Apparent Diffusion Coefficient Histogram Analysis Stratifies Progression-Free Survival in Newly Diagnosed Bevacizumab-Treated Glioblastoma

Pope, Whitney B.; Lai, Albert; Mehta, Rupal I.; Kim, H. J.; Qiao, Jian-Hua; Young, Jonathan R.; Xue, Xi; Goldin, Jonathan G.; Brown, Matthew S.; Nghiemphu, Phioanh L.; Tran, Anh; Cloughesy, Timothy F.

doi:10.3174/ajnr.a2385

Cited by 166 publications

(132 citation statements)

References 27 publications

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“…There have been a few studies that have tried to identify IDH1 mutations using MR spectroscopy. The short-echo MRS is widely available on clinical scanners, though the false-positive rate is approximately 22% [35]. There have been other, more complex MRS techniques that have been more successful, such as Choi et al [36], who identified all patients with IDH mutations without false-positive results.…”

Section: Discussionmentioning

confidence: 99%

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

et al. 2017

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Section: Discussionmentioning

confidence: 99%

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

et al. 2017

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“…The MRI scans were interpreted by two neuroradiologists blinded to the patient outcome. We selected eight cardinal tumor‐related imaging features and dichotomized these features according to previous guidelines using the following criteria: ADC value,12, 13 peritumoral edema,14 contrast‐enhancing tumor (CET),15 necrosis,16 formation of cysts (cyst),16 noncontrast‐enhancing tumor (nCET),17 T1/Flair ratio,16 and deep white matter invasion 15. The exact dichotomy information is listed in Table 1.…”

Section: Methodsmentioning

confidence: 99%

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI‐derived and clinical features, predict adult primary glioblastoma survival

et al. 2018

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PurposeThis study aimed to integrate the TERT promoter mutation status, MGMT promoter methylation status, MRI‐derived features, and clinical features into a survival analysis model to better understand adult primary glioblastoma prognosis‐related markers.MethodA total of 304 adult glioblastoma samples collected after surgical resection were selected for retrospective analysis, and Sanger sequencing was performed to detect IDH and TERT promoter mutations. The methylation of the MGMT promoter was analyzed by pyrosequencing, and MRI‐derived and clinical features were dichotomized into easily acquired variables. Random survival forest analysis, Kaplan‐Meier analysis, Cox proportional hazard regression, and LASSO regression were performed for the survival analysis, and ROC analysis and Pearson's chi‐squared test were employed for the correlation analysis.ResultsWild‐type IDH was present in 89.8% of the adult glioblastoma samples, and TERT promoter mutations and MGMT promoter methylation were observed in 66.42% and 38.49% of all adult primary glioblastomas, respectively. Age and MGMT promoter methylation were identified as independent prognostic biomarkers, and the TERT promoter mutation status and MGMT promoter methylation status, when combined with other tumor‐related factors, generated several different survival subgroups. None of the factors investigated in this study predicted the MGMT promoter status, and MRI‐detected necrosis was positively associated with TERT promoter mutations.ConclusionMGMT promoter methylation and TERT promoter mutations, combined with MRI‐derived and clinical features, revealed different survival subgroups with distinct responses to current treatments, and this information increases the ability to predict the survival of adult primary glioblastoma patients. MRI‐detected necrosis often indicates the presence of TERT promoter mutations.

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“…High-risk patients were identified by ADCL Յ 1.2 m 2 / ms, whereas low-risk patients were identified by ADCL Ͼ 1.2 m 2 /ms, based on empiric thresholds identified in previous studies. 9,10,19,20 …”

Section: Adc Histogram Analysismentioning

confidence: 99%

“…These limitations have resulted in a surge of more advanced imaging biomarkers aimed at predicting response to therapy, as summarized in various review articles. 7,8 Among these new imaging biomarkers showing promise are diffusion MR imaging techniques, [9][10][11][12][13][14][15][16][17][18] including ADC histogram analysis. Previous results have shown that pretreatment ADC histogram analysis performed within the contrast-enhancing tumor regions can stratify patients with recurrent GBM into high-and low-risk groups.…”

mentioning

confidence: 99%

Pretreatment ADC Histogram Analysis Is a Predictive Imaging Biomarker for Bevacizumab Treatment but Not Chemotherapy in Recurrent Glioblastoma

Ellingson¹,

Sahebjam

Kim³

et al. 2013

American Journal of Neuroradiology

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BACKGROUND AND PURPOSE:Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of treatment response in recurrent glioblastoma multiforme.

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Apparent Diffusion Coefficient Histogram Analysis Stratifies Progression-Free Survival in Newly Diagnosed Bevacizumab-Treated Glioblastoma

Cited by 166 publications

References 27 publications

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI‐derived and clinical features, predict adult primary glioblastoma survival

Pretreatment ADC Histogram Analysis Is a Predictive Imaging Biomarker for Bevacizumab Treatment but Not Chemotherapy in Recurrent Glioblastoma

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