RESUMO
Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp's number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to automate polyp detection and segmentation. However, the main issue is that they are not tested rigorously on a large multicentre purpose-built dataset, one reason being the lack of a comprehensive public dataset. As a result, the developed methods may not generalise to different population datasets. To this extent, we have curated a dataset from six unique centres incorporating more than 300 patients. The dataset includes both single frame and sequence data with 3762 annotated polyp labels with precise delineation of polyp boundaries verified by six senior gastroenterologists. To our knowledge, this is the most comprehensive detection and pixel-level segmentation dataset (referred to as PolypGen) curated by a team of computational scientists and expert gastroenterologists. The paper provides insight into data construction and annotation strategies, quality assurance, and technical validation.
Assuntos
Neoplasias do Colo , Pólipos do Colo , Humanos , Pólipos do Colo/diagnóstico , Colonoscopia/métodosRESUMO
This review discusses the rationale behind recommending immunopharmacological guidance of long-term therapies with anti-TNF-α specific biotherapies. "Arguments why therapeutic decision-making should not rely on clinical outcomes alone are presented. Central to this is that the use of theranostics (i.e., monitoring circulating levels of functional anti-TNF-α drugs and antidrug antibodies) would markedly improve treatment because therapies can be tailored to individual patients and provide more effective and economical long-term clinical benefits while minimising risk of side effects. Large-scale immunopharmacological knowledge of the pharmacokinetics of TNF-α biopharmaceuticals in individual patients would also help industry to develop more effective and safer TNF-α inhibitors" [1].