1 Department of Orthopaedics and Trauma Surgery, Musculoskeletal University Center Munich (MUM), Ludwig Maximilian University (LMU) University Hospital, LMU Munich, 81377 Munich, Germany.
2 Department of Orthopaedics and Trauma Surgery, Musculoskeletal University Center Munich (MUM), Ludwig Maximilian University (LMU) University Hospital, LMU Munich, 81377 Munich, Germany.. Electronic address: giles.cheers@med.uni-muenchen.de.
3 Department of Radiology, LMU University Hospital, LMU Munich, 81377 Munich, Germany.
4 Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada.
5 Department of Orthopaedics and Trauma Surgery, Musculoskeletal University Center Munich (MUM), Ludwig Maximilian University (LMU) University Hospital, LMU Munich, 81377 Munich, Germany.. Electronic address: susanne.mayer@med.uni-muenchen.de.

Cavitary bone defects, defined as a volumetric loss of native bone tissue, require accurate preoperative imaging for treatment planning. While CT (computed tomography) has traditionally been the gold standard for segmentation due to its superior resolution of cortical bone, MRI (magnetic resonance imaging) offers unique advantages, particularly in visualizing the soft tissue-bone interface. Furthermore, MRI eliminates the ionizing radiation associated with CT, making it an advantageous alternative, especially in the management of benign and low-grade malignant bone tumors. Despite these advantages, MRI's inherently lower spatial resolution may introduce artifacts, which can complicate segmentation accuracy. This study evaluates the feasibility of MRI as a viable alternative to CT in the preoperative planning of cavitary bone defect treatment. We analyzed CT and MRI scans from 80 patients with benign and locally aggressive primary bone tumors, generating three-dimensional models through manual segmentation in Mimics, validated using Geomagic Control X. Volumetric differences between the CT- and MRI-derived models were assessed using the Wilcoxon signed-rank test and paired t-test. The mean volumetric difference between MRI and CT scans was 2.68 ± 1.44 %, which was not statistically significant (p = 0.15). Additionally, multiple regression analysis examining sex, age, and diagnosis revealed no significant differences in the 3D model volumes derived from the two imaging modalities (sex: p = 0.51, age: p = 0.98, diagnosis: p = 0.50). These results support MRI-based segmentation as a reliable, radiation-free alternative to CT, particularly when precise delineation of soft tissue boundaries is critical for surgical planning.