Fractal Dimension and Lacunarity Measures of Glioma Subcomponents Provide a Quantitative Platform Discriminative of IDH Status: A Radiogenomics Approach in Gliomas

Background The presence of structural and geometric variations within gliomas, even among those with similar histologic grades, reflects the phenotypic heterogeneity unique to a genetic and epigenetic landscape. Whole glioma mass comprises of various subcomponents identified on MR imaging: enhancing, nonenhancing, necrosis, and edema fractions in varied fractions across patients. The geometry of whole tumor mass and the glioma subcomponents is highly irregular. Thereby, traditional Euclidean geometry is not suitable for quantifying the geometric dimensions. Here, we employ non-Euclidean geometric measurements: Fractal Dimension and lacunarity of the glioma subcomponents as a discriminator of IDH and MGMT status of gliomas. Methods Fractality and Lacunarity measurements were obtained using the tumor masks generated for enhancing, nonenhancing, and edema subcomponents from the preoperative T1, T1c, and T2-Flair MRI. Fractality and lacunarity measures of each subcomponent were evaluated between IDH mutant and wildtype gliomas. The fractality and lacunarity measures in IDH mutant and wildtype gliomas were further stratified for MGMT methylated and unmethylated gliomas. The fractality and lacunarities were trained and tested using supervised ML modeling as discriminators of IDH and MGMT status. Further, Cox Hazard estimations and the Kaplan-Meir investigations were performed to evaluate the impact of fractality and lacunarity measures of glioma subcomponents on the overall survival of the patients. Results IDH wildtype gliomas had ∼2-fold higher fractality for the enhancing subcomponent compared to IDH mutant enhancing subcomponent, while IDH mutant gliomas showed higher fractality for the nonenhancing subcomponent. Furthermore, the edema subcomponent did not differ for fractality or lacunarity measures between IDH mutant and wildtype gliomas. Fractal or lacunarity measures for either of the three subcomponents do not vary across MGMT methylated and unmethylated status with a given IDH mutant or wildtype gliomas. A combination of fractal measures of the enhancing and nonenhancing subcomponents together provided highly accurate and sensitive discrimination of IDH status using the supervised ML models. Moreover, fractality measure ≥ 0.69 for the enhancing subcomponent was associated with shortened patient survival: a fractal dimension value corresponding to that of IDH wild type gliomas. However, fractality and lacunarity estimates were not sensitive for discrimination of MGMT status. Conclusion Glioma structural heterogeneity measured as fractality and lacunarity using routine structural MRI measurements provide a noninvasive quantitative platform definitive of the molecular subtype of gliomas: IDH mutant vs. wildtype. Establishing fractality and/or lacunarity quantities as signatures of prognostic molecular events provides an avenue to bypass the need of biopsy/surgical interventions for decision-making, determining the molecular subtypes and overall clinical management of gliomas. Importance of the Study The non-Euclidean geometric measurements such as fractal dimension and lacunarity of enhancing, nonenhancing, and edema subcomponents are potentially unique quantitative metrics, discriminative of IDH status and patient survival. Fractality and Lacunarity estimates using the conventional structural MRI (T1w, T1C, T2, and T2F) provide an easy-to-use quantitative radiogenomics platform for improved clinical decisions, bypassing the need for immediate surgical interventions to ascertain prognostic molecular markers in gliomas, which is likely to improve overall clinical management and outcomes. Key Points Increased fractal dimensions of the enhancing subcomponents in IDH wildtype tumors, suggestive of highly irregular geometry, may potentially serve as a quantitative noninvasive determinant of IDH wildtype tumors. A combined fractal estimation of enhancing and nonenhancing subcomponents is the optimal and accurate discriminator of IDH mutant vs. wildtype. High fractal dimension of enhancing subcomponent and reduced fractality of nonenhancing subcomponent is predictive of shortened patient survival.