Paola Scifo¹, Federico Fallanca¹, Maurizio Barbera², Annarita Savi¹, Valentino Bettinardi¹, Ilaria Neri¹, Giovanna Gattuso³, Maura Massimino³, Paolo Verderio⁴, Sara Pizzamiglio⁴, Andrea Falini^2,5, Luigi Gianolli¹, Filippo Spreafico³, Maria Picchio^1,5, and Cristina Baldoli^2,5
1Nuclear Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy, ²Neuroradiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy, ³Department of Medical Oncology and Hematology, Pediatric Oncology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy, ⁴Unit of Bioinformatics and Biostatistics, Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy, ⁵Vita-Salute San Raffaele University, Milan, Italy

A preliminary comparison between the two Atlas and ZTE attenuation correction methodologies in a group of pediatric patients with brain tumors is presented. The differences of the two ACmaps and PET images were calculated and the PET parameters were compared. Our results show that using ZTE or Atlas to generate ACmaps modifies the SUVs, but the differences in values are very small. Moreover, when metallic artefacts occur, both ZTE and Atlas show loss of signals but ACmaps_Atlas has smaller artefacts.

Archana Vadiraj Malagi¹, Devasenathipathy Kandasamy², Kedar Khare³, Fernando Calamante⁴, Raju Sharma², and Amit Mehndiratta^5,6
1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, Navi Mumbai, India, ²Department of Radiodiagnosis, All India Institute of Medical Sciences Delhi, New Delhi, India, ³Department of Physics, Indian Institute of Technology Delhi, New Delhi, India, ⁴Sydney Imaging and School of Biomedical Engineering, University of Sydney, Sydney, Australia, ⁵Indian Institute of Technology Delhi, New Delhi, India, ⁶Department of Biomedical Engineering, All India Institute of Medical Sciences Delhi, New Delhi, India

Optimization of b-values in IVIM-DKI is required for parameter estimation accuracy. IVIM-DKI model with Total Variation correction approach was employed in this study, which avoids abrupt changes in parameter values and eliminates non-physiological heterogeneity in maps. In pancreatic cancer, different b-value combinations were used: 4,6,8,10, and 13b-values. In terms of accurate parameter estimations and comparable qualitative maps, 8-13 b-values exhibited a similar trend; in contrast, 4b-values indicated inaccurate and noisy maps. 8b-values can be employed in pancreatic cancer with a constrained technique for a shorter acquisition process and reduced noise in parameter maps at low SNR.

Sebastian Eduardo Fonseca¹, Sheng-Qing Lin¹, Limin Zhou¹, Yiming Wang¹, and Ananth J Madhuranthakam^1,2
1Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States, ²Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

Diffusion weighted imaging (DWI) is a highly valuable MR imaging technique in the clinic. Single-shot EPI is the reference standard sequence for DWI due to its speed, however it suffers from severe distortion artifacts that can obscure potential pathologies. In this abstract, we present a novel 3D acquisition strategy that uses a fast spin echo readout and variable density sampling for volumetric DWI. The oversampled center region serves as navigator to correct phase errors. We present preliminary results in brains of healthy volunteers compared  to the standard sequences used in DWI.

Hanna Frantz¹, Tobias Lobmeyer¹, Patrick Metze¹, Thomas Hüfken¹, Kilian Stumpf¹, Julien Rivoire², Hizami Murad², and Volker Rasche^1
1Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany, ²RS2D, Mundolsheim, France

Zero echo time (ZTE) imaging is an established approach for three-dimensional imaging of tissues and materials with ultrashort T2* relaxation times. An intrinsic disadvantage of this approach are missing data points in the center region of k-space due to hardware limitations. These missing points are often retrospectively interpolated or subsequently acquired using single-point imaging approaches or additional ZTE acquisitions with decreased resolutions. The presented approach relies on an interleaved combination of ZTE read-outs with different resolutions in combination with Compressed Sensing, to acquire the k-space center, thus enabling k-space based self-gating.

Brian Matthew Bozymski¹, Xin Shen², Ali Caglar Özen³, Serhat Ilbey³, Albert Thomas⁴, Mark Chiew⁵, Ulrike Dydak^1,6, and Uzay Emir^1,2
1School of Health Sciences, Purdue University, West Lafayette, IN, United States, ²Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, ³Department of Radiology, Medical Center, University of Freiburg, Freiburg, Germany, ⁴Department of Radiology, University of California, Los Angeles, CA, United States, ⁵Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, ⁶Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States

Feasibility of a novel, rosette trajectory UTE (70 μs) 3D ³¹P MRSI sequence is tested at 3T in phantoms and in upper leg scan with healthy subject.  Braino phantom, proton resolution phantom, and highly concentrated ³¹P phantom test demonstrated proper reconstruction and metabolite localization.  In vivo calculations of acquired PCr and β-ATP signals showed competitive SNR across 20 voxels of interest.  With further acceleration, the sequence may serve as a superior alternative to conventional weighted 3D MRSI, allowing for greater SNR or resolution in briefer times.  Notably, this unprecedentedly short UTE ³¹P MRSI intrinsically avoids baseline and phasing issues.

Hans Martin Kjer^1,2, Mariam Andersson², Alexandra Pacureanu³, Vedrana Andersen Dahl¹, Anders Bjorholm Dahl¹, and Tim Bjørn Dyrby^1,2
1Technical University of Denmark, Kgs. Lyngby, Denmark, ²Danish Research Centre for Magnetic Resonance, Hvidovre, Denmark, ³European Synchrotron and Radiation Facility, Grenoble, France

Complex fiber regions where multiple tracts and bundles intersect are challenging to study with diffusion weighted MRI (DWI), due to the anatomical variation and 3D complexity within the volume covered by the measure voxel. Using x-ray nano-holotomography (XNH) we have been able to obtain and analyze a volume from a complex fiber region and make a comparison against DWI measurements from the same location of the same ex-vivo monkey brain. We derive comparable micro-structural features in the form of orientation distributions and anisotropy measures and show strong connections between them.

Chaithya G R^1,2 and Philippe Ciuciu^1,2
1NeuroSpin, Joliot, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France, ²Inria, Parietal, Université Paris-Saclay, F-91120, Palaiseau, France

We benchmark the current existing methods to jointly learn non-Cartesian k-space trajectory and reconstruction: PILOT¹, BJORK² and compare them with those obtained from recently developed generalized hybrid learning (HybLearn) framework³. We present the advantages of using projected gradient descent to enforce MR scanner hardware constraints as compared to using added penalties in the cost function. Further, we use the novel HybLearn scheme to jointly learn and compare our results through retrospective study on fastMRI validation dataset.

Alexandra G O'Neill¹, Tavianne M Kemp¹, Sajan G Lingala², and Angel R Pineda^1
1Mathematics Department, Manhattan College, Riverdale, NY, United States, ²Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States

We evaluated undersampling in MRI using a multicoil SENSE reconstruction with no regularization based the detection of signals by humans.  We used a sparse difference-of-Gaussians (S-DOG) model to predict human performance in the detection of a small and large signal in anatomical backgrounds.  The prediction was then validated using human observer two-alternative forced choice (2-AFC) tasks.  Our model predicted a decrease in performance for both the small and large signal from 4X to 5X acceleration.  Our observer study validated that prediction.  This approach may lead to a way of assessing image quality that predicts human performance with fewer observer studies.

M. Okan Irfanoglu¹, Grayson Clark¹, and Carlo Pierpaoli^1
1QMI, NIBIB/NIH, Bethesda, MD, United States

Our goal is to determine whether diffusion MRI acquisitions with different phase-encoding directions (PEDs) result in comparable quantitative measures in different regions of the human brain, or whether PEDs introduce a bias. Additionally, we aim to determine if for a given region, a set of PEDs has better reproducibility. For several regions, PA phase-encoding direction resulted in values that were significantly different than the other three. LR/RL phase-encoding was more reproducible compared to AP/PA in most brain regions, with frontal white matter being the exception. The main source of these reproducibility variations was identified as ghosts overlapping with brain regions.