Sub-differentiation of PI-RADS 3 lesions in TZ by advanced diffusion-weighted imaging to aid the biopsy decision process.

Background: Performing biopsy for intermediate lesions with PI-RADS 3 has always been controversial. Moreover, it is difficult to differentiate prostate cancer (PCa) and benign prostatic hyperplasia (BPH) nodules in PI-RADS 3 lesions by conventional scans, especially for transition zone (TZ) lesions. The purpose of this study is sub-differentiation of transition zone (TZ) PI-RADS 3 lesions using intravoxel incoherent motion (IVIM), stretched exponential model, and diffusion kurtosis imaging (DKI) to aid the biopsy decision process. Methods: A total of 198 TZ PI-RADS 3 lesions were included. 149 lesions were BPH, while 49 lesions were PCa, including 37 non-clinical significant PCa (non-csPCa) lesions and 12 clinical significant PCa (csPCa) lesions. Binary logistic regression analysis was used to examine which parameters could predict PCa in TZ PI-RADS 3 lesions. The ROC curve was used to test diagnostic efficiency in distinguishing PCa from TZ PI-RADS 3 lesions, while one-way ANOVA analysis was used to examine which parameters were statistically significant among BPH, non-csPCa and csPCa. Results: The logistic model was statistically significant (χ2 = 181.410, p<0.001) and could correctly classify 89.39% of the subjects. Parameters of fractional anisotropy (FA) (p=0.004), mean diffusion (MD) (p=0.005), mean kurtosis (MK) (p=0.015), diffusion coefficient (D) (p=0.001), and distribute diffusion coefficient (DDC) (p=0.038) were statistically significant in the model. ROC analysis showed that AUC was 0.9197 (CI 95%: 0.8736-0.9659). Sensitivity, specificity, positive predictive value and negative predictive value were 92.1%, 80.4%, 93.9% and 75.5%, respectively. FA and MK of csPCa were higher than those of non-csPCa (all p<0.05), while MD, ADC, D, and DDC of csPCa were lower than those of non-csPCa (all p<0.05). Conclusion: FA, MD, MK, D, and DDC can predict PCa in TZ PI-RADS 3 lesions and inform the decision-making process of whether or not to perform a biopsy. Moreover, FA, MD, MK, D, DDC, and ADC may have ability to identify csPCa and non-csPCa in TZ PI-RADS 3 lesions.

In Vivo Assessment of Neurodegeneration in Type C Niemann-Pick Disease by IDEAL-IQ.

Objective: To noninvasively assess the neurodegenerative changes in the brain of patients with Niemann-Pick type C (NPC) disease by measuring the lesion tissue with the iterative decomposition of water and fat with echo asymmetry and least square estimation-iron quantification (IDEAL-IQ). Materials and Methods: Routine brain MRI, IDEAL-IQ and 1H-proton magnetic resonance spectroscopy (1H-MRS, served as control) were performed on 12 patients with type C Niemann-Pick disease (4 males and 8 females; age range, 15-61 years; mean age, 36 years) and 20 healthy subjects (10 males and 10 females; age range, 20-65 years; mean age, 38 years). The regions with lesion and the normal appearing regions (NARs) of patients were measured and analyzed based on the fat/water signal intensity on IDEAL-IQ and the lipid peak on 1H-MRS. Results: Niemann-Pick type C patients showed a higher fat/water signal intensity ratio with IDEAL-IQ on T2 hyperintensity lesions and NARs (3.7-4.9%, p < 0.05 and 1.8-3.0%, p < 0.05, respectively), as compared to healthy controls (HCs) (1.2-2.3%). After treatment, the fat/water signal intensity ratio decreased (2.2-3.4%), but remained higher than in the HCs (p < 0.05). The results of the 1H-MRS measurements showed increased lipid peaks in the same lesion regions, and the micro-lipid storage disorder of NARs in NPC patients was detectable by IDEAL-IQ instead of 1H-MRS. Conclusion: The findings of this study suggested that IDEAL-IQ may be useful as a noninvasive and objective method in the evaluation of patients with NPC; additionally, IDEAL-IQ can be used to quantitatively measure the brain parenchymal adipose content and monitor patient follow-up after treatment of NPC.

[Application of 3D FIESTA sequence in magnetic resonance sialography for obstructive salivary diseases].

OBJECTIVE: To investigate the value of 3D FIESTA sequence in magnetic resonance sialography (MRS) in the diagnosis of obstructive salivary diseases. METHODS: Eleven patients with obstructive salivary diseases underwent MRS, and three-dimensional (3D) reconstruction and virtual endoscopic images of the salivary gland ducts were obtained after MRS data post-processing for comparison with those of sialoendoscopy. RESULTS: The diagnostic accuracy of MRS was 72.7% for obstructive salivary diseases. The virtual endoscopy provided a visual field highly consistent with that by sialoendoscopy. CONCLUSION: MRS is capable of visualizing the tracts of salivary glands. MR virtual endoscopy can provide sufficient morphological and pathological data for preoperative assessment of salivary operations with sialoendoscopy.