Abstract

A method is presented for imaging single isolated cell nuclei in 3D, employing computed tomographic image reconstruction. The system uses a scanning objective lens to create an extended depth-of-field (DOF) image similar to a projection or shadowgram. A microfabricated inverted v-groove allows a microcapillary tube to be rotated with sub-micron precision, and refractive index matching within 0.02 both inside and outside the tube keeps optical distortion low. Cells or bare cell nuclei are injected into the tube and imaged in 250 angular increments from 0 to 180 degrees to collect 250 extended DOF images. After these images are further aligned, the filtered backprojection algorithm is applied to compute the 3D image. To estimate the cutoff spatial frequency in the projection image, a spatial frequency ratio function is calculated by comparing the extended depth-of-field image of a typical cell nucleus to the fixed focus image. To assess loss of resolution from fixed focus image to extended DOF image to 3D reconstructed image, the 10–90% rise distance is measured for a dyed microsphere. The resolution is found to be 0.9 µm for both extended DOF images and 3D reconstructed images. Surface and translucent volume renderings and cross-sectional slices of the 3D images are shown of a stained nucleus from fibroblast and cancer cell cultures with added color histogram mapping to highlight 3D chromatin structure.

© 2005 Optical Society of America

1. Introduction

With the introduction of three-dimensional (3D) x-ray CT imaging, the advantages of having cross-sectional views of human anatomy have revolutionized radiology. In an analogous approach using optical images taken up to 90-degrees apart, Shaw et al. [1] reconstructed images from a single nucleus in 3D. However in practice, the ability to reconstruct 3D images of a cell nucleus from multiple and orthogonal perspectives have been fraught with technical challenges [1, 2, 3]. The previous attempts of rotating cells within a capillary tube appear to have been replaced by having the cells adhere to the outer surface of a spindle that is rotated [4]. The technical challenges of 3D optical tomography are reduced for large multi-cellular specimens such as embryos, and Sharpe et al. [5] has demonstrated exquisite 3D images based on a custom turntable stage and low numerical aperture (NA) optics.

The acquisition of orthogonal views requires custom cell preparation for optical microscopy, while a reduced range of viewing angles can be acquired from the standard microscope slide preparation. These techniques range from using one or more objective lenses [6, 7] to scanning the illumination beam across the high numerical aperture of a single objective lens [8, 9, 10]. Finally, a single perspective 3D image is acquired using laser scanning microscopy [11], and most often in the confocal geometry [12]. However, the single perspective suffers from an anisotropic point spread function that produces at least a three times reduction in spatial resolution along the optical axis compared to the lateral directions [13]. In commercial confocal laser scanning microscope systems, image contrast is limited to fluorescence, which eliminates the direct comparison to cellular specimens prepared for standard histological and cytological purposes. Furthermore, the many recent technical advances in high-resolution 3D optical microscopy that have been developed for imaging in fluorescence are inaccessible for the current needs of pathologists who rely on absorption-based stains, see Garini et al. [14] for a review.

To employ a tomographic reconstruction method, the depth of field must be increased to accommodate the entire specimen. Ideally, in-plane resolution is preserved while DOF is increased. The focal plane of a high NA objective lens is scanned axially through the cell nucleus to create an extended depth of field image [15]. We call the extended depth of field image a “pseudoprojection” to differentiate it from a standard projection image, as the effects of refractile contrast, diffraction, and only semi-quantitative staining yield an image that has yet to be shown to be truly quantitative. Extending the depth of field to create an analog to a projection image is critical when using a tomographic reconstruction method. By scanning the objective lens, the depth of field is extended. Alternative methods for extending the depth of field include wavefront coding [16,17], which could improve the resolution and minimize contrast reversal at larger defocus values, though at the cost of increased system complexity, greater computation time, and a loss of signal-to-noise ratio.

In our approach to developing the optical projection tomography microscope (OPTM), we chose to solve many of the opto-mechanical problems inherent in rotating individual cells around one axis through ≥180°. Our custom microcapillary tube-based rotation stage allows a full 360° of viewing angles of the specimen; having at least 180° is critical to achieving a complete tomographic reconstruction. Technical challenges consist of rotating the specimen accurately, the post-acquisition image correction for motion of the specimen not related to rotation, and the embedding of fixed cells in a suitable medium given the optical requirements and desired specimen position stability.

After the acquisition of all pseudoprojections, the 3D reconstruction is computed using a filtered backprojection method. By imaging in transmission using absorption stains, the resulting 3D image of the stained cell nucleus can be directly compared to knowledge base of pathologists and cytologists for diagnosing disease.

2. Methods

2.1. The optical projection tomography microscope

The optical projection tomography microscope is a modified brightfield transmission optical microscope (Olympus BX-51TF) with microcapillary tube-based rotation stage, which permits injection and viewing of cells radially around the full 360° of rotation. The refractive index matching both inside and outside the microcapillary tube minimizes optical distortion (that would otherwise be present due to the cylindrically-shaped tube). Another key feature is the piezoelectrically-driven objective lens positioner (Piezosystem Jena MIPOS-3 and NV40/1CL controller in closed loop mode) which allows the depth of field to be extended through incoherent superposition, in a manner similar to that described by Häusler [15]. The extension of the depth of field is necessary to form a suitable projection image, so that all features of the cell nucleus are present in equal focus from each different viewing angle. This is necessary for the purposes of tomographic reconstruction.

Figure 1 shows a schematic of the OPTM. In addition to the microcapillary-based specimen rotation stage and controller, and the piezoelectric objective lens positioner and its controller, there are position adjustments for rotation and translation of the CCD camera (Sensovation EZ-140m). These are used to align the microcapillary tube axis (axis of rotation) with the center line of pixels on the CCD, which facilitates reconstruction of the 3D image. A PC (Pentium 4, 2.4 GHz, Windows XP) running LabviewTM (National Instruments) is used to generate and synchronize the control signals for the piezoelectric scanner and the camera trigger. Image data is acquired within Labview by calling the dynamic link library functions supplied by the camera manufacturer. Utilities added to the Labview-based control panel are determinations of the accuracy of rotational and translational camera adjustments, the measurement of camera grayscale histogram, and a routine to view all 250 projection images as a movie.

2.2. Sample preparation

Samples from two cell lines, the lung fibroblast cell line CCD-34Lu and the A-549 lung cancer cell line, are isolated and fixed. Cytoplasm is removed to yield bare cell nuclei, which were then stained with hematoxylin. The specimen is concentrated by centrifugation, and mixed with the optical gel. This cell-gel mixture is then injected under pressure into the microcapillary tube for viewing in the OPTM.

2.3. Microcapillary-based rotation stage

The microcapillary tube-based rotation stage consists of a 150 µm outer diameter, 50 µm inner diameter fused silica microcapillary tube (Polymicro) clipped into a microfabricated inverted v-groove fixture (Corning Polymer Gripper with glass substrate). Rotation is accomplished with a stepper motor (Newport SR50pp and ESP300 controller). Optical gel (Nye OC431A-LVP) is used to suspend the cell nuclei, and the same refractive index-matched optical gel is placed outside the microcapillary tube. Figure 2 illustrates the similarity between a standard slide-mounted specimen and the microcapillary tube-based viewing stage.

 

Fig. 1. Schematic of optical projection tomography microscope (OPTM)

Download Full Size | PPT Slide | PDF

 

Fig. 2. Comparison of standard slide mounting with microcapillary-based stage

Download Full Size | PPT Slide | PDF

Figure 3 shows the refractive index difference between the optical gel and the fused silica microcapillary tubing (Polymicro). The illumination is provided by a 100W quartz-tungsten-halogen lamp (Olympus), and filtered so that the majority of illumination power is from 500–700 nm in wavelength. The filter improves image contrast for the hematoxylin-stained cell nuclei. The hematoxylin dye used to stain the cell nuclei has an absorption peak near 600 nm [18].

 

Fig. 3. Refractive index differences versus illumination wavelength for the microcapillary-based viewing stage

Download Full Size | PPT Slide | PDF

2.4. Projection image formation

In Fig. 4 the method for projection image or pseudoprojection formation is shown. A high numerical aperture (NA) objective lens (Olympus 100x 1.25 NA plan C achromat) is used for imaging. The cell nucleus is scanned over a range of 10 µm. Doing so allows the camera to gather a high-NA, well-focused information from each focal plane within the 10 µm scan range. Each image plane is incoherently superimposed during acquisition to create a pseudoprojection. All features in the pseudoprojections are uniformly defocused as a result, but the best-focus information for each feature is still present (assuming adequate sampling bit depth).

 

Fig. 4. Extending depth of field for high NA objective to create a pseudoprojection

Download Full Size | PPT Slide | PDF

2.5. Post-acquisition image processing

After acquiring 250 pseudoprojections around 180° of rotation (angular interval of 0.72°), within 60 seconds, the object centers of the images are identified through segmentation and grey scale image processing algorithm, and each frame shifted to keep the cell nucleus from translating along the axis of the tube. This post-acquisition processing is employed for motion and registration correction, which is necessary to preserve the submicron tolerances required for a high quality tomographic reconstruction. Centration error is maintained by the instrument to the submicron range but additional correction, supplied by locating tube edges in software, is required to prevent centration artifact in reconstructions. Note that we currently do not correct for movement of the microcapillary tube perpendicular to the tube axis in the plane of the image. Any motion occurring along the optical axis of the microscope objective cannot be corrected for, thus it is of great importance that the microcapillary tube stage rotate with only sub-micron errors in this direction.

2.6. Visualization

After motion correction of the projection images along the direction of the microcapillary tube axis, the 3D image is computed using a filtered backprojection algorithm [19]. Our reconstruction uses cubic voxels, with a linear dimension of 0.0665 microns. We use a ramp filter to compensate for the rolloff in the sampling density, modulated with a Hann window to attenuate the effects of noise [20]. The resulting 3D image is visualized using VolviewTM (Kitware) after noise was reduced through filters selected within Volview. By adjusting the display settings within Volview, three different display modes were generated with 3D features being more easily understood when the specimen is rotated during viewing. These display modes are (1) surface rendering of the cell nucleus, (2) transparency of the surface to reveal inner nuclear structure, and (3) slice viewing from any viewpoint.

2.7. Calculation of the spatial frequency ratio function

When we compute the power spectrum of the fixed-focal plane image, we first apply a 2D FFT to obtain a 2D map of spatial frequencies. In this map, all pixels located at the same distance from the central (DC) pixel have the same spatial frequency, but correspond to different directions. By finding the average of the values for each concentric circle, we obtain the magnitude of the spatial frequency spectrum, independent of direction. By repeating this process with the pseudoprojection, and dividing the resulting magnitude by that of the fixed focal plane image. We define this ratio as the spatial frequency ratio function (SFRF):

SFRF=<FT(pseudoprojection)>angle<FT(fixed_focus_image)>angle

where FT is the fourier transform. The angle subscript indicates that we average each spatial frequency magnitude over all directions to reduce noise.

We estimate the limit of resolution in the pseudoprojection image by finding the spatial frequency at which the SFRF exhibits a minimum. Comparison of the pseudoprojection to the fixed focus image in this manner allows estimation of the loss of resolution due to the extension of the depth of field. For frequencies beyond the first SFRF minimum, the spectrum contains only noise.

2.8. Microsphere imaging and the 10–90% rise distance test

A microsphere-gel mixture of black-dyed microspheres of 2 to 3 µm in diameter (Polysciences) is made. The 10–90% intensity rise distance measurement on a microsphere is used to establish loss of resolution throughout the various steps in forming a 3D image, with the fixed focus image used as the reference. The rise distance method determines the sharpness of the edge as an indicator of resolution. Figure 5 shows an example trace and 10–90% rise distance measurement, where the user sets the upper and lower boundaries to define the 0% and 100% levels. The 10% and 90% levels are calculated and the data point closest to these values is extracted. The 10–90% rise distance test is applied to fixed focus image data, pseudoprojection image data, and all three axes of the reconstructed image. Comparisons are made between these three types of data from the OPTM.

 

Fig. 5. Example graph of 10–90% rise distance measurement

Download Full Size | PPT Slide | PDF

3. Results

3.1. Spatial frequency ratio function and evaluation of resolution

The spatial frequency ratio function (SFRF) shown in Fig. 7 is calculated from the image data shown in Fig. 6. As the defocus becomes greater moving from a fixed focus image to a pseudoprojection image, we expect the spatial cutoff frequency to shift towards the lower spatial frequencies. For a camera with a limited bit depth, this would eventually result in the loss of information about the spectral content at high spatial frequencies. We acquire a pseudoprojection (10 µm scan range) and a fixed-focal plane image of a lung cancer nucleus (see Fig. 6). We then calculate the ratio of the pseudoprojection’s 2D spatial frequency spectrum with that of the fixed-focal plane image. The resulting SFRF, shown in Fig. 7, reaches a minimum at approximately 1.1 line pairs/µm, corresponding to a maximum spatial resolution of approximately 0.9 µm. For higher spatial frequencies, the ratio rises to a value near one; we interpret these higher frequencies as noise, which is expected to have equivalent spectral content in both images.

This SFRF result is somewhat ambiguous, since some features being sampled (at varying degrees of focus) in the pseudoprojection are not present (except as defocused features) in the fixed focal plane image. Examination of the power spectrum of the fixed-focal plane image indicates that it contains spatial frequency signals up to approximately 2.5 line pairs/µm. The ratio of the two images, plotted in Fig. 7, shows that spatial frequencies as high as 1.1 to 1.2 line pairs/µm are reproduced in the pseudoprojection, even for a scan range of 10 µm.

We also plotted the ratio of the fixed-focal plane image with a pseudoprojection acquired using a 20 and a 40 µm scan range (dashed and dotted lines in Fig. 7, respectively). In this case, the usable spatial frequency limit is approximately 0.8 line pairs/µm, which is equivalent to a spatial period of 1.25 µm. A reduction in the upper frequency limit is expected for a greater scan range.

 

Fig. 6. A lung cancer cell nucleus: the pseudoprojection (10 µm focal range, right) and the fixed-focal plane image (left) used for comparison

Download Full Size | PPT Slide | PDF

 

Fig. 7. Profile of the radially symmetric SFRF obtained by comparing the pseudoprojection of a lung cancer nucleus to its fixed focal plane image. The solid line (blue) denotes a 10 µm scan range, the dashed line (yellow) a 20 µm scan range, and the dotted line (pink) a 40 µm scan range

Download Full Size | PPT Slide | PDF

3.2. The 10–90% rise distance and evaluation of loss of resolution

Using the 10–90% rise distance test, the measurements on fixed focus images, pseudoprojections, and 3D reconstructed images of a dyed microsphere are presented in Table 1. Note that there appears to be loss of resolution as indicated by the difference in the 10–90% rise distance for fixed focus images compared to the pseudoprojections. However, there appears to be no significant difference between the pseudoprojections and the reconstructed image in this regard. The 10–90% rise distance is equal for all three axes of the 3D reconstruction, indicating that the resolution is isometric. Note that no deblurring is performed on this data, and the only filtration comes from the filtered backprojection algorithm used to reconstruct the 3-D image.

Tables Icon

Table 1. Diameter measurements and 10–90% rise distance for a single microsphere

The measurement of diameter of the microsphere in the fixed focus image also gives us our standard for comparison to other image types. The average diameter for fixed focus microsphere images is 2.50 µm, whereas the average of microsphere pseudoprojections is 2.56 µm, and the average of all diameters measured from the 3D reconstruction is 2.82 µm. The larger diameter as measured in the 3D reconstruction is primarily due to registration errors that cause feature broadening. The diameter of the microsphere as measured from the surface render is significantly larger because the threshold for surface rendering was chosen to be just above background noise level, and not at the half-maximum intensity level. Additionally, the diameter of the microsphere was measured in every possible dimension to assess feature distortion. The 3D surface rendering of the microsphere, mentioned at the bottom of Table 1, is shown in Fig. 8. The XYZ axes shown in Fig. 8 correlate with the XY, XZ, and YZ planes referred to in Table 1. The Z axis physically corresponds to the axis of the microcapillary tube (axis of rotation), and the XY plane is the plane of reconstruction.

An orange coloration was used for the surface rendering of this microsphere in Fig. 8, and virtual lighting is added using Volview to aid in depth perception.

 

Fig. 8. Microsphere surface view (728 KB avi)

Download Full Size | PPT Slide | PDF

Applying the Rayleigh criterion in equation 2 below gives us the theoretical minimum resolvable distance [21]:

D=1.22λ(NAobj+NAcond)

where D is the minimum resolvable difference, taken to be “resolution”. λ is the wavelength of illumination, NAobj is the numerical aperture of the objective lens, and NAcond is the numerical aperture of the condenser lens.

Inserting our values for objective and condenser NA (1.25 and 0.2 respectively), and the average wavelength of illumination (0.60 µm), we calculate the minimum resolvable distance to be 0.50 µm. Because the minimum resolvable distance is a function of the separation of two peaks, and the 10–90% rise distance relates the sharpness of a single peak edge, the two are not directly comparable. The complex shape of the intensity peaks in real images precludes an exact relationship between the two measures of resolution. However, the Rayleigh criterion specifies that the maximum of one peak occupies the same position as the minimum of the second peak. If we apply this to our edge intensity data (as used in the 10–90% rise distance measurement), we find the peak separation to be 0.93±0.03 µm.

3.3. Cell nucleus images

Figure 9 is a movie of a fibroblast cell nucleus, with surface rendered reflective, and Fig. 10 is a movie of the same cell nucleus, with the surface rendered as translucent so that internal structures are partially visible when coded in bright color. Figure 11 is a movie of the same fibroblast nucleus shown in Fig. 9 & 10, but in a thick slice (2.66 µm thick). The images are color-coded as according to the vertical look-up table bar, with 255 equaling lowest intensity of transmitted light.

All subsequent color movies (Fig. 10, 11, and 13) may differ in the exact assignment of color values. Coloration is used to aid visualization of internal nuclear structures, with particular color bands associated with cytologically relevant features, such as the Barr body (Xi chromosome) in orange (see Discussion). All figures use a pseudoprojection scan range of 10 µm.

 

Fig. 9. Normal lung fibroblast cell nucleus surface view (1.10 MB avi)

Download Full Size | PPT Slide | PDF

 

Fig. 10. Normal lung fibroblast cell nucleus transparent view (1.13 MB avi)

Download Full Size | PPT Slide | PDF

 

Fig. 11. Normal lung fibroblast cell nucleus slice view (546 KB avi)

Download Full Size | PPT Slide | PDF

Figure 12 is a movie of an A-549 type cancer cell nucleus, with the surface rendered reflective. Virtual lighting is added using Volview to aid in depth perception. Figure 13 is a movie of the same cancer cell nucleus shown in Fig. 12, but in a thick slice (1.7 µm thick).

 

Fig. 12. A549 cancer cell nucleus surface view (554 KB avi)

Download Full Size | PPT Slide | PDF

 

Fig. 13. A549 cancer cell nucleus slice view (472 KB avi)

Download Full Size | PPT Slide | PDF

4. Discussion

4.1. OPTM performance

By solving many of the fundamental problems with sample preparation and imaging in a rotating tube, high resolution 3D images of isometric resolution can be acquired using a conventional brightfield transmission microscope. Previous attempts such as Fauver et al. [22] had residual registration errors in the range of 5 to 10 µm, which discouraged any attempt at sub-micron resolution. The recent advances in the optomechanics are the high degree of refractive index matching inside and outside the microcapillary tube, the microfabricated rotational joint, and the choice of an optical gel as embedding medium. The sample preparation procedure uses a thixotropic optical gel that requires high pressures to insert the gel-specimen mixture which remains quite stable with pressure removed.

The difficulty of inserting a test target into the microcapillary tube required a rethinking of methods to quantify resolution of the OPTM. The combination of two different methods, the SFRF and the edge intensity profile-based measurements, lends more confidence that the system resolution is about 0.9 µm. Because the SFRF measurement was performed on unfiltered data, there is no potential for artifact related to image filtration. The surface roughness exhibited in Fig. 8 is interesting because it gives some qualitative indicator of surface render noise, assuming that the microsphere’s surface is smooth. The 10–90% rise distance data for the reconstructed 3D image indicates that resolution is approximately equal along all three orthogonal planes. The rise distance values for the reconstructed 3D image are similar to that of the pseudoprojection. This implies that the filtration, used as part of the filtered backprojection algorithm to create the reconstruction, did not adversely affect the sharpness of the edge. The loss of resolution, which occurred when the depth of field was extended, is not optimal—the theoretical 0.46 micron in plane resolution of the fixed focus image degraded to 0.9 micron in the pseudoprojection. At this resolution, it is less clear that the OPT method provides significant advantages over slice-based methods such as 3D deconvolution brightfield microscopy. However, the OPT method could take advantage of deconvolution methods to improve resolution. Methods such as wavefront coding could alternatively be employed to optimize the tradeoff between in-plane resolution and extended depth of field.

Future tests to be performed include the imaging of microsphere clusters. By varying the microsphere diameter to vary gap size between the microspheres, the resolvability of the each microsphere within the cluster could be established. Microsphere clusters may be used in the future to establish if the OPTM suffers from the feature overlap problem discussed by Pawley [12] for confocal laser scanning microscopes that produce 3D images from only one perspective.

4.1. Biological significance

Figures 9 and 10 demonstrate initial results in feature identification in 3D reconstructions of cell nuclei. One feature selected for identification was the inactivated X-chromosome (Xi, also known as the Barr body). This structure is consistent throughout female mammalian somatic cells, and retains three distinct characteristics: (1) the diameter is approximately one micron, (2) the structure is connected to the inner surface of the nuclear membrane, and (3) the shape is pyramidal. Since the Barr body is expected to uptake the hematoxylin stain and has absorption contrast, no other observable structure in the cell nucleus is consistent with these criteria.

The Barr body has been first described by Barr and Bertram in 1949 [23], and has been clinically used to implement rapid, non-invasive verification of gender. Cytological methods for Barr-body detection usually include the collection of cells from the test person (e.g. with a buccal swab), which are then spread on a slide, fixed and stained with hematoxylin. Since the cells are deposited on a slide in random orientation, only such Xi chromosomes that are coincidentally viewed from a proper angle will reveal the three characteristics of the Barr body, which is the case in only 5–20% of the cells. The aspect of random orientation is eliminated when using the OPTM, where the sample (e.g. cell or nucleus) is rotated, and imaged in three dimensions. Thus, every single cell nucleus of a sample can potentially be identified as Barr-body positive or Barr-body negative.

The nuclear structure differs among cells of different type and transformation status. It is more and more accepted that nuclear architecture and spatial organization of the chromatin assembly play a critical role in the control of gene expression (for a recent review see Vergani et al [24]). Although the underlying mechanisms are mostly unknown [25, 26], changes in nuclear morphology are valuable indicators of certain diseases, such as cancer. Cancerous cells exhibit typical alterations in nuclear morphology, which include changes in size, shape, and ratio of nucleus to cytoplasm, as well as changes in the nucleoli [27].

Morphological alterations in cancer nuclei are usually striking and identifiable with conventional 2D microscopy, without information about the true 3D arrangement of the chromatin. Conversely, nuclear changes in pre-malignant cells can be very subtle and difficult to detect. Here, 3D microscopy using the OPTM will help medical practitioners detect minute changes in nuclear structures, for example the appearance of the perinucleolar compartment [27], a structure of irregular shape with a highly variable size ranging from 0.25 to 1 µm in diameter. The OPT is being developed as a high specimen throughput clinical device that measures 3D morphology on fixed, stained cells. It certainly is of great interest to look at live cells using the OPT methodology, but the refractive index-matched gel media in which the cells are suspended would need to be water miscible.

Our clinical application using the OPTM is the earliest possible detection of malignant and pre-malignant cells in a lung cancer screening program for persons at high risk, such as analyzing the sputum from previous smokers.

Acknowledgments

This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services, under Contract No. HHSN261200433010C. We would like to acknowledge the Washington Technology Center for providing seed funding for this joint academic-industry partnership.

Thanks to Jeff Magula for assistance in design and fabrication of the microcapillary tube-based rotation stage.

References and links

1. P.J. Shaw, D.A. Agard, Y. Hiraoko, and J.W. Sedat, “Tilted view reconstruction in optical microscopy, three-dimensional reconstruction of Drosophila melanogaster embryo nuclei,” Biophys. J. 55:101–110 (1989) [CrossRef]   [PubMed]  

2. J. Bradl, M. Hausmann, B. Schneider, B. Rinke, and C. Cremer, “A versatile 2D-tilting device for fluorescence microscopes,” J. Microscopy 176(3): 211–221 (1992)

3. S. Kikuchi, K. Sonobe, L. S. Sidharta, and N. Ohyama, “Three-dimensional computed tomography for optical microscopes,” Opt. Commun. 107: 432–444 (1994) [CrossRef]  

4. P. Matula, M. Kozubek, F. Staier, and M. Hausmann, “Precise 3D image alignment in micro-axial tomography,” J. Microscopy 209(2), 126–142 (2003) [CrossRef]  

5. J. Sharpe, U. Ahlgren, P. Perry, B. Hill, A. Ross, J. Hecksher-Sorensen, R. Baldock, and D. Davidson, “Optical projection tomography as a tool for 3D microscopy and gene expression studies,” Science 296, 541–545 (2002) [CrossRef]   [PubMed]  

6. S. Kikuchi, S. Kazuo, and N. Ohyama, “Three-dimensional microscopic computed tomography based on generalized Radon transform for optical imaging systems,” Opt. Commun. 123, 725–733 (1996) [CrossRef]  

7. E.H.K. Stelzer and S. Lindek, “Fundamental reduction of the observation volume in far-field light microscopy by detection orthogonal to the illumination axis: confocal theta microscopy,” Opt. Commun. 111(5–6), 536–547 (1994) [CrossRef]  

8. S. Kawata, O. Nakamura, and S. Minami, “Optical microscope tomography. I. Support constraint,” J. Opt. Soc. Am. A , 4(1), 292–297 (1987) [CrossRef]  

9. V. Lauer, “New approach to optical diffraction tomography yielding a vector equation of diffraction tomography and a novel tomographic microscope,” J. Microscopy 205, 165–176 (2002) [CrossRef]  

10. R.O. Chamgoulov, P.M. Lane, and C.E. MacAulay, “Optical computed-tomography microscope using digital spatial light modulation,” in Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing, XI, J.-A. Conchello, C.J. Cogswell, and T. Wilson, eds., Proc. SPIE5324, 182–190 (2004)

11. T. Wilson and C. Sheppard, Theory and Practice of Scanning Optical Microscopy (Academic Press, London, 1984)

12. J.B. Pawley, Ed., Handbook of Biological Confocal Microscopy, 2nd Ed. (Plenum Press, New York, 1995) [CrossRef]  

13. R. Heintzmann and C. Cremer, “Axial tomographic confocal fluorescence microscopy,” J. Microscopy 206(1), 7–23 (2002) [CrossRef]  

14. Y. Garini, B. J. Vermolen, and I. T. Young, “From micro to nano: recent advances in high-resolution microscopy,” Current Opinion in Biotechnology 16, 3–12 (2005) [CrossRef]   [PubMed]  

15. G. Häusler, “A method to increase the depth of focus by two-step image processing,” Opt. Commun. 6, 38–42 (1972) [CrossRef]  

16. E. R. Dowski and W.T. Cathey “Extended Depth of Field Through Wavefront Coding,” Appl. Opt. 34, 1859–1866 (1995) [CrossRef]   [PubMed]  

17. S. Bradburn, E. R. Dowski, and W. Thomas Cathey “Realizations of Focus Invariance in Optical-Digital Systems with Wavefront Coding,” Appl. Opt. 36, 9157–9166 (1997) [CrossRef]  

18. D. Wittekind, E.R. Reinhardt, V. Kretschmer, and E. Zipfel “Influence of staining on fast automated cell segmentation, feature extraction, and cell image analysis” Anal. Quant. Cytol. 5 (1), 55–60 (1983) [PubMed]  

19. A.C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (IEEE Press, New York, 1988)

20. J.C. Russ, The Image Processing Handbook, 4th Ed. (RC Press, New York, 2002)

21. S. Inoue and K. Spring, Video Microscopy: the fundamentals2nd Ed. (Plenum Press, New York, 1997) [CrossRef]  

22. M. Fauver, E. J. Seibel, J.R. Rahn, F.W. Patten, and A.C. Nelson, “Micro optical tomography system,” in Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing, XI, J.-A. Conchello, C.J. Cogswell, and T. Wilson, eds., Proc. SPIE5324, 171–181 (2004)

23. M.L. Barr and E.G. Bertram, “A morphological distinction between neurons of the male and female, and the behavior of the nuclear satellite during accelerated nucleoprotein synthesis,” Nature 163, 676–677 (1949) [CrossRef]   [PubMed]  

24. L. Vergani, M. Grattarola, and C. Nicolini. “Modifications of chromatin structure and gene expression following induced alterations of cellular shape” Int J Biochem Cell Biol. 36(8), 1447–61 (2004) [CrossRef]  

25. G.S. Stein, M. Montecino, A.J. van Wijnen, J.L. Stein, and J.B. Lian. “Nuclear structure-gene expression interrelationships: implications for aberrant gene expression in cancer” Cancer Res. 60, 2067–76 (2000) [PubMed]  

26. J.D. Debes, T.J. Sebo, H.V. Heemers, B.R. Kipp, A.L. Haugen de, C.M. Lohse, and D.J. Tindall. “p300 modulates nuclear morphology in prostate cancer” Cancer Res. 65, 708–12 (2005) [PubMed]  

27. D. Zink, A.H. Fischer, and J.A. Nickerson. “Nuclear structure in cancer cells” Nat Rev Cancer 4, 677–87 (2004) [CrossRef]   [PubMed]  

References

  • View by:
  • |

  1. P.J. Shaw, D.A. Agard, Y. Hiraoko, and J.W. Sedat, �??Tilted view reconstruction in optical microscopy, three-dimensional reconstruction of Drosophila melanogaster embryo nuclei,�?? Biophys. J. 55:101-110 (1989)
    [CrossRef] [PubMed]
  2. J. Bradl, M. Hausmann, B. Schneider, B. Rinke, and C. Cremer, �??A versatile 2D-tilting device for fluorescence microscopes,�?? J. Microscopy 176(3): 211-221 (1992)
  3. S. Kikuchi, K. Sonobe, L. S. Sidharta, and N. Ohyama, �??Three-dimensional computed tomography for optical microscopes,�?? Opt. Commun. 107: 432-444 (1994)
    [CrossRef]
  4. P. Matula, M. Kozubek, F. Staier, and M. Hausmann, �??Precise 3D image alignment in micro-axial tomography,�?? J. Microscopy 209(2), 126-142 (2003)
    [CrossRef]
  5. J. Sharpe, U. Ahlgren, P. Perry, B. Hill, A. Ross, J. Hecksher-Sorensen, R. Baldock, and D. Davidson, �??Optical projection tomography as a tool for 3D microscopy and gene expression studies,�?? Science 296, 541-545 (2002)
    [CrossRef] [PubMed]
  6. S. Kikuchi, S. Kazuo, and N. Ohyama, �??Three-dimensional microscopic computed tomography based on generalized Radon transform for optical imaging systems,�?? Opt. Commun. 123, 725-733 (1996)
    [CrossRef]
  7. E.H.K. Stelzer and S. Lindek, �??Fundamental reduction of the observation volume in far-field light microscopy by detection orthogonal to the illumination axis: confocal theta microscopy,�?? Opt. Commun. 111(5-6), 536-547 (1994)
    [CrossRef]
  8. S. Kawata, O. Nakamura, and S. Minami, �??Optical microscope tomography. I. Support constraint,�?? J. Opt. Soc. Am. A, 4(1), 292-297 (1987)
    [CrossRef]
  9. V. Lauer, �??New approach to optical diffraction tomography yielding a vector equation of diffraction tomography and a novel tomographic microscope,�?? J. Microscopy 205, 165-176 (2002)
    [CrossRef]
  10. R.O. Chamgoulov, P.M. Lane, and C.E. MacAulay, �??Optical computed-tomography microscope using digital spatial light modulation,�?? in Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing, XI, J.-A. Conchello, C.J. Cogswell, and T. Wilson, eds., Proc. SPIE 5324, 182-190 (2004)
  11. T. Wilson and C. Sheppard, Theory and Practice of Scanning Optical Microscopy (Academic Press, London, 1984)
  12. J.B. Pawley, Ed., Handbook of Biological Confocal Microscopy, 2nd Ed. (Plenum Press, New York, 1995)
    [CrossRef]
  13. R. Heintzmann and C. Cremer, �??Axial tomographic confocal fluorescence microscopy,�?? J. Microscopy 206(1), 7-23 (2002)
    [CrossRef]
  14. Y. Garini, B. J. Vermolen, and I. T. Young, �??From micro to nano: recent advances in high-resolution microscopy,�?? Current Opinion in Biotechnology 16, 3-12 (2005)
    [CrossRef] [PubMed]
  15. G. Häusler, �??A method to increase the depth of focus by two-step image processing,�?? Opt. Commun. 6, 38-42 (1972)
    [CrossRef]
  16. E. R. Dowski and W.T. Cathey "Extended Depth of Field Through Wavefront Coding,�?? Appl. Opt. 34, 1859-1866 (1995)
    [CrossRef] [PubMed]
  17. S. Bradburn, E. R. Dowski,, and W. Thomas Cathey "Realizations of Focus Invariance in Optical-Digital Systems with Wavefront Coding,�?? Appl. Opt. 36, 9157-9166 (1997)
    [CrossRef]
  18. D.Wittekind, E.R. Reinhardt, V. Kretschmer, and E. Zipfel �??Influence of staining on fast automated cell segmentation, feature extraction, and cell image analysis�?? Anal. Quant. Cytol. 5 (1), 55-60 (1983)
    [PubMed]
  19. A.C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (IEEE Press, New York, 1988)
  20. J.C. Russ, The Image Processing Handbook, 4th Ed. (RC Press, New York, 2002)
  21. S. Inoue and K. Spring, Video Microscopy: the fundamentals 2nd Ed. (Plenum Press, New York, 1997)
    [CrossRef]
  22. M. Fauver, E. J. Seibel, J.R. Rahn, F.W. Patten, and A.C. Nelson, �??Micro optical tomography system,�?? in Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing, XI, J.-A. Conchello, C.J. Cogswell, and T. Wilson, eds., Proc. SPIE 5324, 171-181 (2004)
  23. M.L. Barr and E.G. Bertram, �??A morphological distinction between neurons of the male and female, and the behavior of the nuclear satellite during accelerated nucleoprotein synthesis,�?? Nature 163, 676-677 (1949)
    [CrossRef] [PubMed]
  24. L.Vergani, M. Grattarola, C. Nicolini. �??Modifications of chromatin structure and gene expression following induced alterations of cellular shape�?? Int J Biochem Cell Biol. 36(8), 1447-61 (2004)
    [CrossRef]
  25. G.S. Stein, M. Montecino, A.J. van Wijnen, J.L. Stein, J.B. Lian �??Nuclear structure-gene expression interrelationships: implications for aberrant gene expression in cancer�?? Cancer Res. 60, 2067-76 (2000)
    [PubMed]
  26. J.D. Debes, T.J. Sebo, H.V. Heemers, B.R. Kipp, A.L.Haugen de, C.M. Lohse, D.J. Tindall. �??p300 modulates nuclear morphology in prostate cancer�?? Cancer Res. 65, 708-12 (2005)
    [PubMed]
  27. D. Zink, A.H. Fischer, J.A. Nickerson. �??Nuclear structure in cancer cells�?? Nat. Rev. Cancer 4, 677-87 (2004)
    [CrossRef] [PubMed]

Anal. Quant. Cytol. (1)

D.Wittekind, E.R. Reinhardt, V. Kretschmer, and E. Zipfel �??Influence of staining on fast automated cell segmentation, feature extraction, and cell image analysis�?? Anal. Quant. Cytol. 5 (1), 55-60 (1983)
[PubMed]

Appl. Opt. (2)

Biophys. J. (1)

P.J. Shaw, D.A. Agard, Y. Hiraoko, and J.W. Sedat, �??Tilted view reconstruction in optical microscopy, three-dimensional reconstruction of Drosophila melanogaster embryo nuclei,�?? Biophys. J. 55:101-110 (1989)
[CrossRef] [PubMed]

Cancer Res. (2)

G.S. Stein, M. Montecino, A.J. van Wijnen, J.L. Stein, J.B. Lian �??Nuclear structure-gene expression interrelationships: implications for aberrant gene expression in cancer�?? Cancer Res. 60, 2067-76 (2000)
[PubMed]

J.D. Debes, T.J. Sebo, H.V. Heemers, B.R. Kipp, A.L.Haugen de, C.M. Lohse, D.J. Tindall. �??p300 modulates nuclear morphology in prostate cancer�?? Cancer Res. 65, 708-12 (2005)
[PubMed]

Current Opinion in Biotechnology (1)

Y. Garini, B. J. Vermolen, and I. T. Young, �??From micro to nano: recent advances in high-resolution microscopy,�?? Current Opinion in Biotechnology 16, 3-12 (2005)
[CrossRef] [PubMed]

Int J Biochem Cell Biol. (1)

L.Vergani, M. Grattarola, C. Nicolini. �??Modifications of chromatin structure and gene expression following induced alterations of cellular shape�?? Int J Biochem Cell Biol. 36(8), 1447-61 (2004)
[CrossRef]

J. Microscopy (4)

R. Heintzmann and C. Cremer, �??Axial tomographic confocal fluorescence microscopy,�?? J. Microscopy 206(1), 7-23 (2002)
[CrossRef]

J. Bradl, M. Hausmann, B. Schneider, B. Rinke, and C. Cremer, �??A versatile 2D-tilting device for fluorescence microscopes,�?? J. Microscopy 176(3): 211-221 (1992)

P. Matula, M. Kozubek, F. Staier, and M. Hausmann, �??Precise 3D image alignment in micro-axial tomography,�?? J. Microscopy 209(2), 126-142 (2003)
[CrossRef]

V. Lauer, �??New approach to optical diffraction tomography yielding a vector equation of diffraction tomography and a novel tomographic microscope,�?? J. Microscopy 205, 165-176 (2002)
[CrossRef]

J. Opt. Soc. Am. A (1)

Nat. Rev. Cancer (1)

D. Zink, A.H. Fischer, J.A. Nickerson. �??Nuclear structure in cancer cells�?? Nat. Rev. Cancer 4, 677-87 (2004)
[CrossRef] [PubMed]

Nature (1)

M.L. Barr and E.G. Bertram, �??A morphological distinction between neurons of the male and female, and the behavior of the nuclear satellite during accelerated nucleoprotein synthesis,�?? Nature 163, 676-677 (1949)
[CrossRef] [PubMed]

Opt. Commun. (4)

S. Kikuchi, S. Kazuo, and N. Ohyama, �??Three-dimensional microscopic computed tomography based on generalized Radon transform for optical imaging systems,�?? Opt. Commun. 123, 725-733 (1996)
[CrossRef]

E.H.K. Stelzer and S. Lindek, �??Fundamental reduction of the observation volume in far-field light microscopy by detection orthogonal to the illumination axis: confocal theta microscopy,�?? Opt. Commun. 111(5-6), 536-547 (1994)
[CrossRef]

G. Häusler, �??A method to increase the depth of focus by two-step image processing,�?? Opt. Commun. 6, 38-42 (1972)
[CrossRef]

S. Kikuchi, K. Sonobe, L. S. Sidharta, and N. Ohyama, �??Three-dimensional computed tomography for optical microscopes,�?? Opt. Commun. 107: 432-444 (1994)
[CrossRef]

Proc. SPIE (2)

R.O. Chamgoulov, P.M. Lane, and C.E. MacAulay, �??Optical computed-tomography microscope using digital spatial light modulation,�?? in Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing, XI, J.-A. Conchello, C.J. Cogswell, and T. Wilson, eds., Proc. SPIE 5324, 182-190 (2004)

M. Fauver, E. J. Seibel, J.R. Rahn, F.W. Patten, and A.C. Nelson, �??Micro optical tomography system,�?? in Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing, XI, J.-A. Conchello, C.J. Cogswell, and T. Wilson, eds., Proc. SPIE 5324, 171-181 (2004)

Science (1)

J. Sharpe, U. Ahlgren, P. Perry, B. Hill, A. Ross, J. Hecksher-Sorensen, R. Baldock, and D. Davidson, �??Optical projection tomography as a tool for 3D microscopy and gene expression studies,�?? Science 296, 541-545 (2002)
[CrossRef] [PubMed]

Other (5)

T. Wilson and C. Sheppard, Theory and Practice of Scanning Optical Microscopy (Academic Press, London, 1984)

J.B. Pawley, Ed., Handbook of Biological Confocal Microscopy, 2nd Ed. (Plenum Press, New York, 1995)
[CrossRef]

A.C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (IEEE Press, New York, 1988)

J.C. Russ, The Image Processing Handbook, 4th Ed. (RC Press, New York, 2002)

S. Inoue and K. Spring, Video Microscopy: the fundamentals 2nd Ed. (Plenum Press, New York, 1997)
[CrossRef]

Supplementary Material (6)

» Media 1: AVI (727 KB)     
» Media 2: AVI (1102 KB)     
» Media 3: AVI (1127 KB)     
» Media 4: AVI (545 KB)     
» Media 5: AVI (554 KB)     
» Media 6: AVI (471 KB)     

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (13)

Fig. 1.
Fig. 1.

Schematic of optical projection tomography microscope (OPTM)

Fig. 2.
Fig. 2.

Comparison of standard slide mounting with microcapillary-based stage

Fig. 3.
Fig. 3.

Refractive index differences versus illumination wavelength for the microcapillary-based viewing stage

Fig. 4.
Fig. 4.

Extending depth of field for high NA objective to create a pseudoprojection

Fig. 5.
Fig. 5.

Example graph of 10–90% rise distance measurement

Fig. 6.
Fig. 6.

A lung cancer cell nucleus: the pseudoprojection (10 µm focal range, right) and the fixed-focal plane image (left) used for comparison

Fig. 7.
Fig. 7.

Profile of the radially symmetric SFRF obtained by comparing the pseudoprojection of a lung cancer nucleus to its fixed focal plane image. The solid line (blue) denotes a 10 µm scan range, the dashed line (yellow) a 20 µm scan range, and the dotted line (pink) a 40 µm scan range

Fig. 8.
Fig. 8.

Microsphere surface view (728 KB avi)

Fig. 9.
Fig. 9.

Normal lung fibroblast cell nucleus surface view (1.10 MB avi)

Fig. 10.
Fig. 10.

Normal lung fibroblast cell nucleus transparent view (1.13 MB avi)

Fig. 11.
Fig. 11.

Normal lung fibroblast cell nucleus slice view (546 KB avi)

Fig. 12.
Fig. 12.

A549 cancer cell nucleus surface view (554 KB avi)

Fig. 13.
Fig. 13.

A549 cancer cell nucleus slice view (472 KB avi)

Tables (1)

Tables Icon

Table 1. Diameter measurements and 10–90% rise distance for a single microsphere

Equations (2)

Equations on this page are rendered with MathJax. Learn more.

SFRF = < FT ( pseudoprojection ) > angle < FT ( fixed _ focus _ image ) > angle
D = 1.22 λ ( NA obj + NA cond )

Metrics