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Background: Thyroid carcinomas represent the most frequent endocrine malignancies. Recent studies were able to distinguish malignant from benign nodules of the thyroid gland with diffusion-weighted imaging (DWI). Although this differentiation is undoubtedly helpful, presurgical discrimination between well-differentiated and undifferentiated carcinomas would be crucial to define the optimal treatment algorithm. Therefore, the aim of this study was to investigate if readout-segmented multishot echo planar DWI is able to differentiate between differentiated and undifferentiated subtypes of thyroid carcinomas., Patients and Methods: Fourteen patients with different types of thyroid carcinomas who received preoperative DWI were included in our study. In all lesions, apparent diffusion coefficient (ADC)min, ADCmean, ADCmax, and D were estimated on the basis of region of interest measurements after coregistration with T1-weighted, postcontrast images. All tumors were resected and analyzed histopathologically. Ki-67 index, p53 synthesis, cellularity, and total and average nucleic areas were estimated using ImageJ version 1.48., Results: Analysis of variance revealed a statistically significant difference in ADCmean values between differentiated and undifferentiated thyroid carcinomas (P=.022). Spearman Rho calculation identified significant correlations between ADCmax and cell count (r=0.541, P=.046) as well as between ADCmax and total nuclei area (r=0.605, P=.022)., Conclusion: DWI can distinguish between differentiated and undifferentiated thyroid carcinomas., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Identification of high-grade meningiomas in preoperative magnetic resonance imaging (MRI) is important for optimized surgical strategy and best possible resection. Numerous studies investigated subjectively determined morphological features as predictors of tumor biology in meningiomas. The aim of this study was to identify the predictive value of more reliable, quantitatively measured signal intensities in MRI for differentiation of high- and low-grade meningiomas and identification of meningiomas with high proliferation rates, respectively., Patients and Methods: Sixty-six patients (56 World Health Organization [WHO] grade I, 9 WHO grade II, and 1 WHO grade I) were included in the study. Preoperative MRI signal intensities (fluid-attenuated inversion recovery [FLAIR], T1 precontrast, and T1 postcontrast as genuine and normalized values) were correlated with Ki-67 expression in tissue sections of resected meningiomas. Differences between the groups (analysis of variance) and Spearman rho correlation were computed using SPSS 22., Results: Mean values of genuine signal intensities of meningiomas in FLAIR, T1 native, and T1 postcontrast were 323.9 ± 59, 332.8 ± 67.9, and 768.5 ± 165.3. Mean values of normalized (to the contralateral white matter) signal intensities of meningiomas in FLAIR, T1 native, and T1 postcontrast were 1.5 ± 0.3, 0.8 ± 0.1, and 1.9 ± 0.4. There was no significant correlation between MRI signal intensities and WHO grade or Ki-67 expression. Signal intensities did not differ significantly between WHO grade I and II/III meningiomas. Ki-67 expression was significantly increased in high-grade meningiomas compared with low-grade meningiomas (P < 0.01). Objectively measured values of MRI signal intensities (FLAIR, T1 precontrast, and T1 postcontrast enhancement) did not distinguish between high-grade and low-grade meningiomas. Furthermore, there was no association between MRI signal intensities and Ki-67 expression representing proliferative activity., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)