Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia

被引:140
|
作者
Wallace, Michael B. [1 ,2 ]
Sharma, Prateek [3 ]
Bhandari, Pradeep [4 ]
East, James [5 ]
Antonelli, Giulio [6 ,7 ,8 ]
Lorenzetti, Roberto [6 ]
Vieth, Micheal [9 ]
Speranza, Ilaria [10 ]
Spadaccini, Marco [6 ]
Desai, Madhav [4 ]
Lukens, Frank J. [1 ]
Babameto, Genci [11 ]
Batista, Daisy [11 ]
Singh, Davinder [11 ]
Palmer, William [1 ]
Ramirez, Francisco [12 ]
Palmer, Rebecca [5 ]
Lunsford, Tisha [12 ]
Ruff, Kevin [12 ]
Bird-Liebermann, Elizabeth [5 ]
Ciofoaia, Victor [11 ]
Arndtz, Sophie [4 ]
Cangemi, David [1 ]
Puddick, Kirsty [4 ]
Derfus, Gregory [13 ]
Johal, Amitpal S. [14 ]
Barawi, Mohammed [15 ]
Longo, Luigi [16 ]
Moro, Luigi [16 ]
Repici, Alessandro [17 ,18 ]
Hassan, Cesare [17 ,18 ]
机构
[1] Mayo Clin Jacksonville, Div Gastroenterol & Hepatol, Jacksonville, FL USA
[2] Sheikh Shakhbout Med City SSMC, Div Gastroenterol, Abu Dhabi, U Arab Emirates
[3] Univ Kansas, Med Ctr, Dept Gastroenterol & Hepatol, Kansas City, KS 66103 USA
[4] Queen Alexandra Hosp, Div Gastroenterol, Portsmouth, Hants, England
[5] John Radcliffe Hosp, Translat Gastroenterol Unit, Oxford, England
[6] Nuovo Regina Margherita Hosp, Gastroenterol Unit, Rome, Italy
[7] Sapienza Univ Rome, Dept Anat Histol Forens Med & Orthoped Sci, Rome, Italy
[8] Osped Castelli Hosp, Gastroenterol & Digest Endoscopy Unit, Rome, Italy
[9] Klinikum Bayreuth GmbH, Inst Pathol, Bayreuth, Germany
[10] Cros NT, Verona, Italy
[11] Mayo Clin LaCrosse, Div Gastroenterol & Hepatol, La Crosse, WI USA
[12] Mayo Clin Scottsdale, Div Gastroenterol & Hepatol, Scottsdale, AZ USA
[13] Mayo Clin Eau Claire, Div Gastroenterol & Hepatol, Eau Claire, WI USA
[14] Geisinger Med Ctr, Div Gastroenterol, Danville, PA 17822 USA
[15] Ascens St John Hosp, Gastroenterol & Digest Hlth, Detroit, MI USA
[16] Cosmo Artificial Intelligence AI Ltd, Dublin, Ireland
[17] Humanitas Univ, Dept Biomed Sci, Milan, Italy
[18] Humanitas Clin & Res Ctr IRCCS, Endoscopy Unit, Milan, Italy
关键词
Colorectal Cancer; Artificial Intelligence; Miss Rate; Tandem Colonoscopy; Adenoma Miss Rate; COMPUTER-AIDED DETECTION; GASTROINTESTINAL ENDOSCOPY; EUROPEAN-SOCIETY; COLONOSCOPY; CANCERS; HISTOLOGY; RISK;
D O I
10.1053/j.gastro.2022.03.007
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
BACKGROUND & AIMS: Artificial intelligence (AI) may detect colorectal polyps that have been missed due to perceptual pitfalls. By reducing such miss rate, AI may increase the detection of colorectal neoplasia leading to a higher degree of colorectal cancer (CRC) prevention. METHODS: Patients undergoing CRC screening or surveillance were enrolled in 8 centers (Italy, UK, US), and randomized (1:1) to undergo 2 same-day, back-to-back colonoscopies with or without AI (deep learning computer aided diagnosis endoscopy) in 2 different arms, namely AI followed by colonoscopy without AI or vice-versa. Adenoma miss rate (AMR) was calculated as the number of histologically verified lesions detected at second colonoscopy divided by the total number of lesions detected at first and second colonoscopy. Mean number of lesions detected in the second colonoscopy and proportion of false negative subjects (no lesion at first colonoscopy and at least 1 at second) were calculated. Odds ratios (ORs) and 95% confidence intervals (CIs) were adjusted by endoscopist, age, sex, and indication for colonoscopy. Adverse events were also measured. RESULTS: A total of 230 subjects (116 AI first, 114 standard colonoscopy first) were included in the study analysis. AMR was 15.5% (38 of 246) and 32.4% (80 of 247) in the arm with AI and non-AI colonoscopy first, respectively (adjusted OR, 0.38; 95% CI, 0.23-0.62). In detail, AMR was lower for AI first for the <= 5 mm (15.9% vs 35.8%; OR, 0.34; 95% CI, 0.21-0.55) and nonpolypoid lesions (16.8% vs 45.8%; OR, 0.24; 95% CI, 0.13-0.43), and it was lower both in the proximal (18.3% vs 32.5%; OR, 0.46; 95% CI, 0.26-0.78) and distal colon (10.8% vs 32.1%; OR, 0.25; 95% CI, 0.11-0.57). Mean number of adenomas at second colonoscopy was lower in the AI-first group as compared with non-AI colonoscopy first (0.33 +/- 0.63 vs 0.70 +/- 0.97, P < .001). False negative rates were 6.8% (3 of 44 patients) and 29.6% (13 of 44) in the AI and non-AI first arms, respectively (OR, 0.17; 95% CI, 0.05-0.67). No difference in the rate of adverse events was found between the 2 groups. CONCLUSIONS: AI resulted in an approximately 2-fold reduction in miss rate of colorectal neoplasia, supporting AI-benefit in reducing perceptual errors for small and subtle lesions at standard colonoscopy.
引用
收藏
页码:295 / +
页数:15
相关论文
共 50 条
  • [41] Artificial intelligence for colorectal neoplasia detection during colonoscopy: a systematic review and meta-analysis of randomized clinical trials
    Lou, Shenghan
    Du, Fenqi
    Song, Wenjie
    Xia, Yixiu
    Yue, Xinyu
    Yang, Da
    Cui, Binbin
    Liu, Yanlong
    Han, Peng
    ECLINICALMEDICINE, 2023, 66
  • [42] Recent Advances in the Artificial Intelligence–Assisted Detection of Esophageal Neoplasia
    Amrit K. Kamboj
    Siddharth Agarwal
    Prasad G. Iyer
    Current Treatment Options in Gastroenterology, 2021, 19 (3) : 459 - 472
  • [43] Artificial intelligence to enhance the diagnosis of ocular surface squamous neoplasia
    Kozma, Kincso
    Janki, Zoltan Richard
    Bilicki, Vilmos
    Csutak, Adrienne
    Szalai, Eszter
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [44] Impact of sarcopenia on the risk of advanced colorectal neoplasia
    Hong, Ji Taek
    Kim, Tae Jun
    Pyo, Jeung Hui
    Kim, Eun Ran
    Hong, Sung Noh
    Kim, Young-Ho
    Ahn, Hyeon Seon
    Sohn, Insuk
    Chang, Dong Kyung
    JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY, 2019, 34 (01) : 162 - 168
  • [45] Early detection of gastric neoplasia: is artificial intelligence the solution? Comment
    Ahmad, Omer F.
    LANCET GASTROENTEROLOGY & HEPATOLOGY, 2021, 6 (09): : 678 - 679
  • [46] Role of artificial intelligence in diagnosing Barrett's esophagusrelated neoplasia
    Meinikheim, Michael
    Messmann, Helmut
    Ebigbo, Alanna
    CLINICAL ENDOSCOPY, 2023, 56 (01) : 14 - 22
  • [47] Performance of artificial intelligence in the characterization of colorectal lesions
    Dos Santos, Carlos E. O.
    Malaman, Daniele
    Sanmartin, Ivan D. Arciniegas
    Leao, Ari B. S.
    Leao, Gabriel S.
    Pereira-Lima, Julio C.
    SAUDI JOURNAL OF GASTROENTEROLOGY, 2023, 29 (04): : 219 - 224
  • [48] Implications of Artificial Intelligence for Colorectal Cancer: Correspondence
    Kleebayoon, Amnuay
    Wiwanitkit, Viroj
    JOURNAL OF SURGICAL ONCOLOGY, 2025,
  • [49] Use of Artificial Intelligence in the Diagnosis of Colorectal Cancer
    Nduma, Basil N.
    Nkeonye, Stephen
    Uwawah, Tesingin D.
    Kaur, Davinder
    Ekhator, Chukwuyem
    Ambe, Solomon
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2024, 16 (01)
  • [50] Artificial intelligence for the prevention and prediction of colorectal neoplasms
    Tokutake, Kohjiro
    Morelos-Gomez, Aaron
    Hoshi, Ken-ichi
    Katouda, Michio
    Tejima, Syogo
    Endo, Morinobu
    JOURNAL OF TRANSLATIONAL MEDICINE, 2023, 21 (01)