• 

  Andrew Reader

  Andrew Reader

  • Title
    Professor
  • Affiliation
    King's College London - Biomedical Engineering Department
  • Phone
    +44 (0)20 7836-5454
  • Email
    Andrew.reader@mcgill.ca
  • Website
    https://kclpure.kcl.ac.uk/portal/andrew.reader.html

  • Reasearch Keywords
  • Biography
  • Research Program
  • Publications

  High-resolution PET Imaging; Image Processing and Reconstruction

  Dr. Reader carried out his doctoral research at the Institute of Cancer Research (University of London, UK) before taking up a lectureship in 1999 at the University of Manchester Institute of Science and Technology (UMIST). After a sabbatical in 2005 working at an INSERM unit in Paris and at Orsay, he was promoted to senior lecturer at the University of Manchester (UK). He was appointed as an associate professor at McGill University in 2008, based in the brain imaging centre (BIC) of the Montreal Neurological Institute (MNI) where he also continues to hold a Canada Research Chair in positron emission tomography (PET) imaging (renewed until 2018).

  Dr. Reader’s research concerns advancing the fields of 3D and 4D image reconstruction, system modeling, data correction and analysis for positron emission tomography (PET). Innovations in these areas can significantly improve image quality for functional and molecular imaging of the human body, improving image resolution and even halving the error levels in functional parameters compared to conventional data processing techniques.

  Recent publications:

  1. * Kotasidis, F.A., Matthews, J.C., Angelis, G.I., Noonan, P.J., Jackson, A., Price, P., Lionheart, W.R. and Reader AJ 2011 “Single scan parameterization of space-variant point spread functions in image space via a printed array: The impact for two PET/CT scanners” Phys. Med. Biol. 56: 2917-2942
  2. * Angelis GI, Reader AJ, Kotasidis FA, Lionheart WR and Matthews JC 2011 “Performance of monotonic and new non-monotonic gradient ascent reconstruction algorithms for high resolution neuroreceptor PET imaging” Phys. Med. Biol. 56:3895-3917
  3. * Markiewicz PJ, Angelis GI, Kotasidis F, Green M, Lionheart WR, Reader AJ, Matthews JC 2011 “A custom-built PET phantom design for quantitative imaging of printed distributions” Phys Med Biol. 56(21):N247-61
  4. * Wiebking, C, Duncan, N.W, Qin, P, Hayes, D.J, Lyttelton, O, Gravel, P, Verhaeghe, J, Kostikov, A.P, Schirrmacher, R, Reader AJ, Bajbouj, M.de, Northoff, G 2012 “External awareness and GABA-A multimodal imaging study combining fMRI and [ 18F]flumazenil-PET” IN PRESS Human Brain Mapping
  5. * Qin P, Duncan NW, Wiebking C, Gravel P, Lyttelton O, Hayes D, Verhaeghe J, Kostikov A, Schirrmacher R, Reader AJ, Northoff G 2012 “GABAA receptors in visual and auditory cortex and neural activity changes during basic visual stimulation” Issue DEC, 7 December 2012 Frontiers in Human Neuroscience
  6. * Gravel P, Verhaeghe J and Reader AJ 2013 “3D PET image reconstruction including both motion correction and registration directly into an MR or stereotaxic spatial atlas” Phys Med Biol. 58:105-126
  7. * Verhaeghe J and Reader AJ 2013 “Simultaneous water activation and glucose metabolic rate imaging with PET” Phys Med Biol. 58:393-411
  8. * Verhaeghe J and Reader AJ 2013 “Accelerated PET water activation acquisition with signal separation methodology” Med. Phys. 40(3): art no. 031909
  9. * Duncan NW, Gravel P, Wiebking C, Reader AJ, Lyttleton O, Northoff G 2013 “Grey matter density and GABAA binding potential show a positive linear relationship across cortical regions” Neuroscience 235:226-231
  10. * Hayes D, Duncan NW, Wiebking C, Pietruska K, Qin P, Lang S, Gagnon J, Gravel P, Verhaeghe J, Kostikov AP, Schirrmacher R, Reader AJ, Doyon J, Rainville P, Northoff G 2013 “GABAA receptors predict aversion-related brain responses: An fMRI-PET investigation in healthy humans” Neuropsychopharmacology 38(8):1438-1450
  11. * Fotros A, Casey KF, Larcher K, Verhaeghe J, Cox SML, Gravel P, Reader AJ, Dagher A, Benkelfat C and Leyton M 2013 “Cocaine Cue-Induced Dopamine Release in Amygdala and Hippocampus: A High-Resolution PET [18F]Fallypride Study in Cocaine Dependent Participants” Neuropsychopharmacology 38(9):1780-1788
  12. * Angelis GI, Reader AJ, Markiewicz PJ, Kotasidis FA, Lionheart WR and Matthews JC 2013 “Acceleration of image-based resolution modelling reconstruction using an expectation maximization nested algorithm” Phys. Med. Biol. 58:5061-5083
  13. * Schirrmacher R, Bernard-Gauthier V, Reader AJ, Soucy JP, Schirrmacher E, Wängler B and Wängler C 2013 “Design of brain imaging agents for positron emission tomography: Do large bioconjugates provide an opportunity for in vivo brain imaging?” Future Medicinal Chemistry 5 (14) , pp. 1621-1634.
  14. * Bieth M, Lombaert H, Reader AJ, Siddiqi K. 2013 “Atlas construction for dynamic (4D) PET using diffeomorphic transformations” Med Image Comput Comput Assist Interv. 16(Pt 2):35-42.
  15. * Kotasidis FA, Angelis GI, Anton-Rodriguez J, Matthews JC, Reader AJ, Zaidi H. 2014 Isotope specific resolution recovery image reconstruction in high resolution PET imaging. Med Phys. 41(5):052503. doi: 10.1118/1.487098.
• 

  Bruce Pike

  Bruce Pike

  • Title
    Professor
  • Affiliation
    University of Calgary, Departments of Radiology and Clinical Neurosciences
  • Phone
    403-220-4026
  • Email
    bruce.pike@ucalgary.ca
  • Website
    http://www.hbi.ucalgary.ca/members/pike

  • Reasearch Keywords
  • Biography
  • Research Program
  • Publications

  Neuroscience; Medical Imaging; Magnetic Resonance Imaging

  Dr. Pike obtained his undergraduate degree in electrical engineering from Memorial University and his M.Sc. and Ph.D. (Hons., 1990) at McGill University with his thesis research focused on stereotactic radiosurgery and magnetic resonance angiography respectively. He conducted postdoctoral studies in Radiological Sciences at Stanford University and joined the faculty of McGill in 1993. From 1999J2013 Dr. Pike was Director of the McConnell Brain Imaging Centre at the Montreal Neurological Institute and was the Killam Professor of Neurology & Neurosurgery and a James McGill Professor with appointments in Medical Physics and Biomedical Engineering. In September 2013 Dr. Pike joined the University of Calgary as the CAIP Chair in Healthy Brain Aging and Head of the Division of Image Science and Deputy Head (Research) in the Department of Radiology. He is also a Professor of Clinical Neurosciences and member of the Hotchkiss Brain Institute.

  Dr. Pike investigates magnetic resonance imaging (MRI) methods and applications for basic and clinical neuroscience research. His recent research has focused on quantitative MRI techniques for measuring tissue microstructure and physiology. He has used his methods to demonstrate focal pathology in multiple sclerosis patients that antedate the development of conventional MRI visible lesions by up to two years. He has also performed pioneering studies on the relationship between cerebral blood flow and oxygen metabolism in the cortex over a broad range of activation and inhibition conditions in healthy subjects and patients. Dr. Pike has published more than 200 scientific papers and book chapters, is an editor of the journal NeuroImage, chairs the CIHR MPI grants panel, and serves on the advisory board for numerous international programs.

  Recent publications:

  1. Xiao Y, Fonov V, Bériault S, Subaie FA, Chakravarty MM, Sadikot AF, Pike GB, Collins DL. Multi-contrast unbiased MRI atlas of a Parkinson’s disease population. Int J Comput Assist Radiol Surg. 2014 May 20. [Epub ahead of print].
  2. Bériault S, Sadikot AF, Alsubaie F, Drouin S, Collins DL, Pike G. Neuronavigation using susceptibility-weighted venography: application to deep brain stimulation and comparison with gadolinium contrast. J Neurosurg. 2014 May 16:1-11. [Epub ahead of print].
  3. Voss P, Pike BG, Zatorre RJ. Evidence for both compensatory plastic and disuse atrophy-related neuroanatomical changes in the blind. Brain. 2014 Apr;137(Pt 4):1224-40.
  4. Wong AP, Pipitone J, Park MT, Dickie EW, Leonard G, Perron M, Pike BG, Richer L, Veillette S, Chakravarty MM, Pausova Z, Paus T. Estimating volumes of the pituitary gland from T1-weighted magnetic-resonance images: Effects of age, puberty, testosterone, and estradiol. NeuroImage, 94, 216-21, Jul 2014.
  5. Alonso-Ortiz E, Levesque IR, Pike GB. MRI-based myelin water imaging: A technical review. Magn Reson Med. 2014 Mar 6. doi: 10.1002/mrm.25198. [Epub ahead of print].
  6. Stikov N, Boudreau M, Levesque IR, Tardif CL, Barral JK, Pike GB. On the accuracy of T1 mapping: Searching for common ground. Magn Reson Med. 2014 Feb 27. doi: 10.1002/mrm.25135. [Epub ahead of print].
  7. Thompson PM, et al., e ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav. 2014 Jun;8(2):153-82.
  8. Klepousniotou E, Gracco VL, Pike GB. Pathways to lexical ambiguity: fMRI evidence for bilateral fronto-parietal involvement in language processing. Brain Lang. 2014 Apr;131:56-64.
  9. Raux M, Tyvaert L, Ferreira M, Kindler F, Bardinet E, Karachi C, Morelot-Panzini C, Gotman J, Pike GB, Koski L, Similowski T. Functional magnetic resonance imaging suggests automatization of the cortical response to inspiratory threshold loading in humans. Respir Physiol Neurobiol. 2013 Dec 1;189(3):571-80.
  10. Campbell JS, Pike GB. Potential and limitations of diffusion MRI tractography for the study of language, Brain Lang. 2014 Apr;131:65-73.
  11. Marečková K, Chakravarty MM, Huang M, Lawrence C, Leonard G, Perron M, Pike BG, Richer L, Veillette S, Pausova Z, Paus T. Does skull shape mediate the relationship between objective features and subjective impressions about the face?. Neuroimage. 2013 Oct 1;79:234-40.
  12. Leppert I.R., Narayanan S., Araújo D., Giacomini P.S., Lapierre Y., Arnold D.L., and
      Pike G.B.. Interpreting Therapeutic Effect in Multiple Sclerosis via MRI Contrast Enhancing Lesions: Now You See Them, Now You Don’t. Journal of Neurology, JOON-D-13-01434R1, in press.
  13. †Klepousniotou E, Pike GB, Steinhauer K, Gracco V. Not all ambiguous words are created equal: An EEG investigation of homonymy and polysemy. Brain and Language, Oct;123(1):11-21. July 21, 2012.
  14. Rittner L., Campbell J.S.W., Freitas P.F., Appenzeller S., Pike G.B. and Lotufo R.A. Analysis of scalar maps for the segmentation of the corpus callosum in diffusion tensor fields. Journal of Mathematical Imaging and Vision. 2013: 45:214-226. Sept 2012 [Epub ahead of print]. DOI 10.1007/s10851-012-0377-4.
  15. Tardif CL, Bedell BJ, Eskildsen SF, Collins DL, Pike GB. Quantitative magnetic resonance imaging of cortical multiple sclerosis pathology. Mult Scler Int. 2012;2012:742018. doi: 10.1155/2012/742018. Epub 2012 Nov 18, 2013.
• 

  Issam EL Naqa

  Issam EL Naqa

  • Title
    Associate Professor
  • Affiliation
    University of Michigan - Radiation Oncology, Medical School
  • Phone
    734-936-4290
  • Email
    ielnaqa@umich.edu
  • Website

  • Reasearch Keywords
  • Biography
  • Research Program
  • Publications

  Biofinormatics; Multimodality Image-guided and Adaptive Radiotherapy; Radiobiological Modelling

  Issam El Naqa received his B.Sc. (1992) and M.Sc. (1995) in Electrical and Communication Engineering from the University of Jordan, Jordan and was awarded a first place young investigator award for his M.Sc. work. He worked as a software engineer at the Computer Engineering Bureau (CEB), Jordan, 1995G1996. He was awarded a DAAD scholarship to Germany, where he was a visiting scholar at the RWTH Aachen, 1996G 1998. He completed his Ph.D. (2002) in Electrical and Computer Engineering from Illinois Institute of Technology, Chicago, IL, USA, receiving highest academic distinction award for his PhD work. He completed an M.A. (2007) in Biology Science from Washington University in St. Louis, St. Louis, MO, USA, where he was pursuing a postGdoctoral fellowship in medical physics and was subsequently hired as a Instructor (2005G2007) and then an Assistant Professor (2007G2010) at the departments of radiation oncology and the division of biomedical and biological sciences and was an adjunct faculty at the department of Electrical engineering. He is currently an Associate Professor at McGill University Health Centre/Medical Physics Unit and associate member of at the departments of Physics, Biomedical Engineering, and Experimental medicine. He is certified Medical Physicist by the American Board of Radiology. He is a recognized expert in the fields of image processing, bioinformatics, computational radiobiology, and treatment outcomes modeling and has published extensively in these areas. He is an acting member of several academic and professional societies, which include IEEE, AAPM, ASTRO, ESTRO, and COMP and participates in their meetings and serves in their task groups. His research has been funded by several federal and private grants and serves as a peerGreviewer and associate editor for several leading international journals in his areas of expertise. He is currently a designated FRSQ and CIHR scholar.

  Our lab’s general research interests are in the areas of oncology bioinformatics, multimodality image analysis, and treatment outcome modeling. The primary motivation is to design and develop novel approaches to unravel cancer patients’ response to chemoradiotherapy treatment by integrating physical, biological, and imaging information into advanced mathematical models. These models could be used to personalize cancer patients’ chemoradiotherapy treatment based on predicted benefit/risk. Our group’s research interests involve three themes:

  Bioinformatics: design and develop datamining methods and software tools to identify robust biomarkers of treatment outcomes from clinical and preclinical data.

  Multimodality image-guided and adaptive radiotherapy: design and develop methods and algorithms for multimodality registration/segmentation, feature extraction, and real time     treatment planning optimization.

  Radiobiological modeling: design and develop predictive models of tumor and normal tissue response to radiotherapy by exploring physical and biological interactions using systemG based and machine learning approaches. Design and development of therapeutic interventions for protection of normal tissue toxicities

  Recent publications:

  1. I El Naqa, “Machine learning methods for predicting tumour response in lung cancer,” WIRES: Datamining and Knowledge Discovery, vol. 2, no. 2, pp 99 – 192, 2012
  2. Manushka Vaidya, Kimberly M. Creach, Jennifer Frye, Farrokh Dehdashti, Jeffrey D. Bradley, and Issam El Naqa, “Using FDG-PET/CT Image Characteristics for Predicting Radiotherapy Response in Lung Cancer,” Radiotherapy and Oncology, 2012 Feb;102(2):239-4
  3. Kimberly M. Creach, Issam El Naqa, Jeffrey D. Bradley, Jeffrey R. Olsen, Parag J. Parikh, Robert E. Dryzmala, Charles Bloch, Clifford G. Robinson, “Dosimetric predictors of chest wall pain after lung stereotactic body radiotherapy,” Radiotherapy and Oncology, 2012 Jul;104(1):23-7
  4. Habib Zaidi, Carolina Llina Fuentes, and Issam El Naqa, “Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma,” Eur J Nucl Med Mol Imaging, 2012 May;39(5):881-91
  5. Sangkyu Lee, Gabriela Stroian, Neil Kopek, Mahmood AlBahhar, Jan Seuntjens and Issam El Naqa, Analytical modeling of regional radiotherapy dose response of lung, Phys. Med. Biol. 57 3309–3321, 2012.
  6. Issam El Naqa, Piotr Pater, Jan Seuntjens, Monte Carlo Role in Radiobiological Modeling of Radiotherapy Outcomes, Phys. Med. Biol. 57 R75-R97, 2012.
  7. Beth Kidd, Issam El Naqa, Siegel BA, Dehdashti F, Grigsby PW, FDG-PET-based prognostic nomograms for locally advanced cervical cancer, Gyn Onc, 2012 Oct; 127 (1):136-40
  8. Matthew E. Johnson, Gisele C. Pereira, Issam M. El Naqa, S. Murty Goddu,
     Rawan Al-Lozi, Aditya Apte, David B. Mansur, “Determination of planning target volume for whole stomach irradiation using daily megavoltage CT images,” Practical Radiation Oncology 2(4), e85-e88, October 2012.
  9. B. White, T. Zhao , J. Lamb , S. Wuenschel , J. Bradley , I. El Naqa , D. Low, “Distribution of Lung Tissue Motion During Free Breathing,” Medical Physics, Med Phys. 2013 Apr;40(4).
     10. C. Robinson, T. DeWees, I. El Naqa, K. Creach, J. Olsen, T. Crabtree, B. Meyers*, V. Puri, P. Parikh, J. Bradley, “Patterns of Failure and Survival after Stereotactic Body Radiation Therapy or Lobar Resection for Clinical Stage I Non-small-cell Lung Cancer,” Journal of Thoracic Oncology (JTO), 2013 Feb;8(2):192-201
  10. Daniel Markel, Habib Zaidi, Issam El Naqa, “Novel Multimodality Segmentation using Level Sets and Jensen-Renyi Divergence,” Medical Physics, 40, 121908 (2013).
  11. El Naqa I., “The role of quantitative PET in predicting cancer treatment outcomes,” Special issue on Trends in PET Quantification, Clinical and Translational Imaging, 2014 (invited).
  12. El Naqa I., “”Biomedical informatics and pharmacogenomics,” WIRES: Data Mining and Knowledge Discovery, 2014 (invited).
  13. Ola M Maria, Ahmed M Maria, Norma Ybarra, PhD, Krishinima Jeyaseela, Sangkyu Lee, Jessica Perez, Shirley Lehnert, Sergio Faria, Monica Serban, Jan Seuntjens, Issam El Naqa, “Investigation of Stem-like Cells Role in Regional Radiosensitivity of the Lung,” Radiation Oncology, submitted.
  14. M. Hatt, J. Lee, C. Caldwell, I. El Naqa, C.R. Schmidtlein, E. De Bernardi, W. Lu, U. Nestle, D. Visvikis, T. Shepherd, S. Das, O. Mawlawi, V. Gregoire, H. Schöder, R. Jeraj, A. Pugachev, E. Spezi, M. MacManus, X. Geets, H. Zaidi, A.S. Kirov, “Report of AAPM TG211: Classification and evaluation strategies of auto-segmentation approaches for PET, Medical Physics, submitted.
• 

  Louis D. Collins

  Louis D. Collins

  • Title
    Professor & Lab Director
  • Affiliation
    McGill University, Montreal Neurological Institute & Hospital
  • Phone
    514-398-4227
  • Email
    louis.collins@mcgill.ca
  • Website
    http://www.bic.mni.mcgill.ca/

  • Reasearch Keywords
  • Biography
  • Research Program
  • Publications

  Neurology; Biomedical Engineering; Medical Image Analysis; Image-guided surgery

  Dr Collins is a professor in the departments of Neurology & Neurosurgery, and Biomedical Engineering at McGill University of Montreal, Canada, associate member of the Center for Intelligent Machines at McGill and associate member for the Center for studies on aging. I work at the McConnell Brain Imaging Centre of the Montreal Neurological Institute. I am head of the Image Processing Laboratory. He teaches BDME650, the Advanced Medical Imaging course in the Department of Biomedical Engineering

  Dr. Collins works on the use of computerized image processing techniques such as non-linear image registration and model-based segmentation to automatically identify structures within the human brain and to quantify anatomical variability. He investigates neuroscientific applications of three dimensional (3D) digital image processing methods for disease diagnosis, prognosis and image-guided surgery.

  These techniques are applied to large databases of magnetic resonance (MR) data from normal subjects to quantify normal anatomical variability in pediatric, young adult and elderly populations. The techniques have also been used to automatically quantify global and regional brain atrophy in MS patients and to look at morphological changes associated with diseases such as schizophrenia and Alzheimer’s dementia.

  In image-guided neurosurgery (IGNS), these techniques provide the surgeon with computerized tools to assist in interpreting anatomical, functional and vascular image data, permitting the effective planning and execution of minimally invasive neurosurgical procedures. Automated atlasing is essential in IGNS for thalamotomy and pallidotomy in the treatment of Parkinson’s disease, or temporal-lobe depth-electrode implantation in the diagnosis of epilepsy, since tissue targets in these procedures cannot be viewed directly on MR. Computerized atlasing minimizes trauma to the patient and allows resection of the smallest amount of brain tissue necessary for effective therapeutic treatment.

  Recent publications:

  1. C. Elliot, DL Collins, D. L. Arnold, T Arbel,”Temporally Consistent Probabilistic Segmentation of New Multiple Sclerosis Lesions in Brain MRI”, IEEE Transactions on medical imaging 2013 Apr 16. [Epub ahead of print].
  2. SF Eskildsen, P Coupé, D García-Lorenzo, V Fonov, JC Pruessner, DL Collins; Prediction of Alzheimer’s disease in subjects with mild cognitive impairment from the ADNI cohort using patterns of cortical thinning. Neuroimage. 2013 Jan 15;65:511-21.
  3. D. García-Lorenzo, S. Francis, S. Narayanan, D. L. Arnold and D. L. Collins. “Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging”, Medical Image analysis, 2013 Jan;17(1):1-18
  4. C. Haegelen, P. Coupé, V. Fonov, N. Guizard, P. Jannin, X. Morandi and D. L. Collins. “Efficiency of automated segmentation of basal ganglia and deep brain structures on MRI of patients with Parkinson’s disease”, International Journal of Computer Assisted Radiology and Surgery, 2013 Jan;8(1):99-110
  5. C. Haegelen, P. Perucca, C.-E. Châtillon, L. Andrade-Valença, R. Zelmann, J. Jacobs, D. L. Collins, F. Dubeau, A. Olivier and J. Gotman. “High-frequency oscillations, extent of surgical resection and surgical outcome in drug-resistant focal epilepsy”, Epilepsia 2013 May;54(5):848-57
  6. Sherif Karama, Mark E. Bastin, Catherine Murray, Natalie A. Royle, Lars Penke, Susana Muñoz Maniega, Alan J. Gow, Janie Corley, Maria del C. Valdés Hernandéz, John D. Lewis, Marc-Étienne Rousseau, Claude Lepage, Vladimir Fonov, D. Louis Collins, Tom Booth, Pierre Rioux, Tarek Sherif, Reza Adalat, John M Starr, Alan C Evans, Joanna M Wardlaw, Ian J Deary. “Childhood IQ explains associations between IQ and brain cortical thickness in old age”, Mol Psychiatry. 2013 Jun 4. doi: 10.1038/mp.2013.64
  7. M. Kersten-Oertel, P. Jannin, D.L. Collins, “The State of the Art in Mixed Reality Visualization in Image-Guided Surgery”, IEEE Transactions on Visualization and Computer Graphics. 2013 Mar;37(2):98-112
  8. Kim, S. H., V. S. Fonov, C. Dietrich, C. Vachet, H. C. Hazlett, R. G. Smith, M. M. Graves, J. Piven, J. H. Gilmore, S. R. Dager, R. C. McKinstry, S. Paterson, A. C. Evans, D. L. Collins, G. Gerig, M. A. Styner and I. network (2013). “Adaptive prior probability and spatial temporal intensity change estimation for segmentation of the one-year-old human brain.” J Neurosci Methods 212(1): 43-55
  9. P.A. MacDonald, H. Ganjavi, D.L. Collins, S. Karama, A.C. Evans, The Brain Development Cooperative Group, “Investigating the relation between striatal volume and IQ”. Brain Imaging Behav. 2013 Jun 30.
  10. L. Mercier, D Araujo, C Haegelen, RF Del Maestro, K Petrecca, DL Collins, “Registering pre- and post-resection 3D ultrasound for improved residual brain tumor localization”, Ultrasound in Medicine and Biology, 2013 Jan;39(1):16-29.
  11. Xiao Y, Fonov V, Bériault S, Subaie FA, Chakravarty MM, Sadikot AF, Pike GB, Collins DL. Multi-contrast unbiased MRI atlas of a Parkinson’s disease population. Int J Comput Assist Radiol Surg. 2014 May 20. [Epub ahead of print].
  12. Bériault S, Sadikot AF, Alsubaie F, Drouin S, Collins DL, Pike G. Neuronavigation using susceptibility-weighted venography: application to deep brain stimulation and comparison with gadolinium contrast. J Neurosurg. 2014 May 16:1-11. [Epub ahead of print].
  13. Weier K, Fonov V, Lavoie K, Doyon J, Collins DL. Rapid automatic segmentation of the human cerebellum and its lobules (RASCAL)-Implementation and application of the patch-based label-fusion technique with a template library to segment the human cerebellum. Hum Brain Mapp. 2014 Apr 28. doi: 10.1002/hbm.22529. [Epub ahead of print]
  14. Xiao Y, Jannin P, D’Albis T, Guizard N, Haegelen C, Lalys F, Vérin M, Collins DL. Investigation of morphometric variability of subthalamic nucleus, red nucleus, and substantia nigra in advanced Parkinson’s disease patients using automatic segmentation and PCA-based analysis. Hum Brain Mapp. 2014 Feb 19. doi: 10.1002/hbm.22478. [Epub ahead of print].
  15. Rivaz H, Karimaghaloo Z, Fonov VS, Collins DL. Nonrigid registration of ultrasound and MRI using contextual conditioned mutual information. IEEE Trans Med Imaging. 2014 Mar;33(3):708-25.
• 

  Luc Beaulieu

  Luc Beaulieu

  • Title
    Professor & Director
  • Affiliation
    Department of Physics, Engineering Physics and at Université Laval
  • Phone
    418-656-2131 poste 3814
  • Email
    luc.beaulieu@phy.ulaval.ca
  • Website
    http://physmed.fsg.ulaval.ca/

  • Reasearch Keywords
  • Biography
  • Research Program
  • Publications

  Scintillation Fiber Dosimetry; Radiotherapy Physics; Brachytherapy Physics; Dose Calculations

  Luc Beaulieu received his PhD from Université Laval in 1996. After a postdoctoral fellowship in Berkeley, California, he worked as a research scientist at the Indiana University Cyclotron Facility in Bloomington. In 2000, he took the leadership of the medical physics research group at Quebec City University Hospital. Under his leadership, a formal graduate medical physics teaching curriculum was setGup and became CAMPEP accredited in 2011. Dr. Beaulieu is a full professor (tenured) at Université Laval and Director of the CAMPEP graduate program. He is a member of the AAPM Brachytherapy Subcommittee, of TGG192, was the Chair of TGG186 (published in 2012) and now leads the AAPM/ESTRO/ABG Working Group on ModelGBased Dose Calculations in brachytherapy. As of 2014, he has mentored more than 65 graduate students and postdoctoral fellows, published 169 peerGreviewed manuscripts and over 330 abstracts at national and international meetings. He is a recognized expert in scintillation dosimetry and brachytherapy.

  The ongoing objective of Prof. Beaulieu’s research program is to increase the accuracy of dose measurements and dose calculations for any radiation based procedures including, but not limited to, radiation therapy, diagnostic and interventional radiology. This is achieved through a comprehensive research program combining elements of basic and applied research in medical physics and biomedical engineering. The program hinges on radiation physics, optics, numerical optimization problems, image and signal processing and highGperformance computing. The program is subGdivided along four main research tracks, namely 1) development of new radiation dosimeters, 2) applied medical image processing, 3) numerical computation in optimization problems and high precision particle transport and dose calculations, and 4) a developing trac.

  Recent publications:

  1. White SA, Landry G, Fonseca GP, Holt R, Rusch T, Beaulieu L, Verhaegen F, Reniers B., Comparison of TG-43 and TG-186 in breast irradiation using a low energy electronic brachytherapy source. Med Phys. 2014 Jun;41(6):061701.
  2. Afsharpour H, Walsh S, Collins Fekete CA, Vigneault E, Verhaegen F, Beaulieu L., On the sensitivity of α/β prediction to dose calculation methodology in prostate brachytherapy. Int J Radiat Oncol Biol Phys. 2014 Feb 1;88(2):345-50.
  3. Poulin E, Fekete CA, Létourneau M, Fenster A, Pouliot J, Beaulieu L. Adaptation of the CVT algorithm for catheter optimization in high dose rate brachytherapy. Med Phys. 2013 Nov;40(11):111724. doi: 10.1118/1.4826335.
  4. Lecavalier ME, Goulet M, Allen CN, Beaulieu L, Larivière D., Water-dispersable colloidal quantum dots for the detection of ionizing radiation. Chem Commun (Camb). 2013 Dec 25;49(99):11629-31.
  5. Desbiens M, D’Amours M, Afsharpour H, Verhaegen F, Lavallée MC, Thibault I, Vigneault É, Beaulieu L., Monte Carlo dosimetry of high dose rate gynecologic interstitial brachytherapy. Radiother Oncol. 2013 Dec;109(3):425-9.
  6. Goulet M, Archambault L, Beaulieu L, Gingras L., 3D tomodosimetry using long scintillating fibers: a feasibility study. Med Phys. 2013 Oct;40(10):101703.
  7. Mashouf S, Lechtman E, Beaulieu L, Verhaegen F, Keller BM, Ravi A, Pignol JP., A simplified analytical dose calculation algorithm accounting for tissue heterogeneity for low-energy brachytherapy sources. Phys Med Biol. 2013 Sep 21;58(18):6299-315.
  8. Guillot M, Gingras L, Archambault L, Beddar S, Beaulieu L.Performance assessment of a 2D array of plastic scintillation detectors for IMRT quality assurance. Phys Med Biol. 2013 Jul 7;58(13):4439-54.
  9. Therriault-Proulx F, Beddar S, Beaulieu L., On the use of a single-fiber multipoint plastic scintillation detector for 192Ir high-dose-rate brachytherapy. Med Phys. 2013 Jun;40(6):062101.
  10. Therriault-Proulx F, Beaulieu L, Archambault L, Beddar S., On the nature of the light produced within PMMA optical light guides in scintillation fiber-optic dosimetry. Phys Med Biol. 2013 Apr 7;58(7):2073-84.
  11. Morin J, Beliveau-Nadeau D, Chung E, Seuntjens J, Theriault D, Archambault L, Beddar S, Beaulieu L., A comparative study of small field total scatter factors and dose profiles using plastic scintillation detectors and other stereotactic dosimeters: the case of the CyberKnife. Med Phys. 2013 Jan;40(1):011719.
  12. Klein D, Briere TM, Kudchadker R, Archambault L, Beaulieu L, Lee A, Beddar S. In-phantom dose verification of prostate IMRT and VMAT deliveries using plastic scintillation detectors. Radiat Meas. 2012 Oct 1;47(10):921-929.
  13. Therriault-Proulx F, Archambault L, Beaulieu L, Beddar S. Development of a novel multi-point plastic scintillation detector with a single optical transmission line for radiation dose measurement. Phys Med Biol. 2012 Nov 7;57(21):7147-59.
  14. Archambault L, Therriault-Proulx F, Beddar S, Beaulieu L. A mathematical formalism for hyperspectral, multipoint plastic scintillation detectors. Phys Med Biol. 2012 Nov 7;57(21):7133-45.
  15. Beaulieu L, Carlsson Tedgren A, Carrier JF, Davis SD, Mourtada F, Rivard MJ, Thomson RM, Verhaegen F, Wareing TA, Williamson JF. Report of the Task Group 186 on model-based dose calculation methods in brachytherapy beyond the TG-43 formalism: current status and recommendations for clinical implementation. Med Phys. 2012 Oct;39(10):6208-36.
• 

  Philippe Després

  Philippe Després

  • Title
    Assistant Professor
  • Affiliation
    Department of Physics, Engineering Physics and Optics at Université Laval
  • Phone
    418-656-2131 poste 2511
  • Email
    philippe.despres@phy.ulaval.ca
  • Website
    http://www.physmed.fsg.ulaval.ca

  • Reasearch Keywords
  • Biography
  • Research Program
  • Publications

  Image Processing; X-ray; CT; PET; SPECT; GPU Processing

  Philippe Després is an Assistant Professor in the Department of Physics, Engineering Physics and Optics at Université Laval and a Medical Physicist at CHU de Québec. He was trained at Université Laval (MSc 2000, Physics), Université de Montréal (PhD 2005, Physics) and University of California, San Francisco (postdoc 2005G2007, Biomedical Engineering, Molecular Imaging).   He has been involved in numerous projects encompassing hardware and software aspects of medical imaging modalities such as XGray, CT, PET and SPECT. He has worked on lowGdose XGray imaging (scanningGslit xenon microstrip detector), advanced imaging techniques (multiG energy XGray imaging), and solidGstate detectors for molecular imaging (PSAPD and CZTGbased PET and SPECT). He also has developed highGperformance computing approaches with commodity graphics hardware (GPUs) that have led to innovative applications in image processing/reconstruction and radiation dose calculation, including a fast GPUGbased Monte Carlo engine to simulate energy transport in matter. He holds grants from NSERC, CIHR, FRQGS and has established research collaborations with numerous industrial and academic partners both locally and abroad.

  The research program pursued by Prof. Després is geared towards the use of highGperformance computing to tackle problems in Medical Physics. Specifically, physicsGrich models are used to reach better, more accurate solutions in a variety of clinical situations. These physicsGrich models however are numerically challenging and usually require large computing resources. As these problems are often intrinsically parallel, they can be implemented on Graphics Processing Units (GPUs) and benefit from their massively parallel architecture (hundreds of cores per processor). Therefore, the numerical burden of realistic modeling is alleviated by the use of GPUs; acceleration factors of 10 to 1000x have been achieved with this technology compared to traditional CPU implementations. This level of performance lets envision the clinical deployment of better solutions in radiation dose calculation and tomographic image reconstructionG. In the first case, a fast GPUG based Monte Carlo engine was developed to simulate the transport of energy in matter. This allows for more accurate dose calculations in external beam radiation therapy, brachytherapy, radiology and nuclear medicine while maintaining calculation times that are compatible with a clinical workflow. In tomographic image reconstruction, GPUG accelera ed iterative algorithms integrating physicsGbased priors have been developed to achieve fewGviews, lowGdose or artefact suppressing solutions.
  In PET and SPECT molecular imaging, efforts are invested in the development of a quantitative imaging platform. An automatic blood activity counter is being developed to monitor the amount of radiotracer available for uptake as a function of time in order to feed pharmacokinetic models and extract valuable physiological information from imaging studies.

  Recent publications:

  1. Lucas-Hourani M, Munier-Lehmann H, Helynck O, Komarova A, Desprès P, Tangy F, Vidalain PO. High-throughput Screening for Broad-spectrum Chemical Inhibitors of RNA Viruses. J Vis Exp. 2014 May 5;(87).
  2. Tangy F, Desprès P., Yellow fever vaccine attenuation revealed: loss of diversity. J Infect Dis. 2014 Feb 1;209(3):318-20.
  3. La Ruche G, Dejour-Salamanca D, Bernillon P, Leparc-Goffart I, Ledrans M, Armengaud A, Debruyne M, Denoyel GA, Brichler S, Ninove L, Desprès P, Gastellu-Etchegorry M., Capture-recapture method for estimating annual incidence of imported dengue, France, 2007-2010. Emerg Infect Dis. 2013 Nov;19(11):1740-8.
  4. Lernout T, Cardinale E, Jego M, Desprès P, Collet L, Zumbo B, Tillard E, Girard S, Filleul L., Rift valley fever in humans and animals in Mayotte, an endemic situation? PLoS One. 2013 Sep 30;8(9):e74192. doi: 10.1371/journal.pone.0074192.
  5. Lucas-Hourani M, Dauzonne D, Jorda P, Cousin G, Lupan A, Helynck O, Caignard G, Janvier G, André-Leroux G, Khiar S, Escriou N, Desprès P, Jacob Y, Munier-Lehmann H, Tangy F, Vidalain PO., Inhibition of pyrimidine biosynthesis pathway suppresses viral growth through innate immunity. PLoS Pathog. 2013;9(10):e1003678. doi: 10.1371/journal.ppat.1003678. Epub 2013 Oct 3.
  6. Gandini M, Gras C, Azeredo EL, Pinto LM, Smith N, Despres P, da Cunha RV, de Souza LJ, Kubelka CF, Herbeuval JP., Dengue virus activates membrane TRAIL relocalization and IFN-α production by human plasmacytoid dendritic cells in vitro and in vivo. PLoS Negl Trop Dis. 2013 Jun 6;7(6):e2257. doi: 10.1371/journal.pntd.0002257. Print 2013.
  7. Larrieu S, Cardinale E, Ocquidant P, Roger M, Lepec R, Delatte H, Camuset G, Desprès P, Brottet E, Charlin C, Michault A., A fatal neuroinvasive West Nile virus infection in a traveler returning from Madagascar: clinical, epidemiological and veterinary investigations. Am J Trop Med Hyg. 2013 Aug;89(2):211-3.
  8. Brandler S, Ruffié C, Combredet C, Brault JB, Najburg V, Prevost MC, Habel A, Tauber E, Desprès P, Tangy F., A recombinant measles vaccine expressing chikungunya virus-like particles is strongly immunogenic and protects mice from lethal challenge with chikungunya virus. Vaccine. 2013 Aug 12;31(36):3718-25.
  9. Bahuon C, Desprès P, Pardigon N, Panthier JJ, Cordonnier N, Lowenski S, Richardson J, Zientara S, Lecollinet S., IS-98-ST1 West Nile virus derived from an infectious cDNA clone retains neuroinvasiveness and neurovirulence properties of the original virus. PLoS One. 2012;7(10):e47666. doi: 10.1371/journal.pone.0047666. Epub 2012 Oct 23.
  10. Lucas-Hourani M, Lupan A, Desprès P, Thoret S, Pamlard O, Dubois J, Guillou C, Tangy F, Vidalain PO, Munier-Lehmann H., A phenotypic assay to identify Chikungunya virus inhibitors targeting the nonstructural protein nsP2. J Biomol Screen. 2013 Feb;18(2):172-9.
  11. Nassiri MA, Hissoiny S, Carrier JF, Després P., Fast GPU-based computation of the sensitivity matrix for a PET list-mode OSEM algorithm. Phys Med Biol. 2012 Oct 7;57(19):6279-93.
  12. Lessard F, Archambault L, Plamondon M, Despres P, Therriault-Proulx F, Beddar S, Beaulieu L., Validating plastic scintillation detectors for photon dosimetry in the radiologic energy range. Med Phys. 2012 Sep;39(9):5308-16.
  13. Henrik Gad H, Paulous S, Belarbi E, Diancourt L, Drosten C, Kümmerer BM, Plate AE, Caro V, Desprès P., The E2-E166K substitution restores Chikungunya virus growth in OAS3 expressing cells by acting on viral entry. Virology. 2012 Dec 5;434(1):27-37.
  14. Hissoiny S, D’Amours M, Ozell B, Despres P, Beaulieu L., Sub-second high dose rate brachytherapy Monte Carlo dose calculations with bGPUMCD. Med Phys. 2012 Jul;39(7):4559-67.
  15. Seuntjens J, Beaulieu L, El Naqa I, Després P. Special section: Selected papers from the Fourth International Workshop on Recent Advances in Monte Carlo Techniques for Radiation Therapy. Phys Med Biol. 2012 Jun 7;57(11). doi: 10.1088/0031-9155/57/11/E01.

SCIENTISTS

• 

  Andrew Reader

  High-resolution PET Imaging; Image Processing and Reconstruction
• 

  Bruce Pike

  Neuroscience; Medical Imaging; Magnetic Resonance Imaging
• 

  Issam EL Naqa

  Bioinformatics; Multimodality Image-guided and Adaptive Radiotherapy; Radiobiological Modelling
• 

  Louis D. Collins

  Neurology; Biomedical Engineering; Medical Image Analysis; Image-guided surgery
• 

  Luc Beaulieu

  Scintillation Fiber Dosimetry; Radiotherapy Physics; Brachytherapy Physics; Dose Calculations
• 

  Philippe Després

  Image Processing; X-ray; CT; PET; SPECT; GPU Processing