Systematic review: Histological remission in inflammatory bowel disease. Is ‘complete’ remission the new treatment paradigm? An IOIBD initiative

AbstractBackground and aimsAdvances in the medical management of inflammatory bowel disease (IBD) have altered treatment targets. Endoscopic mucosal healing is associated with better outcomes in IBD, though less is known about the significance of achieving histological remission. Our aim was to perform a systematic review to investigate whether histological or ‘complete’ remission constitutes a further therapeutic target in IBD.MethodsA bibliographic search was performed on the 1st of October 2013 and subsequently on the 1st of March 2014 of online databases (OVID SP MEDLINE, OVID EMBASE, National Pubmed Central Medline, Cochrane Library, ISI, conference abstracts), using MeSH terms and key words: (“inflammatory bowel diseases” OR “crohn disease” OR “ulcerative colitis” OR “colitis”) AND (“mucosal healing” OR “histological healing” OR “pathological healing” OR “histological scoring” OR “pathological scoring”).ResultsThe search returned 2951 articles. 120 articles were cited in the final analysis. There is no validated definition of histological remission in IBD. There are 22 different histological scoring systems for IBD, none of which are fully validated. Microscopic inflammation persists in 16–100% of cases of endoscopically quiescent disease. There is evidence that histological remission may predict risk of complications in ulcerative colitis beyond endoscopic mucosal healing, though data are scarce in Crohn's disease.ConclusionsHistological remission in IBD represents a target distinct from endoscopic mucosal healing, not yet routinely sought in clinical trials or practice. There remains a need for a standardized and validated histological scoring system and to confirm the prognostic value of histological remission as a treatment target in IBD

Image denoising using the lyapunov equation from non-uniform samples

Abstract. This paper addresses two problems: an image denoising problem assuming dense observations and an image reconstruction problem from sparse data. It shows that both problems can be solved by the Sylvester/Lyapunov algebraic equation. The Sylvester/Lyapunov equation has been extensively studied in Control Theory and it can be efficiently solved by well known numeric algorithms. This paper proposes the use of these equations in image processing and describes simple and fast algorithms for image denoising and reconstruction.