Evidence map›Paper›PMID 36860798›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering

Regional diaphragm motion analysis via dynamic MRI.

You Hao, Jayaram K Udupa, Yubing Tong, Caiyun Wu, Joseph M McDonough, Carina Lott, Abigail Clark, Jason B Anari, Patrick J Cahill, Drew A Torigian

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A Survey on Artificial Intelligence in Pulmonary Imaging.Wiley interdisciplinary reviews. Data mining and knowledge discovery
    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

10 authors.

You HaoMedical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States.
Jayaram K UdupaMedical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States.
Yubing TongMedical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States.
Caiyun WuMedical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States.
Joseph M McDonoughCenter for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Carina LottCenter for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Abigail ClarkCenter for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Jason B AnariCenter for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Patrick J CahillCenter for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Drew A TorigianMedical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, United States.

Funding

Virtual growing child 5-dimensional functional models for treating respiratory anomaliesR01HL150147 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI TORIGIAN, DREW, UDUPA, JAYARAM K · 2020 to 2023
$3.1M
NHLBI NIH HHS R01 HL150147
6 · The paper itself

Abstract

Breathing-related movement analysis is important in the study of many disease processes. The analysis of diaphragmatic motion via thoracic imaging in particular is important in a variety of disorders. Compared to computed tomography (CT) and fluoroscopy, dynamic magnetic resonance imaging (dMRI) has several advantages, such as better soft tissue contrast, no ionizing radiation, and greater flexibility in selecting scanning planes. In this paper, we propose a novel method for full diaphragmatic motion analysis via free-breathing dMRI. Firstly, after 4D dMRI image construction in a cohort of 51 normal children, we manually delineated the diaphragm on sagittal plane dMRI images at end-inspiration and end-expiration. Then, 25 points were selected uniformly and homologously on each hemi-diaphragm surface. Based on the inferior-superior displacements of these 25 points between end-expiration (EE) and end-inspiration (EI) time points, we obtained their velocities. We then summarized 13 parameters from these velocities for each hemi-diaphragm to provide a quantitative regional analysis of diaphragmatic motion. We observed that the regional velocities of the right hemi-diaphragm were almost always statistically significantly greater than those of the left hemi-diaphragm in homologous locations. There was a significant difference for sagittal curvatures but not for coronal curvatures between the two hemi-diaphragms. Using this methodology, future larger scale prospective studies may be considered to confirm our findings in the normal state and to quantitatively assess regional diaphragmatic dysfunction when various disease conditions are present.

Indexed as

curvaturediaphragmdynamic MRImotion analysis

Identifiers

PMID36860798
PMCPMC9974200

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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.