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Morphologic Features on MR Imaging Classify Multifocal Glioblastomas in Different Prognostic Groups.
Pérez-Beteta, J; Molina-García, D; Villena, M; Rodríguez, M J; Velásquez, C; Martino, J; Meléndez-Asensio, B; Rodríguez de Lope, Á; Morcillo, R; Sepúlveda, J M; Hernández-Laín, A; Ramos, A; Barcia, J A; Lara, P C; Albillo, D; Revert, A; Arana, E; Pérez-García, V M.
Afiliación
  • Pérez-Beteta J; 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.
  • Molina-García D; 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.
  • Villena M; Departments of Neurosurgery (M.V.).
  • Rodríguez MJ; Radiology (M.J.R.), Hospital General de Ciudad Real, Ciudad Real, Spain.
  • Velásquez C; Department of Neurosurgery (J.M., C.V.), Hospital Universitario Marqués de Valdecilla and Fundación, Instituto de Investigación Marqués de Valdecilla, Santander, Spain.
  • Martino J; Department of Neurosurgery (J.M., C.V.), Hospital Universitario Marqués de Valdecilla and Fundación, Instituto de Investigación Marqués de Valdecilla, Santander, Spain.
  • Meléndez-Asensio B; Departments of Molecular Biology (B.M.-A.).
  • Rodríguez de Lope Á; Neurosurgery (Á.R.d.L.).
  • Morcillo R; Radiology (R.M.), Hospital Virgen de la Salud, Toledo, Spain.
  • Sepúlveda JM; Departments of Neuro-Oncology (J.M.S.).
  • Hernández-Laín A; Pathology (A.H.-L.).
  • Ramos A; Radiology (A. Ramos), Hospital Universitario 12 de Octubre, Madrid, Spain.
  • Barcia JA; Department of Neurosurgery (J.A.B.), Hospital Clínico San Carlos, Madrid, Spain.
  • Lara PC; Department of Radiation Oncology (P.C.L.), San Roque University Hospital/Universidad Fernando Pessoa Canarias, Gran Canaria, Spain.
  • Albillo D; Department of Radiology (D.A.), Hospital Universitario de Salamanca, Salamanca, Spain.
  • Revert A; Department of Radiology (A. Revert), Hospital de Manises, Valencia, Spain.
  • Arana E; Department of Radiology (E.A.), Fundación Instituto Valenciano de Oncología, Valencia, Spain.
  • Pérez-García VM; 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.
AJNR Am J Neuroradiol ; 40(4): 634-640, 2019 04.
Article en En | MEDLINE | ID: mdl-30923085
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Glioblastoma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: AJNR Am J Neuroradiol Año: 2019 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Glioblastoma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: AJNR Am J Neuroradiol Año: 2019 Tipo del documento: Article País de afiliación: España