Apparent diffusion coefficient changes predict survival after intra-arterial bevacizumab treatment in recurrent glioblastoma

Galla, Naveen; Chiang, Gloria; Chakraborty, Shamik; Singh, Ranjodh; Tsiouris, Apostolos John; Boockvar, John A.; Kovanlıkaya, İlhami

doi:10.1007/s00234-017-1820-4

Cited by 20 publications

(17 citation statements)

References 37 publications

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“…Chang et al [ 65 ], in a similar study setting, used machine learning approach based on a multimodal approach, including ADC texture and four-component histogram metrics, and developed a valid predictive model for OS. The remaining two studies on R-GBM patients investigated the power of normalized ADC mean and min values in enhancing and non-enhancing tumoral regions [ 71 , 84 ]. Galla et al [ 71 ] found that in R-GBM patients treated with superselective intra-arterial cerebral infusion of BV, the change in normalized ADC mean and min after treatment is predictive of OS.…”

Section: Resultsmentioning

confidence: 99%

“…The remaining two studies on R-GBM patients investigated the power of normalized ADC mean and min values in enhancing and non-enhancing tumoral regions [ 71 , 84 ]. Galla et al [ 71 ] found that in R-GBM patients treated with superselective intra-arterial cerebral infusion of BV, the change in normalized ADC mean and min after treatment is predictive of OS. Song et al [ 84 ] found that normalized ADC can be used as an imaging biomarker to determine PFS in R-GBM patients treated with immune checkpoint inhibitors.…”

Section: Resultsmentioning

confidence: 99%

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Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

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Nuzzo

Tramontano

et al. 2020

Cancers

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Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

Brancato

Nuzzo

Tramontano

et al. 2020

Cancers

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“…32,33 Previous studies demonstrated that DWI, and the IVIM model, can contribute to monitor therapeutic effects in pharmacological therapy. 34,35 Some limitations of this study should be acknowledged. The number of malignant tumors is relatively small, but syndromal malignant PNSTs in the context of NF1 are rare tumors, and the number of malignant PNSTs analyzed in this study is comparable to other studies.…”

Section: Well Et Al Diffusion-weighted Imaging In Nf1mentioning

confidence: 95%

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging

et al. 2018

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Background. We sought to determine the value of diffusion-weighted (DW) magnetic resonance imaging (MRI) for characterization of benign and malignant peripheral nerve sheath tumors (PNSTs) in patients with neurofibromatosis type 1 (NF1). Methods. Twenty-six patients with NF1 and suspicion of malignant transformation of PNSTs were prospectively enrolled and underwent DW MRI at 3T. For a set of benign (n = 55) and malignant (n = 12) PNSTs, functional MRI parameters were derived from both biexponential intravoxel incoherent motion (diffusion coefficient D and perfusion fraction f) and monoexponential data analysis (apparent diffusion coefficients [ADCs]). A panel of morphological MRI features was evaluated using T1-and T2-weighted imaging. Mann-Whitney U-test, Fisher's exact test, and receiver operating characteristic (ROC) analyses were applied to assess the diagnostic accuracy of quantitative and qualitative MRI. Cohen's kappa was used to determine interrater reliability. Results. Malignant PNSTs demonstrated significantly lower diffusivity (P < 0.0001) compared with benign PNSTs. The perfusion fraction f was significantly higher in malignant PNSTs (P < 0.001). In ROC analysis, functional MRI parameters showed high diagnostic accuracy for differentiation of PNSTs (eg, ADC mean, 92% sensitivity with 98% specificity, AUC 0.98; D mean, 92% sensitivity with 98% specificity, AUC 0.98). By contrast, morphological imaging features had only limited sensitivity (18-94%) and specificity (18-82%) for identification of malignancy. Interrater reliability was higher for monoexponential data analysis. Conclusion. DW imaging shows better diagnostic performance than morphological features and allows accurate differentiation of benign and malignant peripheral nerve sheath tumors in NF1. Key Points 1. DWI allows sensitive and specific identification of malignancy in NF1. 2. Morphological features have limited accuracy for identifying malignant transformation. Well et al. Diffusion-weighted imaging in NF1 Neuro-Oncology Keywords diffusion-weighted imaging | intravoxel incoherent motion analysis | morphological features | neurofibromatosis type 1 | peripheral nerve sheath tumor

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“…Hsu et al simultaneously showed that the pre-to-post-bevacizumab-treatment ADC reduction was positively associated with tumor volume shrinkage in recurrent low-grade gliomas; however, the relationship between ADC reduction and outcome has not been reported ( Hsu et al, 2015 ). Galla et al investigated 65 rGBM patients treated with bevacizumab and determined that patients with greater pre-to-post-ADC reductions had lower 1-year OS rates ( Galla et al, 2017 ).…”

Section: Physiological Parameters In Anti-angiogenic Therapymentioning

confidence: 99%

Imaging biomarkers guided anti-angiogenic therapy for malignant gliomas

Kong

Yan

Zhu

et al. 2018

NeuroImage: Clinical

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Antiangiogenic therapy is a universal approach to the treatment of malignant gliomas but fails to prolong the overall survival of newly diagnosed or recurrent glioblastoma patients. Imaging biomarkers are quantitative imaging parameters capable of objectively describing biological processes, pathological changes and treatment responses in some situations and have been utilized for outcome predictions of malignant gliomas in anti-angiogenic therapy. Advanced magnetic resonance imaging techniques (including perfusion-weighted imaging and diffusion-weighted imaging), positron emission computed tomography and magnetic resonance spectroscopy are imaging techniques that can be used to acquire imaging biomarkers, including the relative cerebral blood volume (rCBV), Ktrans, and the apparent diffusion coefficient (ADC). Imaging indicators for a better prognosis when treating malignant gliomas with antiangiogenic therapy include the following: a lower pre- or post-treatment rCBV, less change in rCBV during treatment, a lower pre-treatment Ktrans, a higher vascular normalization index during treatment, less change in arterio-venous overlap during treatment, lower pre-treatment ADC values for the lower peak, smaller ADC volume changes during treatment, and metabolic changes in glucose and phenylalanine. The investigation and utilization of these imaging markers may confront challenges, but may also promote further development of anti-angiogenic therapy. Despite considerable evidence, future prospective studies are critically needed to consolidate the current data and identify novel biomarkers.

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Apparent diffusion coefficient changes predict survival after intra-arterial bevacizumab treatment in recurrent glioblastoma

Abstract: In patients with recurrent GB treated with SIACI BV, the change in ADC value after treatment is predictive of overall survival.

Cited by 20 publications

References 37 publications

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging

Imaging biomarkers guided anti-angiogenic therapy for malignant gliomas

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