Tumour classification is becoming increasingly defined by the underlying molecular changes in any given cancer. However, using current morphological and molecular methodologies many tumours defy characterization and classification.
This project proposes to build a robust, international, living library of rare PTs, with a focus on borderline and malignant grades, as well as PTs with malignant heterologous elements. Genomic and histological analyses will inform and refine future classifications.
The Evi-Pat project proposes to develop and evaluate an online training for oncologists and pathologists for the application of these principles to cancer related practice.
The project aims to map the evidence base of the WCT in order to facilitate evidence‐based decisions making in future editions and promote the application of higher research standards in the field.
This project will design and validate software using Artificial Intelligence (AI) to process medical images to create a medical image search engine. Whole slide images are digitized biopsy samples and quite large files usually called gigapixel images.
The project will promote the development of an EBP movement that will allow decisions in tumour classification to be informed by high-quality, relevant, and up-to date evidence synthesis.
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Create pathologist annotated datasets to support the validation of computational pathology. Proposal to support and then grow current “High-Throughput Truthing” (HTT) demonstration project.
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We are developing an easy-to-use, intuitive tool for editors, organizers, and any other interested scientists, to facilitate the selection of experts for scientific tasks and meetings.
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We will develop ISO standards for cancer research laboratory activities, starting with standards for histopathology laboratories. This will enhance the harmonization and comparability of research approaches.
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We have developed an internationally standardized reporting system of autopsies worldwide, and we expect this system to evolve over time to meet various needs. Initially this tool has been designed as a relational database, currently accessed through the IARC Blue Books Online Submission System (BBOSS), with the potential to generate PDF documents from the entries and to populate an open access portal for researchers worldwide.
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