First-Order Histogram Features For Categorizing Functional Vs. Non-Functional Pituitary Macro-Adenoma And Tumor Consistency


1 Shahidbeheshti university of Medical Sciences

2 shahid beheshti university of medical sciences

3 Quantitative MR Imaging and Spectroscopy Group (QMISG), Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences

4 Department of Pathology, Shahid Beheshti University of Medical Sciences


To investigate first-order histogram (FOH) features for prediction of pituitary adenoma consistency in combination with pathological results as well as to differentiate functional vs. non-functional tumors.
 Materials and Methods:
 MR imaging was done using the standard protocols of T1-weighted with and without contrast, T2-weighted, and axial fluid attenuated inversion recovery images in 32 patients with pituitary macro-adenoma. Regions of interest (ROI) and apparent diffusion coefficient (ADC) maps were generated and FOH features were extracted. Collagen contents of the surgically resected tumors were examined histochemically using Masson trichromatic staining and were graded as <1%, 1-3%, and > 3%. Microscopic photographs, in three random regions, were analyzed using the online software. Non-parametric statistics and receiver-operator characteristic (ROC) curves were statistical methods with 95% confidence interval.
 FOH features obtained for 21 (65.6%) males and 11 (34.4%) females. Only uniformity (P=0.02), 75th percentile (P=0.03), and tumor smoothness (P=0.02) were different significantly between functional and non-functional tumors. Tumor smoothness > 5.7×10-9 (AUC= 0.752) had at least 80% sensitivity and 76.19% specificity for diagnosis of functional tumors. Uniformity ≤ 179.271 had a sensitivity of 60% and specificity of 90.48% (AUC=0.757) and 75th percentile >0.7 had a sensitivity of 80% and specificity of 66.67% for categorizing tumors to functional and non-functional types (AUC= 0.738).
 FOH features could be helpful in differentiating functional vs. non-functional pituitary macro-adenoma. FOH features were not meaningfully different for semi-quantitative collagen content. We have proposed some cutoffs for some valuable FOH features, which may be used in clinical settings.