A token-mixer architecture for CAD-RADS classification of coronary stenosis on multiplanar reconstruction CT images

Background and objective: In patients with suspected Coronary Artery Disease (CAD), the severity of stenosis needs to be assessed for precise clinical management. An automatic deep learning-based algorithm to classify coronary stenosis lesions according to the Coronary Artery Disease Reporting and Data System (CAD-RADS) in multiplanar reconstruction images acquired with Coronary Computed Tomography Angiography (CCTA) is proposed. Methods: In this retrospective study, 288 patients with suspected CAD who underwent CCTA scans were included. To model long-range semantic information, which is needed to identify and classify stenosis with challenging appearance, we adopted a token-mixer architecture (ConvMixer), which can learn structural relationship over the whole coronary artery. ConvMixer consists of a patch embedding layer followed by repeated convolutional blocks to enable the algorithm to learn long-range dependences between pixels. To visually assess ConvMixer performance, Gradient-Weighted Class Activation Mapping (Grad-CAM) analysis was used. Results: Experimental results using 5-fold cross-validation showed that our ConvMixer can classify significant coronary artery stenosis (i.e., stenosis with luminal narrowing ≥50%) with accuracy and sensitivity of 87% and 90%, respectively. For CAD-RADS 0 vs. 1–2 vs. 3–4 vs. 5 classification, ConvMixer achieved accuracy and sensitivity of 72% and 75%, respectively. Additional experiments showed that ConvMixer achieved a better trade-off between performance and complexity compared to pyramid-shaped convolutional neural networks. Conclusions: Our algorithm might provide clinicians with decision support, potentially reducing the interobserver variability for coronary artery stenosis evaluation

Stress CMR in Known or Suspected CAD: Diagnostic and Prognostic Role

The recently published 2019 guidelines on chronic coronary syndromes (CCS) focus on the need for noninvasive imaging modalities to accurately establish the diagnosis of coronary artery disease (CAD) and assess the risk of clinical scenario occurrence. Appropriate patient management should rely on controlling symptoms, improving prognosis, and guiding each therapeutic strategy as well as monitoring disease progress. Among the noninvasive imaging modalities, cardiovascular magnetic resonance (CMR) has gained broad acceptance in past years due to its unique features in providing a complete assessment of CAD through data on cardiac anatomy and function and myocardial viability, with high spatial and temporal resolution and without ionizing radiation. In detail, evaluation of the presence and extent of myocardial ischemia through stress CMR (S-CMR) has shown a high rule-in power in detecting functionally significant coronary artery stenosis in patients suspected of CCS. Moreover, S-CMR technique may add significant prognostic value, as demonstrated by different studies which have progressively evidenced the valuable power of this multiparametric imaging modality in predicting adverse cardiac events. The latest scientific progress supports a greater expansion of S-CMR with improvement of quantitative myocardial perfusion analysis, myocardial strain, and native mapping within the same examination. Although further study is warranted, these techniques, which are currently mostly restricted to the research field, are likely to become increasingly prevalent in the clinical setting with the scope of increasing accuracy in the selection of patients to be sent to invasive revascularization. This review investigates the diagnostic and prognostic role of S-CMR in the context of CAD, by analysing a strong, long-standing, scientific evidence together with an appraisal of new advanced techniques which may potentially enrich CAD management in the next future

The incremental role of coronary computed tomography in chronic coronary syndromes

In the context of chronic coronary syndromes (CCS), coronary computed tomography angiography (CCTA) has gained broad acceptance as a noninvasive anatomical imaging tool with ability of excluding coronary stenosis with strong negative predictive value. Atherosclerotic plaque lesions are independent predictors of cardiovascular outcomes in high risk patients with known coronary artery disease (CAD). Calcium detection is commonly expressed through the coronary artery calcium score (CACS), but further research is warranted to confirm the powerness of a CACS-only strategy in both diagnosis and prognosis assessment. Recent studies evidence how defined plaque composition characteristics effectively relate to the risk of plaque instabilization and the overall ischemic burden. Fractional flow reserve from CCTA (FFR-CT) has been demonstrated as a reliable method for noninvasive functional evaluation of coronary lesions severity, while the assessment of perfusion imaging under stress conditions is growing as a useful tool for assessment of myocardial ischemia. Moreover, specific applications in procedural planning of transcatheter valve substitution and follow-up of heart transplantation have gained recent importance. This review illustrates the incremental role of CCTA, which can potentially revolutionize the diagnosis and management pathway within the wide clinical spectrum of CCS

Role of CMR Mapping Techniques in Cardiac Hypertrophic Phenotype

Non-ischemic cardiomyopathies represent a heterogeneous group of myocardial diseases potentially leading to heart failure, life-threatening arrhythmias, and eventually death. Myocardial dysfunction is associated with different underlying pathological processes, ultimately inducing changes in morphological appearance. Thus, classification based on presenting morphological phenotypes has been proposed, i.e., dilated, hypertrophic, restrictive, and right ventricular cardiomyopathies. In light of the key diagnostic and prognostic role of morphological and functional features, cardiovascular imaging has emerged as key element in the clinical workflow of suspected cardiomyopathies, and above all, cardiovascular magnetic resonance (CMR) represents the ideal technique to be used: thanks to its physical principles, besides optimal spatial and temporal resolutions, incomparable contrast resolution allows to assess myocardial tissue abnormalities in detail. Traditionally, weighted images and late enhancement images after gadolinium-based contrast agent administration have been used to perform tissue characterization, but in the last decade quantitative assessment of pre-contrast longitudinal relaxation time (native T1), post-contrast longitudinal relaxation time (post-contrast T1) and transversal relaxation time (T2), all displayed with dedicated pixel-wise color-coded maps (mapping), has contributed to give precious knowledge insight, with positive influence of diagnostic accuracy and prognosis assessment, mostly in the setting of the hypertrophic phenotype. This review aims to describe the available evidence of the role of mapping techniques in the assessment of hypertrophic phenotype, and to suggest their integration in the routine CMR evaluation of newly diagnosed cardiomyopathies with increased wall thickness

Role of CMR mapping techniques in cardiac hypertrophic phenotype

Non-ischemic cardiomyopathies represent a heterogeneous group of myocardial diseases potentially leading to heart failure, life-threatening arrhythmias, and eventually death. Myocardial dysfunction is associated with different underlying pathological processes, ultimately inducing changes in morphological appearance. Thus, classification based on presenting morphological phenotypes has been proposed, i.e., dilated, hypertrophic, restrictive, and right ventricular cardiomyopathies. In light of the key diagnostic and prognostic role of morphological and functional features, cardiovascular imaging has emerged as key element in the clinical workflow of suspected cardiomyopathies, and above all, cardiovascular magnetic resonance (CMR) represents the ideal technique to be used: thanks to its physical principles, besides optimal spatial and temporal resolutions, incomparable contrast resolution allows to assess myocardial tissue abnormalities in detail. Traditionally, weighted images and late enhancement images after gadolinium-based contrast agent administration have been used to perform tissue characterization, but in the last decade quantitative assessment of pre-contrast longitudinal relaxation time (native T1), post-contrast longitudinal relaxation time (post-contrast T1) and transversal relaxation time (T2), all displayed with dedicated pixel-wise color-coded maps (mapping), has contributed to give precious knowledge insight, with positive influence of diagnostic accuracy and prognosis assessment, mostly in the setting of the hypertrophic phenotype. This review aims to describe the available evidence of the role of mapping techniques in the assessment of hypertrophic phenotype, and to suggest their integration in the routine CMR evaluation of newly diagnosed cardiomyopathies with increased wall thickness

Computed tomography predictors of structural valve degeneration in patients undergoing transcatheter aortic valve implantation with balloon-expandable prostheses

Objectives: Computed tomography (CT) provides excellent anatomy assessment of the aortic annulus (AoA) and is utilized for pre-procedural planning of transcatheter aortic valve implantation (TAVI). We sought to investigate if geometrical characteristics of the AoA determined by CT may represent predictors of structural valve degeneration (SVD) in patients undergoing TAVI with balloon-expandable valves. Methods: This is a retrospective study on 124 consecutive patients (mean age: 79 ± 7 years; female: 61%) undergoing balloon-expandable TAVI prospectively enrolled in a registry. AoA maximum diameter (Dmax), minimum diameter (Dmin), and area were assessed using pre-procedural CT. SVD was identified during follow-up with transthoracic echocardiography documenting structural prosthetic valve abnormalities with or without hemodynamic changes. Results: The mean follow-up was 5.9 ± 1.7 years. SVD was found in 48 out of 124 patients (38%). AoA Dmax, Dmin, and area were significantly smaller in patients with SVD compared to patients without SVD (25.6 ± 2.2 mm vs. 27.1 ± 2.8 mm, p = 0.012; 20.5 ± 2.1 mm vs. 21.8 ± 2.1 mm, p = 0.001 and 419 ± 77 mm2 vs. 467 ± 88 mm2, p = 0.002, respectively). At univariable analysis, female sex, BSA, 23-mm prosthetic valve size, Dmax < 27.1 mm, and a Dmin < 19.9 mm were associated with SVD, whereas at multivariable analysis, only Dmin < 19.9 mm (OR = 2.873, 95% CI: 1.191–6.929, p = 0.019) and female sex (OR = 2.659, 95% CI: 1.095–6.458, p = 0.031) were independent predictors of SVD. Conclusions: Female sex and AoA Dmin < 19.9 mm are associated with SVD in patients undergoing TAVI with balloon-expandable valves. When implanting large prostheses in order to avoid paraprosthetic regurgitation, caution should be observed due to the risk of excessive stretching of the AoA Dmin, which may play a role in SVD. Key Points: • Long-term durability is a concern for transcatheter aortic valve bioprosthesis. • CT provides an excellent assessment of the aortic annulus’s geometrical characteristics for prosthesis sizing before transcatheter aortic valve implantation (TAVI). • Female sex and a small minimum aortic annulus diameter measured with CT are independent predictors of structural valve degeneration in patients undergoing TAVI with balloon-expandable valves

Identification of subclinical cardiac amyloidosis in aortic stenosis patients undergoing transaortic valve replacement using radiomic analysis of computed tomography myocardial texture

Background: Cardiac amyloidosis (CA) is an increasingly diagnosed pathology sharing several phenotypical features with aortic stenosis (AS). As diagnosing the two diseases has important prognostic and therapeutic implications, this study aims to identify a set of stable and discriminative radiomic features derived from cardiac computed tomography (CCT) to differentiate them. Methods: Forty-two patients were included in the study. For each patient, 107 radiomics features were extracted and evaluated by means of geometrical transformations (translations) to the region of interests (ROIs), and ICC (intra class correlation coefficient) computation. A stratified 7-fold cross validation (k=7) was performed to split data into learning, validation and test set. Three features selection methods (Wilcoxon signed rank- based method and/or LASSO regression) and five machine learning classifiers (k-nearest neighbors, support vector classifier, decision tree, logistic regression and gradient boosting) were tested. Results: Ninety radiomic features satisfied the robustness criteria and 10 were kept after feature selection. The best results were obtained using the logistic regression classifier, combined with Wilcoxon signed rank and LASSO regression, obtaining an accuracy of 95% 7% and sensitivity and specificity both equal to 95% 12% in the test set. Conclusions: In this study, radiomics has shown promising results in distinguishing left ventricle hypertrophy caused by CA from AS and might be used as non-invasive tool able to support clinical decision makin

Additional diagnostic value of cardiac magnetic resonance feature tracking in patients with biopsy-proven arrhythmogenic cardiomyopathy

none30siBackground: We aim to evaluate the value of Cardiac magnetic resonance (CMR) feature tracking (CMR-FT) in addition to Task Force Criteria(TFC) in patients with (arrhythmogenic cardiomyopathy) AC biopsy-proved. Methods: Thirty-five patients with AC histologically proven who performed CMR with late gadolinium enhancement (LGE) acquisition were enrolled. The study population was divided in Group1 (negative CMR TFC and LV ejection fraction≥55%) and Group2 (positive CMR TFC and/or LVEF<55%) and compared to an age and gender-matched control group. CMR datasets of all patients were analyzed to calculate LV indexed end-diastolic (LVEDi) and end-systolic (LVESi) volumes and RV indexed end-diastolic (RVEDi) and end-systolic (RVESi) volumes, both LV ejection fraction (LVEF) and RV ejection fraction (RVEF). Moreover, LV and RV global longitudinal (GLS), circumferential (GCS) and radial (GRS) strain were measured. Results: The AC patients showed both higher LVEDi (p:0.002) and RVEDi (p:0.017) and lower LVEF (p: 0.016) as compared to control patients. Moreover, AC patients showed impaired LV-GLS (p < 0.001), LV-GRS (p < 0.001), LV-GCS (p < 0.001) and RV-GRS (p:0.026) as compared to control subjects. Group1 patients showed a significant reduction of LV-GRS (p < 0.05) and LV-GCS p < 0.01) as compared to control subjects. At univariate analysis LV-GCS was the most discriminatory parameter between Group1 vs heathy subjects with an optimal cut-off of −15.8 (Sensitivity: 74%; Specificity: 10%). Conclusions: In patients with AC biopsy-proven, CMR-FT could improve the diagnostic yield in the subset of patients who results negative for imaging TFC criteria resulting as useful gatekeeper for indication of myocardial biopsy in case of equivocal clinical and imaging presentation.noneMuscogiuri G.; Fusini L.; Ricci F.; Sicuso R.; Guglielmo M.; Baggiano A.; Gasperetti A.; Casella M.; Mushtaq S.; Conte E.; Annoni A.; Formenti A.; Mancini M.E.; Babbaro M.; Mollace R.; Collevecchio A.; Scafuri S.; Kukavica D.; Andreini D.; Basso C.; Rizzo S.; De Gaspari M.; Priori S.; Dello Russo A.; Tondo C.; Pepi M.; Sommariva E.; Rabbat M.; Guaricci A.I.; Pontone G.Muscogiuri, G.; Fusini, L.; Ricci, F.; Sicuso, R.; Guglielmo, M.; Baggiano, A.; Gasperetti, A.; Casella, M.; Mushtaq, S.; Conte, E.; Annoni, A.; Formenti, A.; Mancini, M. E.; Babbaro, M.; Mollace, R.; Collevecchio, A.; Scafuri, S.; Kukavica, D.; Andreini, D.; Basso, C.; Rizzo, S.; De Gaspari, M.; Priori, S.; Dello Russo, A.; Tondo, C.; Pepi, M.; Sommariva, E.; Rabbat, M.; Guaricci, A. I.; Pontone, G