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Accuracy of diffusion weighted imagingmagnetic resonance

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

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 Haghighatkhah1, Afshin Moradi, Anahita Fathi Kazerooni, Mohammadreza Alviri and Abdorrahim Absalan

 

journal

The Neuroradiology Journal

 

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 deviation ¼ 43.09  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  109 (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 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.

 

Keywords

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