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Gordon Lecture: Advanced MRIs in CNS


Dr. Meiyun Wang is a neuroradiologist, Professor and Chair of the Medical Imaging Center of Henan Province and Chair of the Department of Radiology of Henan Provincial People’s Hospital. She received her M.D. from Southeast University in 1995, a PhD from Capital University of Medical Sciences in 2005, and then worked as a post-doctoral research fellow at the Massachusetts General Hospital, Harvard Medical School from 2006-2008. She became the Vice-Chair in 2008 Chair in 2016 of the Department of Radiology of Henan Provincial People’s Hospital in China.
Below is a summary of her presentation.

In this talk, the applications of three non-contrast enhanced advanced MR techniques, including Diffusion Kurtosis Imaging (DKI), Strategically Acquired Gradient Echo (STAGE) and a Length and Offset Varied Saturation (LOVARS) in central nervous system (CNS) were summarized.

DKI has been used to measure non-Gaussian diffusion, which has the potential to characterize both normal and pathologic tissue better than diffusion-tensor imaging. Some previous researchers have suggested that DKI might provide more accurate information about water diffusion. Dr. Wang's study showed that mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.

STAGE is an advanced Susceptibility weighted imaging (SWI) which can provide multi-contrast images in one scan, such as T1W, PDW, T1 MAP, PD MAP, R2* MAP, SWI, and even MRA images in 5 minutes. It is very helpful in early detecting and evaluating ischemia, brain trauma and some other CNS diseases.

LOVARS is a novel Chemical exchange-dependent saturation transfer (CEST) technique with variable length of saturation for 1 pair of offsets, which can detect endogenous macromolecules (e.g. Tumor associated glycoprotein MUC-1) and metabolites. Some preliminary studies have showed that LOVARS is not only helpful in early detection and separation of cerebral ischemia and intracranial hemorrhage, but also in grading glioma, evaluating the therapy effect and even differentiating treatment effect from tumor reoccurrence. Furthermore, it can also detect and differentiate cerebral ischemia from intracranial hemorrhage at very early stage. So it may have the potential to improve the diagnostic flow for early stroke. But its post-processing is still complicated.

Gordon Lecture Series: Learning reconstruction and analysis for medical imaging


Dr. Shanshan Wang is an associate professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. She received her dual Ph.D degree from the University of Sydney and Shanghai Jiaotong University respectively in information technologies and biomedical engineering. Dr. Wang was a finalist for the Australian John Makepeace Bennett Best Thesis Award and won the 2018 OCSMRM Outstanding Research Award. Her research interests include machine learning, fast medical imaging and biomedical signal analysis.
Below is a summary of her presentation

Inverse problems are ubiquitous in the field of medical imaging and image processing. Prominent examples include fast MR imaging and image denoising. The goal of these problems is to reconstruct or restore an unknown image from a set of direct/indirect measurements. However, due to the limitation of the acquisition time or the existence of noise, the obtained measurements are often corrupted or incomplete, which introduces big challenges for the reconstruction process and the following clinical diagnosis. In order to remove the noise or overcome the ill-posed nature caused by the insufficient measurements, it is necessary to explore the prior knowledge and utilize them to form constraints in the reconstruction process so as to make up for the missing or corrupted information.

However, traditional prior knowledge regularizations and their corresponding algorithms suffer from loss of the detailed information such as texture and structure while reducing the image degradation factors. To attack these issues, Dr. Wang and her colleagues have developed a series of machine learning based medical imaging methods and algorithms, which can draw valuable prior from either the target or offline medical images and therefore assist efficient clinical uses. To better facilitate clinical diagnosis, they also have sought to extract quantitative features from medical images to uncover disease characteristics that fail to be appreciated by the naked eye. They try to build computer aided tools to release the clinicians from boring and tedious work like image segmentation, classification and lesion detection. The developed methods are being applied in different clinical settings including stroke MR imaging using deep prior learning, dictionary learning for undersampled reconstruction, as well as breast cancer analysis with neural network guided lesion classification and segmentation algorithms. 

Dr. Kwon

Gordon Lecture: Activatable Molecular Probes for Optical Imaging


Dr. Ick Chan Kwon is a Presidential Scholar at KIST-DFCI On-Site-Lab in Department of Cancer Biology, Dana Farber Cancer Institute Boston. He is a Tenured Principal Research Scientist of Korea Institute of Science and Technology (KIST). He received his B.S. and M.S. degrees in College of Engineering at Seoul National University and his Ph. D. in Pharmaceutics and Pharmaceutical Chemistry from University of Utah. After a post-doctoral training at CCCD in University of Utah, he joined KIST where he started his research on polymeric nanoparticle-based drug delivery system for antibiotics, anticancer drugs and gene therapy. He also pioneered in a research filed of Theragnosis, by combining molecular imaging and drug delivery system with smart nano-probes. He is a fellow of The Korean Academy of Science & Technology and a member of The National Academy of Engineering of Korea.
Below is a summary of his presentation

Dr. Kwon

For decades, molecular imaging which can monitor inter-/intracellular functions or molecular processes in an organism has provided valuable information for various research fields. Biomarkers such as enzymes, receptors and proteins can be utilized as a target of molecular imaging since they can provide information for early diagnosis and monitoring therapeutic effect of diseases. Among them, receptor-ligand interaction based molecular imaging technique has been emerging promising strategy in theragnosis of intractable diseases such as cancer.
In this talk, Dr. Kwon introduced epidermal growth factor receptor (EGFR) and CD 47 receptor-specific self-quenched imaging probes, which can emit fluorescence (activate) via de-quenching reaction in lysosome. His talk also included a simple noninvasive labeling and tracking technique for cell therapeutics via combination of metabolic glycoengineering and biootherogonal copper-free click chemistry, resulting in the cells being tracked via near-infrared fluorescence (NIRF), magnetic resonance (MR) and computed tomography (CT) imaging without cytotoxicity and functional interference.

Gordon Lecture Series: Identify External Funding Opportunities with Pivot


The facilitator, Amy Robb is Associate Director for Prospect Research and Funding Opportunities in the Office of Development. Ms. Robb holds a master’s in library and information science from UIUC and a graduate certificate in women’s studies from the George Washington University. Below is a summary of her presentation.

Amy Robb

In this seminar, Ms. Robb taught how to identify external funding opportunities using Pivot – a library database that indexes announcements for grants, fellowships, conferences and equipment acquisition.  The advantage of Pivot is that it contains information about government, philanthropic, industry, and international funding opportunities from across different scientific disciplines. 

Ms. Robb discussed with the audience potential strategies to diversify funding portfolios. She also provided useful tips on searching funding opportunities and configuring funding alerts to provide individualized notification of new funding opportunities.

Dr. Georges El Fakhri Earns Edward J. Hoffman Award


This story was originally published on 03/12/2019 by Rad Times, a publication of the Mass General Hospital Department of Radiology.

The Edward J. Hoffman Award honors those who have made outstanding contributions to nuclear medicine research and education. The 2019 recipient is Georges El Fakhri, PhD, professor of radiology at Harvard Medical School and Massachusetts General Hospital in Boston, Massachusetts. He is receiving the award for outstanding contributions to quantitative SPECT, PET-CT and PET-MR imaging and to the education of nuclear medicine scientists and physicians.

Dr. Georges El Fakhri was one of twelve scientists and physicians elected Fellow to the Society of Nuclear Medicine and Molecular Imaging for his contributions to quantitative PET, CT and MR imaging during a special plenary session at the society’s 2018 annual meeting in June in Philadelphia. The SNMMI Fellowship was established in 2016 to recognize distinguished service to the society as well as exceptional achievement in the field of nuclear medicine and molecular imaging. It is one of the most prestigious formal recognitions available to longtime SNMMI members.

Gordon Lecture: Chemogenetics and Biobehavioral Imaging Integration Using PET


Dr. Juan Gomez is a Postdoctoral Fellow at the National Institute on Drug Abuse (NIDA) in Baltimore, Maryland. At NIDA, Dr. Gomez helped design and set up a new laboratory space integrating PET imaging and behavioral neuroscience modalities. His doctoral research was conducted with Dr. Victoria Luine at Hunter College, where he studied interactions between alcohol exposure and stress in rodents and received his Ph.D. from The Graduate Center of CUNY in 2012. Below is his presentation summary.

Dr. Gomez delivering his lecture

The use of chemogenetic technologies has produced minimally invasive techniques to modulate specific brain structures and/or neural networks in research animals and potentially in humans. Utilizing these methods has provided a boon in behavioral testing that does not involve the hindrance of movement restricting devices. Assisted by PET, Dr. Gomez's lab has characterized the mechanism of action of existing chemogenetic ligands used for activating virally implanted “designer” receptors. Data gathered from these experiments has led to novel revelations about the mechanism of action of popular chemogenetic technologies and more recently to synthesis of novel chemogenetic actuators and PET ligands with high affinity and efficacy for established chemogenetic receptors. Their goal is to leverage the availability of such minimally-invasive neuromodulation technologies with biobehavioral PET imaging methods to study pertinent behavioral neuroscience questions.

Gordon Lecture: Development of High Resolution PET Scanners with Depth Encoding Detectors


Prof. Yongfeng Yang got his Ph.D from Kyushu University, Japan in 2001. From 2002-2014 he worked at Prof. Simon Cherry’s lab at Department of Biomedical Engineering, UC Davis as postdoctoral fellow and project scientist. He has been a professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences since 2015. His research interests focus on instrumentation and application of positron emission tomography. The research of his lab is currently supported by Chinese National Science Foundation and Shenzhen City. Below is his presentation summary.

Depth of interaction uncertainty of the traditional PET detectors is solely the biggest obstacle for small animal and brain PET scanners to achieve high sensitivity and high spatial resolution simultaneously. In this presentation, first Dr. Yang presented his previous work on developing dual-ended readout depth encoding PET detectors with position sensitive APDs and developing a high resolution dedicated mouse brain PET scanner. Then the current work of his lab on developing MRI compatible small animal and brain PET scanners by using dual-ended readout detectors with SiPMs will be presented.

Radiology Employee Earns Certifications in Three Areas of Research Administration


This story was originally published on 03/12/2019 by  Rad Times, a publication of the Mass General Hospital Department of Radiology.

Ramzi El Fakhri, MBA, has become the first individual in New England to be certified in all three areas of research administration, namely research finance (CFRA), pre-award (CPRA), and general/post-award administration (CRA). There are only 11 other administrators in the US who hold all three designations at the same time.

The CFRA, CPRA and CRA recognize an individual’s knowledge in research administration and increase sponsored research offices' credibility. The minimum requirements for each designation are a bachelor’s degree, three years of relevant professional experience, and the successful completion of a national and rigorous exam organized by the Research Administrators Certification Council (RACC).

Ramzi manages a portfolio of grants and the PET Core research facility at the MGH Gordon Center where he has worked for the past three and half years.

Ramzi El Fakhri