Lawrence M White1,2,3, Angela Atinga4,5, Ali M Naraghi4,6,7, Katherine Lajkosz8, Jay S Wunder7,9, Peter Ferguson7,9, Kim Tsoi7,9, Anthony Griffin9, Masoom Haider4,6. 1. Department of Medical Imaging, University of Toronto, Toronto, ON, Canada. Lawrence.white@uhn.ca. 2. Joint Department of Medical Imaging, Mount Sinai Hospital, University Health Network and Women's College Hospital, Rm 562-A, 600 University Ave, Toronto, ON, M5G 1X5, Canada. Lawrence.white@uhn.ca. 3. Toronto Sarcoma Program, Mount Sinai Hospital, Toronto, ON, Canada. Lawrence.white@uhn.ca. 4. Department of Medical Imaging, University of Toronto, Toronto, ON, Canada. 5. Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada. 6. Joint Department of Medical Imaging, Mount Sinai Hospital, University Health Network and Women's College Hospital, Rm 562-A, 600 University Ave, Toronto, ON, M5G 1X5, Canada. 7. Toronto Sarcoma Program, Mount Sinai Hospital, Toronto, ON, Canada. 8. Department of Biostatistics, University Health Network, Princess Margaret Cancer Centre, Toronto, ON, Canada. 9. Department of Surgery, Division of Orthopedic Surgery, Musculoskeletal Oncology, Mount Sinai Hospital, Toronto, ON, Canada.
Abstract
OBJECTIVE: To analyze radiomic features obtained from pre-treatment T2-weighted MRI acquisitions in patients with histologically proven intramedullary high-grade osteosarcomas and assess the accuracy of radiomic modelling as predictive biomarker of tumor necrosis following neoadjuvant chemotherapy (NAC), overall survival (OS), and disease-free survival (DFS). MATERIALS AND METHODS: Pre-treatment MRI exams in 105 consecutive patients who underwent NAC and resection of high-grade intramedullary osteosarcoma were evaluated. Histologic necrosis following NAC, and clinical outcome-survival data was collected for each case. Radiomic features were extracted from segmentations performed by two readers, with poorly reproducible features excluded from further analysis. Cox proportional hazard model and Spearman correlation with multivariable modelling were used for assessing relationships of radiomics features with OS, DFS, and histologic tumor necrosis. RESULTS: Study included 74 males, 31 females (mean 32.5yrs, range 15-77 years). Histologic assessment of tumor necrosis following NAC was available in 104 cases, with good response (≥ 90% necrosis) in 41, and poor response in 63. Fifty-three of 105 patients were alive at follow-up (median 40 months, range: 2-213 months). Median OS was 89 months. Excluding 14 patients with metastases at presentation, median DFS was 19 months. Eleven radiomics features were employed in final radiomics model predicting histologic tumor necrosis (mean AUC 0.708 ± 0.046). Thirteen radiomic features were used in model predicting OS (mean concordance index 0.741 ± 0.011), and 12 features retained in predicting DFS (mean concordance index 0.745 ± 0.010). CONCLUSIONS: T2-weighted MRI radiomic models demonstrate promising results as potential prognostic biomarkers of prospective tumor response to neoadjuvant chemotherapy and prediction of clinical outcomes in conventional osteosarcoma.
OBJECTIVE: To analyze radiomic features obtained from pre-treatment T2-weighted MRI acquisitions in patients with histologically proven intramedullary high-grade osteosarcomas and assess the accuracy of radiomic modelling as predictive biomarker of tumor necrosis following neoadjuvant chemotherapy (NAC), overall survival (OS), and disease-free survival (DFS). MATERIALS AND METHODS: Pre-treatment MRI exams in 105 consecutive patients who underwent NAC and resection of high-grade intramedullary osteosarcoma were evaluated. Histologic necrosis following NAC, and clinical outcome-survival data was collected for each case. Radiomic features were extracted from segmentations performed by two readers, with poorly reproducible features excluded from further analysis. Cox proportional hazard model and Spearman correlation with multivariable modelling were used for assessing relationships of radiomics features with OS, DFS, and histologic tumor necrosis. RESULTS: Study included 74 males, 31 females (mean 32.5yrs, range 15-77 years). Histologic assessment of tumor necrosis following NAC was available in 104 cases, with good response (≥ 90% necrosis) in 41, and poor response in 63. Fifty-three of 105 patients were alive at follow-up (median 40 months, range: 2-213 months). Median OS was 89 months. Excluding 14 patients with metastases at presentation, median DFS was 19 months. Eleven radiomics features were employed in final radiomics model predicting histologic tumor necrosis (mean AUC 0.708 ± 0.046). Thirteen radiomic features were used in model predicting OS (mean concordance index 0.741 ± 0.011), and 12 features retained in predicting DFS (mean concordance index 0.745 ± 0.010). CONCLUSIONS: T2-weighted MRI radiomic models demonstrate promising results as potential prognostic biomarkers of prospective tumor response to neoadjuvant chemotherapy and prediction of clinical outcomes in conventional osteosarcoma.
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