The pathophysiology of psychiatric disorders is complex and cannot be easily assessed by laboratory studies. Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique increasingly used for noninvasive and quantitative evaluation of abnormalities of the cerebral white matter because it provides exquisite details on tissue microstructures and also can perform sophisticated computer-based analyses. We review basic principles of DTI; methods of diffusion tensor analysis; recent DTI findings in major psychiatric diseases, such as schizophrenia, bipolar disorder, major depressive disorder, and anxiety disorder; and factors to keep in mind when interpreting the results of DTI analysis. We recommend the frequent use of DTI as a routine clinical protocol to assess white matter abnormalities in patients with psychiatric disorders.
Since its launch onto the world medical market, gadoxetic acid has received a great deal of attention from a diverse group of researchers, including gastroenterologists, hepatologists, and abdominal radiologists. Gadoxetic acid in liver magnetic resonance (MR) imaging might be considered to have excellent utility. However, several issues remain that radiologists should keep in mind when utilizing this product. We compiled this review to introduce gadoxetic acid, describe how it should be used, highlight the situations in which it is most and least reliable, and suggest potential avenues for future research.
Purpose: Small loop surface coils are generally recommended for ocular magnetic resonance (MR) imaging, but the optimal coil setup has not been systematically investigated. In this phantom study, we investigated which coil setup of those coils available for our MR imaging system provides the highest signal-to-noise ratio (SNR) in ocular MR imaging at 1.5 tesla. Materials and Methods: Using a phantom to simulate the eyeball and the orbital fat, we employed loop surface coils of 4- and 6-cm diameter and a multi-channel head coil to obtain images using a T1-weighted spin-echo sequence and then measured the SNR for each coil and coil combination. Results: Use of the 6-cm loop coil alone yielded the highest mean SNR (27.5). Even in superficial regions (mesial and temporal), the SNR was higher using the 6-cm loop coil (33.6 and 45.5) than the 4-cm loop coil (28.0 and 33.8). Additional use of the head coil reduced the mean SNR to 10.4. Conclusion: This quantitative analysis suggests that use of a 6-cm loop surface coil offers the best results in ocular MR imaging. Combinations of loop coils or additional use of a head coil cannot be recommended because higher noise degrades image quality.
Purpose: We attempted to optimize scan parameters for T1-weighted fluid-attenuated inversion recovery (T1-FLAIR) sequence at 3 and 1.5 tesla (T) using computer simulation. Methods: We measured the T1 and T2 relaxation time values (T1v and T2v) of gray (GM) and white matter (WM) at 3 and 1.5T, generated computer-simulated T1-FLAIR (CS-T1-FLAIR) images using those values, and compared the simulated and actual T1-FLAIR images to verify the contrast reliability of our computer simulation. We mathematically and visually evaluated CS-T1-FLAIR images at various repetition times (TR) and echo times (TE). Results: At 3T, the measured relaxation values for GM were T1v, 1524 ms, and T2v, 85 ms, and for WM, T1v, 750 ms, and T2v, 65 ms. At 1.5T, the measured relaxation values for GM were T1v, 1251 ms, and T2v, 99 ms, and for WM, T1v, 623 ms, and T2v, 75 ms. Contrast of CS-T1-FLAIR and actual T1-FLAIR images was identical. An optimal TR of 3140 ms was determined for T1-FLAIR at 3T and 2440 ms at 1.5T based on mathematical evaluation. The optimal TR ranges were 2400 to 3900 ms at 3T and 1800 to 3200 ms at 1.5T based on visual assessment of CS-T1-FLAIR. A shorter TE provided better T1 contrast. Conclusion: We optimized T1-FLAIR by focusing on its most important scan parameters using computer simulations and determined that a longer TR was suitable at 3T than at 1.5T. Our computer simulation was useful for determining the optimal scan parameters.
Purpose: We investigated possible correlations between apparent diffusion coefficient (ADC) values and prognostic factors of breast cancer. Methods: We retrospectively evaluated 81 patients who underwent magnetic resonance (MR) imaging of the breast and were diagnosed pathologically with invasive ductal carcinoma (IDC) not otherwise specified with invasive foci one cm or larger. We excluded ductal carcinoma in situ and IDC with invasive foci smaller than one cm because small lesions decrease the reliability of signal intensity of diffusion-weighted imaging (DWI). We also excluded special type cancers. We used t-test to compare the mean ADC values of cancers of Stage pT1 (≤2 cm) versus pT2 or 3 (>2 cm), cancers with versus without vascular invasion, axillary lymph node (N)-positive versus N-negative cancers, estrogen receptor (ER)-positive versus ER-negative cancers, and progesterone receptor (PgR)-positive versus PgR-negative cancers. We analyzed correlations between the ADC value with nuclear grade (NG) and human epidermal growth factor receptor 2 (HER2) score by rank test using Spearman's correlation coefficient. Results: The mean ADC value was significantly higher for N-positive (n=28; 0.97±0.20×10−3 mm2/s) than N-negative cancers (n=53; 0.87±0.17×10−3 mm2/s) (P=0.017); significantly lower for ER-positive (n=63; 0.88±0.15×10−3 mm2/s) than ER-negative cancers (n=18; 1.01±0.21×10−3 mm2/s) (P=0.005); and significantly lower for PgR-positive (n=47; 0.88±0.16×10−3 mm2/s) than PgR-negative cancers (n=34; 0.95±0.18×10−3 mm2/s) (P=0.048). Tumor size, vascular invasion, NG, and HER2 status showed no significant correlation with ADC values. Conclusion: ADC values were higher for N-positive and ER-negative breast cancers than N-negative and ER-positive cancers.
Purpose: Tract-specific analysis (TSA) measures diffusion parameters along a specific fiber that has been extracted by fiber tracking using manual regions of interest (ROIs), but TSA is limited by its requirement for manual operation, poor reproducibility, and high time consumption. We aimed to develop a fully automated extraction method for the cingulum bundle (CB) and to apply the method to TSA in neurobehavioral disorders such as Parkinson's disease (PD). Materials and Methods: We introduce the voxel classification (VC) and auto diffusion tensor fiber-tracking (AFT) methods of extraction. The VC method directly extracts the CB, skipping the fiber-tracking step, whereas the AFT method uses fiber tracking from automatically selected ROIs. We compared the results of VC and AFT to those obtained by manual diffusion tensor fiber tracking (MFT) performed by 3 operators. We quantified the Jaccard similarity index among the 3 methods in data from 20 subjects (10 normal controls [NC] and 10 patients with Parkinson's disease dementia [PDD]). We used all 3 extraction methods (VC, AFT, and MFT) to calculate the fractional anisotropy (FA) values of the anterior and posterior CB for 15 NC subjects, 15 with PD, and 15 with PDD. Results: The Jaccard index between results of AFT and MFT, 0.72, was similar to the inter-operator Jaccard index of MFT. However, the Jaccard indices between VC and MFT and between VC and AFT were lower. Consequently, the VC method classified among 3 different groups (NC, PD, and PDD), whereas the others classified only 2 different groups (NC, PD or PDD). Conclusion: For TSA in Parkinson's disease, the VC method can be more useful than the AFT and MFT methods for extracting the CB. In addition, the results of patient data analysis suggest that a reduction of FA in the posterior CB may represent a useful biological index for monitoring PD and PDD.
Purpose: We propose a post-processing framework for localized two-dimensional (2D) magnetic resonance spectroscopy (MRS) in vivo. Methods: Our framework consists of corrections on eddy current and subject motion along with the framework used in conventional analytical 2D nuclear magnetic resonance (NMR) spectroscopy. In the eddy current correction, the phases of the free induction decays (FIDs) of the metabolite 1H are corrected along the t2 direction by the phase of the FID of water 1H. The corrected FIDs are Fourier transformed along the t2 direction, and interferograms of F(t1, ω2) are calculated. In the motion correction, the zero-order phase of the N-acetyl aspartate (NAA) singlet peak for each t1 axis is corrected after correction of frequency drift. We applied this framework in phantom and human brain measurements in a 4.7T whole-body MR system. Two-dimensional data were collected by the localized 2D constant-time correlation spectroscopy (CT-COSY) sequence. We used a phantom containing a brain metabolite mixture of NAA, creatine (Cr), glutamate (Glu), glutamine (Gln) and γ-amino butyric acid (GABA). We demonstrated the eddy current correction procedure in the phantom experiments and the subject motion correction in human measurements. Results: Though asymmetric patterns of the singlets of NAA and Cr were shown around the peak along the F2 direction in the reconstructed phantom spectra without eddy current correction, symmetric patterns arose after the correction. The t1 noise caused by those singlets was found in the human brain spectra without motion correction. The t1 noise was sufficiently suppressed by the motion correction. Conclusion: Our proposed post-processing framework for localized 2D MRS can improve the quality of in vivo 2D spectra and may allow improved quantitation and robustness of in vivo 2D spectroscopy.
Eleven patients with suspected Ménière's disease received intratympanic (IT) administration of gadolinium (gadopentetate dimeglumine; Gd) prior to acquisition of 3-dimensional (3D) fluid-attenuated inversion recovery (FLAIR), 3D real inversion recovery (IR), and fast T1 mapping by dual flip angle 3D gradient echo (FT1-map) imaging sequences to evaluate the degree of perilymph enhancement. Though 3-dimensional FLAIR could detect lower concentrations of gadolinium than 3D real IR, in 2 patients, poor enhancement still prevented visualization of the endolymphatic space using 3D FLAIR. We could predict poor contrast enhancement in these 2 patients using the FT1-map technique.
Purpose: We compared diffusion-weighted imaging (DWI) of the breast using 2 different b-values to determine the optimal b-value for greatest signal contrast between tumors and normal tissue of the breast. Materials and Methods: We performed DWI of the breast at b-values of 1000 s/mm2 and 1500 s/mm2 in 120 patients (121 lesions, 19 benign, 102 malignant) and visually scored image quality with regard to artifact and visibility of tumors. We quantitatively evaluated the signal-to-noise ratio (SNR) of the tumor and contrast-to-noise ratio (CNR) and contrast ratio (CR) between the tumor and normal breast parenchyma. Results: The CR of invasive carcinoma (IC), ductal carcinoma in situ (DCIS), and benign tumors significantly improved with b=1500 s/mm2 compared with b=1000 s/mm2. The SNR and CNR were significantly lower with b=1500 s/mm2 than b=1000 s/mm2 despite the increasing number of excitations at b=1500 s/mm2. At b=1500 s/mm2, the difference in SNR, CNR, and CR between IC and DCIS and benign tumors was statistically significant. Conclusion: DWI may depict breast tumors more clearly with b=1500 s/mm2 than b=1000 s/mm2.
Purpose: Our purposes were to establish suitable conditions for proton magnetic resonance spectroscopy (MRS) to measure dynamic changes in alcohol concentration in the human brain, to evaluate these changes, and to compare the findings with data from analysis of breath vapor and blood samples. Materials and Methods: We evaluated 4 healthy volunteers (mean age 26.5 years; 3 males, one female) with no neurological findings. All studies were performed with 3-tesla clinical equipment using an 8-channel head coil. We applied our modified single-voxel point-resolved spectroscopy (PRESS) sequence. Continuous measurements of MRS, breath vapor, and blood samples were conducted before and after the subjects drank alcohol with a light meal. The obtained spectra were quantified by LCModel Ver. 6.1, and the accuracy of the MRS measurements was estimated using the estimated standard deviation expressed in percentage (%SD) as a criterion. Results: Alcohol peaks after drinking were clearly detected at 1.2 ppm for all durations of measurement. Good correlations between breath vapor or blood sample and MRS were found by sub-minute MRS measurement. The continuous measurement showed time-dependent changes in alcohol in the brain and various patterns that differed among subjects. Conclusions: The clinical 3T equipment enables direct evaluation of sub-minute changes in alcohol metabolism in the human brain.