Pituitary macroadenoma: Accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness

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. Materials and methods: 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/mm 2. 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. Results: The skewness of the apparent diffusion coefficient histogram only showed significant differences among MIB-1 indices (p ¼ 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 ¼ 0.011, kurtosis p ¼ 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. Conclusion: Skewness and kurtosis of the apparent diffusion coefficient histogram were the predictive parameters for assessing tumor proliferative potential and recurrence of pituitary adenomas.

Predicting the Consistency of Pituitary Macroadenomas: The Utility of Diffusion-Weighted Imaging and Apparent Diffusion Coefficient Measurements for Surgical Planning

“…On the other hand, the other imaging parameters, including DWI, T1W1, T2W1, and tumor morphology, did not exhibit statistically significant associations with tumor consistency. These results align with previous investigations that highlighted the utility of ADC in preoperatively predicting pituitary adenoma texture [ 26 , 28 , 31 , 32 ]. The high statistical significance of the ADC map in predicting macroadenoma consistency suggests its potential as a valuable imaging biomarker for the clinical assessment of these tumors.…”

Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences—An Updated Review

“…Another study successfully differentiated between functional and non-functional macroadenomas by analyzing ADC histogram features [174]. In addition, ADC histogram values (skewness and kurtosis) have been proven useful in predicting macroadenoma proliferative potential and recurrence after surgery [175].…”