Kidney shape statistical analysis: associations with disease and anthropometric factors

Area of Science:

• Radiology and Medical Imaging
• Nephrology
• Biomedical Engineering

Background:

• Magnetic resonance imaging (MRI) organ measurements offer potential for understanding phenotypic variations in clinical conditions.
• Kidney morphometrics can reveal subtle anatomical differences linked to disease states.

Purpose of the Study:

• To investigate kidney shape variations using advanced morphometric methods.
• To associate kidney shape with anthropometric traits and diseases like chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension.
• To assess the utility of statistical shape analysis (SSA) in predicting disease risk.

Main Methods:

• Applied morphometric methods to construct surface meshes from kidney segmentations in 38,868 UK Biobank participants' abdominal MRI data.
• Utilized mesh-based analysis with statistical parametric maps (SPMs) to identify regional kidney variations.
• Employed statistical shape analysis (SSA) with principal component analysis to analyze shape variations and assess disease event risk.

Main Results:

• Chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension were significantly associated with kidney shape.
• Age, body mass index (BMI), and waist-to-hip ratio (WHR) showed associations with kidney shape, particularly in the T2D cohort.
• Identified significant links between kidney length/width and incidence of CKD and hypertension, with specific hazard ratios reported.

Conclusions:

• Kidney shape analysis, using MRI-derived data, can significantly augment the categorization of pathologies in chronic kidney conditions.
• Shape-based morphometrics provide a valuable tool for understanding disease phenotypes and risk stratification.