Revisión sistemática : uso de imágenes por difusión en RMN, para predecir sobrevida en pacientes adultos con diagnostico de glioblastoma multiforme
Contribuinte(s) |
Trillos Peña, Carlos Enrique |
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Data(s) |
28/10/2012
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Resumo |
El Glioblastoma multiforme (GBM), es el tumor cerebral más frecuente, con pronóstico grave y baja sensibilidad al tratamiento inicial. El propósito de este estudio fue evaluar si la Difusión en RM (IDRM), es un biomarcador temprano de respuesta tumoral, útil para tomar decisiones tempranas de tratamiento y para obtener información pronostica. Metodología La búsqueda se realizo en las bases de datos EMBASE, CENTRAL, MEDLINE; las bibliografías también fueron revisadas. Los artículos seleccionados fueron estudios observacionales (casos y controles, cohortes, corte transversal), no se encontró ningún ensayo clínico; todos los participante tenían diagnostico histopatológico de GBM, sometidos a resección quirúrgica y/o radio-quimioterapia y seguimiento de respuesta al tratamiento con IDRM por al menos 6 meses. Los datos extraídos de forma independiente fueron tipo de estudio, participantes, intervenciones, seguimiento, desenlaces (sobrevida, progresión/estabilización de la enfermedad, muerte) Resultados Quince estudios cumplieron los criterios de inclusión. Entre las técnicas empleadas de IDRM para evaluar respuesta radiológica al tratamiento, fueron histogramas del coeficiente aparente de difusion ADC (compararon valores inferiores a la media y el percentil 10 de ADC, con los valores superiores); encontrando en términos generales que un ADC bajo es un fuerte predictor de sobrevida y/o progresión del tumor. (Esto fue significativo en 5 estudios); mapas funcionales de difusion (FDM) (midieron el porcentaje de cambio de ADC basal vs pos tratamiento) que mostro ser un fuerte predictor de sobrevida en pacientes con progresión tumoral. DISCUSION Desafortunadamente la calidad de los estudios fue intermedia-baja lo que hace que la aplicabilidad de los estudios sea limitada. Universidad del Rosario y Nacional introduction Glioblastoma multiforme (GBM) is the most common brain tumor with poor prognosis and low sensitivity to initial treatment. The purpose of this study was to evaluate whether Diffusion MRI (IDRM) is an early biomarker of tumor response, useful for early treatment decisions and forecast information. methodology The search was conducted in the databases EMBASE, CENTRAL, MEDLINE, bibliographies were also reviewed. Selected articles were observational studies (case-control, cohort, cross-section), we found no clinical trial, all participants had histopathologic diagnosis of GBM, underwent surgical resection and / or radio-chemotherapy and monitoring response to treatment with IDRM for at least 6 months. Data were independently extracted study type, participants, interventions, monitoring, outcomes (survival, progression / stable disease, death) Results Fifteen studies met the inclusion criteria. Among the techniques employed to evaluate IDRM radiological response to treatment, were histograms of apparent diffusion coefficient (ADC values compared below average and the 10th percentile of ADC, with higher values), generally finding that a low ADC is a strong predictor of survival and / or tumor progression. (This was significant in five studies); functional diffusion maps (FDM) (measured ADC percentage change of baseline vs. post treatment) was shown to be a strong predictor of survival in patients with tumor progression. DISCUSSION Unfortunately, the quality of the studies was intermediate-low which makes the applicability of the studies is limited. |
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application/pdf |
Identificador | |
Idioma(s) |
spa |
Publicador |
Facultad de medicina |
Direitos |
info:eu-repo/semantics/openAccess |
Fonte |
instname:Universidad del Rosario reponame:Repositorio Institucional EdocUR 1 SEER [internet]. Bethesda: National Cancer Institute; 1975-2006 [fecha de acceso 15 de Julio de 2011]. Cancer statistics review; [aproximadamente dos patallas]. Disponible en: http://seer.cancer.gov/ab 2 Instituto Nacional de Cancerología. Anuario Estadístico 2008. Volumen 6 3 Padhani AR, Koh DM. Diffusion MR Imaging for Monitoring of Treatment Response. Magn Reson Imaging Clin N Am. 2011 Feb;19(1):181-209. 4 Brandes AA, Tosoni A, Franceschi E, Reni M, Gatta G, Vecht C. Glioblastoma in adults. Crit Rev Oncol Hematol. 2008 Aug;67(2):139-52. Epub 2008 Apr 5 Burger PC, Kleihues P. Cytologic composition of the untreated glioblastoma with implications for evaluation of needle biopsies. Cancer. 1989 May 15;63(10):2014-23 6 Grupo de Neurooncologia, Sociedad Española de Neuroradiologia, Criterios de Respuesta de los Tumores Cerebrales. Diciembre del 2011. 7 Figueiredo EH, Borgonovi AF, Doring TM. Basic Concepts of MR Imaging, diffusion MR Imaging, and Diffusion Tensor Imaging. Magn Reson Imaging Clin N Am. 2011 Feb;19(1):1-22 8 Chenevert TL, Ross BD. Diffusion imaging for therapy response assessment of brain tumor. Neuroimaging Clin N Am. 2009 Nov;19(4):559-71 DeAngelis LM, Loeffler JS, Adam N. Mamelak AN, Adam N. Mamelak AN. Primary and Metastatic Brain Tumors. Cancer Management: A Multidisciplinary Approach, 2007; 10th Ed 10 Laws ER, Parney IF, Huang W, Anderson F, Morris AM, Asher A. Survival following surgery and prognostic factors for recently diagnosed malignant glioma: data from the Glioma Outcomes Project. J Neurosurg. 2003 Sep;99(3):467-73. 11 Cook B, Dvorak T. Radiation Oncology/CNS/High grade glioma/Overview Wikibooks. 2008 12 Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005 Mar 10;352(10):987-96. 13 Macdonald DR, Cascino TL, Schold SC Jr, Cairncross JG. Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol. 1990 Jul;8(7):1277-80. 14 Sorensen AG, Patel S, Harmath C, Bridges S, Synnott J, Sievers A. et al. Comparison of diameter and perimeter methods for tumor volume calculation. J Clin Oncol. 2001 Jan 15;19(2):551-7. 15 Scott JN, Rewcastle NB, Brasher PM, Fulton D, Hagen NA, MacKinnon JA, Long-term glioblastoma multiforme survivors: a population-based study. Can J Neurol Sci. 1998 Aug;25(3):197-201 16 Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer. 2009 Jan;45(2):228-47 17 Pope WB, Lai A, Mehta R, Kim HJ, Qiao J, Young JR, et al. Apparent diffusion coefficient histogram analysis stratifies progression-free survival in newlydiagnosed bevacizumab-treated glioblastoma. AJNR Am J Neuroradiol. 2011 May;32(5):882-9. Epub 2011 Feb 17 18 Saraswathy S, Crawford FW, Lamborn KR, Pirzkall A, Chang S, Cha S, et al.Evaluation of MR markers that predict survival in patients with newly diagnosed GBM prior toadjuvant therapy. J Neurooncol. 2009 Jan;91(1):69-81. Epub 2008 Sep 23. 19 Yamasaki F, Sugiyama K, Ohtaki M, Takeshima Y, Abe N, Akiyama Y, et al. Glioblastoma treated with postoperative radio-chemotherapy: prognostic value of apparentdiffusion coefficient at MR imaging. Eur J Radiol. 2010 Mar;73(3):532-7. Epub 2009 Feb 27. 20 Gupta A, Young RJ, Karimi S, Sood S, Zhang Z, Mo Q, et al. Isolated diffusion restriction precedes the development of enhancing tumor in a subset of patientswith glioblastoma. AJNR Am J Neuroradiol. 2011 Aug;32(7):1301-6. Epub 2011 May 19. 21 Khayal IS, Polley MY, Jalbert L, Elkhaled A, Chang SM, Cha S, et al, Evaluation of diffusion parameters as early biomarkers of disease progression in glioblastomamultiforme. Neuro Oncol. 2010 Sep;12(9):908-16. Epub 2010 May 25 22 Hamstra DA, Chenevert TL, Moffat BA, Johnson TD, Meyer CR, Mukherji SK, et al. Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overallsurvival in high-grade glioma. Proc Natl Acad Sci U S A. 2005 Nov 15;102(46):16759-64. Epub 2005 Nov 2. 23 Ellingson BM, Cloughesy TF, Zaw T, Lai A, Nghiemphu PL, Harris R, et al. Functional diffusion maps (fDMs) evaluated before and after radiochemotherapy predictprogression-free and overall survival in newly diagnosed glioblastoma. Neuro Oncol. 2012 Mar;14(3):333-43. Epub 2012 Jan 22. 24 Li Y, Lupo JM, Polley MY, Crane JC, Bian W, Cha S, et al. Serial analysis of imaging parameters in patients with newly diagnosed glioblastoma multiforme. Neuro Oncol. 2011 May;13(5):546-57. Epub 2011 Feb 4. 25 Oh J, Henry RG, Pirzkall A, Lu Y, Li X, Catalaa I, et al. Survival analysis in patients with glioblastoma multiforme: predictive value of choline-to-N acetylaspartate index, apparent diffusion coefficient, and relative cerebral blood volume. J Magn Reson Imaging. 2004 May;19(5):546-54 26 Hamstra DA, Galbán CJ, Meyer CR, Johnson TD, Sundgren PC, Tsien C, et al. Functional diffusion map as an early imaging biomarker for high-grade glioma: correlation withconventional radiologic response and overall survival. J Clin Oncol. 2008 Jul 10;26(20):3387-94. Epub 2008 Jun 9. 27 Higano S, Yun X, Kumabe T, Watanabe M, Mugikura S, Umetsu A, et al. Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction ofgrade and prognosis. Radiology. 2006 Dec;241(3):839-46. Epub 2006 Oct 10. 28 Murakami R, Sugahara T, Nakamura H, Hirai T, Kitajima M, Hayashida Y, et al.Malignant supratentorial astrocytoma treated with postoperative radiation therapy: prognosticvalue of pretreatment quantitative diffusion-weighted MR imaging. Radiology. 2007 May;243(2):493-9. Epub 2007 Mar 13. 29 Ellingson BM, Malkin MG, Rand SD, LaViolette PS, Connelly JM, Mueller WM, et al. Volumetric analysis of functional diffusion maps is a predictive imaging biomarker for cytotoxicand antiangiogenic treatments in malignant gliomas. J Neurooncol. 2011 Mar;102(1):95-103. Epub 2010 Aug 27. 30 Jain R, Scarpace LM, Ellika S, Torcuator R, Schultz LR, Hearshen D, et al. Imaging response criteria for recurrent gliomas treated with bevacizumab: role of diffusionweighted imaging as an imaging biomarker. J Neurooncol. 2010 Feb;96(3):423-31. Epub 2009 Oct 27. 31 Pope WB, Kim HJ, Huo J, Alger J, Brown MS, Gjertson D, et al. Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumabtreatment. Radiology. 2009 Jul;252(1):182-9. 32 Karnofsky DA, Burchenal JH (1949) The clinical evaluation of chemotherapeutic agents in cancer. In: MacLeod CM (ed) Evaluation of chemotherapeutic agents. Columbia University Press, New York, pp 191–205 33 Debnam JM, Schellingerhout D. Diffusion MR Imaging of the Brain in Patients with Cancer. Int J Mol Imaging. ;2011:714021. Epub 2011 Oct 25. 34 Egger M, Davey G, Altman D, Systematic Reviews in Health Care. 2da ed. London: BMJ Publishing Group; 2001. P 231-35. 35 Laupacis A, Wells G, Richardson S, Tugwell P. Users' Guides to the Medical Literature V. How to Use an Article About Prognosis. Evidence-Based Medicine Working Group; JAMA, 1994, Vol 272, n°3 36 Hygino da Cruz Jr, I. Rodriguez, R.C. Domingues. Pseudoprogression and Pseudoresponse: Imaging Challenges in the Assessment of Posttreatment Glioma. AJNR Am J Neuroradiol 32:1978–85 Dec 2011 37 Sasaki M, Yamada K,Watanabe Y, et al. Variability in absolute apparent diffusion coefficient values across different platforms may be substantial: amultivendor, multi-institutional comparison study. Radiology 2008;249(2):624–30. 38 Engelter ST, Provenzale JM, Petrella JR, DeLong DM, MacFall JR. The effect of aging on the apparent diffusion coefficient of normal-appearing white matter. AJR Am J Roentgenol 2000;175(2):425–30. TEME 0094 2012 |
Palavras-Chave | #GLIOBLASTOMA #TERAPIA DEL GEN #NEOPLASMAS DE CABEZA Y CUELLO #Diffusion Magnetic Resonance Imaging/methods #Treatment Outcome #Glioblastoma/ therapy |
Tipo |
info:eu-repo/semantics/bachelorThesis info:eu-repo/semantics/acceptedVersion |