This study is intended as a review of 3Tesla (T) magnetic resonance (MR) imaging of the triangular fibrocartilage complex (TFCC). The recent advances in MR imaging, which includes high field strength magnets, multi-channel coils, and isotropic 3-dimensional (3D) sequences have enabled the visualization of precise TFCC anatomy with high spatial and contrast resolution. In addition to the routine wrist protocol, there are specific techniques used to optimize 3T imaging of the wrist; including driven equilibrium sequence (DRIVE), parallel imaging, and 3D imaging. The coil choice for 3T imaging of the wrist depends on a number of variables, and the proper coil design selection is critical for high-resolution wrist imaging with high signal and contrast-to-noise ratio. The TFCC is a complex structure and is composed of the articular disc (disc proper), the triangular ligament, the dorsal and volar radioulnar ligaments, the meniscus homologue, the ulnar collateral ligament (UCL), the extensor carpi ulnaris (ECU) tendon sheath, and the ulnolunate and ulnotriquetral ligaments. The Palmer classification categorizes TFCC lesions as traumatic (type 1) or degenerative (type 2). In this review article, we present clinical high-resolution MR images of normal TFCC anatomy and TFCC injuries with this classification system.
Purpose: Various magnetic resonance imaging (MRI) techniques including T2*-weighted imaging, susceptibility-weighted imaging, and MR relaxometry had been performed to evaluate different patterns of brain iron depositions in Parkinsonian syndrome. The aim of the present study was to evaluate the diagnostic value of a volume of interest (VOI) analysis on the principles of echo shifting with a train of observations (PRESTO) imaging using the statistical parametric mapping (SPM) 8 and the WFU PickAtlas program for the diagnosis of Parkinsonian syndrome., Methods: Fifty subjects, including 13 with the Parkinsonian variant of multiple system atrophy (MSA-P), 12 with progressive supranuclear palsy (PSP), 12 with Parkinson’s disease (PD) and 13 controls were evaluated in this study. After the spatial normalization of PRESTO images on SPM8, the WFU PickAtlas program was performed to create target VOIs in the putamen, red nucleus, substantia nigra, subthalamic nucleus, and dentate nucleus. The signal intensity ratio (SIR) was calculated by normalizing the signal of each VOI to that of the cerebrospinal fluid space. These SIRs were used as determinants in receiver operating characteristic (ROC) analyses. Results: SIR of the putamen was significantly lower in MSA-P than in PSP (P = 0.0051) and controls (P = 0.0004). In contrast, SIR of the red nucleus was significantly lower in PSP than in MSA-P (P = 0.0003), PD (P = 0.0029), and controls (P = 0.0011). In ROC analyses, SIR of the putamen exhibited the highest areas under the curves (AUCs) of 0.83 (vs. PSP) and 0.91 (vs. controls) in the diagnosis of MSA-P. On the other hand, SIR of the red nucleus exhibited the highest AUCs of 0.87 (vs. MSA-P), 0.90 (vs. PD), and 0.89 (vs. controls) in the diagnosis of PSP. Conclusions: The VOI analysis based on spatially normalized PRESTO images may be useful for depicting hypointensity, indicative of abnormal iron depositions, of the putamen and red nucleus in the diagnosis of MSA-P and PSP.
Purpose: The B0 and B1+ maps required for calculation of the radiofrequency (RF) pulse of parallel transmission (pTx) are obtained in calibration scans; however, they may be affected by respiratory motion. We aimed to compare the reproducibility of B0 and B1+ maps and gradient echo (GRE) images of the brain scanned with pTx at 7T between free-breathing (FB) and breath-holding (BH) conditions during the calibration scan. Methods: Nine healthy volunteers were scanned by 7T MRI using a two-channel quadrature head coil. In the pTx calibration scans performed with FB and BH, the B0 map was obtained from two different TE images and the B1+ map was calculated by the Bloch-Siegert method. A GRE image (gradient-recalled-acquisition in steady state) was also obtained with RF shimming and RF design of pTx with spoke method, as well as quadrature transmission (qTx). All the scans were repeated over five sessions. The reproducibility of the B0 and B1+ maps and GRE image was evaluated with region-of-interest measurements using inter-session standard deviation (SD) and coefficient of variation (CV) values. Intensity homogeneity of GRE images was also assessed with in-plane CV. Results: Inter-session SDs of B0 and B1+ maps were significantly smaller in BH (P < 0.01). Inter-session CVs of GRE images were significantly smaller in qTx than BH and FB (P < 0.01, both); however, the CVs of BH were significantly smaller (P < 0.01). In-plane CVs of FB and BH with RF shimming were not significantly different with qTx; however, CVs of FB and BH with RF design were significantly smaller than those of qTx (P < 0.05 and P < 0.01, respectively). Conclusion: BH could improve the reproducibility of B0 and B1+ maps in pTx calibration scans and GRE images. These results might facilitate the development of pTx in human brain at 7T.
Purpose: The Bayesian estimation algorithm improves the precision of bolus tracking perfusion imaging. However, this algorithm cannot directly calculate Tmax, the time scale widely used to identify ischemic penumbra, because Tmax is a non-physiological, artificial index that reflects the tracer arrival delay (TD) and other parameters. We calculated Tmax from the TD and mean transit time (MTT) obtained by the Bayesian algorithm and determined its accuracy in comparison with Tmax obtained by singular value decomposition (SVD) algorithms. Methods: The TD and MTT maps were generated by the Bayesian algorithm applied to digital phantoms with time-concentration curves that reflected a range of values for various perfusion metrics using a global arterial input function. Tmax was calculated from the TD and MTT using constants obtained by a linear least-squares fit to Tmax obtained from the two SVD algorithms that showed the best benchmarks in a previous study. Correlations between the Tmax values obtained by the Bayesian and SVD methods were examined. Results: The Bayesian algorithm yielded accurate TD and MTT values relative to the true values of the digital phantom. Tmax calculated from the TD and MTT values with the least-squares fit constants showed excellent correlation (Pearson’s correlation coefficient = 0.99) and agreement (intraclass correlation coefficient = 0.99) with Tmax obtained from SVD algorithms. Conclusions: Quantitative analyses of Tmax values calculated from Bayesian-estimation algorithm-derived TD and MTT from a digital phantom correlated and agreed well with Tmax values determined using SVD algorithms.
Purpose: The importance of arterial transit time (ATT) correction for arterial spin labeling MRI has been well debated in neuroimaging, but it has not been well evaluated in renal imaging. The purpose of this study was to evaluate the feasibility of pulsed continuous arterial spin labeling (pcASL) MRI with multiple post-labeling delay (PLD) acquisition for measuring ATT-corrected renal blood flow (ATC-RBF). Materials and Methods: A total of 14 volunteers were categorized into younger (n = 8; mean age, 27.0 years) and older groups (n = 6; 64.8 years). Images of pcASL were obtained at three different PLDs (0.5, 1.0, and 1.5 s), and ATC-RBF and ATT were calculated using a single-compartment model. To validate ATC-RBF, a comparative study of effective renal plasma flow (ERPF) measured by 99mTc-MAG3 scintigraphy was performed. ATC-RBF was corrected by kidney volume (ATC-cRBF) for comparison with ERPF. Results: The younger group showed significantly higher ATC-RBF (157.68 ± 38.37 mL/min/100 g) and shorter ATT (961.33 ± 260.87 ms) than the older group (117.42 ± 24.03 mL/min/100 g and 1227.94 ± 226.51 ms, respectively; P < 0.05). A significant correlation was evident between ATC-cRBF and ERPF (P < 0.05, r = 0.47). With suboptimal single PLD (1.5 s) settings, there was no significant correlation between ERPF and kidney volume-corrected RBF calculated from single PLD data. Conclusion: Calculation of ATT and ATC-RBF by pcASL with multiple PLD was feasible in healthy volunteers, and differences in ATT and ATC-RBF were seen between the younger and older groups. Although ATT correction by multiple PLD acquisitions may not always be necessary for RBF quantification in the healthy subjects, the effect of ATT should be taken into account in renal ASL–MRI as debated in brain imaging.
Purpose: Cerebral arteriolar vasomotor function plays an important role in brain health. Since respiratory changes in the partial arterial pressure of CO2 (PaCO2) cause arterioles to vasodilate or vasoconstrict, resting-state arteriolar vasomotion results in the fluctuation of venous blood oxygenation, which can be monitored by observing magnetic resonance (MR) signals. Focusing on the superior sagittal sinus as the largest cerebral vein, we developed a method to elucidate the respiratory fluctuation of cerebral venous oxygenation that may reflect the vasomotor function. Methods: Single slices of varying thickness (7–15 mm) taken perpendicular to the superior sagittal sinus of five volunteers were imaged by spin-echo echo-planar imaging using a 1.5-T MR system. The time series of the signal intensity at the superior sagittal sinus was Fourier-transformed, and the spectral fluctuation intensity (SFI) at respiratory frequency was obtained. The amplitude of the respiratory fluctuation in the cerebral venous oxygenation was calculated from the gradient of the relation between the SFI and the average signal intensity, which increased proportionally with an increase in slice thickness. The amplitude of the fluctuation in cerebral venous oxygenation at low (<0.1 Hz) and cardiac pulsation frequencies was also calculated for comparison with the respiratory fluctuation. Results: The amplitude of respiratory fluctuation in the cerebral venous oxygenation was quantified as 1.2%, demonstrating the validity of our method via the highest significant correlation (r = 0.82) in the plot of SFI and average signal intensities; the correlations at low and cardiac pulsation frequencies were 0.60 and 0.63, respectively. Conclusion: We have successfully demonstrated cerebral venous oxygenation fluctuation at respiratory frequencies in the resting state. This fluctuation was non-invasively evaluated as 1.2%, representing the control value for the arteriolar vasomotor function of a healthy human.
Purpose: 11.7 Tesla MRI was examined to detect Virchow–Robin spaces (VRSs) smaller than 100 μm in the rat brain. The effects of maternal exposure to lipopolysaccharide (LPS) were evaluated on basis of the number of dilated VRSs in the offspring rat brain. Methods: T2-weighted MRI with an in-plane resolution up to 78 μm (repetition time = 5000 ms, echo time = 35 ms, slice thickness = 250 μm, imaging plane, coronal) was applied to identify VRSs. The dilated VRSs were counted in the rat brain at 5 and 10 weeks of age. The dams of half the number in each group were treated with LPS during pregnancy, and the remaining half was employed as control. LPS injection in gestation period was used to simulate maternal infections, the method of which was widely accepted as a rat model inducing neuropsychiatric disorders in the offspring. Effects of LPS exposure on the offspring rat brain were statistically investigated. Results: VRSs as small as 78 μm were successfully detected by the ultra high-field MRI. All dilated VRSs were observed within lacunosum molecular layer of hippocampus, and molecular and granular layers of dentate gyrus around hippocampal fissure. In juvenile rats (5 weeks of age), the number of dilated VRSs was significantly increased in the prenatal LPS exposed rat brain (12.9 ± 2.4, n = 7) than in the control (5.3 ± 1.5, n = 7, P < 0.05), while in young adult rats (10 weeks of age), there was no significant difference in the number between the prenatal LPS exposed rat brain (3.6 ± 0.9, n = 5) and the control (2.6 ± 0.4, n = 5). Conclusion: The results of the present study suggested that maternal infection might cause dilatation of VRSs through neural damages especially in the dentate gyrus of the offspring rats. Thus, ultra high-field MRI can offer a promising diagnostic tool capable of determining the location of neonatal brain damage caused by maternal infections.
Purpose: In textbooks, the perivascular space (PVS) is described as non-enhancing after the intravenous administration of gadolinium-based contrast agent (IV-GBCA). We noticed that the PVS sometimes has high signal intensity (SI) on heavily T2-weighted 3D-FLAIR (hT2-FL) images obtained 4 h after IV-GBCA. The purpose of this study was to retrospectively evaluate the contrast enhancement of the PVS.
Materials and Methods: In 8 healthy subjects and 19 patients with suspected endolymphatic hydrops, magnetic resonance cisternography (MRC) and hT2-FL images were obtained before and 4 h after a single dose of IV-GBCA. No subjects had renal insufficiency. On axial MRC at the level of the anterior commissure (AC)-posterior commissure (PC) line, 1 cm circular regions of interest (ROIs) were drawn centering on the PVS in the bilateral basal ganglia and thalami. Three-millimeter diameter ROIs were set in the cerebrospinal fluid (CSF) of the bilateral ambient cistern. The ROIs on MRC were copied onto the hT2-FL images and the SI was measured. The SI ratio (SIR) was defined as SIRPVS = SI of PVS/SI of the thalami, and SIRCSF = SI of CSF/SI of the thalami. The average of the bilateral values was used for the calculation. The SIRCSF, SIRPVS, and SI of the thalami were compared between before and 4 h after IV-GBCA.
Results: The SIR was increased significantly from 1.02 ± 0.37 to 2.65 ± 0.82 in the CSF (P < 0.01) and from 1.20 ± 0.35 to 2.13 ± 1.23 in the PVS at 4 h after IV-GBCA (P < 0.01). The SI of the thalami showed no significant difference.
Conclusion: The enhancement of the PVS at 4 h after IV-GBCA was confirmed even in subjects without renal insufficiency. It is possible that the GBCA in the blood vessels might have permeated into the cerebrospinal fluid (CSF) space and the PVS. This might be a first step in the imaging evaluation of the glymphatic system (waste clearance system) of the brain.
Purpose: To evaluate the feasibility of computed diffusion weighted imaging (DWI) in cervical cancer and investigate the optimal b-value using computed DWI.
Methods: The present retrospective study involved 85 patients with cervical cancer in the International Federation of Gynecology and Obstetrics (FIGO) stage IB, IIA or IIB. DWI was obtained with b-values of 0, 100, 500 and 1000 s/mm2. Computed DWI with b-values of 800, 1000, 1300, 1600 and 2000 s/mm2 (cDWI800, cDWI1000, cDWI1300, cDWI1600, cDWI2000) were generated from all measured DWI (mDWI) data. Qualitatively, computed DWI was evaluated in terms of tumor conspicuity, signal suppression of the fat in the imaged area and total image quality by two radiologists independently with reference to mDWI with b-value of 1000 s/mm2. The b-value at which the signal of the endocervical canal was suppressed was recorded. Quantitatively, the signal intensities of tumor, myometrium, endocervical canal, endometrium, and gluteal subcutaneous fat were measured and represented as contrast ratios (CR).
Results: Regarding tumor conspicuity and total image quality, significantly higher scores were obtained at cDWI1300 and cDWI1600 compared to the others (post-hoc comparison, P < 0.001), except for the total image quality between cDWI1000 and cDWI1600 in one reader. Signal suppression of the fat was the worst at cDWI2000. The signal intensity of the endocervical canal was suppressed in 24/27 cases on cDWI1600 and in 26/27 cases on cDWI2000. The CRs of tumor to myometrium, cervix, and endometrium increased with higher b-values, while the CRs of tumor to fat decreased and were statistically significant (post-hoc comparison, P < 0.001).
Conclusion: Computed DWI with the b-values of 1300 and 1600 would be suitable for the evaluation of cervical cancer due to good tumor conspicuity.
Purpose: To elucidate whether any differences are present in the stiffness map obtained with a multiscale direct inversion algorithm (MSDI) vs that with a multimodel direct inversion algorithm (MMDI), both qualitatively and quantitatively.
Materials and Methods: The MR elastography (MRE) data of 37 consecutive patients who underwent liver MR elastography between September and October 2014 were retrospectively analyzed by using both MSDI and MMDI. Two radiologists qualitatively assessed the stiffness maps for the image quality in consensus, and the measured liver stiffness and measurable areas were quantitatively compared between MSDI and MMDI.
Results: MMDI provided a stiffness map of better image quality, with comparable or slightly less artifacts. Measurable areas by MMDI (43.7 ± 17.8 cm2) was larger than that by MSDI (37.5 ± 14.7 cm2) (P < 0.05). Liver stiffness measured by MMDI (4.51 ± 2.32 kPa) was slightly (7%), but significantly less than that by MSDI (4.86 ± 2.44 kPa) (P < 0.05).
Conclusion: MMDI can provide stiffness map of better image quality, and slightly lower stiffness values as compared to MSDI at 3T MRE, which radiologists should be aware of.
We examined the capability of a gray-scale arterial spin labeling blood flow pattern variation (BFPV) map with two different post labeling delay (PLD) times to discriminate pannus in patients with rheumatoid arthritis (RA) at 3T. There was a statistically significant difference in the BFPV values between artery, pannus, and surrounding tissue. Furthermore, the color-coded BFPV map was able to accurately distinguish pannus from other tissues. These results suggest this approach may be capable of identifying pannus noninvasively.
We report a 34-year-old male who manifested T1 shortening of the cerebral cortices after more than 86 contrast-enhanced MRI studies. We observed high-signal intensity (SI) on T1-weighted images (T1WIs) not only in the globus pallidus, dentate nucleus, and pulvinar of thalamus, but also in the cortices of the pre- and post-central gyri and around the calcarine sulcus. High SI in the cerebral cortices was not clearly demonstrated on T1WI scans performed 11 years earlier. The high SI we observed in these areas of the brain corresponded to areas with a normal iron-deposition predilection. Gadolinium deposition in the brain may be associated with the iron metabolism.