1. February 19 th – 22 nd Technologies to Enable Personalized Medicine San Antonio, TX Point Spread Function, Spectral Calibration and beyond: Quality Assurance Testing / Phase Two Light Microscopy Research Group Robert F. Stack / Richard W. Cole Wadsworth Center / NYSDOH Albany, New York

2. History of performance standards / Light Microscopy Current state of performance standards in light microscopy vendor initiated – none / acceptance specs only NIST developed -- none imaging community at large – lab specific Why ? – until the last 5-10 yrs, simply observing a specimen was sufficient; recent advances in light microscopes necessitate traceable standards & procedures Overall Goal – the creation of a range of imaging parameters traceable to standard references  NIH – Realizes the need for and supports the “core” model – 40% of S10 grants funded in FY2009 were for imaging in general; 13% were for confocal microscopes  NIST – create traceable references with the goal of moving medical imaging & lab testing from an art to a science  FDA – device & drug approval processes ensure manufacturers systems are reliable and drugs are safe & efficacious  Congress – provide the financial support for standards research Quality and standards: Making bioimaging ‘measure up’ Susan M. Reiss BioOptics World, Jan/Feb 2010, Vol.3 No.1, p.14-18 Access sparks action Lila Guterman NCRR Reporter, Winter 2010, p.4-8

3.  starting in early 2009, the LMRG began conducting Phase One of a worldwide research study to ascertain the current state of light microscope performance using simple, efficient & robust tests for LASER stability, field illumination & coregistration  define & improve cross-platform standards that will assist core managers and users in the maintaining their microscopes for optimal operation with the ultimate goal of improving the validity of quantitative measurements in light microscopy  the results of this study were accepted for publication in late 2010 in Microscopy and Microanalysis, one of the highest rated imaging journals (early 2011)  throughout 2010, the LMRG tested and defined additional areas of instrument performance (Phase Two) and refined the methodology for determining a system’s Spectral calibration, Spectral separation ability and finally the Point Spread Function of an imaging system Purpose of Phase Two of the Quality Assurance study

5. Phase One Study participation by country

6. Phase One Imaging stations by vendor

7. Proposed Procedures Spectral calibration Purpose: Measure spectral calibration of the detection system. MIDL lamp / mirror slide protocol:  Use 10x lens or no lens (system dependent)  Set up the MIDL lamp as the illumination source or use laser(s) and mirror slide (remove blocking)  Set the PMT gains to be ‘equivalent’  Perform a lambda scan and measure the signal-to-noise  Compare acquired spectra with published spectra Analysis: 1.Determine if your PMT(s) show significant spectral variation (sliders) or signs of aging reference: http://www.lightforminc.com/MIDL/index.html

11. PARISS Spectral Calibration Lamp, Lightform,Inc. Asheville, NC Overlay of 5 PMT responses and MIDL lamp calibrated output / before repair

12. PARISS Spectral Calibration Lamp, Lightform,Inc. Asheville, NC Overlay of 5 PMT responses and MIDL lamp calibrated output / after repair

13. Proposed Procedures Quality of Spectral un-mixing: Purpose: Measure the spectral un-mixing capability of an imaging system. Protocol: Bead slide: 6.0 µm FocalCheck Double Orange fluorescent microspheres (excitation/emission maxima: orange1 = 532/552 & orange2 = 545/565) o use same optical settings/components (i.e. laser line/excitation, dichroic filter) to acquire reference and experimental spectra o set detection to maximize S/N without any pixel saturation o select a detection bandwidth wide enough to encompass full emission range (e.g. DoubleOrange beads 520-575 nm) o if available, choose detection set-up (i.e. parallel vs. lambda) o split detection into smallest discreet ‘bins’ if using lambda scanning mode o select an area of the reference spectra (via ROI) with the highest S/N and store in database Analysis: Select the most appropriate unmixing data-processing algorithm available:  automatic mode (1 st pass / not generally adequate)  parallel mode (simultaneous data acquisition across multiple PMTs)  lambda mode (lambda scanning utilizing one PMT)

14. Spectral separation FocalCheck™ fluorescence microscope test slide Ring 589/613 nm Core 578/605 nm Image of a bead where the core and ring have a small spectral separation ring and core are pseudo-colored for illustration purposes

15. Linear Unmixing Algorithms  The measured spectra of a ‘mixed pixel’ is broken down into a collection of component spectra (endmembers) and a set of subsequent fractions (abundances) that indicate the ratio of each endmember in the pixel  Three distinct stages of spectral unmixing : - dimension reduction (i.e. data reduction) - endmember determination (i.e. # of distinct spectra) - inversion (i.e. abundance estimation)  Employs a linear mixing model A Survey of Spectral Unmixing Algorithms Nirmal Keshava Lincoln Laboratory Journal, Vol.14 No.1, 2003, p.55-78

16. reference: http://www.lightforminc.com/ Spectral_Unmixing.html

17. Resolution  point at which two objects are perceived as separate and distinct from one another  as the Numerical Aperture (NA) of a lens increases, so does the resolution of the imaging system (up to a point)  NA = measure of the acceptance angle of a lens, a.k.a. how well it bends light  Resolution obtained from an imaging system is affected by: the specific wavelength of light in use the diffraction of light (Rayleigh, Abbe & Sparrow limits) lens aberrations sample prep (coverslip thickness, mounting media, RI matching)  Lens imperfections such as coma, astigmatism and spherical aberrations will result in a loss of resolution  microscope resolution and the extent of image ‘blur’ is typically described in terms of its Point Spread Function (PSF)  an ‘ideal’ PSF demonstrates symmetric balance and proportion Limit of resolution: d = 0.612 (λ) / N.A.

18. What is a Point Spread Function & why is it so important ?  a measure of the degree of blurring of an object being imaged and any potential optical path aberrations  speaks directly to the quality/resolution of an imaging system  a point of light (object plane) spreads out in the image plane  ‘Image’ = convolution of an object and the point spread function  In 1835, G.B. Airy described a diffraction-limited spot of light focused by a ‘perfect’ lens with a circular aperture  an object plane light wave refocused by a lens produces a blurred focal plane point commonly referred to as an ‘airy disc / airy pattern’  sub-resolutional beads are typically used  the PSF of an imaging system directly impacts image refinement using deconvolution algorithms

19. Proposed Procedures Point Spread Function: Purpose: Measure the point spread function of an imaging system. Protocol: Bead slide: 175 nm PS-Speck beads (mixture of blue, green, orange & deep red single-color beads) o test multiple lens: i.e. 20x, 40x, 63x & 100x (all objectives routinely used for imaging in your lab) o collect a Z series or scan in XZY mode o if needed, suitably rotate image to obtain a ‘side view’ o if your system is filter based (non-AOBS), check various dichroic filters Analysis:  use the MetroloJ plug-in (Fiji / ImageJ) to determine the FWHM lateral & axial resolution  compare the experimental vs. theoretical resolution values  check the curve fits for all three

20. Leica SP5 / PSF set-up

21. MetroloJ plug-in special thanks to Fabrice Cordelieres / Microscopie Photonique de Fluorescence Multidimensionnelle

22. MetroloJ PSF report http://pacific.mpi-cbg.de/wiki/index.php/Fijispecial thanks to Fabrice Cordelieres

23. MetroloJ PSF report http://pacific.mpi-cbg.de/wiki/index.php/Fijispecial thanks to Fabrice Cordelieres

24. ‘Idealized’ PSF images courtesy of Zeiss

25. Theoretical PSF images / Confocal vs. Widefield courtesy of Media Cybernetics

26. Widefield PSF of thick specimen coverslip  decreasing depth & worsening PSFs | V

27. ‘3D’ Widefield PSF

28. 20x oil immersion lens NA 0.7

29. 20x / Refractive Index mismatch collar incorrectly set to water // RI(water)=1.33, RI(Leica imm.oil)=1.518

30. PSF / 40x oil NA 1.25 / pinhole = 1 airy unit

31. 40x oil NA 1.25 / pinhole = 0.5 & 2 airy units

32. 40x oil NA 1.25 / pinhole = 3 & 5 airy units

33. 40x oil NA 1.25 / pinhole = 7 & 8 airy units

34. 63x N.A. 1.4 oil immersion lens / Brownian motion

35. Corrective Actions Spectral Calibration – a.Service call Spectral Unmixing – a.Try a different unmixing algorithm - avoid using ‘automatic’ - try various linear algorithms - try non-linear (e.g. SWCCA) algorithms b.Try a different detector set-up - use (5) PMTs with simultaneous scanning OR - use (1) PMT with lambda scanning c. Improve the signal-to-noise Point Spread Function – a.Clean the lens and optics / remove all air bubbles b.Check for any possible refractive index mismatches c.Try a different lens d.Open pinhole aperture to mimic widefield conditions e.Check for optical misalignment ** It is important to note that the above suggestions DO NOT encompass all possible solutions to these issues **

36. The test specimens proposed for both phases of this study were decided upon by the members of the LMRG for their applicability, robustness, ease-of-use and relative cost. While the phase I & II tests utilize materials from specific vendors who offer excellent products for these purposes, neither the members of the LMRG nor the ABRF endorse the use of these specific vendors, and fully acknowledge the use of legitimate alternatives for the purposes of instrument performance testing.

37. Acknowledgements Light Microscopy Research Group Richard Cole(Chair)Wadsworth Center / NYSDOH Carol BaylesCornell University Claire BrownMcGill University Karen Jonscher(EB Liaison)University of Colorado Karen MartinWest Virginia University Cynthia OpanskyBlood Center of Wisconsin Katherine SchulzBlood Center of Wisconsin Robert StackWadsworth Center / NYSDOH Anne-Marie GirardOregon State University Ad hoc members: Jay JeromeVanderbilt University George McNamaraUniversity of Miami Robert ZuckerUS EPA * We would also like to thank the ABRF for their financial support and commitment to this project *