Evidence map›Paper›PMID 35465442›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2021

Lung parenchymal characterization via thoracic dynamic MRI in normal children and pediatric patients with TIS.

Yubing Tong, Jayaram K Udupa, Joseph M McDonough, Carina Lott, Caiyun Wu, Chamith S Rajapakse, Jason B Anari, Drew A Torigian, Patrick J Cahill

Open access · greenAbstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. QdMRI: A system for comprehensive analysis of thoracic dynamics via dynamic MRI.Proceedings of SPIE--the International Society for Optical Engineering
    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

9 authors at 3 institutions in 1 country.

Yubing TongMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Jayaram K UdupaMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Joseph M McDonoughThe Wyss/Campbell Center for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States.
Carina LottThe Wyss/Campbell Center for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States.
Caiyun WuMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Chamith S RajapakseDepartment of Radiology and Department of Orthopedic Surgery, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Jason B AnariThe Wyss/Campbell Center for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States.
Drew A TorigianMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Patrick J CahillThe Wyss/Campbell Center for Thoracic Insufficiency Syndrome, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States.
Children's Hospital of Philadelphia · USCalifornia University of Pennsylvania · USUniversity of Pennsylvania · US

Funding

Phenotypic Diversity in COVID-19UL1TR001878 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2016 to 2025
$102.4M
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
NCATS NIH HHS UL1 TR001878NHLBI NIH HHS R01 HL150147
6 · The paper itself

Abstract

Quantitative thoracic dynamic magnetic resonance imaging (QdMRI), a recently developed technique, provides a potential solution for evaluating treatment effects in thoracic insufficiency syndrome (TIS). In this paper, we demonstrate how lung parenchymal characteristics can be assessed via intensity properties in lung dynamic MRI, a modality suitable for use in pediatric patients. The QdMRI-based approach includes dynamic MR image acquisition, 4D image construction, image pre-processing with non-uniformity correction and intensity standardization, and lung segmentation from the 4D constructed image via a deep learning approach, as well as extraction of image parenchymal intensity properties from the segmented lungs and statistical comparisons among different clinical scenarios. We include 22 dMRI scans from 11 TIS patients (each with both pre-operative and post-operative scans) and 23 dMRI scans from healthy children. Two-sided paired t-testing is performed to compare lung intensity properties between end of expiration (EE) and end of inspiration (EI) within TIS patients (pre-operative and post-operative, separately) and normal children. We also compare the lung intensity properties at EE and EI among pre-operative TIS patients, post-operative TIS patients, and normal children. Experimental results show that lung (T2) intensity at EI is significantly lower than that at EE and lung intensity of post-operative TIS patients is significantly lower than that in pre-operative TIS patients and closer to that of normal children than to that of pre-operative TIS patients, indicating improvement in lung aeration. To our knowledge, this is the first study to provide a quantitative dynamic functional method to analyze lung parenchyma during tidal breathing on dynamic MRI in both healthy children and pediatric patients with TIS.

Indexed as

4D constructiondynamic MRIlung aerationlung parenchymathoracic insufficiency syndrome (TIS)

Identifiers

PMID35465442
PMCPMC9032054
OpenAlexW3133143548

What OpenQuestion holds

Textmetadata
LicenceTDM
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.