# Synchrotron-based X-ray 3D phase contrast imaging and analysis of transmural myocardial tissue from heart failure patients

## TL;DR

This paper uses synchrotron X-ray imaging to study heart tissue from heart failure patients, revealing new 3D structural details that could improve disease understanding.

## Contribution

The study introduces synchrotron-based X-ray phase contrast imaging as a novel method for 3D analysis of myocardial tissue in heart failure.

## Key findings

- X-PCI visualized myocyte orientation disruptions in dilated cardiomyopathy.
- Collagen matrix patterns varied by heart failure cause.
- X-PCI provides high-resolution 3D imaging of myocardial tissue.

## Abstract

Synchrotron-based X-ray phase contrast imaging (X-PCI) is a non-destructive imaging modality that can provide high resolution three-dimensional (3D) visualisation of transmural myocardial tissue, collagen matrix reconstruction, and quantification of myocyte aggregate orientation (‘myomapping’). We aimed to use X-PCI to analyse microstructural features in transmural myocardial samples from patients with advanced heart failure. Six patients were included: two receiving a left ventricular assist device (LVAD) for ischaemic (ICM) and dilated cardiomyopathy (DCM), and four undergoing heart transplantation (HTx), two for the ICM, one for DCM and one for toxic cardiomyopathy. Samples were obtained by left ventricular (LV) apical coring (LVAD group) or from the LV free wall of the explanted hearts (HTx group) and imaged by X-PCI using a multi-scale setup (maximal resolution at 0.65 µm pixel size). The 3D image datasets were analysed via two-dimensional orthogonal cuts in different layers. Visualisation and quantification of the myocyte aggregates orientation showed a disruption in epicardial-to-endocardial transition in DCM, whereas the collagen matrix reconstruction identified characteristic fibrosis patterns amongst different HF aetiologies. In conclusion, X-PCI is a 3D imaging method that can extend the amount of information available from ex-vivo tissue analysis and, as an addition to multimodal imaging protocols, potentially improve disease phenotyping.

The online version contains supplementary material available at 10.1038/s41598-025-04012-5.