Evidence map›Paper›PMID 33247903›Full record

ArticleEuropean heart journal. Cardiovascular Imaging2021

Non-calcific aortic tissue quantified from computed tomography angiography improves diagnosis and prognostication of patients referred for transcatheter aortic valve implantation.

Kajetan Grodecki, Balaji K Tamarappoo, Zenon Huczek, Szymon Jedrzejczyk, Sebastien Cadet, Jacek Kwiecinski, Bartosz Rymuza, Radoslaw Parma, Anna Olasinska-Wisniewska, Jadwiga Fijalkowska and 11 more

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in European heart journal. Cardiovascular Imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06136689 (Role of Aortic Valve Composition in Pathophysiology and Diagnosis of Aortic Stenosis), which is not on this map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.4field-weighted citation impact, top 9% of its field
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.

NCT06136689 unknown statusnot on this mapstarted 2022, after this paper: background citation

Role of Aortic Valve Composition in Pathophysiology and Diagnosis of Aortic Stenosis

TypeobservationalSponsorMedical University of WarsawRan2022 to 2025Enrolled55ConditionsAortic Stenosis, Aortic Valve Disease, Aortic Valve Calcification
3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Thrombus characterisation and evolution of hypoattenuating leaflet thickening after transcatheter aortic valve implantation.EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology · 2025
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Advanced Cardiac Imaging in the Assessment of Aortic Stenosis.Journal of cardiovascular development and disease · 2023
    Review
  12. Article
  13. Latest Advances in Multimodality Imaging of Aortic Stenosis.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
    Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors at 8 institutions in 2 countries.

Kajetan GrodeckiDepartments of Biomedical Sciences and Medicine, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute,116N Robertson Blvd, Suite 400, Los Angeles, CA 90048, USA.
Balaji K TamarappooSmidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Zenon Huczek1st Department of Cardiology, Medical University of Warsaw, Banacha 1A, 02-097 Warsaw, Poland.
Szymon Jedrzejczyk1st Department of Cardiology, Medical University of Warsaw, Banacha 1A, 02-097 Warsaw, Poland.
Sebastien CadetDepartments of Biomedical Sciences and Medicine, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute,116N Robertson Blvd, Suite 400, Los Angeles, CA 90048, USA.
Jacek KwiecinskiDepartment of Interventional Cardiology and Angiology, Institute of Cardiology, Alpejska 42 04-628 Warsaw, Poland.
Bartosz Rymuza1st Department of Cardiology, Medical University of Warsaw, Banacha 1A, 02-097 Warsaw, Poland.
Radoslaw ParmaDivision of Cardiology and Structural Heart Diseases, Medical University of Silesia, Ziołowa 45/47, 40-635 Katowice, Poland.
Anna Olasinska-WisniewskaDepartment of Cardiac Surgery and Transplantology, Poznan University of Medical Sciences, Długa 1/2, 61-848 Poznan, Poland.
Jadwiga Fijalkowska2nd Department of Radiology, Medical University of Gdansk, Mariana Smoluchowskiego 17, 80-214 - Gdansk, Poland.
Marcin ProtasiewiczDepartment of Cardiology, Wroclaw Medical University, Borowska 213, 50-556 Wroclaw, Poland.
Andrzej WalczakDepartment of Cardiac Surgery, Medical University of Lodz, Pomorska 251, 92-213 Lodz, Poland.
Adrianna NowakDivision of Cardiology and Structural Heart Diseases, Medical University of Silesia, Ziołowa 45/47, 40-635 Katowice, Poland.
Radoslaw GocolDepartment of Cardiac Surgery, Medical University of Silesia, Ziołowa 45/47, 40-635 Katowice, Poland.
Piotr J SlomkaDepartments of Biomedical Sciences and Medicine, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute,116N Robertson Blvd, Suite 400, Los Angeles, CA 90048, USA.
Krzysztof ReczuchDepartment of Cardiology, Wroclaw Medical University, Borowska 213, 50-556 Wroclaw, Poland.
Dariusz JagielakDepartment of Cardiac Surgery, Medical University of Gdansk, Mariana Smoluchowskiego 17, 80-214 - Gdansk, Poland.
Marek GrygierDepartment of Cardiology, Poznan University of Medical Sciences, Długa 1/2, 61-848 Poznan, Poland.
Wojciech WojakowskiDivision of Cardiology and Structural Heart Diseases, Medical University of Silesia, Ziołowa 45/47, 40-635 Katowice, Poland.
Krzysztof J Filipiak1st Department of Cardiology, Medical University of Warsaw, Banacha 1A, 02-097 Warsaw, Poland.
Damini DeyDepartments of Biomedical Sciences and Medicine, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute,116N Robertson Blvd, Suite 400, Los Angeles, CA 90048, USA.ORCID 0000-0003-2236-6970
Cedars-Sinai Medical Center · USMedical University of Silesia · PLMedical University of Warsaw · PLGdańsk Medical University · PLPoznan University of Medical Sciences · PLWroclaw Medical University · PLInstitute of Cardiology · PLMedical University of Lodz · PL

Funding

Integrated prediction of cardiovascular events by automated coronary plaque and pericoronary adipose tissue quantification from CT AngiographyR01HL148787 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI DEY, DAMINI · 2020 to 2023
$3.0M
Automated quantitative CT imaging of epicardial adipose tissue and risk of cardiac eventsR01HL133616 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI DEY, DAMINI · 2016 to 2019
$2.6M
NHLBI NIH HHS R01 HL133616NHLBI NIH HHS R01 HL148787
6 · The paper itself

Abstract

aimsWe aimed to investigate the role of aortic valve tissue composition from quantitative cardiac computed tomography angiography (CTA) in patients with severe aortic stenosis (AS) for the differentiation of disease subtypes and prognostication after transcatheter aortic valve implantation (TAVI). METHODS AND

resultsOur study included 447 consecutive AS patients from six high-volume centres reporting to a prospective nationwide registry of TAVI procedures (POL-TAVI), who underwent cardiac CTA before TAVI, and 224 matched controls with normal aortic valves. Components of aortic valve tissue were identified using semi-automated software as calcific and non-calcific. Volumes of each tissue component and composition [(tissue component volume/total tissue volume) × 100%] were quantified. Relationship of aortic valve composition with clinical outcomes post-TAVI was evaluated using Valve Academic Research Consortium (VARC)-2 definitions.High-gradient (HG) AS patients had significantly higher aortic tissue volume compared to low-flow low-gradient (LFLG)-AS (1672.7 vs. 1395.3 mm3, P < 0.001) as well as controls (509.9 mm3, P < 0.001), but increased non-calcific tissue was observed in LFLG compared to HG patients (1063.6 vs. 860.2 mm3, P < 0.001). Predictive value of aortic valve calcium score [area under the curve (AUC) 0.989, 95% confidence interval (CI): 0.981-0.996] for severe AS was improved after addition of non-calcific tissue volume (AUC 0.995, 95% CI: 0.991-0.999, P = 0.011). In the multivariable analysis of clinical and quantitative computed tomography parameters of aortic valve tissue, non-calcific tissue volume [odds ratio (OR) 5.2, 95% CI 1.8-15.4, P = 0.003] and history of stroke (OR 2.6, 95% CI 1.1-6.5, P = 0.037) were independent predictors of 30-day major adverse cardiovascular event (MACE).

conclusionQuantitative CTA assessment of aortic valve tissue volume and composition can improve detection of severe AS, differentiation between HG and LFLG-AS in patients referred for TAVI as well as prediction of 30-day MACEs post-TAVI, over the current clinical standard.

Indexed as

Aortic Valve StenosisTranscatheter Aortic Valve ReplacementAortic ValveComputed Tomography AngiographyHumansProspective StudiesRisk FactorsSeverity of Illness IndexTreatment Outcomeaortic stenosiscomputed tomography angiographytranscatheter aortic valve implantation

Identifiers

PMID33247903
PMCPMC8453378
OpenAlexW3109459175

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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.