The Utility of a Convolutional Neural Network for Generating a Myelin Volume Index Map from Rapid Simultaneous Relaxometry Imaging.

PURPOSE: A current algorithm to obtain a synthetic myelin volume fraction map (SyMVF) from rapid simultaneous relaxometry imaging (RSRI) has a potential problem, that it does not incorporate information from surrounding pixels. The purpose of this study was to develop a method that utilizes a convolutional neural network (CNN) to overcome this problem. METHODS: RSRI and magnetization transfer images from 20 healthy volunteers were included. A CNN was trained to reconstruct RSRI-related metric maps into a myelin volume-related index (generated myelin volume index: GenMVI) map using the MVI map calculated from magnetization transfer images (MTMVI) as reference. The SyMVF and GenMVI maps were statistically compared by testing how well they correlated with the MTMVI map. The correlations were evaluated based on: (i) averaged values obtained from 164 atlas-based ROIs, and (ii) pixel-based comparison for ROIs defined in four different tissue types (cortical and subcortical gray matter, white matter, and whole brain). RESULTS: For atlas-based ROIs, the overall correlation with the MTMVI map was higher for the GenMVI map than for the SyMVF map. In the pixel-based comparison, correlation with the MTMVI map was stronger for the GenMVI map than for the SyMVF map, and the difference in the distribution for the volunteers was significant (Wilcoxon sign-rank test, P < 0.001) in all tissue types. CONCLUSION: The proposed method is useful, as it can incorporate more specific information about local tissue properties than the existing method. However, clinical validation is necessary.

Ventricular volumetry and free-water corrected diffusion tensor imaging of the anterior thalamic radiation in idiopathic normal pressure hydrocephalus.

BACKGROUND AND PURPOSE: The pathophysiology of idiopathic normal pressure hydrocephalus (iNPH) has not been completely clarified. We investigated the brain structure in iNPH using automatic ventricular volumetry, single-tensor diffusion tensor imaging (DTI) and bi-tensor free-water (FW) imaging analyses while focusing on cognitive impairments before and after lumboperitoneal shunt surgery. MATERIALS AND METHODS: This retrospective study included 12 iNPH patients with structural magnetic resonance imaging (MRI) and diffusion MRI (dMRI) on a 3T-MRI scanner who underwent neuropsychological assessments before and after shunting and 8 healthy controls. Ventricular volumetry was conducted on structural MRI datasets using FreeSurfer. Ventricular volume was compared pre- and postoperatively. Correlation analyses were performed between ventricular volume or volume change and neuropsychological scores or score change. Tract-based spatial statistics were performed using dMRI datasets for group analyses between iNPH and controls and between pre- and post-surgery iNPH patients and for correlation analyses using neuropsychological scores. Tract-specific analyses were performed in the anterior thalamic radiation (ATR), followed by comparison and correlation analyses. RESULTS: The third ventricular volume was significantly decreased after shunting; its volume reduction negatively correlated with a neuropsychological improvement. Compared with controls, iNPH patients had lower fractional anisotropy and higher axial, radial, and mean diffusivities, and FW in the periventricular white matter including ATR, resulting in no difference in FW-corrected indices. Single-tensor DTI indices partially correlated with neuropsychological improvements, while FW-corrected indices had no correlations. CONCLUSION: Third ventricle enlargement is possibly linked to cognitive impairment and FW imaging possibly provides better white matter characterization in iNPH.

Signal Intensity within Cerebral Venous Sinuses on Synthetic MRI.

PURPOSE: Flowing blood sometimes appears bright on synthetic T1-weighted images, which could be misdiagnosed as a thrombus. This study aimed to investigate the frequency of hyperintensity within cerebral venous sinuses on synthetic MR images and to evaluate the influence of increasing flow rates on signal intensity using a flow phantom. MATERIALS AND METHODS: Imaging data, including synthetic and conventional MRI scans, from 22 patients were retrospectively analyzed. Signal intensities at eight locations of cerebral venous sinuses on synthetic images were graded using the following three-point scale: 0, "dark vessel"; 1, "hyperintensity within the walls"; and 2, "hyperintensity within the lumen." A phantom with gadolinium solution inside a U-shaped tube was acquired without flow and then with increasing flow rates (60, 100, 200, 300, 400 ml/min). RESULTS: Considering all sinus locations, the venous signal intensity on synthetic T1-weighted images was graded as 2 in 79.8% of the patients. On synthetic T2-weighted images, all sinuses were graded as 0. On fluid-attenuated inversion recovery (FLAIR) images, sinuses were almost always graded as 0 (99.4%). In the phantom study, the signal initially became brighter on synthetic T1-weighted images as the flow rate increased. Above a certain flow rate, the signal started to decrease. CONCLUSION: High signal intensity within the cerebral venous sinuses is a frequent finding on synthetic T1-weighted images. This corresponds to the hyperintensity noted at certain flow rates in the phantom experiment.

Gray Matter Alterations in Early and Late Relapsing-Remitting Multiple Sclerosis Evaluated with Synthetic Quantitative Magnetic Resonance Imaging.

Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration ≤5 and >5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = -0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients.

Estimation of Gadolinium-based Contrast Agent Concentration Using Quantitative Synthetic MRI and Its Application to Brain Metastases: A Feasibility Study.

PURPOSE: Gadolinium-based contrast agents (GBCA) provide valuable information for assessing and differentiating lesions in the body. However, contrast enhancement evaluation on conventional MRI is qualitative because the signal intensity uses an arbitrary scale. An approach that allows more quantitative assessment of tissue enhancement that can be integrated into clinical use is desirable. This study aimed to provide a method that can estimate GBCA concentration in a clinically applicable scan-time. METHODS: Gadolinium-based contrast agent concentrations were quantified in phantoms containing water and nine different concentrations of Gadoteridol (Gd-HP-DO3A), ranging from 0.02 to 1.00 mmol/L, using quantitative synthetic MRI. Simple linear regression analysis between the estimated GBCA concentration and the reference values were performed to assess the accuracy. We performed region of interest analysis on each phantom, and recorded the mean and standard deviation. We evaluated the precision of the GBCA map by calculating the coefficient of variation (CV) for each concentration. The GBCA concentration quantification method was applied for 10 patients with metastatic brain tumors to demonstrate the feasibility of this method. RESULTS: For the phantom study, estimated GBCA concentrations were in a strong linear relationship (R2 = 0.998) with reference values, with a slope and intercept on simple linear regression analysis of 0.98 and 0.02, respectively. On precision assessment, the CV was <5%, with the exception of concentrations under 0.07 mmol/L. In the range of 0.07-0.99 mmol/L, the mean CV was 1.5 ± 1.2%. For application to brain metastases, the maximum estimated GBCA concentration in the metastases was 0.73 mmol/L, which was under the upper limit evaluated in the phantom study (i.e. -0.99 mmol/L). CONCLUSION: The concentration of Gd-HP-DO3A in the range of 0.07-0.99 mmol/L can be measured in a clinically applicable scan time using quantitative synthetic MRI, even though this study's results are only preliminary due to several limitations.

Linearity, Bias, Intrascanner Repeatability, and Interscanner Reproducibility of Quantitative Multidynamic Multiecho Sequence for Rapid Simultaneous Relaxometry at 3 T: A Validation Study With a Standardized Phantom and Healthy Controls.

OBJECTIVES: The aim of this study was to evaluate the linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative values derived from a multidynamic multiecho (MDME) sequence for rapid simultaneous relaxometry. MATERIALS AND METHODS: The NIST/ISMRM (National Institute of Standards and Technology/International Society for Magnetic Resonance in Medicine) phantom, containing spheres with standardized T1 and T2 relaxation times and proton density (PD), and 10 healthy volunteers, were scanned 10 times on different days and 2 times during the same session, using the MDME sequence, on three 3 T scanners from different vendors. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. The measured phantom values were compared with reference values; volunteer values were compared with their averages across 3 scanners. RESULTS: The linearity of both phantom and volunteer measurements in T1, T2, and PD values was very strong (R = 0.973-1.000, 0.979-1.000, and 0.982-0.999, respectively) The highest intrascanner coefficients of variation (CVs) for T1, T2, and PD were 2.07%, 7.60%, and 12.86% for phantom data, and 1.33%, 0.89%, and 0.77% for volunteer data, respectively. The highest interscanner CVs of T1, T2, and PD were 10.86%, 15.27%, and 9.95% for phantom data, and 3.15%, 5.76%, and 3.21% for volunteer data, respectively. Variation of T1 and T2 tended to be larger at higher values outside the range of those typically observed in brain tissue. The highest intrascanner and interscanner CVs for brain tissue volumetry were 2.50% and 5.74%, respectively, for cerebrospinal fluid. CONCLUSIONS: Quantitative values derived from the MDME sequence are overall robust for brain relaxometry and volumetry on 3 T scanners from different vendors. Caution is warranted when applying MDME sequence on anatomies with relaxometry values outside the range of those typically observed in brain tissue.

Myelin Measurement: Comparison Between Simultaneous Tissue Relaxometry, Magnetization Transfer Saturation Index, and T1w/T2w Ratio Methods.

Magnetization transfer (MT) imaging has been widely used for estimating myelin content in the brain. Recently, two other approaches, namely simultaneous tissue relaxometry of R1 and R2 relaxation rates and proton density (SyMRI) and the ratio of T1-weighted to T2-weighted images (T1w/T2w ratio), were also proposed as methods for measuring myelin. SyMRI and MT imaging have been reported to correlate well with actual myelin by histology. However, for T1w/T2w ratio, such evidence is limited. In 20 healthy adults, we examined the correlation between these three methods, using MT saturation index (MTsat) for MT imaging. After calibration, white matter (WM) to gray matter (GM) contrast was the highest for SyMRI among these three metrics. Even though SyMRI and MTsat showed strong correlation in the WM (r = 0.72), only weak correlation was found between T1w/T2w and SyMRI (r = 0.45) or MTsat (r = 0.38) (correlation coefficients significantly different from each other, with p values < 0.001). In subcortical and cortical GM, these measurements showed moderate to strong correlations to each other (r = 0.54 to 0.78). In conclusion, the high correlation between SyMRI and MTsat indicates that both methods are similarly suited to measure myelin in the WM, whereas T1w/T2w ratio may be less optimal.

Neurite orientation dispersion and density imaging of the nigrostriatal pathway in Parkinson's disease: Retrograde degeneration observed by tract-profile analysis.

INTRODUCTION: Parkinson's disease (PD) is marked by the degeneration of dopaminergic neurons in the nigrostriatal pathway (NSP). We aimed to identify the microstructural changes in the NSP of PD patients using neurite orientation dispersion and density imaging (NODDI). METHODS: NSPs of 29 PD patients, who were retrospectively selected from patients previously admitted to our institution, and 29 age- and gender-matched healthy controls were isolated via deterministic tractography. The NODDI indices, intracellular volume fraction (Vic), orientation dispersion index (OD), and isotropic volume fraction (Viso) were compared between the two groups. The significant results were assessed with a tract-profile analysis. The correlation between indices and disease duration or motor symptom severity was evaluated with the Pearson's correlation test. RESULTS: The contralateral distal Vic (p = 0.00028) of the nigrostriatal pathway was significantly lower in PD patients than in healthy controls. No correlations were detected between any of the indices and disease duration or motor symptom severity. CONCLUSIONS: NODDI can be used to identify retrograde degeneration of the NSP in PD patients and might be useful for monitoring the disease progression of PD.

SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement.

Conventional magnetic resonance images are usually evaluated using the image signal contrast between tissues and not based on their absolute signal intensities. Quantification of tissue parameters, such as relaxation rates and proton density, would provide an absolute scale; however, these methods have mainly been performed in a research setting. The development of rapid quantification, with scan times in the order of 6 minutes for full head coverage, has provided the prerequisites for clinical use. The aim of this review article was to introduce a specific quantification method and synthesis of contrast-weighted images based on the acquired absolute values, and to present automatic segmentation of brain tissues and measurement of myelin based on the quantitative values, along with application of these techniques to various brain diseases. The entire technique is referred to as "SyMRI" in this review. SyMRI has shown promising results in previous studies when used for multiple sclerosis, brain metastases, Sturge-Weber syndrome, idiopathic normal pressure hydrocephalus, meningitis, and postmortem imaging.

Diffusion imaging of reversible and irreversible microstructural changes within the corticospinal tract in idiopathic normal pressure hydrocephalus.

The symptoms of idiopathic normal pressure hydrocephalus (iNPH) can be improved by shunt surgery, but prediction of treatment outcome is not established. We investigated changes of the corticospinal tract (CST) in iNPH before and after shunt surgery by using diffusion microstructural imaging, which infers more specific tissue properties than conventional diffusion tensor imaging. Two biophysical models were used: neurite orientation dispersion and density imaging (NODDI) and white matter tract integrity (WMTI). In both methods, the orientational coherence within the CSTs was higher in patients than in controls, and some normalization occurred after the surgery in patients, indicating axon stretching and recovery. The estimated axon density was lower in patients than in controls but remained unchanged after the surgery, suggesting its potential as a marker for irreversible neuronal damage. In a Monte-Carlo simulation that represented model axons as undulating cylinders, both NODDI and WMTI separated the effects of axon density and undulation. Thus, diffusion MRI may distinguish between reversible and irreversible microstructural changes in iNPH. Our findings constitute a step towards a quantitative image biomarker that reflects pathological process and treatment outcomes of iNPH.

Contrast-enhanced synthetic MRI for the detection of brain metastases.

BACKGROUND: Synthetic magnetic resonance imaging (MRI), a technique that enables creation of various contrast-weighted images from a single MRI quantification scan, is a useful clinical tool. However, there are currently no reports examining the use of contrast-enhanced synthetic MRI for detecting brain metastases. PURPOSE: To assess whether contrast-enhanced synthetic MRI is suitable for detecting brain metastases. MATERIAL AND METHODS: Ten patients with a combined total of 167 brain metastases who underwent quantitative MRI and conventional T1-weighted inversion recovery fast spin-echo (conventional T1IR) MRI before and after administration of a contrast agent were included in the study. Synthetic T1IR and T1-weighted (synthetic T1W) images were produced after parameter quantification. Lesion-to-white matter contrast and contrast-to-noise ratio were calculated for each image. The number of visible lesions in each image was determined by two neuroradiologists. RESULTS: The mean lesion-to-white matter contrast and mean contrast-to-noise ratio of the synthetic T1IR images were significantly higher than those of the synthetic T1W (P < 0.001 and P < 0.001, respectively) and conventional T1IR (P = 0.04 and P = 0.002, respectively) images. Totals of 130 and 124 metastases were detected in the synthetic T1IR images by the first and second radiologists, respectively. The corresponding numbers were 91 and 85 in the synthetic T1W images and 119 and 119 in the conventional T1IR images. Statistical significance was not found among detected numbers of lesions. CONCLUSION: Synthetic T1IR imaging created better contrast compared with synthetic T1W or conventional T1IR imaging. The ability to detect brain metastases was comparable among these imaging.