Individualized small bowel preparation for computed tomography enterography: A prospective randomized controlled trial.

BACKGROUND AND AIM: The study aims to evaluate the feasibility of body mass index (BMI)-based individualized small bowel preparation for computed tomography enterography (CTE). METHODS: In this prospective randomized controlled study, patients undergoing CTE were randomly assigned to the individualized group or standardized group. Those in individualized group were given different volumes of mannitol solution based on BMI (1000 mL for patients with BMI < 18.5 kg/m2, 1500 mL for patients with 18.5 kg/m2 ≤ BMI < 25 kg/m2 and 2000 mL for patients with BMI ≥ 25 kg/m2) while patients in the standardized group were all asked to consume 1500-mL mannitol solution. CTE images were reviewed by two experienced radiologists blindly. Each segment of the small bowel was assessed for small bowel image quality and disease detection rates. Patients were invited to record a diary regarding adverse events and acceptance. RESULTS: A total of 203 patients were enrolled and randomly divided into two groups. For patients with BMI < 18.5 kg/m2, 1000-mL mannitol solution permitted a significantly lower rate of flatulence (P = 0.045) and defecating frequency (P = 0.011) as well as higher acceptance score (P = 0.015), but did not affect bowel image quality and diseases detection compared with conventional dosage. For patients with BMI ≥ 25 kg/m2, 2000-mL mannitol solution provided better overall image quality (P = 0.033) but comparable rates of adverse events and patients' acceptance compared with conventional dosage. CONCLUSIONS: Individualized bowel preparation could achieve both satisfactory image quality and patients' acceptance thus might be an acceptable alternative in CTE.

Real-time artificial intelligence for endoscopic diagnosis of early esophageal squamous cell cancer (with video).

BACKGROUND AND AIMS: Endoscopic diagnosis of early esophageal squamous cell cancer (ESCC) is complicated and dependent on operators' experience. This study aimed to develop an artificial intelligence (AI) model for automatic diagnosis of early ESCC. METHODS: Non-magnifying and magnifying endoscopic images of normal/noncancerous lesions, early ESCC, and advanced esophageal cancer (AEC) were retrospectively obtained from Qilu Hospital of Shandong University. A total of 10,988 images from 5075 cases were chosen for training and validation. Another 2309 images from 1055 cases were collected for testing. One hundred and four real-time videos were also collected to evaluate the diagnostic performance of the AI model. The diagnostic performance of the AI model was compared with endoscopists by magnifying images and the assistant efficiency of the AI model for novices was evaluated. RESULTS: The AI diagnosis for non-magnifying images showed a per-patient accuracy, sensitivity, and specificity of 99.5%, 100%, 99.5% for white light imaging, and 97.0%, 97.2%, 96.4% for optical enhancement/iodine straining images. Regarding diagnosis for magnifying images, the per-patient accuracy, sensitivity, and specificity were 88.1%, 90.9%, and 85.0%. The diagnostic accuracy of the AI model was similar to experts (84.5%, P = 0.205) and superior to novices (68.5%, P = 0.005). The diagnostic performance of novices was significantly improved by AI assistance. When it comes to the diagnosis for real-time videos, the AI model showed acceptable performance as well. CONCLUSIONS: The AI model could accurately recognize early ESCC among noncancerous mucosa and AEC. It could be a potential assistant for endoscopists, especially for novices.

Cresyl violet as a new contrast agent in probe-based confocal laser endomicroscopy for in vivo diagnosis of gastric intestinal metaplasia.

BACKGROUND AND AIM: Cresyl violet (CV) is a topical dye that allows simultaneous chromoendoscopy and in vivo confocal laser endomicroscopy in identification of neoplastic changes of the lower gastrointestinal tract without intravenous injection of fluorescein, but as yet no investigation has reported its application in the diagnosis of gastric intestinal metaplasia (GIM). This study aims to assess the feasibility as well as diagnosis accuracy of topical CV for in vivo diagnosis of GIM by using probe-based confocal laser endomicroscopy (pCLE). METHODS: In this prospective, open-label, feasibility study, 129 confocal videos from 22 patients with known GIM were analyzed and compared with corresponding histological images to establish the CV staining characteristics. In addition, 47 patients with known or suspected GIM were prospectively enrolled to evaluate the accuracy of this topical CV endomicroscopic imaging. RESULTS: Probe-based confocal laser endomicroscopy with topical CV enabled clear visualization of the goblet cells, absorptive cells, and intestinal villi of GIM. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of pCLE diagnosis of GIM on a per-location analysis was 93.01%, 91.95%, 93.51%, 86.96%, and 96.11%, respectively. The intraclass correlation coefficient for inter-observer agreement and mean kappa value for intra-observer agreement for the diagnosis of GIM was 0.82 and 0.87, respectively. CONCLUSIONS: Topical CV enables real-time chromoendoscopy in conjunction with pCLE examination of the stomach and warrants accurate diagnosis of GIM. It may be an acceptable and potentially alternative dye for confocal imaging in the future.