From imaging to therapy: a novel photon-counting CT method for patient-specific image modeling and individualized atrial ablation strategies

In cardiac electrophysiology, preprocedural imaging has the potential to improve ablation strategies on an individual basis. Although clinical tools are increasingly being developed, data on practical workflows are limited. In this study, we sought to evaluate a high-resolution PCCT-based framework for individualized lesion design and digital modeling of ablation lines. In 198 patients, PCCT was performed before catheter ablation of atrial fibrillation (AF). Imaging data were semi-automatically segmented. Metrics such as left atrial wall thickness (LAWT) and epicardial adipose tissue (EAT) were extracted. Several ablation lesions were simulated, including linear lesions and circumferential pulmonary vein isolation (PVI) sets. LAWT along a standard ablation line was compared to individualized lines. For proof of concept, imaging-based decisions on lesion sets were applied to clinical cases. In all 198 patients, the imaging resolution of the PCCT scan was sufficient for further semi-automated segmentation. Further analysis of wall thickness revealed a mean wall thickness in the left atrium of 1.57 ± 0.75 mm (range 0.1–8.25 mm; median 1.43 mm). Mean EAT thickness was 1.59 ± 2.11 mm (range 0–10.22 mm; median 1.01 mm). Using a custom-developed algorithm, ablation lesions could be simulated and measured for length, wall thickness distribution, and EAT. PCCT provides high-resolution structural imaging enabling individualized atrial modeling. Beyond visualizing atrial wall thickness and epicardial adipose tissue, this method forms the basis for an atrial twin, which allow virtual testing and optimization of ablation strategies. Personalized imaging may aid in creating continuous, durable lesions, minimizing the risk of reconnection and ablation failure.