Left ventricular strain and hemodynamic forces from cine CMR for detecting constrictive physiology in pericarditis

Abstract Objectives Constrictive physiology (CP) may complicate pericarditis and requires timely recognition, yet CMR assessment is largely qualitative. This study evaluated the diagnostic value of cine-based strain and hemodynamic forces (HDF) analysis for distinguishing CP from non-constrictive physiology (NCP). Materials and methods HDF analysis was retrospectively performed on routine 1.5 T cine images from 2008 to 2024 in patients with CMR-confirmed pericarditis. Patients were classified as CP or NCP non-invasively using guideline-defined clinical and imaging criteria. In addition to left ventricular (LV) function, global longitudinal strain (GLS), global circumferential strain (GCS), and HDF parameters (e.g., apical–basal [A–B] HDF strength) were analyzed. Student’s t -test, binary logistic regression, and receiver operating characteristic analysis were performed. Results Among 103 patients with pericarditis (mean age 53 ± 18 years), 42 (41%) had CP and 61 (59%) had NCP. LV ejection fraction did not differ between groups, whereas LV end-diastolic volume index was reduced in CP (62.0 ± 16.7 mL/m² vs 75.4 ± 18.2, p = 0.003). Strain and HDF parameters were significantly impaired in CP (e.g., A–B HDF strength: 15.3 ± 6.2% vs 21.4 ± 7.3%, p < 0.001). LV GLS and A–B HDF strength achieved good diagnostic performance for detecting CP (area under the curve [AUC] 0.76 and 0.78, respectively), further enhanced when combined (AUC 0.82). Both were independent predictors of CP on multivariable analysis (odds ratio [OR] 1.21, p = 0.002; and OR 0.83, p = 0.007, respectively). Conclusions LV strain and HDF analysis using routine CMR cine enabled quantitative detection of CP in pericarditis. A–B HDF strength, particularly in combination with LV GLS, provided the highest diagnostic accuracy. Clinical relevance statement Strain and HDF analysis derived from routine cine CMR enable detection of CP in pericarditis, providing novel quantitative parameters that complement conventional qualitative CMR assessment of CP without additional sequences. Key Points CP may complicate pericarditis and can be addressed by targeted therapy, yet CMR diagnosis remains largely qualitative and challenging. Novel CMR metrics, including LV GLS and apical–basal HDF, showed good diagnostic performance. LV strain and HDF analysis from routine cine CMR cine enabled quantitative detection of CP in pericarditis without additional sequences.

Authors

Institutions

Publication Details

Journal
Insights into Imaging
Published
2026-06-13
DOI
https://doi.org/10.1186/s13244-026-02332-2
Primary Topic
Pericarditis and Cardiac Tamponade
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Left ventricular strain and hemodynamic forces from cine CMR for detecting constrictive physiology in pericarditis

Thomas Vollbrecht, Dmitrij Kravchenko, Taraneh Aziz-Safaie, Narine Mesropyan et al.
Insights into Imaging
Pericarditis and Cardiac Tamponade
article

Left ventricular strain and hemodynamic forces from cine CMR for detecting constrictive physiology in pericarditis

Thomas Vollbrecht, Dmitrij Kravchenko, Taraneh Aziz-Safaie, Narine Mesropyan, Alexander Isaak, Lucia D Beissel, Simon Bienert, Sophia Juraschitz, L Bischoff, A Proff, Julian A. Luetkens, Claus C. Pieper, Daniel L. Kuetting
article en

Abstract

Abstract Objectives Constrictive physiology (CP) may complicate pericarditis and requires timely recognition, yet CMR assessment is largely qualitative. This study evaluated the diagnostic value of cine-based strain and hemodynamic forces (HDF) analysis for distinguishing CP from non-constrictive physiology (NCP). Materials and methods HDF analysis was retrospectively performed on routine 1.5 T cine images from 2008 to 2024 in patients with CMR-confirmed pericarditis. Patients were classified as CP or NCP non-invasively using guideline-defined clinical and imaging criteria. In addition to left ventricular (LV) function, global longitudinal strain (GLS), global circumferential strain (GCS), and HDF parameters (e.g., apical–basal [A–B] HDF strength) were analyzed. Student’s t -test, binary logistic regression, and receiver operating characteristic analysis were performed. Results Among 103 patients with pericarditis (mean age 53 ± 18 years), 42 (41%) had CP and 61 (59%) had NCP. LV ejection fraction did not differ between groups, whereas LV end-diastolic volume index was reduced in CP (62.0 ± 16.7 mL/m² vs 75.4 ± 18.2, p = 0.003). Strain and HDF parameters were significantly impaired in CP (e.g., A–B HDF strength: 15.3 ± 6.2% vs 21.4 ± 7.3%, p < 0.001). LV GLS and A–B HDF strength achieved good diagnostic performance for detecting CP (area under the curve [AUC] 0.76 and 0.78, respectively), further enhanced when combined (AUC 0.82). Both were independent predictors of CP on multivariable analysis (odds ratio [OR] 1.21, p = 0.002; and OR 0.83, p = 0.007, respectively). Conclusions LV strain and HDF analysis using routine CMR cine enabled quantitative detection of CP in pericarditis. A–B HDF strength, particularly in combination with LV GLS, provided the highest diagnostic accuracy. Clinical relevance statement Strain and HDF analysis derived from routine cine CMR enable detection of CP in pericarditis, providing novel quantitative parameters that complement conventional qualitative CMR assessment of CP without additional sequences. Key Points CP may complicate pericarditis and can be addressed by targeted therapy, yet CMR diagnosis remains largely qualitative and challenging. Novel CMR metrics, including LV GLS and apical–basal HDF, showed good diagnostic performance. LV strain and HDF analysis from routine cine CMR cine enabled quantitative detection of CP in pericarditis without additional sequences.

Insights into ImagingVol. 17(1)
University Hospital Bonn (DE)
Openalex Percentile: Top 6%
Pericarditis and Cardiac Tamponade
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.