Evidence map›Paper›PMID 25893746›Full record

ArticleThe international journal of cardiovascular imaging2015

CT evaluation prior to transapical aortic valve replacement: semi-automatic versus manual image segmentation.

Borek Foldyna, Camelia Jungert, Christian Luecke, Konstantin von Aspern, Sonja Boehmer-Lasthaus, Eva Maria Rueth, Matthias Grothoff, Stefan Nitzsche, Matthias Gutberlet, Friedrich Wilhelm Mohr and 1 more

Abstract readComparative Study
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In one paragraph

Article in The international journal of cardiovascular imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Fully automated measurement of aortic root anatomy using Philips HeartNavigator computed tomography software: fast, accurate, or both?European heart journal supplements : journal of the European Society of Cardiology · 2022
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Cardiovascular imaging 2015 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2016
    Review
  9. Review
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

11 authors.

Borek FoldynaDepartment of Interventional and Diagnostic Radiology, University of Leipzig - Heart Center, Struempellstrasse 39, 04289, Leipzig, Germany, b.foldyna@gmail.com.
Camelia Jungert
Christian Luecke
Konstantin von Aspern
Sonja Boehmer-Lasthaus
Eva Maria Rueth
Matthias Grothoff
Stefan Nitzsche
Matthias Gutberlet
Friedrich Wilhelm Mohr
Lukas Lehmkuhl

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To compare the performance of semi-automatic versus manual segmentation for ECG-triggered cardiovascular computed tomography (CT) examinations prior to transcatheter aortic valve replacement (TAVR), with focus on the speed and precision of experienced versus inexperienced observers. The preoperative ECG-triggered CT data of 30 consecutive patients who were scheduled for TAVR were included. All datasets were separately evaluated by two radiologists with 1 and 5 years of experience (novice and expert, respectively) in cardiovascular CT using an evaluation software program with or without a semi-automatic TAVR workflow. The time expended for data loading and all segmentation steps required for the implantation planning were assessed. Inter-software as well as inter-observer reliability analysis was performed. The CT datasets were successfully evaluated, with mean duration between 520.4 ± 117.6 s and 693.2 ± 159.5 s. The three most time-consuming steps were the 3D volume rendering, the measurement of aorta diameter and the sizing of the aortic annulus. Using semi-automatic segmentation, a novice could evaluate CT data approximately 12.3% faster than with manual segmentation, and an expert could evaluate CT data approximately 10.3% faster [mean differences of 85.4 ± 83.8 s (p < 0.001) and 59.8 ± 101 s (p < 0.001), respectively]. The inter-software reliability for a novice was slightly lower than for an expert; however, the reliability for a novice and expert was excellent (ICC 0.92, 95% CI 0.75-0.97/ICC 0.96, 95% CI 0.91-0.98). Automatic aortic annulus detection failed in two patients (6.7%). The study revealed excellent inter-software and inter-observer reliability, with a mean ICC of 0.95. TAVR evaluation can be accomplished significantly faster with semi-automatic rather than with manual segmentation, with comparable exactness, showing a benefit for experienced and inexperienced observers.

Indexed as

AgedAged, 80 and overAortic ValveAortic Valve StenosisAutomationCardiac CatheterizationClinical CompetenceElectrocardiographyFemaleGermanyHeart Valve ProsthesisHeart Valve Prosthesis ImplantationHumansMaleMultidetector Computed TomographyObserver Variation

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Registered trials

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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.