Purpose:The feasibility of steady-state sequences for 17O imaging was evaluated based on a kinetic analysis of the brain parenchyma and cerebrospinal fluid (CSF).Materials and Methods:The institutional review board approved this prospective study with written informed consent. Dynamic 2D or 3D steady-state sequences were performed in five and nine participants, respectively, with different parameters using a 3T scanner. During two consecutive dynamic scans, saline was intravenously administered for control purposes in the first scan, and 20% 17O-labeled water (1 mL/Kg) was administered in the second scan. Signal changes relative to the baseline were calculated, and kinetic analyses of the curves were conducted for all voxels. Region of interest analysis was performed in the brain parenchyma, choroid plexus, and CSF spaces.Results:Average signal drops were significantly larger in the 17O group than in the controls for most of the imaging parameters. Different kinetic parameters were observed between the brain parenchyma and CSF spaces. Average and maximum signal drops were significantly larger in the CSF spaces and choroid plexus than in the brain parenchyma. Bolus arrival, time to peak, and the first moment of dynamic curves of 17O in the CSF space were delayed compared to that in the brain parenchyma. Significant differences between the ventricle and subarachnoid space were also noted.Conclusion:Steady-state sequences are feasible for indirect 17O imaging with reasonable temporal resolution; this result is potentially important for the analysis of water kinetics and aquaporin function for several disorders.

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1373-1379.

BackgroundTo assess the utility of histogram and texture analysis of magnetic resonance (MR) fat-suppressed T2-weighted imaging (Fs-T2WI) for the prediction of histological diagnosis of head and neck squamous cell carcinoma (SCC) and malignant lymphoma (ML).MethodsThe cases of 57 patients with SCC (45 well/moderately and 12 poorly differentiated SCC) and 10 patients with ML were retrospectively analyzed. Quantitative parameters with histogram features (relative mean signal, coefficient of variation, kurtosis and skewness) and gray-level co-occurrence matrix (GLCM) features (contrast, correlation, energy and homogeneity) were calculated using Fs-T2WI data with a manual tumor region of interest (ROI).ResultsThe following significantly different values were obtained for the total SCC versus ML groups: relative mean signal (3.65 ± 0.86 vs. 2.61 ± 0.49), contrast (72.9 ± 16.2 vs. 49.3 ± 8.7) and homogeneity (2.22 ± 0.25 × 10− 1 vs. 2.53 ± 0.12 × 10− 1). In the comparison of the SCC histological grades, the relative mean signal and contrast were significantly lower in the poorly differentiated SCC (2.89 ± 0.63, 56.2 ± 12.9) compared to the well/moderately SCC (3.85 ± 0.81, 77.5 ± 13.9). The homogeneity in poorly differentiated SCC (2.56 ± 0.15 × 10− 1) was higher than that of the well/moderately SCC (2.1 ± 0.18 × 10− 1).ConclusionsParameters obtained by histogram and texture analysis of Fs-T2WI may be useful for noninvasive prediction of histological type and grade in head and neck malignancy.

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BackgroundTo clarify the relationship between the probability of prostate cancer scaled using a 5-point Likert system and the biological characteristics of corresponding tumor foci.MethodsThe present study involved 44 patients undergoing 3.0-Tesla multiparametric MRI before laparoscopic radical prostatectomy. Tracing based on pathological and MRI findings was performed. The relationship between the probability of cancer scaled using the 5-point Likert system and the biological characteristics of corresponding tumor foci was evaluated.ResultsA total of 102 tumor foci were identified histologically from the 44 specimens. Of the 102 tumors, 55 were assigned a score based on MRI findings (score 1: n = 3; score 2: n = 3; score 3: n = 16; score 4: n = 11 score 5: n = 22), while 47 were not pointed out on MRI. The tracing study revealed that the proportion of >0.5 cm3 tumors increased according to the upgrade of Likert scores (score 1 or 2: 33 %; score 3: 68.8 %; score 4 or 5: 90.9 %, χ2 test, p < 0.0001). The proportion with a Gleason score >7 also increased from scale 2 to scale 5 (scale 2: 0 %; scale 3: 56.3 %; scale 4: 72.7 %; 5: 90.9 %, χ2 test, p = 0.0001). On using score 3 or higher as the threshold of cancer detection on MRI, the detection rate markedly improved if the tumor volume exceeded 0.5 cm3 (<0.2 cm3: 10.3 %; 0.2-0.5 cm3: 25 %; 0.5-1.0 cm3: 66.7 %; 1.0 < cm3: 92.1 %).ConclusionsEach Likert scale favobably reflected the corresponding tumor’s volume and Gleason score. Our observations show that “score 3 or higher” could be a useful threshold to predict clinically significant carcinoma when considering treatment options.