Abstract

The purpose of this study is to evaluate the accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness using histogram apparent diffusion coefficient values. Eighteen patients with surgically proved pituitary macroadenomas were included in this study. Diffusion-weighted imaging with single-shot echo-planar sequence at 3-T with a 32-channel head coil was performed with b values of 0 and 1000 s/mm2. Calculated apparent diffusion coefficient maps were generated, and a 3-D volume of interest was placed on the tumor while superimposing contrast-enhanced magnetic resonance images. All apparent diffusion coefficient values within the volume of interest were used to compute the average apparent diffusion coefficient of the tumor. The apparent diffusion coefficient values were binned to construct the apparent diffusion coefficient histogram. Using the histogram, the mean, percentiles, skewness, and kurtosis of the apparent diffusion coefficient of the entire tumor were computed. Apparent diffusion coefficient histogram parameters were compared with the MIB-1 index, invasiveness, and recurrence for grading tumor aggressiveness of pituitary adenomas. The skewness of the apparent diffusion coefficient histogram only showed significant differences among MIB-1 indices ( p = 0.030). All apparent diffusion coefficient histogram parameters showed no significant differences between negative and positive invasion. The skewness and kurtosis of the apparent diffusion coefficient histogram showed significant differences between positive and negative recurrence (skewness p = 0.011, kurtosis p = 0.011). Receiver-operating characteristics analysis between positive and negative recurrence showed that both skewness and kurtosis of the apparent diffusion coefficient achieved area under the curve at 0.967. Skewness and kurtosis of the apparent diffusion coefficient histogram were the predictive parameters for assessing tumor proliferative potential and recurrence of pituitary adenomas.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.