ArticleQuantitative imaging in medicine and surgery2026
Sex differences in CT-FFR of myocardial bridging with or without atherosclerosis: an AI-based quantitative study.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Myocardial bridging (MB) is a prevalent coronary anomaly with potential links to major adverse cardiac events. While computed tomography-derived fractional flow reserve (FFRCT) offers a non-invasive functional assessment, current evidence predominantly treats MB as a homogeneous entity, overlooking potential sex differences in hemodynamic impact. Existing studies often fail to distinguish between isolated MB and MB with concomitant atherosclerosis, and rarely employ sex-stratified analyses. This study aimed to noninvasively assess sex-specific differences in FFRCT among patients with MB, with or without atherosclerosis, using an artificial intelligence (AI)-based platform to clarify the clinical implications of these differences. Methods: This retrospective cohort study included 300 left anterior descending artery (LAD)-MB patients, subdivided into an MB group (n=155) and an MB with atherosclerosis (MBLA) group (n=145), along with 104 controls with normal coronary computed tomography angiography (CCTA) findings. Demographic data, clinical symptoms, and risk factors were collected. Morphological parameters of MB were quantitatively analyzed using cardiac function post-processing software, and whole-vessel and local segments (proximal to MB, within MB, and distal to MB) FFRCT values were obtained via an AI-based platform (Shukun-FFRCT). Patients were stratified by FFRCT <0.8, and statistical analyses [t-tests, analysis of variance (ANOVA), Mann-Whitney U tests, and binary logistic regression] were applied to examine sex-based associations with FFRCT abnormalities and influencing factors. Results: (I) Demographic analysis revealed significantly higher proportions of male patients in the MB (52.9%) and MBLA (57.2%) groups compared to controls (24.0%, both P<0.05). (II) Sex-stratified analysis within pathological subgroups showed that in the MB group, females had significantly lower distal FFRCT values (FFR3: median 0.92 Conclusions: This study innovatively demonstrates through CT-AI quantitative analysis that sex significantly influences FFRCT in LAD-MB patients. Females with isolated MB exhibit more pronounced distal hemodynamic alterations, whereas sex differences diminish when atherosclerosis coexists. Notably, MB length is an independent risk factor for FFRCT abnormalities, with a greater impact observed in females. These findings provide preliminary evidence to inform risk stratification of MB.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.