Head of Imaging & Technology
c/o Clinical Research Centre (CRC)
James Arrott Drive
Ninewells Hospital & Medical School
+(44) 01382 383431
Luc Bidaut moved to Dundee in July 2010 as Chair of Translational Imaging and Director of Imaging for the Centre of Oncology and Molecular Medicine. In March 2011, Luc Bidaut was named Head of the Imaging & Technology Core Group (ITCG), a virtual construct to regroup all related entities and activities under a common umbrella. In November 2011, major components of the ITCG were regrouped under a formal Division of Imaging & Technology (DIT; Luc Bidaut, Head; Andreas Melzer, co-Head) within the newly created Medical Research Institute.
From January 2005 until July 2010, Luc Bidaut was the founding Director of the Image Processing and Visualization Laboratory (IPVL) at the University of Texas' M. D. Anderson Cancer Center (MDACC) in Houston, TX-USA. Additionally, he was the Head of the Scientific Computing Resource (SCR) and an Associate Professor in the Department of Imaging Physics.
Before coming to M. D. Anderson, Prof. Bidaut was Associate Attending/Professor in the Departments of Radiology and Medical Physics as well as the founding Technical Director for Advanced Imaging at Memorial Sloan-Kettering Cancer Center (MSKCC) in New York, NY-USA. Prior to that he was project leader and founding Director of the Laboratory of Functional and Multidimensional Imaging (LFMI) in the Departments of Radiology and Surgery at the University Hospitals in Geneva-Switzerland. Previously, he was a co-founder and the Head of Instrumentation, Imaging and Data Processing for the PET and Biomedical Cyclotron center at the Free University's Erasme Hospital in Brussels-Belgium. For several years prior to that, he was R&D and Computer Scientist in the Division of Biophysics and Nuclear Medicine at the University of California in Los Angeles (UCLA), USA where he had moved after working on PET and SPECT R&D at the Service Hospitalier Frédéric Joliot (SHFJ) in Orsay-France
Throughout his career in Europe and the US, Prof. Bidaut's main interests have centered on designing, developing, implementing and exploiting new tools, approaches, infrastructures and entities for extracting, combining, visualizing and maximizing the utility of information that can be collected from various medical modalities and sensors such as PET, SPECT, CT, MR, EEG, etc. These concepts - that can be defined in a nutshell as "advanced quantitative imaging" - span the whole spectrum of micro to animal to humans and are eminently relevant to research as well as to translational and clinical applications.
Prof. Bidaut’s primary goals lie in the development, implementation and application of advanced quantitative imaging and visualization techniques. The related techniques and approaches apply to either or both clinical and research paradigms, whether for the diagnosis, assessment and characterization of disease, or to manage the many sides and ancillaries of therapy. Accordingly, Luc Bidaut's main objectives are to develop, implement and exploit sophisticated processing and imaging concepts beyond standard radiological review, and to provide a functional, image-based multidisciplinary gateway between research, translational and clinical applications.
Related efforts are principally directed towards furthering the understanding, application and exploitation of biomedical imaging in its broadest sense. Of primary importance is understanding what each imaging modality can bring to this compound concept, as well as determining the best way to extract and analyze all relevant information from the data at hand in order to present it accessibly to the end-users. The scope of this research includes the human, animal and even microscopic sides of biomedical imaging along with its clinical and research exploitation.
Central to this broad scope is the following non-exhaustive list of topics:
- Advanced biomedical imaging
- Multidimensional imaging and visualization
- Image segmentation
- Multimodality and hybrid imaging
- Image registration and fusion
- Image-guided therapy (e.g., protocols and devices)
- Interventional planning and monitoring (e.g., radiology, surgery, MI, RT)
- Quantitative/parametric imaging
- Functional and Molecular imaging (e.g., positron emission tomography and others)
- Modeling and simulation
- Therapy follow-up and response assessment
- Scientific visualization
- High-Performance Visualization and Computing
Corollary to these core interests is the multidisciplinary strategizing and collaborations that are associated with implementing and furthering such concepts through the mixing of disciplines that do not traditionally interact with each other, and by fostering and pulling together resources that require complementary support from diverse entities. Other than for the sheer necessity of bundling up various types of expertise and technology to address efficiently the corresponding challenges, the multidisciplinarity of QAI is further boosted and justified by the multiple applications of this complex field, also well outside the purely biomedical realm. Such a versatility makes this field particularly well suited to both inter- and intra-entities collaborations and also to the promotion of core models suitable to address the diverse needs of a diverse community.
As overarching theme of Prof. Bidaut’s clinical interests, advanced quantitative imaging (QAI) is a concept that naturally lends itself to most aspects of disease characterization and therapy management - from diagnosis and therapy planning to delivery and response assessment -, and this especially for complex diseases such as cancer. In turn, QAI contributes to the overall advancement of biomedical imaging as a valid and fundamental component of new biomarkers. Clinical areas and disciplines of interest are ones that can either exploit or contribute to - either directly or indirectly - advanced imaging approaches and paradigms. Such areas include imaging modalities and protocols as well as the diagnosis and characterization of disease. They also include therapy and interventional planning along with guidance and response assessment for routine or trial treatment. While medical disciplines like radiology, surgery, oncology and radiation therapy are obvious consumers of the products of such approaches, other disciplines - including engineering, basic sciences and even art - are also crucial to furthering these concepts and broadening the scope of their applications.
- Guerrero, T.; Sanders, K.; Castillo, E.; Zhang, Y.; Bidaut, L.; Pan, T.; Komaki, R. Dynamic ventilation imaging from four-dimensional computed tomography. Physics in Medicine and Biology, 2006; 51(4):777-791.
- Oden, J.T.; Diller, K.R.; Bajaj, C.; Browne, J.C.; Hazle, J.; Babuska, I.; Bass, J.; Bidaut, L.; Demkowicz, L.; Elliott, A.; Feng, Y.; Fuentes, D.; Prudhomme, S.; Rylander, M.N.; Stafford, R.J.; Zhang, Y. Dynamic data-driven finite element models for laser treatment of cancer. Numerical Methods and Partial Differential Equations, 2007; 23:904-922.
- Bligh, M.; Bidaut, L.; White, R.A.; Murphy, W.A.; Stevens, D.M.; Cody, D.D. Helical Multi-Detector Row Quantitative Computed Tomography (QCT) Precision. Academic Radiology, 2009; 16(2):150-159.
- Lu, J.; Steeg, P.S.; Price, J.E.; Krishnamurthy, S.; Mani, S.; Reuben, J.; Cristofanilli, M.; Dontu, G.; Bidaut, L.; Valero, V.; Hortobagyi, G.N.; Yu, D. Breast Cancer Metastasis: Challenges and Opportunities. Cancer Research, 2009; 69(12):4951-4953.
- Meyer, C.R.; Armato, S.G. III; Fenimore, C.P.; McLennan, G.; Bidaut, L.M.; Barboriak, D.P.; Gavrielides, M.A.; Jackson, E.F.; McNitt-Gray, M.F.; Kinahan, P.E.; Petrick, N.; Zhao, B. Quantitative Imaging to Assess Tumor Response to Therapy: Common Themes of Measurement, Truth Data & Error Sources. Translational Oncology, 2009; 2(4):198-210.
- Wang, J.*; Zhang, S.*; Rabinovich, B.**; Bidaut, L.**; Soghomonyan, S.; Alauddin, M.M.; Bankson, J.A.; Shpall, E.; Willerson, J.T.; Gelovani, J.G.; Yeh, E.T.H. Human CD34+ Cells in Experimental Myocardial Infarction. Long-term Survival, Sustained Functional Improvement, and Mechanism of Action. Circulation Research, 2010; 106(12):1904-1911 (both *1st and **3rd authors, resp.)
- Hanasono, M.M.; Jacob, R.F.; Bidaut, L.; Robb, G.L.; Skoracki, R.J. Mid-Facial Reconstruction Using Virtual Planning, Rapid Prototype Modeling, and Stereotactic Navigation. Plastic & Reconstructive Surgery, 2010; 126(6):2002-2006.
- Levin, V.A.; Bidaut, L.; Hou, P.; Kumar, A.J.; Wefel, J.S.; Bekele, B.N.; Prabhu, S.; Loghin, M.; Gilbert, M.R.; Jackson, E.F. Randomized double-blind placebo controlled trial of bevacizumab therapy for radiation necrosis of the CNS. Int J of Rad Onco Biol Phys (IJROBP/Red Journal), 2011; 79(5):1487-1495. (reviewed as "Must Read" by Faculty of 1000 - Medicine)
- Armato, S.G.; McLennan, G.; Bidaut, L.; McNitt-Gray, M.F.; Meyer, C.R.; Reeves, A.P.; Zhao, B.; Aberle, D.R.; Kazerooni, E.A.; MacMahon, H.; van Beek, E.J.R.; Yankelevitz, D.; Henschke, C.I.; Hoffman, E.A.; Bland, P.H.; Engelmann, R.M.; Laderach, G.E.; Max, D.; Pais, R.C.; Piker, C.W.; Qing, D.; Smith, A.; Starkey, A.; Towfic, Z.; Batra, P.; Caligiuri, P.; Jude, C.M.; Quint, L.E.; Sundaram, B.; Roberts, R.Y.; Croft, B.Y.; Clarke, L.P. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans. Medical Physics, 2011; 38(2):915-931.
- Schwartz, D.L.; Bankson, J.*; Bidaut, L.*; He, Y.; Williams, R.; Lemos, R.; Thitai-Kumar, A.; Oh, J.; Volgin, A.; Soghomonyan, S.; Yeh, H.-H.; Nishii, R.; Mukhopadhay, U.; Alauddin, M.; Mushkudiani, I.; Kuno, N.; Krishnan, S.; Bornman, W.; Lai, S.; Powis, G.; Hazle, J.; Gelovani, J. HIF-1 Dependent Stromal Adaptation to Ischemia Mediates In Vivo Tumor Radiation Resistance. Molecular Cancer Research, 2011; 9(3):259-270 (* both 2nd authors)