Abstract: A classification training method for training classifiers adapted to identify specific mutations associated with different cancer including identifying driver mutations. First cells from mutation cell lines derived from conditions having the number of driver mutations are acquired and 3D image feature data from the number of first cells is identified. 3D cell imaging data from the number of first cells and from other malignant cells is generated, where cell imaging data includes a number of first individual cell images. A second set of 3D cell imaging data is generated from a set of normal cells where the number of driver mutations are expected to occur, where the second set of cell imaging data includes second individual cell images. Supervised learning is conducted based on cell line status as ground truth to generate a classifier.

Abstract: A method for a system and method for morphometric detection of malignancy associated change (MAC) is disclosed including the acts of obtaining a sample; imaging cells to produce 3D cell images for each cell; measuring a plurality of different structural biosignatures for each cell from its 3D cell image to produce feature data; analyzing the feature data by first using cancer case status as ground truth to supervise development of a classifier to test the degree to which the features discriminate between cells from normal or cancer patients; using the analyzed feature data to develop classifiers including, a first classifier to discriminate normal squamous cells from normal and cancer patients, a second classifier to discriminate normal macrophages from normal and cancer patients, and a third classifier to discriminate normal bronchial columnar cells from normal and cancer patients.

Abstract: A classification training method for training classifiers adapted to identify specific mutations associated with different cancer including identifying driver mutations. First cells from mutation cell lines derived from conditions having the number of driver mutations are acquired and 3D image feature data from the number of first cells is identified. 3D cell imaging data from the number of first cells and from other malignant cells is generated, where cell imaging data includes a number of first individual cell images. A second set of 3D cell imaging data is generated from a set of normal cells where the number of driver mutations are expected to occur, where the second set of cell imaging data includes second individual cell images. Supervised learning is conducted based on cell line status as ground truth to generate a classifier.

Abstract: A method of treating a malignancy in a human subject by analyzing pseudo-projection images of cells obtained from a sputum specimen obtained from a subject employs a biological specimen classifier that identifies cells from the sputum specimen as normal or abnormal. If abnormal cells are detected, then the abnormal cells are further classified as dysplastic or cancerous. If the cells are classified as dysplastic, then an immunomodulating agent is administered to the subject over a predetermined time period designed to achieve a therapeutic dosage.

Abstract: A classification training method for training classifiers adapted to identify specific mutations associated with different cancer including identifying driver mutations. First cells from mutation cell lines derived from conditions having the number of driver mutations are acquired and 3D image feature data from the number of first cells is identified. 3D cell imaging data from the number of first cells and from other malignant cells is generated, where cell imaging data includes a number of first individual cell images. A second set of 3D cell imaging data is generated from a set of normal cells where the number of driver mutations are expected to occur, where the second set of cell imaging data includes second individual cell images. Supervised learning is conducted based on cell line status as ground truth to generate a classifier.

Abstract: A method to develop one or more morphometric classifiers to identify a mismatch repair deficiency (MMRD). The method provides a non-invasive method of characterizing MMRD that is responsive to a tumor in its early stages of development and irrespective of the tumor size. The method allows targeting cancer therapy to the specific characteristics of the cancer that the patient may have, allowing more efficient cancer management with far fewer side effects.

Abstract: A method for a system and method for morphometric detection of malignancy associated change (MAC) is disclosed including the acts of obtaining a sample; imaging cells to produce 3D cell images for each cell; measuring a plurality of different structural biosignatures for each cell from its 3D cell image to produce feature data; analyzing the feature data by first using cancer case status as ground truth to supervise development of a classifier to test the degree to which the features discriminate between cells from normal or cancer patients; using the analyzed feature data to develop classifiers including, a first classifier to discriminate normal squamous cells from normal and cancer patients, a second classifier to discriminate normal macrophages from normal and cancer patients, and a third classifier to discriminate normal bronchial columnar cells from normal and cancer patients.

Abstract: A method for pre-positioning a coaxial sample and sheath combination includes calculating a load shape profile including a plurality of layers of substantially equal volume. The calculated load shape profile is incrementally divided into cross-sectional slices at a first set of distance coordinates along a first axis. Each cross-sectional slice transects the plurality of layers. A sample includes a number of objects residing in solution. A sample chamber is loaded with the sample by incrementally dispensing the sample in a plurality of portions along a vertical axis divided into a second set of distance coordinates proportional to the first set of distance coordinates, where each portion has a volume proportional to the cross-sectional slice at the first distance coordinate nearest in value to the second distance coordinate.

Abstract: A method to develop one or more morphometric classifiers to identify a tumor mutation burden (TMB). The method provides a non-invasive method of characterizing TMB that is responsive to a tumor in its early stages of development and irrespective of the tumor size. The method allows targeting cancer therapy to the specific characteristics of the cancer that the patient may have, allowing more efficient cancer management with far fewer side effects.

Abstract: A method for measuring microscopic object velocities in fluid flow in a capillary tube including scanning a microscope focal plane through a fluid filled space for objects, where the scanning follows an interrupted repeating pattern having sub-patterns where the sub-patterns position the microscope focus plane beginning at a selected focus position at a first time and ending at the selected focus position at a later second time. A sensor registers images in image frames during the scanning. A first object image is registered in a first image frame at the selected focus position and a second object image is registered in a second image frame at the selected focus position. The object in the first object image and the second object image are identified as the same object. A processor determines a velocity for the identified object.

Abstract: A method for enhancing gating performance of a cell sorter to prepare an enriched specimen for optical tomography cell analysis includes introducing a specimen into a FACS to generate 2D event data; generating a first scatterplot of the 2D data; identifying target objects; constructing a boundary within the first scatterplot to produce a first gate; counting target objects within the first gate; comparing the number of target objects within the first gate to a first predetermined value and adjusting the first gate as necessary. A boundary around a set of target objects is constructed in a second scatterplot to produce a subset second gate and target objects within the second gate are counted and the count compared to a second predetermined value. When a boundary around target objects meets specifications the first and second gates are stored in memory and used to enrich patient specimens.

Abstract: A method for pre-positioning a coaxial sample and sheath combination includes calculating a load shape profile including a plurality of layers of substantially equal volume. The calculated load shape profile is incrementally divided into cross-sectional slices at a first set of distance coordinates along a first axis. Each cross-sectional slice transects the plurality of layers. A sample includes a number of objects residing in solution. A sample chamber is loaded with the sample by incrementally dispensing the sample in a plurality of portions along a vertical axis divided into a second set of distance coordinates proportional to the first set of distance coordinates, where each portion has a volume proportional to the cross-sectional slice at the first distance coordinate nearest in value to the second distance coordinate.

Abstract: A method for measuring microscopic object velocities in fluid flow in a capillary tube including scanning a microscope focal plane through a fluid filled space for objects, where the scanning follows an interrupted repeating pattern having sub-patterns where the sub-patterns position the microscope focus plane beginning at a selected focus position at a first time and ending at the selected focus position at a later second time. A sensor registers images in image frames during the scanning. A first object image is registered in a first image frame at the selected focus position and a second object image is registered in a second image frame at the selected focus position. The object in the first object image and the second object image are identified as the same object. A processor determines a velocity for the identified object.

Abstract: A method of treating a malignancy in a human subject by analyzing pseudo-projection images of cells obtained from a sputum specimen obtained from a subject employs a biological specimen classifier that identifies cells from the sputum specimen as normal or abnormal. If abnormal cells are detected, then the abnormal cells are further classified as dysplastic or cancerous. If the cells are classified as dysplastic, then an immunomodulating agent is administered to the subject over a predetermined time period designed to achieve a therapeutic dosage.

Abstract: A cytological analysis test for 3D cell classification from a specimen. The method includes isolating and preserving a cell from the specimen and enriching the cell before embedding the enriched cell into an optical medium. The embedded cell is injected into a capillary tube where pressure is applied until the cell appears in a field of view of a pseudo-projection viewing subsystem to acquire a pseudo-projection image. The capillary tube rotates about a tube axis to provide a set of pseudo-projection images for each embedded cell which are reconstructed to produce a set of 3D cell reconstructions. Reference cells are classified and enumerated and a second cell classifier detects target cells. An adequacy classifier compares the number of reference cells against a threshold value of enumerated reference cells to determine specimen adequacy.

Abstract: A cytological analysis test for 3D cell classification from a specimen. The method includes isolating and preserving a cell from the specimen and enriching the cell before embedding the enriched cell into an optical medium. The embedded cell is injected into a capillary tube where pressure is applied until the cell appears in a field of view of a pseudo-projection viewing subsystem to acquire a pseudo-projection image. The capillary tube rotates about a tube axis to provide a set of pseudo-projection images for each embedded cell which are reconstructed to produce a set of 3D cell reconstructions. Reference cells are classified and enumerated and a second cell classifier detects target cells. An adequacy classifier compares the number of reference cells against a threshold value of enumerated reference cells to determine specimen adequacy.

Abstract: A method for 3D imaging of a biologic object (1) in an optical tomography system where a subcellular structure of a biological object (1) is labeled by introducing at least one nanoparticle-biomarker. The labeled biological object (1) is moved relatively to a microscope objective (62) to present varying angles of view and the labeled biological object (1) is illuminated with radiation having wavelengths between 150 nm and 900 nm. Radiation transmitted through the labeled biological object (1) and the microscope objective (62) within at least one wavelength bands is sensed with a color camera, or with a set of at least four monochrome cameras. A plurality of cross-sectional images of the biological object (1) from the sensed radiation is formed and reconstructed to make a 3D image of the labeled biological object (1).

Abstract: A method for 3D imaging of cells in an optical tomography system includes moving a biological object relatively to a microscope objective to present varying angles of view. The biological object is illuminated with radiation having a spectral bandwidth limited to wavelengths between 150 nm and 390 nm. Radiation transmitted through the biological object and the microscope objective is sensed with a camera from a plurality of differing view angles. A plurality of pseudoprojections of the biological object from the sensed radiation is formed and the plurality of pseudoprojections is reconstructed to form a 3D image of the cell.

Abstract: An object of interest is illuminated within the field of view of a microscope objective lens located to receive light passing through the object of interest. Light transmitted through the microscope objective lens impinges upon a variable power element. The variable power element is driven with respect to the microscope objective lens to scan through multiple focal planes in the object of interest. Light transmitted from the variable power element is sensed by a sensing element or array.

Abstract: A method for 3D imaging of cells in an optical tomography system includes moving a biological object relatively to a microscope objective to present varying angles of view. The biological object is illuminated with radiation having a spectral bandwidth limited to wavelengths between 150 nm and 390 nm. Radiation transmitted through the biological object and the microscope objective is sensed with a camera from a plurality of differing view angles. A plurality of pseudoprojections of the biological object from the sensed radiation is formed and the plurality of pseudoprojections is reconstructed to form a 3D image of the cell.