In Vivo Detection of EGFRvIII in Glioblastoma via Perfusion Magnetic Resonance Imaging Signature Consistent with Deep Peritumoral Infiltration: The ϕ-Index

Abstract

PURPOSE The epidermal growth factor receptor variant III (EGFRvIII) mutation has been considered a driver mutation and therapeutic target in glioblastoma, the most common and aggressive brain cancer. Currently, detecting EGFRvIII requires postoperative tissue analyses, which are ex vivo and unable to capture the tumor’s spatial heterogeneity. Considering the increasing evidence of in vivo imaging signatures capturing molecular characteristics of cancer, this study aims to detect EGFRvIII in primary glioblastoma non-invasively, using routine clinically-acquired imaging. EXPERIMENTAL DESIGN We found peritumoral infiltration and vascularization patterns being related to EGFRvIII status. We therefore constructed a quantitative within-patient peritumoral heterogeneity index (PHI/φ-index), by contrasting perfusion patterns of immediate and distant peritumoral edema. Application of φ-index in preoperative perfusion scans of independent discovery (n=64) and validation (n=78) cohorts, revealed the generalizability of this EGFRvIII imaging signature. RESULTS Analysis in both cohorts demonstrated that the obtained signature is highly accurate (89.92%), specific (92.35%) and sensitive (83.77%), with significantly distinctive ability (p=4.0033×10−10, AUC=0.8869). Findings indicated a highly infiltrative-migratory phenotype for EGFRvIII+ tumors, which displayed similar perfusion patterns throughout peritumoral edema. Contrarily, EGFRvIII− tumors displayed perfusion dynamics consistent with peritumorally-confined vascularization, suggesting potential benefit from extensive peritumoral resection/radiation. CONCLUSIONS This EGFRvIII signature is potentially suitable for clinical translation, since obtained from analysis of clinically-acquired images. Use of within-patient heterogeneity measures, rather than population-based associations, renders φ-index potentially resistant to inter-scanner variations. Overall, our findings enable non-invasive evaluation of EGFRvIII for patient selection for targeted therapy, stratification into clinical trials, personalized treatment planning, and potentially treatment-response evaluation.

Advanced Magnetic Resonance Imaging in Glioblastoma: A Review

“…17 Dynamic susceptibility contrast (DSC) MR imaging may be helpful in preoperative diagnosis 18 of malignant lesions. Imaging features extracted from standard and advanced preoperative MR sequences can predict survival, molecular subtype, and mutational status in glioblastoma, 19,20 potentially enhancing the set of imaging biomarkers available to clinicians.…”

Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma

“…5). Its accuracy (89.92%), specificity (92.53%), sensitivity (83.77%), as well as its independent sample repeatability (Intra-class Correlation Coefficient (ICC) = 0.825) and reproducibility (ICC = 0.775), supports its potential routine clinical use [6, 7, 10]. Such signatures contribute to personalized medicine, and can enable non-invasive patient selection for targeted therapy, stratification into clinical trials, and repeatable monitoring of mutations during the treatment course.…”

“…Extensive literature over the past decade has shown that rich panels of quantitative imaging features can result in non-invasive imaging signatures with diagnostic, prognostic and predictive value for many types of cancer, such as lung [38, 39], neck [38] and brain [2, 6–10, 40–43]. Specifically, these features have shown evidence of imaging signatures relating to underlying molecular characteristics, treatment response, patient survival, with the potential of augmenting conventional prognostic and predictive assays.…”

“…The principal component features of temporal perfusion dynamics have been related to recurrence and infiltration [24, 42], as well as molecular characteristics [6, 7, 10, 44]. Furthermore, the textural features available in brain-CaPTk capture characteristics of the local micro-architecture of tissue and have already demonstrated predictive and prognostic value [9, 38, 41, 44, 45].…”

“…The specific mutations that have been assessed so far comprise the splice variant III (EGFRvIII) [6, 10] and the amplification of the wild-type EGFR [7]. This marker requires the annotation of two regions; one near and another far from the enhancing tumor, but still within the peritumoral edema depicted by the abnormal T2-FLAIR signal.…”