A micro-fluorometric scanner for the differential detection of cells; application of exfoliative cytology

Application of Artificial Intelligence in the Diagnosis, Treatment, and Prognostic Evaluation of Mediastinal Malignant Tumors

Artificial intelligence (AI), also known as machine intelligence, is widely utilized in the medical field, promoting medical advances. Malignant tumors are the critical focus of medical research and improvement of clinical diagnosis and treatment. Mediastinal malignancy is an important tumor that attracts increasing attention today due to the difficulties in treatment. Combined with artificial intelligence, challenges from drug discovery to survival improvement are constantly being overcome. This article reviews the progress of the use of AI in the diagnosis, treatment, and prognostic prospects of mediastinal malignant tumors based on current literature findings.

Artificial intelligence in cancer diagnostics and therapy: current perspectives

Artificial intelligence (AI) has found its way into every sphere of human life including the field of medicine. Detection of cancer might be AI's most altruistic and convoluted challenge to date in the field of medicine. Embedding AI into various aspects of cancer diagnostics would be of immense use in dealing with the tedious, repetitive, time-consuming job of lesion detection, remove opportunities for human error, and cut costs and time. This would be of great value in cancer screening programs. By using AI algorithms, data from digital images from radiology and pathology that are imperceptible to the human eye can be identified (radiomics and pathomics). Correlating radiomics and pathomics with clinico-demographic-therapy-morbidity-mortality profiles will lead to a greater understanding of cancers. Specific imaging phenotypes have been found to be associated with specific gene-determined molecular pathways involved in cancer pathogenesis (radiogenomics). All these developments would not only help to personalize oncologic practice but also lead to the development of new imaging biomarkers. AI algorithms in oncoimaging and oncopathology will broadly have the following uses: cancer screening (detection of lesions), characterization and grading of tumors, and clinical decision-making and prognostication. However, AI cannot be a foolproof panacea nor can it supplant the role of humans. It can however be a powerful and useful complement to human insights and deeper understanding. Multiple issues like standardization, validity, ethics, privacy, finances, legal liability, training, accreditation, etc., need to be overcome before the vast potential of AI in diagnostic oncology can be fully harnessed.

Screening for cervical cancer using automated analysis of PAP-smears

Cervical cancer is one of the most deadly and common forms of cancer among women if no action is taken to prevent it, yet it is preventable through a simple screening test, the so-called PAP-smear. This is the most effective cancer prevention measure developed so far. But the visual examination of the smears is time consuming and expensive and there have been numerous attempts at automating the analysis ever since the test was introduced more than 60 years ago. The first commercial systems for automated analysis of the cell samples appeared around the turn of the millennium but they have had limited impact on the screening costs. In this paper we examine the key issues that need to be addressed when an automated analysis system is developed and discuss how these challenges have been met over the years. The lessons learned may be useful in the efforts to create a cost-effective screening system that could make affordable screening for cervical cancer available for all women globally, thus preventing most of the quarter million annual unnecessary deaths still caused by this disease.

Debris removal in Pap-smear images

Since its introduction in the 1940s the Pap-smear test has helped reduce the incidence of cervical cancer dramatically in countries where regular screening is standard. The automation of this procedure is an open problem that has been ongoing for over fifty years without reaching satisfactory results. Existing systems are discouragingly expensive and yet they are only able to make a correct distinction between normal and abnormal samples in a fraction of cases. Therefore, they are limited to acting as support for the cytotechnicians as they perform their manual screening. The main reason for the current limitations is that the automated systems struggle to overcome the complexity of the cell structures. Samples are covered in artefacts such as blood cells, overlapping and folded cells, and bacteria, that hamper the segmentation processes and generate large number of suspicious objects. The classifiers designed to differentiate between normal cells and pre-cancerous cells produce unpredictable results when classifying artefacts. In this paper, we propose a sequential classification scheme focused on removing unwanted objects, debris, from an initial segmentation result, intended to be run before the actual normal/abnormal classifier. The method has been evaluated using three separate datasets obtained from cervical samples prepared using both the standard Pap-smear approach as well as the more recent liquid based cytology sample preparation technique. We show success in removing more than 99% of the debris without loosing more than around one percent of the epithelial cells detected by the segmentation process.

Technologies supporting analytical cytology: clinical, research and drug discovery applications

The tools and techniques developed for analytical cytology have become invaluable in expanding the development of cancer screening programs and biomarker discovery for personalized medicine. Detecting cellular, molecular, and functional changes of diseased tissue as defined by quantitative analytical methodologies has enhanced the field of medical diagnostics and prognostics. The focus of this review is to outline applications and recent technical advances in flow cytometry, laser scanning cytometry, image cytometry, and quantitative image analysis, as they pertain to clinical, research, and drug discovery applications.

Laser scanning confocal fluorescence microscopy: an overview

Innovative and important aspects of laser scanning confocal fluorescence imaging (LSCFI) are presented here as a general overview. We have described and discussed the technology of the procedure in some detail. We also report some of our original work with transmembranous uptake of 5S gamma-globulin on living human leukocytes as an example of one specific application of LSCFI. These original data and results are presented, as well as citing other uses and applications, to show the power of LSCFI technique. The article will hopefully be useful for those not familiar with the methodology and utility of laser scanning confocal fluorescence microscopy. Applications of LSCFI are very diverse, and there are new applications of this technology constantly being developed. Interest is growing in LSCFI, particularly in the pharmacologic and therapeutic areas, as demonstrated in this article.

High-speed 1-frame/ms scanning confocal microscope with a microlens and Nipkow disks

We have developed a high-speed confocal laser microscope. A microlens-array disk set in front of a pinhole-array disk improved optical efficiency more than ten times compared with that of conventional Nipkow confocal microscopy. This new microscope achieves a high-speed measurement of 1 frame/ms. We expect that it will be used for measuring biological and industrial active samples.

Current status of flow cytometry in cell and molecular biology

This review summarizes recent developments in flow cytometry (FC). It gives an overview of techniques currently available, in terms of apparatus and sample handling, a guide to evaluating applications, an overview of dyes and staining methods, an introduction to internet resources, and a broad listing of classic references and reviews in various fields of interest, as well as some recent interesting articles.

Apparatus for high-precision repetitive sequential optical measurement of living cells

A system is described which permits the repetitive spectroscopic measurement of individual cells within a population of many cells, while the location of each cell is preserved during various manipulations of the cells and/or their surrounding medium. The central mechanical feature of the system is the cell carrier, a matrix of apertures in which the cells become trapped. The detector electronics operate in a preset photon counting mode, permitting the measurement of low and high light intensities with the same degree of precision. The present instrument configuration is specifically designed for the accurate and precise measurement of the polarization of fluorescence of probes within living cells for application to routine performance of the Cercek SCM test for cancer. With modifications, the apparatus can be applied to a wide range of other clinical and research tasks.

Microscope-based multiparameter laser scanning cytometer yielding data comparable to flow cytometry data

We describe a computer-controlled 10 microns spot size laser scanning cytometer for making multiple wavelength fluorescence and scatter measurements of unconstrained cells on a surface such as a microscope slide. Designated areas of slides placed on a microscope stage are automatically scanned, and cells which generate above-threshold scatter or fluorescence values are found and individually processed to determine a list of measurement parameters. For each fluorescence or scatter measurement parameter, this list contains the integrated and peak values and bit pattern images of a scan window centered on the cell. The measurement time, the position of the cell on the slide, and two segmentation indices are also included in the list. Measurement time, cell position, and properties derived from the bit patterns are used interchangeably with integrated or peak measurement values as coordinates of multiproperty displays. Cells may be selected for counting, data display in various forms, or visual observation based on their meeting complex criteria among a chain of two property screens. Cells with selected properties may be viewed during an experiment or retrospectively. A designated specimen field may be repeatedly remeasured to perform kinetic cell studies. An argon ion and a HeNe- based laser instrument have been constructed and software has been written and evaluated with the specific goal of increasing the precision of propidium iodide-stained cellular DNA measurements. Some of the capabilities of the instrument and its current performance are described.

Automatic analysis of Papanicolaou smears by digital image processing

Papanicolaou smears from 378 patients were analyzed in a fully automated microscope system using an image analysis technique. The logic of the system subdivided the smears into "normal" (63%), "not possible to analyze in the machine" (17%) and "positive" (20%). The results have been compared with the conventional screening method available today taking into consideration the definition problems of a true diagnosis, cytopathological and histopathological consensus, reproducibility, sample-taking and interpretation mistakes, etc. As 37% (rejected and positive) of the smears in this particular study were analyzed visually after machine prescreening, it could be demonstrated that the false-negative rate among the remaining 63% of the specimens was significantly lower among the machine-screened smears when compared with visual screening if the results were correlated with histopathological consensus. The results clearly indicate that the technology required to build computerized microscope systems, which are able to automatically sort out at least two thirds of Papanicolaou smears is available today. The only limiting factor is the cost-benefit relationship.

Cesar: cervical smear analyser and reader. A new approach to evaluating cells in cytological preparations

Cesar presents an automated multiparameter approach to pattern recognition in the rapid detection of malignant cells from cervical and other cancers. Cells are cybernetically classified. They are collected into a container into which a nuclear stain may be incorporated and laid as a track on 35 mm. film using a disposable mapping pen device. The film track (Cytotrack) may be scanned using conventional optics and provision may be made for electronic sensing devices measuring a number of parameters, some of which are not normally used in conventional microscopy.

FLUORESCENCE MICROSCOPY IN COLONIC EXFOLIATIVE CYTOLOGY

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Ultraviolet Absorption in Epidermoid Cancer Cells

The "excessive functional activity" of some cancer cells first found by Caspersson has been observed in fixed, stained smears of cervical epidermoid carcinomas from four patients. Preliminary results suggest that there may be a characteristic difference between the absorption profiles of some epidermoid cancer cells and other cells found in cytological smears. It is our belief that with an appropriate electronic scanning system such cells can be detected by measurements of their absorptions at two different wavelengths. However, the effect on the absorptions of cells with abnormalities other than cancer, and whether every epidermoid carcinoma will contain such cells, must yet be determined.