Associations of lesion-specific pericoronary adipose tissue attenuation and CT-derived fractional flow reserve with coronary stenosis progression: a retrospective selected-lesion study

Background Coronary disease that is non-obstructive at baseline may progress, while luminal stenosis alone does not capture local pericoronary tissue characteristics or lesion-specific functional impairment. Objective To assess associations of lesion-specific pericoronary adipose tissue (PCAT) attenuation and CT-derived fractional flow reserve (CT-FFR) with imaging-defined stenosis progression and to evaluate an exploratory multivariable model. Methods This retrospective single-center study included 201 patients undergoing serial coronary computed tomography angiography with selected target lesions classified as minimal or mild at baseline. In progressors, the lesion with the greatest follow-up progression was selected; in non-progressors, the lesion with the greatest baseline stenosis was selected. Thus, target-lesion selection was outcome dependent. Lesion-specific PCAT and CT-FFR were quantified using dedicated automated software after target-lesion identification. Five logistic models specified before reanalysis fitting were fitted in a common complete-case population ( n = 191), and Model E retained nine predictors. Internal performance was assessed with 2,000 patient-level bootstrap resamples. Results Progression occurred in 115 of 201 patients. In Model E, less-negative PCAT attenuation (odds ratio [OR] per 10-HU increase, 1.552; 95% CI, 1.137–2.119; P = 0.006) and lower CT-FFR (OR per 0.05 decrease, 1.360; 95% CI, 1.041–1.778; P = 0.024) were associated with progression; age showed an inverse conditional association (OR per 10-year increase, 0.509; 95% CI, 0.346–0.749; P < 0.001). Model E had an apparent AUC of 0.767 (95% CI, 0.700–0.834) and an optimism-corrected AUC of 0.722 (95% bootstrap interval, 0.659–0.787). The corrected Brier score was 0.217 (0.189–0.251), calibration intercept −0.0002 (−0.354 to 0.361), and calibration slope 0.779 (0.539–1.100). Versus Model B, corrected Δ AUC was 0.053 (−0.005 to 0.088), indicating apparent improvement with uncertainty. Conclusions Less-negative lesion-specific PCAT attenuation and lower CT-FFR were associated with imaging-defined stenosis progression. The combined model showed moderate optimism-corrected discrimination, but incremental discrimination remained uncertain. Because lesion selection in progressors incorporated follow-up information and no external validation was available, this internally derived model is exploratory and is not a clinically validated decision tool.

Authors

Institutions

Publication Details

Journal
Frontiers in Cardiovascular Medicine
Published
2026-11-09
DOI
https://doi.org/10.3389/fcvm.2026.1954142
Primary Topic
Cardiovascular Disease and Adiposity
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Associations of lesion-specific pericoronary adipose tissue attenuation and CT-derived fractional flow reserve with coronary stenosis progression: a retrospective selected-lesion study

Li Feng, Sheng He, Wenfeng Wei, CHEN Suping et al.
Frontiers in Cardiovascular Medicine
Cardiovascular Disease and Adiposity
article

Associations of lesion-specific pericoronary adipose tissue attenuation and CT-derived fractional flow reserve with coronary stenosis progression: a retrospective selected-lesion study

Li Feng, Sheng He, Wenfeng Wei, CHEN Suping, Kenan Song, Jun Wang, Yanjun Hou, Jian Liu, Wenqing Chen, Zengyu Jiang
article en

Abstract

Background Coronary disease that is non-obstructive at baseline may progress, while luminal stenosis alone does not capture local pericoronary tissue characteristics or lesion-specific functional impairment. Objective To assess associations of lesion-specific pericoronary adipose tissue (PCAT) attenuation and CT-derived fractional flow reserve (CT-FFR) with imaging-defined stenosis progression and to evaluate an exploratory multivariable model. Methods This retrospective single-center study included 201 patients undergoing serial coronary computed tomography angiography with selected target lesions classified as minimal or mild at baseline. In progressors, the lesion with the greatest follow-up progression was selected; in non-progressors, the lesion with the greatest baseline stenosis was selected. Thus, target-lesion selection was outcome dependent. Lesion-specific PCAT and CT-FFR were quantified using dedicated automated software after target-lesion identification. Five logistic models specified before reanalysis fitting were fitted in a common complete-case population ( n = 191), and Model E retained nine predictors. Internal performance was assessed with 2,000 patient-level bootstrap resamples. Results Progression occurred in 115 of 201 patients. In Model E, less-negative PCAT attenuation (odds ratio [OR] per 10-HU increase, 1.552; 95% CI, 1.137–2.119; P = 0.006) and lower CT-FFR (OR per 0.05 decrease, 1.360; 95% CI, 1.041–1.778; P = 0.024) were associated with progression; age showed an inverse conditional association (OR per 10-year increase, 0.509; 95% CI, 0.346–0.749; P < 0.001). Model E had an apparent AUC of 0.767 (95% CI, 0.700–0.834) and an optimism-corrected AUC of 0.722 (95% bootstrap interval, 0.659–0.787). The corrected Brier score was 0.217 (0.189–0.251), calibration intercept −0.0002 (−0.354 to 0.361), and calibration slope 0.779 (0.539–1.100). Versus Model B, corrected Δ AUC was 0.053 (−0.005 to 0.088), indicating apparent improvement with uncertainty. Conclusions Less-negative lesion-specific PCAT attenuation and lower CT-FFR were associated with imaging-defined stenosis progression. The combined model showed moderate optimism-corrected discrimination, but incremental discrimination remained uncertain. Because lesion selection in progressors incorporated follow-up information and no external validation was available, this internally derived model is exploratory and is not a clinically validated decision tool.

Frontiers in Cardiovascular MedicineVol. 13
Shanxi Medical University (CN), First Hospital of Shanxi Medical University (CN)
Cardiovascular Disease and Adiposity
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.

Laika access coming soon