Alain Venot

Automated Correction of Patient Motion and Gray Values Prior to Subtraction in Digitized Angiography

This paper deals with an automated method for the simultaneous correction of patient motion and gray values prior to subtraction in digitized angiography. The algorithm consists of maximizing the deterministic sign change (DSC) criterion with respect to three registration parameters (two translational shifts and one constant value added to the pixel values of the image with contrast medium). This method is proved to be very efficient to correct for patient motion artifacts and is computationally cheap. Its main advantage is to permit the use of regions of interest which include vascular structures for the registration procedure. This method can be proposed for a routine use on every commercial digitized angiographic system.

Assessment of healing kinetics through true color image processing

A quantitative method of skin healing assessment using true color image processing is presented. The method was developed during a clinical trial using healthy volunteers, the goal of which was to study a drug for accelerating healing. Photographic images of the skin were sequentially acquired between day 1 and day 12 after pure painless epidermal wounds. The images were digitized in controlled conditions using a color video camera connected to a computer system. A color threshold based segmentation was developed to provide an operator-independent delineation of the wound. Two healing indexes were built measuring, the wound area and the wound color. The method was implemented in a software system allowing a fully automated determination of the healing indexes. The method provides a new quantitative global assessment of healing kinetics. It is noninvasive and well suited for multicentric clinical trials.

An iconic language for the graphical representation of medical concepts

BackgroundMany medication errors are encountered in drug prescriptions, which would not occur if practitioners could remember the drug properties. They can refer to drug monographs to find these properties, however drug monographs are long and tedious to read during consultation. We propose a two-step approach for facilitating access to drug monographs. The first step, presented here, is the design of a graphical language, called VCM.MethodsThe VCM graphical language was designed using a small number of graphical primitives and combinatory rules. VCM was evaluated over 11 volunteer general practitioners to assess if the language is easy to learn, to understand and to use. Evaluators were asked to register their VCM training time, to indicate the meaning of VCM icons and sentences, and to answer clinical questions related to randomly generated drug monograph-like documents, supplied in text or VCM format.ResultsVCM can represent the various signs, diseases, physiological states, life habits, drugs and tests described in drug monographs. Grammatical rules make it possible to generate many icons by combining a small number of primitives and reusing simple icons to build more complex ones. Icons can be organized into simple sentences to express drug recommendations. Evaluation showed that VCM was learnt in 2 to 7 hours, that physicians understood 89% of the tested VCM icons, and that they answered correctly to 94% of questions using VCM (versus 88% using text, p = 0.003) and 1.8 times faster (p < 0.001).ConclusionVCM can be learnt in a few hours and appears to be easy to read. It can now be used in a second step: the design of graphical interfaces facilitating access to drug monographs. It could also be used for broader applications, including the design of interfaces for consulting other types of medical document or medical data, or, very simply, to enrich medical texts.

Predicting mortality in adult burned patients: Methodological aspects of the construction and validation of a composite ratio scale

This article describes the methodology of construction and validation of a composite measurement scale (CMS) to predict the risk of death for burned patients, with severity of burn considered as a continuous phenomenon. Three large data sets of burned patients hospitalized in France were analyzed. Logistic regression was used to construct a prognostic model, based on age and initial evaluation of total body surface area burned. The resulting model appears to be a valid clinical tool for predicting the risk of death. In addition, the devised CMS has satisfactory content and construct validity and reliability, and provides a high measurement level (logistic ratio level). Moreover, its simplicity of use (the score is integer based) is appropriate for the daily activities of burn unit physicians, emergency medical technicians, and public health professionals.

Structured Representation of the Pharmacodynamics Section of the Summary of Product Characteristics for Antibiotics: Application for Automated Extraction and Visualization of Their Antimicrobial Activity Spectra

OBJECTIVE The aim of this study was to construct automatically a knowledge base concerning the pharmacodynamic properties of antibiotics and a visualization tool. DESIGN The authors studied the various guidelines used to write the pharmacodynamics section of the Summary of Product Characteristics (SPC) for antibiotics and constructed a conceptual model of the information. Particular words, syntagms, and punctuation elements were marked in the SPC texts, and automatic extraction was then used to build a knowledge base. This base was used to create dynamic HTML tables displaying the activity spectra of the antibiotics. MEASUREMENTS The authors analyzed the performances of automatic extraction (recall and precision). RESULTS The conceptual pharmacodynamics model dealt with antibiotics, pathogens, susceptibility tests, and the prevalence of resistance. Automatic extraction had a recall rate of 97.9% and a precision of 96.2%. The tool displaying antibiotic spectra and resistance prevalences used color codes to identify differences in susceptibility. CONCLUSION This tool can provide an overview of the prevalence of resistance as expressed in SPC in primary care settings. Its potential impact should be evaluated.

OPTIMAL DISCRIMINANT ANALYSIS FOR ORDINAL RESPONSES

Optimal classification formulation is adapted to the context of discrimination when the response is ordinal. The resulting method, optimal discriminant analysis for ordinal responses (ODAO), is presented and compared with two reference discrimination techniques used in this context (proportional-odds ordinal logistic regression and normal discrimination) using a study of prognosis following burn injuries and simulated data. The ODAO method clearly outperforms both reference methods in terms of classification accuracy (in training and validation samples), robustness to outliers, simplicity of use and applicability in clinical settings. ODAO is a promising method for improving classification performance in discrimination with ordinal responses and merits further investigation.

Designing concept maps for a precise and objective description of pharmaceutical innovations

BackgroundWhen a new drug is launched onto the market, information about the new manufactured product is contained in its monograph and evaluation report published by national drug agencies. Health professionals need to be able to determine rapidly and easily whether the new manufactured product is potentially useful for their practice. There is therefore a need to identify the best way to group together and visualize the main items of information describing the nature and potential impact of the new drug. The objective of this study was to identify these items of information and to bring them together in a model that could serve as the standard for presenting the main features of new manufactured product.MethodsWe developed a preliminary conceptual model of pharmaceutical innovations, based on the knowledge of the authors. We then refined this model, using a random sample of 40 new manufactured drugs recently approved by the national drug regulatory authorities in France and covering a broad spectrum of innovations and therapeutic areas. Finally, we used another sample of 20 new manufactured drugs to determine whether the model was sufficiently comprehensive.ResultsThe results of our modeling led to three sub models described as conceptual maps representingi) the medical context for use of the new drug (indications, type of effect, therapeutical arsenal for the same indications), ii) the nature of the novelty of the new drug (new molecule, new mechanism of action, new combination, new dosage, etc.), and iii) the impact of the drug in terms of efficacy, safety and ease of use, compared with other drugs with the same indications.ConclusionsOur model can help to standardize information about new drugs released onto the market. It is potentially useful to the pharmaceutical industry, medical journals, editors of drug databases and medical software, and national or international drug regulation agencies, as a means of describing the main properties of new pharmaceutical products. It could also used as a guide for the writing of comprehensive and objective texts summarizing the nature and interest of new manufactured product.

Theoretical properties of sign change criteria for robust off-line estimation

Abstract Asymptotic properties of two off-line estimators based on sign change criteria are considered. Under rather mild conditions, the expectation of the first criterion is shown to reach a (local) maximum for the true value of the parameters. Conditions under which the estimator associated with the second criterion converges to the true value of the parameters are exhibited. The robustness of both estimators to severe outliers is evidenced.

Design and evaluation of a software for the objective and easy-to-read presentation of new drug properties to physicians

BackgroundWhen new pharmaceutical products appear on the market, physicians need to know whether they are likely to be useful in their practices. Physicians currently obtain most of their information about the market release and properties of new drugs from pharmaceutical industry representatives. However, the official information contained in the summary of product characteristics (SPCs) and evaluation reports from health agencies, provide a more complete view of the potential value of new drugs, although they can be long and difficult to read. The main objective of this work was to design a prototype computer program to facilitate the objective appraisal of the potential value of a new pharmaceutical product by physicians. This prototype is based on the modeling of pharmaceutical innovations described in a previous paper.MethodsThe interface was designed to allow physicians to develop a rapid understanding of the value of a new drug for their practices. We selected five new pharmaceutical products, to illustrate the function of this prototype. We considered only the texts supplied by national or international drug agencies at the time of market release. The perceived usability of the prototype was evaluated qualitatively, except for the System Usability Scale (SUS) score evaluation, by 10 physicians differing in age and medical background.ResultsThe display is based on the various axes of the conceptual model of pharmaceutical innovations. The user can select three levels of detail when consulting this information (highly synthetic, synthetic and detailed). Tables provide a comparison of the properties of the new pharmaceutical product with those of existing drugs, if available for the same indication, in terms of efficacy, safety and ease of use.The interface was highly appreciated by evaluators, who found it easy to understand and suggested no other additions of important, internationally valid information. The mean System Usability Scale score for the 10 physicians was 82, corresponding to a “good” user interface.ConclusionsThis work led us to propose the selection, grouping, and mode of presentation for various types of knowledge on pharmaceutical innovations in a way that was appreciated by evaluators. It provides physicians with readily accessible objective information about new drugs.

Using visual analytics for presenting comparative information on new drugs

OBJECTIVE When a new drug is marketed, physicians must decide whether they will consider it for their future practice. However, information about new drugs can be biased or hard to find. In this work, our objective was to study whether visual analytics could be used for comparing drug properties such as contraindications and adverse effects, and whether this visual comparison can help physicians to forge their own well-founded opinions about a new drug. MATERIALS AND METHODS First, an ontology for comparative drug information was designed, based on the expectations expressed during focus groups comprised of physicians. Second, a prototype of a visual drug comparator website was developed. It implements several visualization methods: rainbow boxes (a new technique for overlapping set visualization), dynamic tables, bar charts and icons. Third, the website was evaluated by 22 GPs for four new drugs. We recorded the general satisfaction, the physicians decision whether to consider the new drug for future prescription, both before and after consulting the website, and their arguments to justify their choice. RESULTS The prototype website permits the visual comparison of up to 10 drugs, including efficacy, contraindications, interactions, adverse effects, prices, dosage regimens,…All physicians found that the website allowed them to forge a well-founded opinion on the four new drugs. The physicians changed their decision about using a new drug in their future practice in 29 cases (out of 88) after consulting the website. DISCUSSION AND CONCLUSION Visual analytics is a promising approach for presenting drug information and for comparing drugs. The visual comparison of drug properties allows physicians to forge their opinions on drugs. Since drug properties are available in reference texts, reviewed by public health agencies, it could contribute to the independent of drug information.