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BACKGROUND: The Cubresa Spark is a novel benchtop silicon-photomultiplier (SiPM)-based preclinical SPECT system. SiPMs in SPECT significantly improve resolution and reduce detector size compared to preclinical cameras with photomultiplier tubes requiring highly magnifying collimators. The NEMA NU 1 Standard for Performance Measurements of Gamma Cameras provides methods that can be readily applied or extended to characterize preclinical cameras with minor modifications. The primary objective of this study is to characterize the Spark according to the NEMA NU 1-2018 standard to gain insight into its nuclear medicine imaging capabilities. The secondary objective is to validate a GATE Monte Carlo simulation model of the Spark for use in preclinical SPECT studies. METHODS: NEMA NU 1-2018 guidelines were applied to characterize the Spark's intrinsic, system, and tomographic performance with single- and multi-pinhole collimators. Phantoms were fabricated according to NEMA specifications with deviations involving high-resolution modifications. GATE was utilized to model the detector head with the single-pinhole collimator, and NEMA measurements were employed to tune and validate the model. Single-pinhole and multi-pinhole SPECT data were reconstructed with the Software for Tomographic Image Reconstruction and HiSPECT, respectively. RESULTS: The limiting intrinsic resolution was measured as 0.85 mm owing to a high-resolution SiPM array combined with a 3 mm-thick scintillation crystal. The average limiting tomographic resolution was 1.37 mm and 1.19 mm for the single- and multi-pinhole collimators, respectively, which have magnification factors near unity at the center of rotation. The maximum observed count rate was 15,400 cps, and planar sensitivities of 34 cps/MBq and 150 cps/MBq were measured at the center of rotation for the single- and multi-pinhole collimators, respectively. All simulated tests agreed well with measurement, where the most considerable deviations were below 7%. CONCLUSIONS: NEMA NU 1-2018 standards determined that a SiPM detector mitigates the need for highly magnifying pinhole collimators while preserving detailed information in projection images. Measured and simulated NEMA results were highly comparable with differences on the order of a few percent, confirming simulation accuracy and validating the GATE model. Of the collimators initially provided with the Spark, the multi-pinhole collimator offers high resolution and sensitivity for organ-specific imaging of small animals, and the single-pinhole collimator enables high-resolution whole-body imaging of small animals.

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OBJECTIVE: Extensive blood-brain barrier (BBB) leakage has been linked to cognitive impairment in SLE. This study aimed to examine the associations of brain functional connectivity (FC) with cognitive impairment and BBB dysfunction among patients with SLE. METHODS: Cognitive function was assessed by neuropsychological testing (n = 77). Resting-state FC (rsFC) between brain regions, measured by functional MRI (n = 78), assessed coordinated neural activation in 131 regions across five canonical brain networks. BBB permeability was measured by dynamic contrast-enhanced MRI (n = 61). Differences in rsFC were compared between SLE patients with cognitive impairment (SLE-CI) and those with normal cognition (SLE-NC), between SLE patients with and without extensive BBB leakage, and with healthy controls. RESULTS: A whole-brain rsFC comparison found significant differences in intra-network and inter-network FC in SLE-CI vs SLE-NC patients. The affected connections showed a reduced negative rsFC in SLE-CI compared with SLE-NC and healthy controls. Similarly, a reduced number of brain-wide connections was found in SLE-CI patients compared with SLE-NC (P = 0.030) and healthy controls (P = 0.006). Specific brain regions had a lower total number of brain-wide connections in association with extensive BBB leakage (P = 0.011). Causal mediation analysis revealed that 64% of the association between BBB leakage and cognitive impairment in SLE patients was mediated by alterations in FC. CONCLUSION: SLE patients with cognitive impairment had abnormalities in brain rsFC which accounted for most of the association between extensive BBB leakage and cognitive impairment.

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OBJECTIVE: Cognitive impairment is common in patients with SLE but the cause is unknown. The current cross-sectional study examined the association between select SLE-related autoantibodies, other serological biomarkers and extensive blood-brain barrier (BBB) leakage in patients with SLE with and without cognitive impairment. In addition, we determined whether the relationship between SLE autoantibodies, other biomarkers and cognitive impairment differed depending on the presence or absence of concurrent extensive BBB leakage. METHODS: Consecutive patients with SLE, recruited from a single academic medical centre, underwent formal neuropsychological testing for assessment of cognitive function. On the same day, BBB permeability was determined using dynamic contrast-enhanced MRI scanning. SLE autoantibodies and other serological biomarkers were measured. Regression modelling was used to determine the association between cognitive impairment, extensive BBB leakage and autoantibodies/biomarkers. RESULTS: There were 102 patients with SLE; 90% were female and 88% were Caucasian, with a mean±SD age of 48.9±13.8 years. The mean±SD SLE disease duration was 14.8±11.0 years. Impairment in one or more cognitive tests was present in 47 of 101 (47%) patients and included deficits in information processing speed (9%), attention span (21%), new learning (8%), delayed recall (15%) and executive abilities (21%). Extensive BBB leakage was present in 20 of 79 (25%) patients and was associated with cognitive impairment (15 of 20 (75%) vs 24 of 59 (41%); p=0.01) and shorter disease duration (median (IQR): 7 (8-24 years) vs 15 (2-16 years); p=0.02). No serological parameters were associated with extensive BBB leakage and there was no statistically significant association between cognitive impairment and circulating autoantibodies even after adjusting for BBB leakage. CONCLUSIONS: Extensive BBB leakage alone was associated with cognitive impairment. These findings suggest that BBB leakage is an important contributor to cognitive impairment, regardless of circulating SLE-related autoantibodies.

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PURPOSE: Multiparametric MRI (mp-MRI) is a widely used tool for diagnosing and staging prostate cancer. The purpose of this study was to evaluate whether transfer learning, unsupervised pre-training and test-time augmentation significantly improved the performance of a convolutional neural network (CNN) for pixel-by-pixel prediction of cancer vs. non-cancer using mp-MRI datasets. METHODS: 154 subjects undergoing mp-MRI were prospectively recruited, 16 of whom subsequently underwent radical prostatectomy. Logistic regression, random forest and CNN models were trained on mp-MRI data using histopathology as the gold standard. Transfer learning, unsupervised pre-training and test-time augmentation were used to boost CNN performance. Models were evaluated using Dice score and area under the receiver operating curve (AUROC) with leave-one-subject-out cross validation. Permutation feature importance testing was performed to evaluate the relative value of each MR contrast to CNN model performance. Statistical significance (p<0.05) was determined using the paired Wilcoxon signed rank test with Benjamini-Hochberg correction for multiple comparisons. RESULTS: Baseline CNN outperformed logistic regression and random forest models. Transfer learning and unsupervised pre-training did not significantly improve CNN performance over baseline; however, test-time augmentation resulted in significantly higher Dice scores over both baseline CNN and CNN plus either of transfer learning or unsupervised pre-training. The best performing model was CNN with transfer learning and test-time augmentation (Dice score of 0.59 and AUROC of 0.93). The most important contrast was apparent diffusion coefficient (ADC), followed by Ktrans and T2, although each contributed significantly to classifier performance. CONCLUSIONS: The addition of transfer learning and test-time augmentation resulted in significant improvement in CNN segmentation performance in a small set of prostate cancer mp-MRI data. Results suggest that these techniques may be more broadly useful for the optimization of deep learning algorithms applied to the problem of semantic segmentation in biomedical image datasets. However, further work is needed to improve the generalizability of the specific model presented herein.

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Nonalcoholic fatty liver disease (NAFLD) is a growing health problem, and a major challenge in NAFLD management is identifying which patients are at risk of progression to more serious disease. Simple measurements of liver fat content are not strong predictors of clinical outcome, but biomarkers related to fatty acid composition (ie, saturated vs. unsaturated fat) may be more effective. MR spectroscopic imaging (MRSI) methods allow spatially resolved, whole-liver measurements of chemical composition but are traditionally limited by slow acquisition times. In this work we present an accelerated MRSI acquisition based on spin echo single point imaging (SE-SPI), which, using appropriate sampling and compressed sensing reconstruction, allows free-breathing acquisition in a mouse model of fatty liver disease. After validating the technique's performance in oil/water phantoms, we imaged mice that had received a normal diet or a methionine and choline deficient (MCD) diet, some of which also received supplemental injections of iron to mimic hepatic iron overload. SE-SPI was more resistant to the line-broadening effects of iron than single-voxel spectroscopy measurements, and was consistently able to measure the amplitudes of low-intensity spectral peaks that are important to characterizing fatty acid composition. In particular, in the mice receiving the MCD diet, SE-SPI showed a significant decrease in a metric associated with unsaturated fat, which is consistent with the literature. This or other related metrics may therefore offer more a specific biomarker of liver health than fat content alone. This preclinical study is an important precursor to clinical testing of the proposed method. MR-based quantification of fatty acid composition may allow for improved characterization of non-alcoholic fatty liver disease. A spectroscopic imaging method with appropriate sampling strategy allows whole-liver mapping of fat composition metrics in a free-breathing mouse model. Changes in metrics like the surrogate unsaturation index (UIs) are visible in mice receiving a diet which induces fat accumulation in the liver, as compared to a normal diet; such metrics may prove useful in future clinical studies of liver disease.

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OBJECTIVES: To examine the association between blood-brain barrier (BBB) integrity, brain volume and cognitive dysfunction in adult patients with systemic lupus erythematosus (SLE). METHODS: A total of 65 ambulatory patients with SLE and 9 healthy controls underwent dynamic contrast-enhanced MRI scanning, for quantitative assessment of BBB permeability. Volumetric data were extracted using the VolBrain pipeline. Global cognitive function was evaluated using a screening battery consisting of tasks falling into five broad cognitive domains, and was compared between patients with normal versus extensive BBB leakage. RESULTS: Patients with SLE had significantly higher levels of BBB leakage compared with controls (p=0.04). Extensive BBB leakage (affecting over >9% of brain volume) was identified only in patients with SLE (16/65; 24.6%), who also had smaller right and left cerebral grey matter volumes compared with controls (p=0.04). Extensive BBB leakage was associated with lower global cognitive scores (p=0.02), and with the presence of impairment on one or more cognitive tasks (p=0.01). CONCLUSION: Our findings provide evidence for a link between extensive BBB leakage and changes in both brain structure and cognitive function in patients with SLE. Future studies should investigate the mechanisms underlying BBB-mediated cognitive impairment, validate the diagnostic utility of BBB imaging, and determine the potential of targeting the BBB as a therapeutic strategy in patients with SLE.

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Bipolar disorder affects approximately 2% of the population and is typically characterized by recurrent episodes of mania and depression. While some patients achieve remission using mood-stabilizing treatments, a significant proportion of patients show progressive changes in symptomatology over time. Bipolar progression is diverse in nature and may include a treatment-resistant increase in the frequency and severity of episodes, worse psychiatric and functional outcomes, and a greater risk of suicide. The mechanisms underlying bipolar disorder progression remain poorly understood and there are currently no biomarkers for identifying patients at risk. The objective of this study was to explore the potential of blood-brain barrier (BBB) imaging as such a biomarker, by acquiring the first imaging data of BBB leakage in bipolar patients, and evaluating the potential association between BBB dysfunction and bipolar symptoms. To this end, a cohort of 36 bipolar patients was recruited through the Mood Disorders Clinic (Nova Scotia Health Authority, Canada). All patients, along with 14 control subjects (matched for sex, age and metabolic status), underwent contrast-enhanced dynamic MRI scanning for quantitative assessment of BBB leakage as well as clinical and psychiatric evaluations. Outlier analysis has identified a group of 10 subjects with significantly higher percentages of brain volume with BBB leakage (labeled the "extensive BBB leakage" group). This group consisted exclusively of bipolar patients, while the "normal BBB leakage" group included the entire control cohort and the remaining 26 bipolar subjects. Among the bipolar cohort, patients with extensive BBB leakage were found to have more severe depression and anxiety, and a more chronic course of illness. Furthermore, all bipolar patients within this group were also found to have co-morbid insulin resistance, suggesting that insulin resistance may increase the risk of BBB dysfunction in bipolar patients. Our findings demonstrate a clear link between BBB leakage and greater psychiatric morbidity in bipolar patients and highlight the potential of BBB imaging as a mechanism-based biomarker for bipolar disorder progression.

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Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a method of temporal imaging that is commonly used to aid in prostate cancer (PCa) diagnosis and staging. Typically, machine learning models designed for the segmentation and detection of PCa will use an engineered scalar image called Ktrans to summarize the information in the DCE time-series images. This work proposes a new model that amalgamates the U-net and the convGRU neural network architectures for the purpose of interpreting DCE time-series in a temporal and spatial basis for segmenting PCa in MR images. Ultimately, experiments show that the proposed model using the DCE time-series images can outperform a baseline U-net segmentation model using Ktrans. However, when other types of scalar MR images are considered by the models, no significant advantage is observed for the proposed model.

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The American College of Rheumatology's case definitions for 19 neuropsychiatric syndromes in systemic lupus erythematosus (SLE) constitute a comprehensive classification of nervous system events in this disease. However, additional strategies are needed to determine whether a neuropsychiatric syndrome is attributable to SLE versus a competing comorbidity. Cognitive function is a clinical surrogate of overall brain health, with applications in both diagnosis and determination of clinical outcomes. Ischemic and inflammatory mechanisms are both key components of the immunopathogenesis of neuropsychiatric SLE (NPSLE), including abnormalities of the blood-brain barrier and autoantibody-mediated production of proinflammatory cytokines. Advances in neuroimaging provide a platform to assess novel disease mechanisms in a noninvasive way. The convergence of more rigorous clinical characterization, validation of biomarkers, and brain neuroimaging provides opportunities to determine the efficacy of novel targeted therapies in the treatment of NPSLE.

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OBJECTIVE: Purely phase-encoded techniques such as single point imaging (SPI) are generally unsuitable for in vivo imaging due to lengthy acquisition times. Reconstruction of highly undersampled data using compressed sensing allows SPI data to be quickly obtained from animal models, enabling applications in preclinical cellular and molecular imaging. MATERIALS AND METHODS: TurboSPI is a multi-echo single point technique that acquires hundreds of images with microsecond spacing, enabling high temporal resolution relaxometry of large-R 2* systems such as iron-loaded cells. TurboSPI acquisitions can be pseudo-randomly undersampled in all three dimensions to increase artifact incoherence, and can provide prior information to improve reconstruction. We evaluated the performance of CS-TurboSPI in phantoms, a rat ex vivo, and a mouse in vivo. RESULTS: An algorithm for iterative reconstruction of TurboSPI relaxometry time courses does not affect image quality or R 2* mapping in vitro at acceleration factors up to 10. Imaging ex vivo is possible at similar acceleration factors, and in vivo imaging is demonstrated at an acceleration factor of 8, such that acquisition time is under 1 h. CONCLUSIONS: Accelerated TurboSPI enables preclinical R 2* mapping without loss of data quality, and may show increased specificity to iron oxide compared to other sequences.

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PURPOSE: Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. METHODS: Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. RESULTS: The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). CONCLUSIONS: We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping.

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BACKGROUND: Recent evidence shows that functional magnetic resonance imaging (fMRI) can detect activation in white matter (WM). Such advances have important implications for understanding WM dysfunction. A key step in linking neuroimaging advances to the evaluation of clinical disorders is to examine whether WM activation can be detected at the individual level during clinical tests associated with WM function. We used an adapted Symbol Digit Modalities Test (SDMT) in a 4T fMRI study of healthy adults. RESULTS: RESULTS from 17 healthy individuals revealed WM activation in 88% of participants (15/17). The activation was in either the corpus callosum (anterior and/or posterior) or internal capsule (left and/or right). CONCLUSIONS: The findings link advances in fMRI to an established clinical test of WM function. Future work should focus on evaluating patients with WM dysfunction.

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Many studies have investigated test-retest reliability of active voxel classification for fMRI, which is increasingly important for emerging clinical applications. The implicit impact of voxel-wise thresholding on this type of reliability has previously been under-appreciated. This has had two detrimental effects: (1) reliability studies use different fixed thresholds, making comparison of results is challenging; (2) typical studies do not assess reliability at the individual level, which could provide information for selecting activation thresholds. To show the limitations of traditional fixed-threshold approaches, we investigated the threshold dependence of fMRI reliability measures, with the goal of developing an automated threshold selection routine. For this purpose, we demonstrated threshold dependence of both novel (ROC-reliability or ROC-r) and established (Rombouts overlap or RR) reliability measures. Both methods rely minimally on statistical assumptions, and provide a data-driven summary of the threshold-reliability relationship. We applied these methods to data from eight subjects performing a simple finger tapping task across repeated fMRI sessions. We showed that the reliability measures varied dramatically with threshold. This variation depended strongly on the individual tested. Finally, we demonstrated novel procedures using ROC-r and overlap analysis to optimize thresholds on a case-by-case basis. Ultimately, a method to determine robust individual-level activation maps represents a critical advance for fMRI as a diagnostic tool.

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BACKGROUND: One of the major disadvantages of mandibular distraction osteogenesis (MDO) is the prolonged time required for consolidation of the regenerate bone. The objective of the present study is to perform a contemporary review of various adjuvant therapies to enhance bone consolidation in MDO. METHODS: A PubMed search for articles related to MDO, along with the references of those articles, was performed. Inclusion and exclusion criteria were applied to all experimental studies assessing adjuvant therapies to enhance bone consolidation. RESULTS: A total of 1414 titles and abstracts were initially reviewed; 61 studies were included for full review. Many studies involved growth factors, hormones, pharmacological agents, gene therapy, and stem cells. Other adjuvant therapies included mechanical stimulation, laser therapy, and hyperbaric oxygen. Majority of the studies demonstrated positive bone healing effects and thus adjuvant therapies remain a viable strategy to enhance and hasten the consolidation period. CONCLUSION: Although most studies have demonstrated promising results, many questions still remain, such as optimal amount, timing, and delivery methods required to stimulate the most favorable bone regeneration. As well, further studies comparing various adjuvant therapies and documentation of long-term adverse effects are required prior to clinical application.

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Functional magnetic resonance imaging (fMRI) activation in white matter is controversial. Given that many of the studies that report fMRI activation in white matter used high field MRI systems, we investigated the field strength dependence of sensitivity to white matter fMRI activation. In addition, we evaluated the temporal signal to noise ratio (tSNR) of the different tissue types as a function of field strength. Data were acquired during a motor task (finger tapping) at 1.5 T and 4 T. Group and individual level activation results were considered in both the sensorimotor cortex and the posterior limb of the internal capsule. We found that sensitivity increases associated with field strength were greater for white matter than gray matter. The analysis of tSNR suggested that white matter might be less susceptible to increases in physiological noise related to increased field strength. We therefore conclude that high field MRI may be particularly advantageous for fMRI studies aimed at investigating activation in both gray and white matter.

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BACKGROUND: There is growing evidence for the idea of fMRI activation in white matter. In the current study, we compared hemodynamic response functions (HRF) in white matter and gray matter using 4 T fMRI. White matter fMRI activation was elicited in the isthmus of the corpus callosum at both the group and individual levels (using an established interhemispheric transfer task). Callosal HRFs were compared to HRFs from cingulate and parietal activation. RESULTS: Examination of the raw HRF revealed similar overall response characteristics. Finite impulse response modeling confirmed that the WM HRF characteristics were comparable to those of the GM HRF, but had significantly decreased peak response amplitudes. CONCLUSIONS: Overall, the results matched a priori expectations of smaller HRF responses in white matter due to the relative drop in cerebral blood flow (CBF) and cerebral blood volume (CBV). Importantly, the findings demonstrate that despite lower CBF and CBV, white matter fMRI activation remained within detectable ranges at 4 T.

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Recent developments have shown that it is possible to detect functional magnetic resonance imaging (fMRI) activation in white matter (WM). Enhanced sensitivity to WM fMRI signals has been associated with the asymmetric spin echo (ASE) spiral sequence. The ASE spiral sequence produces three consecutive images that have equal blood-oxygen level-dependent (BOLD) contrast but increasing T(2) contrast. The current study evaluated whether ASE spiral sensitivity differed between white and gray matter in the corpus callosum, superior parietal lobes, cingulate gyrus, and inferior frontal lobes. Contrast and noise were compared across the three images for each region. Results showed increasing gains in functional contrast in both white and gray matter as a function of T(2) contrast. The third image, with the most T(2) contrast, showed the largest increase in contrast, while changes in noise were maintained. The results suggest that ASE spiral increases fMRI sensitivity globally through the addition of T(2) weighted contrast.

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Susceptibility field gradients (SFGs) cause problems for functional magnetic resonance imaging (fMRI) in regions like the orbital frontal lobes, leading to signal loss and image artifacts (signal displacement and "pile-up"). Pulse sequences with spiral-in k-space trajectories are often used when acquiring fMRI in SFG regions such as inferior/medial temporal cortex because it is believed that they have improved signal recovery and decreased signal displacement properties. Previously postulated theories explain differing reasons why spiral-in appears to perform better than spiral-out; however it is clear that multiple mechanisms are occurring in parallel. This study explores differences in spiral-in and spiral-out images using human and phantom empirical data, as well as simulations consistent with the phantom model. Using image simulations, the displacement of signal was characterized using point spread functions (PSFs) and target maps, the latter of which are conceptually inverse PSFs describing which spatial locations contribute signal to a particular voxel. The magnitude of both PSFs and target maps was found to be identical for spiral-out and spiral-in acquisitions, with signal in target maps being displaced from distant regions in both cases. However, differences in the phase of the signal displacement patterns that consequently lead to changes in the intervoxel phase coherence were found to be a significant mechanism explaining differences between the spiral sequences. The results demonstrate that spiral-in trajectories do preserve more total signal in SFG regions than spiral-out; however, spiral-in does not in fact exhibit decreased signal displacement. Given that this signal can be displaced by significant distances, its recovery may not be preferable for all fMRI applications.

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This work proposes the use of TurboSPI, a multi-echo single point imaging sequence, for the quantification of labeled cells containing moderate to high concentrations of iron oxide contrast agent. At each k-space location, TurboSPI acquires several hundred time points during a spin echo, permitting reliable relaxation rate mapping of large-R(2)(∗) materials. An automatic calibration routine optimizes image quality by promoting coherent alignment of spin and stimulated echoes throughout the multi-echo train, and this calibration is sufficiently robust for in vivo applications. In vitro relaxation rate measurements of SPIO-loaded cervical cancer cells exhibit behavior consistent with theoretical predictions of the static dephasing regime in the spin echo case; the relaxivity measured with TurboSPI was 10.47±2.3 s(-1)/mG, comparable to the theoretical value of 10.78 s(-1)/mG. Similar measurements of micron-sized iron oxide particles (0.96 µm and 1.63 µm diameter) show a reduced relaxivity of 8.06±0.68 s(-1)/mG and 7.13±0.31 s(-1)/mG respectively, indicating that the static dephasing criterion was not met. Nonetheless, accurate quantification of such particles is demonstrated up to R(2)(∗)=900 s(-1), with a potentially higher upper limit for loaded cells having a more favorable R(2)('):R(2) ratio. Based on the cells used in this study, reliable quantification of cells loaded with 10 pg of iron per cell should be possible up to a density of 27 million cells/mL. Such quantification will be of crucial importance to the development of longitudinal monitoring for cellular therapy and other procedures using iron-labeled cells.

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