Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task.

Introduction: Approximately one in six people will experience an episode of major depressive disorder (MDD) in their lifetime. Effective treatment is hindered by subjective clinical decision-making and a lack of objective prognostic biomarkers. Functional MRI (fMRI) could provide such an objective measure but the majority of MDD studies has focused on static approaches, disregarding the rapidly changing nature of the brain. In this study, we aim to predict depression severity changes at 3 and 6 months using dynamic fMRI features. Methods: For our research, we acquired a longitudinal dataset of 32 MDD patients with fMRI scans acquired at baseline and clinical follow-ups 3 and 6 months later. Several measures were derived from an emotion face-matching fMRI dataset: activity in brain regions, static and dynamic functional connectivity between functional brain networks (FBNs) and two measures from a wavelet coherence analysis approach. All fMRI features were evaluated independently, with and without demographic and clinical parameters. Patients were divided into two classes based on changes in depression severity at both follow-ups. Results: The number of coherence clusters (nCC) between FBNs, reflecting the total number of interactions (either synchronous, anti-synchronous or causal), resulted in the highest predictive performance. The nCC-based classifier achieved 87.5% and 77.4% accuracy for the 3- and 6-months change in severity, respectively. Furthermore, regression analyses supported the potential of nCC for predicting depression severity on a continuous scale. The posterior default mode network (DMN), dorsal attention network (DAN) and two visual networks were the most important networks in the optimal nCC models. Reduced nCC was associated with a poorer depression course, suggesting deficits in sustained attention to and coping with emotion-related faces. An ensemble of classifiers with demographic, clinical and lead coherence features, a measure of dynamic causality, resulted in a 3-months clinical outcome prediction accuracy of 81.2%. Discussion: The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts.

Fast 19 F spectroscopic imaging with pseudo-spiral k-space sampling.

Fluorine MRI is finding wider acceptance in theranostics applications where imaging of 19 F hotspots of fluorinated contrast material is central. The essence of such applications is to capture ghosting-artifact-free images of the inherently low MR response under clinically viable conditions. To serve this purpose, this work introduces the balanced spiral spectroscopic imaging (BaSSI) sequence, which is implemented on a 3.0 T clinical scanner and is capable of generating 19 F hotspot images in an efficient manner. The sequence utilizes an all-phase-encoded pseudo-spiral k-space trajectory, enabling the acquisition of broadband (80 ppm) fluorine spectra free from chemical shift ghosting. BaSSI can acquire a 64 × 64 image with 1 mm × 1 mm voxels in just 14 s, significantly outperforming typical MRSI sequences used in 1 H or 31 P imaging. The study employed in silico characterization to verify essential design choices such as the excitation pulse, as well as to identify the boundaries of the parameter space explored for optimization. BaSSI's performance was further benchmarked against the 3D ultrashort-echo-time balanced steady-state free precession (3D UTE BSSFP) sequence, a well established method used in 19 F MRI, in vitro. Both sequences underwent extensive optimization through exploration of a wide parameter space on a small phantom containing 10 µL of non-diluted bulk perfluorooctylbromide (PFOB) prior to comparative experiments. Subsequent to optimization, BaSSI and 3D UTE BSSFP were employed to capture images of small non-diluted bulk PFOB samples (0.10 and 0.05 µL), with variations in the number of signal averages, and thus the total scan time, in order to assess the detection sensitivities of the sequences. In these experiments, the detection sensitivity was evaluated using the Rose criterion (Rc ), which provides a quantitative metric for assessing object visibility. The study further demonstrated BaSSI's utility as a (pre)clinical tool through postmortem imaging of polymer microspheres filled with PFOB in a BALB/c mouse. Anatomic localization of 19 F hotspots was achieved by denoising raw data obtained with BaSSI using a filter based on the Rose criterion. These data were then successfully registered to 1 H anatomical images. BaSSI demonstrated superior detection sensitivity in the benchmarking analysis, achieving Rc values approximately twice as high as those obtained with the 3D UTE BSSFP method. The technique successfully facilitated imaging and precise localization of 19 F hotspots in postmortem experiments. However, it is important to highlight that imaging 10 mM PFOB in small mice postmortem, utilizing a 48 × 48 × 48 3D scan, demanded a substantial scan time of 1 h and 45 min. Further studies will explore accelerated imaging techniques, such as compressed sensing, to enhance BaSSI's clinical utility.

Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects.

Objective diagnosis and prognosis in major depressive disorder (MDD) remains a challenge due to the absence of biomarkers based on physiological parameters or medical tests. Numerous studies have been conducted to identify functional magnetic resonance imaging-based biomarkers of depression that either objectively differentiate patients with depression from healthy subjects, predict personalized treatment outcome, or characterize biological subtypes of depression. While there are some findings of consistent functional biomarkers, there is still lack of robust data acquisition and analysis methodology. According to current findings, primarily, the anterior cingulate cortex, prefrontal cortex, and default mode network play a crucial role in MDD. Yet, there are also less consistent results and the involvement of other regions or networks remains ambiguous. We further discuss image acquisition, processing, and analysis limitations that might underlie these inconsistencies. Finally, the current review aims to address and discuss possible remedies and future opportunities that could improve the search for consistent functional imaging biomarkers of depression. Novel acquisition techniques, such as multiband and multiecho imaging, and neural network-based cleaning approaches can enhance the signal quality in limbic and frontal regions. More comprehensive analyses, such as directed or dynamic functional features or the identification of biological depression subtypes, can improve objective diagnosis or treatment outcome prediction and mitigate the heterogeneity of MDD. Overall, these improvements in functional MRI imaging techniques, processing, and analysis could advance the search for biomarkers and ultimately aid patients with MDD and their treatment course.

The effects of multi-echo fMRI combination and rapid T2*-mapping on offline and real-time BOLD sensitivity.

A variety of strategies are used to combine multi-echo functional magnetic resonance imaging (fMRI) data, yet recent literature lacks a systematic comparison of the available options. Here we compare six different approaches derived from multi-echo data and evaluate their influences on BOLD sensitivity for offline and in particular real-time use cases: a single-echo time series (based on Echo 2), the real-time T2*-mapped time series (T2*FIT) and four combined time series (T2*-weighted, tSNR-weighted, TE-weighted, and a new combination scheme termed T2*FIT-weighted). We compare the influences of these six multi-echo derived time series on BOLD sensitivity using a healthy participant dataset (N = 28) with four task-based fMRI runs and two resting state runs. We show that the T2*FIT-weighted combination yields the largest increase in temporal signal-to-noise ratio across task and resting state runs. We demonstrate additionally for all tasks that the T2*FIT time series consistently yields the largest offline effect size measures and real-time region-of-interest based functional contrasts and temporal contrast-to-noise ratios. These improvements show the promising utility of multi-echo fMRI for studies employing real-time paradigms, while further work is advised to mitigate the decreased tSNR of the T2*FIT time series. We recommend the use and continued exploration of T2*FIT for offline task-based and real-time region-based fMRI analysis. Supporting information includes: a data repository (https://dataverse.nl/dataverse/rt-me-fmri), an interactive web-based application to explore the data (https://rt-me-fmri.herokuapp.com/), and further materials and code for reproducibility (https://github.com/jsheunis/rt-me-fMRI).

Quality and denoising in real-time functional magnetic resonance imaging neurofeedback: A methods review.

Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open-source rtfMRI-NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality-and-denoising-in-rtfmri-nf.

Neu3CA-RT: A framework for real-time fMRI analysis.

Real-time functional magnetic resonance imaging (rtfMRI) allows visualisation of ongoing brain activity of the subject in the scanner. Denoising algorithms aim to rid acquired data of confounding effects, enhancing the blood oxygenation level-dependent (BOLD) signal. Further image processing and analysis methods, like general linear models (GLM) or multivariate analysis, then present application-specific information to the researcher. These processes are typically applied to regions of interest but, increasingly, rtfMRI techniques extract and classify whole brain functional networks and dynamics as correlates for brain states or behaviour, particularly in neuropsychiatric and neurocognitive disorders. We present Neu3CA-RT: a Matlab-based rtfMRI analysis framework aiming to advance scientific knowledge on real-time cognitive brain activity and to promote its translation into clinical practice. Design considerations are listed based on reviewing existing rtfMRI approaches. The toolbox integrates established SPM preprocessing routines, real-time GLM mapping of fMRI data to a basis set of spatial brain networks, correlation of activity with 50 behavioural profiles from the BrainMap database, and an intuitive user interface. The toolbox is demonstrated in a task-based experiment where a subject executes visual, auditory and motor tasks inside a scanner. In three out of four experiments, resulting behavioural profiles agreed with the expected brain state.

Functional network abnormalities consistent with behavioral profile in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in which the severity of symptoms varies over subjects. The iCAPs model (innovation-driven co-activation patterns) is a recently developed spatio-temporal model to describe fMRI data. In this study, the iCAPs model was employed to find functional imaging biomarkers for ASD in resting-state fMRI data. MRI data from 125 ASD patients and 243 healthy controls was selected from the online ABIDE data repository. Following standard fMRI preprocessing steps, the iCAP patterns were fitted to the data to obtain network time series. Furthermore, specific combinations of iCAPs were mapped to behavioral domain time series. To quantify to which extent the time series contribute to the fMRI dynamics, their (temporal) standard deviation was calculated and compared between patients and controls. Abnormalities were found in networks involving subcortical and limbic areas and default mode network regions. When mapping the network dynamics to behavioral domain time series, abnormalities were found in emotional and visual behavioral subdomains, and within the ASD spectrum were more pronounced in subjects with autism compared to Asperger's syndrome. Also a trend towards impairment in networks facilitating social cognition was found. The functional imaging abnormalities are consistent with the behavioral impairments typical for ASD.

Gradient Artefact Correction and Evaluation of the EEG Recorded Simultaneously with fMRI Data Using Optimised Moving-Average.

Over the past years, coregistered EEG-fMRI has emerged as a powerful tool for neurocognitive research and correlated studies, mainly because of the possibility of integrating the high temporal resolution of the EEG with the high spatial resolution of fMRI. However, additional work remains to be done in order to improve the quality of the EEG signal recorded simultaneously with fMRI data, in particular regarding the occurrence of the gradient artefact. We devised and presented in this paper a novel approach for gradient artefact correction based upon optimised moving-average filtering (OMA). OMA makes use of the iterative application of a moving-average filter, which allows estimation and cancellation of the gradient artefact by integration. Additionally, OMA is capable of performing the attenuation of the periodic artefact activity without accurate information about MRI triggers. By using our proposed approach, it is possible to achieve a better balance than the slice-average subtraction as performed by the established AAS method, regarding EEG signal preservation together with effective suppression of the gradient artefact. Since the stochastic nature of the EEG signal complicates the assessment of EEG preservation after application of the gradient artefact correction, we also propose a simple and effective method to account for it.

89 Zr- and Fe-Labeled Polymeric Micelles for Dual Modality PET and T1 -Weighted MR Imaging.

In this study, a new 89 Zr- and Fe3+ -labeled micelle nanoplatform (89 Zr/Fe-DFO-micelles) for dual modality position emission tomography/magnetic resonance (PET/MR) imaging is investigated. The nanoplatform consists of self-assembling amphiphilic diblock copolymers that are functionalized with 89 Zr-deferoxamine (89 Zr-DFO) and Fe3+ -deferoxamine (Fe-DFO) for PET and MR purposes, respectively. 89 Zr displays favorable PET imaging characteristics with a 3.3 d half-life suitable for imaging long circulating nanoparticles. The nanoparticles are modified with Fe-DFO as MR T1 -contrast label instead of commonly used Gd3+ -based chelates. As these micelles are cleared by liver and spleen, any long term Gd- related toxicity such as nephrogenic systemic fibrosis is avoided. As a proof of concept, an in vivo PET/MR study in mice is presented showing tumor targeting of 89 Zr/Fe-DFO-micelles through the enhanced permeability and retention (EPR) effect of tumors, yielding high tumor-to-blood (10.3 ± 3.6) and tumor-to-muscle (15.3 ± 8.1) ratios at 48 h post injection. In vivo PET images clearly delineate the tumor tissue and show good correspondence with ex vivo biodistribution results. In vivo magnetic resonance imaging (MRI) allows visualization of the intratumoral distribution of the 89 Zr/Fe-DFO-micelles at high resolution. In summary, the 89 Zr/Fe-DFO-micelle nanoparticulate platform allows EPR-based tumor PET/MRI, and, furthermore, holds great potential for PET/MR image guided drug delivery.

Relaxometric studies of gadolinium-functionalized perfluorocarbon nanoparticles for MR imaging.

Fluorine MRI ((19) F MRI) is receiving an increasing attention as a viable alternative to proton-based MRI ((1) H MRI) for dedicated application in molecular imaging. The (19) F nucleus has a high gyromagnetic ratio, a 100% natural abundance and is furthermore hardly present in human tissues allowing for hot spot MR imaging. The applicability of (19) F MRI as a molecular and cellular imaging technique has been exploited, ranging from cell tracking to detection and imaging of tumors in preclinical studies. In addition to applications, developing new contrast materials with improved relaxation properties has also been a core research topic in the field, since the inherently low longitudinal relaxation rates of perfluorocarbon compounds result in relatively low imaging efficiency. Borrowed from (1) H MRI, the incorporation of lanthanides, specifically Gd(III) complexes, as signal modulating ingredients in the nanoparticle formulation has emerged as a promising approach to improvement of the fluorine signal. Three different perfluorocarbon emulsions were investigated at five different magnetic field strengths. Perfluoro-15-crown-5-ether was used as the core material and Gd(III)DOTA-DSPE, Gd(III)DOTA-C6-DSPE and Gd(III)DTPA-BSA as the relaxation altering components. While Gd(III)DOTA-DSPE and Gd(III)DOTA-C6-DSPE were favorable constructs for (1) H NMR, Gd(III)DTPA-BSA showed the strongest increase in (19F) R(1). These results show the potential of the use of paramagnetic lipids to increase (19F) R(1) at clinical field strengths (1.5-3 T). At higher field strengths (6.3-14 T), gadolinium does not lead to an increase in (19F) R(1) compared with emulsions without gadolinium, but leads to an significant increase in (19F) R(2). Our data therefore suggest that the most favorable situation for fluorine measurements is at high magnetic fields without the inclusion of gadolinium constructs.

Noninvasive automated motion assessment of intestinal motility by continuously tagged MR imaging.

PURPOSE: To evaluate continuously tagged 3 Tesla MRI for monitoring glucagon-induced bowel motility changes in healthy volunteers. MATERIALS AND METHODS: After standardized oral bowel preparation, 10 healthy volunteers underwent a free-breathing, continuously tagged three-dimensional (3D) dynamic fast-field-echo (FFE), at a 3.36 Hz sampling frequency. One milligram of glucagon was administered intravenously during data acquisition. Each dataset was divided into four temporal sets of 2 min (period 1 to 4). Taglines were tracked automatically using a scale spaced based algorithm. Assessment of global spectral resolution was performed for three frequency intervals: 0.008-0.300 Hz (motility), 0.300-0.400 Hz (breathing motion), and 0.400-0.533 Hz (higher order motion). Additional analyses were performed at fine spectral resolution in frequency bands of 0.033 Hz. Glucagon-induced motility changes were investigated by means of a motility index (spectral power normalized to the maximal spectral power per-volunteer), resulting in a range of 0 to 1 (no motion to maximal motion). Statistical comparison was done for period 1 and 4 (Wilcoxon-signed rank test). RESULTS: After glucagon administration, a significant decrease in the motility index was found for the low- (0.008-0.300 Hz) (P < 0.0001) and high-frequency interval (0.400-0.533 Hz) (P < 0.0001). Around breathing motion frequencies, no decrease in motility index was detected. CONCLUSION: Free-breathing, continuously tagged MR imaging is a noninvasive method for automated bowel motility assessment and allows for detection of drug-induced changes.

A scale space based algorithm for automated segmentation of single shot tagged MRI of shearing deformation.

OBJECT: This study proposes a scale space based algorithm for automated segmentation of single-shot tagged images of modest SNR. Furthermore the algorithm was designed for analysis of discontinuous or shearing types of motion, i.e. segmentation of broken tag patterns. MATERIALS AND METHODS: The proposed algorithm utilises non-linear scale space for automatic segmentation of single-shot tagged images. The algorithm's ability to automatically segment tagged shearing motion was evaluated in a numerical simulation and in vivo. A typical shearing deformation was simulated in a Shepp-Logan phantom allowing for quantitative evaluation of the algorithm's success rate as a function of both SNR and the amount of deformation. For a qualitative in vivo evaluation tagged images showing deformations in the calf muscles and eye movement in a healthy volunteer were acquired. RESULTS: Both the numerical simulation and the in vivo tagged data demonstrated the algorithm's ability for automated segmentation of single-shot tagged MR provided that SNR of the images is above 10 and the amount of deformation does not exceed the tag spacing. The latter constraint can be met by adjusting the tag delay or the tag spacing. CONCLUSION: The scale space based algorithm for automatic segmentation of single-shot tagged MR enables the application of tagged MR to complex (shearing) deformation and the processing of datasets with relatively low SNR.

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation.

PURPOSE: Typically spatial modulation of the magnetization (SPAMM) tagged magnetic resonance imaging (MRI) requires many repeated motion cycles limiting the applicability to highly repeatable tissue motions only. This paper describes the validation of a novel SPAMM tagged MRI and post-processing framework for the measurement of complex and dynamic 3D soft tissue deformation following just three motion cycles. Techniques are applied to indentation induced deformation measurement of the upper arm and a silicone gel phantom. METHODS: A SPAMM tagged MRI methodology is presented allowing continuous (3.3-3.6 Hz) sampling of 3D dynamic soft tissue deformation using non segmented 3D acquisitions. The 3D deformation is reconstructed by the combination of three mutually orthogonal tagging directions, thus requiring only three repeated motion cycles. In addition a fully automatic post-processing framework is presented employing Gabor scale-space and filter-bank analysis for tag extrema segmentation and triangulated surface fitting aided by Gabor filter bank derived surface normals. Deformation is derived following tracking of tag surface triplet triangle intersections. The dynamic deformation measurements were validated using indentation tests (∼20 mm deep at 12 mm/s) on a silicone gel soft tissue phantom containing contrasting markers which provide a reference measure of deformation. In addition, the techniques were evaluated in vivo for dynamic skeletal muscle tissue deformation measurement during indentation of the biceps region of the upper arm in a volunteer. RESULTS: For the phantom and volunteer tag point location precision were 44 and 92 µm, respectively resulting in individual displacements precisions of 61 and 91 µm, respectively. For both the phantom and volunteer data cumulative displacement measurement accuracy could be evaluated and the difference between initial and final locations showed a mean and standard deviation of 0.44 and 0.59 mm for the phantom and 0.40 and 0.73 mm for the human data. Finally accuracy of (cumulative) displacement was evaluated using marker tracking in the silicone gel phantom. Differences between true and predicted marker locations showed a mean of 0.35 mm and a standard deviation of 0.63 mm. CONCLUSIONS: A novel SPAMM tagged MRI and fully automatic post-processing framework for the measurement of complex 3D dynamic soft tissue deformation following just three repeated motion cycles was presented. The techniques demonstrate dynamic measurement of complex 3D soft tissue deformation at subvoxel accuracy and precision and were validated for 3.3-3.6 Hz sampling of deformation speeds up to 12 mm/s.

Use of continuously MR tagged imaging for automated motion assessment in the abdomen: a feasibility study.

PURPOSE: To investigate the feasibility of measuring motion in the abdomen using a continuously tagged magnetic resonance imaging sequence. MATERIALS AND METHODS: To assess (nonperiodic) motion in the abdomen, a nontriggered, continuously tagged transient field echo (TFE) sequence was implemented that acquires one complete 3D dataset per prepulse after a fixed delay. In postprocessing, a frequency analysis approach was developed for compact reviewing of the data and noise suppression. For proof of principle, a simulation was made and one free-breathing dynamic in vivo scan was acquired in a healthy volunteer. During the dynamic scan the volunteer received glucagon intravenously. RESULTS: The simulation showed that this frequency analysis enables the extraction of motion at low signal-to-noise ratio levels. Motion information was successfully gathered from the in vivo scan. The decline in bowel motion caused by the administration of glucagon could be quantitatively measured using the continuously tagged sequence. CONCLUSION: Continuously tagged imaging in the abdomen for the purpose of automated gathering of motion information is feasible and could aid the study of bowel motion.

Validation of interventional fiber optic spectroscopy with MR spectroscopy, MAS-NMR spectroscopy, high-performance thin-layer chromatography, and histopathology for accurate hepatic fat quantification.

OBJECTIVES: To validate near-infrared (NIR)-based optical spectroscopy measurements of hepatic fat content using a minimally invasive needle-like probe with integrated optical fibers, enabling real-time feedback during percutaneous interventions. The results were compared with magnetic resonance spectroscopy (MRS) as validation and with histopathology, being the clinical gold standard. Additionally, ex vivo magic angle spinning nuclear magnetic resonance spectroscopy and high-performance thin-layer chromatography were performed for comparison. MATERIALS AND METHODS: Ten mice were used for the study, of which half received a regular chow diet and the other half received a high-fat diet to induce obesity and hepatosteatosis. The mice were imaged with a clinical 3-Tesla MR to select a region of interest within the right and left lobes of the liver, where MRS measurements were acquired in vivo. Subsequently, optical spectra were measured ex vivo at the surface of the liver at 6 different positions immediately after resection. Additionally, hepatic fat was determined by magic angle spinning nuclear magnetic resonance spectroscopy and high-performance thin-layer chromatography. Histopathologic analyses were performed and used as the reference standard. Pearson correlation and linear regression analyses were performed to assess the correlation of the various techniques with NIR. A 1-way analysis of variance including post hoc Tukey multiple comparison tests was used to study the difference in fat estimation between the various techniques. RESULTS: For both the mice groups, the estimated fat fractions by the various techniques were significantly similar (P = 0.072 and 0.627 for chow diet and high-fat diet group, respectively). The Pearson correlation value between NIR and the other techniques for fat determination showed the same strong linear correlation (P above 0.990; P < 0.001), whereas for histopathologic analyses, which is a rather qualitative measure, the Pearson correlation value was slightly lower (P = 0.925, P < 0.001) . Linear regression coefficient computed to compare NIR with the other techniques resulted in values close to unity with MRS having the narrowest confidence interval (r = 0.935, 95% confidence interval: 0.860-1.009), demonstrating highly correlating results between NIR and MRS. CONCLUSIONS: NIR spectroscopy measurements from a needle-like probe with integrated optical fibers for sensing at the tip of the needle can quickly and accurately determine hepatic fat content during an interventional procedure and might therefore be a promising novel diagnosing tool in the clinic.

Validation of SPAMM tagged MRI based measurement of 3D soft tissue deformation.

PURPOSE: This study presents and validates a novel (non-ECG-triggered) MRI sequence based on spatial modulation of the magnetization (SPAMM) to noninvasively measure 3D (quasistatic) soft tissue deformations using only six acquisitions (three static and three indentations). In the current SPAMM tagged MRI approaches, data are typically constructed from many repeated motion cycles. This has so far restricted its application to the measurement of highly repeatable and periodic movements (e.g., cardiac deformation). In biomechanical applications where soft tissue deformation is artificially induced, often by indentation, significant repeatability constraints exist, and for clinical applications, discomfort and health issues generally preclude a large number of repetitions. METHODS: A novel (non-ECG-triggered) SPAMM tagged MRI sequence is presented, whereby a single 1-1 (first order) SPAMM set is acquired following a 3D transient field echo acquisition. Full 3D deformation measurement is achieved through the combination of only six acquisitions (three static and three motion cycles). The 3D deformation measurements were validated using quasistatic indentation tests and marker tracking in a silicone gel soft tissue phantom. In addition, the technique's ability to measure 3D soft tissue deformation in vivo was evaluated using indentation of the biceps region of the upper arm in a volunteer. RESULTS: Following comparison to marker tracking in the silicone gel phantom, the SPAMM tagged MRI based displacement measurement demonstrated subvoxel accuracy with a mean displacement difference of 72 microm and a standard deviation of 289 microm. In addition, precision of displacement magnitude was evaluated for both the phantom and the volunteer data. The standard deviations of the displacement magnitude with respect to the average displacement magnitude were 75 and 169 microm for the phantom and volunteer data, respectively. CONCLUSIONS: The subvoxel accuracy and precision demonstrated in the phantom in combination with the precision comparison between the phantom and the volunteer data provide confidence in the methods presented for measurement of soft tissue deformation in vivo. To the author's knowledge, since only six acquisitions are required, the presented methodology is the fastest SPAMM tagged MRI method currently available for the noninvasive measurement of quasistatic 3D soft tissue deformation.

In vitro demonstration using 19F magnetic resonance to augment molecular imaging with paramagnetic perfluorocarbon nanoparticles at 1.5 Tesla.

OBJECTIVES: This study explored the use of F spectroscopy and imaging with targeted perfluorocarbon nanoparticles for the simultaneous identification of multiple bio-signatures at 1.5 T. MATERIALS AND METHODS: Two nanoparticle emulsions with perfluoro-15-crown-5-ether (CE) or perfluorooctylbromide (PFOB) cores were targeted in vitro to fibrin clot phantoms (n=12) in 4 progressive ratios using biotin-avidin interactions. The CE nanoparticles incorporated gadolinium. Fluorine images were acquired using steady-state gradient-echo techniques; spectra using volume-selective and nonselective sampling. RESULTS: On conventional T1-weighted imaging, clots with CE nanoparticles enhanced as expected, with intensity decreasing monotonically with CE concentration. All clots were visualized using wide bandwidth fluorine imaging, while restricted bandwidth excitation permitted independent imaging of CE or PFOB nanoparticles. Furthermore, F imaging and spectroscopy allowed visual and quantitative confirmation of relative perfluorocarbon nanoparticle distributions. CONCLUSIONS: F MRI/S molecular imaging of perfluorocarbon nanoparticles in vitro suggests that noninvasive phenotypic characterization of pathologic bio-signatures is feasible at clinical field strengths.

Optimizing PRESS localized citrate detection at 3 Tesla.

Analytical methods are used to characterize the response of the strongly coupled two-spin system of citrate to point-resolved spectroscopy (PRESS)-based sequences at 3 T. The signal output is analyzed line by line, as well as in the Cartesian product operator basis. Patterns with a periodicity of 80.9 ms are identified. Furthermore, it is shown that at TE = n . 80.9 ms (n in {0,1,2,...}), the spin evolution can be described without direct reference to strong coupling terms. The theoretical results are found to be in good agreement with in vivo experiments. These results can be used to design protocols for prostate MRS and MRSI at 3 T, and give guidelines for optimizing spin-echo-based acquisition schemes for detecting two-spin systems at arbitrary field strengths.

Catheter tracking and visualization using 19F nuclear magnetic resonance.

This work presents an investigation into catheter visualization and localization using 19F nuclear magnetic resonance (NMR) in conjunction with proton imaging. For this purpose, the imaging capabilities of a standard system were extended to allow for 19F excitation and signal detection. Two modes of operation were implemented: 1) a real-time tracking mode that provides tip tracking and automatic slice position updates interleaved with real-time, interactive proton imaging; and 2) a non-real-time catheter length visualization mode in which the entire length of a catheter can be assessed. Initial phantom experiments were conducted with the use of an angiographic balloon catheter filled with the blood substitute perfluorooctylbromide (PFOB). Using limited bandwidth excitation centered at the resonances of the CF2 groups of PFOB, we found that sufficient signal could be received to facilitate tip tracking during catheter motion and length visualization for various catheter configurations. The present approach is considered a promising alternative to existing methods, which either are associated with safety concerns (if active markers are employed) or suffer from insufficient, direction-dependent contrast (if passive visualization is used). Furthermore, our approach enables visualization of the entire length of the catheter. The proposed method provides a safe technique that, unlike electrical or optical devices, does not require modification of commercially available catheters.

1H metabolite relaxation times at 3.0 tesla: Measurements of T1 and T2 values in normal brain and determination of regional differences in transverse relaxation.

PURPOSE: To measure 1H relaxation times of cerebral metabolites at 3 T and to investigate regional variations within the brain. MATERIALS AND METHODS: Investigations were performed on a 3.0-T clinical whole-body magnetic resonance (MR) system. T2 relaxation times of N-acetyl aspartate (NAA), total creatine (tCr), and choline compounds (Cho) were measured in six brain regions of 42 healthy subjects. T1 relaxation times of these metabolites and of myo-inositol (Ins) were determined in occipital white matter (WM), the frontal lobe, and the motor cortex of 10 subjects. RESULTS: T2 values of all metabolites were markedly reduced with respect to 1.5 T in all investigated regions. T2 of NAA was significantly (P < 0.001) shorter in the motor cortex (247 +/- 13 msec) than in occipital WM (301 +/- 18 msec). T2 of the tCr methyl resonance showed a corresponding yet less pronounced decrease (162 +/- 16 msec vs. 178 +/- 9 msec, P = 0.021). Even lower T2 values for all metabolites were measured in the basal ganglia. Metabolite T1 relaxation times at 3.0 T were not significantly different from the values at 1.5 T. CONCLUSION: Transverse relaxation times of the investigated cerebral metabolites exhibit an inverse proportionality to magnetic field strength, and especially T2 of NAA shows distinct regional variations at 3 T. These can be attributed to differences in relative WM/gray matter (GM) contents and to local paramagnetism.