Evidence map›Paper›PMID 27626802›Full record

ArticlePloS one2016

Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension.

Fabian Rengier, Stefan Wörz, Claudius Melzig, Sebastian Ley, Christian Fink, Nicola Benjamin, Sasan Partovi, Hendrik von Tengg-Kobligk, Karl Rohr, Hans-Ulrich Kauczor and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. 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 at 7 institutions in 3 countries.

Fabian RengierDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
Stefan WörzDepartment of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Claudius MelzigDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
Sebastian LeyRadiology Isar Klinikum, Sonnenstrasse 22-24, 80331 Munich, Germany.
Christian FinkInstitute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany.
Nicola BenjaminTranslational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
Sasan PartoviDepartment of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, 11100 Euclid Ave, Cleveland, Ohio, United States of America.
Hendrik von Tengg-KobligkDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
Karl RohrDepartment of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Hans-Ulrich KauczorDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
Ekkehard GrünigTranslational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
German Center for Lung Research · DEHeidelberg University · DEUniversity Hospital Heidelberg · DEGerman Cancer Research Center · DELudwig-Maximilians-Universität München · DEUniversity Hospitals Cleveland Medical Center · USUniversity Medical Centre Mannheim · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo demonstrate feasibility of automated 3D volumetry of central pulmonary arteries based on magnetic resonance angiography (MRA), to assess pulmonary artery volumes in patients with pulmonary hypertension compared to healthy controls, and to investigate the potential of the technique for predicting pulmonary hypertension.

methodsMRA of pulmonary arteries was acquired at 1.5T in 20 patients with pulmonary arterial hypertension and 21 healthy normotensive controls. 3D model-based image analysis software was used for automated segmentation of main, right and left pulmonary arteries (MPA, RPA and LPA). Volumes indexed to vessel length and mean, minimum and maximum diameters along the entire vessel course were assessed and corrected for body surface area (BSA). For comparison, diameters were also manually measured on axial reconstructions and double oblique multiplanar reformations. Analyses were performed by two cardiovascular radiologists, and by one radiologist again after 6 months.

resultsMean volumes of MPA, RPA and LPA for patients/controls were 5508 ± 1236/3438 ± 749, 3522 ± 934/1664 ± 468 and 3093 ± 692/1812 ± 474 μl/(cm length x m2 BSA) (all p<0.001). Mean, minimum and maximum diameters along the entire vessel course were also significantly increased in patients compared to controls (all p<0.001). Intra- and interobserver agreement were excellent for both volume and diameter measurements using 3D segmentation (intraclass correlation coefficients 0.971-0.999, p<0.001). Area under the curve for predicting pulmonary hypertension using volume was 0.998 (95% confidence interval 0.990-1.0, p<0.001), compared to 0.967 using manually measured MPA diameter (95% confidence interval 0.910-1.0, p<0.001).

conclusionsAutomated MRA-based 3D volumetry of central pulmonary arteries is feasible and demonstrated significantly increased volumes and diameters in patients with pulmonary arterial hypertension compared to healthy controls. Pulmonary artery volume may serve as a superior predictor for pulmonary hypertension compared to manual measurements on axial images but verification in a larger study population is warranted.

Indexed as

AdultFemaleHumansHypertension, PulmonaryImaging, Three-DimensionalMagnetic Resonance AngiographyMaleMiddle AgedPulmonary ArteryYoung Adult

Identifiers

PMID27626802
PMCPMC5023190
OpenAlexW2520154276

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.