ABSTRACT
Background: Colon capsule endoscopy (CCE) has gained momentum as an alternative modality for the investigation of the lower gastrointestinal tract. Of the few challenges that remain, the comparison and - eventually - matching of polyps at different timestamps leads to the potential for double reporting and can contribute to false-positive findings and inaccuracies. With the impending artificial intelligence integration, the risk of double reporting the same polyp due to the lack of information on spatial orientation underscores the necessity for establishing criteria for polyp matching. Objectives: This RAND/University of California, Los Angeles (modified Delphi) process aims to identify the key factors or components used to match polyps within a CCE video. This involves exploring the attributes of each factor to create comprehensive polyp-matching criteria based on international expert consensus. Design: A systematic qualitative study using surveys. Methods: A panel of 11 international CCE experts convened to assess a survey comprised of 60 statements. Participants anonymously rated statement appropriateness on a 1-9 scale (1-3: inappropriate, 4-6: uncertain and 7-9: appropriate). Following a virtual group discussion of the Round 1 results, a Round 2 survey was developed and completed before the final analysis. Results: The factors that were agreed to be essential for polyp matching include (1) timestamp, (2) polyp localization, (3) polyp vascular pattern, (4) polyp size, (5) time interval of the polyp appearance between the green and yellow camera, (6) surrounding tissue, (7) polyp morphology and (8) polyp surface and contour. When five or more factors are satisfied, it was agreed that the comparing polyps are likely the same polyp. Conclusion: This study has established the first complete criteria for polyp matching in CCE. While it might not provide a definitive solution for matching difficult, small and common polyps, these criteria serve as a framework to guide and facilitate the process of polyp-matching.
Creating criteria and standards for matching polyps (abnormal growth in the bowels) on colon capsule video analysis: an international expert agreement using the RAND (modified Delphi process) process Background: Doctors often use colon capsule endoscopy (CCE), a high-tech capsule with two cameras, to record and check for diseases in the small and large bowels as the capsule travels through the intestines. One of the most common conditions in the large bowel is polyps, which are abnormal growths in the lining of the bowel. Comparing and matching polyps in the same video from the capsule can be tricky as they look very similar, leading to the possibility of incorrectly reporting the same polyp twice or more. This can lead to wrong results and inaccuracies. The literature did not have any criteria or standards for matching polyps in CCE before. Aim: Using the RAND/UCLA (modified Delphi) process, this study aims to identify the key factors or components used to match polyps within a CCE video. The goal is to explore each factor and create complete criteria for polyp matching based on the agreement from international experts. Method: A group of 11 international CCE experts came together to evaluate a survey with 60 statements. They anonymously rated each statement on a scale from 1 to 9 (1-3: inappropriate, 4-6: uncertain, and 7-9: appropriate). After discussing the Round 1 results virtually, a Round 2 survey with the same but revised questions was created and completed before the final analysis of their agreement. Results: The main factors for matching polyps are 1) the timing when the polyp was seen, 2) where it is in the bowel, 3) its blood vessel pattern, 4) size, 5) the timing of its appearance between cameras, 6) surrounding tissue features, 7) its shape, and 8) surface features. If five or more of these factors match, the compared polyps are likely the same. Conclusion: This study establishes the first complete criteria for matching polyps in CCE. While it may not provide a definitive solution for matching challenging and small polyps, these criteria serve as a guide to help and make the process of polyp matching easier.
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In the present issue of the World Journal of Hepatology, Ferrassi et al examine the problem of liver fibrosis staging in chronic hepatitis C. They identify novel biomarkers in an effort to predict accurate fibrosis staging with the aid of the metabolome of Hepatitis C patients. Overall I think Ferrassi et al took a different approach in identifying fibrosis biomarkers, by looking at the patients' metabolome. Their biomarkers clearly separate patients from controls. They can also separate out, patients with minimal fibrosis (F0-F1 stage) and patients with cirrhosis (F4 stage). Obviously, if these biomarkers were to be widely used, tests for all the important metabolites would need to be readily available for use in hospitals or outpatient setting and that may prove difficult and above all, costly. Nevertheless, this step could eventually lead to a metabolomic approach for novel biomarkers of Fibrosis. Obviously, it would need to be validated, but could represent a step towards the Holy Grail of Hepatology.
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Inflammatory bowel disease (IBD) is an umbrella term for Crohn's disease (CD) and ulcerative colitis (UC). In light of evolving epidemiology of CD, its clinical management is still complex and remains a challenge for contemporary physicians. With the advent of new diagnostic and treatment paradigms, there is a growing need for new biomarkers to guide decision-making, differential diagnosis, disease activity monitoring, as well as prognosis. However, both clinical and endoscopic scoring systems, widely utilized for disease monitoring and prognosis, have drawbacks and limitations. In recent years, biochemical peptides have become available for IBD monitoring and more frequently used as surrogate markers of gut inflammation. Emerging concepts that revolve around molecular, stem cell, epigenetic, microbial or metabolomic pathways associated with vascular and epithelial gut barrier could lead to development of new CD biomarkers. Measurement of cell-derived microvesicles (MVs) in the blood of IBD patients is another emerging concept helpful in future disease management. In this review, we discuss novel concepts of non-invasive biomarkers, which may become useful in monitoring of CD activity and prognosis. We discuss metabolomics as a new powerful tool for clinicians to guide differential IBD diagnosis. In the coming years, new developments of prognostic tools are expected, aiming for breakthroughs in the management of patients with CD.
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AIM: To identify plasma metabolites used as biomarkers in order to distinguish cirrhotics from controls and encephalopathics. METHODS: A clinical study involving stable cirrhotic patients with and without overt hepatic encephalopathy was designed. A control group of healthy volunteers was used. Plasma from those patients was analysed using (1)H - nuclear magnetic resonance spectroscopy. We used the Carr Purcell Meiboom Gill sequence to process the sample spectra at ambient probe temperature. We used a gated secondary irradiation field for water signal suppression. Samples were calibrated and referenced using the sodium trimethyl silyl propionate peak at 0.00 ppm. For each sample 128 transients (FID's) were acquired into 32 K complex data points over a spectral width of 6 KHz. 30 degree pulses were applied with an acquisition time of 4.0 s in order to achieve better resolution, followed by a recovery delay of 12 s, to allow for complete relaxation and recovery of the magnetisation. A metabolic profile was created for stable cirrhotic patients without signs of overt hepatic encephalopathy and encephalopathic patients as well as healthy controls. Stepwise discriminant analysis was then used and discriminant factors were created to differentiate between the three groups. RESULTS: Eighteen stabled cirrhotic patients, eighteen patients with overt hepatic encephalopathy and seventeen healthy volunteers were recruited. Patients with cirrhosis had significantly impaired ketone body metabolism, urea synthesis and gluconeogenesis. This was demonstrated by higher concentrations of acetoacetate (0.23 ± 0.02 vs 0.05 ± 0.00, P < 0.01), and b-hydroxybutarate (0.58 ± 0.14 vs 0.08 ± 0.00, P < 0.01), lower concentrations of glutamine (0.44 ± 0.08 vs 0.63 ± 0.03, P < 0.05), histidine (0.16 ± 0.01 vs 0.36 ± 0.04, P < 0.01) and arginine (0.08 ± 0.01 vs 0.14 ± 0.02, P < 0.03) and higher concentrations of glutamate (1.36 ± 0.25 vs 0.58 ± 0.04, P < 0.01), lactate (1.53 ± 0.11 vs 0.42 ± 0.05, P < 0.01), pyruvate (0.11 ± 0.02 vs 0.03 ± 0.00, P < 0.01) threonine (0.39 ± 0.02 vs 0.08 ± 0.01, P < 0.01) and aspartate (0.37 ± 0.03 vs 0.03 ± 0.01). A five metabolite signature by stepwise discriminant analysis could separate between controls and cirrhotic patients with an accuracy of 98%. In patients with encephalopathy we observed further derangement of ketone body metabolism, impaired production of glycerol and myoinositol, reversal of Fischer's ratio and impaired glutamine production as demonstrated by lower b-hydroxybutyrate (0.58 ± 0.14 vs 0.16 ± 0.02, P < 0.0002), higher acetoacetate (0.23 ± 0.02 vs 0.41 ± 0.16, P < 0.05), leucine (0.33 ± 0.02 vs 0.49 ± 0.05, P < 0.005) and isoleucine (0.12 ± 0.02 vs 0.27 ± 0.02, P < 0.0004) and lower glutamine (0.44 ± 0.08 vs 0.36 ± 0.04, P < 0.013), glycerol (0.53 ± 0.03 vs 0.19 ± 0.02, P < 0.000) and myoinositol (0.36 ± 0.04 vs 0.18 ± 0.02, P < 0.010) concentrations. A four metabolite signature by stepwise discriminant analysis could separate between encephalopathic and cirrhotic patients with an accuracy of 87%. CONCLUSION: Patients with cirrhosis and patients with hepatic encephalopathy exhibit distinct metabolic abnormalities and the use of metabonomics can select biomarkers for these diseases.
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BACKGROUND: The aim of this study was to develop a prognostic model of outcome for patients with paracetamol induced acute liver injury based on admission parameters METHODS: We used a cohort of 97 patients admitted to the Scottish Liver Transplant Unit between 1997 and 1998 to identify biochemical prognostic markers of outcome and thus create a prognostic model. Blood samples were taken on admission for analysis. The model was subsequently validated by testing it on a second cohort of 86 patients admitted between 1999 and 2000. RESULTS: The following were identified as independent variables of poor prognosis (death/ transplant); phenylalanine, pyruvate, alanine, acetate, calcium, haemoglobin and lactate. A prognostic model was then constructed by stepwise forward logistic regression analysis: (400xPyruvate mmols/L)+(50xPhenylalanine (mmols/L)-(4 x Hemoglobin (g/dL). A value of <16 had an accuracy of 93% in predicting death correctly. When applied to the validation cohort this model had a positive predictive value of 91%, a negative predictive value of 94%, a sensitivity of 91%, and a specificity of 94%. On the same population overall, the positive and negative predictive value of the King's criteria were 94% and 93% respectively, whereas their sensitivity and specificity were 88% and 96% respectively. CONCLUSIONS: Using admission characteristics our model is able to identify patients who die from paracetamol overdose fulminant hepatic failure as accurately as King's College criteria, but at a much earlier stage in their condition.
