SPECT/CT Radiomics for Differentiating between Enchondroma and Grade I Chondrosarcoma

Tomography. 2023 Oct 16;9(5):1868-1875. doi: 10.3390/tomography9050148.

Abstract

This study was performed to assess the value of SPECT/CT radiomics parameters in differentiating enchondroma and atypical cartilaginous tumors (ACTs) located in the long bones. Quantitative HDP SPECT/CT data of 49 patients with enchondromas or ACTs in the long bones were retrospectively reviewed. Patients were randomly split into training (n = 32) and test (n = 17) data, and SPECT/CT radiomics parameters were extracted. In training data, LASSO was employed for feature reduction. Selected parameters were compared with classic quantitative parameters for the prediction of diagnosis. Significant parameters from training data were again tested in the test data. A total of 12 (37.5%) and 6 (35.2%) patients were diagnosed as ACTs in training and test data, respectively. LASSO regression selected two radiomics features, zone-length non-uniformity for zone (ZLNUGLZLM) and coarseness for neighborhood grey-level difference (CoarsenessNGLDM). Multivariate analysis revealed higher ZLNUGLZLM as the only significant independent factor for the prediction of ACTs, with sensitivity and specificity of 85.0% and 58.3%, respectively, with a cut-off value of 191.26. In test data, higher ZLNUGLZLM was again associated with the diagnosis of ACTs, with sensitivity and specificity of 83.3% and 90.9%, respectively. HDP SPECT/CT radiomics may provide added value for differentiating between enchondromas and ACTs.

Keywords: HDP bone SPECT/CT; chondrosarcoma; enchondromas; radiomics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bone Neoplasms* / diagnostic imaging
  • Bone Neoplasms* / pathology
  • Chondroma* / diagnostic imaging
  • Chondroma* / pathology
  • Chondrosarcoma* / diagnostic imaging
  • Chondrosarcoma* / pathology
  • Diagnosis, Differential
  • Humans
  • Retrospective Studies
  • Tomography, Emission-Computed, Single-Photon
  • Tomography, X-Ray Computed

Grants and funding

This research was supported by a grant from Institute of Information & communications Technology Planning & Evaluation (2021-0-00986).