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

Abstract

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. Diffusion-weighted imaging magnetic resonance imaging was performed on 32 patients (age mean±standard deviation = 43.09 ± 11.02 years; min = 22 and max = 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. Among selected first or second-order histogram features, uniformity ( p = 0.02), 75th percentile ( p = 0.03), and tumor smoothness ( p = 0.02) were significantly different between functional and non-functional tumors. Tumor smoothness > 5.7 × 10-9 (area under the curve = 0.75; 0.56-0.89) had 70% (95% confidence interval = 34.8-93.3%) sensitivity and 33.33% (95% confidence interval = 14.6-57.0%) specificity for diagnosis of functional tumors. Uniformity ≤179.271 had a sensitivity of 60% (95% confidence interval = 26.2-87.8%) and specificity of 90.48% (95% confidence interval = 69.6-98.8%) with area under the curve = 0.76; 0.57-0.89. The 75th percentile >0.7 had a sensitivity of 80% (95% confidence interval = 44.4-97.5%) and specificity of 66.67% (95% confidence interval = 43.0-85.4%) for categorizing tumors to functional and non-functional types (area under the curve = 0.74; 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. First or second-order histogram features could be helpful in differentiating functional vs non-functional pituitary macro-adenoma tumors.