Automated prediction of the Thoracolumbar Injury Classification and Severity Score from CT using a novel deep learning algorithm.

OBJECTIVE: Damage to the thoracolumbar spine can confer significant morbidity and mortality. The Thoracolumbar Injury Classification and Severity Score (TLICS) is used to categorize injuries and determine patients at risk of spinal instability for whom surgical intervention is warranted. However, calculating this score can constitute a bottleneck in triaging and treating patients, as it relies on multiple imaging studies and a neurological examination. Therefore, the authors sought to develop and validate a deep learning model that can automatically categorize vertebral morphology and determine posterior ligamentous complex (PLC) integrity, two critical features of TLICS, using only CT scans. METHODS: All patients who underwent neurosurgical consultation for traumatic spine injury or degenerative pathology resulting in spine injury at a single tertiary center from January 2018 to December 2019 were retrospectively evaluated for inclusion. The morphology of injury and integrity of the PLC were categorized on CT scans. A state-of-the-art object detection region-based convolutional neural network (R-CNN), Faster R-CNN, was leveraged to predict both vertebral locations and the corresponding TLICS. The network was trained with patient CT scans, manually labeled vertebral bounding boxes, TLICS morphology, and PLC annotations, thus allowing the model to output the location of vertebrae, categorize their morphology, and determine the status of PLC integrity. RESULTS: A total of 111 patients were included (mean ± SD age 62 ± 20 years) with a total of 129 separate injury classifications. Vertebral localization and PLC integrity classification achieved Dice scores of 0.92 and 0.88, respectively. Binary classification between noninjured and injured morphological scores demonstrated 95.1% accuracy. TLICS morphology accuracy, the true positive rate, and positive injury mismatch classification rate were 86.3%, 76.2%, and 22.7%, respectively. Classification accuracy between no injury and suspected PLC injury was 86.8%, while true positive, false negative, and false positive rates were 90.0%, 10.0%, and 21.8%, respectively. CONCLUSIONS: In this study, the authors demonstrate a novel deep learning method to automatically predict injury morphology and PLC disruption with high accuracy. This model may streamline and improve diagnostic decision support for patients with thoracolumbar spinal trauma.

Magnetization transfer contrast-suppressed imaging of amide proton transfer and relayed nuclear overhauser enhancement chemical exchange saturation transfer effects in the human brain at 7T.

PURPOSE: To use the variable delay multipulse (VDMP) chemical exchange saturation transfer (CEST) approach to obtain clean amide proton transfer (APT) and relayed Nuclear Overhauser enhancement (rNOE) CEST images in the human brain by suppressing the conventional magnetization transfer contrast (MTC) and reducing the direct water saturation contribution. METHODS: The VDMP CEST scheme consists of a train of RF pulses with a specific mixing time. The CEST signal with respect to the mixing time shows distinguishable characteristics for protons with different exchange rates. Exchange rate filtered CEST images are generated by subtracting images acquired at two mixing times at which the MTC signals are equal, while the APT and rNOE-CEST signals differ. Because the subtraction is performed at the same frequency offset for each voxel and the CEST signals are broad, no B0 correction is needed. RESULTS: MTC-suppressed APT and rNOE-CEST images of human brain were obtained using the VDMP method. The APT-CEST data show hyperintensity in gray matter versus white matter, whereas the rNOE-CEST images show negligible contrast between gray and white matter. CONCLUSION: The VDMP approach provides a simple and rapid way of recording MTC-suppressed APT-CEST and rNOE-CEST images without the need for B0 field correction.

Measurement of arteriolar blood volume in brain tumors using MRI without exogenous contrast agent administration at 7T.

PURPOSE: Arteriolar cerebral-blood-volume (CBVa) is an important perfusion parameter that can be measured using inflow-based vascular-space-occupancy (iVASO) MRI without exogenous contrast agent administration. The purpose of this study is to assess the potential diagnostic value of CBVa in brain tumor patients by comparing it with total-CBV (including arterial, capillary and venous vessels) measured by dynamic-susceptibility-contrast (DSC) MRI. MATERIALS AND METHODS: Twelve brain tumor patients were scanned using iVASO (on 7T as part of a research project) and DSC (on 3T as part of routine clinical protocols) MRI. Region-of-interest analysis was performed to compare the resulting perfusion measures between tumoral and contralateral regions, and to evaluate their associations with tumor grades. RESULTS: CBVa measured by iVASO MRI significantly correlated with WHO grade (ρ = 0.37, P = 0.04). Total-CBV measured by DSC MRI showed a trend of correlation with WHO grade (ρ = 0.28, P = 0.5). The signal-to-noise ratio was comparable (P > 0.1) between the two methods, while the contrast-to-noise ratio between tumoral and contralateral regions was higher in iVASO-CBVa than DSC-CBV in WHO II/III patients (P < 0.05) but comparable in WHO IV patients (P > 0.1). A trend of positive correlation between DSC-CBV and iVASO-CBVa was observed (R2 = 0.28, P = 0.07). CONCLUSION: In this initial patient study, CBVa demonstrated a stronger correlation with WHO grade than total-CBV. Further investigation with a larger cohort is warranted to validate whether CBVa can be a better classifier than total-CBV for the stratification of brain tumors, and whether iVASO MRI can be a useful alternative method for the assessment of tumor perfusion, especially when exogenous contrast agent administration is difficult in certain patient populations. J. Magn. Reson. Imaging 2016;44:1244-1255.

Whole-brain amide proton transfer (APT) and nuclear overhauser enhancement (NOE) imaging in glioma patients using low-power steady-state pulsed chemical exchange saturation transfer (CEST) imaging at 7T.

PURPOSE: To explore the relationship of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) signal intensities with respect to different World Health Organization (WHO) brain tumor grades (II to IV) at 7T. MATERIALS AND METHODS: APT-based and NOE-based signals at 7T using low-power steady-state chemical exchange saturation transfer (CEST) were compared among de novo primary gliomas of different WHO grades (II to IV). The quantitative APT and NOE signals, calculated by fitting approach using extrapolated semisolid MT reference (EMR) signals, were compared with the magnetization transfer ratio asymmetry (MTRasym ) analysis, commonly used in APT-weighted MRI. RESULTS: The observed NOE signals of all glioma grades were significantly lower than normal brain tissue (P < 0.01). NOE signals significantly differed between low-grade (II) gliomas and high-grade (III, IV) gliomas (P < 0.05). APT signals showed no difference between the tumor regions for any glioma grades (M = 3.08%, 2.64%, and 3.10%, 95% confidence interval [CI] = 2.81% ∼ 3.33%, 2.36% ∼ 2.91%, and 2.85% ∼ 3.36% for grade II, III, and IV, respectively), and between normal brain tissue and all glioma grades (P = 0.08, M = 4.29% and 2.94%, 95% CI = 3.57% ∼ 4.99% and 2.47% ∼ 3.41% for normal and average grade II, III, and IV), while MTRasym differed significantly between normal tissue and all glioma grades (P < 0.05). CONCLUSION: NOE contributes substantially to APT-weighted MRI at 7T at low RF saturation power and provides a promising biomarker for glioma grading.J. Magn. Reson. Imaging 2016;44:41-50.

Magnetic susceptibility contrast variations in multiple sclerosis lesions.

PURPOSE: Recent magnetic resonance imaging (MRI) studies have revealed heterogeneous magnetic susceptibility contrasts in multiple sclerosis (MS) lesions. Due to its sensitivity to disease-related iron and myelin changes, magnetic susceptibility-based measures may better reflect some pathological features of MS lesions. Hence, we sought to characterize MS lesions using combined R2* mapping and quantitative susceptibility mapping (QSM). MATERIALS AND METHODS: In all, 306 MS lesions were selected from 24 MS patients who underwent 7T MRI. Maps of R2*, frequency, and quantitative susceptibility were calculated using acquired multiecho gradient echo (GRE) phase data. Lesions were categorized based on their image intensity or their anatomical locations. R2* and susceptibility values were quantified in each lesion based on manually drawn lesion masks and compared between lesion groups showing different contrast patterns. Correlations between R2* and susceptibility were also tested in these lesion groups. RESULTS: In 38% of selected lesions the frequency map did not show the same contrast pattern as the susceptibility map. While most lesions (93%) showed hypointensity on R2*, the susceptibility contrast in lesions varied, with 40% being isointense and 58% being hyperintense in the lesion core. Significant correlations (r = 0.31, P < 0.001) between R2* and susceptibility were found in susceptibility hyperintense lesions, but not in susceptibility isointense lesions. In addition, a higher proportion (74%) of periventricular lesions was found to be susceptibility hyperintense as compared to subcortical (53%) or juxtacortical (38%) lesions. CONCLUSION: Combining R2* and QSM is useful to characterize heterogeneity in MS lesions.

Thalamic lesions in multiple sclerosis by 7T MRI: Clinical implications and relationship to cortical pathology.

OBJECTIVE: Pathology in both cortex and deep gray matter contribute to disability in multiple sclerosis (MS). We used the increased signal-to-noise ratio of 7-tesla (7T) MRI to visualize small lesions within the thalamus and to relate this to clinical information and cortical lesions. METHODS: We obtained 7T MRI scans on 34 MS cases and 15 healthy volunteers. Thalamic lesion number and volume were related to demographic data, clinical disability measures, and lesions in cortical gray matter. RESULTS: Thalamic lesions were found in 24/34 of MS cases. Two lesion subtypes were noted: discrete, ovoid lesions, and more diffuse lesional areas lining the periventricular surface. The number of thalamic lesions was greater in progressive MS compared to relapsing-remitting (mean ±SD, 10.7 ±0.7 vs. 3.0 ±0.7, respectively, p < 0.001). Thalamic lesion burden (count and volume) correlated with EDSS score and measures of cortical lesion burden, but not with white matter lesion burden or white matter volume. CONCLUSIONS: Using 7T MRI allows identification of thalamic lesions in MS, which are associated with disability, progressive disease, and cortical lesions. Thalamic lesion analysis may be a simpler, more rapid estimate of overall gray matter lesion burden in MS.

Quantitative magnetic susceptibility mapping without phase unwrapping using WASSR.

The magnetic susceptibility of tissue within and around an image voxel affects the magnetic field and thus the local frequency in that voxel. Recently, it has been shown that spatial maps of frequency can be used to quantify local susceptibility if the contributions of surrounding tissue can be deconvolved. Currently, such quantitative susceptibility mapping (QSM) methods employ gradient recalled echo (GRE) imaging to measure spatial differences in the signal phase evolution as a function of echo time, from which frequencies can be deduced. Analysis of these phase images, however, is complicated by phase wraps, despite the availability and usage of various phase unwrapping algorithms. In addition, lengthy high-resolution GRE scanning often heats the magnet bore, causing the magnetic field to drift over several Hertz, which is on the order of the frequency differences between tissues. Here, we explore the feasibility of applying the WAter Saturation Shift Referencing (WASSR) method for 3D whole brain susceptibility imaging. WASSR uses direct saturation of water protons as a function of frequency irradiation offset to generate frequency maps without phase wraps, which can be combined with any image or spectroscopy acquisition. By utilizing a series of fast short-echo-time direct saturation images with multiple radiofrequency offsets, a frequency correction for field drift can be applied based on the individual image phases. Regions of interest were delineated with an automated atlas-based method, and the average magnetic susceptibilities calculated from frequency maps obtained from WASSR correlated well with those from the phase-based multi-echo GRE approach at 3T.

Pattern separation of emotional information in hippocampal dentate and CA3.

Emotional arousal, mediated by the amygdala, is known to modulate episodic memories stored by the hippocampus, a region involved in pattern separation (the process by which similar representations are independently stored). While emotional modulation and pattern separation have been examined independently, this study attempts to link the two areas of research to propose an alternative account for how emotion modulates episodic memory. We used an emotional discrimination task designed to tax pattern separation of emotional information by concurrently varying emotional valence and similarity of stimuli. To examine emotional modulation of memory at the level of hippocampal subfields, we used high-resolution fMRI (1.5 mm isotropic) of the medial temporal lobe. Consistent with prior reports, we observed engagement of the hippocampal dentate gyrus (DG) and CA3 during accurate discrimination of highly similar items (behavioral correlate of pattern separation). Furthermore, we observed an emotional modulation of this signal (negative > neutral) specific to trials on which participants accurately discriminated similar emotional items. The amygdala was also modulated by emotion, regardless of the accuracy of discrimination. Additionally, we found aberrant amygdala-hippocampal network activity in a sample of adults with depressive symptoms. In this sample, amygdala activation was enhanced and DG/CA3 activation was diminished during emotional discrimination compared to those without depressive symptoms. Depressive symptom severity was also negatively correlated with DG/CA3 activity. This study suggests a novel mechanistic account for how emotional information is processed by hippocampal subfields as well as how this network may be altered in mood disorders.

Whole-brain three-dimensional T2-weighted BOLD functional magnetic resonance imaging at 7 Tesla.

PURPOSE: A new acquisition scheme for T2-weighted spin-echo BOLD fMRI is introduced. METHODS: It uses a T2-preparation module to induce blood-oxygenation-level-dependent (BOLD) contrast, followed by a single-shot three-dimensional (3D) fast gradient-echo readout with short echo time (TE). It differs from most spin-echo BOLD sequences in that BOLD contrast is generated before the readout, which eliminates the "dead time" due to long TE required for T2 contrast, and substantially improves acquisition efficiency. This approach, termed "3D T2prep-GRE," was implemented at 7 Tesla (T) with a typical spatial (2.5 × 2.5 × 2.5 mm(3) ) and temporal (TR = 2.3 s) resolution for functional MRI (fMRI) and whole-brain coverage (55 slices), and compared with the widely used 2D spin-echo EPI sequence. RESULTS: In fMRI experiments of simultaneous visual/motor activities, 3D T2prep-GRE showed minimal distortion and little signal dropout across the whole brain. Its lower power deposition allowed greater spatial coverage (55 versus 17 slices with identical TR, resolution and power level), temporal SNR (60% higher) and CNR (35% higher) efficiency than 2D spin-echo EPI. It also showed smaller T2* contamination. CONCLUSION: This approach is expected to be useful for ultra-high field fMRI, especially for regions near air cavities. The concept of using T2-preparation to generate BOLD contrast can be combined with many other sequences at any field strength.

Variable delay multi-pulse train for fast chemical exchange saturation transfer and relayed-nuclear overhauser enhancement MRI.

PURPOSE: Chemical exchange saturation transfer (CEST) imaging is a new MRI technology allowing the detection of low concentration endogenous cellular proteins and metabolites indirectly through their exchangeable protons. A new technique, variable delay multi-pulse CEST (VDMP-CEST), is proposed to eliminate the need for recording full Z-spectra and performing asymmetry analysis to obtain CEST contrast. METHODS: The VDMP-CEST scheme involves acquiring images with two (or more) delays between radiofrequency saturation pulses in pulsed CEST, producing a series of CEST images sensitive to the speed of saturation transfer. Subtracting two images or fitting a time series produces CEST and relayed-nuclear Overhauser enhancement CEST maps without effects of direct water saturation and, when using low radiofrequency power, minimal magnetization transfer contrast interference. RESULTS: When applied to several model systems (bovine serum albumin, crosslinked bovine serum albumin, l-glutamic acid) and in vivo on healthy rat brain, VDMP-CEST showed sensitivity to slow to intermediate range magnetization transfer processes (rate < 100-150 Hz), such as amide proton transfer and relayed nuclear Overhauser enhancement-CEST. Images for these contrasts could be acquired in short scan times by using a single radiofrequency frequency. CONCLUSIONS: VDMP-CEST provides an approach to detect CEST effect by sensitizing saturation experiments to slower exchange processes without interference of direct water saturation and without need to acquire Z-spectra and perform asymmetry analysis.

Asymmetry of the Frontal Aslant Tract Depends on Handedness.

BACKGROUND AND PURPOSE: The human brain displays structural and functional disparities between its hemispheres, with such asymmetry extending to the frontal aslant tract. This plays a role in a variety of cognitive functions, including speech production, language processing, and executive functions. However, the factors influencing the laterality of the frontal aslant tract remain incompletely understood. Handedness is hypothesized to impact frontal aslant tract laterality, given its involvement in both language and motor control. In this study, we aimed to investigate the relationship between handedness and frontal aslant tract lateralization, providing insight into this aspect of brain organization. MATERIALS AND METHODS: The Automated Tractography Pipeline was used to generate the frontal aslant tract for both right and left hemispheres in a cohort of 720 subjects sourced from the publicly available Human Connectome Project in Aging database. Subsequently, macrostructural and microstructural parameters of the right and left frontal aslant tract were extracted for each individual in the study population. The Edinburgh Handedness Inventory scores were used for the classification of handedness, and a comparative analysis across various handedness groups was performed. RESULTS: An age-related decline in both macrostructural parameters and microstructural integrity was noted within the studied population. The frontal aslant tract demonstrated a greater volume and larger diameter in male subjects compared with female participants. Additionally, a left-side laterality of the frontal aslant tract was observed within the general population. In the right-handed group, the volume (P < .001), length (P < .001), and diameter (P = .004) of the left frontal aslant tract were found to be higher than those of the right frontal aslant tract. Conversely, in the left-handed group, the volume (P = .040) and diameter (P = .032) of the left frontal aslant tract were lower than those of the right frontal aslant tract. Furthermore, in the right-handed group, the volume and diameter of the frontal aslant tract showed left-sided lateralization, while in the left-handed group, a right-sided lateralization was evident. CONCLUSIONS: The laterality of the frontal aslant tract appears to differ with handedness. This finding highlights the complex interaction between brain lateralization and handedness, emphasizing the importance of considering handedness as a factor in evaluating brain structure and function.

Automated identification of fleck lesions in Stargardt disease using deep learning enhances lesion detection sensitivity and enables morphometric analysis of flecks.

PURPOSE: To classify fleck lesions and assess artificial intelligence (AI) in identifying flecks in Stargardt disease (STGD). METHODS: A retrospective study of 170 eyes from 85 consecutive patients with confirmed STGD. Fundus autofluorescence images were extracted, and flecks were manually outlined. A deep learning model was trained, and a hold-out testing subset was used to compare with manually identified flecks and for graders to assess. Flecks were clustered using K-means clustering. RESULTS: Of the 85 subjects, 45 were female, and the median age was 37 years (IQR 25-59). A subset of subjects (n=41) had clearly identifiable fleck lesions, and an AI was successfully trained to identify these lesions (average Dice score of 0.53, n=18). The AI segmentation had smaller (0.018 compared with 0.034 mm2, p<0.001) but more numerous flecks (75.5 per retina compared with 40.0, p<0.001), but the total size of flecks was not different. The AI model had higher sensitivity to detect flecks but resulted in more false positives. There were two clusters of flecks based on morphology: broadly, one cluster of small round flecks and another of large amorphous flecks. The per cent frequency of small round flecks negatively correlated with subject age (r=-0.31, p<0.005). CONCLUSIONS: AI-based detection of flecks shows greater sensitivity than human graders but with a higher false-positive rate. With further optimisation to address current shortcomings, this approach could be used to prescreen subjects for clinical research. The feasibility and utility of quantifying fleck morphology in conjunction with AI-based segmentation as a biomarker of progression require further study.

Whole-lesion assessment of volume and signal changes after sclerotherapy of extremity venous malformations.

PURPOSE: To investigate quantitative changes in MRI signal intensity (SI) and lesion volume that indicate treatment response and correlate these changes with clinical outcomes after percutaneous sclerotherapy (PS) of extremity venous malformations (VMs). METHODS: VMs were segmented manually on pre- and post-treatment T2-weighted MRI using 3D Slicer to assess changes in lesion volume and SI. Clinical outcomes were scored on a 7-point Likert scale according to patient perception of symptom improvement; treatment response (success or failure) was determined accordingly. RESULTS: Eighty-one patients with VMs underwent 125 PS sessions. Treatment success occurred in 77 patients (95 %). Mean (±SD) changes were -7.9 ± 24 cm3 in lesion volume and -123 ± 162 in SI (both, P <.001). Mean reduction in lesion volume was greater in the success group (-9.4 ± 24 cm3) than in the failure group (21 ± 20 cm3) (P =.006). Overall, lesion volume correlated with treatment response (ρ = -0.3, P =.004). On subgroup analysis, volume change correlated with clinical outcomes in children (ρ = -0.3, P =.03), in sodium tetradecyl sulfate-treated lesions (ρ = -0.5, P =.02), and in foot lesions (ρ = -0.6, P =.04). SI change correlated with clinical outcomes in VMs treated in 1 PS session (ρ = -0.3, P =.01) and in bleomycin-treated lesions (ρ = -0.4, P =.04). CONCLUSIONS: Change in lesion volume is a reliable indicator of treatment response. Lesion volume and SI correlate with clinical outcomes in specific subgroups.

Deformable registration of preoperative MR and intraoperative long-length tomosynthesis images for guidance of spine surgery via image synthesis.

PURPOSE: Improved integration and use of preoperative imaging during surgery hold significant potential for enhancing treatment planning and instrument guidance through surgical navigation. Despite its prevalent use in diagnostic settings, MR imaging is rarely used for navigation in spine surgery. This study aims to leverage MR imaging for intraoperative visualization of spine anatomy, particularly in cases where CT imaging is unavailable or when minimizing radiation exposure is essential, such as in pediatric surgery. METHODS: This work presents a method for deformable 3D-2D registration of preoperative MR images with a novel intraoperative long-length tomosynthesis imaging modality (viz., Long-Film [LF]). A conditional generative adversarial network is used to translate MR images to an intermediate bone image suitable for registration, followed by a model-based 3D-2D registration algorithm to deformably map the synthesized images to LF images. The algorithm's performance was evaluated on cadaveric specimens with implanted markers and controlled deformation, and in clinical images of patients undergoing spine surgery as part of a large-scale clinical study on LF imaging. RESULTS: The proposed method yielded a median 2D projection distance error of 2.0 mm (interquartile range [IQR]: 1.1-3.3 mm) and a 3D target registration error of 1.5 mm (IQR: 0.8-2.1 mm) in cadaver studies. Notably, the multi-scale approach exhibited significantly higher accuracy compared to rigid solutions and effectively managed the challenges posed by piecewise rigid spine deformation. The robustness and consistency of the method were evaluated on clinical images, yielding no outliers on vertebrae without surgical instrumentation and 3% outliers on vertebrae with instrumentation. CONCLUSIONS: This work constitutes the first reported approach for deformable MR to LF registration based on deep image synthesis. The proposed framework provides access to the preoperative annotations and planning information during surgery and enables surgical navigation within the context of MR images and/or dual-plane LF images.

Investigating axonal damage in multiple sclerosis by diffusion tensor spectroscopy.

Sensitive and specific in vivo measures of axonal damage, an important determinant of clinical status in multiple sclerosis (MS), might greatly benefit prognostication and therapy assessment. Diffusion tensor spectroscopy (DTS) combines features of diffusion tensor imaging and magnetic resonance spectroscopy, allowing measurement of the diffusion properties of intracellular, cell-type-specific metabolites. As such, it may be sensitive to disruption of tissue microstructure within neurons. In this cross-sectional pilot study, diffusion of the neuronal metabolite N-acetylaspartate (NAA) was measured in the human normal-appearing corpus callosum on a 7 tesla MRI scanner, comparing 15 MS patients and 14 healthy controls. We found that NAA parallel diffusivity is lower in MS (p = 0.030) and inversely correlated with both water parallel diffusivity (p = 0.020) and clinical severity (p = 0.015). Interpreted in the context of previous experiments, our findings provide preliminary evidence that DTS can distinguish axonopathy from other processes such as inflammation, edema, demyelination, and gliosis. By detecting reduced diffusion of NAA parallel to axons in white matter, DTS may thus be capable of distinguishing axonal disruption in MS in the setting of increased parallel diffusion of water, which is commonly observed in MS but pathologically nonspecific.

Nuclear Overhauser enhancement (NOE) imaging in the human brain at 7T.

Chemical exchange saturation transfer (CEST) is a magnetization transfer (MT) technique to indirectly detect pools of exchangeable protons through the water signal. CEST MRI has focused predominantly on signals from exchangeable protons downfield (higher frequency) from water in the CEST spectrum. Low power radiofrequency (RF) pulses can slowly saturate protons with minimal interference of conventional semi-solid based MT contrast (MTC). When doing so, saturation-transfer signals are revealed upfield from water, which is the frequency range of non-exchangeable aliphatic and olefinic protons. The visibility of such signals indicates the presence of a relayed transfer mechanism to the water signal, while their finite width reflects that these signals are likely due to mobile solutes. It is shown here in protein phantoms and the human brain that these signals build up slower than conventional CEST, at a rate typical for intramolecular nuclear Overhauser enhancement (NOE) effects in mobile macromolecules such as proteins/peptides and lipids. These NOE-based saturation transfer signals show a pH dependence, suggesting that this process is the inverse of the well-known exchange-relayed NOEs in high resolution NMR protein studies, thus a relayed-NOE CEST process. When studying 6 normal volunteers with a low-power pulsed CEST approach, the relayed-NOE CEST effect was about twice as large as the CEST effects downfield and larger in white matter than gray matter. This NOE contrast upfield from water provides a way to study mobile macromolecules in tissue. First data on a tumor patient show reduction in both relayed NOE and CEST amide proton signals leading to an increase in magnetization transfer ratio asymmetry, providing insight into previously reported amide proton transfer (APT) effects in tumors.

Implementation of vascular-space-occupancy MRI at 7T.

Vascular-space-occupancy (VASO) MRI exploits the difference between blood and tissue T1 to null blood signal and measure cerebral blood volume changes using the residual tissue signal. VASO imaging is more difficult at higher field because of sensitivity loss due to the convergence of tissue and blood T1 values and increased contamination from blood-oxygenation-level-dependent (BOLD) effects. In addition, compared to 3T, 7T MRI suffers from increased geometrical distortions, e.g., when using echo-planar-imaging, and from increased power deposition, the latter especially problematic for the spin-echo-train sequences commonly used for VASO MRI. Third, non-steady-state blood spin effects become substantial at 7T when only a head coil is available for radiofrequency transmit. In this study, the magnetization-transfer-enhanced-VASO approach was applied to maximize tissue-blood signal difference, which boosted signal-to-noise ratio by 149% ± 13% (n = 7) compared to VASO. Second, a 3D fast gradient-echo sequence with low flip-angle (7°) and short echo-time (1.8 ms) was used to minimize the BOLD effect and to reduce image distortion and power deposition. Finally, a magnetization-reset technique was combined with a motion-sensitized-driven-equilibrium approach to suppress three types of non-steady-state spins. Our initial functional MRI results in normal human brains at 7T with this optimized VASO sequence showed better signal-to-noise ratio than at 3T.

Imaging of endogenous exchangeable proton signals in the human brain using frequency labeled exchange transfer imaging.

PURPOSE: To image endogenous exchangeable proton signals in the human brain using a recently reported method called frequency labeled exchange transfer (FLEX) MRI. METHODS: As opposed to labeling exchangeable protons using saturation (i.e., chemical exchange saturation transfer, or CEST), FLEX labels exchangeable protons with their chemical shift evolution. The use of short high-power frequency pulses allows more efficient labeling of rapidly exchanging protons, while time domain acquisition allows removal of contamination from semi-solid magnetization transfer effects. RESULTS: FLEX-based exchangeable proton signals were detected in human brain over the 1-5 ppm frequency range from water. Conventional magnetization transfer contrast and the bulk water signal did not interfere in the FLEX spectrum. The information content of these signals differed from in vivo CEST data in that the average exchange rate of these signals was 350-400 s(-1) , much faster than the amide signal usually detected using direct saturation (∼30 s(-1) ). Similarly, fast exchanging protons could be detected in egg white in the same frequency range where amide and amine protons of mobile proteins and peptides are known to resonate. CONCLUSIONS: FLEX MRI in the human brain preferentially detects more rapidly exchanging amide/amine protons compared to traditional CEST experiments, thereby changing the information content of the exchangeable proton spectrum. This has the potential to open up different types of endogenous applications as well as more easy detection of rapidly exchanging protons in diaCEST agents or fast exchanging units such as water molecules in paracest agents without interference of conventional magnetization transfer contrast.

Time domain removal of irrelevant magnetization in chemical exchange saturation transfer Z-spectra.

PURPOSE: To evaluate the possibility of processing Z-spectra using time domain analysis. METHODS: An inverse Fourier transform (IFT) is applied on Z-spectra, thus transforming the chemical exchange saturation transfer (CEST) data into the time domain. Here, large interfering signals from solvent and semisolid magnetization transfer can be fit and filtered out. The method is demonstrated on a range of phantoms (creatine, a para-CEST agent, and hen egg white) and also in vivo on a mouse brain. RESULTS: Using time domain analysis, signal components in Z-spectra could be fit very well, thus enabling irreverent or nuisance components to be removed. The method worked equally well for samples in a solution or a gel where the large contribution from conventional magnetization transfer contrast (MTC) was easily separated out. Results from egg white and mouse brain in vivo data showed that the large water resonance could easily be removed thus allowing the remaining signal to be analyzed without interference from direct water saturation. CONCLUSIONS: This method successfully filtered out the large nuisance signals from bulk water and MTC in Z-spectra in a large variety of phantom types and also in vivo. It is expected to be a potentially powerful tool for CEST studies without needing asymmetry analysis.

Multiparametric MRI correlates of sensorimotor function in the spinal cord in multiple sclerosis.

BACKGROUND: Spinal cord (SC) pathology is a major contributor to clinical disability in multiple sclerosis (MS). Conventional magnetic resonance imaging (MRI), specifically SC-MRI lesion load measures that include lesion count and volume, demonstrate only a modest relationship with the clinical status of MS patients. Although SC cross-sectional area (CSA) correlates better with clinical dysfunction than MRI lesion count, SC atrophy likely signifies irreversible tissue loss. Using quantitative MRI indices sensitive to early and late microstructural changes in the spinal cord, we searched for the presence of better correlations between MRI measures and clinical status in MS. OBJECTIVES: We investigated whether diffusion-tensor imaging indices and the magnetization-transfer ratio (MTR) were better associated with the clinical status of MS patients than conventional SC-MRI measures. METHODS: A total of 129 MS patients underwent 3-tesla cervical SC-MRI and quantitative sensorimotor function testing, using the Vibratron-II and dynamometer. Regions-of-interest circumscribed the SC on axial slices between C3-C4. We calculated SC-CSA, fractional anisotropy (FA), mean diffusivity (MD), perpendicular diffusivity (λ perpendicular), parallel diffusivity (λ||) and MTR. We used multivariable linear regression to determine if there were any associations between MRI indices and clinical measures of dysfunction. RESULTS: All MRI indices were significantly different in subjects with MS versus healthy controls, and between the progressive versus relapsing MS subtypes, with the exception of λ||. In multivariable regression models that were adjusted for age, sex, brain parenchymal fraction, and SC-CSA, the MRI indices independently explained variability in hip flexion strength (p-values: MD, λ perpendicular, λ|| < 0.001; FA = 0.07), vibration sensation threshold (p-values: FA = 0.04; MTR = 0.05; λ perpendicular = 0.06), and Expanded Disability Status Scale scores (p-values: FA = 0.003; MD = 0.03; λ perpendicular = 0.005; MTR = 0.02). CONCLUSIONS: In a large, heterogeneous MS sample, quantitative SC-MRI indices demonstrated independent associations with system-specific and global clinical dysfunction. Our findings suggest that the indices studied may provide important information about microstructural SC changes and the substrates of limb disability in MS. The identified structure-function relationships underpin the potential utility of these measures in assessments of therapeutic efficacy.