Automated single-cell sorting system based on optical trapping

We provide a basis for automated single-cell sorting based on optical trapping and manipulation using human peripheral blood as a model system. A counterpropagating dual-beam optical-trapping configuration is shown theoretically and experimentally to be preferred due to a greater ability to manipulate cells in three dimensions. Theoretical analysis performed by simulating the propagation of rays through the region containing an erythrocyte (red blood cell) divided into numerous elements confirms experimental results showing that a trapped erythrocyte orients with its longest axis in the direction of propagation of the beam. The single-cell sorting system includes an image-processing system using thresholding, background subtraction, and edge-enhancement algorithms, which allows for the identification of single cells. Erythrocytes have been identified and manipulated into designated volumes using the automated dual-beam trap. Potential applications of automated single-cell sorting, including the incorporation of molecular biology techniques, are discussed.     

Application of a model based on fuzzy logic for evaluating nursing diagnostic accuracy of students

PurposeTo describe a model for assessing nursing diagnostic accuracy and its application to undergraduate students, comparing students’ performance according to the course year.MethodsThis model, based on the theory of fuzzy sets, guides a student through three steps: (a) the student must parameterize the model by establishing relationship values between defining characteristic/risk factors and nursing diagnoses; (b) presentation of a clinical case; (c) the student must define the presence of each defining characteristic/risk factors for the clinical case. Subsequently, the model computes the most plausible diagnoses by taking into account the values indicated by the student. This gives the student a performance score in comparison with parameters and diagnoses that were previously provided by nursing experts. These nursing experts collaborated with the construction of the model indicating the strength of the relationship between the concepts, meaning, they parameterized the model to compare the student's choice with the expert's choice (gold standard), thus generating performance scores for the student. The model was tested using three clinical cases presented to 38 students in their third and fourth years of the undergraduate nursing course.ResultsThird year students showed superior performance in identifying the presence of defining characteristic/risk factors, while fourth year students showed superior performance in the diagnoses by the model.ConclusionsThe Model for Evaluation of Diagnostic Accuracy Based on Fuzzy Logic applied in this study is feasible and can be used to evaluate students’ performance. In this regard, it will open a broad variety of applications for learning and nursing research.LimitationsDespite the ease in filling the printed questionnaires out, the number of steps and fields to fill in may explain the considerable number of questionnaires with incorrect or missing data. This was solved in the digital version of the questionnaire. In addition, in more complex cases, it is possible that an expert opinion can lead to a wrong decision due to the subjectivity of the diagnostic process.     

A diagnostic protocol for evaluating nonimmediate reactions to aminopenicillins

BACKGROUND: Maculopapular and urticarial rashes are nonimmediate manifestations common during aminopenicillin (AP) treatment, and the former often represent cell-mediated hypersensitivity. OBJECTIVES: We sought to determine the significance and incidence of skin test reactions to APs in adults reporting adverse reactions during therapy with these beta-lactams and, particularly, to evaluate the potential of patch tests, delayed-reading skin tests, and challenges in the diagnosis of nonimmediate reactions. METHODS: We used skin tests with penicilloylpolylysine, minor determinant mixture, benzylpenicillin, ampicillin, and amoxicillin, as well as patch tests with the last 3 drugs. We also performed in vitro assays for specific IgE and challenges with the suspect penicillin in subjects with nonimmediate reactions. RESULTS: Among the 144 patients reporting nonimmediate manifestations (mostly maculopapular rashes), delayed hypersensitivity was diagnosed in 62 on the basis of positive patch test and/or delayed intradermal test results and responses to challenges; negative reactions to challenges allowed us to reasonably exclude the possibility of allergy in 66 subjects, and the challenge confirmed that 1 patient had linear IgA bullous dermatosis. Definitive diagnoses could not be provided for the remaining 15 subjects, who had negative allergologic test results, because they did not consent to challenges. In 40 of 49 immediate reactors, a diagnosis of IgE-mediated hypersensitivity was made. CONCLUSIONS: Both patch and intradermal tests are useful in evaluating nonimmediate reactions to APs. Positive patch test and delayed intradermal responses together indicate delayed hypersensitivity. Intradermal testing appears to be more sensitive than patch testing, but the pattern of positive delayed intradermal test responses and negative patch test responses needs further investigation because of false-positive cases.     

On the process for evaluating Proposed new diagnostic EEG tests

Summary Assessment of new technology is an important part of the evolving art of medicine. For a variety of reasons, it is appropriate to restrict clinical applications of new technology to those tests which have been shown to be safe and effective. Efficacy of new EEG technology can be assessed through a variety of standard procedures, generally based on controlled, well organized clinical studies. Scientific reports using new EEG technology all too often fail to meet the standards traditionally expected for such clinical trials. Many such studies were never designed to be clinical trials. Misunderstandings occur when reports of scientific studies and informal clinical series become confused with formal clinical trials of efficacy. Based upon examples given during the 1991 ISBET meeting symposium on discriminant analysis, examples are discussed regarding how well individual kinds of presentations can be used to help clarify the generic clinical efficacy of the presented diagnostic tests.     

Computerized system for evaluating peripheral hemodynamics

Institute of Superhard Materials, Academy of Sciences of the Ukrainian SSR, Kiev. Translated from Meditsinskaya Tekhnika, No. 3, pp. 29–33, May–June, 1989.     

Imaging methods for evaluating brain function in man

Imaging of brain function and neurotransmission is an important bridge between basic and clinical research. Regional cerebral energy metabolism and blood flow are normally coupled to regional cerebral function. Positron tomography (PET) studies of cerebral glucose metabolism and blood flow, single photon tomography (SPECT) and MRI studies of cerebral perfusion, have been used to image cerebral development and aging in man. The sensitivity, temporal resolution, spatial resolution and lack of radiation have led to the widespread utilization of blood oxygen level dependent (BOLD) and MRI perfusion techniques. PET and SPECT methods for studying cerebral neurotransmission include studies of dopaminergic, serotonergic, cholinergic, opiate and GABAergic neurotransmission in man. Studies of cerebral neurotransmission in man have helped to delineate the mechanisms of action of antipsychotic and antidepressant drugs, the diagnosis and progression of Parkinson's disease, and to evaluate neuroprotective drugs. The strengths, limitations, and application of these modalities are reviewed. The application of these methods to cerebral development and aging are briefly discussed.     

Methods and recommendations for evaluating and reporting a new diagnostic test

No standardized guidelines exist for the biostatistical methods appropriate for studies evaluating diagnostic tests. Publication recommendations such as the STARD statement provide guidance for the analysis of data, but biostatistical advice is minimal and application is inconsistent. This article aims to provide a self-contained, accessible resource on the biostatistical aspects of study design and reporting for investigators. For all dichotomous diagnostic tests, estimates of sensitivity and specificity should be reported with confidence intervals. Power calculations are strongly recommended to ensure that investigators achieve desired levels of precision. In the absence of a gold standard reference test, the composite reference standard method is recommended for improving estimates of the sensitivity and specificity of the test under evaluation.     

Automated live cell screening system based on a 24-well-microplate with integrated micro fluidics

In research, pharmacologic drug-screening and medical diagnostics, the trend towards the utilization of functional assays using living cells is persisting. Research groups working with living cells are confronted with the problem, that common endpoint measurement methods are not able to map dynamic changes. With consideration of time as a further dimension, the dynamic and networked molecular processes of cells in culture can be monitored. These processes can be investigated by measuring several extracellular parameters. This paper describes a high-content system that provides real-time monitoring data of cell parameters (metabolic and morphological alterations), e.g., upon treatment with drug compounds. Accessible are acidification rates, the oxygen consumption and changes in adhesion forces within 24 cell cultures in parallel. Addressing the rising interest in biomedical and pharmacological high-content screening assays, a concept has been developed, which integrates multi-parametric sensor readout, automated imaging and probe handling into a single embedded platform. A life-maintenance system keeps important environmental parameters (gas, humidity, sterility, temperature) constant.     

An automated diagnostic system of polycystic ovary syndrome based on object growing

Objective

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that seriously affects women's health. The disorder is characterized by the formation of many follicles in the ovary. Currently the predominant diagnosis is to manually count the number of follicles, which may lead to inter-observer and intra-observer variability and low efficiency. A computer-aided PCOS diagnostic system may overcome these problems. However the methods reported in recently published literature are not very effective and often need human interaction. To overcome these problems, we propose an automated PCOS diagnostic system based on ultrasound images.

Methods and materials

The proposed system consists of two major functional blocks: preprocessing phase and follicle identification based on object growing. In the preprocessing phase, speckle noise in the input image is removed by an adaptive morphological filter, then contours of objects are extracted using an enhanced labeled watershed algorithm, and finally the region of interest is automatically selected. The object growing algorithm for follicle identification first computes a cost map to distinguish between the ovary and its external region and assigns each object a cost function based on the cost map. The object growing algorithm initially selects several objects that are likely to be follicles with very high probabilities and dynamically update the set of possible follicles based on their cost functions. The proposed method was applied to 31 real PCOS ultrasound images obtained from patients and its performance was compared with those of three other methods, including level set method, boundary vector field (BVF) method and the fuzzy support vector machine (FSVM) classifier.

Results

Based on the judgment of subject matter experts, the proposed diagnostic system achieved 89.4% recognition rate (RR) and 7.45% misidentification rate (MR) while the RR and MR of the level set method, the BVF method and the FSVM classifier are around 65.3% and 2.11%, 76.1% and 4.53%, and 84.0% and 16.3%, respectively. The proposed diagnostic system also achieved better performance than those reported in recently published literature.

Conclusion

The paper proposed an automated diagnostic system for the PCOS using ultrasound images, which consists of two major functional blocks: preprocessing phase and follicle identification based on object growing. Experimental results showed that the proposed system is very effective in follicle identification for PCOS diagnosis.     

A medical diagnostic tool based on radial basis function classifiers and evolutionary simulated annealing

ObjectiveThe profusion of data accumulating in the form of medical records could be of great help for developing medical decision support systems. The objective of this paper is to present a methodology for designing data-driven medical diagnostic tools, based on neural network classifiers.MethodsThe proposed approach adopts the radial basis function (RBF) neural network architecture and the non-symmetric fuzzy means (NSFM) training algorithm, which presents certain advantages including better approximation capabilities and shorter computational times. The novelty in this work consists of adapting the NSFM algorithm to train RBF classifiers, and suitably tailoring the evolutionary simulated annealing (ESA) technique to optimize the produced RBF models. The integration of ESA is critical as it helps the optimization procedure to escape from local minima, which could arise from the application of the traditional simulated annealing algorithm, and thus discover improved solutions. The resulting method is evaluated in nine different medical benchmark datasets, where the common objective is to train a suitable classifier. The evaluation includes a comparison with two different schemes for training classifiers, including a standard RBF training technique and support vector machines (SVMs). Accuracy% and the Matthews Correlation Coefficient (MCC) are used for comparing the performance of the three classifiers.ResultsResults show that the use of ESA helps to greatly improve the performance of the NSFM algorithm and provide satisfactory classification accuracy. In almost all benchmark datasets, the best solution found by the ESA-NSFM algorithm outperforms the results produced by the SFM algorithm and SVMs, considering either the accuracy% or the MCC criterion. Furthermore, in the majority of datasets, the average solution of the ESA-NSFM population is statistically significantly higher in terms of accuracy% and MCC at the 95% confidence level, compared to the global optimum solution that its rivals could achieve. As far as computational times are concerned, the proposed approach was found to be faster compared to SVMs.ConclusionsThe results of this study suggest that the ESA-NSFM algorithm can form the basis of a generic method for knowledge extraction from data originating from different kinds of medical records. Testing the proposed approach on a number of benchmark datasets, indicates that it provides increased diagnostic accuracy in comparison with two different classifier training methods.     

Diagnosis by the bit: a method for evaluating the diagnostic process

The extent to which a diagnostic observation or test contributes to a diagnosis is usually represented by a conditional, or Bayesian, probability. According to information theory, the contribution of a diagnostic observation can also be measured in bits of information. This offers a representation of the Bayes rule which may be useful in comparing and evaluating diagnostic sequences, since the diagnostic contributions of the various tests, expressed as bits of information, are additive, providing a simple and graphic representation of the diagnostic process.     

Development and testing of a PC-based system with menu-driven software for evaluating lung function in ICU patients

This paper describes a portable PC-based system for measuring respiratory system resistance (Rrs) and dynamic lung compliance (Cdyn) in intubated and mechanically ventilated patients. A pneumotachometer placed immediately proximal to the endotracheal tube measures flow, and a pressure catheter with its tip at the distal end of the endotracheal tube measures lateral airway pressure. The software is menu driven and allows the user to select from options including patient information display and entry, data collection, data editing, and waveform display. Up to ten consecutive breaths can be analyzed per run. Rrs and Cdyn are calculated on a breath by breath basis. Results are displayed to the screen, output to the system printer, and written to a user-specified ACSII data file. The system was tested by measuring resistance and compliance in a model of the lung, and results compared with those calculated from analog signals. It was then used to make measurements in intubated post-operative patients. Results were comparable to those previously reported in intubated ICU patients without primary lung disease. We conclude that our system provides reliable measurements of lung mechanics in the intubated patient, and represents an inexpensive and more versatile alternative to microprocessor-based ventilator systems currently being marketed.     

Machine vision system for diagnostic histopathology

In a machine vision system for the diagnostic assessment of histopathologic sections, human diagnostic knowledge and human ability to recognize components in a complex image need to be emulated. This is attempted by three integrated expert systems, supported by a multiprocessor computer with data-driven, dynamically reconfigurable architecture.