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 (six to 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.
Thoracic Insufficiency Syndrome (TIS) is a rare condition that results in restricted lung growth and impaired respiratory function. Investigation of the impact of scoliotic spinal curve on regional respiratory function in individuals with TIS is important to elucidate the underlying mechanisms behind restricted respiratory function and to optimize effective treatment approaches. However, there are currently no suitable parameters for quantifying pulmonary respiratory function that demonstrate a strong correlation with scoliotic spinal curve. A new study of the relationship between scoliotic spinal curve and diaphragm motion is proposed in this work to uncover how spinal scoliosis impacts respiration, providing new insights into the specific mechanisms for respiratory dysfunction. The diaphragm was delineated at End Inspiration (EI) and End Expiration (EE) time points in reconstructed 4D images via dynamic MRI and was divided into left and right hemi-diaphragms. To facilitate the regional description of motion, we partitioned each hemi-diaphragm into 13 distinct regions and computed the velocity and curvature for each of these regions. An analysis was conducted on 26 cases with Main Thoracic Curves (MTC), including 15 cases with right-sided MTC (MTC-R) and 11 cases with left-sided MTC (MTC-L). T-testing comparing the MTC-R group with the MTC-L group revealed the impact of spinal curve sidedness on the motion of the left hemi-diaphragm. The velocity cloud maps exhibited a restriction of left diaphragmatic motion due to leftward spinal curve. Furthermore, correlation analysis demonstrated a significant influence of major curve angles (TCA and LCA) on hemi-diaphragm velocities in specific regions. Such findings improve our understanding of the pathophysiological mechanisms that lead to abnormal respiratory function in TIS.
It is important to understand the dynamic thoracoabdominal architecture and its change after surgery since thoracic insufficiency syndrome (TIS) patients often suffer from spinal deformation, leading to alterations in regional respiratory structure and function. Free-breathing based quantitative dynamic MRI (QdMRI) provides a practical solution to evaluate the regional dynamics of the thorax quantitatively for TIS patients. Our current aim is to investigate if QdMRI can also be utilized to measure architecture for TIS patients before and after surgery. 49 paired TIS patients (before and after surgery, with 98 dynamic MRI), and another 150 healthy children comprise our study cohort. 248 dynamic MRI images were first acquired and then 248 4D images were constructed. 3D volume images at end expiration (EE) and end inspiration (EI) were used in the analysis, leading to a total of 496 3D volume images in this study. Left and right lungs, left and right hemi-diaphragms, left and right kidneys, and liver were then segmented automatically via deep learning prior to architectural analysis. Architectural parameters (3D distances and angles from the centroids of multiple objects) at EE and EI of TIS patients and healthy children were computed and compared via t-testing. The distance between the right lung and right hemi-diaphragm is found to be significantly larger at EI than that at EE for TIS patients and healthy children, and after surgery becomes closer to that of healthy children.
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