Blue laser imaging endoscopy system for the early detection and characterization of colorectal lesions: a guide for the endoscopist

Blue laser imaging is a new system for image-enhanced endoscopy using laser light. Blue laser imaging utilizes two monochromatic lasers (410 and 450 nm) instead of xenon light. A 410 nm laser visualizes vascular microarchitecture, similar to narrow band imaging, and a 450 nm laser provides white light by excitation. According to three recently published reports, the diagnostic ability of polyp characterization using blue laser imaging compares favorably with narrow band imaging. No published data are available to date regarding polyp detection with blue laser imaging. However, blue laser imaging has the possibility to increase the detection of colorectal polyps by depicting brighter and clearer endoscopic images, even at a distant view, compared with first-generation image-enhanced endoscopy. A clinical trial to compare the detection between blue laser imaging and xenon light is warranted

Laser Imaging Facilitates Early Detection of Synchronous Adenocarcinomas in Patients with Barrett’s Esophagus

Barrett’s adenocarcinoma may occur in multiple sites, and recurrence and metachronous lesions are the major problems with endoscopic resection. Therefore, early detection of such lesions is ideal to achieve complete resection and obtain improved survival rates with minimally invasive treatment. Laser imaging systems allow multiple modalities of endoscopic imaging by using white light laser, flexible spectral imaging color enhancement (FICE), blue laser imaging (BLI), and linked color imaging even at a distant view. However, the usefulness of these modalities has not been sufficiently reported regarding Barrett’s adenocarcinoma. Here, we report on a patient with three synchronous lesions followed by one metachronous lesion in a long segment with changes of Barrett’s esophagus, all diagnosed with this new laser endoscopic imaging system and enhanced by using FICE and/or BLI with high contrast compared with the surrounding mucosa. Laser endoscopic imaging may facilitate the detection of malignancies in patients with early Barrett’s adenocarcinoma

Feasibility of an AI-Based Measure of the Hand Motions of Expert and Novice Surgeons

This study investigated whether parameters derived from hand motions of expert and novice surgeons accurately and objectively reflect laparoscopic surgical skill levels using an artificial intelligence system consisting of a three-layer chaos neural network. Sixty-seven surgeons (23 experts and 44 novices) performed a laparoscopic skill assessment task while their hand motions were recorded using a magnetic tracking sensor. Eight parameters evaluated as measures of skill in a previous study were used as inputs to the neural network. Optimization of the neural network was achieved after seven trials with a training dataset of 38 surgeons, with a correct judgment ratio of 0.99. The neural network that prospectively worked with the remaining 29 surgeons had a correct judgment rate of 79% for distinguishing between expert and novice surgeons. In conclusion, our artificial intelligence system distinguished between expert and novice surgeons among surgeons with unknown skill levels