Apparent diffusion coefficient histogram analysis for prediction of prognosis in glioblastoma

Masatoshi Kondo, Yoshikazu Uchiyama

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Background: To investigate the potential to predict prognosis of glioblastoma (GBM) patients by analysis of the broader and lower values in the lower distribution of apparent diffusion coefficient (ADCL) (B&L-ADCL) values in the ADC histogram. Background: Presurgical publicly available diffusion-weighted images (DWI) and contrast-enhanced T1-weighted images from 76 GBM patients were analyzed. With applied 2-mixture normal distribution in the ADC histogram of enhanced lesions on T1-weighted images, the mean and width of ADCL were analyzed. We dichotomized the lower mean of ADCL (L-ADCL) and the broader width of ADCL (B-ADCL) at their own average. B&L-ADCL was defined as B-ADCL with L-ADCL. Progression-free survival (PFS) and overall survival (OS) were determined by using Cox proportional hazards analysis and the Kaplan–Meier method with the log-rank test. The difference between PFS and OS was calculated. Results: Six (7.89%) patients had B&L-ADCL values. B&L-ADCL was strongly associated with poor PFS (hazard risk: 5.747; P = 0.002) and OS (hazard risk: 3.331; P = 0.018). There were significant differences in PFS (median, 77 vs. 302 days; P < 0.001) and OS (median, 199 vs. 472 days; P = 0.004) between the patents with and without B&L-ADCL. There was no significant difference in the OS–PFS duration difference between the patients with (median, 79 days) and without B&L-ADCL (median, 132 days) (P = 0.348). Conclusion: In this study, B&L-ADCL from pretreatment ADC analysis predicted poor PFS. B&L-ADCL may indicate higher cellularity and heterogeneity in GBM tumor tissue.

Original languageEnglish
Pages (from-to)236-241
Number of pages6
JournalJournal of Neuroradiology
Volume45
Issue number4
DOIs
Publication statusPublished - Jul 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

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