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Prediction of the early recurrence in spinal giant cell tumor of bone using radiomics of preoperative CT: Long-term outcome of 62 consecutive patients
- Source :
- Journal of Bone Oncology, Journal of Bone Oncology, Vol 27, Iss, Pp 100354-(2021)
- Publication Year :
- 2020
-
Abstract
- Highlights • Characteristics of 62 patients with spinal GCTB who underwent surgery. • A prognostic classification model was built based on features selected by SVM. • The combined histogram and texture features could predict recurrence of GCTB.<br />Objectives To determine if radiomics analysis based on preoperative computed tomography (CT) can predict early postoperative recurrence of giant cell tumor of bone (GCTB) in the spine. Methods In a retrospective review, 62 patients with pathologically confirmed spinal GCTB from March 2008 to February 2018, with a minimum follow-up of 24 months, were identified. The mean follow-up was 73.7 months (range, 28.7–152.1 months). The clinical information including age, gender, lesion location, multi-vertebral involvement, and surgical methods, were obtained. CT images acquired before the operation were retrieved for radiomics analysis. For each case, the tumor regions of interest (ROI) was manually outlined, and a total of 107 radiomics features were extracted. The features were selected via the sequential selection process by using the support vector machine (SVM), then used to construct classification models with Gaussian kernels. The differentiation between recurrence and non-recurrence groups was evaluated by ROC analysis, using 10-fold cross-validation. Results Of the 62 patients, 17 had recurrence with a recurrence rate of 27.4%. None of the clinical information was significantly different between the two groups. Patients receiving curettage had a higher recurrence rate (6/16 = 37.5%) compared to patients receiving TES (6/26 = 23.1%) or intralesional spondylectomy (5/20 = 25%). The final radiomics model was built using 10 selected features, which achieved an accuracy of 89% with AUC of 0.78. Conclusions The radiomics model developed based on pre-operative CT can achieve a high accuracy to predict the recurrence of spinal GCTB. Patients who have a high risk of early recurrence should be treated more aggressively to minimize recurrence.
- Subjects :
- 0301 basic medicine
medicine.medical_specialty
Early Recurrence
medicine.medical_treatment
ROI, Regions of Interest
Computed tomography
SVM, Support Vector Machine
Diseases of the musculoskeletal system
MRI, Magnetic Resonance Imaging
Surgical methods
GLSZM, Gray Level Size Zone Matrix
03 medical and health sciences
0302 clinical medicine
Radiomics
GLCM, Gray Level Co-occurrence Matrix
Clinical information
medicine
NGTDM, Neighborhood Gray Tone Difference Matrix
GLRLM, Gray Level Run Length Matrix
DICOM, Digital Imaging and Communications in Medicine
GLDM, Gray Level Dependence Matrix
RC254-282
Retrospective review
medicine.diagnostic_test
business.industry
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
ROC, Receiver Operating Characteristic
CT, Computed Tomography
PACS, Picture Archiving and Communication System
medicine.disease
Prognosis
GCTB, Giant Cell Tumor of Bone
Curettage
OPG, Osteoprotegerin
Spine
Giant cell tumor of bone
030104 developmental biology
Oncology
RC925-935
030220 oncology & carcinogenesis
CT texture analysis
RANKL, Receptor Activator of Nuclear factor Kappa-Β Ligand
Radiology
RANK, Receptor Activator of Nuclear factor Kappa-Β
business
Giant-cell tumor of bone
Research Article
Subjects
Details
- ISSN :
- 22121366
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- Journal of bone oncology
- Accession number :
- edsair.doi.dedup.....f7fe4fcad64c27821b2719da81d66af2