Image analysis – Applications – Biomedical applications
Reexamination Certificate
2002-05-14
2003-10-21
Johns, Andrew W. (Department: 2621)
Image analysis
Applications
Biomedical applications
Reexamination Certificate
active
06636623
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to projection imaging systems in general and cell classification, and more particularly, to high throughput automated systems using projection imaging, such as flow optical tomography (FOT), for detecting cancer in high risk individuals based on highly quantitative measurements of nuclear or cytoplasmic molecular marker compartmentalization associated with malignancy and disease.
BACKGROUND OF THE INVENTION
The most common method of diagnosing cancer in patients is by obtaining a sample of the suspect tissue and examining it under a microscope for the presence of obviously malignant cells. While this process is relatively easy when the anatomic location of the suspect tissue is known and can be sampled thoroughly (e.g. the uterine cervix), it is not so easy when there is no readily identifiable tumor or lesion and the area to be sampled is very large. For example, with reference to the detection of lung cancer, it is not possible to swab the entire airway of the lungs. A sample such as sputum must be used as it contains cells exfoliated from the air passages in the lungs. This creates a dilution problem because an early lung cancer is very small compared to the entire internal surface of the lungs and, as a result, the number of cells shed from the tumor is also very small relative to that of normal cells. The problem is compounded because only a small portion of the sputum sample is actually examined. Thus, detection of lung cancer with traditional sputum cytology requires one or more relatively rare cancer cells to be present in the portion of the sample that is examined. Therefore, if the sample does not perceptively and accurately reflect the conditions of the lung, then patients having lung cancer may not be diagnosed properly.
One example of a microscope-based system and method for detecting diagnostic cells and cells having malignancy-associated changes is disclosed in Palcic et al., U.S. Pat. No. 6,026,174. The Palcic et al. system includes an automated classifier having a conventional microscope, camera, image digitizer, a computer system for controlling and interfacing these components, a primary classifier for initial cell classification, and a secondary classifier for subsequent cell classification. The method utilizes the automated classifier to automatically detect diagnostic cells and cells having malignancy-associated changes. This method improves on traditional cytology by detecting cells exhibiting malignancy-associated changes, which are more common than cancer cells. However, the quality of the diagnostic result is limited by the use of a conventional microscope, which does not permit accurate measurement of stain densities. Furthermore, the method of Palcic et al. does not address the use of specific molecular probes nor the compartmentalization of molecular markers.
With the advent of specific molecular probes, such as antibodies and nucleic acid probes, new disease related questions can be addressed by tagging these molecular probes and then measuring their location and concentration within biological cells and tissues. The use of tagged, specific molecular probes enable the indirect quantitation and compartmentalization of molecular markers such as pRb, p53/p53 binding protein 1 (53BP1), Sam68, PTEN, E2F and 5-methylcytosine-guanine (methyl CpG) which may be informative of disease processes such as cancer. (See, for example, Pasquale, D., “Retinoblastoma Protein Tethered to Promoter DNA Represses TBP-Mediated Transcription”, Journal of Cellular Biochemistry, 70:281-287, 1998, Rappold I, “Tumor Suppressor p53 Binding Protein 1 (53BP1) Is Involved in DNA Damage-signaling Pathways”, The Journal of Cell Biology, 153 (3):613-620. 2001, Chen, T., “A Role for the GSG Domain in Localizing Sam68 to Novel Nuclear Structures in Cancer Cell Lines”, Molecular Biology of the Cell 10:3015-3033, 1999, Perren, A., “Mutation and Expression Analyses Reveal Differential Subcellular Compartmentalization of PTEN in Endocrine Pancreatic Tumors Compared to Normal Islet Cells”, American Journal of Pathology, 157 (4):1097-1103, 2000, Gil, R., “Subcellular Compartmentalization of E2F Family Members Is Required for Maintenance of the Postmitotic State in Terminally Differentiated Muscle”, The Journal of Cell Biology, 148(6): 1187-1201, 2000, Rountree, M., “DNA methylation, chromatin inheritance, and cancer”, Oncogene , 20:3156-3165, 2001). As the need to more accurately localize and quantify these probes is emerging, there is a concomitant need for improved techniques to measure probe densities with submicron resolution in two dimensions (2D) and three dimensions (3D). Conventional light microscopy, which utilizes cells mounted on glass slides, can only approximate 2D density measurements because of limitations in focal plane depth, sampling angles, and problems with cell preparations that typically cause cells to overlap in the plane of the image. Another drawback of light microscopy is the inherent limitation of viewing through an objective lens where only the area within the narrow focal plane provides accurate data for analysis.
Flow cytometry methods generally overcome the cell overlap problem by causing cells to flow one-by-one in a fluid stream. Unfortunately, flow cytometry systems do not generate images of cells of the same quality as traditional light microscopy, and, in any case, the images are not three-dimensional. For background, those skilled in the art are directed to Shapiro, H M,
Practical Flow Cytometry,
3
rd
ed., Wiley-Liss, 1995.
Confocal microscopy offers 3D imaging of samples by imaging successive thin layers of the sample to create a stack of 2D images, which can be viewed in 3D. The imaging is accomplished by scanning a narrow spot of light across the sample on a glass slide. Fluorescent or reflected light is focused onto a detector through a pinhole, which blocks out-of-focus light from impinging on the detector. Thus, the size of the pinhole determines the resolution in the vertical direction and the spot size determines the resolution in the horizontal directions. Unfortunately, confocal microscopy is a very slow procedure because the image is built up by scanning a small spot of light in a raster across the sample and the sample has to be rescanned to produce each additional slice. Another drawback is that cells deposited on slides are flattened, causing distortions of cellular structures.
In the area of computer aided tomography, U.S. Pat. No. 5,402,460, issued Mar. 28, 1995, to Johnson, et al. entitled “Three-dimensional Microtomographic Analysis System” discloses a microtomographic system for generating high-resolution, three-dimensional images of a specimen using an x-ray generator and an x-ray detector that measures the attenuation of the x-ray beam through the specimen. Two projections, each using a different energy x-ray beam, of each view of the specimen are made with Johnson, et al.'s microtomographic system. After the two projections of one view of the specimen are made, the specimen is rotated on the specimen holder and another set of projections is made. The projections of each view of the specimen are analyzed together to provide a quantitative indication of the phase fraction of the material comprising the specimen. The projections of the different views are combined to provide a three-dimensional image of the specimen. U.S. Pat. No. 5,402,460 is incorporated herein by reference. Although the x-ray technology as taught by U.S. Pat. No. 5,402,460 is useful for some applications, it does not provide an optical solution useful for flow cytometry, whereby one could measure the 3D distribution of molecular density within a biological cell.
To overcome the aforementioned limitations and others found in such systems, it is a motivation of this invention to combine the one-by-one cell presentation of flow cytometry with computational optical tomography from multiple point source projections to reconstruct density information within a cell from a plurality of projections. The reconstruc
Chu Chee-Wui
Nelson Alan C.
Webster Robert W.
Johns Andrew W.
Leone George A.
Nakhjavan Shervin
VisionGate, Inc.
LandOfFree
Optical projection imaging system and method for... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Optical projection imaging system and method for..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optical projection imaging system and method for... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3160160