C4d Presence in Kidney Allograft Biopsy: Sensitivity and Specifity of Immunoperoxidase vs Immunofluorescence

OBJECTIVES: Evaluate the sensitivity/specificity of immunoperoxidase method in comparison with the standard immunofluorescence. MATERIAL AND METHODS: Retrospective review of 87 biopsies made for allograft dysfunction. Immunofluorescence (IF) was performed in frozen allograft biopsies using monoclonal antibody anti-C4d from Quidel®. The indirect immunoperoxidase (IP) technique was performed in paraffin-embebbed tissue with polyclonal antiserum from Serotec®. Biopsies were independently evaluated by two nephropathologist according Banff 2007 classification. RESULTS: By IF, peritubular C4d deposition were detected in 60 biopsies and absent in 27 biopsies. The evaluation of biopsy by IP was less precise due to the presence of background and unspecific staining. We find 13.8% (12/87) of false negative and Banff classification concordance in 79.3% (69/87) of cases (table1). The ROC curve study reveal a specificity of 100% and sensitivity of 80.0 % of IP method in relation to the gold standard (area under curve:0.900; 95% Confidence interval :0.817-0.954; p=0.0001). Banff Classification C4d Cases Immunofluorescence Immunoperoxidase n =87 Diffuse Negative 3 (3.4%) Focal Negative 9 (10.3%) Negative Negative 27 (31.0%) Diffuse Diffuse 33 (37.9%) Focal Focal 9 (10.3%) Diffuse Focal 6 (6.9%) CONCLUSION: The IP method presents a good specificity, but lesser sensitivity to C4d detection in allograft dysfunction. The evaluation is more difficult, requiring more experience of the observer than IF method. If frozen tissue is unavailable, the use of IP for C4d detection is acceptable.

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Diagnosic Classification: Results from a Clinical Experience of Three Years with DC: 0–3

Infancy and early childhood are characterized by a dynamic and ever changing process. Since the beginning of their clinical work at the Infancy Unit, the authors were concerned with individual assessment and the questions about the role played by parents as well as by babies in pathology and intervention.In this article, the authors begin with a description of the path that led them to the selection of DC 0–3 as a diagnostic classification system and how this has been instrumental in helping them to better define infant psychopathology and guide them in treatment orientations. Next, they present the results of the applicationof Axis I and II of DC: 0–3 in their clinical population in the years 1997, 1998, and 1999. The objectives of this study were to learn more about the distribution of mental disorders in a clinical population up tofour years of age. The authors attempted to separate infants at risk for developing psychic disorders from those presenting current psychopathology as well as the possible influence of demographic features on this distribution, to define a target population and design adapted therapeutic measures. The identification of these objectives provides the rationale for the use of a diagnostic tool, like DC: 0–3, which is essential to plan clinical activity, to evaluate therapeutic efficacy, and to develop specific programs.