The role of artificial intelligence in prospective real-time histological prediction of colorectal lesions during colonoscopy: a systematic review and meta-analysis

Artificial intelligence (AI) presents a novel platform for improving disease diagnosis. However, the clinical utility of AI remains limited to discovery studies, with poor translation to clinical practice. Current data suggests that 26% of diminutive pre-malignant lesions and 3.5% of colorectal cancers are missed during colonoscopies. The primary aim of this study was to explore the role of artificial intelligence in real-time histological prediction of colorectal lesions during colonoscopy. A systematic search using MeSH headings relating to “AI”, “machine learning”, “computer-aided”, “colonoscopy”, and “colon/rectum/colorectal” identified 2290 studies. Thirteen studies reporting real-time analysis were included. A total of 2958 patients with 5908 colorectal lesions were included. A meta-analysis of six studies reporting sensitivities (95% CI) demonstrated that endoscopist diagnosis was superior to a computer-assisted detection platform, although no statistical significance was reached (p = 0.43). AI applications have shown encouraging results in differentiating neoplastic and non-neoplastic lesions using narrow-band imaging, white light imaging, and blue light imaging. Other modalities include autofluorescence imaging and elastic scattering microscopy. The current literature demonstrates that despite the promise of new endoscopic AI models, they remain inferior to expert endoscopist diagnosis. There is a need to focus developments on real-time histological predictions prior to clinical translation to demonstrate improved diagnostic capabilities and time efficiency

Evaluation of the oesophagogastric cancer associated microbiome: a systematic review and quality assessment

Objective. Oesophagogastric cancer is the fifth most common cancer worldwide, with poor survival outcomes. The role of bacteria in the pathogenesis of oesophagogastric cancer remains poorly understood. Design. A systematic search identified studies assessing the oesophagogastric cancer microbiome. The primary outcome was to identify bacterial enrichment specific to oesophagogastric cancer. Secondary outcomes included appraisal of the methodology, diagnostic performance of cancer bacteria and the relationship between oral and tissue microbiome. Results. A total of 9295 articles were identified, and 87 studies were selected for analysis. Five genera were enriched in gastric cancer: Lactobacillus, Streptococcus, Prevotella, Fusobacterium and Veillonella. No clear trends were observed in oesophageal adenocarcinoma. Streptococcus, Prevotella and Fusobacterium were abundant in oesophageal squamous cell carcinoma. Functional analysis supports the role of immune cells, localised inflammation and cancer-specific pathways mediating carcinogenesis. STORMS reporting assessment identified experimental deficiencies, considering batch effects and sources of contamination prevalent in low-biomass samples. Conclusions. Functional analysis of cancer pathways can infer tumorigenesis within the cancer–microbe–immune axis. There is evidence that study design, experimental protocols and analytical techniques could be improved to achieve more accurate and representative results. Whole-genome sequencing is recommended to identify key metabolic and functional capabilities of candidate bacteria biomarkers

Tumour length as an independent prognostic factor in resectable oesophageal carcinoma

INTRODUCTION: Oesophageal longitudinal tumour length has been investigated as a prognostic indicator for disease recurrence and overall survival in resectable oesophageal carcinoma. However, there is conflicting evidence regarding its use in clinical practice. This study aims to assess the prognostic significance of histological tumour length in potentially curative oesophageal resections for cancer. MATERIALS AND METHODS: Patients with locally advanced oesophageal carcinoma (squamous or adenocarcinoma) were identified in a single centre between July 2000 and December 2016. Patient demographics, tumour characteristics and survival outcomes were assimilated. Unifactorial and multifactorial analysis was performed to assess tumour length correlation with oncological outcomes. RESULTS: A total of 281 patients were included; 226 (80.4%) male and 55 (19.6%) female, with a median age of 66 years; 39 patients (13.9%) developed local recurrence and 104 (37%) distant metastases. Disease progression rate was 44.8% with a median progression-free survival of 21 months and median overall survival of 30 months. Median tumour length was 3 cm (interquartile range 2-4.5 cm). Multivariate analysis demonstrated longer tumours to be significantly associated with a higher rate of local recurrence (p=0.028), metastases (p=0.016), disease progression (p=0.001) and shorter progression-free survival (p=0.001). DISCUSSION: This study demonstrates histological tumour length as an independent prognostic factor for local recurrence, metastases, disease progression and progression-free survival. Further larger multicentre studies are required to define the role of longitudinal tumour length as a marker to identify patients who are at higher risk of poor oncological outcomes following surgery

Usability challenges in the use of medical devices in the home environment: a systematic review of literature

Background Home care medical devices are the fastest-growing segment of the medical device industry with associated safety and usability challenges. Human factor studies in the home environment present many difficulties resulting in limited knowledge of device use in this setting. This systematic review aims to identify usability challenges reported directly by end-users in the home environment. Methods A systematic review of the literature was conducted concentrating on studies involving end user reporting. Reported challenges were grouped into a) device-user, b) device use environment and c) device-user interface challenges. Results 3471 studies were screened and 202 underwent full-text review. Only twelve studies had direct involvement of end users. Multiple challenges were identified, with device-user interface problems being the most common. No effective, standardised method was found to collect patient/user feedback on usability challenges in the post-market stage, leading to a knowledge gap. Conclusions This study brought together multiple usability challenges reported by individual studies. Involvement of medical device end-users in usability studies is essential and their experiences must be effectively utilised in device design

Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma

BACKGROUND: Oesophageal adenocarcinoma poses a significant global health burden, yet the staging used to predict survival has limited ability to stratify patients by outcome. This study aimed to identify published clinical models that predict survival in oesophageal adenocarcinoma and to evaluate them using an independent international multicentre dataset. METHODS: A systematic literature search (title and abstract) using the Ovid Embase and MEDLINE databases (from 1947 to 11 July 2020) was performed. Inclusion criteria were studies that developed or validated a clinical prognostication model to predict either overall or disease-specific survival in patients with oesophageal adenocarcinoma undergoing surgical treatment with curative intent. Published models were validated using an independent dataset of 2450 patients who underwent oesophagectomy for oesophageal adenocarcinoma with curative intent. RESULTS: Seventeen articles were eligible for inclusion in the study. Eleven models were suitable for testing in the independent validation dataset and nine of these were able to stratify patients successfully into groups with significantly different survival outcomes. Area under the receiver operating characteristic curves for individual survival prediction models ranged from 0.658 to 0.705, suggesting poor-to-fair accuracy. CONCLUSION: This study highlights the need to concentrate on robust methodologies and improved, independent, validation, to increase the likelihood of clinical adoption of survival predictions models

The Biomarker Toolkit - an evidence-based guideline to predict cancer biomarker success and guide development

BACKGROUND: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation. METHODS: All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist. RESULTS: Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869-0.935, CRC: p>0.0001, 95.0% CI: 0.918-0.954). CONCLUSIONS: This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed

Predictors of abnormalities on magnetic resonance cholangiopancreatography: Is there a role when the biliary tree is normal on previous imaging?

Background There is limited evidence supporting the use of magnetic resonance cholangiopancreatography (MRCP) if the biliary tree is within normal limits on ultrasound scan (US) or computed tomography (CT). The aim of this study was to assess the role of MRCP in the absence of a dilated biliary system on index imaging. Methods A retrospective observational study of consecutive MRCP investigations (n=427) was performed between October 2010 and June 2013 at a single district general hospital. Data collected included patient demographics, clinical presentation, liver function tests (LFTs) and radiological presence of stones. Binary logistic regression and chi-square test were performed using SPSS v23. Results We included 358 cases, 65% female (n=231) and 35% male (n=127), with a mean age of 60 years. Of these, 63% presented with abdominal pain (n=225), with 20% having concurrent deranged LFTs (n=44) and 8% jaundice (n=18). Index imaging demonstrated a dilated biliary system >6 mm in 68% (n=245). Alkaline phosphatase (ALP) elevation was an independent positive predictor for an abnormal MRCP (P=0.003). Abnormal index imaging, ALP and clinical jaundice were all significantly associated with a positive MRCP (P<0.001, P=0.028, P=0.018). Conclusions It is efficacious to proceed to MRCP with abnormal findings on index imaging, clinical jaundice or elevated ALP. An MRCP scan should be strongly considered in the context of elevated ALP and normal US/CT biliary system

Salivary Volatile Organic Compound Analysis: An Optimised Methodology and Longitudinal Assessment Using Direct Injection Mass Spectrometry

Analysis of salivary volatile organic compounds (VOCs) may offer a novel noninvasive modality for disease detection. This study aims to optimise saliva headspace VOC analysis and assess longitudinal variation of salivary VOCs. Whole saliva from healthy participants was acquired in order to assess four methodological parameters: saliva collection, volume, dilution, and acidification. Saliva VOCs were analysed using untargeted proton transfer reaction time-of-flight mass spectrometry. Using the optimised method, five saliva samples collected over 3 weeks assessed the longitudinal VOC variability and reproducibility with targeted selected ion flow tube-mass spectrometry analysis. The method of saliva collection influenced VOC detection and was a source of contamination. An amount of 500 µL of whole saliva by passive drool yielded optimal VOCs. Longitudinal variation was negligible with target short chain fatty acids and aldehydes. However, certain compounds showed variability suggesting the influence of potential exogenous factors. Overall, there was an acceptable range of inter- and intraindividual VOC variability. Standardisation with morning sampling after a 6 h fast is recommended demonstrating minimal intersubject variability. Future studies should seek to establish salivary VOC levels in healthy and diseased populations