Hyperspectral Imaging and Multivariate Curve Resolution

Technology Summary

Researchers at Sandia have designed and constructed a hyperspectral confocal fluorescence microscope. Hyperspectral microscopes image hundreds of spectral wavelengths when obtaining spectral images. Included in the hyperspectral imaging system are software programs for controlling the microscope and its data collection, as well as spectral image viewing software for viewing both the raw image data and the spectral and image results from the multivariate curve resolution (MCR) analyses.

Description

The hyperspectral microscope allows for rapid detection of all emitting fluorescence species in an image and determines their relative concentrations throughout the image without any prior information. The microscope is combined with Sandia's unique and proprietary multivariate algorithms and software to form a complete system for the extraction of quantitative image information from the hyperspectral images at diffraction-limited spatial resolutions. Sandia's MCR software employs new algorithmic approaches to accomplish dramatically faster computation of the rigorous, constrained alternating least-squares MCR analysis.

This microscope system can reveal new fluorescent species that may not have been known to exist. It also allows an expansion of the structural stains and molecular fluorophores that biologists can introduce into biological samples simultaneously. This microscope and analysis system can accurately multiplex and recover the individual composition maps of each fluorophore, even if they are highly overlapped spectrally and/or spatially.

Youtube video: http://www.youtube.com/watch?v=X-aubh_OHzs

Benefits

  • Allows blind unmixing of the hyperspectral images to determine and quantify all of the independently varying fluorescence species in the image
  • Accurate detection and quantification of unexpected or unknown fluorescence species in imaged samples
  • Changes in the pure emission spectra can be used to indirectly monitor the local environment of the fluorescent molecules in biological sample
  • Hyperspectral imaging in a purely discovery mode for all those samples where the set of emission components is either not known or where the emission component spectra are dependent on the local environment of the sample
  • Relative concentration maps of each of the emission components in sample can be obtained without fear of spectral cross talk from overlapping spectral components

Applications and Industries

  • Imaging of any sample that can be placed under the microscope objective and that has fluorescence species that can be excited by the laser, including biological samples such as living plant, animal, and bacterial cells; thin animal and plant tissue samples; and biofilm on water purification membranes
  • Live monitoring of the synthesis of quantum dots in microfluidic platforms to better understand the kinetic reaction mechanisms and rate constants involve in their synthesis
  • Monitoring of cell viability or the metabolic state of the cell to obtain unprecedented image contrast
  • Gene expression microarrays for studying genetic markers for leukemia and treatment outcomes
  • Material durability diagnostics (e.g., aging characteristics and viability materials used in airplanes and nuclear reactors)

Additional Information

Publications

Michael B Sinclair, David M. Haaland, Jerilyn A. Timlin, and Howland D.T. Jones. (2006)."Hyperspectral Confocal Microscope." Applied Optics. 45(24), pp 6283-6291. [online]. Available: http://www.opticsinfobase.org/view_article.cfm?gotourl=http%3A%2F%2Fwww%2Eopticsinfobase%2Eorg%2FDirectPDFAccess%2FCF7746EC%2DAA88%2D18FA%2D8DD45DEA81003270%5F96177%2Epdf%3Fda%3D1%26id%3D96177%26seq%3D0%26mobile%3Dno&org=Sandia%20National%20Labs%20Albuquerque%20Technical%20Lib

Willem F. J. Vermaas, Jerilyn A. Timlin, Howland D. T. Jones, Michael B. Sinclair, Linda T. Nieman, Sawsan Hamad, David K. Melgaard, and David M. Haaland. (2008, March). "In vivo Hyperspectral Confocal Fluorescence Imaging to Determine Pigment Localization and Distribution in Cyanobacterial Cells." Proceedings of the National Academies of Sciences. 105 (10), pp 4050-4055. [online]. Available: http://www.pnas.org/content/105/10/4050.full.pdf+html

P. G. Kotula, M. R. Keenan, and J. R. Michael. (2003). "Automated Analysis of SEM X-Ray Spectral Images: A Powerful New Microanalysis Tool." Microsc. Microanal. 9, pp 1-17. [online]. Available: http://www.geology.wisc.edu/~johnf/g777/MM/Kotula-2003.pdf

Mark H. Van Benthem, Michael R. Keenan, and David M. Haaland. (2002). "Application of Equality Constraints on Variables during Alternating Least Squares Procedures." Journal of Chemometrics. 16, pp 613-622. [online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/cem.761/pdf

M. H. Van Benthem and M. R. Keenan. (2004). "Fast algorithm for the solution of large-scale non-negativity-constrained least squares problems." Journal of Chemometrics. 18, pp 441-450. [online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/cem.889/pdf

Additional Related Sandia References

David M. Haaland, Frederick W. Koehler IV, and Mark H. Van Benthem. (2002, January). "Reducing System Artifacts in Hyperspectral Image Data Analysis with the Use of Estimates of the Error Covariance in the Data." SAND2001-3638.

Michael R. Keenan, Jerilyn A. Timlin, Mark H. Van Benthem, and David M. Haaland, "Algorithms for Constrained Linear Unmixing with Application to the Hyperspectral Analysis of Fluorophore Mixtures." Imaging Spectrometry VIII. S. S. Shen, editor, Proceedings of SPIE, 4816, (SPIE, Bellingham, WA, 2002), pp 193-194.

M. Juanita Martinez, Anthony D. Aragon, Angelina Rodriguez, Jose Weber, Jerilyn A. Timlin, Michael B. Sinclair, David M. Haaland, and Margaret Werner-Washburne. (2003). "Identification and Removal of Contaminating Fluorescence from Commercial and In-house Printed DNA Microarrays." Nucleic Acids Research. (31, 4), e18. DOI: 10.1093/nar/gng018

David M. Haaland, Jerilyn A. Timlin, Michael B. Sinclair, Mark H. Van Benthem, M. Juanita Martinez, Anthony D. Aragon, and Margaret Werner-Washburne, "Multivariate Curve Resolution for Hyperspectral Image Analysis: Applications to Microarray Technology." Proceedings of SPIE, Vol. 4959, Spectral Imaging: Instrumentation, Applications, and Analysis II, edited by Richard M. Levenson, Gregory H. Bearman, Anita Mahadevan-Jansen (SPIE, Bellingham, WA, 2003), pp 55-66.

George S. Davidson, David M. Haaland, Shawn Martin, Jerilyn A. Timlin, Michael B. Sinclair, Mark H. Van Benthem, Michael R. Keenan, Edward V. Thomas, Kevin W. Boyack, Brian N. Wylie, Jim Cowie, Juanita Martinez, Anthony Aragon, Margaret Werner-Washburne, Monica Mosquera-Caro, and Cheryl Willman. (2003 December). "High Throughput Instruments, Methods, and Informatics for Systems Biology." SAND2003-4664.

H. K. Baca, J. H. Flemming, C. Ashley, T. Hartenberger, M. Manginell, D. R. Dunphy, S. M. Brozik, M. Werner-Washburne, P. Calvert, J. Cesarano III, G. P. Lopez, M. B. Sinclair, J. A. Timlin, and C. J. Brinker. (2003). "Biocompatible self-assembly of nano-materials for bio-MEMS and insect reconnaissance." SAND2003-4075.

Michael B. Sinclair, Jerilyn A. Timlin, David M. Haaland, and Margaret Werner-Washburne. (2004). "Design, Construction, Characterization, and Application of a Hyperspectral Microarray Scanner." Applied Optics. (43), pp 2079-2088.

M. R. Keenan and P. G. Kotula. (2004). "Accounting for Poisson noise in the multivariate analysis of ToF-SIMS spectrum images." Surf. Interface Anal. (36), pp 203-212.

M. R. Keenan and P. G. Kotula. (2004). "Optimal scaling of TOF-SIMS spectrum-images prior to multivariate statistical analysis." Appl. Surf. Sci. pp 231-232, pp 240-244.

J. A. Ohlhausen, M.R. Keenan, P.G. Kotula, and D.E. Peebles. (2004). "Multivariate statistical analysis of time-of-flight secondary ion mass spectrometry images using AXSIA." Appl. Surf. Sci. pp 231-232, 230-234.

V. S. Smentkowski, J. A. Ohlhausen, P.G. Kotula, and M. R. Keenan. (2004). "Multivariate statistical analysis of time-of-flight secondary ion mass spectrometry images--looking beyond the obvious." Appl. Surf. Sci. 231-232, 245-249.

Chris L. Stork, Michael R. Keenan, and David M. Haaland. (2004). "Multivariate Curve Resolution for the Analysis of Remotely Sensed Thermal Infrared Hyperspectral Images." Proceedings of SPIE, Imaging Spectrometry X, (5546), pp 271-284.

M. R. Keenan and P. G. Kotula. (2004). "Accounting for Poisson noise in the multivariate analysis of ToF-SIMS spectrum images." Surf. Interface Anal. (36), pp 203-212.

Jerilyn A. Timlin, David M. Haaland, Michael B. Sinclair, M.Juanita Martinez, and Margaret Werner-Washburne. (2005). "Hyperspectral Microarray Scanning: Impact on the Accuracy and Reliability of Genomic Data." BMC Genomics. 6:72. [online]. Available: http://www.biomedcentral.com/1471-2164/6/72.

J. F. Guzowski, J. A. Timlin, B. Roysam, B. L. McNaughton, P. F. Worley, and C. A. Barnes. (2005)."Mapping behaviorally relevant neural circuits with immediate-early gene expression." Current Opinion in Neurobiology. (15), 599-606.

V. S. Smentkowski, M. R. Keenan, J. A. Ohlhausen, and P. G. Kotula. (2005). "Multivariate Statistical Analysis of Concatenated Time-of-Flight Secondary Ion Mass Spectrometry Spectral Images. Complete Description of the Sample with One Analysis." Anal. Chemistry. (77), pp 1530-1536.

M. R. Keenan. (2005). "Maximum likelihood principal component analysis of time-of-flight secondary ion mass spectrometry spectral images." J. Vac. Sci. Technol. A. 23, 746-750.

V. S. Smentkowski, M. R. Keenan, J. A. T. Ohlhausen, P. G. Kotula. (2005). "Multivariate statistical analysis of concatenated time-of-flight secondary ion mass spectrometry spectral images. Complete description of the sample with one analysis." Analytical Chemistry. (77), 1530-1536.

Jerilyn A. Timlin, Linda T. Nieman, Howland D. T. Jones, David. M. Haaland, Michael B. Sinclair, John F. Guzowski. (2006, January). "Imaging Multiple Endogenous and Exogenous Fluorescent Species in Cells and Tissues." Progress in Biomedical Optics and Imaging - Proceedings of SPIE; 2006; v.6088, Conference: Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IV; San Jose, CA, United States.

J. A. Timlin in DNA Microarrays. (2006). Part B: Databases and Statistics. Eds., A. Kimmel and B. Oliver, p 411, Academic Press, New York.

R. M. Noek and J. A. Timlin. (2006)."Hyperspectral imaging of zebra fish microarrays." Sandia National Laboratories. SAND2006-6750P.

V. S. Smentkowski, H. M. Duong, R. Tamaki, M. R. Keenan, J. A. T. Ohlhausen, P. G. Kotula. (2006). "Using time-of-flight secondary ion mass spectrometry and multivariate statistical analysis to detect and image octabenzyl-polyhedral oligomeric silsesquioxane in polycarbonate." Applied Surface Science. (253), pp 1015-22.

P. G. Kotula, M. R. Keenan, J. R. Michael. (2006). "Tomographic spectral imaging with multivariate statistical analysis: comprehensive 3D microanalysis." Microscopy and Microanalysis. (12), pp 36-48.

David M. Haaland, Michael B. Sinclair, Howland D. T. Jones, Jerilyn A. Timlin, Linda T. Nieman, George D. Bachand, Darryl Y. Sasaki, George S. Davidson, and Mark H. Van Benthem. (2007, February). "3D Optical Sectioning with a New Hyperspectral Confocal Fluorescence Imaging System." SAND2007-0399.

D. S. Lidke, N. L. Andrews, J. R. Pfeiffer, H. D. T. Jones, M. B. Sinclair, David M. Haaland, Alan R. Burns, Bridget S. Wilson, J. M. Oliver and K. A. Lidke. (2007). "Exploring membrane protein dynamics by multicolor single quantum dot imaging using wide field, TIRF, and hyperspectral microscopy." Proceedings of SPIE, 6448: 6448Y1-8.

David M. Haaland, Howland D. T. Jones, Michael B. Sinclair, Bryan Carson, Catherine Branda, Jens F. Poschet, Roberto Rebeil, Bing Tian, Ping Liu, and Allan R. Brasier. (2007, October). "Hyperspectral confocal fluorescence imaging of cells." Next-Generation Spectroscopic Technologies." Christopher D. Brown, Mark A. Druy, John P. Coates, editors , Proceedings of SPIE, Vol. 6765, 676509.

V. S. Smentkowski, S. G. Ostromiski, E. Braunstein, M. R. Keenan, J. A. T. Ohlhausen, P. G. Kotula. (2007). "Multivariate statistical analysis of three-spatial-dimension TOF-SIMS raw data sets." Analytical Chemistry. (79), pp 7719-7726.

V. Sutherland, J. A. Timlin, L. T. Nieman, J. F. Guzowski, M. K. Chawla, B. Roysam, P. F. Worley, B. L. McNaughton, M. B. Sinclair, and C. A. Barnes. (2007). "Advanced imaging of multiple mRNAs in brain tissue using a custom hyperspectral imager and multivariate curve resolution." Journal of Neuroscience Methods. (160), pp 144-148.

M. R. Keenan; V. S. Smentkowski, J. A. T. Ohlhausen, P. G. Kotula. (2008). "Mitigating dead-time effects during multivariate analysis of ToF-SIMS spectral images." Surface and Interface Analysis. (40), pp 97-106.

J. A. Timlin, R. M. Noek, J. N. Kaiser, M. B. Sinclair, H. D. T. Jones, R. W. Davis, and T. W. Lane. (2008). "Accurate measurement of cellular autofluorescence is critical for imaging of host-pathogen interactions." Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VI, San Jose, CA.

Intellectual Property

Title
ID Number
Patent Number
Date
Fast combinatorial algorithm for the solution of linearly constrained least squares problems 7166.1 7,451,173 11/11/2008
Issued
Augmented classical least squares multivariate spectral analysis 6969.3 6,922,645 07/26/2005
Issued
Methods for spectral image analysis by exploiting spatial simplicity 7363.1 7,725,517 05/25/2010
Issued
Spectral compression algorithms for the analysis of very large multivariate images 7276.1 7,283,684 10/16/2007
Issued
Spatial compression algorithm for the analysis of very large multivariate images 7213.0 7,400,772 07/15/2008
Issued
Augmented classical least squares multivariate spectral analysis 6969.1 6,687,620 02/03/2004
Issued
Method for exploiting bias in factor analysis using constrained alternating least squares algorithms 7450.0 7,472,153 12/30/2008
Issued
Augmented classical least squares multivariate spectral analysis 6969.2 6,842,702 01/11/2005
Issued
Method to analyze remotely sensed spectral data 7796.1 7,491,944 02/17/2009
Issued
Apparatus and system for multivariate spectral analysis 6896.0 6,584,413 06/24/2003
Issued
Methods for spectral image analysis by exploiting spatial simplicity 7363.2 7,840,626 11/23/2010
Issued
Method of multivariate spectral analysis 6728.0 6,675,106 01/06/2004
Issued
Technology IDSD#6728Development StagePrototypeAvailabilityAvailablePublished11/14/2011Last Updated02/06/2013