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 shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dynamic magnetic resonance imaging (dMRI) images during one breathing cycle for each normal child and also 10 object segmentations at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right separately, are also reported. The database has 2,820 3D segmentations from 141 healthy children, which to our knowledge is the largest dMRI dataset of healthy children to date. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for healthy children. The database can serve as a reference standard to quantify regional respiratory abnormalities 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 image-based object segmentation and analysis.

The normative database is from our ongoing NIH funded virtual growing child (VGC) project. All dMRI scans are acquired from healthy children during free-breathing. The dMRI protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm³, 320×320 matrix, bandwidth 258 Hz, and flip angle 76^o. With recent advances, for each sagittal location across the thorax and abdomen, we acquire 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular subject.

The collected dMRI goes through the procedure of 4D image construction, image processing, object segmentation, and then volumetric measurements from segmentations.

(1) 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach [1] to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects roughly 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method.

(2) Image processing: Intensity standardization [2] is performed on every time point/3D volume of the 4D image.

(3) Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All of the healthy children in this study have larger field of view (LFOV) images, which include the full thorax and abdomen in sagittal dMRI images. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under supervision of a radiologist (DAT) with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all data sets.

(4) Volumetric measurements based on object segmentations for lung (left and right separately) volumes at end expiration/end inspiration, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported.

[1] Hao Y, Udupa JK, Tong Y, Wu C, Li H, McDonough JM, Lott C, Qiu C, Galagedera N, Anari JB, Torigian DA, Cahill PJ. OFx: A method of 4D image construction from free-breathing non-gated MRI slice acquisitions of the thorax via optical flux. Med Image Anal. 2021;72:102088. doi: 10.1016/j.media.2021.102088. PubMed PMID: 34052519; PMCID: PMC8316349.

[2] Nyul LG, Udupa JK. On standardizing the MR image intensity scale. Magn Reson Med. 1999;42(6):1072-81. doi: 10.1002/(sici)1522-2594(199912)42:6<1072::aid-mrm11>3.0.co;2-m. PubMed PMID: 10571928.