Lin Chen^1,2, Anja Soldan³, Kenichi Oishi¹, Andreia Faria¹, Marilyn Albert³, Peter van Zijl^1,2, and Xu Li^1,2
1Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ³Department of Neurology, Johns Hopkins University, Baltimore, MD, United States

We investigated associations of brain volume, iron levels as measured by QSM-MRI, and β-amyloid plaque load as measured by ¹¹C-PiB PET imaging on prospective cognitive trajectories, measured using a global and domain-specific cognitive composite scores (e.g., episodic memory, executive function, visuospatial processing and language) in cognitively normal older adults with maximum follow-up of 5 years. Greater volume of multiple cortical and subcortical brain regions was strongly associated with the rate of cognitive decline. Associations between brain iron and β-amyloid and longitudinal cognitive decline were weaker, with brain iron in the basal ganglia and entorhinal cortex predicting global decline.

Ryota Sato¹, Kohsuke Kudo², Niki Udo³, Masaaki Matsushima⁴, Ichiro Yabe⁴, Akinori Yamaguchi², Makoto Sasaki⁵, Masafumi Harada⁶, Noriyuki Matsukawa⁷, Tomoki Amemiya¹, Yasuo Kawata¹, Yoshitaka Bito¹, Hisaaki Ochi¹, and Toru Shirai^1
1Healthcare Business Unit, Hitachi, Ltd., Tokyo, Japan, ²Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Hokkaido, Japan, ³Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan, ⁴Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Hokkaido, Japan, ⁵Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan, ⁶Department of Radiology, Tokushima University, Tokushima, Japan, ⁷Department of Neurology, Nagoya City University, Aichi, Japan

For early diagnosis of Alzheimer’s disease, we created and evaluated a prediction method of amyloid β deposition based on multiple regression analysis of quantitative susceptibility mapping. A multiple regression model to predict standard uptake values (SUVs) of amyloid PET was constructed based on susceptibilities in 47 brain regions with the constraint Aβ deposition and susceptibility being positively correlated. The correlation coefficients between true and predicted SUVs were increased by incorporating the constraint, and the area under the receiver operating characteristics curve to predict Aβ positivity was 70%. The results suggest that the model could predict Aβ positivity at moderate accuracy.

Marta Lancione^1,2, Matteo Cencini^2,3, Mauro Costagli^3,4, Graziella Donatelli^2,5, Michela Tosetti^2,3, Claudio Pacchetti⁶, Pietro Cortelli^7,8, and Mirco Cosottini^5
1IMT School for Advanced Studies Lucca, Lucca, Italy, ²IMAGO7 Foundation, Pisa, Italy, ³IRCCS Stella Maris, Pisa, Italy, ⁴Department of Neuroscience, Rehabilitation, Ophtalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genova, Genova, Italy, ⁵Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy, ⁶Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy, ⁷Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy, ⁸Clinica Neurologica, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy

In this work we quantified iron deposition in gray matter nuclei in a cohort of MSA patients with parkinsonian and cerebellar phenotypes using Quantitative Susceptibility Mapping (QSM). As it captures different tissues contribution depending on TE, we performed an ROI-based histogram analysis on susceptibility maps computed at each TE of a multi-echo GRE sequence. We observed significant differences among groups in several ROIs, such as putamen, globus pallidus, caudate nucleus, substantia nigra and dentate nucleus. The area under the ROC curve was higher for short TEs suggesting that short-TE QSM enhances diagnostic performances in the presence of strong susceptibility sources.

Ibrahim Khormi^1,2, Oun Al-iedani^1,2, Amir Fazlollahi^2,3, Bryan Paton^2,4, Jeannette Lechner-Scott^2,4,5, Abdulaziz Alshehri^1,2, Kieran O'Brien^6,7, Steffen Bollmann⁸, Rishma Vidyasagar⁹, Scott Ayton⁹, Anne-Louise Ponsonby^9,10, and Saadallah Ramadan^1,2
1School of Health Sciences, University of Newcastle, Newcastle, Australia, ²Hunter Medical Research Institute, Newcastle, Australia, ³CSIRO Health and Biosecurity, Brisbane, Australia, ⁴University of Newcastle, Newcastle, Australia, ⁵John Hunter Hospital, Newcastle, Australia, ⁶Siemens Healthcare Pty Ltd, Brisbane, Austria, ⁷ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia, ⁸The University of Queensland, Brisbane, Australia, ⁹The Florey Institute of Neuroscience & Mental Health, Parkville, Australia, ¹⁰Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Melbourne, Australia

This novel study compared quantitative magnetic susceptibility signal of deep grey matter (DGM) structures in the MS brain. We evaluated the QSM metrics in selected deep grey matter regions in 5 RRMS patients and 9 matched HCs.  The STI suite software package was used for QSM image reconstruction. Compared to a reference region in HCs, a significant susceptibility change was detected in most DGM regions showing statistically significant RRMS cohort differences. QSM metrics in caudate showed strong correlations with depression scores, while pallidum and thalamus correlated significantly with anxiety. While results are limited due to small numbers, they provide the opportunity for further investigation in larger cohorts and strengthen these preliminary results.

Julian Emmerich^1,2, Frederik L. Sandig³, and Sina Straub^1
1Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany, ³Division Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

Quantitative susceptibility mapping (QSM) is known for its usefulness in imaging multiple sclerosis lesions. However, the co-occurrence of demyelination and iron accumulation due to the underlying inflammatory processes limit QSM from truthfully representing histology-like information as phase effects from positive and negative susceptibility sources within the same voxel cancel out in QSM. Here, it is shown that the separation of positive and negative susceptibility sources provides additional information to characterize susceptibility lesions.

Zungho Zun^1,2,3,4, Kushal Kapse¹, Nicole Andersen¹, Scott Barnett^1,2,3,4, Anushree Kapse¹, Kristina Espinosa¹, Jessica Quistorff¹, Catherine Lopez¹, Jonathan Murnick^1,3,4, Mary T. Donofrio^2,3,5, and Catherine Limperopoulos^1,2,3,4
1Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, United States, ²Division of Fetal and Transitional Medicine, Children's National Hospital, Washington, DC, United States, ³Department of Pediatrics, George Washington University, Washington, DC, United States, ⁴Department of Radiology, George Washington University, Washington, DC, United States, ⁵Division of Cardiology, Children’s National Hospital, Washington, DC, United States

Quantitative susceptibility mapping may be used to assess brain development in infants based on its ability to evaluate iron and myelin contents. We measured magnetic susceptibilities in healthy infants and those diagnosed with congenital heart disease (CHD) in the early postnatal period and investigated the associations with neurodevelopmental outcomes. We report significantly lower magnetic susceptibilities in white matter and temporal lobe of the CHD cohort and significant associations between magnetic susceptibility of the temporal lobe and Bayley-III language scores at 18 months. Our findings may suggest disturbed iron deposition in the temporal lobe can lead to delays in language development.
 

Alexander Mark Weber¹, Yuting Zhang², Christian Kames³, and Alexander Rauscher^1
1Pediatrics, UBC, Vancouver, BC, Canada, ²Radiology, Children’s Hospital of Chongqing Medical University, Chongqing, China, ³Physics, UBC, Vancouver, BC, Canada

We aimed to test whether Cerebral venous oxygen saturation (CS_VO₂) could be measured using quantitative susceptibility mapping (QSM) in three distinct groups: healthy term neonates, and asphyxia injured term and preterm neonates.

We acquired multi-echo gradient echo MRI data in 16 neonates with perinatal asphyxia and moderate or severe hypoxic-ischemic encephalopathy (HIE) (eight term-age, eight preterm, in eight healthy term-age controls.

QSM derived oxygen saturation values in preterm and term neonates agreed well with past literature. CS_VO₂ in preterm and term neonates with HIE, however, were not found to be significantly different from each other or healthy controls.

Russell Murdoch¹, Hanne Stotesbury², Jamie Kawadler², Dawn Saunders², Fenella Kirkham², and Karin Shmueli^1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Imaging and Biophysics, Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom

In 88 sickle cell anaemia (SCA) patients and 30 healthy controls, quantitative susceptibility mapping (QSM) showed significantly lower venous oxygen saturation (Y_v) in the superior sagittal sinus of SCA patients. SCA subjects with silent cerebral infarcts (SCI) showed significantly lower Y_v relative to those without SCI. 39 SCA subjects participated in a clinical study investigating the effect of auto-adjusting positive airways pressure (APAP) over a period of six months. No significant Y_v differences were observed between 21 patients receiving APAP and 18 receiving standard care. In the APAP group, treatment compliance was positively correlated with increases in Y_v.

Jian Shen¹, Aart Nederveen², and John Wood^1,3
1Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, ²Radiology, Academic Medical Center, Amsterdam, Netherlands, ³Children's Hospital Los Angeles, Los Angeles, CA, United States

Brain oxygenation can be measured using either T2-based methods or magnetic susceptibility-based methods. This study validates QSM and CISSCO methods in measuring the oxygenation in the internal cerebral vein and compares the results in sickle cell disease patients, anemia subjects with normal hemoglobin and healthy controls. Both methods reveal the group difference in the oxygen saturation in the deep structures. The limitations for both methods are discussed and the explanation for the bias between the two methods is provided.

Russell Murdoch¹, Hanne Stotesbury², Jamie Kawadler², Dawn Saunders², Fenella Kirkham², and Karin Shmueli^1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Imaging and Biophysics, Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, United Kingdom

Little is known about the histopathology of silent cerebral infarcts (SCI) in sickle cell anaemia (SCA). Therefore, we measured the magnetic susceptibility (χ) of SCI in 45 SCA subjects and 10 healthy controls using quantitative susceptibility mapping (QSM) calculated from two different gradient-echo (GRE) acquisitions. Significantly lower χ was measured in lesions located in the parietal lobes relative to the frontal lobe. No significant relationships with mean lesion χ were observed with subject age, lesion size or depth in white matter. Strong correlations and minimal biases were observed between mean lesion χ measured using the two GRE acquisitions. 

Julia V Velikina¹, Ruiyang Zhao^1,2, Collin Buelo², Alexey A Samsonov¹, Scott Reeder^1,2,3,4,5, and Diego Hernando^1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, ³Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States, ⁴Emergency Medicine, University of Wisconsin - Madison, Madison, WI, United States, ⁵Medicine, University of Wisconsin - Madison, Madison, WI, United States

QSM may enable accurate quantification of liver iron overload.  However, QSM of the abdomen faces a number of unique challenges due to large variations in susceptibility, presence of fat, and motion, which further confound the ill-posed inverse problem. We propose an approach to optimize the use of additional information provided by CSE imaging to regularize the QSM inversion problem. We validated this approach at 3T in patients with various levels of iron overload, including assessment of test-retest repeatability. This approach resulted in significantly reduced shading artifact, improved quality of susceptibility maps, and higher repeatability of measurements.

Ruiyang Zhao^1,2, Collin J Buelo², Julia V Velikina¹, Steffen Bollmann³, Ante Zhu⁴, Scott B Reeder^1,2,5,6,7, and Diego Hernando^1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ³School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia, ⁴GE Global Research, Niskayuna, NY, United States, ⁵Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁶Medicine, University of Wisconsin-Madison, Madison, WI, United States, ⁷Emergency Medicine, University of Wisconsin-Madison, Madison, WI, United States

A novel deep learning-based technique for quantitative susceptibility mapping (QSM) of liver iron overload was developed and validated. The proposed method relies on a 3D fully convolutional neural network, trained using synthetic dataset from a digital torso phantom that includes major organs. This study also included patients with iron overload who were imaged under 3T with using a single breath-hold multi-echo acquisition. Results showed promising performance and agreement with reference susceptibility measurements across a wide range of iron overload cases.

Ashmita De¹, Derek J. Emery², Kenneth S. Butcher³, and Alan H. Wilman^1
1Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada, ²Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada, ³Division of Neurology, Department of Medicine, University of Alberta, Edmonton, AB, Canada

Quantitative Susceptibility Weighted Imaging or True SWI(tSWI) has been recently developed to overcome the shortcomings of SWI. SWI images are computed from filtered phase images, however, tSWI utilizes the susceptibility maps for its computation. Eight intracranial hemorrhage patients were scanned at 3T with 3D SWI sequence. Blooming effect and phase wrap artifacts that remain on SWI images of hemorrhage are removed in tSWI.  tSWI provides better susceptibility weighting than magnitude within the hemorrhage and improved the texture visualization as compared Quantitative Susceptibility Mapping(QSM). Thus, tSWI can be a useful addition for hemorrhage visualization when SWI cannot provide a clear depiction.

Anja Samardzija¹, Thanh Nguyen², Elizabeth Sweeney², Kailyn Lee², Ilhami Kovanlikaya², Yi Wang ², Andrew Schweitzer², and Apostolos Tsiouris^2
1Electrical and Computer Engineering, Cornell University, Highlands, NJ, United States, ²Weill Cornell Medicine, New York City, NY, United States

We trained a Random Forest classification model to classify amyotrophic lateral sclerosis (ALS) patients from those with mimicking clinical presentations based on QSM radiomic features extracted from the primary motor cortex. In a validation set, the model has 0.8 accuracy, 0.75 specificity of 0.75 and 0.84 sensitivity, which is superior to models using the mean QSM value as cutoff with 0.59 accuracy, 0.94 specificity and 0.14 sensitivity. 

Marjolein Bulk¹, Thijs van Harten¹, Boyd Kenkhuis¹, Francesca Inglese¹, Ingrid Hegeman¹, Sjoerd van Duinen¹, Ece Ercan¹, Cesar Magro-Checa^1,2, Jelle Goeman¹, Christian Mawrin³, Mark van Buchem¹, Gerda Steup-Beekman¹, Tom Huizinga¹, Louise van der Weerd¹, and Itamar Ronen^1
1Leiden University Medical Center, Leiden, Netherlands, ²Zuyderland Medical Center, Heerlen, Netherlands, ³Otto-von-Guericke University, Magdeburg, Germany

We explored the link between iron accumulation and neuroinflammation in basal ganglia in SLE using quantitative susceptibility mapping. We hypothesized that SLE patients, and in particular NPSLE patients would have increased numbers of activated microglia co-localizing with iron, which in turn would be reflected in increased local susceptibility. Based on QSM results in patients, as well as on iron staining of post-mortem SLE brain tissue, our results suggest that neuroinflammation in NPSLE is not necessarily associated with iron accumulation, and that the inflammatory pathomechanism in SLE may differ from the one observed in neurodegenerative diseases and in multiple sclerosis.

Jan Sedlacik^1,2, Raphael Tomi-Tricot^1,3, Pip Bridgen^1,2, Tom Wilkinson^1,2, Sharon Giles^1,2, Karin Shmueli⁴, Jo V Hajnal^1,2, and Shaihan J Malik^1,2
1Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom, ²Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom, ³MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, ⁴MRI Group, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom

Quantitative Susceptibility Mapping (QSM) used for microstructural assessment of white matter (WM) is very attractive at ultra high magnetic field  strengths, due to the increased signal-to-noise ratio (SNR) and phase sensitivity. This allows shortening echo and repetition times and, therefore, acquisition time. Further advantages of QSM are the low flip angles used for scanning, which results in low specific absorption rates, and the B₁ insensitivity of the signal phase. However, suboptimal choice of imaging parameters will result in suboptimal SNR. The purpose of this work is to find and test optimal scanning parameters for QSM of the WM at 7T.

Alexey Dimov¹, Thanh Nguyen¹, Susan Gauthier², and Yi Wang^3
1Radiology, Weill Cornell Medicine, New York, NY, United States, ²Neurology, Weill Cornell Medicine, New York, NY, United States, ³Weill Cornell Medicine, New York, NY, United States

The role of CSF segmentation for zero-referenced MEDI+0 is demonstrated. In the present study we show that it is essential to enforce consistency in the CSF mask between different timepoints to ensure value reproducibility and to minimize effects of random shifts in the solution of MEDI+0 minimization

Priya S Balasubramanian^1,2, Alexandra Grace Roberts^1,2, Pascal Spincemaille², Thanh Nguyen ², and Yi Wang^1,2
1Cornell University, New York City, NY, United States, ²Weill Cornell Medical College, New York City, NY, United States

QSM uses a mask to separate tissue of interest from background to avoid the strong susceptibility sources and poor signals that are known to cause artifacts in QSM. In brain QSM, the strongly paramagnetic superior sagittal sinus (SSS) lies at the border of brain mask. Perturbing the brain mask by reducing the SSS inclusion in QSM reconstruction also affects the convergence of strong susceptibility sources inside the brain. This mask perturbation propagates into QSM perturbation, which may be used as a measure of artifacts associated with strong susceptibility sources as validated in numerical phantom and COSMOS data. 

Priya S Balasubramanian^1,2, Pascal Spincemaille², Thanh Nguyen², and Yi Wang^1,2
1Cornell University, New York City, NY, United States, ²Weill Cornell Medical College, New York City, NY, United States

Quantitative susceptibility mapping methods that selectively mask based on susceptibility thresholds and do regional reconstructions  have been introduced to reduce shadowing artifacts when dealing with a large dynamic susceptibility range within the image. Here, we combine this technique with total field reconstructions, which have been shown to reduce errors resulting from incomplete background field removal. Reduced errors and shadow artifacts are demonstrated when compared to prior techniques.

Chang Liu¹, Hongru Jia¹, Weiqiang Dou², Jing Ye¹, and Xianfu Luo^1
1Northern Jiangsu People’s Hospital, Yang zhou, China, ²GE Healthcare,MR Research China, Bei jing, China

In this study, we aimed to investigate susceptibility changes related to microvascular invasion (MVI) of hepatocellular carcinoma. We applied liver quantitative susceptibility mapping to measure lesions’ susceptibility. Significant differences in both tumorous and peritumoral susceptibility values were observed for MVI positive and negative lesions. With these findings, QSM imaging can be considered a potential technique for noninvasive preoperational assessment of MVI in hepatocellular carcinoma.