Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography
<b>Background</b>: Cardiovascular diseases are the leading cause of global mortality, with 80% of coronary heart disease in patients over 65. Understanding aging cardiovascular structures is crucial. Photon-counting computed tomography (PCCT) offers improved spatial and temporal resoluti...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/15/14/1796 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849246323909328896 |
|---|---|
| author | Alexander Hertel Mustafa Kuru Johann S. Rink Florian Haag Abhinay Vellala Theano Papavassiliu Matthias F. Froelich Stefan O. Schoenberg Isabelle Ayx |
| author_facet | Alexander Hertel Mustafa Kuru Johann S. Rink Florian Haag Abhinay Vellala Theano Papavassiliu Matthias F. Froelich Stefan O. Schoenberg Isabelle Ayx |
| author_sort | Alexander Hertel |
| collection | DOAJ |
| description | <b>Background</b>: Cardiovascular diseases are the leading cause of global mortality, with 80% of coronary heart disease in patients over 65. Understanding aging cardiovascular structures is crucial. Photon-counting computed tomography (PCCT) offers improved spatial and temporal resolution and better signal-to-noise ratio, enabling texture analysis in clinical routines. Detecting structural changes in aging left-ventricular myocardium may help predict cardiovascular risk. <b>Methods</b>: In this retrospective, single-center, IRB-approved study, 90 patients underwent ECG-gated contrast-enhanced cardiac CT using dual-source PCCT (NAEOTOM Alpha, Siemens). Patients were divided into two age groups (50–60 years and 70–80 years). The left ventricular myocardium was segmented semi-automatically, and radiomics features were extracted using pyradiomics to compare myocardial texture features. Epicardial adipose tissue (EAT) density, thickness, and other clinical parameters were recorded. Statistical analysis was conducted with R and a Python-based random forest classifier. <b>Results</b>: The study assessed 90 patients (50–60 years, <i>n</i> = 54, and 70–80 years, <i>n</i> = 36) with a mean age of 63.6 years. No significant differences were found in mean Agatston score, gender distribution, or conditions like hypertension, diabetes, hypercholesterolemia, or nicotine abuse. EAT measurements showed no significant differences. The Random Forest Classifier achieved a training accuracy of 0.95 and a test accuracy of 0.74 for age group differentiation. Wavelet-HLH_glszm_GrayLevelNonUniformity was a key differentiator. <b>Conclusions</b>: Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. Radiomics analysis of left ventricular myocardium offers a unique opportunity to visualize changes in myocardial texture during aging and could serve as a cardiac risk predictor. |
| format | Article |
| id | doaj-art-6d34a470aea14b71ac55121c5fd74cd7 |
| institution | Kabale University |
| issn | 2075-4418 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj-art-6d34a470aea14b71ac55121c5fd74cd72025-08-20T03:58:31ZengMDPI AGDiagnostics2075-44182025-07-011514179610.3390/diagnostics15141796Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed TomographyAlexander Hertel0Mustafa Kuru1Johann S. Rink2Florian Haag3Abhinay Vellala4Theano Papavassiliu5Matthias F. Froelich6Stefan O. Schoenberg7Isabelle Ayx8Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyFirst Department of Medicine-Cardiology, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, GermanyDepartment of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany<b>Background</b>: Cardiovascular diseases are the leading cause of global mortality, with 80% of coronary heart disease in patients over 65. Understanding aging cardiovascular structures is crucial. Photon-counting computed tomography (PCCT) offers improved spatial and temporal resolution and better signal-to-noise ratio, enabling texture analysis in clinical routines. Detecting structural changes in aging left-ventricular myocardium may help predict cardiovascular risk. <b>Methods</b>: In this retrospective, single-center, IRB-approved study, 90 patients underwent ECG-gated contrast-enhanced cardiac CT using dual-source PCCT (NAEOTOM Alpha, Siemens). Patients were divided into two age groups (50–60 years and 70–80 years). The left ventricular myocardium was segmented semi-automatically, and radiomics features were extracted using pyradiomics to compare myocardial texture features. Epicardial adipose tissue (EAT) density, thickness, and other clinical parameters were recorded. Statistical analysis was conducted with R and a Python-based random forest classifier. <b>Results</b>: The study assessed 90 patients (50–60 years, <i>n</i> = 54, and 70–80 years, <i>n</i> = 36) with a mean age of 63.6 years. No significant differences were found in mean Agatston score, gender distribution, or conditions like hypertension, diabetes, hypercholesterolemia, or nicotine abuse. EAT measurements showed no significant differences. The Random Forest Classifier achieved a training accuracy of 0.95 and a test accuracy of 0.74 for age group differentiation. Wavelet-HLH_glszm_GrayLevelNonUniformity was a key differentiator. <b>Conclusions</b>: Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. Radiomics analysis of left ventricular myocardium offers a unique opportunity to visualize changes in myocardial texture during aging and could serve as a cardiac risk predictor.https://www.mdpi.com/2075-4418/15/14/1796myocardial agingcardiac CTphoton-counting computed tomographyradiomics |
| spellingShingle | Alexander Hertel Mustafa Kuru Johann S. Rink Florian Haag Abhinay Vellala Theano Papavassiliu Matthias F. Froelich Stefan O. Schoenberg Isabelle Ayx Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography Diagnostics myocardial aging cardiac CT photon-counting computed tomography radiomics |
| title | Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography |
| title_full | Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography |
| title_fullStr | Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography |
| title_full_unstemmed | Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography |
| title_short | Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography |
| title_sort | radiomics signature of aging myocardium in cardiac photon counting computed tomography |
| topic | myocardial aging cardiac CT photon-counting computed tomography radiomics |
| url | https://www.mdpi.com/2075-4418/15/14/1796 |
| work_keys_str_mv | AT alexanderhertel radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT mustafakuru radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT johannsrink radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT florianhaag radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT abhinayvellala radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT theanopapavassiliu radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT matthiasffroelich radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT stefanoschoenberg radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography AT isabelleayx radiomicssignatureofagingmyocardiumincardiacphotoncountingcomputedtomography |