Jin Zhang¹, Karl Kiser¹, Chongda Zhang¹, Ayesha Bharadwaj Das¹, and Sungheon Gene Kim^1
1New York University School of Medicine, New York, NY, United States

Quantitative pharmacokinetic model parameter maps from dynamic contrast enhanced (DCE)-MRI can provide useful physiologically relevant information about tumor microenvironment, but often in low spatial resolution due to challenges in acquiring high resolution 3D data with high temporal resolution. The purpose of this study is to investigate the feasibility of generating the whole tumor high resolution pharmacokinetic model parameter maps with the 3D-UTE-GRASP¹ sequence for both T₁ mapping and dynamic scan. 

Inge Verheggen¹, Joost de Jong², Martin van Boxtel¹, Alida Postma², Frans Verhey¹, Jacobus Jansen^2,3, and Walter Backes^2
1Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands, ²Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, ³Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands

Circumventricular organs (CVOs), located around the ventricles without blood-brain barrier, maintain homeostasis between the blood, cerebrospinal fluid, and brain. Secretory CVOs are involved in peptide release and sensory CVOs regulate signal transmission. These organs can be an entrance point for pathogens. For the first time, physiological properties of the CVOs were assessed in vivo with dynamic contrast-enhanced (DCE) MRI.

Assessing pharmacokinetics (leakage rate; blood perfusion; uptake capacity/retention) with DCE MRI in 20 healthy males, demonstrated that only secretory CVOs had noticeable stronger hemodynamics and higher permeability than normal-appearing brain matter.

Xingfeng Shao¹, Samantha Jenny Ma¹, and Danny JJ Wang^1,2
1Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ²Department of Neurology, University of Southern California, Los Angeles, CA, United States

A diffusion-weighted arterial spin labeling (DW-ASL) technique has been proposed to non-invasively measure water exchange rate (kw) across the BBB. kw was compared with GBCAs permeability (Ktrans) in aged subjects at risk of small vessel disease. A positive correlation was found between kw and Ktrans only in the caudate, suggesting different BBB mechanisms probed by kw and Ktrans. Significant increase of kw was found in subjects with diabetes or high vascular risk while no Ktrans difference was observed. Water permeability could be a sensitive biomarker to study glymphatic function and vascular diseases before detectable BBB disruption occurs.

Benoît Bourassa-Moreau¹, Réjean Lebel¹, Guillaume Gilbert², David Mathieu³, and Martin Lepage^1
1Centre d’imagerie moléculaire de Sherbrooke, Département de médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, QC, Canada, ²MR Clinical Science, Philips Healthcare Canada, Markham, ON, Canada, ³Service de neurochirurgie, Département de chirurgie, Université de Sherbrooke, Sherbrooke, QC, Canada

The arterial input function measured for brain dynamic contrast-enhanced MRI is contaminated by the signal contribution of surrounding tissues. This work corrects these partial volume effects on signal level by using the surrounding gray matter enhancement to discriminate pure arterial signal. The method also accounts for the high contrast agent concentration reached in arteries and veins that leads to signal non-linearity, saturation, and concurrent unwanted $$$T_2^*$$$ effects. This partial volume correction method is compared to concentration scaling on a digital reference object and on eight subjects. Better recovery of the arterial first pass and recirculation are shown.

Yannick Bliesener¹, Robert Marc Lebel^2,3, Jay Acharya⁴, Richard Frayne⁵, and Krishna Shrinivas Nayak^1
1Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, ²Applications and Workflow, GE Healthcare, Calgary, AB, Canada, ³Department of Radiology, University of Calgary, Calgary, AB, Canada, ⁴Department of Clinical Radiology, Keck School of Medicine of University of Southern California, Los Angeles, CA, United States, ⁵Departments of Radiology, and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada

Brain DCE MRI suffers from poor spatial coverage, lack of standardization, and insufficient quantitative understanding of the extent of (physical) uncertainty in the measurements. Here, we attempt to overcome these by providing a fully automated high-resolution whole-brain DCE MRI pipeline with no user interaction. Prospective test-retest repeatability evaluation is challenging, therefore we employ a surrogate: multiple post-treatment time points in stable brain tumor patients. The proposed framework is able to yield consistent vascular input functions and tracer kinetic parameter histograms for repeated visits.

Oliver Gurney-Champion¹, Matthew Orton¹, Kevin Harrington¹, Uwe Oelfke¹, and Sebastiano Barbieri^2
1The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom, ²Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia

We introduce a novel approach to fitting parameters from DCE MRI using an unsupervised neural network. The network is trained on in vivo data, with no ground truth, and is able to predicts DCE model parameters directly from the obtained MRI images. In simulations, our method outperformed the ordinary least squares fit approach in that it is more accurate and precise. In vivo, it produced substantially less noisy parameter maps than the current practise least-squares fit.

Qihao Zhang¹, Liangdong Zhou², John Morgan³, Thanh D Nguyen⁴, Pascal Spincemaille³, and Yi Wang^2
1Biomedical Engineeering, Cornell University, New York, NY, United States, ²Weill Cornell Medicine, New York, NY, United States, ³Radiology, Weill Cornell Medicine, New York, NY, United States, ⁴Weill Cornell Medicine College, New York, NY, United States

We purpose to calculate a tracer velocity field by solving the inverse problem of a voxelized transport equation for time resolved 3D (4D) dynamic contrast enhanced (DCE) data, which is termed as quantitative transport mapping (QTM). Using a porous medium model, the 4D imaging data is connected to the voxel-averaged transport equation of mass flux. The transport inverse problem is solved to estimate velocity and pseudo tortuosity. QTM provides the advantage of high accuracy in numerical validation and automated procession without manual input for in vivo DCE brain tumor data, compared to the traditional Kety’s method of perfusion quantification.

Patrick Werner^1,2, Patrick Schuenke¹, Antje Ludwig³, Daria Dymnikova⁴, Christian Teutloff⁴, Matthias Taupitz⁵, and Leif Schröder^1
1Leibniz-Forschungsinstitut fuer Molekulare Pharmakologie (FMP), Berlin, Germany, ²BIOphysical Quantitative Imaging Towards Clinical Diagnosis (BIOQIC), Berlin, Germany, ³Center for Cardiovascular Research (CCR), Charite Berlin, Berlin, Germany, ⁴Freie Universität Berlin, Berlin, Germany, ⁵Department of Radiology, Charite Berlin, Berlin, Germany

Gd³⁺-ions can be released from GBCAs after in vivo application and polysaccharides like glycosaminoglycans are candidates for binding of released Gd³⁺-ions by acting as competing chelators. We showed that the chelation of Gd³⁺-ions to polysaccharides cause an increase of R₁ due to the high relaxivity of such complexes. However, at high GAG/Gd³⁺ ratios and in cell experiments, we observed a decrease of R₁ after the chelation of Gd³⁺. Our results demonstrate the importance of more in vivo-like setups for the investigation of gadolinium transchelation processes to prevent an underestimation of the amount of deposited gadolinium in biological tissues.

Obata Takayuki¹, Takuya Urushihata¹, Manami Takahashi¹, Sayaka Shibata¹, Nobuhiro Nitta¹, Jeff Kershaw¹, Yasuhiko Tachibana¹, Masato Yasui², Ichio Aoki¹, Tatsuya Higashi¹, Makoto Higuchi¹, and Hiroyuki Takuwa^1
1National Institute of Radiological Sciences, QST, Chiba, Japan, ²Department of Pharmacology, Keio University School of medicine, Tokyo, Japan

Using dynamic PDWI after intraperitoneal D2O injection, we observed a difference in the D2O distribution between aquaporin-4 knockout (AQP4-ko) and wild type (Wild) mice with MCA occlusion. The results suggest that blood flow changes and cell membrane water permeability have a complex relationship.

Michaël Bernier^1,2, Olivia Viessmann^1,2, Ned Ohringer¹, Jingyuan E. Chen^1,2, Nina E. Fultz^1,3, Rebecca Karp Leaf⁴, Lawrence L. Wald^1,2,5, and Jonathan R. Polimeni^1,2,5
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Radiology, Harvard Medical School, Boston, MA, United States, ³Engineering, Boston University, Boston, MA, United States, ⁴Division of Hematology, Massachusetts General Hospital, Boston, MA, United States, ⁵5Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

Ferumoxytol—a safe, superparamagnetic iron oxide nanoparticle that amplifies T2* dephasing in blood vessels—can be used as a powerful image contrast enhancement agent to aid vascular imaging. Combining this with an innovative vascular segmentation tool, here we evaluate how Ferumoxytol improves vascular detection throughout the brain using a region-based analysis of the gray-matter and a bundle-specific analysis of the white-matter. We report increases in white-matter vasculature specificity and uncover spatial patterns similar to white-matter tracts, therefore this work sheds new light on the possible existence and influence of a concurrent network of vasculature that follows the known fiber bundles.