Evidence map›Paper›PMID 42606810›Full record

ArticleAnnals of biomedical engineering2026

One-Click CT-Based Pipeline for Regional Quantification of Aortic Valve Fibrocalcific Degeneration.

Marta Liberotti, Anna Palmisano, Alberto Colombo, Davide Vignale, Federica Piccione, Marco Bruno Ancona, Matteo Montorfano, Antonio Esposito

Registry-linked trialAbstract read
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In one paragraph

Article in Annals of biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06029400 (CT-based Myocardial Characterization), which is not on this map. Not yet cited in PubMed.

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1 · What the graph read from it

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.

2 · The registry

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.

NCT06029400 recruitingnot on this map

CT-based Myocardial Characterization

TypeobservationalSponsorIRCCS San RaffaeleRan2020 to 2032Enrolled2,200ConditionsCardiovascular Diseases
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Marta LiberottiSan Raffaele AI Center (S-RACE), Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy.
Anna PalmisanoSchool of Medicine, Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy. palmisano.anna@hsr.it.ORCID http://orcid.org/0000-0002-1564-2060
Alberto ColomboSan Raffaele AI Center (S-RACE), Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy.
Davide VignaleSchool of Medicine, Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy.
Federica PiccioneSchool of Medicine, Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy.
Marco Bruno AnconaDepartment of Interventional Cardiology, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Matteo MontorfanoSchool of Medicine, Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy.
Antonio EspositoSan Raffaele AI Center (S-RACE), Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy.

Funding

European Union - Next Generation EU PRIN PNRR 2022 (P2022JBKN2)
6 · The paper itself

Abstract

purposeAortic Stenosis (AS) involves progressive fibrocalcific degeneration of the aortic valve. Current imaging methods for valve tissue quantification remain semi-automated and lack detailed spatial tissue characterization. We present a CT-based pipeline that fully automates the quantification of fibrotic and calcific components and enables semi-automated regional tissue analysis.

methodsWe developed a standardized pipeline that performs automatic multiplanar reconstruction of pre-TAVI cardiac CT scans, automatic fibrocalcific volume quantification, and semi-automated regional volume assessment requiring only a single user input. We evaluated the accuracy of the pipeline by comparing each module with manual analyses performed independently by two radiologists with different levels of expertise. Agreement between automated and manual results was assessed using Bland-Altman analysis and standard similarity metrics.

resultsWe analyzed 25 patients with severe AS (13 females/12 males; median age 82 years, IQR 78-86). The pipeline processed for each patient in ≤ 2.5 min. Multiplanar reconstruction showed an angular error of 5.38° (IQR 3.29-8.33) between the expert user and the pipeline. Bland-Altman analysis revealed minimal bias for fibrocalcific volume and density, comparable to inter-user variability. Expert-pipeline Dice coefficients for regional divisions were high (0.86-0.89), and entropy of fibrocalcific ratio demonstrated substantial tissue heterogeneity among patients.

conclusionThe proposed pipeline enables accurate assessment of aortic valve disease severity by integrating fibrotic and calcific quantification with spatial distribution, offering potential to inform TAVI planning and clinical decision-making with minimal user input and analysis time.

trial registrationNCT06029400, registered on 1 September 2023.

Indexed as

Aortic valve stenosisComputed tomographyFibrocalcific volumeImage processingRegional tissue characterizationTranscatheter aortic valve implantation

Identifiers

PMID42606810

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