Workshop and Launch of the Integrative Cancer Imaging Research Program (iCIRP)

The Integrative Cancer Imaging Research Program (iCIRP) is a joint program between Emory University School of Medicine Department of Radiology and Imaging Sciences, Georgia Tech/Emory Coulter Department of Biomedical Engineering, and Winship Cancer Institute of Emory University. This program will build on and synergize unique strengths inherent in Emory units and centers that foster multidisciplinary collaborations within and among the disciplines of imaging science, cancer biology, nanotechnology, biomarker development, computation, and clinical cancer research. The overarching goal of the iCIRP program is to advance cancer detection, diagnosis, prognosis, image-guided therapy, prediction of efficacy, and monitoring of treatment.

Dr. Baowei Fei’s talk on the introduction of the Program: PDF File

For more information about this program, please visit: http://feilab.org/publication_pdf/Fei_iCIRP.pdf

Dr. Baowei Fei served as Chair for NIH Study Section ZRG1 SBIB-F (56)R on Early Phase Clinical Trials in Imaging and Image-guided Interventions

This Funding Opportunity Announcement (FOA) is intended to support clinical trials conducting preliminary evaluation of the safety and efficacy of imaging agents, as well as an assessment of imaging systems, image processing, image-guided therapy, contrast kinetic modeling, 3-D reconstruction and other quantitative tools. As many such preliminary evaluations are early in development, this FOA will provide investigators with support for pilot (Phase I and II) cancer imaging clinical trials, including patient monitoring and laboratory studies. This FOA supports novel uses of known/standard clinical imaging agents and methods as well as the evaluation of new agents, systems, or methods. The imaging and image-guided intervention (IGI) investigations, if proven successful in these early clinical trials, can then be validated in larger studies through competitive R01 mechanisms, or through clinical trials in the Specialized Programs of Research Excellence (SPOREs), Cancer Centers and/or the NCI's National Clinical Trials Network. October 21, 2016

Guolan Lu successfully defended her PhD thesis and joined Stanford University

As an emerging optical modality, hyperspectral imaging (HSI) holds great promise for early cancer detection and image-guided surgery. The major advantage of HSI is that it is a noninvasive technology that doesn't require any contrast agent, and it combines wide-field imaging and spectroscopy to simultaneously attain both spatial and spectral information from an object in a non-contact way. Light delivered to the tissue surface undergoes multiple elastic scattering and absorption interactions, and part of it returns as diffuse reflectance carrying diagnostic information about the underlying tissue structure and composition. The biochemical and morphological properties of the tissue change during disease progression. Therefore hyperspectral images, which contain high-dimensional spectral information at each image point, can be analyzed for visualization, characterization, and quantification of the disease state in biological tissue.

The overall goal of this dissertation was to investigate the potential of label-free HSI technology combined with machine learning methods as a noninvasive diagnostic tool for quantitative detection and delineation of head and neck cancer. More specifically, this dissertation work has two applications: the early detection of cancer, and surgical guidance. To achieve this, we had four different aims. The first two aims evaluated the diagnostic performance of HSI and machine learning algorithms at differentiating cancer from normal tissue in preclinical animal models, including a subcutaneous cancer model (Aim 1), and a chemically-induced tongue carcinogenesis model (Aim 2). The last two aims investigated the detection and delineation of head and neck cancer in a surgical animal model (Aim 3) and fresh surgical specimens of human patients (Aim 4).

FDA approves Emory-developed prostate cancer imaging probe (FACBC/Axumin)

A cancer imaging agent that was originally developed at Emory University was approved on Friday, May 27 by the U.S. Food and Drug Administration. Axumin, a PET (positron emission tomography) imaging agent, is indicated for diagnosis of recurrent prostate cancer in men who have elevated blood levels of prostate specific antigen (PSA) after previous treatment. Axumin, now being commercialized by UK-based Blue Earth Diagnostics, is also known as 18F-fluciclovine or FACBC (an abbreviation for anti-1-amino-3-[18F]fluorocyclobutane-1- carboxylic acid). Imaging using axumin is expected to help doctors detect and localize recurrent prostate cancer, and could guide biopsy or the planning of additional treatment, says David Schuster, MD, director of the Division of Nuclear Medicine and Molecular Imaging and associate professor of radiology and imaging sciences at Emory University School of Medicine and Winship Cancer Institute. Fluciclovine was originally developed by Mark Goodman, PhD, professor of radiology and imaging sciences at Emory University School of Medicine and Winship Cancer Institute, and Emory Endowed Chair of Imaging Sciences, along with Timothy Shoup, PhD, now at Massachusetts General Hospital. Baowei Fei, PhD, EngD, is researching how to combine fluciclovine with ultrasound to guide prostate biopsy. Fei is associate professor of radiology and imaging sciences, a Georgia Research Alliance Distinguished Cancer Scientist, and part of the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory.

For more information about this news, please visit: http://news.emory.edu/stories/2016/06/fluciclovine_fda_approval/

For more information about the targeted biopsy study, please visit: https://www.clinicaltrials.gov/ct2/show/NCT02744534/

Guolan Lu Received the Outstanding Translational Research Award

This Outstanding Translational Research Award honors a graduate student who has demonstrated excellence in translational research as shown by publications in translation-focused journals, patents, clinical testing, achieving FDA clearance, etc. Guolan Lu received the 2016 Wallace B Coulter Department of Biomedical Engineering Annual Graduate Student Award – Outstanding Translational Research Award. Guolan is a Ph.D. candidate in the Quantitative BioImaging Laboratory and has performed her thesis research under the supervision of Prof. Baowei Fei in the Department of Radiology and Imaging at Emory University and in the Department of Biomedical Engineering at Emory University and Georgia Institute of Technology. Guolan’s research work on hyperspectral imaging demonstrated highly translational potential from animals to human patients for the applications in cancer detection and image-guided surgery. One of her papers on medical hyperspectral imaging has received national and international attentions, being cited more than 200 times in only two years and being the Top Download from Journal of Biomedical Optics. This prestigious award is to honor best and brightest among more than 150 Ph.D. students in the nationally top-ranked Coulter Department of Biomedical Engineering at Emory University and Georgia Institute of Technology. May 2, 2016

For more information about the Award, please visit:

http://www.gradadmiss.gatech.edu/hg/item/531711

Top Downloads from Journal of Biomedical Optics:

http://biomedicaloptics.spiedigitallibrary.org/journal.aspx

Lu G and Fei B, "Medical hyperspectral imaging: a review", Journal of Biomedical Optics. 19(1), 010901 (Jan 20, 2014)

http://biomedicaloptics.spiedigitallibrary.org/article.aspx?articleid=1816617

Ms. Guolan Lu, PhD Candidate at QBIL, won the Outstanding Translational Research Award at Georgia Tech

This Outstanding Translational Research Award honors a graduate student who has demonstrated excellence in translational research as demonstrated by publications in translation-focused journals, patents, clinical testing, achieving FDA clearance, etc. Guolan’s research work on hyperspectral imaging demonstrated highly translational potential from animals and human patients for cancer detection and image-guided surgery. This is a prestigious award among more than 150 PhD students in the top-ranked Coulter Department of Biomedical Engineering at Emory University and Georgia Institute of Technology. – April 2016

Lu G, Fei B, “Medical Hyperspectral Imaging: A Review”, Journal of Biomedical Optics, Jan. 2014, 10901 Full Text

Dr. Baowei Fei and Dr. Xulei Qin at QBIL were granted a U.S. patent on cardiac imaging

Systems, methods, and computer-readable storage media relate to segmenting an image series of at least one image of a region of interest of a subject. The methods, systems, and computer readable storage media can automatically segment interior and exterior boundaries relative to the region of interest (e.g., epicardial and endocardial boundaries with respect to a right ventricle) from an image series by combining sparse matrix transform, a training model, and a localized region based level set function. – April 2016

Fei B, Qin X, “Systems, methods and computer readable storage media storing instructions for automatically segmenting images of a region of interest”, United States Patent , No. 9,142,030 B2 Full Text

Dr. Baowei Fei will serve as Conference Chair for SPIE Medical Imaging

Dr. Fei will serve as the Conference Chair for the International Conference of SPIE Medical Imaging – Image-Guided Procedures, Robotics Interventions, and Modeling from 2017-2020. SPIE is an international society advancing an interdisciplinary approach to the science and application of light. Established in 1955, the not-for-profit society advances emerging technologies through interdisciplinary information exchange, continuing education, publications, patent precedent, and career and professional growth. The SPIE Medical Imaging Conference is the internationally recognized premier forum for reporting state-of-the-art research and development in medical imaging. The event focuses on the latest innovations found in underlying fundamental scientific principles, to technology developments, scientific evaluation, and clinical application. In 2017, the conference will offer a special track on Precision Medicine. The symposium covers the full range of medical imaging modalities including medical image acquisition, display, processing, analysis, perception, decision support, and informatics.

For more information about SPIE Medical Imaging Conference, please visit: http://spie.org/MI/conferencedetails/image-guided-procedures/

Dr. Fei serves as Conference Chair for the International Conference of SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling in 2017-2020.

SPIE is an international society advancing an interdisciplinary approach to the science and application of light. Established in 1955, the not-for-profit society advances emerging technologies through interdisciplinary information exchange, continuing education, publications, patent precedent, and career and professional growth. The SPIE Medical Imaging Conference is the internationally recognized premier forum for reporting state-of-the-art research and development in medical imaging. The event focuses on the latest innovations found in underlying fundamental scientific principles, to technology developments, scientific evaluation, and clinical application. In 2017, the conference will offer a special track on Precision Medicine. The symposium covers the full range of medical imaging modalities including medical image acquisition, display, processing, analysis, perception, decision support, and informatics.

For more information, please visit the conference website:
https://spie.org/MI/conferencedetails/image-guided-procedures/

Call-for-Papers

Dr. Zhiqiang Tian at QBIL won the Second Place for the MICCAI PROMISE12 Challenge

The MICCAI ‘Prostate MR Image Segmentation Challenge (PROMISE12) is to compare interactive and (semi)-automatic segmentation algorithms for MRI of the prostate. The results of the challenge were presented in conjunction with a live challenge, evaluating the algorithms on unseen data. Eighteen teams (research groups, companies, etc.) who are developing a segmentation algorithm registered and downloaded multi-center, multi-vendor training data from the PROMISE12 website to train their algorithms. Test data were also be supplied. The segmentation results of the algorithms on the test data were submitted through the website, including a short paper explaining the algorithm. The segmentations were automatically evaluated against the reference standard. The results of the algorithms were then ranked and shown in the results section of the website. Among the 18 research teams from the international community, the QBIL team from Emory University won the second place for this MICCAI PROMISE12 Challenge.– July 2015

For more information about the MICCAI PROMISE12 Challenge, please visit: http://promise12.grand-challenge.org/details