Accuracy of diffusion-weighted imagingmagnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency

Morteza Sanei Taheri, Farnaz Kimia, Mersad Mehrnahad, Hamidreza Saligheh Rad, Hamidreza Haghighatkhah, Afshin Moradi, Anahita Fathi Kazerooni, Mohammadreza Alviri and Abdorrahim Absalan

Keywords

Pituitary adenoma, tumor consistency, apparent diffusion coefficient, magnetic resonance imaging

Abstract

Purpose: 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
meanstandard deviation¼43.0911.02 years; min¼22 and max¼65 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 (p¼0.02), 75th percentile (p¼0.03), and tumor smoothness (p¼0.02) were significantly different between functional and non-functional tumors. Tumor smoothness> 5.7109 (area under the curve¼0.75; 0.56–0.89) had 70% (95% confidence interval¼34.8–93.3%) sensitivity and 33.33% (95% confidence interval¼14.6–57.0%) specificity for diagnosis of functional tumors. Uniformity 179.271 had a sensitivity of 60% (95% confidence interval¼26.2–87.8%) and specificity of 90.48% (95% confidence interval¼69.6–98.8%) with area under the curve¼0.76; 0.57–0.89. The 75th percentile >0.7 had a sensitivity of 80% (95% confidence interval¼44.4–97.5%) and specificity of 66.67% (95% confidence interval¼43.0–85.4%) for categorizing tumors to functional and non-functional types (area under the curve¼0.74; 0.55–0.88). Using these cut-offs, 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.