A normative database of free-breathing thoracic 4D dynamic MRI images and associated regional respiratory parameters of healthy children

被引:0
|
作者
Tong, Yubing [1 ]
Udupa, Jayaram K. [1 ]
McDonough, Joseph M. [2 ]
Wu, Caiyun [1 ]
Akhtar, Yusuf [1 ]
Xie, Lipeng [1 ]
Alnoury, Mostafa [1 ]
Hosseini, Mahdie [1 ]
Tong, Leihui [1 ]
Gogel, Samantha [2 ]
Biko, David M. [2 ]
Mayer, Oscar H. [3 ]
Anari, Jason B. [2 ]
Torigian, Drew A. [1 ]
Cahill, Patrick J. [2 ]
机构
[1] Univ Penn, Dept Radiol, Med Image Proc Grp, Philadelphia, PA 19104 USA
[2] Childrens Hosp Philadelphia, Wyss Campbell Ctr Thorac Insufficiency Syndrome, Philadelphia, PA 19104 USA
[3] Childrens Hosp Philadelphia, Div Pulmonol, Philadelphia, PA 19104 USA
关键词
Healthy children; normative database; respiratory anomalies; thoracic insufficiency syndrome (TIS); dynamic magnetic resonance imaging (dMRI); deep learning; INSUFFICIENCY SYNDROME;
D O I
10.1117/12.3006807
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. The purpose of this study is to introduce a large open-source normative database from our ongoing virtual growing child (VGC) project, which includes measurements of volumes, architecture, and regional dynamics in healthy children (6-20 years) derived via dynamic magnetic resonance imaging (dMRI) images. The database provides four categories of regional respiratory measurement parameters including morphological, architectural, dynamic, and developmental. The database has 3,820 3D segmentations (around 100,000 2D slices with segmentations), which to our knowledge is the largest dMRI dataset of healthy children. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters for healthy children. The database can serve as a reference standard to quantify regional respiratory abnormalities on dMRI in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can be useful to advance future AI-based research on MRI-based object segmentation and analysis.
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页数:6
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