Automated segmentation and quantification of geometrical and structural parameters of the hip in 3D-MRI data sets: Development of algorithms for reliable data analysis in large cohorts (German National Cohort)

• Applicants: Professor Dr. Mike Notohamiprodjo; Professor Dr. Fritz Schick; Professor Dr.-Ing. Bin Yang
• Subject Area: Nuclear Medicine, Radiotherapy, Radiobiology
• Term: from 2017 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 325028047

Standardized and validated tools with a high degree of automatization are required for the assessment of the MRI-data of the approximately 30,000 participants of the German National Cohort (GNC) imaging sub-study. The purpose of this project is to develop and test software algorithms for automated segmentation of the hip joint exploiting the pelvis sequences of 200 exemplary MRI datasets provided by the GNC. The software algorithms will automatically quantify the following imaging parameters: Acetabular coverage, sphericity of the femoral head, offset femoral head/neck, proximal femoral form, cartilage area and thickness, acetabular and femoral cysts. These automatically derived parameters will be compared to manual analysis and validated in a separate clinically correlated patient cohort. Finally, the developed software tools will allow for automated quantitative assessment of structural changes which may predispose individuals to develop hip osteoarthritis.

• DFG Programme: Research Grants