Identifying spatially variable genes by projecting to morphologically relevant curves.

Spatial transcriptomics enables high-resolution gene expression measurements while preserving the two-dimensional spatial organization of the sample. A common objective in spatial transcriptomics data analysis is to identify spatially variable genes within predefined cell types or regions within the tissue. However, these regions are often implicitly one-dimensional, making standard two-dimensional coordinate-based methods less effective as they overlook the underlying tissue organization.

Machine learning for pacemaker implantation prediction after TAVI using multimodal imaging data.

Pacemaker implantation (PMI) after transcatheter aortic valve implantation (TAVI) is a common complication. While computed tomography (CT) scan data are known predictors of PMI, no machine learning (ML) model integrating CT with clinical, ECG, and transthoracic echocardiography (TTE) data has been proposed. This study investigates the contribution of ML methods to predict PMI after TAVI, with a focus on the role of CT imaging data.

Optical coherence tomography characterization of degradation kinetics between second- and third-generation resorbable magnesium scaffold.

Aims: This preclinical study aimed to establish optical coherence tomography (OCT)-derived parameters that could be used in the clinical setting for assessing strut degradation in the third-generation drug-eluting resorbable magnesium scaffold (DREAMS-3G), and characterize the comparative degradation profile against its precursor device (Magmaris scaffold).

Methods And Results: Twelve DREAMS-3G and 10 Magmaris scaffolds were implanted in juvenile pigs, and OCT images obtained at baseline and follow-up (6 or 12 months). Strut degradation was assessed by planimetric analysis and compared with OCT-derived indices to validate their diagnostic accuracy.

Intravascular ICG-enhanced NIRF-IVUS imaging to assess progressive atherosclerotic lesions in excised human coronary arteries.

Indocyanine green (ICG)-enhanced intravascular near-infrared fluorescence (NIRF) imaging enhances the information obtained with intravascular ultrasound (IVUS) by visualizing pathobiological characteristics of atherosclerotic plaques. To advance our understanding of this hybrid method, we aimed to assess the potential of NIRF-IVUS to identify different stages of atheroma progression by characterizing ICG uptake in human pathological specimens. After excision, 15 human coronary specimens from 13 adult patients were ICG-perfused and imaged with NIRF-IVUS.