J Pérez-Beteta1, D Molina-García2, M Villena3, M J Rodríguez4, C Velásquez5, J Martino5, B Meléndez-Asensio6, Á Rodríguez de Lope7, R Morcillo8, J M Sepúlveda9, A Hernández-Laín10, A Ramos11, J A Barcia12, P C Lara13, D Albillo14, A Revert15, E Arana16, V M Pérez-García1. 1. From the Department of Mathematics (J.P.-B., D.M.-G., V.M.P.-G.), Mathematical Oncology Laboratory, Universidad de Castilla-La Mancha, Ciudad Real, Spain. 2. From the Department of Mathematics (J.P.-B., D.M.-G., V.M.P.-G.), Mathematical Oncology Laboratory, Universidad de Castilla-La Mancha, Ciudad Real, Spain david.molina@uclm.es. 3. Departments of Neurosurgery (M.V.). 4. Radiology (M.J.R.), Hospital General de Ciudad Real, Ciudad Real, Spain. 5. Department of Neurosurgery (J.M., C.V.), Hospital Universitario Marqués de Valdecilla and Fundación, Instituto de Investigación Marqués de Valdecilla, Santander, Spain. 6. Departments of Molecular Biology (B.M.-A.). 7. Neurosurgery (Á.R.d.L.). 8. Radiology (R.M.), Hospital Virgen de la Salud, Toledo, Spain. 9. Departments of Neuro-Oncology (J.M.S.). 10. Pathology (A.H.-L.). 11. Radiology (A. Ramos), Hospital Universitario 12 de Octubre, Madrid, Spain. 12. Department of Neurosurgery (J.A.B.), Hospital Clínico San Carlos, Madrid, Spain. 13. Department of Radiation Oncology (P.C.L.), San Roque University Hospital/Universidad Fernando Pessoa Canarias, Gran Canaria, Spain. 14. Department of Radiology (D.A.), Hospital Universitario de Salamanca, Salamanca, Spain. 15. Department of Radiology (A. Revert), Hospital de Manises, Valencia, Spain. 16. Department of Radiology (E.A.), Fundación Instituto Valenciano de Oncología, Valencia, Spain.
Abstract
BACKGROUND AND PURPOSE: Multifocal glioblastomas (ie, glioblastomas with multiple foci, unconnected in postcontrast pretreatment T1-weighted images) represent a challenge in clinical practice due to their poor prognosis. We wished to obtain imaging biomarkers with prognostic value that have not been found previously. MATERIALS AND METHODS: A retrospective review of 1155 patients with glioblastomas from 10 local institutions during 2006-2017 provided 97 patients satisfying the inclusion criteria of the study and classified as having multifocal glioblastomas. Tumors were segmented and morphologic features were computed using different methodologies: 1) measured on the largest focus, 2) aggregating the different foci as a whole, and 3) recording the extreme value obtained for each focus. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell concordance indices (c-indices) were used for the statistical analysis. RESULTS: Age (P < .001, hazard ratio = 2.11, c-index = 0.705), surgery (P < .001, hazard ratio = 2.04, c-index = 0.712), contrast-enhancing rim width (P < .001, hazard ratio = 2.15, c-index = 0.704), and surface regularity (P = .021, hazard ratio = 1.66, c-index = 0.639) measured on the largest focus were significant independent predictors of survival. Maximum contrast-enhancing rim width (P = .002, hazard ratio = 2.05, c-index = 0.668) and minimal surface regularity (P = .036, hazard ratio = 1.64, c-index = 0.600) were also significant. A multivariate model using age, surgery, and contrast-enhancing rim width measured on the largest foci classified multifocal glioblastomas into groups with different outcomes (P < .001, hazard ratio = 3.00, c-index = 0.853, median survival difference = 10.55 months). Moreover, quartiles with the highest and lowest individual prognostic scores based on the focus with the largest volume and surgery were identified as extreme groups in terms of survival (P < .001, hazard ratio = 18.67, c-index = 0.967). CONCLUSIONS: A prognostic model incorporating imaging findings on pretreatment postcontrast T1-weighted MRI classified patients with glioblastoma into different prognostic groups.
BACKGROUND AND PURPOSE: Multifocal glioblastomas (ie, glioblastomas with multiple foci, unconnected in postcontrast pretreatment T1-weighted images) represent a challenge in clinical practice due to their poor prognosis. We wished to obtain imaging biomarkers with prognostic value that have not been found previously. MATERIALS AND METHODS: A retrospective review of 1155 patients with glioblastomas from 10 local institutions during 2006-2017 provided 97 patients satisfying the inclusion criteria of the study and classified as having multifocal glioblastomas. Tumors were segmented and morphologic features were computed using different methodologies: 1) measured on the largest focus, 2) aggregating the different foci as a whole, and 3) recording the extreme value obtained for each focus. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell concordance indices (c-indices) were used for the statistical analysis. RESULTS: Age (P < .001, hazard ratio = 2.11, c-index = 0.705), surgery (P < .001, hazard ratio = 2.04, c-index = 0.712), contrast-enhancing rim width (P < .001, hazard ratio = 2.15, c-index = 0.704), and surface regularity (P = .021, hazard ratio = 1.66, c-index = 0.639) measured on the largest focus were significant independent predictors of survival. Maximum contrast-enhancing rim width (P = .002, hazard ratio = 2.05, c-index = 0.668) and minimal surface regularity (P = .036, hazard ratio = 1.64, c-index = 0.600) were also significant. A multivariate model using age, surgery, and contrast-enhancing rim width measured on the largest foci classified multifocal glioblastomas into groups with different outcomes (P < .001, hazard ratio = 3.00, c-index = 0.853, median survival difference = 10.55 months). Moreover, quartiles with the highest and lowest individual prognostic scores based on the focus with the largest volume and surgery were identified as extreme groups in terms of survival (P < .001, hazard ratio = 18.67, c-index = 0.967). CONCLUSIONS: A prognostic model incorporating imaging findings on pretreatment postcontrast T1-weighted MRI classified patients with glioblastoma into different prognostic groups.
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