Steps of pathological diagnosis in the diagnostic process associated with adult liver transplantation

ПЕЧЕНИ ТРАНСПЛАНТАЦИЯПАТОМОРФОЛОГИЯТРАНСПЛАНТАЦИЯДИАГНОСТИЧЕСКИЕ МЕТОДЫ ХИРУРГИЧЕСКИ

Evaluation of chronic HCV infection in transplanted livers using a modified histological activity index

The majority of histopathological classifications of primary chronic viral hepatitis and recurrence of HCV infection in liver transplants is based on the histological activity index (HAI) introduced by Knodell et al in 1981; however, correlation between HAI and clinical/laboratory data is poor. Therefore, the aim of this study was to present a modification of HAI (mHAI) adapted to distinct features of graft infection, and to evaluate its usefulness in the description of disease activity

Post-transplant lymphoproliferative disorder in view of the new WHO classification: a more rational approach to a protean disease?

Post-transplant lymphoproliferative disorders (PTLDs) are serious, life-threatening complications of solid-organ transplantation (SOT) and bone marrow transplantation leading to a high mortality (30-60%). PTLD represents a heterogeneous group of lymphoproliferative diseases. They become clinically relevant because of the expansion of transplantation medicine together with the development of potent immunosuppressive drugs. Although the diagnostic morphological criteria of different forms of PTLD are commonly known, rapid and correct diagnosis is not always easy. Because of the limited number of clinical trials, a consensus is lacking on the optimal treatment of PTLD. This review focuses on incidence, risk factors, clinical picture of the disease and diagnostic tools including histopathology relating to the new classification introduced in 2008 by the World Health Organisation (WHO) and treatment of PTLD

Dataset of B-mode fatty liver ultrasound images

<p>The dataset used and described in: M. Byra, G. Styczynski, C. Szmigielski, P. Kalinowski. Ł. Michałowski4. R. Paluszkiewicz. B. Ziarkiewicz-Wróblewska, K. Zieniewicz. P. Sobieraj, A. Nowicki. Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images. International Journal of Computer Assisted Radiology and Surgery, 2018. DOI: 10.1007/s11548-018-1843-2. </p> <p>Please refer to the above work if you use the dataset in your research. </p> <p>Contact:<br> Michal Byra<br> Department of Ultrasound<br> Institute of Fundamental Technological Research<br> Polish Academy of Sciences, Warsaw, Poland<br> [email protected]<br> [email protected]</p