Defying Standard Criteria for Digital Replantation: A Case Series

INTRODUCTION: There is much controversy regarding the current indications and contraindications for digital replantation. PRESENTATION OF CASE: Three patients with absolute contraindications for digital replantation according to classical criteria are presented (Case 1: multilevel amputation of the hand and fingers; Case 3: avulsion of the thumb; Case 4: index amputation proximal to the insertion of the flexor digitorum superficialis). In addition a patient with a very distal digital amputation (Case 2), whose indication for replantation is controversial is also presented. In all cases, the patients were replanted and showed good functional and aesthetical results. DISCUSSION: Most authors advocate that the classical indications for replantation have been validated by experience, are predicated on the potential for long-term function, and should be followed in most if not all cases. However, some surgeons have been adopting a more liberal attitude with good results. CONCLUSION: The clinical cases presented in this paper suggest that the standard criteria for digital replantation should not be followed rigidly but instead should be regarded as a general guide.

Conexão Venosa Pulmonar Anómala. Estudo de Vinte e Quatro Crianças com Angiografia de Subtracção Digital

Objectivo: Avaliar a acuidade da angiografia de subtracção digital (ASD) no diagnóstico morfológico da conexão venosa pulmonar anómala (CVPA) em crianças. Concepção do estudo: Estudo prospectivo de doentes consecutivos entre Janeiro de 1989 e Julho de 1992. Tipo de Atendimento: Serviço de Cardiologia Pediátrica de um Hospital Central. População: Vinte e quatro doentes com CVPA. Métodos: Todos os doentes fizeram avaliação clínica e ecocardiográfica completa (modo M, bidimensional e Doppler) antes da realização do exame hemodinâmico. Em todos os casos se fizeram, de modo sistemático, injecções selectivas de contraste de baixa osmolaridade (0,5-1 ml/kg; dose total <6 mi/kg) no tronco e ramos da artéria pulmonar com registo em angiografia com subtracção digital (ASD). As imagens colhidas foram trabalhadas, selecciona das e armazenadas em video-cassetes e películas fotográficas (câmara multiformato). Resultados: Dezasseis doentes tinham CVPA total (CVPAT): onze à veia cava superior (VCS), dois ao seio coronário e três infradiafragmáticos (dois à veia cava inferior (VCI) e um à veia porta). Oito crianças tinham CVPA parcial (CVPAP): três à VCS, uma à aurícula direita (AD), três à VCI (síndroma da cimitarra) e num caso a CVPA era mista. Em oito doentes (seis com CVPAT e dois com CVPAP), a ASD contribuiu significativamente para o diagnóstico final tendo completado ou corrigido a informação obtida por ecocardiografia. Nos dezoito doentes submetidos a cirurgia cardíaca foi confirmado o diagnóstico obtido por ASD. Conclusões: A ASD é um método muito útil para o diagnóstico anatómico de doentes com CVPA. Na nossa experiência foi particularmente informativa a análise de registos em «video». A ASD está indicada nos casos em que os achados clínicos e ecocardiográficos não sejam típicos.

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.