PhD Scientific Days 2026

Cardiovascular Medicine and Research 3.

Prognostic Value of Myocardial Radiomic Phenotype for Long-Term Mortality in Patients undergoing Transcatheter Aortic Valve Implantation

Előadó neve

Dr. Benyó, Franciska

Neptune code

YB2GJE

Előadó munkahelye

Gottsgen National Cardiovascular Center

Előadó telefonszáma

+36202757626

Előadó e-mail címe

franciska.benyo@gokvi.hu

Az előadás címe

Prognostic Value of Myocardial Radiomic Phenotype for Long-Term Mortality in Patients undergoing Transcatheter Aortic Valve Implantation

Szerző(k) neve és munkahelye

Franciska Benyó MD¹, Fanni Mohácsi MD¹, Shan-yu Lin MD¹, Zsolt Szedlacsek MD¹, Anita Káposzta MD¹, Mónika Dénes MD, PhD¹, Péter Andréka MD, PhD¹, Márton Kolossváry MD, PhD¹

1: Gottsegen National Cardiovascular Center

Bemutatás módja

Szóbeli

Szekció

Cardiovascular Medicine and Research 3.

Language of the presentation

English

Preferred session

Cardiovascular Medicine and Research

Összefoglaló szövege

Introduction:
Survival rates and quality-of-life after transcatheter aortic valve implantation (TAVI) vary widely among patients, while predictors of favorable outcome are still unclear. While TAVI reduces afterload and facilitates left ventricle (LV) remodeling, the presence of pre-existing myocardial damage may limit beneficial effects. Currently, methods to assess the remodeling capacity of the LV myocardium (LVM) are limited.
Aims:
The aim of this study was to assess whether radiomic analysis of preprocedural cardiac CT can characterize LV myocardial remodeling capacity and predict long‑term all‑cause mortality after TAVI.
Method:
In this observational cohort study, we included consecutive patients who underwent TAVI at out institution between January 1, 2020, and April 30, 2025. Preprocedural LVM was segmented using a semi-automated approach. A total of 615 radiomic features—139 (23%) intensity-based, 450 (73%) textural, and 26 (4%) morphological features—were extracted and evaluated for their prognostic association with all-cause mortality. Cox proportional hazards models adjusted for age, sex, diabetes mellitus, hypertension, significant coronary artery disease, atrial fibrillation, high aortic valve gradient (>40 mmHg), low-flow status (stroke volume index <35 mL/m²), preserved ejection fraction (≥50%), NYHA functional class, and CT-derived LV mass index were used. False discovery rate (FDR) correction was applied to account for multiple comparisons.
Results:
In total, 1,101 patients undergoing TAVI were analyzed (mean age 81.4 ± 4.0 years; 57% female; 77% with high-gradient aortic stenosis). During a median follow-up of 1.8 years (IQR: 1.0–3.1 years), 297 patients passed away. In multivariable Cox regression models adjusted for clinical risk factors, 282 radiomic features (46%) were significantly associated with all-cause mortality. After false discovery rate correction, significant associations were observed in 62 intensity-based features (45%), 218 textural features (48%), and 2 morphological features (8%).
Conclusion:
Pre‑TAVI CT‑based left ventricular myocardial radiomic features are associated with long‑term all‑cause mortality and may enable improved risk stratification and personalized treatment strategies in TAVI patients.
Funding:
Project PD147269, Excellence 151118

University

Semmelweis University

Supervisor

Márton Kolossváry MD, PhD

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

phd.section.field

in doctoral studies before complex exam (PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

jóváhagyta

Előadó

9367

Start

15:15

End

15:25