Value of Magnifying Chromoendoscopy and Magnifying Optical Enhancement Technology in Classifying Colorectal Polyps: A Prospective Controlled Study

Background and Aims. Magnifying chromoendoscopy (ME-CE) through the observation of pit patterns is a productive way to distinguish between neoplastic and nonneoplastic polyps. Magnifying optical enhancement technology (ME-OE) is an emerging virtual chromoendoscopy imaging technology and appeared to be a promising approach. However, this information is currently not available. This study is aimed at comparing the differential diagnostic value of ME-CE and OE for neoplastic and nonneoplastic polyps. Patients and Methods. Consecutive patients undergoing colonoscopy were randomized (1 : 1) into examination by ME-OE or ME-CE. Histopathological findings were utilized as the reference standard. Accuracy, sensitivity, specificity, and positive and negative predictive values of two endoscopy methods were compared using ME-OE (were classified according to the JNET classification) and ME-CE (were classified according to the Kudo pit pattern classification), respectively, and the time to predict the histological polyp type was compared. And the agreements between the pathological and clinical diagnosis by ME-OE or ME-CE were analyzed. Results. A total of 365 polyps were found in the 220 patients included (ME-OE: 185; ME-CE: 180.202 had nonneoplastic polyps, 163 had neoplastic polyps). The diagnostic accuracy of ME-OE was higher than that of ME-CE (93% vs. 92%, p > 0.05 ). The average diagnosis time was lower in ME-OE than ME-CE ( 83 ± 26.4 s vs. 194 ± 17.7 s , p < 0.001 ). The agreements between the pathological and clinical diagnosis were at least substantial in both groups. Conclusion. ME-OE was superlative to ME-CE in predicting the histology of polyps. OE devoted classification would possibly similarly enhance the endoscopist performance. The trial is registered with ChiCT2000032075.

Endoscopic Ultrasound Elastography as a Novel Diagnostic Method for the Assessment of Hardness and Depth of Invasion in Colorectal Neoplasms

<b><i>Introduction:</i></b> We aimed to compare the efficacy of endoscopic ultrasound elastography (EUS-EG) with that of magnifying chromoendoscopy (MCE) and endoscopic ultrasonography (EUS) for the diagnosis of the depth of invasion in colorectal neoplasms. This is an important clinical issue as the depth of invasion is associated with the risk of metastasis. <b><i>Methods:</i></b> Consecutive patients with suspected superficial colorectal neoplasms, evaluated by MCE, EUS, and EUS-EG, for whom endoscopic submucosal dissection was considered, were enrolled in 2018 (derivation study) and in 2019–2020 (validation study). The primary clinical endpoint was the diagnostic yield differentiating intramucosal and shallow submucosal neoplasms from deep submucosal (dSM) and advanced colorectal cancers. In addition, inter- and intra-observer agreements of the elastic score of colorectal neoplasm (ES-CRN) were evaluated by 2 expert and 2 non-expert endoscopists. <b><i>Results:</i></b> Thirty-one (33 lesions) and 50 (55 lesions) patients were enrolled in the derivation and validation studies, respectively. Sensitivity, specificity, positive, and negative predictive values, and accuracy of assessment of the depth of submucosal or deeper invasion in the derivation and validation groups were as follows: EUS-EG, 100/88.2/86.7/100/93.3% and 77.8/86.1/73.7/88.6/83.3%; MCE, 66.7/94.4/90.9/77.3/81.8% and 84.2/91.4/84.2/91.4/88.9%; and EUS, 93.3/77.8/77.8/93.3/84.8% and 89.5/65.7/58.6/92.0/74.1%, respectively. For the 2 expert endoscopists, interobserver agreement for the ES-CRN (first and second assessments) in the derivation group was 0.84 and 0.78, respectively; these values were 0.73 and 0.49, respectively, for the 2 non-expert endoscopists. <b><i>Discussion/Conclusion:</i></b> All 3 modalities presented similar diagnostic yield. Inter- and intra-observer agreements of the ES-CRN were substantial, even for non-expert endoscopists. Therefore, EUS-EG may be a useful modality in determining the depth of invasion in colorectal neoplasms.

Scope of Artificial Intelligence in Screening and Diagnosis of Colorectal Cancer

Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a “second look” for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization.