Predicting Therapeutic Intervention for Patients with Quiescent Crohn's Disease Using the Small Bowel Capsule Endoscopy Score.

Introduction: Small bowel (SB) capsule endoscopy (SBCE) is a sensitive modality for screening the entire SB of patients with Crohn's disease (CD); however, the prognostic impact of the results is unclear. We evaluated the ability of the SBCE score to predict therapeutic intervention for patients with CD and SB lesions without clinical symptoms as well as negative C-reactive protein (CRP) levels. Methods: Fifty-six patients who underwent a patency evaluation and had a CD activity index (CDAI) score <150 mg/dL and CRP level <0.5 mg/dL were included. Twenty-one and 35 patients had CD classified as Montreal classifications L1 and L3, respectively. The initial SBCE scores were subsequently grouped according to the presence or absence of intervention based on cutoff values. We examined whether the scores could predict the need for therapeutic intervention at 1 year, 2 years, and 5 years. The CD activity in capsule endoscopy (CDACE) score was used as the SBCE score. Results: The median observation period was 1,326 days. Twenty-one patients received therapeutic intervention. There were significant differences between patients with and without treatment intervention according to the CDACE cutoff value of 420 at 1 year, 2 years, and 5 years. Significant differences between patients with Montreal classification L1 with and without intervention were observed at 1 year and 2 years. The CDACE score was moderately and strongly correlated with the Lewis score and capsule endoscopy CDAI score, respectively (Spearman rank correlation coefficient: ρ = 0.6462 and ρ = 0.9199, respectively; p < 0.0001). Conclusion: A CDACE score ≥420 is predictive of intervention after 1 year for patients with CD, a CDAI score <150, and a CRP level <0.5 mg/dL. A larger study with a prospective design is necessary to validate our findings.

Efficacy of serum leucine-rich alpha-2 glycoprotein in predicting findings of Crohn's disease small bowel lesion in capsule endoscopy.

Background/Aims: Small bowel capsule endoscopy (SBCE) is an evaluation method for small bowel (SB) lesions in Crohn's disease (CD). However, the relationship between SBCE findings and the serological biomarker leucine-rich alpha-2 glycoprotein (LRG) remains unclear. We aimed to establish appropriate cutoff values of LRG to predict the presence of SB lesions in CD through SBCE. Methods: Patients with CD with SB lesions who had undergone SBCE and LRG measurements 1 month before and after the SBCE were included. The LRG values for ulcers ≥0.5 cm and other inflammatory lesions noted in SBCE were determined using the Youden Index, and the sensitivity and specificity were calculated. Additionally, the correlation between the SBCE scores (CD Activity in Capsule Endoscopy) and LRG values was evaluated. Results: Forty patients without active colorectal lesions were included in the study. When the cutoff value of LRG for SB ulcers ≥ 0.5 cm was set at 14 µg/mL, the sensitivity was 92.3%, specificity was 81.5%, positive predictive value (PPV) was 70.6%, and negative predictive value (NPV) was 95.7%. In contrast, an LRG cutoff value of 12 µg/mL without inflammatory findings had a sensitivity of 91.7%, specificity of 82.1%, PPV of 68.8%, and NPV of 95.8%. CD Activity in Capsule Endoscopy correlated well with LRG values (Spearman's rank correlation coefficient ρ = 0.681, P< 0.001). Conclusions: An LRG cutoff value of 14 µg/mL may be useful in predicting the presence of SB ulcers ≥ 0.5 cm, and an LRG cutoff value of 12 µg/mL may be useful in predicting the absence of SB inflammatory findings.

Comparison of Endoscopic and Artificial Intelligence Diagnoses for Predicting the Histological Healing of Ulcerative Colitis in a Real-World Clinical Setting.

Background: Artificial intelligence (AI)-assisted colonoscopy systems with contact microscopy capabilities have been reported previously; however, no studies regarding the clinical use of a commercially available system in patients with ulcerative colitis (UC) have been reported. In this study, the diagnostic performance of an AI-assisted ultra-magnifying colonoscopy system for histological healing was compared with that of conventional light non-magnifying endoscopic evaluation in patients with UC. Methods: The data of 52 patients with UC were retrospectively analyzed. The Mayo endoscopic score (MES) was determined by 3 endoscopists. Using the AI system, healing of the same spot assessed via MES was defined as a predicted Geboes score (GS) < 3.1. The GS was then determined using pathology specimens from the same site. Results: A total of 191 sites were evaluated, including 159 with a GS < 3.1. The MES diagnosis identified 130 sites as MES0. A total of 120 sites were determined to have healed based on AI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of MES0 for the diagnosis of GS < 3.1 were 79.2%, 90.6%, 97.7%, 46.8%, and 81.2%, respectively. The AI system performed similarly to MES for the diagnosis of GS < 3.1: sensitivity, 74.2%; specificity: 93.8%; PPV: 98.3%; NPV: 42.3%; and accuracy: 77.5%. The AI system also significantly identified a GS of < 3.1 in the setting of MES1 (P = .0169). Conclusions: The histological diagnostic yield the MES- and AI-assisted diagnoses was comparable. Healing decisions using AI may avoid the need for histological examinations.