Myrte Wennen^1,2, Manon Moll³, Tim Marcus², Joost Kuijer², Leo Heunks¹, Christina Lavini², Gustav Strijkers², Aart Nederveen², and Oliver Gurney-Champion^2
1Intensive Care, Amsterdam UMC, Amsterdam, Netherlands, ²Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands, ³University of Twente, Enschede, Netherlands

Hector Lise de Moura¹, Marcelo Victor Wust Zibetti¹, and Ravinder Regatte^1
1Radiology, NYU Langone Health, New York, NY, United States

 T1ρ-Mapping requires acquisition with multiple Spin-Lock Times (TSLs) in order to fit the free parameters of the model. Reducing the #TSLs poses a trade-off between acquisition time and estimation error. Also, the choice of TSLs has a significant influence on the fitting results. A previous study analyzed the Cramér-Rao Lower Bound (CRLB) as an optimization criterium for the TSL choices using different #TSLs for Mono-Exponential models. This study extends the use of CRLB for Stretched- and Bi-exponential models using complex-valued fitting via Non-linear Least Squares. Experiments show that optimized TSL sequences improve parameter estimation when compared to non-optimized TSL sequences.

Aurelie Bussy^1,2, Raihaan Patel^1,3, Alyssa Salaciak¹, Sarah Farzin¹, Stephanie Tullo^1,2, Sandra Pelleieux⁴, Sylvia Villeneuve^4,5, Judes Poirier^4,5, John CS Breitner^4,5, Gabriel A. Devenyi^1,5, Christine L. Tardif^3,6, and M. Mallar Chakravarty^1,2,3,5
1Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canada, ²Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada, ³Department of Biomedical Engineering, McGill University, Montreal, QC, Canada, ⁴Centre for the Studies on the Prevention of AD, Douglas Mental Health University Institute, Montreal, QC, Canada, ⁵Department of Psychiatry, McGill University, Montreal, QC, Canada, ⁶McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada

Morphometric and quantitative magnetic resonance imaging techniques have rarely been used simultaneously to characterise healthy aging and Alzheimer’s disease (AD) progression. Here, we are extracting four vertex-wise cortical metrics : cortical thickness, surface area, T1 value (myelin) and T2* values (iron). All these metrics were analysed using non-negative matrix factorization and linear models. Overall, cortical thinning seemed to be linked to both aging and AD progression, while decrease in myelin seemed to be a phenomenon mostly related to aging. No significant patterns of changes were seen in the prodromal phase of AD.

Barbara Dymerska¹, Oliver Josephs¹, and Martina Callaghan^1
1Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom

R₂*-mapping delivers quantitative information about tissue microstructure. We investigate the scale of image distortions in high-resolution, bipolar, multi-echo GRE acquisitions at 7T and their effects on R₂*-mapping. We study reduction in variance by applying field map-based distortion correction while also considering the confounding effect of local smoothing. We show that for regions with signal displacement > 0.5 voxels the reduction in variance comes largely, not from smoothing, but from the appropriate repositioning of the tissue signal. Therefore, correcting distortions, also in sub-voxel regime, improves data consistency in bipolar GRE acquisitions, facilitating more robust R₂*-mapping in high-resolution laminar studies for instance.

Sven Nouwens¹, Kemal Sumser², Maarten Paulides^2,3, Bram de Jager¹, and Maurice Heemels^1
1Mechanical Engineering, Control Systems Technology, Technical University Eindhoven, Eindhoven, Netherlands, ²Radiotherapy, Erasmus MC, Rotterdam, Netherlands, ³Electrical Engineering, Electromagnetics for Care & Cure, Technical University Eindhoven, Eindhoven, Netherlands

Proton resonance frequency shift based MR thermometry is widely used to non-invasively monitor thermal therapies in vivo. Multi-echo gradient-echo sequences are being studied to increase the effective temperature to noise ratio, however, choosing the optimal echo-times is non-trivial. We developed an optimization framework based on measurement noise models to compute the optimal echo placement for schemes that either correct or do not correct for the conductivity bias. In a 4-echo phantom experiment, we demonstrated a reduction in the noise standard deviation of 22% when comparing optimal to equidistant echo placements. 

Laura Nunez-Gonzalez¹, Karin A. van Garderen^1,2, Marion Smits^1,2, Jaap Jaspers², Alejandra Méndez Romero², Dirk H. J. Poot¹, and Juan A. Hernandez-Tamames^1,3
1Erasmus MC, Rotterdam, Netherlands, ²Erasmus MC Cancer Institute, Rotterdam, Netherlands, ³TU Delft, Delft, Netherlands

We analyze quantitative values in glioma obtained with MAGiC, which allows obtaining quantitative T1, T2 and PD maps in one single acquisition of less than 6 minutes for a whole brain. The maps were obtained before contrast-agent injection in 14 patients with glioma. We investigated the possibility of characterizing tumor regions based on quantitative maps acquired without contrast-agent. The results showed significant differences among tumoral tissue, tissue with T1w-enhancement, and normal white matter. Voxel-wise, this allowed to distinguish tumoral tissue but did not allow to accurately predicting T1w-enhancement. However, promising results were found predicting T1w-enhancement inside the tumor.

Sai Man Cheung¹, Wing Shan Wu¹, Nicholas Senn¹, Ravi Sharma², Trevor McGoldrick², Tanja Gagliardi^1,3, Ehab Husain⁴, Yazan Masannat⁵, and Jiabao He^1
1Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom, ²Oncology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, ³Radiology Department, Royal Marsden Hospital, London, United Kingdom, ⁴Pathology Department, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, ⁵Breast Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom

Intravoxel incoherent motion (IVIM) model approximates the tissue perfusion as a form of pseudo-diffusion, extracted as fast diffusion component in diffusion weighted imaging (DWI). Despite the central role of tissue perfusion in the angiogenesis in cancer, the clinical application of IVIM is hampered due to the susceptibility to noise and tendency of overfitting bi-exponential decay function. Recent introduction of Bayesian algorithm significantly enhanced the robustness and accuracy of IVIM method, renewing its potential as a clinical tool. We therefore set out to examine current IVIM algorithms in the context of neoadjuvant chemotherapy on patients with breast cancer preceding the treatment.

Elif Aygun^1,2 and Emine Ulku Saritas^1,2,3
1Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey, ²National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey, ³Neuroscience Graduate Program, Bilkent University, Ankara, Turkey

Multi-shell dMRI metrics quantify information on micro-properties of neural tissue and can be used as markers for neurological diseases. The protocols used to acquire dMRI data often have prolonged acquisition times. In this work, we propose different undersampling strategies that reduce the acquisition time to half, and evaluate how the performances of multi-shell dMRI metrics change under these strategies. The results show that, while the best performing strategy changes for each metric, 3-shell gradient schemes with small variance of b-vector density on consecutive shells demonstrate improved performance. Additionally, more complex dMRI metrics exhibit relatively increased sensitivity to undersampling.

Ekaterina A Brui¹, Charles A de Mayenne ², Stanislas Rapacchi ³, Thomas Troalen ⁴, Christophe Vilmen³, and David Bendahan^1,3
1School of Physics and Engineering, ITMO University, Saint-Petersburg, Russian Federation, ²National Higher French Institute of Aeronautics and Space, Toulouse, France, ³Aix-Marseille Universite, CNRS, Centre de Résonance Magnétique Biologique et Médicale, Marseille, France, ⁴Siemens Healthcare SAS, Saint-Denis, France

Previously, an elegant method based on the generation of echo modulation curves (EMC) demonstrated a very high accuracy of T2 measurements. However, the original approach considered EMC dictionary modelling only for a single slice mode of multi-echo spin echo (MESE) sequence. For some applications, such as T2 mapping of cartilage in small joints, contiguous MRI is required. As a result, slice cross-talk effect may affect the accuracy of T2 estimation. In this work, we report a modified version of the EMC technique, which can be used to quantify T2 values for zero-gap multi-slice MESE acquisitions in tissues with long T1.

Scott D. Swanson¹, Dariya I. Malyarenko¹, and Thomas L. Chenevert^1
1Radiology, University of Michigan, Ann Arbor, MI, United States

Nanoparticle lipid vesicles are developed with controllable water exchange to provide a ground-truth benchmark for MR methods which measure exchange. Diffusion data are collected as a function of diffusion delay Δ. An exchange time, τ, is measured to be 164 ms in a phantom with a highly fluid membrane. These materials should help to clarify water dynamics in complex systems.

Damien J McHugh^1,2, Michael J Dubec^1,2, James Price^2,3, Chris Moore¹, David L Buckley^1,4, James P. B. O'Connor^2,5,6, David J Thomson³, and Andrew McPartlin^3
1Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom, ²Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom, ³Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United Kingdom, ⁴Biomedical Imaging, University of Leeds, Leeds, United Kingdom, ⁵Department of Radiology, The Christie NHS Foundation Trust, Manchester, United Kingdom, ⁶Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom

Intravoxel incoherent motion (IVIM) can provide information about tissue perfusion in tumours and organs at risk, but the model may not be applicable in all voxels in a region of interest. Here, a model comparison framework is developed, based on comparing IVIM and apparent diffusion coefficient model fits, aiming to identify perfused voxels and quantify the proportion of tissue containing a perfusion component, p_IVIM. Technical validation of the framework is performed, with simulations and phantom data showing that SNR and diffusion properties can bias p_IVIM, while in vivo parotid gland data show that p_IVIM exhibits good repeatability.

Alexandre Triay Bagur¹, Michael Brady², Arun Jandor², Paul Aljabar², and Daniel Bulte^1
1Department of Engineering Science, University of Oxford, Oxford, United Kingdom, ²Perspectum Ltd, Oxford, United Kingdom

Impairment of the pancreas has been shown in initial findings of the Long COVID-19 study (COVERSCAN), that uses quantitative MRI and expert manual analysis of the pancreas. Quantitative MRI analysis in such large-scale studies benefits from the decision support made possible by advanced image analysis methods. In this work, we validate a semi-automated pancreas processing pipeline that involves manual slice selection and automated segmentation and MRI-PDFF quantification. We show good agreement of the semi-automatic method with the reference manual processing by experts, as well as repeatable quantification in a scan re-scan subset of healthy subjects within COVERSCAN (n=35).