The purpose of this study was to determine the accuracy of selected first or second-order histogram features in differentiation of functional types of pituitary macro-adenomas. Materials and methods: Diffusion-weighted imaging magnetic resonance imaging was performed on 32 patients (age meanAEstandard deviation ¼ 43.09 AE 11.02 years; min ¼ 22 and max ¼ 65 years) with pituitary macro-adenoma (10 with functional and 22 with non-functional tumors). Histograms of apparent diffusion coefficient were generated from regions of interest and selected first or second-order histogram features were extracted. Collagen contents of the surgically resected tumors were examined histochemically using Masson trichromatic staining and graded as containing <1%, 1-3%, and >3% of collagen. Results: Among selected first or second-order histogram features, uniformity (p ¼ 0.02), 75th percentile (p ¼ 0.03), and tumor smoothness (p ¼ 0.02) were significantly different between functional and non-functional tumors. Tumor smoothness > 5.7 Â 10 À9 (area under the curve ¼ 0.75; 0.56-0.89) had 70% (95% confidence interval ¼ 34.8-93.3%) sensitivity and 33.33% (95% confidence interval ¼ 14.6-57.0%) specificity for diagnosis of functional tumors. Uniformity 179.271 had a sensitivity of 60% (95% confidence interval ¼ 26.2-87.8%) and specificity of 90.48% (95% confidence interval ¼ 69.6-98.8%) with area under the curve ¼ 0.76; 0.57-0.89. The 75th percentile >0.7 had a sensitivity of 80% (95% confidence interval ¼ 44.4-97.5%) and specificity of 66.67% (95% confidence interval ¼ 43.0-85.4%) for categorizing tumors to functional and non-functional types (area under the curve ¼ 0.74; 0.55-0.88). Using these cutoffs , smoothness and uniformity are suggested as negative predictive indices (non-functional tumors) whereas 75th percentile is more applicable for diagnosis of functional tumors. Conclusion: First or second-order histogram features could be helpful in differentiating functional vs non-functional pituitary macro-adenoma tumors.

Purpose The purpose of this study was to differentiate glioblastoma multiforme from primary central nervous system lymphoma using the customised first and second-order histogram features derived from apparent diffusion coefficients. Methods and materials: A total of 82 patients (57 with glioblastoma multiforme and 25 with primary central nervous system lymphoma) were included in this study. The axial T1 post-contrast and fluid-attenuated inversion recovery magnetic resonance images were used to delineate regions of interest for the tumour and peritumoral oedema. The regions of interest were then co-registered with the apparent diffusion coefficient maps, and the first and second-order histogram features were extracted and compared between glioblastoma multiforme and primary central nervous system lymphoma groups. Receiver operating characteristic curve analysis was performed to calculate a cut-off value and its sensitivity and specificity to differentiate glioblastoma multiforme from primary central nervous system lymphoma. Results Based on the tumour regions of interest, apparent diffusion coefficient mean, maximum, median, uniformity and entropy were higher in the glioblastoma multiforme group than the primary central nervous system lymphoma group ( P ≤ 0.001). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the maximum of 2.026 or less (95% confidence interval (CI) 75.1–99.9%), and the most specific first and second-order histogram feature was smoothness of 1.28 or greater (84.0% CI 70.9–92.8%). Based on the oedema regions of interest, most of the first and second-order histogram features were higher in the glioblastoma multiforme group compared to the primary central nervous system lymphoma group ( P ≤ 0.015). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the 25th percentile of 0.675 or less (100% CI 83.2–100%) and the most specific first and second-order histogram feature was the median of 1.28 or less (85.9% CI 66.3–95.8%). Conclusions Texture analysis using first and second-order histogram features derived from apparent diffusion coefficient maps may be helpful in differentiating glioblastoma multiforme from primary central nervous system lymphoma.

Introduction: Lymphomas comprise a diverse group of neoplasms derived from B cells, T cells, or NK cells. Although GI tract is a current site for the secondry spread of non-hodgkin lymphoma, it's involvment as the primary site is less common noticeably showing only 10% -15%. The more lymphoid tissue is in parts of small intestine, the more incidence of lymphoma is depicted; thus, as expected, ileocecal region is the most frequent site and the duodenum remains as the most infrequent site. Case Report: An 18-year-old woman with no pervious history of any disease was admitted to the emergency room of Shohaday-eTajrish hospital that is a tertiary hospital in Tehran, Iran. The patient presented with weakness, nausea, and retractile vomiting. The CT scan was performed, showing that stomach and proximal of duodenum were dilated significantly and wall thickening of duodenum, 2nd and 3rd portions, was obvious. No pathological lymph node or invasion to adjacent organs was seen. The patient was explored; operation findings were dilatation of stomach and duodenum; thickening of duodenojejunal junction with 10 cm extension was mentioned. Biopsied tissue during operation showed diffuse large B cell lymphoma. Conclusions: Duodenal lymphoma is infrequent and it is rare to represent with obstruction. Thus, if there is any clinical indication and no definite diagnosis in such patient, biopsy and histopathological investigation is necessary after radiological studies.