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1.
AJNR Am J Neuroradiol ; 39(3): 507-514, 2018 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-29371254

RESUMO

BACKGROUND AND PURPOSE: Malignant glioma is a highly infiltrative malignancy that causes variable disruptions to the structure and function of the cerebrovasculature. While many of these structural disruptions have known correlative histopathologic alterations, the mechanisms underlying vascular dysfunction identified by resting-state blood oxygen level-dependent imaging are not yet known. The purpose of this study was to characterize the alterations that correlate with a blood oxygen level-dependent biomarker of vascular dysregulation. MATERIALS AND METHODS: Thirty-two stereotactically localized biopsies were obtained from contrast-enhancing (n = 16) and nonenhancing (n = 16) regions during open surgical resection of malignant glioma in 17 patients. Preoperative resting-state blood oxygen level-dependent fMRI was used to evaluate the relationships between radiographic and histopathologic characteristics. Signal intensity for a blood oxygen level-dependent biomarker was compared with scores of tumor infiltration and microvascular proliferation as well as total cell and neuronal density. RESULTS: Biopsies corresponded to a range of blood oxygen level-dependent signals, ranging from relatively normal (z = -4.79) to markedly abnormal (z = 8.84). Total cell density was directly related to blood oxygen level-dependent signal abnormality (P = .013, R2 = 0.19), while the neuronal labeling index was inversely related to blood oxygen level-dependent signal abnormality (P = .016, R2 = 0.21). The blood oxygen level-dependent signal abnormality was also related to tumor infiltration (P = .014) and microvascular proliferation (P = .045). CONCLUSIONS: The relationship between local, neoplastic characteristics and a blood oxygen level-dependent biomarker of vascular function suggests that local effects of glioma cell infiltration contribute to vascular dysregulation.


Assuntos
Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Glioma/diagnóstico por imagem , Glioma/patologia , Oxigênio/sangue , Adulto , Feminino , Humanos , Imageamento por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade
2.
AJNR Am J Neuroradiol ; 38(5): 890-898, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28255030

RESUMO

BACKGROUND AND PURPOSE: The complex MR imaging appearance of glioblastoma is a function of underlying histopathologic heterogeneity. A better understanding of these correlations, particularly the influence of infiltrating glioma cells and vasogenic edema on T2 and diffusivity signal in nonenhancing areas, has important implications in the management of these patients. With localized biopsies, the objective of this study was to generate a model capable of predicting cellularity at each voxel within an entire tumor volume as a function of signal intensity, thus providing a means of quantifying tumor infiltration into surrounding brain tissue. MATERIALS AND METHODS: Ninety-one localized biopsies were obtained from 36 patients with glioblastoma. Signal intensities corresponding to these samples were derived from T1-postcontrast subtraction, T2-FLAIR, and ADC sequences by using an automated coregistration algorithm. Cell density was calculated for each specimen by using an automated cell-counting algorithm. Signal intensity was plotted against cell density for each MR image. RESULTS: T2-FLAIR (r = -0.61) and ADC (r = -0.63) sequences were inversely correlated with cell density. T1-postcontrast (r = 0.69) subtraction was directly correlated with cell density. Combining these relationships yielded a multiparametric model with improved correlation (r = 0.74), suggesting that each sequence offers different and complementary information. CONCLUSIONS: Using localized biopsies, we have generated a model that illustrates a quantitative and significant relationship between MR signal and cell density. Projecting this relationship over the entire tumor volume allows mapping of the intratumoral heterogeneity in both the contrast-enhancing tumor core and nonenhancing margins of glioblastoma and may be used to guide extended surgical resection, localized biopsies, and radiation field mapping.


Assuntos
Neoplasias Encefálicas/diagnóstico por imagem , Glioblastoma/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Adulto , Algoritmos , Neoplasias Encefálicas/patologia , Contagem de Células , Feminino , Glioblastoma/patologia , Humanos , Masculino , Pessoa de Meia-Idade , Carga Tumoral
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