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ADC texture--an imaging biomarker for high-grade glioma?
Brynolfsson, Patrik; Nilsson, David; Henriksson, Roger; Hauksson, Jón; Karlsson, Mikael; Garpebring, Anders; Birgander, Richard; Trygg, Johan; Nyholm, Tufve; Asklund, Thomas.
Afiliação
  • Brynolfsson P; Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå SE-901 87, Sweden.
  • Nilsson D; Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, Umeå SE-901 87, Sweden.
  • Henriksson R; Department of Radiation Sciences, Oncology, Umeå University, Umeå SE-901 87, Sweden and Regionalt Cancercentrum Stockholm, Karolinska Universitetssjukhuset, Solna, Stockholm SE-102 39, Sweden.
  • Hauksson J; Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå SE-901 87, Sweden.
  • Karlsson M; Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå SE-901 87, Sweden.
  • Garpebring A; Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå SE-901 87, Sweden.
  • Birgander R; Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå SE-901 87, Sweden.
  • Trygg J; Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, Umeå SE-901 87, Sweden.
  • Nyholm T; Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå SE-901 87, Sweden.
  • Asklund T; Department of Radiation Sciences, Oncology, Umeå University, Umeå SE-901 87, Sweden.
Med Phys ; 41(10): 101903, 2014 Oct.
Article em En | MEDLINE | ID: mdl-25281955
ABSTRACT

PURPOSE:

Survival for high-grade gliomas is poor, at least partly explained by intratumoral heterogeneity contributing to treatment resistance. Radiological evaluation of treatment response is in most cases limited to assessment of tumor size months after the initiation of therapy. Diffusion-weighted magnetic resonance imaging (MRI) and its estimate of the apparent diffusion coefficient (ADC) has been widely investigated, as it reflects tumor cellularity and proliferation. The aim of this study was to investigate texture analysis of ADC images in conjunction with multivariate image analysis as a means for identification of pretreatment imaging biomarkers.

METHODS:

Twenty-three consecutive high-grade glioma patients were treated with radiotherapy (2 Gy/60 Gy) with concomitant and adjuvant temozolomide. ADC maps and T1-weighted anatomical images with and without contrast enhancement were collected prior to treatment, and (residual) tumor contrast enhancement was delineated. A gray-level co-occurrence matrix analysis was performed on the ADC maps in a cuboid encapsulating the tumor in coronal, sagittal, and transversal planes, giving a total of 60 textural descriptors for each tumor. In addition, similar examinations and analyses were performed at day 1, week 2, and week 6 into treatment. Principal component analysis (PCA) was applied to reduce dimensionality of the data, and the five largest components (scores) were used in subsequent analyses. MRI assessment three months after completion of radiochemotherapy was used for classifying tumor progression or regression.

RESULTS:

The score scatter plots revealed that the first, third, and fifth components of the pretreatment examinations exhibited a pattern that strongly correlated to survival. Two groups could be identified one with a median survival after diagnosis of 1099 days and one with 345 days, p = 0.0001.

CONCLUSIONS:

By combining PCA and texture analysis, ADC texture characteristics were identified, which seems to hold pretreatment prognostic information, independent of known prognostic factors such as age, stage, and surgical procedure. These findings encourage further studies with a larger patient cohort.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Interpretação de Imagem Assistida por Computador / Imagem de Difusão por Ressonância Magnética / Glioma Tipo de estudo: Observational_studies / Prognostic_studies Limite: Adult / Aged / Humans / Middle aged Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Interpretação de Imagem Assistida por Computador / Imagem de Difusão por Ressonância Magnética / Glioma Tipo de estudo: Observational_studies / Prognostic_studies Limite: Adult / Aged / Humans / Middle aged Idioma: En Ano de publicação: 2014 Tipo de documento: Article