Anatomical Imaging and Post-Genomic Biology

  • Benedikt Hallgrímsson
  • Nicholas Jones


Anatomical imaging provides the morphological context for post-genomic biology. Volumetric imaging is central to the creation of atlases of gene expression as well as the visualization of increasingly complex molecular information in a spa-tiotemporal context. To become integrated into the types of hypotheses that systems biology and other post-genomic approaches generate, however, anatomical imaging must evolve further. Modes of phenotypic analyses must begin to generate databases and data repositories that will support data-mining approaches to increasingly complex and broad biological questions. For this to happen there must be increasing emphasis on high-throughput phenotypic analysis, data standardization, data sharing, and the systematic quantification of phenotypic variation. The solutions to these issues will lay the foundations for a new field of study, that of phenogenomics.


Phenotypic Analysis Microcomputed Tomography Compute Microtomography Volumetric Dataset Optical Projection Tomography 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bentley MD, Ortiz MC, Ritman EL, Romero JC (2002) The use of microcomputed tomography to study microvasculature in small rodents. Am J Physiol Regul Integr Comp Physiol 28 2:R1267– R1279Google Scholar
  2. Boeckmann B, Blatter MC, Famiglietti L et al. (2005) Protein variety and functional diversity: Swiss-Prot annotation in its biological context. C R Biol 328:882–899PubMedCrossRefGoogle Scholar
  3. Bogue M (2003) Mouse phenome project: understanding human biology through mouse genetics and genomics. J Appl Physiol 95:1335–1337PubMedGoogle Scholar
  4. Chen XJ, Kovacevic N, Lobaugh NJ, Sled JG, Henkelman RM, Henderson JT (2006) Neu-roanatomical differences between mouse strains as shown by high-resolution 3D MRI. Neuroimage 29:99–105PubMedCrossRefGoogle Scholar
  5. Cooper DM, Turinsky AL, Sensen CW, Hallgrimsson B (2003) Quantitative 3D analysis of the canal network in cortical bone by micro-computed tomography. Anat Rec B New Anat 274:169–179PubMedCrossRefGoogle Scholar
  6. Cooper DML, Matyas JR, Katzenberg MA, Hallgrimsson B (2004) Comparison of microcomputed tomographic and microradiographic measurements of cortical bone porosity. Calcified Tissue Int 74(5):437–447CrossRefGoogle Scholar
  7. Cooper DML, Thomas CDL, Clement JG, Hallgrimsson B (2006) Three-dimensional micro-computed tomography imaging of basic multicellular unit-related resorption spaces in human cortical bone. Anatomical Record Part a-Discoveries Mol Cell Evol Biol 288A:806–816CrossRefGoogle Scholar
  8. Dorr AE, Lerch JP, Spring S, Kabani N, Henkelman RM (2008) High resolution three-dimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6J mice. Neuroimage 42(1):60–69PubMedCrossRefGoogle Scholar
  9. Grubb SC, Churchill GA, Bogue MA (2004) A collaborative database of inbred mouse strain characteristics. Bioinformatics 20:2857–2859PubMedCrossRefGoogle Scholar
  10. Hallgrímsson B, Dorval CJ, Zelditch ML, German RZ (2004a) Craniofacial variability and morphological integration in mice susceptible to cleft lip and palate. J Anat 205:501–517CrossRefGoogle Scholar
  11. Hallgrímsson B, Willmore K, Dorval C, Cooper DM (2004b) Craniofacial variability and modularity in macaques and mice. J Exp Zoolog B Mol Dev Evol 302:207–225Google Scholar
  12. Henkelman RM, Chen XJ, Sled JG (2005) Disease phenotyping: structural and functional readouts. Prog Drug Res 62:151–184PubMedCrossRefGoogle Scholar
  13. Hildebrand T, Rüegsegger P (1997a) A new method for the model-independent assessment of thickness in three-dimensional images. J Microsc 185:67–75CrossRefGoogle Scholar
  14. Hildebrand T, Rüegsegger P (1997b) Quantification of bone microarchitecture with the structure model index. Comput Methods Biomech Biomed Eng 1:15–23CrossRefGoogle Scholar
  15. Hildebrand T, Laib A, Muller R, Dequeker J, Rüegsegger P (1999) Direct three-dimensional mor-phometric analysis of human cancellous bone: microstructural data from spine, femur, iliac crest, and calcaneus. J Bone Miner Res 14:1167–1174PubMedCrossRefGoogle Scholar
  16. Kristensen E, Parsons TE, Gire J, Hallgrimsson B, Boyd S (2008) A novel high-throughput morphological method for phenotypic analysis. IEE Comput Graphics Appl. doi:10.1109/TBME.2008.923106Google Scholar
  17. Lander ES, Linton LM, Birren B et al. (2001) Initial sequencing and analysis of the human genome. Nature 409:860–921PubMedCrossRefGoogle Scholar
  18. Lieberman D, Hallgrimsson B, Liu W, Parsons TE, Jamniczky HA (2008) Spatial packing, cranial base angulation, and craniofacial shape variation in the mammalian skull: testing a new model using mice. J Anat 23:12Google Scholar
  19. McDougal JJ, Andruski B, Schuelert N, Hallgrimsson B JRM (2008) Unravelling the relationship between age, pain sensation, and joint destruction in naturally occurring osteoarthritis of Dunkin—guinea pigsGoogle Scholar
  20. Muller R, Hildebrand T, Ruegsegger P (1994) Non-invasive bone biopsy: a new method to analyse and display the three-dimensional structure of trabecular bone. Phys Med Biol 39:145–164PubMedCrossRefGoogle Scholar
  21. Nieman BJ, Flenniken AM, Adamson SL, Henkelman RM, Sled JG (2006) Anatomical phenotyp-ing in the brain and skull of a mutant mouse by magnetic resonance imaging and computed tomography. Physiol Genomics 24:154–162PubMedGoogle Scholar
  22. Olafsdottir H, Darvann TA, Hermann NV et al. (2007) Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the Crouzon mutation Fgfr2(C342Y). J Anat 211:37–52PubMedCrossRefGoogle Scholar
  23. Paigen K, Eppig JT (2000) A mouse phenome project. Mamm Genome 11:715–717PubMedCrossRefGoogle Scholar
  24. Peltonen L, McKusick VA (2001) Genomics and medicine. Dissecting human disease in the postgenomic era. Science 291:1224–1229PubMedCrossRefGoogle Scholar
  25. Ulrich D, Hildebrand T, Van Rietbergen B, Muller R, Ruegsegger P (1997) The quality of trabecu-lar bone evaluated with micro-computed tomography, FEA and mechanical testing. Stud Health Technol Inform 40:97–112PubMedGoogle Scholar
  26. Venter JC, Adams MD, Myers EW et al. (2001) The sequence of the human genome. Science 291:1304–1351PubMedCrossRefGoogle Scholar
  27. Wan SY, Ritman EL, Higgins WE (2002) Multi-generational analysis and visualization of the vascular tree in 3D micro-CT images. Comput Biol Med 32:55–71PubMedCrossRefGoogle Scholar
  28. Wang Y, Xiao R, Yang F et al. (2005) Abnormalities in cartilage and bone development in the Apert syndrome FGFR2(+/S252W) mouse. Development 132:3537–3548PubMedCrossRefGoogle Scholar
  29. Waterston RH, Lindblad-Toh K, Birney E et al. (2002) Initial sequencing and comparative analysis of the mouse genome. Nature 420:520–562PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Benedikt Hallgrímsson
    • 1
  • Nicholas Jones
    • 1
  1. 1.Department of Cell Biology and Anatomy and the McCaig Bone and Joint InstituteUniversity of Calgary, Faculty of MedicineCalgaryCanada

Personalised recommendations