Differentiating Enhancing Multiple Sclerosis Lesions, Glioblastoma, and Lymphoma with Dynamic Texture Parameters Analysis (DTPA) - a Feasibility Study.

PURPOSE MR-imaging hallmarks of glioblastoma (GB), cerebral lymphoma (CL), and demyelinating lesions are gadolinium (Gd) uptake due to blood brain barrier disruption. Thus, initial diagnosis may be difficult based on conventional Gd enhanced MRI alone. Here, the added value of a dynamic texture parameter analysis (DTPA) in the differentiation between these three entities is examined. DTPA is an in-house software tool that incorporates the analysis of quantitative texture parameters extracted from dynamic susceptibility contrast enhanced (DSCE) images. METHODS Twelve patients with multiple sclerosis (MS), fifteen patients with GB, and five patients with CL were included. The image analysis method focuses on the DSCE-image time series during bolus passage. Three time intervals were examined: inflow, outflow, and reperfusion time interval. Texture maps were computed. From the DSCE image series mean, difference, standard deviation, and variance texture parameters were calculated and statistically analyzed and compared between the pathologies. RESULTS The texture parameters of the original DSCE-image series for mean, standard deviation and variance showed the most significant differences (p-value between <0.00 and 0.05) between pathologies. Further, the texture parameters related to the standard deviation or variance (both associated with tissue heterogeneity) revealed the strongest discriminations between the pathologies. CONCLUSION We conclude that dynamic perfusion texture parameters as assessed by the DTPA-method allow discriminating MS-, GB- and CL-lesions during the first passage of contrast. DTPA used in combination with classification algorithms have the potential to find the most likely diagnosis given a postulated differential diagnosis. This article is protected by copyright. All rights reserved

Glucose Metabolism and Its Complicated Relationship with Tumor Growth and Perfusion in Head and Neck Squamous Cell Carcinoma

Objective: To determine the relationship between tumor glucose metabolism and tumor blood flow (TBF) in head and neck squamous cell carcinoma (HNSCC). Methods: We retrospectively analyzed 57 HNSCC patients. Tumor glucose metabolism was assessed by maximum and mean standardized uptake values (SUVmax and SUVmean) obtained by 18F-fluorodeoxyglucose positron-emission tomography. TBF values were obtained by arterial spin labeling with 3-tesla MRI. The correlations between both SUVs and TBF were assessed in the total series and among patients divided by T-stage (T1-T3 and T4 groups) and tumor location (pharynx/oral cavity and sinonasal cavity groups). Pearson's correlation coefficients were calculated for significant correlations. Results: Significant correlations were detected: a negative correlation in the advanced T-stage group (TBF and SUV max: r, -0.61, SUVmean: r, -0.62), a positive correlation in the non-advanced T-stage pharynx/oral cavity group (TBF and SUVmax: r, 0.70, SUVmean: r, 0.73), a negative correlation in the advanced T-stage pharynx/oral cavity group (TBF and SUVmax: r, -0.62, SUVmean: r, -0.65), and a negative correlation in the advanced Tstage sinonasal cavity group (TBF and SUVmax: r, -0.61, SUVmean: r, -0.65). Conclusion: Significant correlations between glucose uptake and TBF in HNSCC were revealed by the division of T-stage and tumor location