Biopsy targeting with dynamic contrast-enhanced versus standard neuronavigation MRI in glioma: a prospective double-blinded evaluation of selection benefits

Conventional and advanced imaging throughout the cycle of care of gliomas

Although imaging of gliomas has evolved tremendously over the last decades, published techniques and protocols are not always implemented into clinical practice. Furthermore, most of the published literature focuses on specific timepoints in glioma management. This article reviews the current literature on conventional and advanced imaging techniques and chronologically outlines their practical relevance for the clinical management of gliomas throughout the cycle of care. Relevant articles were located through the Pubmed/Medline database and included in this review. Interpretation of conventional and advanced imaging techniques is crucial along the entire process of glioma care, from diagnosis to follow-up. In addition to the described currently existing techniques, we expect deep learning or machine learning approaches to assist each step of glioma management through tumor segmentation, radiogenomics, prognostication, and characterization of pseudoprogression. Thorough knowledge of the specific performance, possibilities, and limitations of each imaging modality is key for their adequate use in glioma management.

Can dynamic contrast-enhanced MRI evaluate VEGF expression in brain glioma? An MRI-guided stereotactic biopsy study

PURPOSE

To investigate whether pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to evaluate vascular endothelial growth factor (VEGF) expression in brain glioma based on a point-to-point basis.

MATERIALS AND METHODS

Forty-seven patients with treatment-naïve glioma received preoperative DCE-MRI before stereotactic biopsy. We histologically quantified VEGF from section of stereotactic biopsies, and co-registered biopsy locations with localized measurements of DCE-MRI parameters including volume transfer coefficient (K^trans), reverse reflux rate constant (Kep), extracellular extravascular volume fraction (Ve) and blood plasma volume (Vp). The correlations between DCE-MRI parameters (K^trans, Kep, Ve and Vp) and VEGF were determined using Spearman correlation coefficient. P≤.05 was considered statistically significant.

RESULTS

Seventy-nine biopsy samples were obtained and graded into 45 high-grade gliomas (HGGs) and 34 low-grade gliomas (LGGs). K^trans showed a significant positive correlation with VEGF expression in HGGs group (ρ=0.505, P<0.001) and in combined group (LGGs+HGGs) (ρ=0.549, P<0.001), but not in LGGs group (P>0.05). Kep, Ve or Vp was not correlated with VEGF even though a positive trend showed (P>0.05).

CONCLUSIONS

DCE-MRI is a useful, non-invasive imaging technique for quantitative evaluation of VEGF, and its parameter K^trans other than Kep, Ve or Vp may be used as a surrogate for VEGF expression in brain gliomas.

Conventional and advanced magnetic resonance imaging in patients with high-grade glioma

Magnetic resonance imaging is integral to the care of patients with high-grade gliomas. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic and molecular characteristics of central nervous system neoplasms. These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumor burden and therapy response. The following is an overview of current strategies based on advanced magnetic resonance imaging that are used in the assessment of high-grade glioma patients with an emphasis on how novel imaging biomarkers can potentially advance patient care.

Meningioma assessment: Kinetic parameters in dynamic contrast-enhanced MRI appear independent from microvascular anatomy and VEGF expression

BACKGROUND AND PURPOSE

Kinetic parameters of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are considered to be influenced by microvessel environment. This study was performed to explore the extent of this association for meningiomas.

MATERIALS AND METHODS

DCE-MRI kinetic parameters (contrast agent transfer constants K^trans and k_ep, volume fractions v_p and v_e) were determined in pre-operative 3T MRI of meningioma patients for later biopsy sites (19 patients; 15 WHO I^o, no previous radiation, and 4 WHO III^o pre-radiated recurrent tumors). Sixty-three navigated biopsies were consecutively retrieved. Biopsies were immunohistochemically investigated with endothelial marker CD34 and VEGF antibodies, stratified in a total of 4383 analysis units and computationally assessed for VEGF expression and vascular parameters (vessel density, vessel quantity, vascular fraction within tissue [vascular area ratio], vessel wall thickness). Derivability of kinetic parameters from VEGF expression or microvascularization was determined by mixed linear regression analysis. Tissue kinetic and microvascular parameters were tested for their capacity to identify the radiation status in a subanalysis.

RESULTS

Kinetic parameters were neither significantly related to the corresponding microvascular parameters nor to tissue VEGF expression. There was no significant association between microvessel density and its presumed correlate v_p (P=0.07). The subgroup analysis of high-grade radiated meningiomas showed a significantly reduced microvascular density (AUC 0.91; P<0.0001) and smaller total vascular fraction (AUC 0.73; P=0.01).

CONCLUSIONS

In meningioma, DCE-MRI kinetic parameters neither allow for a reliable prediction of tumor microvascularization, nor for a prediction of VEGF expression. Kinetic parameters seem to be determined from different independent factors.