Effect of small bowel transit time on accuracy of video capsule endoscopy in evaluating suspected small bowel bleeding

BACKGROUND Obscure small bowel bleeding is defined as gastrointestinal bleeding(GIB)that is unidentifiable with esophagogastroduodenoscopy and a colonoscopy with video capsule endoscopy(VCE)being the next gold standard step for evaluation.Small bowel transit time(SBTT)is a metric of a VCE study that is defined as the time the capsule takes to travel through the small intestine.AIM To determine if SBTT within the VCE study,correlates to overall detection of obscure small bowel bleeds.Furthermore,we attempted to identify any existing correlation between SBTT and re-bleeding after a negative VCE study.METHODS This is a single center retrospective analysis of VCE studies performed for overt and occult GIB at Einstein Medical Center,Philadelphia,between 2015 and 2019.Inclusion criteria primarily consisted of patients 18 years or older who had a VCE study done as part of the workup for a GIB.Patients with incomplete VCEs,poor preparation,or with less than 6 mo of follow up were excluded.A re-bleeding event was defined either as overt or occult within a 6-mo timeframe.Overt rebleeding was defined as Visible melena or hematochezia with>2 gm/dL drop in hemoglobin defined an overt re-bleeding event;whereas an unexplained>2 gm/dL drop in hemoglobin with no visible bleeding defined an occult re-bleed.RESULTS Results indicated that there was a significant and positive point biserial correlation between SBTT of 220 min and detection of a bleeding focus with a statistically significant p value of 0.008.However,the area under the curve was negligible when trying to identify a threshold time for SBTT to discriminate between risk of re-bleeding events after a negative VCE.CONCLUSION In terms of SBTT and association with accuracy of VCE finding a bleeding focus,220 min was found to be adequate transit time to accurately find a bleeding focus,when present.It was found that no threshold SBTT could be identified to help predict re-bleeding after a negative VCE.

Artificial intelligence as a means to improve recognition of gastrointestinal angiodysplasia in video capsule endoscopy

Gastrointestinal angiodysplasia(GIAD)is defined as the pathological process where blood vessels,typically venules and capillaries,become engorged,tortuous and thin walled–which then form arteriovenous connections within the mucosal and submucosal layers of the gastrointestinal tract.GIADs are a significant cause of gastrointestinal bleeding and are the main cause for suspected small bowel bleeding.To make the diagnosis,gastroenterologists rely on the use of video capsule endoscopy(VCE)to“target”GIAD.However,the use of VCE can be cumbersome secondary to reader fatigue,suboptimal preparation,and difficulty in distinguishing images.The human eye is imperfect.The same capsule study read by two different readers are noted to have miss rates like other forms of endoscopy.Artificial intelligence(AI)has been a means to bridge the gap between human imperfection and recognition of GIAD.The use of AI in VCE have shown that detection has improved,however the other burdens and limitations still need to be addressed.The use of AI for the diagnosis of GIAD shows promise and the changes needed to enhance the current practice of VCE are near.

A Wireless Video Capsule Endoscopy System: Design and Realization

Wireless capsule endoscopy(CE), an image inspection technique, has been an important advancement in the diagnosis of gastrointestinal(GI) tract diseases. A video capsule endoscopy(VCE) system is analyzed in this study. A complementary metal oxide semiconductor(CMOS) analog image sensor is adopted, and other illumination, communication and energy modules are designed for functional realization. Measuring only φ11 mm ×25 mm, the VCE has a total power consumption of 52.5 m W, which enables it to work continuously for 8 h. The in vivo experiment on a living pig indicates that a clear video with high frame rate of 30 f/s can be obtained.

Understanding deep learning in capsule endoscopy: Can artificial intelligence enhance clinical practice?

Wireless capsule endoscopy(WCE)enables physicians to examine the gastrointestinal tract by transmitting images wirelessly from a disposable capsule to a data recorder.Although WCE is the least invasive endoscopy technique for diagnosing gastrointestinal disorders,interpreting a WCE study requires significant time effort and training.Analysis of images by artificial intelligence,through advances such as machine or deep learning,has been increasingly applied to medical imaging.There has been substantial interest in using deep learning to detect various gastrointestinal disorders based on WCE images.This article discusses basic knowledge of deep learning,applications of deep learning in WCE,and the implementation of deep learning model in a clinical setting.We anticipate continued research investigating the use of deep learning in interpreting WCE studies to generate predictive algorithms and aid in the diagnosis of gastrointestinal disorders.

Prediction models for recurrence in patients with small bowel bleeding

Obscure gastrointestinal bleeding(OGIB)has traditionally been defined as gastrointestinal bleeding whose source remains unidentified after bidirectional endoscopy.OGIB can present as overt bleeding or occult bleeding,and small bowel lesions are the most common causes.The small bowel can be evaluated using capsule endoscopy,device-assisted enteroscopy,computed tomography enterography,or magnetic resonance enterography.Once the cause of smallbowel bleeding is identified and targeted therapeutic intervention is completed,the patient can be managed with routine visits.However,diagnostic tests may produce negative results,and some patients with small bowel bleeding,regardless of diagnostic findings,may experience rebleeding.Predicting those at risk of rebleeding can help clinicians form individualized surveillance plans.Several studies have identified different factors associated with rebleeding,and a limited number of studies have attempted to create prediction models for recurrence.This article describes prediction models developed so far for identifying patients with OGIB who are at greater risk of rebleeding.These models may aid clinicians in forming tailored patient management and surveillance.

Double balloon enteroscopy in children:Diagnosis,treatment,and safety

AIM:To assess the feasibility and utility of double balloon enteroscopy(DBE)in the management of small bowel diseases in children. METHODS:Fourteen patients(10 males)with a median age of 12.9 years(range 8.1-16.7)underwent DBE; 5 for Peutz-Jeghers syndrome(PJ syndrome),2 for chronic abdominal pain,4 for obscure gastrointestinal (GI)bleeding,2 with angiomatous malformations(1 blue rubber bleb nevus syndrome)having persistent GI bleeding,and 1 with Cowden's syndrome with multiple polyps and previous intussusception.Eleven procedures were performed under general anesthesia and 3 with deep sedation. RESULTS:The entire small bowel was examined in 6 patients,and a length between 200 cm and 320 cm distal to pylorus in the remaining 8.Seven patients had both antegrade(trans-oral)and retrograde(transanal and via ileostomy)examinations.One patient underwent DBE with planned laparoscopic assistance.The remaining 6 had trans-oral examination only.The median examination time was 118 min(range 95-195). No complications were encountered.Polyps were detected and successfully removed in all 5 patients with PJ syndrome,in a patient with tubulo-villous adenoma of the duodenum,in a patient with significant anemia and occult bleeding,and in a patient with Cowden's syndrome.A diagnosis was made in a patient with multiple angiomata not amenable to endotherapy,and in 1 with a discrete angioma which was treated with argon plasma coagulation.The source of bleeding was identified in a further patient with varices.DBE was normal or revealed minor mucosal friability in the remaining 3 patients.Hence a diagnostic yield of 11/14 with therapeutic success in 9/14 was achieved. CONCLUSION:Double balloon enteroscopy can be a useful diagnostic and therapeutic tool for small bowel disease in children,allowing endo-therapeutic intervention beyond the reach of the conventional endoscope.

Treatment of gastrointestinal bleeding in left ventricular assist devices:A comprehensive review

Left ventricular assist devices(LVAD)are increasingly become common as life prolonging therapy in patients with advanced heart failure.Current devices are now used as definitive treatment in some patients given the improved durability of continuous flow pumps.Unfortunately,continuous flow LVADs are fraught with complications such as gastrointestinal(GI)bleeding that are primarily attributed to the formation of arteriovenous malformations.With frequent GI bleeding,antiplatelet and anticoagulation therapies are usually discontinued increasing the risk of life-threatening events.Small bowel bleeds account for 15%as the source and patients often undergo multiple endoscopic procedures.Treatment strategies include resuscitative measures and endoscopic therapies.Medical treatment is with octreotide.Novel treatment options include thalidomide,angiotensin converting enzyme inhibitors/angiotensinⅡreceptor blockers,estrogen-based hormonal therapies,doxycycline,desmopressin and bevacizumab.Current research has explored the mechanism of frequent GI bleeds in this population,including destruction of von Willebrand factor,upregulation of tissue factor,vascular endothelial growth factor,tumor necrosis factor-α,tumor growth factor-β,and angiopoetin-2,and downregulation of angiopoetin-1.In addition,healthcare resource utilization is only increasing in this patient population with higher admissions,readmissions,blood product utilization,and endoscopy.While some of the novel endoscopic and medical therapies for LVAD bleeds are still in their development stages,these tools will yet be crucial as the number of LVAD placements will likely only increase in the coming years.

Comment on “Artificial intelligence in gastroenterology: A state-ofthe- art review”

Colon capsule endoscopy(CCE)was introduced nearly two decades ago.Initially,it was limited by poor image quality and short battery time,but due to technical improvements,it has become an equal diagnostic alternative to optical colonoscopy(OC).Hastened by the coronavirus disease 2019 pandemic,CCE has been introduced in clinical practice to relieve overburdened endoscopy units and move investigations to out-patient clinics.A wider adoption of CCE would be bolstered by positive patient experience,as it offers a diagnostic investigation that is not inferior to other modalities.The shortcomings of CCE include its inability to differentiate adenomatous polyps from hyperplastic polyps.Solving this issue would improve the stratification of patients for polyp removal.Artificial intelligence(AI)has shown promising results in polyp detection and characterization to minimize incomplete CCEs and avoid needless examinations.Onboard AI appears to be a needed application to enable near-real-time decision-making in order to diminish patient waiting times and avoid superfluous subsequent OCs.With this letter,we discuss the potential and role of AI in CCE as a diagnostic tool for the large bowel.

Optimization Design and Experiment of the Radio Frequency Transmission Utilized in Video Capsule Endoscope

In view of fuzzy and unstable images received in video capsule endoscopy, and the poor communication effect, an improved radio frequency(RF) transmission circuit module with low power consumption and helix antenna is designed to improve the performance of video transmission and to extend the working time of the capsule. Simulation and analysis of the circuits and antenna with HFSS12 and ADS2011 software are highlighted.Video capsule endoscope prototypes are made and evaluated to verify the feasibility of the proposed design. In vitro tests and animal experiments show that the results of the antenna tests basically meet the simulation, and the power consumption of RF circuit is 15.9 mV. The video capsule endoscope works well with the receiver with multiple receiving antennas, and the working time is more than 9 h. It can realize the wireless transmission of the video data, and images received are clear and stable in comparison with the previous designs.