CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.

<h4>Purpose</h4>To explore whether there are computed tomography (CT) imaging biomarkers that can stratify the severity of patients with pulmonary hypertension (PH).<h4>Methods</h4>We retrospectively enrolled 144 consecutive patients with suspected PH who underwent CT pulmona...

Full description

Saved in:
Bibliographic Details
Main Authors: Do Won Yoon, Yeonyee E Yoon, In Chang Hwang, Wonjae Lee, Ki-Yeal Lee, Eun Ju Chun
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0313235
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850040555733516288
author Do Won Yoon
Yeonyee E Yoon
In Chang Hwang
Wonjae Lee
Ki-Yeal Lee
Eun Ju Chun
author_facet Do Won Yoon
Yeonyee E Yoon
In Chang Hwang
Wonjae Lee
Ki-Yeal Lee
Eun Ju Chun
author_sort Do Won Yoon
collection DOAJ
description <h4>Purpose</h4>To explore whether there are computed tomography (CT) imaging biomarkers that can stratify the severity of patients with pulmonary hypertension (PH).<h4>Methods</h4>We retrospectively enrolled 144 consecutive patients with suspected PH who underwent CT pulmonary angiography and right heart catheterization (RHC). CT findings were analyzed by two observers for large vessel size [ascending aorta (A), pulmonary artery (P), inferior vena cava (IVC)], each chamber size, and septal angle. We investigated the associations between CT imaging parameters and the mean pulmonary artery pressure (mPAP) from RHC. During a median follow-up of 36 months, we observed major adverse cardiovascular events (MACE; all-cause mortality and hospitalization for PH worsening). Univariate and multivariate Cox regression models were used with hazard ratios (HR) and 95% confidence intervals (95% CI) to determine independent predictors of MACE in patients with PH.<h4>Results</h4>Of 144 patients, 116 (80.2%) were diagnosed with PH based on an mPAP of 20 mmHg. Among CT parameters, P, P/A ratio, right ventricle (RV), and RV/left ventricle (LV) ratio were strongly correlated with mPAP values (Pearson's correlation coefficient, all r < 0.001). During the follow-up period, 44 (30.6%) patients developed MACE (14 deaths and 30 hospitalizations). Using multivariate Cox regression analysis, the RV/LV ratio (HR 2.32; 95% CI: 1.17-4.59) was the best predictor of MACE, followed by age (HR 1.03, 95% CI;1.00-1.05) (all p < 0.05). Among various CT parameters, A, P, and P/A ratio showed excellent reliability with intraclass correlation coefficient ≥ 0.95.<h4>Conclusion</h4>Among CT parameters, the RV/LV ratio was the most robust predictor of MACE in patients with PH, while the P and P/A ratios served as reliable indicators reflecting mPAP levels.
format Article
id doaj-art-48a76c1856744112b691886fa4af5fb0
institution DOAJ
issn 1932-6203
language English
publishDate 2025-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj-art-48a76c1856744112b691886fa4af5fb02025-08-20T02:56:03ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031323510.1371/journal.pone.0313235CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.Do Won YoonYeonyee E YoonIn Chang HwangWonjae LeeKi-Yeal LeeEun Ju Chun<h4>Purpose</h4>To explore whether there are computed tomography (CT) imaging biomarkers that can stratify the severity of patients with pulmonary hypertension (PH).<h4>Methods</h4>We retrospectively enrolled 144 consecutive patients with suspected PH who underwent CT pulmonary angiography and right heart catheterization (RHC). CT findings were analyzed by two observers for large vessel size [ascending aorta (A), pulmonary artery (P), inferior vena cava (IVC)], each chamber size, and septal angle. We investigated the associations between CT imaging parameters and the mean pulmonary artery pressure (mPAP) from RHC. During a median follow-up of 36 months, we observed major adverse cardiovascular events (MACE; all-cause mortality and hospitalization for PH worsening). Univariate and multivariate Cox regression models were used with hazard ratios (HR) and 95% confidence intervals (95% CI) to determine independent predictors of MACE in patients with PH.<h4>Results</h4>Of 144 patients, 116 (80.2%) were diagnosed with PH based on an mPAP of 20 mmHg. Among CT parameters, P, P/A ratio, right ventricle (RV), and RV/left ventricle (LV) ratio were strongly correlated with mPAP values (Pearson's correlation coefficient, all r < 0.001). During the follow-up period, 44 (30.6%) patients developed MACE (14 deaths and 30 hospitalizations). Using multivariate Cox regression analysis, the RV/LV ratio (HR 2.32; 95% CI: 1.17-4.59) was the best predictor of MACE, followed by age (HR 1.03, 95% CI;1.00-1.05) (all p < 0.05). Among various CT parameters, A, P, and P/A ratio showed excellent reliability with intraclass correlation coefficient ≥ 0.95.<h4>Conclusion</h4>Among CT parameters, the RV/LV ratio was the most robust predictor of MACE in patients with PH, while the P and P/A ratios served as reliable indicators reflecting mPAP levels.https://doi.org/10.1371/journal.pone.0313235
spellingShingle Do Won Yoon
Yeonyee E Yoon
In Chang Hwang
Wonjae Lee
Ki-Yeal Lee
Eun Ju Chun
CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.
PLoS ONE
title CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.
title_full CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.
title_fullStr CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.
title_full_unstemmed CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.
title_short CT imaging biomarkers to predict severity and prognosis of pulmonary hypertension.
title_sort ct imaging biomarkers to predict severity and prognosis of pulmonary hypertension
url https://doi.org/10.1371/journal.pone.0313235
work_keys_str_mv AT dowonyoon ctimagingbiomarkerstopredictseverityandprognosisofpulmonaryhypertension
AT yeonyeeeyoon ctimagingbiomarkerstopredictseverityandprognosisofpulmonaryhypertension
AT inchanghwang ctimagingbiomarkerstopredictseverityandprognosisofpulmonaryhypertension
AT wonjaelee ctimagingbiomarkerstopredictseverityandprognosisofpulmonaryhypertension
AT kiyeallee ctimagingbiomarkerstopredictseverityandprognosisofpulmonaryhypertension
AT eunjuchun ctimagingbiomarkerstopredictseverityandprognosisofpulmonaryhypertension