Autofluorescence imaging endoscopy for identification and assessment of inflammatory ulcerative colitis - Osada, Taro (Baishideng Publishing Group Co., Limited, 2011)
AIM: To validate the clinical relevance of autofluorescence imaging (AFI) endoscopy for the assessment of inflammatory ulcerative colitis (UC). METHODS: A total of 572 endoscopic images were selected from 42 UC patients: 286 taken with white light imaging (WLI) and 286 with AFI from the same sites. WLI images were assessed for overall mucosal inflammation according to Mayo endoscopic subscore (MES), and for seven characteristic endoscopic features. Likewise, AFI photographs were scored according to relative abundance of red, green and blue color components within each image based on an RGB additive color model. WLI and AFI endoscopic scores from the same sites were compared. Histological evaluation of biopsies was according to the Riley Index. RESULTS: Relative to red (r = 0.52, P < 0.01) or blue (r = 0.56, P < 0.01) color component, the green color component of AFI (r = -0.62, P < 0.01) corresponded more closely with mucosal inflammation sites. There were significant differences in green color components between MES-0 (0.396 ± 0.043) and MES-1 (0.340 ± 0.035) (P < 0.01), and between MES-1 and ≥ MES-2 (0.318 ± 0.037) (P < 0.01). The WLI scores for “vascular patterns” (r = -0.65, P < 0.01), “edema” (r = -0.62, P < 0.01), histology scores for “polymorphonuclear cells in the lamina propria” (r = -0.51, P < 0.01) and “crypt architectural irregularities” (r = -0.51, P < 0.01) showed correlation with the green color component of AFI. There were significant differences in green color components between limited (0.399 ± 0.042) and extensive (0.375 ± 0.044) (P = 0.014) polymorphonuclear cell infiltration within MES-0. As the severity of the mucosal inflammation increased, the green color component of AFI decreased. The AFI green color component was well correlated with the characteristic endoscopic and histological inflammatory features of UC. CONCLUSION: AFI has application in detecting inflammatory lesions, including microscopic activity in the colonic mucosa of UC patients, based on the green color component of images.