Texture Analysis of High b-Value Diffusion-Weighted Imaging for Evaluating Consistency of Pituitary Macroadenomas

Background Preoperative evaluation of the consistency of pituitary macroadenomas is important for neurosurgeons to prepare the surgical plan. Purpose To evaluate the diagnostic performance of texture analysis (TA) of diffusion-weighted imaging (DWI) at a standard b-value (b = 1000 s/mm(2)) and a high b-value (b = 2000 s/mm(2)) for their ability to assess the tumor consistency of pituitary macroadenomas. Study Type Retrospective. Population/Subjects Fifty patients with histologically confirmed pituitary macroadenomas were classified as soft (n = 37) or hard (n = 13) types. Field Strength/Sequence Coronal T-2-weighted imaging (T2WI), Readout Segmentation of Long Variable Echo-trains (RESOLVE) DWI at b = 1000 s/mm(2) and b = 2000 s/mm(2) were acquired with 3.0T MRI. Assessment The corresponding apparent diffusion coefficient (ADC) maps (ADC(1000) and ADC(2000)) were registered to T2WI. Regions of interest (ROIs) were manually drawn along the solid part of the tumor from the coregistered T2WI-ADC images. The texture parameters from T2WI, ADC(1000), and ADC(2000) were acquired. Statistical Tests The texture parameters were compared between the two types by using unpaired Student's t-test. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to assess their diagnostic performance. Results Significant differences in TA parameters of ADC(1000) and ADC(2000) were observed between soft and hard types (P < 0.05 for all), whereas the TA of T2WI resulted in no significant difference (P > 0.05 for all). TA of ADC(2000) provided a superior diagnostic performance compared with that of ADC(1000) (P = 0.038). A combination of mean value and entropy of ADC(2000) yielded an AUC, a sensitivity, and a specificity of 0.911, 78.4% and 92.3%, respectively. Data Conclusion TA of ADC values were useful for assessing the tumor consistency of pituitary macroadenomas. ADC(2000) may facilitate better type discrimination. Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.