Project description:In a cluster-randomized study compare if feedback from two computerized feedback systems doing a colonoscopy (CoPS and CoRS) can improve the adenoma detection rate and decrease patient discomfort.
Project description:Colorectal cancer screening program has been proven to reduce colorectal cancer (CRC) mortality and is cost-effective. It has been adopted by most countries in the world, and colonoscopy is regarded as the most accurate test for detecting colorectal neoplasm. After screenees underwent colonoscopy, most endoscopists do not routinely explain the preliminary optical diagnosis to the subjects before they going home, which may cause unnecessary anxiety and may reduce the quality of life of the subjects before acquiring the final results. In recent years, endoscopic optical diagnostic technology has been validated by meta-analysis studies as an excellent tool to predict the histology of colorectal polyps and to differentiate the invasion depth of colorectal cancer. The real time feature of endoscopic optical diagnosis allows endoscopists to explain the preliminary results confidently to the subjects immediately after colonoscopy, which is expected to reduce the anxiety of the subjects before they acquired the final results and improve their quality of life. We designed a randomized controlled trial to validate whether real-time endoscopic optical diagnosis could decrease the anxiety burden and improve the quality of life for colorectal-cancer screenees after colonoscopy.
Project description:The accuracy of endoscopic optical diagnosis for colorectal polyps has been approaching histological diagnosis after implementation of image enhancement endoscopic technologies. The real-time notification of possible nature of resected polyp after colonoscopy is expected to reduce the anxiety and depression level of the patients before the availability of histological diagnosis and improve their quality of life. We designed and conducted a randomized control trial to confirm this hypothesis.
Project description:This is a prospective, multicenter, randomized Trial to assess the safety and efficacy of the Olympus Endoscopy Computer-Aided Detection (CADe) system, OIP-1, in the detection of colorectal neoplasia’s during real-time colonoscopy. The aim of this system is to improve physician performance in the detection of potential mucosal abnormalities during colonoscopy performed for primary Colorectal Cancer screening or postpolypectomy surveillance.
Project description:Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Artificial intelligence has great potential in image analysis in gastrointestinal endoscopy. Aim of this study is to investigate the real-time diagnostic performance of AI4CRP for the classification of diminutive colorectal polyps, and to compare it with the real-time diagnostic performance of commercially available CADx systems.
Project description:In mass spectrometry-based lipidomics complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MSn) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level levels. Structural resolution of reported lipid identifications is routinely enhanced by integrating both positive and negative-mode analyses, requiring two separate runs or polarity switching during a single analysis. MS3+ can further elucidate lipid structure, but the lengthened MS duty cycle can negatively impact analysis depth. Recently functionality has been introduced on several Orbitrap-Tribrid mass spectrometry platforms to identify eluting molecular species on-the-fly. These real-time identifications can be leveraged to trigger downstream tandem MS to improve structural characterization of a specific compound with lessened impacts on analysis depth. Here we describe a novel lipidomics real-time library search (RTLS) approach which utilizes the lipid class of real-time identifications to trigger class-targeted MSn and to improve the structural characterization of phosphotidylcholines, phosphotidylethanolamines, phosphotidylinositols, phosphotidylglycerols, phosphotidylserine, and sphingomyelins in the positive ion mode. Our class-based RTLS method demonstrates improved selectivity compared to current methodology of triggering MSn on the presence of characteristic ions or neutral losses.
Project description:Mass spectrometry-based proteomics technologies are the prime methods for the high-throughput identification of proteins expressed in complex biological samples. Nevertheless, mass spectrometry’s technical limitations still hinder its ability to identify low abundance proteins in complex samples. Characterizing such proteins is essential to provide a comprehensive understanding of the biological processes taking place in a sample. Still today, a large part of the mass spectrometry-based proteomics performed use a data-dependent approach that favors the acquisition of mass spectra and detection of proteins of higher abundance. Combined to the fact that the computational identification of proteins from mass spectrometry data is typically performed after mass spectrometry data acquisition, large numbers of mass spectra are redundantly collected from the same abundant proteins and little to no mass spectra are acquired for proteins of lower abundance. To address this problem, we propose a novel supervised learning algorithm that identifies proteins in real-time as mass spectrometry data is acquired and prevents the further data acquisition related to confidently identified proteins to improve the identification sensitivity of low abundance proteins. We show in real-time simulations of a previously performed mass spectrometry analysis of a HEK293 cell lysates that our approach can identify 92.1% of the proteins using 66.2% of the MS2 spectra acquired in the experiment. We also demonstrate that our approach is fast enough for real-time mass spectrometry analysis, is flexible and that it outperforms previously proposed methods. Our method efficient usage of mass spectrometry resources will provide a more comprehensive characterization of proteomes in complex samples.
Project description:Raw data for our manuscript in prep, titled: "Real time health monitoring through urine analysis: A preliminary observational study."
Project description:I plan to investigate the value of video-based feedback in endoscopic training - specifically, the role of terminal video feedback as compared to usual concurrent feedback on cold snare polypectomy technique in trainees, using Direct Observation of Polypectomy Skills (DOPyS) competency score. I have focused the study on the competency of cold snare polypectomy for subcentimeter polyps. The majority (>75%) of colon polyps are smaller than one centimeter. Cold snare polypectomy has been shown, and recommended by the American Society for Gastrointestinal Endoscopy (ASGE), to be an effective removal technique. However, its widespread use and moreover, its teaching to trainees is lacking. It takes time and resources to learn and teach endoscopic techniques. Our study will hope to identify a mechanism through video-based feedback that could help to improve the translation of the training of polypectomy skills to its actual performance, and to accelerate the learning curve.