Abstract #2958

Automated Pipeline for Shoulder Cartilage Segmentation and Extraction of T2 and Texture Features

Vladimir Juras¹, Markus Schreiner², Veronika Janacova¹, Pavol Szomolanyi^1,3, Esther Raithel⁴, Rahel Heule⁵, Oliver Bieri⁶, and Siegfried Trattnig^1,7,8

¹Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ²Department of Orthopedics and Trauma Surgery, Medical University of Vienna, Vienna, Austria, ³Department of Imaging Methods, Institute of Measurement Science, Bratislava, Slovakia, ⁴Siemens Healthcare AG, Forchheim, Germany, ⁵Center for MR Research, University Children's Hospital, Zurich, Switzerland, ⁶Division of Radiological Physics, University of Basel Hospital, Basel, Switzerland, ⁷Austrian Cluster for Tissue Regeneration, Ludwig Boltzmann Institute for Experimental and Clinical Traumatology,, Vienna, Austria, ⁸Institute for Clinical Molecular MRI in the Musculoskeletal System, Karl Landsteiner Society, Vienna, Austria

Synopsis

Keywords: Cartilage, Cartilage, segmentation

Motivation: Automated evaluation of the quantitative MRI T2 maps in the shoulder joint cartilage can improve the efficiency, reproducibility and accuracy of the clinical studies.

Goal(s): To design and validate automated shoulder cartilage pipeline, including fully automated cartilage segmentation as well as three T2 modalities, co-registered with the morphological 3D MRI.

Approach: Automated shoulder cartilage segmentation provided sixteen cartilage regions, on which the three T2 modalities have been registered. Additionally, texture analysis has been performed on all three T2 maps.

Results: While the absolute T2 values were statistically significantly different between three methods, the texture features were not.

Impact: This automated pipeline for shoulder cartilage segmentation and extraction of T2 and texture features offers a reliable, efficient approach to assess cartilage health. The integration of T2 mapping techniques are paving the way for quantitative cartilage evaluation in musculoskeletal imaging.

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