for CT of Chronic Total Coronary Occlusion.

Background CT imaging of chronic total occlusion (CTO) is useful in guiding revascularization, but manual reconstruction and quantification are time consuming. Purpose To develop and validate a deep learning (DL) model for automated CTO reconstruction. Materials and Methods In this retrospective study, a DL model for automated CTO segmentation and reconstruction was developed using coronary CT angiography images from a training set of 6066 patients (582 with CTO, 5484 without CTO) and a validation set of 1962 patients (208 with CTO, 1754 without CTO). The algorithm was validated using an external test set of 211 patients with CTO. The consistency and measurement agreement of CTO quantification were compared between the DL model and the conventional manual protocol using the intraclass correlation coefficient, Cohen κ coefficient, and Bland-Altman plot. The predictive values of CT-derived Multicenter CTO Registry of Japan (J-CTO) score for revascularization success were evaluated. Results In the external test set, 211 patients (mean age, 66 years ± 11 [SD]; 164 men) with 240 CTO lesions were evaluated. Automated segmentation and reconstruction of CTOs by DL was successful in 95% of lesions (228 of 240) without manual editing and in 48% of lesions (116 of 240) with the conventional manual protocol (P < .001). The total postprocessing and measurement time was shorter for DL than for manual reconstruction (mean, 121 seconds ± 20 vs 456 seconds ± 68; P < .001). The quantitative and qualitative CTO parameters evaluated with the two methods showed excellent correlation (all correlation coefficients > 0.85, all P < .001) and minimal measurement difference. The predictive values of J-CTO score derived from DL and conventional manual quantification for procedure success showed no difference (area under the receiver operating characteristic curve, 0.76 [95% CI: 0.69, 0.82] and 0.76 [95% CI: 0.69, 0.82], respectively; P = .55). Conclusion When compared with manual reconstruction, the deep learning model considerably reduced postprocessing time for chronic total occlusion quantification and had excellent correlation and agreement in the anatomic assessment of occlusion features. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Loewe in this issue.

Radiomics features of pericoronary adipose tissue improve CT-FFR performance in predicting hemodynamically significant coronary artery stenosis.

OBJECTIVES: To evaluate the value of radiomics-based model of pericoronary adipose tissue (PCAT) combined with CT fractional flow reserve (CT-FFR) in predicting hemodynamically significant coronary stenosis. METHODS: Patients with suspected or known coronary artery disease, who had coronary computed tomography angiography (CCTA), invasive coronary angiography (ICA), and FFR within 1 month, were retrospectively included. Radiomics features of lesion-based PCAT were extracted. The lesion-specific CT-FFR values, CCTA-derived diameter stenosis, lesion length, and PCAT attenuation were also measured. FFR values were used as the reference standard to assess the diagnostic performance of radiomics model, CT-FFR, and combined model for detection of flow-limiting stenosis. RESULTS: A total of 146 patients with 180 lesions were included in the study. All lesions were divided into training and validation cohorts at a ratio of 2:1. CT-FFR model exhibited the highest area under the curve (AUC) (0.803 for training, 0.791 for validation) in predicting hemodynamically significant stenosis, followed by radiomics model (0.776 for training, 0.744 for validation). However, no statistically significant difference was found between the AUCs of the above two models (p > 0.05). When CT-FFR was combined with radiomics model, the AUC reached 0.900 for training cohort and 0.875 for validation cohort, which were significantly higher than that of CT-FFR and radiomics model alone (both p < 0.05). CONCLUSION: The diagnostic performance of PCAT radiomics model was comparable to that of CT-FFR for identification of ischemic coronary stenosis. Adding PCAT radiomics model to CT-FFR showed incremental value in discriminating flow-limiting from non-flow-limiting lesions. KEY POINTS: • Radiomics analysis of lesion-based PCAT is potentially an alternative method to identify hemodynamic significance of coronary artery stenosis. • Adding radiomics model of PCAT to CT-FFR improved diagnostic performance for the detection of flow-limiting coronary stenosis. • Radiomics features + CT-FFR is a promising noninvasive method for comprehensive evaluation of hemodynamic significance of coronary artery stenosis.

A Novel Computed Tomography-Based Imaging Approach for Etiology Evaluation in Patients With Acute Coronary Syndrome and Non-obstructive Coronary Angiography.

Objective: This study sought to investigate the diagnostic value of dynamic CT myocardial perfusion imaging (CT-MPI) combined with coronary CT angiography (CCTA) in acute coronary syndrome (ACS) patients without obstructive coronary angiography. Methods: Consecutive ACS patients with normal or non-obstructive coronary angiography findings who had cardiac magnetic resonance (CMR) contraindications or inability to cooperate with CMR examinations were prospectively enrolled and referred for dynamic CT-MPI + CCTA + late iodine enhancement (LIE). ACS etiology was determined according to combined assessment of coronary vasculature by CCTA, quantified myocardial blood flow (MBF) and presence of LIE. Results: Twenty two patients were included in the final analysis. CCTA revealed two cases of side branch occlusion and one case of intramural hematoma which were overlooked by invasive angiography. High risk plaques were observed in 6 (27.3%) patients whereas myocardial ischemia was presented in 19 (86.4%) patients with varied extent and severity. LIE was positive in 13 (59.1%) patients and microvascular obstruction was presented in three cases with side branch occlusion or spontaneous intramural hematoma. The specific etiology was identified in 20 (90.9%) patients, of which the most common cause was cardiomyopathies (41%), followed by microvascular dysfunction (14%) and plaque disruption (14%). Conclusion: Dynamic CT-MPI + CCTA was able to reveal the potential etiologies in majority of patients with ACS and non-obstructive coronary angiography. It may be a useful alternative to CMR for accurate etiology evaluation.