Joint Annual Meeting ISMRM-ESMRMB 2014 10-16 May 2014 Milan, Italy


RELAXATION (13:30-15:30)

3122-3148 Relaxation: All Flavours

Relaxation: All Flavours

Thursday 15 May 2014
Traditional Poster Hall  13:30 - 15:30

3122.   Exchange-Induced Relaxations in the Presence of Fictitious Fields
Timo Liimatainen1, Dennis Sorce2, Silvia Mangia2, Michael Garwood2, and Shalom Michaeli2
1A.I.Virtanen Institute, University of Eastern Finland, Kuopio, FI, Finland, 2Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States

The RAFFn pulses are designed to generate fictitious fields that allow locking of magnetization in the rotating frames of rank n. Exchange induced relaxations during RAFFn pulses for two site exchange were described using Bloch-McConnell formalism. The results demonstrate that with the increase of n the sensitivity of RAFFn to the slow motional regime increases.

3123.   Characterization of Intrinsic Susceptibility Gradients Using R1lower case Greek rho Dispersion
John Thomas Spear1,2 and John C. Gore2,3
1Physics & Astronomy, Vanderbilt University, Nashville, TN, United States, 2Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 3Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

Diffusion of water through susceptibility gradients causes R1lower case Greek rho dispersion to a degree that depends on the geometry and size of the inhomogeneities responsible for the gradients. Finite difference simulations were run and compared to experimental data to further substantiate a method to quantify the spatial scales of packed inhomogeneities that has been presented in the literature. R1lower case Greek rho dispersions were simulated for spherical and cylindrical structures with varying radii and volume fractions to estimate the correlation time, a parameter that estimates the scale of the gradients.

3124.   Observation of time-dependent transverse relaxation rate due to mesoscopic magnetic structure
Philipp Emerich1, Alexander Ruh1, Harald Scherer2, Dmitry S. Novikov3, and Valerij G. Kiselev1
1Dept. of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany, 2Dept. of Inorganic and Analytical Chemistry, University Freiburg, Freiburg, Germany, 3Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, United States

Transverse relaxation in biological tissues is sensitive to the structural organization of magnetic inhomogeneities on the cellular level. A recently developed theory predicts a reflection of this structural organization in the long-time behavior of the induced relaxation rate as a power law approach to the asymptote. We report the first experiment aimed at verification of this theory in a model system of microbeads suspended in aqueous solution of variable magnetic susceptibility. Experimental results are in a good agreement with theoretical predictions and Monte Carlo simulations.

3125.   In vivo quantification of myowater anatomical compartmentation with proton T2-relaxation studies using a three site two exchange (3S2X) model
Ericky C.A. Araujo1, Yves Fromes2, and Pierre G Carlier1
1AIM-CEA Institut de Myologie, Laboratoire RMN, Paris, France, 2Université Pierre et Marie Curie Paris 6, Paris, France

Confirmation of the anatomical compartmentation theory to explain the biexponential T2-relaxation of bulk-water in skeletal muscle is motivated by the great clinical interest on a non-invasive tool for quantification of myowater distribution in vivo. In vivo T2-relaxation data were acquired from the soleus of healthy volunteers at different vascular filling conditions (vascular-draining, normal and vascular-filling). Variations on T2-spectra following the different vascular conditions offered strong evidences in favour of the anatomical compartmentation theory. Data were analysed by means of compartmental exchange analysis. A 3S2X model has been shown to be capable of predicting NMR relaxation data for realistic transmembrane exchange values.

3126.   Use of L1-norm solution to Impose Spatial Smoothness Constraints in Quantitative T2 Relaxometry
Dushyant Kumar1,2, Susanne Siemonsen1,2, Margherita Porcelli3, Jens Fiehler1, Christoph Heesen4, and Jan Sedlacik1
1Dept. of Neuroradiology, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Hamburg, Germany, 2Multiple Sclerosis Imaging Section (SeMSI), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Hamburg, Germany, 3Mathematics, University of Bologna, Bologna, Bologna, Italy, 4Institute for Neuroimmunology and Clinical MS Research, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Hamburg, Germany

Problem: A moderately high SNR (~200) QT2R data is needed for robust tissue-water-fraction-map reconstruction if L2-norm based spatial smoothness is implemented. We are testing L1-norm-solver as other possible candidate. Methods: We are developing L1-norm-solver in this context and its performance is compared against L2-norm-solver in context of imposing spatial constraints. Results & Conclusions: Results using L2- and L1-norms are similar at high SNR (>200); however, L2-norm-solver performs better at lower SNR. In near future, we would develop “hybrid” filter to impose smoothness and sparsity simultaneously to make L1-norm performs better at low SNR.

3127.   Accurate T2 Mapping with Sparisty and Linear Predictability Filtering
Xi Peng1, Leslie Ying2, Xin Liu1, and Dong Liang1
1Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Shenzhen Institutes of Advanced Technology, Shenzhen, Guangdong, China,2Department of Biomedical Engineering, Department of Electrical Engineering, The State University of New York at Buffalo, Buffalo, New York, United States

Accelerating the acquisition of T2 mapping via sparse sampling has drawn considerable attention. However, due to non-ideal conditions in practical settings (i.e., insufficient sparsity/rank and coherent sampling), errors occur in the T2-weighted images and the subsequent relaxation map especially with high reduction factors and noisy measurements. We address this issue by integrating the prior information (i.e., exponential functions) on the temporal signals into the image reconstruction step. This is in contrast to the conventional wisdom where the image reconstruction and parameter mapping are performed independently. The proposed method was demonstrated with an in-vivo brain dataset and shows promising results.

3128.   Regularized, Joint Estimation of T1 and M0 Maps
Gopal Nataraj1, Jon-Fredrik Nielson2,3, and Jeffrey A. Fessler1,2
1Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI: Michigan, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI: Michigan, United States, 3Functional MRI Laboratory, University of Michigan, Ann Arbor, MI: Michigan, United States

We have developed a model-based approach for joint reconstruction of spin-lattice relaxation time T1 and proton density M0 maps from DESPOT1 sequences. Our statistical methods employ regularization to reduce noise amplification issues common in conventional least-squares estimators. The proposed technique dramatically improves mapping precision and quality, both for synthetic and in vivo data, and at a wide range of noise thresholds and flip angle combinations.

3129.   Direct & accelerated parameter mapping using the unscented Kalman filter
Li Zhao1 and Craig H. Meyer1,2
1Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States, 2Radiology, University of Virginia, Charlottesville, Virginia, United States

Parameter mapping is essential for clinic diagnose and its acceleration is highly demanded. With under sampling in kspace-parameter encoding space, we proposed an unscented Kalman filter based method to estimation the parameter directly without reconstruction of the interval images. This method was verified in accelerated T2 mapping on numerical phantom and volunteer data. Comparing to compressed sensing with K-SVD, unscented Kalman filter provides more accurate T2 map in less reconstruction time.

3130.   A Model-based Reconstruction Technique for Fast Dynamic T1 Mapping
Johannes Tran-Gia1, Sotirios Bisdas2, Herbert Köstler1, and Uwe Klose2
1Institute of Radiology, University of Würzburg, Würzburg, Germany, 2Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany

A setup for dynamic parameter mapping with a temporal resolution of up to 7.2s is presented. It uses the previously presented IR-MAP technique to reconstruct relaxation curves for successive inversions, each followed by a radial Look-Locker FLASH acquisition and a short waiting time for relaxation. After a correction of T_1 errors caused by an insufficient relaxation between successive inversions, this allows monitoring T_1 variations over time, which is desirable in many applications such as dynamic contrast enhanced MRI. After the functionality of the technique is validated on a phantom and in vivo, the feasibility of the technique in dynamic contrast-enhanced MRI is demonstrated in a brain tumor patient.

Rapid and Accurate T2 Mapping from Multi Spin Echo Data Using Bloch-Simulation-Based Reconstruction
Noam Ben-Eliezer1, Daniel K. Sodickson1, and Kai Tobias Block1
1Department of Radiology, New York University School of Medicine, Bernard and Irene Schwartz Center for Biomedical Imaging, New York, NY, United States

Accurate quantification of T2 values in vivo is a long-standing challenge hampered by the extensive scan times associated with full Spin-Echo (SE) acquisitions, or by the inherent bias of rapid multi-SE sequences resulting from stimulated and indirect echoes. Recently, a novel proof-of-principle T2 mapping technique – the echo-modulation curve (EMC) algorithm – has been proposed based on precise Bloch simulations. In this work we establish the EMC technique applicability to various body regions, analyze its accuracy and precision at different SNR levels and present extensions both to non-Cartesian trajectories and to multiparametric mapping of T2 relaxation, proton density and transmit B1+ profile.

El-Sayed H. Ibrahim1, Ayman M. Khalifa2, Ahmed K. Eldaly2, and Andrew W. Bowman1
1Mayo Clinic, Jacksonville, Florida, United States, 2Helwan University, Cairo, Egypt

MRI has been established as an effective technique for evaluating iron overload by measuring T2* in the liver. Although the process of calculating T2* is conceptually straightforward, various factors associated with image analysis could change the resulting measurement, including the signal averaging method, exponential fitting model, region-of-interest (ROI) location and size, echo truncation, iron overload severity, and inter-/intra-observer variabilities. In this study, we evaluate the influences of these factors on T2* estimation in calibrated phantoms and eleven patients with different degrees of iron overload. The results show various degrees of similarities and differences between the performances of different analysis approaches.

3133.   Which one is most accurate and has highest precision? - A comprehensive analysis of T2(*) estimation techniques
Ferdinand Schweser1, Ines Krumbein1, Karl-Heinz Herrmann1, Hans-Joachim Mentzel2, and Jürgen R Reichenbach1
1Medical Physics Group, Institute of Diagnostic and Interventional Radiology I, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany, 2Section Pediatric Radiology, Institute of Diagnostic and Interventional Radiology I, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany

MR relaxation parameters are often used to quantify the state of tissue and to distinguish pathological from normal conditions. MR magnitude noise can introduce a serious bias toward higher or lower relaxation parameters. Such a bias may have serious clinical consequences, e.g., when relaxation parameters are used for treatment decisions such as in liver iron overload diseases. With the current contribution, we aim to give clear recommendations how to estimate relaxation rates for different experimental scenarios, such as in slow and fast relaxing tissues.

3134.   MRI evaluation of the relationship between R2, R2*, and tissue iron in the human basal ganglia
Joanna Collingwood1,2, Mary Finnegan1, Zobair Arya3, Jean-Pierre Hagen1, Saherabanu Chen1, Alimul Chowdhury4, Sarah Wayte5, Eddie Ngandwe5, Naomi Visanji6, Jon Dobson7, Penny Gowland8, Lili-Naz Hazrati9, and Charles Hutchinson5,10
1School of Engineering, University of Warwick, Coventry, West Midlands, United Kingdom, 2Materials Science and Engineering, University of Florida, Gainesville, Florida, United States, 3Department of Physics, University of Warwick, West Midlands, United Kingdom, 4School of Psychology, University of Birmingham, West Midlands, United Kingdom, 5University Hospitals Coventry and Warwickshire, West Midlands, United Kingdom, 6Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, Ontario, Canada, 7J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Florida, United States, 8School of Physics & Astronomy, University of Nottingham, Nottinghamshire, United Kingdom, 9Tanz Centre for Research in Neurodegenerative Disease, University of Toronto, Ontario, Canada, 10Warwick Medical School, University of Warwick, West Midlands, United Kingdom

R2 and R2* were determined for primary regions in the basal ganglia. Ten adult volunteers were measured at 3.0T and 1.5T on clinical platforms; R2*, R2, and the field-dependent R2 increase (FDRI) were compared with previously reported iron concentrations for the same regions. A set of post-mortem tissues were measured at 9.4T using a Bruker MicWB40; relationships between iron, R2, and R2* were directly evaluated by mapping tissue iron distribution with synchrotron X-ray fluorescence, enabling spatial correlation with MRI maps. These data indicate that at 9.4T the linear relationship between both R2 and R2*, and tissue iron concentration, is preserved.

El-Sayed H. Ibrahim1 and Andrew W. Bowman1
1Mayo Clinic, Jacksonville, Florida, United States

T2*-weighted MRI has been established for evaluating myocardial iron overload with strong correlation with biopsy. The recently introduced dual-energy computed-tomography (DECT) has the potential for evaluating iron overload without energy-dependent CT attenuation or tissue fat effects. This study investigates the performance of DECT for evaluating myocardial iron overload (from images acquired at different diagnostic imaging energies of 80/100/120/140 kVp) and compare the results to MRI T2* based on experiments on phantoms with calibrated iron concentrations. DECT showed high accuracy for evaluating iron overload independent of the implemented imaging energy, with the results comparable to those from MRI T2* measurements.

3136.   Improved T2* assessment in liver iron overload by 2D fuzzy c-mean clustering
Pairash Saiviroonporn1, Vip Viprakasit2, Rungroj Krittayaphong3, and John C Wood4
1Radiology Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkoknoi, Bangkok, Thailand, 2Department of Pediatrics, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkoknoi, Bangkok, Thailand, 3Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkoknoi, Bangkok, Thailand, 4Department of Pediatrics, Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, California, United States

The study investigated the usefulness of the 2D fuzzy c-mean (FCM) clustering to lower the variability of the T2* liver iron assessment by separated the vessel pixels from parenchyma. The manual and 2D-FCM segmentations were performed on the multi-echo T2* images and their LIC maps of 60 thalassemia major patients. The 2D FCM method can correctly segment the parenchyma and vessel pixels by 95.7±7.9% and 99.5±2.4%, respectively. The variability of the T2* measurement then can be lower by 32%, but finding the optimal clustering variables are necessary before it can be practically employed.

3137.   On the Lorentzian versus Gaussian Character of Time Domain Spin Echo Signals Sampled via Gradient Echoes: Implications for Iron Deposition Analyses
Robert V. Mulkern1, Mukund Balasubramanian1, and Dimitrios Mitsouras2
1Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, United States, 2Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, United States

Previous MRI studies of brain iron deposition have estimated R2 and R2* (or R2') simultaneously from multiple gradient echo sampling of either a single spin echo or a free induction decay and the left side of a spin echo. These studies have, explicitly or implicitly, assumed Lorentzian frequency distributions for the water resonance. Here, we demonstrate that Gaussian frequency distributions, which have a markedly different time domain response, provide a better fit to signals from brain tissue, leading to a more accurate characterization of both the reversible and the irreversible transverse relaxation processes in these tissues.

3138.   Liver T2* measurements: The best curve fitting model for ROI based method and Pixel based method
Monruedee Tapanya1, Kittichai Wantanajittikul2, Busakol Ngammuang1, Suchaya Silvilairat3, Suthat Fuchareon4, Kittiphong Paiboonsukwong4, and Suwit Saekho1,2
1Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand, 2Biomedical Engineering Center, Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand, 3Pediatrics, Faculty of Medicine,Chiang Mai University, Chiang Mai, Thailand, 4Thalassemia Research Center Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom, Thailand

We compared between median T2*obtained from pixel based method and the T2* derived from ROI based method in 3 different fitting models, mono-exponential, Offset and Truncation model. Fifteen β thalassemia major patients were involved to this study. The results showed strongly correlation between T2* obtained from two methods with offset fitting model and there was no significant difference between the 2 methods with this fitting model. ROI based method with offset fitting model potentially provided similar T2* to that of pixel based method for liver T2* measurements.

3139.   Myelin Water Fraction (MWF) Imaging using Flip angle mapping and a Dual Channel Transmit Coil at 3T
Gisela E Hagberg1,2, Samuel Groeschel3, Thomas Prasloski4, Alex MacKay4, Uwe Klose5, Ingeborg Krägeloh-Mann3, and Klaus Scheffler1,2
1Biomedical Magnetic Resonance, University Hospital Tuebingen, Tuebingen, Germany, Germany, 2High Field Magnetic Resonance, MPI for Biological Cybernetics, Tuebingen, Germany, 3University Children's Hospital, Tuebingen, Germany, 4University of British Columbia, Vancouver, Canada, 5Department ofDiagnostic and Interventional Neuroradiology, University Hospital Tuebingen, Germany

The quality of MWF maps obtained with the standard approach, were compared with results obtained from measured and scaled flip angle maps in a cohort of 10 healthy young volunteers. Two scaling approaches were used; an expected 180 degree pulse and scaling to the first pass fitted FA. The two-step procedure was found to be a viable approach to improve the MWF maps, without a too high cost in terms of goodness-of-fit or distinction between components.

3140.   A framework for getting the correct T2 distribution from multiple echo magnitude MRI signal
Ruiliang Bai1,2, Cheng Guan Koay3, and Peter J Basser1
1Section on Tissue Biophysics and Biomimetics, PPITS, NICHD, National Institutes of Health, Bethesda, MD, United States, 2Biophysics Program, Institute for Physical Science and Technology, University of Maryland, College Park, MD, United States, 3Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States

The noise-induced bias in the magnitude multi-echo MRI signals causes artifacts in T2 distributions calculated by conventional inverse Laplace transform (ILT) algorithms, that implicitly assume the noisy signal is always Gaussian distributed. Here we propose a signal transformational framework to map the noisy Rician-distributed magnitude signal back to a Gaussian distribution and then perform an ILT algorithm on the corrected data to obtain an accurate T2 distribution. Both simulations and experiments validate the efficiency of this approach in correcting these artifacts.

3141.   Myelin Water Imaging using Direct Visualization of Short Transverse Relaxation Time Component (ViSTa) at 7T
Sung Suk Oh1, Joon Yul Choi1, and Jongho Lee1
1Radiology, University of Pennsylvania, Philadelphia, PA, United States

A new myelin water imaging method, ViSTa (Direct Visualization of Short Transverse Relaxation Time Component) was applied at 7T and compared to 3T. The ViSTa images at 7T showed a factor of 3 higher SNR than at 3T, demonstrating potential of using ViSTa at 7T.

3142.   Multi-component transverse relaxation in egg yolk: Relaxations times, relative amplitudes and spectral assignments
Dimitrios Mitsouras1, Robert V Mulkern2, and Stephan E Maier3
1Brigham and Womens Hospital, Boston, MA, United States, 2Children's Hospital Boston, MA, United States, 3Brigham and Womens Hospital, MA, United States

We characterized the multi-component transverse relaxation (T2) decay in egg yolk with high-SNR, high-quality Carr-Purcell-Meiboom-Gill (CPMG) sequences. Three T2 components are identified; two fast-decaying (12 and 23ms) of roughly equal proportion, associated with water and lipids. The third is a small (2%) slow component (293ms). The egg yolk is a widely available phantom material that may prove useful in validating methods to extract information from short T2 species like brain myelin-associated water (MAW).

3143.   Myelin Water Fraction of the Whole Brain: 3D GRASE MWI vs. 3D ViSTa MWI
Se-Hong Oh1,2, Joon Yul Choi2, Yeiji Im2, Thomas Prasloski3, and Jongho Lee2
1Imaging Institute, Cleveland Clinic, Cleveland, Ohio, United States, 2Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States, 3Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada

In this study, the whole brain MWF map from conventional MWI (GRASE) was compared to that from a novel MWI method, Direct Visualization of Short Transverse Relaxation Time Component (ViSTa). The voxel-wise correlation shows a high correlation between the two maps. Compared to the conventional MWI, ViSTa provides superior image quality with better reproducibility. It also covers a larger volume in a shorter scan time.

3144.   Assessment of mcDESPOT Precision Using Constrained Estimation
Samuel Anthony Hurley1 and Andrew L Alexander1,2
1Medical Physics, University of Wisconsin, Madison, WI, United States, 2Psychiatry, University of Wisconsin, Madison, WI, United States

Multicomponent relaxation with steady state imaging (mcDESPOT) method is evaluated using both Monte Carlo simulations and Cramér–Rao lower bound computations. The effects of the Gaussian contraction constrained estimation on the precision of the model are investigated.

3145.   Multi-Component Fitting of T2* Relaxation in White Matter at 3 and 7 Tesla
Erika P. Raven1, Peter van Gelderen2, Xiaozhen Li2, Jacco A. de Zwart2, John VanMeter3,4, and Jeff H. Duyn2
1Neuroscience, Georgetown University, Washington, DC, United States, 2Advanced MRI section, LFMI, NINDS, National Institutes of Health, Bethesda, MD, United States,3Neurology, Georgetown University, Washington, DC, United States, 4Georgetown Center for Functional and Molecular Imaging, Washington, DC, United States

Previous studies have demonstrated separation of cellular compartments by utilizing large, local frequency shifts (Δf) and increased T2* relaxation at high magnetic field strength (7 T). This abstract examines the reproducibility of a multi-component fitting model at 7 T, while also investigating the feasibility of this method at 3 T. Our findings suggest the possibility of separating cellular specific contributions in white matter at both 3 and 7 T. Quantification of cellular compartments, importantly the myelin-water fraction, has important implications for the study of normal aging and disease.

3146.   T2-relaxometry for Myelin Water Fraction Estimation using a Mixture of Wald Distributions
Alireza Akhondi-Asl1,2, Onur Afacan1,2, Robert V. Mulkern1,2, and Simon K. Warfield1,2
1Boston Children’s Hospital, Boston, MA, United States, 2Harvard Medical School, MA, United States

We introduce a novel model with small number of parameters to characterize transverse relaxation rate spectrum at each voxel. We use mixture of three Wald distributions with unknown mixture weights, mean and shape parameters to represent the distribution of the relative amount of water in between myelin sheets, tissue water, and cerebrospinal fluid. Wald distribution has a Gaussian-like distribution with positive support and a closed form Laplace transform which are exceptional and distinctive attributes for the representation of transverse relaxation rate distribution. The parameters of the model are estimated using the constrained variable projection method as a substantial number of unknown parameters is linear.

3147.   A novel approach for fast MWF quantification
Sofya Kulikova1, Lucie Hertz-Pannier1, Ghislaine Deahene-Lambertz2, Cyril Poupon3, and Jessica Dubois2
1UMR 663 Neurospin/UNIACT, INSERM-CEA, Gif-sur-Yvette, France, 2UMR 992 Neurospin/UNICOG, INSERM-CEA, Gif-sur-Yvette, France, 3Neurospin/UNIRS, CEA-Saclay, Gif-sur-Yvette, France

Myelin Water Fraction (MWF) is computed from multicomponent relaxation analysis that requires long acquisition and post-processing times limiting its practical application in infants. Here we suggest a novel 2-step strategy for fast MWF quantification. We fitted a 3-component model (myelin-related water, intra/extra-cellular water, CSF) with adults’ data having a large number of measurements to identify the most appropriate T1 and T2 values for each component over the whole brain. These values were fixed for the following MWF quantification with a reduced number of measurements. Infant MWF maps showed progressive myelination with age and were in qualitative agreement with other studies.

3148.   Limitations in Biexponential Fitting of Nuclear Magnetic Resonance (NMR) Inversion-Recovery Data to Differentiate Between Cell Compartmental NMR Signals
Mohammed Salman Shazeeb1,2
1Radiology, University of Massachusetts Medical School, Worcester, MA, United States, 2Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, United States

A biexponential model can be used to fit inversion-recovery NMR data to differentiate between compartmental relaxation times and magnetization fractions in order to measure compartment-specific apparent diffusion coefficients. Due to the presence of noise in acquired data and sensitivity to actual observed parameter values, the fitted parameters display different amounts of error depending on whether an extracellular or intracellular contrast agent is administered. In this study, simulations of data sets corresponding to both scenarios were generated to determine the effects of signal to noise and parameter limitations on the constraints of fitting by calculating the root mean square percentage error.