US20070121196A1 - Method and apparatus for method for viewing and analyzing of one or more biological samples with progressively increasing resolutions - Google Patents

Method and apparatus for method for viewing and analyzing of one or more biological samples with progressively increasing resolutions Download PDF

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US20070121196A1
US20070121196A1 US11/537,123 US53712306A US2007121196A1 US 20070121196 A1 US20070121196 A1 US 20070121196A1 US 53712306 A US53712306 A US 53712306A US 2007121196 A1 US2007121196 A1 US 2007121196A1
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information
processing arrangement
arrangement
exemplary
generate
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Guillermo Tearney
Dvir Yelin
Benjamin Vakoc
Melissa Suter
Brett Bouma
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General Hospital Corp
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General Hospital Corp
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Assigned to GENERAL HOSPITAL CORPORATION, THE reassignment GENERAL HOSPITAL CORPORATION, THE ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BOUMA, BRETT EUGENE, SUTER, MELISSA, TEARNEY, GUILLERMO J., VAKOC, BENJAMIN J., YELIN, DVIR
Publication of US20070121196A1 publication Critical patent/US20070121196A1/en
Assigned to NATIONAL INSTITUTES OF HEALTH (NIH), U.S. DEPT. OF HEALTH AND HUMAN SERVICES (DHHS), U.S. GOVERNMENT reassignment NATIONAL INSTITUTES OF HEALTH (NIH), U.S. DEPT. OF HEALTH AND HUMAN SERVICES (DHHS), U.S. GOVERNMENT CONFIRMATORY LICENSE (SEE DOCUMENT FOR DETAILS). Assignors: GENERAL HOSPITAL CORPORATION DBA MASS
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Definitions

  • the present invention relates to relates to methods and arrangement for viewing and analyzing of one or more biological samples and anatomic structures with progressively increasing resolutions.
  • Radiological techniques such as X-ray computed tomography (“CT”), magnetic resonance imaging (“MRI”), and ultrasound can enable noninvasive visualization of human pathology at the organ level.
  • CT computed tomography
  • MRI magnetic resonance imaging
  • ultrasound can enable noninvasive visualization of human pathology at the organ level.
  • these modalities may be capable of identifying large-scale pathology
  • the diagnosis of cancer can require the evaluation of microscopic structures that is beyond the resolution of conventional imaging techniques. Consequently, biopsy and histopathologic examination may be required for diagnosis.
  • precancerous growth and early stage cancers often arise on a microscopic scale, they can present significant challenges for identification and diagnosis.
  • Conventional screening and surveillance of these pathologies relies on unguided biopsy and morphological analysis of Hematoxylin and Eosin (“H&E”) stained slides.
  • H&E Hematoxylin and Eosin
  • RCM can be implemented, e.g., by rapidly scanning a focused beam of electromagnetic radiation in a plane parallel to a tissue surface, yielding transverse or en face images of tissue.
  • the large numerical aperture (NA) that may be used in RCM can yield a very high spatial resolution (1-2 ⁇ m), enabling visualization of subcellular structures.
  • High NA imaging can be particularly sensitive to aberrations that arise as light propagates through inhomogeneous tissue.
  • high-resolution imaging with RCM is typically limited to a depth of about 100-400 ⁇ m.
  • RCM has been extensively demonstrated as a viable imaging technique for skin tissue. Development of endoscopic confocal microscopy systems has been more difficult, owing at least in part to the substantial technical challenges involved in miniaturizing a scanning microscope.
  • One major obstacle to direct application of the concepts of confocal microscopy to endoscopy is the engineering of a mechanism for rapidly rastering a focused beam at the distal end of a small-diameter, flexible probe.
  • MEMS micro-electromechanical systems
  • RCM may provide microscopic images only at discrete locations—a “point sampling” technique. As currently implemented, point sampling can be inherent to RCM because it has a limited field of view, which may be comparable to or less than that of an excisional biopsy, and the imaging rate can be too slow for comprehensive large field microscopy.
  • miniaturization of high NA objectives can be achieved by providing, e.g., a gradient-index lens system, dual-axis objectives, or custom designs of miniature objectives.
  • a gradient-index lens system e.g., a gradient-index lens system
  • dual-axis objectives e.g., dual-axis objectives
  • custom designs of miniature objectives e.g., detailed images of the morphology of cervical epithelium may be obtained in vivo using a fiber optic bundle coupled to a miniature objective lens, and fluorescence-based images of colorectal lesions may be achieved using commercial instruments such as those which may be obtained, e.g., from Olympus Corp. and Pentax/Optiscan.
  • One of the objects of the present invention is to overcome certain deficiencies and shortcomings of the prior art systems (including those described herein above), and provide exemplary embodiments of methods and arrangement for viewing and analyzing of one or more biological samples and anatomic structures with progressively increasing resolutions. Such exemplary methods and arrangements can be used along with a visual inspection of the data or by automatic processing procedures of the data to guide the visualization of areas that are most likely to contain abnormal and/or unhealthy tissue.
  • method, apparatus and arrangement can be provided and which may analyze and/or illustrate at least one portion of an anatomical structure.
  • light can be forwarded to such portion so as to generate first information which is related to the portion.
  • the light can be provided on or within a subject.
  • the first information can be received, and at least one section of the portion may be selected based on the first information so as to generate second information.
  • a magnification of a display of the portion may be progressively modified as a function of the second information.
  • display of position and/or depth of the at least one portion can be modified (e.g., within the anatomical structure).
  • the second information can be associated with a region provided within such portion, and/or may be obtained by user-selecting the region.
  • the selection can be automatically performed by a processing arrangement without an input from a user.
  • An area of an abnormality within the at least one portion can be determined, and the processing arrangement may perform the selection and modification so as to display at least one section of the abnormality.
  • An area of an abnormality can be determined within the portion using the processing arrangement so as to generate third information, and the selection can be performed by the user and/or the processing arrangement as a function of the third information.
  • the first information can be associated with two-, three- or four or more-dimensional, representation of the portion. Further, the portion can have an area that is greater than 1 mm 2 and/or 10 mm 2 . A displayed section of the portion can have an area is less than 1 cm 2 , 1 mm 2 and/or 100 ⁇ 2 .
  • the first information can be associated with a confocal microscopy procedure, a spectrally-encoded confocal microscopy procedure, an optical coherence tomography procedure, and/or an optical frequency domain interferometry procedure. An arrangement can be situated within the anatomical structure so as to provide the light to the portion.
  • FIG. 1 is a schematic illustration of an exemplary spectrally encoded confocal microscopy (SECM) system
  • FIG. 2A is an exemplary SECM image of a swine intestinal epithelium, obtained ex vivo, 100 ⁇ m from the tissue surface using a single mode source and single-mode detection (SM-MM) configuration;
  • SM-MM single mode source and single-mode detection
  • FIG. 2B is another exemplary SECM image of a swine intestinal epithelium, obtained using a single-mode source and multi-mode detection (SM-MM) configuration;
  • SM-MM single-mode source and multi-mode detection
  • FIG. 2C is a magnified view of an SECM image of a swine intestinal epithelium
  • FIG. 3A is an exemplary SECM image of a swine intestinal epithelium, obtained ex vivo, after compression of the bowel wall at an imaging depth of 50 ⁇ m;
  • FIG. 3B is an exemplary SECM image of a swine intestinal epithelium, obtained ex vivo, after compression of the bowel wall at an imaging depth of 100 ⁇ m;
  • FIG. 4 is a schematic illustration of an exemplary SECM apparatus
  • FIG. 5 is an exemplary SECM image of a USAF chart
  • FIG. 6A is an exemplary SECM image based on data taken from a lens paper sample, displayed at a magnification of 1 ⁇ ;
  • FIG. 6B is an exemplary SECM image based on data taken from a lens paper sample, displayed at a magnification of 4.5 ⁇ ;
  • FIG. 6C is an exemplary SECM image based on data taken from a lens paper sample, displayed at a magnification of 16.7 ⁇ ;
  • FIG. 6D is an exemplary SECM image based on data taken from a lens paper sample, displayed at a magnification of 50 ⁇ ;
  • FIG. 6E is an exemplary SECM image based on data taken from a lens paper sample, displayed at a magnification of 125 ⁇ ;
  • FIG. 7 is a series of exemplary SECM data obtained from a lens paper sample at five different focal positions, together with a combine image that was generated by combining the data in the five individual images;
  • FIG. 8A is an exemplary SECM image based on data taken from a swine intestinal tissue fragment, displayed at a magnification of 1 ⁇ ;
  • FIG. 8B is an exemplary SECM image based on data taken from a swine intestinal tissue fragment, displayed at a magnification of 4 ⁇ ;
  • FIG. 8C is an exemplary SECM image based on data taken from a swine intestinal tissue fragment, displayed at a magnification of 20 ⁇ ;
  • FIG. 8D is an exemplary SECM image based on data taken from a swine intestinal tissue fragment, displayed at a magnification of 40 ⁇ ;
  • FIG. 9A are front and elevation side views of microscopic images of a porcine esophagus in vivo which shows a vascular network within the submucosa without image enhancement or exogenous contrast agents using an exemplary embodiment of a method and an arrangement according to the present invention
  • FIG. 9B is a side view of the microscopic image of a longitudinal cross-section through a wall of the esophageal at a location illustrated in FIG. 9A ;
  • FIG. 9C is a side view of an unwrapped transverse section at the location illustrated in A;
  • FIG. 9D is a side view of an expanded view of a selected section of the image illustrated in FIG. 9C ;
  • FIG. 9E is an exemplary image of a representative histology section obtained from the anatomical region corresponding to the image illustrated in FIG. 9D ;
  • FIG. 10 is a flow diagram of an exemplary embodiment of the method for progressively zooming into a microscopy dataset of an anatomical structure of the present invention
  • FIG. 11 is a series of exemplary images of esophageal mucosa obtained using optical coherence tomography (“OCT”) techniques, demonstrating an implementation of an exemplary embodiment of an automatic processing procedure for identifying normal squamous mucosa as compared to Barrett's esophagus and adenocarcinoma;
  • OCT optical coherence tomography
  • FIG. 12 is a set of exemplary images of atherosclerotic plaque obtained using the OCT techniques, which have been processed to identify a macrophage density
  • FIG. 13 is a flow diagram of another exemplary embodiment of the method according to the present invention for progressively zooming to a microscopy dataset of an anatomical structure based on the results obtained via a signal processing technique to automatically identify regions of interest that may be viewed at a high magnification.
  • methods and arrangement according to exemplary embodiments of the present invention can be provided for viewing and analyzing of one or more biological samples and anatomic structures with progressively increasing resolutions. Such exemplary methods and arrangements can be used along with a visual inspection of the data or by automatic processing procedures of the data to guide the visualization of areas that are most likely to contain abnormal and/or unhealthy tissue.
  • FIG. 1 An exemplary SECM technique is shown in FIG. 1 .
  • the output from a single-mode optical fiber 100 which may be located at a distal end of a probe, can be collimated by a collimating lens 110 , and then illuminate a dispersive optical element (such as, e.g., a transmission diffraction grating 120 ).
  • An objective lens 130 can then focus each diffracted wavelength to a distinct spatial location within the specimen, resulting in a transverse line focus 140 where each point on the line may be characterized by a distinct wavelength.
  • the optical signal After reflection from the specimen, which may be, e.g., biological tissue, the optical signal can be recombined by the diffraction element 120 and collected by the single-mode fiber 100 .
  • the core aperture of the single-mode fiber 100 can provide a spatial filtering mechanism that is capable of rejecting out-of-focus light.
  • the spectrum of the returned light can be measured and converted into confocal reflectance as a function of transverse displacement within the specimen.
  • the spectral decoding can be performed rapidly. Thus an image created by scanning the beam in a direction orthogonal to the line focus can be accomplished by relatively slow and straightforward mechanical actuation.
  • SECM techniques may allow the use of endoscopic RCM, and it can be capable of providing image data at extremely high rates using high-speed linear CCD cameras.
  • Commercially available linear CCD arrays can obtain data at a rate greater than about 60 million pixels per second. When incorporated into an SECM spectrometer, these arrays can produce confocal images at speeds that are about 10 times faster than a typical video rate and up to 100 times faster than some endoscopic RCM techniques.
  • the rapid imaging rate and fiber-optic design of typical SECM systems can permit comprehensive, large area microscopy through an endoscopic probe.
  • OCT optical coherence tomography
  • TD-OCT time-domain OCT
  • SD-OCT and SECM systems can be complementary, and a hybrid platform utilizing both techniques can provide information on the architectural and cellular structure of tissue that may be essential to accurate diagnosis.
  • SECM and SD-OCT systems can share key components, and a high-performance multi-modality system can be provided without substantially increasing complexity or cost of the individual systems.
  • An SECM system in accordance with certain exemplary embodiments of the present invention can utilize a wavelength-swept 1300 nm source and a single-element photodetector to obtain spectrally encoded information as a function of time.
  • images can be acquired at rates of up to about 30 frames/second having high lateral (1.4 ⁇ m) and axial (6 ⁇ m) resolutions, over a 400 ⁇ m field of view (“FOV”).
  • FOV field of view
  • FIGS. 2A-2C depict exemplary SECM images of a swine intestinal epithelium obtained ex vivo using two imaging modes and corresponding fiber configurations: a single-mode illumination with single-mode detection (“SM-SM”), and a single-mode illumination with multi-mode detection (“SM-MM”).
  • SM-SM single-mode illumination with single-mode detection
  • SM-MM single-mode illumination with multi-mode detection
  • the SM-SM image in FIG. 2A shows the epithelium structure 100 ⁇ m from the tissue surface using a single mode source and single-mode detection.
  • the image of the same tissue region shown in FIG. 2B obtained using a using a single mode source and multi-mode detection (SM-MM) with a core:aperture ratio of 1:4, appears smoother and may be more easily interpreted because of the reduction in speckle noise.
  • FIG. 2C is a magnified view of the image shown in FIG. 2B that shows evidence of villi containing a poorly reflecting core (e.g., lamina intestinal or “lp”) and a more highly scattering columnar epithelium. Bright image densities visible at the base of the columnar cells, consistent with nuclei (indicated by arrows) are evident in FIG. 2C .
  • a poorly reflecting core e.g., lamina basement or “lp”
  • the thickness of an esophageal wall being imaged in vivo using OCT techniques can be decreased, e.g., by about a factor of two using an inflated balloon.
  • the swine intestinal sample shown in FIGS. 2A-2C was decreased by the same amount, and the subcellular features observed using SECM techniques were well preserved.
  • FIGS. 3A and 3B show images of this thinned sample obtained at a depth of 50 ⁇ m and 100 ⁇ m, respectively.
  • the penetration depth of a commercial 800 nm laser scanning confocal microscope was observed to be reduced by about 20% as compared to that obtained with a 1300 nm SECM system. This reduced penetration may be a result of increased scattering of the shorter wavelength source.
  • an SECM system using an 840 nm source may provide sufficient penetration to identify subcellular structure of, e.g., an intestinal epithelium.
  • FIG. 4 An apparatus in accordance with certain exemplary embodiments of the present invention that is configured to provide comprehensive SECM images is illustrated schematically in FIG. 4 .
  • This exemplary apparatus can be configured to obtain images from a cylindrical sample having a length of 2.5 cm and a diameter of 2.0 cm, which are approximately the dimensions of the distal esophagus.
  • a fiber-coupled 2.0 mW superluminescent diode 200 having a wavelength centered at 800 nm and a bandwidth of 45 nm (QSSL-790-2, qPhotonics, Chesapeake, Va.) was configured to illuminate a 50 / 50 single-mode fiber optic beam splitter 405 .
  • Light transmitted through one port of the splitter was collimated by a collimator 410 and transmitted through a fiber 412 to a focusing apparatus 415 and to a grating-lens pair that includes a grating 420 (1780 lpmm, Holographix, LLC, Hudson, Mass.) and a 350230 -B asphere lens 425 (Thor Labs, Inc., Newton, N.J.) having a focal length, f, of 4.5 mm, a clear aperture of 5.0 mm, and a NA of 0.55.
  • This arrangement was capable of producing a 500 ⁇ m longitudinal linear array, or line, of focused, spectrally-encoded spots 430 on an interior surface of the cylindrical sample.
  • the grating-lens pair was affixed to the shaft of a motor 435 ( 1516 SR, 15 mm diameter, MicroMo Electronics, Inc., Clearwater, Fla.) by a housing 440 .
  • a motor 435 1516 SR, 15 mm diameter, MicroMo Electronics, Inc., Clearwater, Fla.
  • the motor 435 rotated, the spectrally encoded line was scanned across the inner circumference of the cylindrical sample.
  • the motor 435 , housing 440 , and grating-lens pair were translated along a longitudinal axis of the cylindrical sample during rotation of the motor 435 using a computer-controlled linear stage 445 (Nanomotion II, 2.5 cm range, Melles Griot, Rochester, N.Y.). This procedure produced a helical scan of the entire interior surface of the cylindrical sample.
  • a spectrometer 450 and linear CCD 455 that includes 2048 pixels and has a 30 kHz line rate (Basler L 104 K, Basler Vision Technologies, Exton, Pa.).
  • a computer 460 was used to store, analyze and display image data provided by the spectrometer 450 and CCD 455 .
  • Approximately 60,000 points per motor rotation (at 0.5 Hz, or 30 rpm) were digitized to achieve a 1.0 ⁇ m circumferential sampling density.
  • the longitudinal velocity of the motor was 0.25 mm/s and the time required for one complete scan of the cylindrical sample was 100 seconds.
  • the 1/e 2 diameter of the collimated beam on the grating-lens pair was 4.0 mm.
  • the effective NA of this exemplary apparatus was approximately 0.4, which corresponds to a theoretical spot diameter of approximately 1.2 ⁇ m and a confocal parameter of approximately 2.5 ⁇ m.
  • the theoretical spectral resolution on the sample may be 0.8 ⁇ , which can yield up to approximately 630 resolvable points across the spectrally encoded line 430 .
  • the spectrometer 450 in the detection arm was designed to exceed the predicted spectral resolution of the probe.
  • FIG. 5 An SECM scan of a 1951 USAF resolution chart obtained using this apparatus is shown in FIG. 5 .
  • SECM image data for a complete pullback image of a 2.5 cm phantom specimen are shown in FIG. 6 .
  • Polar coordinates were converted to rectangular coordinates prior to generating these displayed images.
  • the phantom specimen was made using lens paper affixed to the inner surface of a 2.1 cm inner diameter Teflon tube.
  • FIG. 6A In a low magnification image shown in FIG. 6A , macroscopic structure of the paper, including folds and voids, can be observed. Circumferential stripes that are visible may have resulted from the lower spectral power and lens aberrations that may be present at or near the ends of the spectrally-encoded line. Individual fibers and fiber microstructure can be clearly resolved in regions of this data set that are presented at higher magnifications, as shown in FIGS. 6B-6E .
  • cylindrical two-dimensional (“2D”) images of the phantom sample were acquired at five discrete focal depths over a range of 120 ⁇ m. These five images 710 - 750 shown in FIG. 7 were then summed to create an integrated image 760 , which demonstrates a nearly complete coverage of the surface of the phantom sample.
  • FIG. 8A A 360° scan of this sample, which was acquired in 1 second, is shown in FIG. 8A .
  • Imaged tissue appears in only one sector of the cylindrical scan because the probe was not centered and the sample did not wrap completely around the cylinder.
  • FIGS. 8B-8D show a sequence of magnified regions of this tissue sample.
  • the image shown in FIG. 8B is an expansion of a 1.5 cm sector outlined by a dotted rectangle in FIG. 8A .
  • FIG. 8B A 360° scan of this sample, which was acquired in 1 second
  • FIG. 8C represents an expansion of the rectangle outlined in FIG. 8B
  • the image in FIG. 8D represents an expansion of the rectangle outlined in FIG. 8 C.
  • Magnified images of the tissue in the image FIG. 8B are suggestive of a glandular structure.
  • the magnified images in FIGS. 8C-8D exhibit villi and nuclear features that are similar to those observed using a 1300 nm SECM system, as shown in FIGS. 2 and 3 .
  • Other areas of the SECM scan in FIG. 8A show artifacts, including specular reflectance from the transparent cylinder and complete signal dropout, both of which may result from improper positioning of a focused SECM beam.
  • Such challenges may include, e.g., increasing the imaging rate, miniaturizing the probe optics and mechanical components, incorporating a centering mechanism, and implementing a technique for dynamically changing the focal plane.
  • the image acquisition speed of an SECM system can be improved by, e.g., a factor of about 2-4 as compared with the exemplary system described hereinabove. Such an improvement can be realized by providing certain modifications.
  • a higher power semiconductor light source such as, e.g., a Superlum Diode, T-840 HP: 25 mW, 840 nm, 100 nm spectral bandwidth
  • T-840 HP 25 mW
  • 840 nm 100 nm spectral bandwidth
  • the increase in optical power can improve sensitivity and the larger bandwidth may widen the field of view, making it possible to scan the SECM beam approximately two times faster.
  • an optical circulator such as, e.g., an OC-3-850 (Optics for Research, Caldwell, N.J.) can increase the efficiency of light delivered to the probe and collected from the probe.
  • a faster, more sensitive linear CCD such as, for example, an AVIIVA M4-2048 having 2048 pixels and a 60 kHz readout rate (Atmel Corporation,) can provide a twofold increase in data acquisition speed and an improved spectral response over the wavelength range used to generate image data.
  • Performance may also be improved by using, e.g., a Camera Link interface that can be capable of transferring data at a rate of approximately 120 MB/s from a camera to a hard-drive array for storage.
  • Sensitivity which can be understood to refer to a minimum detectable reflectance, is a system parameter that can affect confocal image quality and penetration depth.
  • a fraction of the incident light which may be approximately 10 ⁇ 4 to 10 ⁇ 7 , can be reflected from skin at depths up to approximately 300 ⁇ m when using a near-infrared RCM technique.
  • the exemplary SECM probe objective described herein may collect approximately 3 ⁇ 10 ⁇ 4 to 3 ⁇ 10 ⁇ 7 of the illuminating light reflected from deep within tissue.
  • the 25 mW light source may be separated into, e.g., approximately 1000 independent beams.
  • a maximum double pass insertion loss can be estimated to be approximately 10 dB (6 dB from the probe, and 4 dB from the fiber optics and spectrometer).
  • Each pixel in an array may thus be illuminated by approximately 50 to 50,000 photons/pixel for each line integration period based on these estimated parameters.
  • a factor of 10 signal gain may be achieved, resulting in approximately 500 to 500,000 photons/pixel per scan for such a configuration.
  • a single pixel on an Atmel AVIIVA M 4 camera e.g., can reliably detect light if a signal is above the dark current fluctuation that occurs at approximately 240 photons. If this device has approximately a 50% quantum efficiency at these wavelengths, a minimum detectable signal can be produced at approximately 480 photons/pixel per scan. Based on these approximations, an Atmel camera may have sufficient sensitivity to allow SECM imaging at deeper tissue depths. Quantum noise-limited detection of a predicted minimum reflectance can be achieved by using a multi-mode fiber for collection or by increasing the source power.
  • methods and arrangements can be provided for navigating, analyze and display large microscopic datasets from anatomical structures.
  • FIGS. 9A-9E illustrate various images of a porcine esophagus in vivo obtained using comprehensive microscopy and the exemplary embodiments of the methods and arrangements of the present invention.
  • These exemplary images can be generated by a computer 460 (e.g., personal computer, mini computer, etc.) shown in FIG. 4 or another processing arrangement which may be configured (e.g., by software) to forward such images to a display 470 of FIG. 4 or another output arrangement.
  • the computer 460 can control various component of the exemplary system of FIG.
  • FIG. 9A shows front and elevation side views 900 , 905 , respectively, of microscopic images of a porcine esophagus in vivo which provides a vascular network within the submucosa without image enhancement or exogenous contrast agents using such exemplary embodiment of the method and arrangement.
  • 14 GB volumetric data set of FIG. 9A can be rendered and downsampled for a presentation in arbitrary orientations and perspectives.
  • the vascular network within the submucosa is shown without such image enhancement or exogenous contrast agents.
  • Cross-sectional images can be located on the volume image for higher resolution viewing using the computer 460 configured for such exemplary task(s) and other components of the system of FIG. 4 .
  • FIG. 9B shows a side view 910 of the microscopic image of a longitudinal cross-section through a wall of the esophageal at a location illustrated in FIG. 9A .
  • this image 910 is inverted with epithelium at the top; dimensions: 45 mm horizontal, 2.6 mm vertical.
  • a periodic vertical offset corresponding to the motion of the beating heart can be observed.
  • An exemplary embodiment of a surface-aligning procedure can be used to reduce this artifact but a residual vertical banding, that may still be observed with a period of 300 microns corresponding to a heart rate of 90 beats/min.
  • the exemplary longitudinal pitch between adjacent A-lines is shown as 32 ⁇ m.
  • FIG. 9C shows a side view 920 of an unwrapped transverse section (e.g., cylindrical coordinates r & ⁇ are mapped to vertical and horizontal) at the location illustrated in FIG. 9A .
  • the exemplary dimensions of the illustration are as follows: 57 mm—horizontal, 2.6 mm—vertical.
  • FIGS. 9B and 9C illustrate the imaging through the entire esophageal wall, and can enable an identification of the squamous epithelium (e), lamina basement (lp), muscularis mucosa (mm), submucosa (s), and muscularis laminate (mp).
  • FIG. 9D shows a side view 930 of an expanded view of a selected section of the image illustrated in FIG. 9C which can be used to assist with such identification.
  • FIG. 9E shows an exemplary image of a representative histology section (H&E stain) obtained from the anatomical region corresponding to the image illustrated in FIG. 9D .
  • H&E stain H
  • FIG. 10 depicts a flow diagram describing an exemplary embodiment of a method or a procedure according to the present invention for analyzing and/or viewing the data set at progressively higher resolutions, which can be executed using the computer 460 shown in FIG. 4 .
  • a microscopic dataset which can have a resolution of less than 10 ⁇ m, may be acquired over a large area of tissue or from a volume of tissue, or organ therein.
  • the data can then be formatted (in step 1010 ) in a representation that may illustrate a low magnification or low power view of the entire data set or a portion of the data set.
  • the user may view the data set, and using a computer interface, can select (a) a rectangular region, (b) a point, (c) an arbitrary shaped region, and/or (d) a depth in which to visualize a higher magnification view.
  • the new region can be viewed in step 1020 , and the user can (a) select another region, (b) zoom in at a point, (c) zoom out, (d) translate the current view in three dimensions, and/or (e) change the depth location of viewing within the dataset.
  • the entire exemplary process illustrated in FIG. 10 can be repeated until the area or areas of interest can be identified for visualization.
  • the user can select different images at any magnification or view to store for later inspection. Labeling of each individual view can also be conducted during the exemplary navigation procedure. Various regions/images at different magnifications/locations can be bookmarked so that the user can return to the same region/image during a subsequent navigation session.
  • FIGS. 6A-6E , 7 and 9 A- 9 E illustrate examples of the progressive magnification while viewing a large area microscopic dataset.
  • FIG. 11 depicts a series of exemplary images of esophageal mucosa obtained using optical coherence tomography (“OCT”) techniques, demonstrating an implementation of an exemplary embodiment of an automatic processing procedure for identifying normal or benign squamous mucosa as compared to Barrett's esophagus and adenocarcinoma via an analysis of OCT image spatial frequencies.
  • OCT optical coherence tomography
  • FIG. 11 OCT images 1100 , 1110 , and 1120 and spatial frequency distributions 1105 , 1115 , and 1125 of different disease states are shown.
  • Squamous epithelium 1100 SE
  • SE has vertical spatial frequencies (see arrows 1007 in panel 1105 ), corresponding to horizontal layers that may not be present in SIM.
  • a widely varying spatial frequency distribution are shown in the exemplary OCT images of adenocarcinoma (CA) 1120 and its corresponding spatial frequencies 1125 compared with SIMND 1110 and 1115 .
  • FIG. 12 depicts an illustration of a macrophage content 1210 obtained from OCT images of atherosclerotic plaques 1200 by determining the normalized standard deviation parameter (NSD). The density of macrophages can be obtained and displayed as an image using a color table 1220 .
  • NSD normalized standard deviation parameter
  • FIG. 13 depicts a flow diagram of an exemplary embodiment of the method and procedure according to the present invention for navigating and evaluating the microscopic image data set.
  • a microscopic dataset can be obtained in step 1300 , which preferably has a resolution of less than 10 ⁇ m, possibly acquired over a large area of tissue or from a volume of tissue or organ therein.
  • the data is then processed automatically by a processing arrangement (e.g., using the computer 460 ) in step 1310 to identify regions/locations that either contain areas suspect for disease or conversely areas that are suspected to contain no disease (i.e., healthy portions).
  • a processing arrangement e.g., using the computer 460
  • the unhealthy areas can be represented using a color or other marking method, and then viewed at low magnification of the entire microscopic data volume in step 1330 .
  • the user can then select a region to view in step 1340 , guided by the processing data and the representation thereof.
  • the user may then view the data set and, using a computer interface, select (a) a rectangular region, (a) a point, (c) an arbitrary shaped region, and/or (d) a depth in which to visualize a higher magnification view.
  • the new region can be viewed, and the user (or the computer 460 ) can manually or automatically (a) select another region, (b) zoom in at a point/zoom out (step 1350 ), (d) translate the current view in three dimensions, and/or (e) change the depth location of viewing within the dataset. Further, in step 1360 , the user can view the newly illustrated region.
  • the exemplary method/procedure may be repeated until the area(s) of interest is/are identified for visualization.
  • the user or the computer 460 can select different images at any magnification or view to store for later inspection. Labeling of each individual view can also be conducted during the exemplary navigation process. The regions/images at different magnifications/locations can be bookmarked and stored so that the user can return to the same region/image during a subsequent navigation session.
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