Background: This study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases. Methods: A retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC_50Hz and ADC_0Hz), we generated maps of the ADC change (cADC): ADC_50Hz − ADC_0Hz and the relative ADC change (rcADC): (ADC_50Hz − ADC_0Hz)/ ADC_0Hz × 100 (%). Results: The mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC_0Hz and ADC_50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10⁻³mm²/s vs. 0.14 ± 0.03 × 10⁻³mm²/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC_0Hz^5th (0.595; all p < 0.001). Conclusions: The time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (v_e), blood plasma volume per unit volume of tissue (v_p), volume transfer constant between blood plasma and EES (K^trans), and rate constant between EES and blood plasma (k_ep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), v_e (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and K^trans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between v_e and PCC (r = 0.601, p < 0.01). The v_e derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

BACKGROUND AND PURPOSE: DWI with conventional single-shot EPI of the pituitary gland is hampered by strong susceptibility artifacts. Our purpose was to evaluate the feasibility of intravoxel incoherent motion assessment by using DWI based on TSE of the normal anterior pituitary lobe. MATERIALS AND METHODS: The intravoxel incoherent motion parameters, including the true diffusion coefficient (D), the perfusion fraction (f), and the pseudo-diffusion coefficient (D*), were obtained with TSE-DWI in 5 brain regions (the pons, the WM and GM of the vermis, and the genu and splenium of the corpus callosum) in 8 healthy volunteers, and their agreement with those obtained with EPI-DWI was evaluated by using the intraclass correlation coefficient. The 3 intravoxel incoherent motion parameters in the anterior pituitary lobe were compared with those in the brain regions by using the Dunnett test. RESULTS: The agreement between TSE-DWI and EPI-DWI was moderate (intraclass correlation coefficient = 0.571) for D, substantial (0.699) for f', but fair (0.405) for D*. D in the anterior pituitary lobe was significantly higher than in the 5 brain regions (P < .001). The f in the anterior pituitary lobe was significantly higher than in the 5 brain regions (P < .001), except for the vermian GM. The pituitary D* was not significantly different from that in the 5 brain regions. CONCLUSIONS: Our results demonstrated the feasibility of intravoxel incoherent motion assessment of the normal anterior pituitary lobe by using TSE-DWI. High D and f values in the anterior pituitary lobe were thought to reflect its microstructural and perfusion characteristics.