Evidence map›Paper›PMID 30552522›Full record

ArticleThe international journal of cardiovascular imaging2019

A novel software tool for semi-automatic quantification of thoracic aorta dilatation on baseline and follow-up computed tomography angiography.

Xinpei Gao, Sara Boccalini, Pieter H Kitslaar, Ricardo P J Budde, Shengxian Tu, Boudewijn P F Lelieveldt, Jouke Dijkstra, Johan H C Reiber

Open access · hybridAbstract readComparative StudyEvaluation Study
In one paragraph

Article in The international journal of cardiovascular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 12% 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.

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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Three-dimensional aortic geometry mapping via registration of non-gated contrast-enhanced or gated and respiratory-navigated MR angiographies.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2024
    Observational
  6. Article
  7. Article
  8. Article
  9. Article
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  13. Cardiovascular imaging 2019 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2020
    Article
  14. Article
  15. Cardiovascular imaging 2018 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2019
    Article
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 at 2 institutions in 2 countries.

Xinpei GaoDivision of Image Processing, Department of Radiology, LUMC, Leiden, The Netherlands.
Sara BoccaliniDepartment of Radiology, University Medical Center, Rotterdam, The Netherlands.
Pieter H KitslaarLKEB, LUMC, Leiden, The Netherlands.
Ricardo P J BuddeDepartment of Radiology, University Medical Center, Rotterdam, The Netherlands.
Shengxian TuShanghai Jiao Tong University, Shanghai, China.
Boudewijn P F LelieveldtLKEB, LUMC, Leiden, The Netherlands.
Jouke DijkstraLKEB, LUMC, Leiden, The Netherlands.
Johan H C ReiberLKEB, LUMC, Leiden, The Netherlands. J.H.C.reiber@lumc.nl.
Leiden University Medical Center · NLShanghai Jiao Tong University · CN

Funding

China Scholarship Council 201206090162Shanghai Pujiang Program 15PJ1404200
6 · The paper itself

Abstract

A dedicated software package that could semi-automatically assess differences in aortic maximal cross-sectional diameters from consecutive CT scans would most likely reduce the post-processing time and effort by the physicians. The aim of this study was to present and assess the quality of a new tool for the semi-automatic quantification of thoracic aorta dilation dimensions. Twenty-nine patients with two CTA scans of the thoracic aorta for which the official clinical report indicated an increase in aortic diameters were included in the study. Aortic maximal cross-sectional diameters of baseline and follow-up studies generated semi-automatically by the software were compared with corresponding manual measurements. The semi-automatic measurements were performed at seven landmarks defined on the baseline scan by two operators. Bias, Bland-Altman plots and intraclass correlation coefficients were calculated between the two methods and, for the semi-automatic software, also between two observers. The average time difference between the two scans of a single patient was 1188 ± 622 days. For the semi-automatic software, in 2 out of 29 patients, manual interaction was necessary; in the remaining 27 patients (93.1%), semi-automatic results were generated, demonstrating excellent intraclass correlation coefficients (all values ≥ 0.91) and small differences, especially for the proximal aortic arch (baseline: 0.19 ± 1.30 mm; follow-up: 0.44 ± 2.21 mm), the mid descending aorta (0.37 ± 1.64 mm; 0.37 ± 2.06 mm), and the diaphragm (0.30 ± 1.14 mm; 0.37 ± 1.80 mm). The inter-observer variability was low with all errors in diameters ≤ 1 mm, and intraclass correlation coefficients all ≥ 0.95. The semi-automatic tool decreased the processing time by 40% (13 vs. 22 min). In this work, a semi-automatic software package that allows the assessment of thoracic aorta diameters from baseline and follow-up CTs (and their differences), was presented, and demonstrated high accuracy and low inter-observer variability.

Indexed as

SoftwareAdultAgedAged, 80 and overAnatomic LandmarksAorta, ThoracicAortic Aneurysm, ThoracicAortographyAutomationComputed Tomography AngiographyDilatation, PathologicDisease ProgressionFemaleHumansMaleMiddle AgedAortaComputed tomography angiographyDimensional measurement accuracyFollow-up studiesSegmentationSemi-automatic data processingSoftware assessmentThoracic

Identifiers

PMID30552522
PMCPMC6482131
OpenAlexW2904158636

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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.