Right ventricular pressure-strain relationship-derived myocardial work reflects contractility: Validation with invasive pressure-volume analysis.

Three-dimensional (3D) echocardiography-derived right ventricular (RV) ejection fraction (EF) and global longitudinal strain (GLS) are valuable RV functional markers; nevertheless, they are substantially load-dependent. Global myocardial work index (GMWI) is a novel parameter calculated by the area of the RV pressure-strain loop. By adjusting myocardial deformation to instantaneous pressure, it may reflect contractility. To test this hypothesis, we enrolled 60 patients who underwent RV pressure-conductance catheterization to determine load-independent markers of RV contractility and ventriculo-arterial coupling. Detailed 3D echocardiography was also performed, and we calculated RV EF, RV GLS, and using the RV pressure trace curve, RV GWMI. While neither RV EF nor GLS correlated with Ees, GMWI strongly correlated with Ees. In contrast, RV EF and GLS showed a relationship with Ees/Ea. By dividing the population based on their Reveal Lite 2 risk classification, different characteristics were seen among the subgroups. RV GMWI may emerge as a useful clinical tool for risk stratification and follow-up in patients with RV dysfunction.

Phenogrouping and risk stratification of patients undergoing cardiac resynchronization therapy upgrade using topological data analysis.

Choosing the optimal device during cardiac resynchronization therapy (CRT) upgrade can be challenging. Therefore, we sought to provide a solution for identifying patients in whom upgrading to a CRT-defibrillator (CRT-D) is associated with better long-term survival than upgrading to a CRT-pacemaker (CRT-P). To this end, we first applied topological data analysis to create a patient similarity network using 16 clinical features of 326 patients without prior ventricular arrhythmias who underwent CRT upgrade. Then, in the generated circular network, we delineated three phenogroups exhibiting significant differences in clinical characteristics and risk of all-cause mortality. Importantly, only in the high-risk phenogroup was upgrading to a CRT-D associated with better survival than upgrading to a CRT-P (hazard ratio: 0.454 (0.228-0.907), p = 0.025). Finally, we assigned each patient to one of the three phenogroups based on their location in the network and used this labeled data to train multi-class classifiers to enable the risk stratification of new patients. During internal validation, an ensemble of 5 multi-layer perceptrons exhibited the best performance with a balanced accuracy of 0.898 (0.854-0.942) and a micro-averaged area under the receiver operating characteristic curve of 0.983 (0.980-0.986). To allow further validation, we made the proposed model publicly available ( https://github.com/tokmarton/crt-upgrade-risk-stratification ).

Topological data analysis to identify cardiac resynchronization therapy patients exhibiting benefit from an implantable cardioverter-defibrillator.

BACKGROUND: Current guidelines recommend considering multiple factors while deciding between cardiac resynchronization therapy with a defibrillator (CRT-D) or a pacemaker (CRT-P). Nevertheless, it is still challenging to pinpoint those candidates who will benefit from choosing a CRT-D device in terms of survival. OBJECTIVE: We aimed to use topological data analysis (TDA) to identify phenogroups of CRT patients in whom CRT-D is associated with better survival than CRT-P. METHODS: We included 2603 patients who underwent CRT-D (54%) or CRT-P (46%) implantation at Semmelweis University between 2000 and 2018. The primary endpoint was all-cause mortality. We applied TDA to create a patient similarity network using 25 clinical features. Then, we identified multiple phenogroups in the generated network and compared the groups' clinical characteristics and survival. RESULTS: Five- and 10-year mortality were 43 (40-46)% and 71 (67-74)% in patients with CRT-D and 48 (45-50)% and 71 (68-74)% in those with CRT-P, respectively. TDA created a circular network in which we could delineate five phenogroups showing distinct patterns of clinical characteristics and outcomes. Three phenogroups (1, 2, and 3) included almost exclusively patients with non-ischemic etiology, whereas the other two phenogroups (4 and 5) predominantly comprised ischemic patients. Interestingly, only in phenogroups 2 and 5 were CRT-D associated with better survival than CRT-P (adjusted hazard ratio 0.61 [0.47-0.80], p < 0.001 and adjusted hazard ratio 0.84 [0.71-0.99], p = 0.033, respectively). CONCLUSIONS: By simultaneously evaluating various clinical features, TDA may identify patients with either ischemic or non-ischemic etiology who will most likely benefit from the implantation of a CRT-D instead of a CRT-P. Topological data analysis to identify phenogroups of CRT patients in whom CRT-D is associated with better survival than CRT-P. AF atrial fibrillation, CRT cardiac resynchronization therapy, CRT-D cardiac resynchronization therapy defibrillator, CRT-P cardiac resynchronization therapy pacemaker, DM diabetes mellitus, HTN hypertension, LBBB left bundle branch block, LVEF left ventricular ejection fraction, MDS multidimensional scaling, MRA mineralocorticoid receptor antagonist, NYHA New York Heart Association.

Design of a Machine Learning System to Predict the Thickness of a Melanoma Lesion in a Non-Invasive Way from Dermoscopic Images.

OBJECTIVES: Melanoma is the deadliest form of skin cancer, but it can be fully cured through early detection and treatment in 99% of cases. Our aim was to develop a non-invasive machine learning system that can predict the thickness of a melanoma lesion, which is a proxy for tumor progression, through dermoscopic images. This method can serve as a valuable tool in identifying urgent cases for treatment. METHODS: A modern convolutional neural network architecture (EfficientNet) was used to construct a model capable of classifying dermoscopic images of melanoma lesions into three distinct categories based on thickness. We incorporated techniques to reduce the impact of an imbalanced training dataset, enhanced the generalization capacity of the model through image augmentation, and utilized five-fold cross-validation to produce more reliable metrics. RESULTS: Our method achieved 71% balanced accuracy for three-way classification when trained on a small public dataset of 247 melanoma images. We also presented performance projections for larger training datasets. CONCLUSIONS: Our model represents a new state-of-the-art method for classifying melanoma thicknesses. Performance can be further optimized by expanding training datasets and utilizing model ensembles. We have shown that earlier claims of higher performance were mistaken due to data leakage during the evaluation process.

There is more than just longitudinal strain: Prognostic significance of biventricular circumferential mechanics.

Introduction: Despite the significant contribution of circumferential shortening to the global ventricular function, data are scarce concerning its prognostic value on long-term mortality. Accordingly, our study aimed to assess both left (LV) and right ventricular (RV) global longitudinal (GLS) and global circumferential strain (GCS) using three-dimensional echocardiography (3DE) to determine their prognostic importance. Methods: Three hundred fifty-seven patients with a wide variety of left-sided cardiac diseases were retrospectively identified (64 ± 15 years, 70% males) who underwent clinically indicated 3DE. LV and RV GLS, and GCS were quantified. To determine the prognostic power of the different patterns of biventricular mechanics, we divided the patient population into four groups. Group 1 consisted of patients with both LV GLS and RV GCS above the respective median values; Group 2 was defined as patients with LV GLS below the median while RV GCS above the median, whereas in Group 3, patients had LV GLS values above the median, while RV GCS was below median. Group 4 was defined as patients with both LV GLS and RV GCS below the median. Patients were followed up for a median of 41 months. The primary endpoint was all-cause mortality. Results: Fifty-five patients (15%) met the primary endpoint. Impaired values of both LV GCS (HR, 1.056 [95% CI, 1.027-1.085], p < 0.001) and RV GCS (1.115 [1.068-1.164], p < 0.001) were associated with increased risk of death by univariable Cox regression. Patients with both LV GLS and RV GCS below the median (Group 4) had a more than 5-fold increased risk of death compared with those in Group 1 (5.089 [2.399-10.793], p < 0.001) and more than 3.5-fold compared with those in Group 2 (3.565 [1.256-10.122], p = 0.017). Interestingly, there was no significant difference in mortality between Group 3 (with LV GLS above the median) and Group 4, but being categorized into Group 3 versus Group 1 still held a more than 3-fold risk (3.099 [1.284-7.484], p = 0.012). Discussion: The impaired values of both LV and RV GCS are associated with long-term all-cause mortality, emphasizing the importance of assessing biventricular circumferential mechanics. Reduced RV GCS is associated with significantly increased risk of mortality even if LV GLS is preserved.