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Rondonotti E, Bergna IMB, Paggi S, Amato A, Andrealli A, Scardino G, Tamanini G, Lenoci N, Mandelli G, Terreni N, Rocchetto SI, Piagnani A, Di Paolo D, Bina N, Filippi E, Ambrosiani L, Hassan C, Correale L, Radaelli F. White light computer-aided optical diagnosis of diminutive colorectal polyps in routine clinical practice. Endosc Int Open 2024; 12:E676-E683. [PMID: 38774861 PMCID: PMC11108657 DOI: 10.1055/a-2303-0922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 04/04/2024] [Indexed: 05/24/2024] Open
Abstract
Background and study aims Artificial Intelligence (AI) systems could make the optical diagnosis (OD) of diminutive colorectal polyps (DCPs) more reliable and objective. This study was aimed at prospectively evaluating feasibility and diagnostic performance of AI-standalone and AI-assisted OD of DCPs in a real-life setting by using a white light-based system (GI Genius, Medtronic Co, Minneapolis, Minnesota, United States). Patients and methods Consecutive colonoscopy outpatients with at least one DCP were evaluated by 11 endoscopists (5 experts and 6 non-experts in OD). DCPs were classified in real time by AI (AI-standalone OD) and by the endoscopist with the assistance of AI (AI-assisted OD), with histopathology as the reference standard. Results Of the 480 DCPs, AI provided the outcome "adenoma" or "non-adenoma" in 81.4% (95% confidence interval [CI]: 77.5-84.6). Sensitivity, specificity, positive and negative predictive value, and accuracy of AI-standalone OD were 97.0% (95% CI 94.0-98.6), 38.1% (95% CI 28.9-48.1), 80.1% (95% CI 75.2-84.2), 83.3% (95% CI 69.2-92.0), and 80.5% (95% CI 68.7-82.8%), respectively. Compared with AI-standalone, the specificity of AI-assisted OD was significantly higher (58.9%, 95% CI 49.7-67.5) and a trend toward an increase was observed for other diagnostic performance measures. Overall accuracy and negative predictive value of AI-assisted OD for experts and non-experts were 85.8% (95% CI 80.0-90.4) vs. 80.1% (95% CI 73.6-85.6) and 89.1% (95% CI 75.6-95.9) vs. 80.0% (95% CI 63.9-90.4), respectively. Conclusions Standalone AI is able to provide an OD of adenoma/non-adenoma in more than 80% of DCPs, with a high sensitivity but low specificity. The human-machine interaction improved diagnostic performance, especially when experts were involved.
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Affiliation(s)
| | - Irene Maria Bambina Bergna
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- University of Milan, Milano, Italy
- Gastroenterology and Digestive Endoscopy Unit, Alessandro Manzoni Hospital, Lecco, Italy
| | - Silvia Paggi
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | - Arnaldo Amato
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- Gastroenterology and Digestive Endoscopy Unit, Alessandro Manzoni Hospital, Lecco, Italy
| | | | | | | | | | | | | | - SImone Rocchetto
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- University of Milan, Milano, Italy
| | - Alessandra Piagnani
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- University of Milan, Milano, Italy
| | | | - Niccolò Bina
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | | | | | - Cesare Hassan
- Department of Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
| | - Loredana Correale
- Department of Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano, Italy
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Xin Y, Zhang Q, Liu X, Li B, Mao T, Li X. Application of artificial intelligence in endoscopic gastrointestinal tumors. Front Oncol 2023; 13:1239788. [PMID: 38144533 PMCID: PMC10747923 DOI: 10.3389/fonc.2023.1239788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 11/17/2023] [Indexed: 12/26/2023] Open
Abstract
With an increasing number of patients with gastrointestinal cancer, effective and accurate early diagnostic clinical tools are required provide better health care for patients with gastrointestinal cancer. Recent studies have shown that artificial intelligence (AI) plays an important role in the diagnosis and treatment of patients with gastrointestinal tumors, which not only improves the efficiency of early tumor screening, but also significantly improves the survival rate of patients after treatment. With the aid of efficient learning and judgment abilities of AI, endoscopists can improve the accuracy of diagnosis and treatment through endoscopy and avoid incorrect descriptions or judgments of gastrointestinal lesions. The present article provides an overview of the application status of various artificial intelligence in gastric and colorectal cancers in recent years, and the direction of future research and clinical practice is clarified from a clinical perspective to provide a comprehensive theoretical basis for AI as a promising diagnostic and therapeutic tool for gastrointestinal cancer.
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Affiliation(s)
| | | | | | | | | | - Xiaoyu Li
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
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Leung WK, Tsui VWM, Mak LLY, Cheung MKS, Hui CKY, Lam CPM, Wong SY, Liu KSH, Ko MKL, To EWP, Guo CG, Lui TKL. Blue-light imaging or narrow-band imaging for proximal colonic lesions: a prospective randomized tandem colonoscopy study. Gastrointest Endosc 2023; 98:813-821.e3. [PMID: 37307902 DOI: 10.1016/j.gie.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/03/2023] [Accepted: 06/05/2023] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND AIMS Blue-light imaging (BLI) is a new image-enhanced endoscopy with a wavelength filter similar to narrow-band imaging (NBI). We compared the 2 with white-light imaging (WLI) on proximal colonic lesion detection and miss rates. METHODS In this 3-arm prospective randomized study with tandem examination of the proximal colon, we enrolled patients aged ≥40 years. Eligible patients were randomized in 1:1:1 ratio to receive BLI, NBI, or WLI during the first withdrawal from the proximal colon. The second withdrawal was performed using WLI in all patients. Primary outcomes were proximal polyp (pPDRs) and adenoma (pADRs) detection rates. Secondary outcomes were miss rates of proximal lesions found on tandem examination. RESULTS Of 901 patients included (mean age, 64.7 years; 52.9% men), 48.1% underwent colonoscopy for screening or surveillance. The corresponding pPDRs of the BLI, NBI, and WLI groups were 45.8%, 41.6, and 36.6%, whereas the corresponding pADRs were 36.6%, 33.8%, and 28.3%. There was a significant difference in pPDR and pADR between BLI and WLI groups (difference, 9.2% [95% confidence interval {CI}, 3.3-16.9] and 8.3% [95% CI, 2.7-15.9]) and between NBI and WLI groups (difference, 5.0% [95% CI, 1.4-12.9] and 5.6% [95% CI, 2.1-13.3]). Proximal adenoma miss rates were significantly lower with BLI (19.4%) than with WLI (27.4%; difference, -8.0%; 95% CI, -15.8 to -.1) but not between NBI (27.2%) and WLI. CONCLUSIONS Both BLI and NBI were superior to WLI on detecting proximal colonic lesions, but only BLI had lower proximal adenoma miss rates than WLI. (Clinical trial registration number: NCT03696992.).
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Affiliation(s)
- Wai K Leung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong; Department of Medicine, Queen Mary Hospital, Hong Kong
| | | | - Loey Lung-Yi Mak
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong; Department of Medicine, Queen Mary Hospital, Hong Kong
| | - Michael Ka-Shing Cheung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong; Department of Medicine, Queen Mary Hospital, Hong Kong
| | | | | | - Siu-Yin Wong
- Department of Medicine, Queen Mary Hospital, Hong Kong
| | | | | | | | - Chuan-Guo Guo
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong
| | - Thomas Ka-Luen Lui
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong; Department of Medicine, Queen Mary Hospital, Hong Kong
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Yoshida N, Draganov PV, John S, Neumann H, Rani RA, Hsu WH, Fernandopulle N, Siah KTH, Morgenstern R, Tomita Y, Inoue K, Dohi O, Hirose R, Itoh Y, Murakami T, Inagaki Y, Inada Y, Arantes V. Comparison of LED and LASER Colonoscopy About Linked Color Imaging and Blue Laser/Light Imaging of Colorectal Tumors in a Multinational Study. Dig Dis Sci 2023; 68:3943-3952. [PMID: 37558800 DOI: 10.1007/s10620-023-08057-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 07/23/2023] [Indexed: 08/11/2023]
Abstract
INTRODUCTION In light-emitting diode (LED) and LASER colonoscopy, linked color imaging (LCI) and blue light/laser imaging (BLI) are used for lesion detection and characterization worldwide. We analyzed the difference of LCI and BLI images of colorectal lesions between LED and LASER in a multinational study. METHODS We prospectively observed lesions with white light imaging (WLI), LCI, and BLI using both LED and LASER colonoscopies from January 2020 to August 2021. Images were graded by 27 endoscopists from nine countries using the polyp visibility score: 4 (excellent), 3 (good), 2 (fair), and 1 (poor) and the comparison score (LED better/similar/LASER better) for WLI/LCI/BLI images of each lesion. RESULTS Finally, 32 lesions (polyp size: 20.0 ± 15.2 mm) including 9 serrated lesions, 13 adenomas, and 10 T1 cancers were evaluated. The polyp visibility scores of LCI/WLI for international and Japan-expert endoscopists were 3.17 ± 0.73/3.17 ± 0.79 (p = 0.92) and 3.34 ± 0.78/2.84 ± 1.22 (p < 0.01) for LED and 3.30 ± 0.71/3.12 ± 0.77 (p < 0.01) and 3.31 ± 0.82/2.78 ± 1.23 (p < 0.01) for LASER. Regarding the comparison of lesion visibility about between LED and LASER colonoscopy in international endoscopists, a significant difference was achieved not for WLI, but for LCI. The rates of LED better/similar/LASER better for brightness under WLI were 54.5%/31.6%/13.9% (International) and 75.0%/21.9%/3.1% (Japan expert). Those under LCI were 39.2%/35.4%/25.3% (International) and 31.3%/53.1%/15.6% (Japan expert). There were no significant differences in the diagnostic accuracy and the comparison score of BLI images between LED and LASER. CONCLUSIONS The differences of lesion visibility for WLI/LCI/BLI between LED and LASER in international endoscopists could be compared to those in Japanese endoscopists.
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Affiliation(s)
- Naohisa Yoshida
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, 602-8566, Japan.
| | - Peter V Draganov
- Endoscopy Department, University of Florida, Gainesville, FL, USA
| | - Sneha John
- Department of Gastroenterology, Gold Coast University, Gold Coast, Australia
| | - Helmut Neumann
- First Medical Department, Interdisciplinary Endoscopy, University Medical Center Mainz, Mainz, Germany
| | - Rafiz Abdul Rani
- Gastroenterology Unit, Faculty of Medicine, Universiti Teknologi MARA, Selangor, Malaysia
| | - Wen-Hsin Hsu
- Division of Gastroenterology, Department of Internal Medicine, Yuan's General Hospital, Kaohsiung, Taiwan
| | | | - Kewin Tien Ho Siah
- Division of Gastroenterology & Hepatology, University Medicine Cluster, National University Hospital, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ricardo Morgenstern
- Division of Gastroenterology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yuri Tomita
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, 602-8566, Japan
| | - Ken Inoue
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, 602-8566, Japan
| | - Osamu Dohi
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, 602-8566, Japan
| | - Ryohei Hirose
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, 602-8566, Japan
| | - Yoshito Itoh
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, 602-8566, Japan
| | - Takaaki Murakami
- Department of Gastroenterology, Aiseikai Yamashina Hospital, Kyoto, Japan
| | | | - Yutaka Inada
- Department of Gastroenterology, Kyoto First Red Cross Hospital, Kyoto, Japan
| | - Vitor Arantes
- Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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Li JW, Wu CCH, Lee JWJ, Liang R, Soon GST, Wang LM, Koh XH, Koh CJ, Chew WD, Lin KW, Thian MY, Matthew R, Kim G, Khor CJL, Fock KM, Ang TL, So JBY. Real-World Validation of a Computer-Aided Diagnosis System for Prediction of Polyp Histology in Colonoscopy: A Prospective Multicenter Study. Am J Gastroenterol 2023; 118:1353-1364. [PMID: 37040553 DOI: 10.14309/ajg.0000000000002282] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/28/2023] [Indexed: 04/13/2023]
Abstract
INTRODUCTION Computer-aided diagnosis (CADx) of polyp histology could support endoscopists in clinical decision-making. However, this has not been validated in a real-world setting. METHODS We performed a prospective, multicenter study comparing CADx and endoscopist predictions of polyp histology in real-time colonoscopy. Optical diagnosis based on visual inspection of polyps was made by experienced endoscopists. After this, the automated output from the CADx support tool was recorded. All imaged polyps were resected for histological assessment. Primary outcome was difference in diagnostic performance between CADx and endoscopist prediction of polyp histology. Subgroup analysis was performed for polyp size, bowel preparation, difficulty of location of the polyps, and endoscopist experience. RESULTS A total of 661 eligible polyps were resected in 320 patients aged ≥40 years between March 2021 and July 2022. CADx had an overall accuracy of 71.6% (95% confidence interval [CI] 68.0-75.0), compared with 75.2% (95% CI 71.7-78.4) for endoscopists ( P = 0.023). The sensitivity of CADx for neoplastic polyps was 61.8% (95% CI 56.9-66.5), compared with 70.3% (95% CI 65.7-74.7) for endoscopists ( P < 0.001). The interobserver agreement between CADx and endoscopist predictions of polyp histology was moderate (83.1% agreement, κ 0.661). When there was concordance between CADx and endoscopist predictions, the accuracy increased to 78.1%. DISCUSSION The overall diagnostic accuracy and sensitivity for neoplastic polyps was higher in experienced endoscopists compared with CADx predictions, with moderate interobserver agreement. Concordance in predictions increased this diagnostic accuracy. Further research is required to improve the performance of CADx and to establish its role in clinical practice.
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Affiliation(s)
- James Weiquan Li
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore
| | - Clement Chun Ho Wu
- Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore
- Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore Health Services, Singapore
| | - Jonathan Wei Jie Lee
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, National University Health System, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Institute of Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore
| | - Raymond Liang
- Department of Gastroenterology and Hepatology, Tan Tock Seng Hospital, National Healthcare Group, Singapore
| | - Gwyneth Shook Ting Soon
- Department of Pathology, National University Hospital, National University Health System, Singapore
| | - Lai Mun Wang
- Department of Laboratory Medicine, Changi General Hospital, Singapore Health Services, Singapore
| | - Xuan Han Koh
- Department of Health Sciences Research, Changi General Hospital, Singapore
| | - Calvin Jianyi Koh
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, National University Health System, Singapore
| | - Wei Da Chew
- Department of Gastroenterology and Hepatology, Tan Tock Seng Hospital, National Healthcare Group, Singapore
| | - Kenneth Weicong Lin
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore
| | - Mann Yie Thian
- Department of Gastroenterology and Hepatology, Tan Tock Seng Hospital, National Healthcare Group, Singapore
| | - Ronnie Matthew
- Department of Colorectal Surgery, Singapore General Hospital, Singapore Health Services, Singapore
| | - Guowei Kim
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- University Surgical Cluster, National University Hospital, Singapore
| | - Christopher Jen Lock Khor
- Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore
- Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore Health Services, Singapore
| | - Kwong Ming Fock
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore
| | - Tiing Leong Ang
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, Singapore
- Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore
| | - Jimmy Bok Yan So
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- University Surgical Cluster, National University Hospital, Singapore
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Yoshida N, Hayashi Y, Kashida H, Tomita Y, Dohi O, Inoue K, Hirose R, Itoh Y, Okada M, Yoshimoto S, Fujinuma T, Sakamoto H, Sunada K, Komeda Y, Sekai I, Okai N, Yamamoto H. Images of laser and light-emitting diode colonoscopy for comparing large colorectal lesion visibility with linked color imaging and white-light imaging. Dig Endosc 2022; 34:1413-1421. [PMID: 35656632 DOI: 10.1111/den.14370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/31/2022] [Indexed: 02/08/2023]
Abstract
OBJECTIVES In light-emitting diode (LED) and laser colonoscopy, linked color imaging (LCI) superiority to white-light imaging (WLI) for polyp detection is shown separately. We analyzed the noninferiority of LCI between LED and laser colonoscopy and that of WLI (LECOL study). METHODS We prospectively collected nonpolypoid lesions with WLI and LCI using LED and laser colonoscopy from January 2021 to August 2021. All images were evaluated randomly by 12 endoscopists (six nonexperts and six experts in three institutions) using the polyp visibility score: 4, excellent; 3, good; 2, fair; and 1, poor. The comparison score (LED better/similar/laser better) for redness and brightness was evaluated for WLI and LCI pictures of each lesion. RESULTS Finally, 63 nonpolypoid lesions were evaluated, and the mean polyp size was 24.5 ± 13.4 mm. Histopathology revealed 13 serrated lesions and 50 adenomatous/cancerous lesions. The mean polyp visibility scores of LCI pictures were significantly higher than those of WLI in the LED (3.35 ± 0.85 vs. 3.08 ± 0.91, P < 0.001) and the laser (3.40 ± 1.71 vs. 3.05 ± 0.97, P < 0.001) group, and the noninferiority of LCI pictures between LED and laser was significant (P < 0.001). The comparison scores revealed that the evaluation of redness and brightness (LED better/similar/laser better) were 26.8%/40.1%/33.1% and 43.5%/43.5%/13.0% for LCI pictures (P < 0.001) and 20.6%/44.3%/35.1% and 60.3%/31.7%/8.0% for WLI pictures (P < 0.001), respectively. CONCLUSION The noninferiority of polyp visibility with WLI and LCI in LED and laser colonoscopy was shown. WLI and LCI of LED tended to be brighter and less reddish than those of laser.
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Affiliation(s)
- Naohisa Yoshida
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yoshikazu Hayashi
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
| | - Hiroshi Kashida
- Department of Gastroenterology and Hepatology, Faculty of Medicine, Kindai University, Osaka, Japan
| | - Yuri Tomita
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Osamu Dohi
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Ken Inoue
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Ryohei Hirose
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yoshito Itoh
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Masahiro Okada
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
| | - Shiori Yoshimoto
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
| | - Toshihiro Fujinuma
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
| | - Hirotsugu Sakamoto
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
| | - Keijiro Sunada
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
| | - Yoriaki Komeda
- Department of Gastroenterology and Hepatology, Faculty of Medicine, Kindai University, Osaka, Japan
| | - Ikue Sekai
- Department of Gastroenterology and Hepatology, Faculty of Medicine, Kindai University, Osaka, Japan
| | - Natsuki Okai
- Department of Gastroenterology and Hepatology, Faculty of Medicine, Kindai University, Osaka, Japan
| | - Hironori Yamamoto
- Division of Gastroenterology, Department of Medicine, Jichi Medical University, Tochigi, Japan
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Hossain E, Abdelrahim M, Tanasescu A, Yamada M, Kondo H, Yamada S, Hamamoto R, Marugame A, Saito Y, Bhandari P. Performance of a novel computer-aided diagnosis system in the characterization of colorectal polyps, and its role in meeting Preservation and Incorporation of Valuable Endoscopic Innovations standards set by the American Society of Gastrointestinal Endoscopy. DEN OPEN 2022; 3:e178. [PMID: 36320934 PMCID: PMC9614381 DOI: 10.1002/deo2.178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/27/2022] [Accepted: 10/02/2022] [Indexed: 11/06/2022]
Abstract
Background and aims There has been an increasing role of artificial intelligence (AI) in the characterization of colorectal polyps. Recently, a novel AI algorithm for the characterization of polyps was developed by NEC Corporation (Japan). The aim of our study is to perform an external validation of this algorithm. Methods The study was a video-based evaluation of the computer-aided diagnosis (CADx) system. Patients undergoing colonoscopy were recruited to record videos of colonic polyps. The frozen polyp images extracted from these videos were used for real-time histological prediction by the endoscopists and by the CADx system, and the results were compared. Results A total of 115 polyp images were extracted from 66 patients. Sensitivity, negative predictive value and accuracy for diminutive polyps on white light imaging (WLI) and image-enhanced endoscopy (IEE) when assessed by CADx was 90.9% [95% confidence interval (CI) 77.3-100] and 95.8% [95% CI 87.5-100], 80% [95% CI 44.4-97.5] and 90.9% [95% CI 58.7-99.8], 84.8% [95% CI 72.7-97] and 84.6% [95%CI 71.8-94.9], respectively, compared to 48.1% [95%CI 37.7-59.1] and 72% [95% CI 62.5-81], 37.5% [95% CI 28.8-46.8] and 55% [95% CI 44.7-65.0], 53.7% [95% CI 44.2-63.2] and 66.7% [95% CI 59.7-73.3] when assessed by endoscopists. Concordance between histology and CADx-based post-polypectomy surveillance intervals was 93.02% on WLI and 96% on IEE. Conclusion AI-based optical diagnosis is promising and has the potential to be better than the performance of general endoscopists. We believe that AI can help make real-time optical diagnoses of polyps meeting the Preservation and Incorporation of Valuable endoscopic Innovations standards set by the American Society of Gastrointestinal Endoscopy.
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Affiliation(s)
| | | | | | - Masayoshi Yamada
- National Cancer Center HospitalEndoscopy DivisionTokyoJapan,National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan
| | - Hiroko Kondo
- National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan,RIKEN Center for Advanced Intelligence ProjectTokyoJapan
| | - Shijemi Yamada
- National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan,RIKEN Center for Advanced Intelligence ProjectTokyoJapan
| | - Ryuji Hamamoto
- National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan,RIKEN Center for Advanced Intelligence ProjectTokyoJapan
| | | | | | - Pradeep Bhandari
- Portsmouth Hospitals NHS TrustPortsmouthUK,University of Portsmouth, University HousePortsmouthUK
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The Efficacy of Tumor Characterization for Colorectal Lesions with Blue Light Imaging of a Compact Light-Emitting Diode Endoscopic System Compared to a Laser Endoscopic System: A Pilot Study. Gastroenterol Res Pract 2022; 2022:9998280. [PMID: 35462983 PMCID: PMC9019446 DOI: 10.1155/2022/9998280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 03/18/2022] [Accepted: 03/28/2022] [Indexed: 11/17/2022] Open
Abstract
Background: A compact and cost-effective light source-processor combined 3-color light-emitting diode (LED) endoscopic system (ELUXEO-Lite: EP-6000, Fujifilm Co., Tokyo) with a magnified colonoscope (EC-6600ZP, Fujifilm Co.) has been released. Aims: In this study, we analyzed the efficacy of this system for colorectal tumor characterization with magnified blue light imaging (BLI-LED) and image's subjective and objective evaluations, compared to a magnified blue laser imaging (BLI-LASER) using a standard LASER endoscopic system. Methods: We retrospectively reviewed 37 lesions observed with both BLI-LED and BLI-LASER systems from 2019 using the Japanese narrow band imaging classification. Two representative magnified images, one BLI-LED and one BLI-LASER, of the same area of a lesion were evaluated for diagnostic accuracy and visualization quality by three experts and three non-experts. Their color difference values (CDVs) and brightness values (BVs) were also calculated as objective indicators. Results: Among 37 lesions, mean tumor size was 18.9 ± 13.1 mm, and 21 lesions were nonpolypoid. Histopathology revealed 14 sessile serrated lesions, 7 adenomas, 12 high-grade dysplasias and T1a cancers, and 4 T1b cancers. The diagnostic accuracy rates of BLI-LED/BLI-LASER of experts and non-experts were 90.1% and 87.4% (p = 0.52) and 89.2% and 89.2% (p = 0.99). The percentages of instances where BLI-LED images were better, the two imaging types were equivalent, or BLI-LASER images were better were 16%/83%/1% for experts and 19%/58%/23% for non-experts (p < 0.001). CDVs and BVs between BLI-LED and BLI-LASER were not significantly different (CDVs: p = 0.653, BVs: p = 0.518). Conclusions: BLI-LED using the compact system was noninferior to BLI-LASER for colorectal tumor characterization and image quality.
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Cohen J. Top tips for using image-enhanced endoscopy during colonoscopy (with videos). Gastrointest Endosc 2022; 95:780-786. [PMID: 34890696 DOI: 10.1016/j.gie.2021.11.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 11/30/2021] [Indexed: 12/11/2022]
Affiliation(s)
- Jonathan Cohen
- Department of Medicine, NYU Grossman School of Medicine, New York, New York, USA
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10
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Li JW, Wang LM, Ang TL. Artificial intelligence-assisted colonoscopy: a narrative review of current data and clinical applications. Singapore Med J 2022; 63:118-124. [PMID: 35509251 PMCID: PMC9251247 DOI: 10.11622/smedj.2022044] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
Colonoscopy is the reference standard procedure for the prevention and diagnosis of colorectal cancer, which is a leading cause of cancer-related deaths in Singapore. Artificial intelligence systems are automated, objective and reproducible. Artificial intelligence-assisted colonoscopy has recently been introduced into clinical practice as a clinical decision support tool. This review article provides a summary of the current published data and discusses ongoing research and current clinical applications of artificial intelligence-assisted colonoscopy.
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Affiliation(s)
- James Weiquan Li
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- SingHealth Duke-NUS Medicine Academic Clinical Programme, Singapore
| | - Lai Mun Wang
- Pathology Section, Department of Laboratory Medicine, Changi General Hospital, Singapore
- SingHealth Duke-NUS Pathology Academic Clinical Programme, Singapore
| | - Tiing Leong Ang
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- SingHealth Duke-NUS Medicine Academic Clinical Programme, Singapore
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11
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Houwen BB, Vleugels JL, Pellisé M, Rivero-Sánchez L, Balaguer F, Bisschops R, Tejpar S, Repici A, Ramsoekh D, Jacobs MA, Schreuder RM, Kamiński MF, Rupińska M, Bhandari P, van Oijen MG, Koens L, Bastiaansen BA, Tytgat KM, Fockens P, Dekker E, Hazewinkel Y. Real-time diagnostic accuracy of blue light imaging, linked color imaging and white-light endoscopy for colorectal polyp characterization. Endosc Int Open 2022; 10:E9-E18. [PMID: 35047330 PMCID: PMC8759942 DOI: 10.1055/a-1594-1693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 07/29/2021] [Indexed: 11/25/2022] Open
Abstract
Background and study aims Fujifilm has developed a novel ELUXEO 7000 endoscope system that employs light-emitting diodes (LEDs) at four different wavelengths as light sources that enable blue light imaging (BLI), linked color imaging (LCI), and high-definition white-light endoscopy (HD-WLE). The aim of this study was to address the diagnostic accuracy of real-time polyp characterization using BLI, LCI and HD-WLE (ELUXEO 7000 endoscopy system). Patients methods This is a prespecified post-hoc analysis of a prospective study in which 22 experienced endoscopists (> 2,000 colonoscopies) from eight international centers participated. Using a combination of BLI, LCI, and HD-WLE, lesions were endoscopically characterized including a high- or low-confidence statement. Per protocol, digital images were created from all three imaging modalities. Histopathology was the reference standard. Endoscopists were familiar with polyp characterization, but did not take dedicated training for purposes of this study. Results Overall, 341 lesions were detected in 332 patients. Of the lesions, 269 histologically confirmed polyps with an optical diagnosis were included for analysis (165 adenomas, 27 sessile serrated lesions, and 77 hyperplastic polyps). Overall, polyp characterization was performed with high confidence in 82.9 %. The overall accuracy for polyp characterization was 75.1 % (95 % confidence interval [CI] 69.5-80.1 %), compared with an accuracy of 78.0 % (95 % CI 72.0-83.2 %) for high confidence assignments. The accuracy for endoscopic characterization for diminutive polyps was 74.7 % (95 %CI 68.4-80.3 %), compared with an accuracy of 78.2 % (95 % CI 71.4-84.0 %) for high-confidence assignments. Conclusions The diagnostic accuracy of BLI, LCI, and HD-WLE by experienced endoscopist for real-time polyp characterization seems limited (NCT03344289).
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Affiliation(s)
- Britt B.S.L. Houwen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location Academic Medical Center, University of Amsterdam, the Netherlands
| | - Jasper L.A. Vleugels
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location Academic Medical Center, University of Amsterdam, the Netherlands
| | - Maria Pellisé
- Department of Gastroenterology, Hospital Clinic of Barcelona, Barcelona, Spain,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut dʼInvestigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Liseth Rivero-Sánchez
- Department of Gastroenterology, Hospital Clinic of Barcelona, Barcelona, Spain,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut dʼInvestigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Francesc Balaguer
- Department of Gastroenterology, Hospital Clinic of Barcelona, Barcelona, Spain,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut dʼInvestigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Raf Bisschops
- Department of Gastroenterology and Hepatology, University Hospital Leuven, Leuven, Belgium
| | - Sabine Tejpar
- Department of Gastroenterology and Hepatology, University Hospital Leuven, Leuven, Belgium
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Rozzano, Italy,Department of Gastroenterology, Humanitas Clinical and Research Center – IRCCS, Rozzano, Italy
| | - D. Ramsoekh
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location VU University Medical Centre, VU University Amsterdam, Amsterdam, the Netherlands
| | - M. A.J.M Jacobs
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location VU University Medical Centre, VU University Amsterdam, Amsterdam, the Netherlands
| | - Ramon-Michel Schreuder
- Department of Gastroenterology and Hepatology, Catharina Hospital, Eindhoven, the Netherlands
| | - Michal F. Kamiński
- Department of Cancer Prevention, The Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Warsaw, Poland,Department of Gastroenterology, Hepatology and Clinical Oncology, Medical Center for Postgraduate Education, Warsaw, Poland
| | - Maria Rupińska
- Department of Cancer Prevention, The Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Warsaw, Poland,Department of Gastroenterology, Hepatology and Clinical Oncology, Medical Center for Postgraduate Education, Warsaw, Poland
| | - Pradeep Bhandari
- Department of Gastroenterology, Queen Alexandra Hospital, Portsmouth Hospitals NHS Trust, Portsmouth, United Kingdom
| | - M. G.H. van Oijen
- Department of Medical Oncology, Amsterdam University Medical Center, location Academic Medical Centre, University of Amsterdam, the Netherlands
| | - L. Koens
- Department of Pathology, Amsterdam University Medical Center, location Academic Medical Centre, University of Amsterdam, the Netherlands
| | - Barbara A.J. Bastiaansen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location Academic Medical Center, University of Amsterdam, the Netherlands
| | - K. M.A.J. Tytgat
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location Academic Medical Center, University of Amsterdam, the Netherlands
| | - Paul Fockens
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location Academic Medical Center, University of Amsterdam, the Netherlands
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location Academic Medical Center, University of Amsterdam, the Netherlands
| | - Yark Hazewinkel
- Department of Gastroenterology and Hepatology, Radboud University Nijmegen Medical Center, Radboud University of Nijmegen, Nijmegen, The Netherlands
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12
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Fonollà R, van der Zander QEW, Schreuder RM, Subramaniam S, Bhandari P, Masclee AAM, Schoon EJ, van der Sommen F, de With PHN. Automatic image and text-based description for colorectal polyps using BASIC classification. Artif Intell Med 2021; 121:102178. [PMID: 34763800 DOI: 10.1016/j.artmed.2021.102178] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/01/2021] [Accepted: 09/21/2021] [Indexed: 12/18/2022]
Abstract
Colorectal polyps (CRP) are precursor lesions of colorectal cancer (CRC). Correct identification of CRPs during in-vivo colonoscopy is supported by the endoscopist's expertise and medical classification models. A recent developed classification model is the Blue light imaging Adenoma Serrated International Classification (BASIC) which describes the differences between non-neoplastic and neoplastic lesions acquired with blue light imaging (BLI). Computer-aided detection (CADe) and diagnosis (CADx) systems are efficient at visually assisting with medical decisions but fall short at translating decisions into relevant clinical information. The communication between machine and medical expert is of crucial importance to improve diagnosis of CRP during in-vivo procedures. In this work, the combination of a polyp image classification model and a language model is proposed to develop a CADx system that automatically generates text comparable to the human language employed by endoscopists. The developed system generates equivalent sentences as the human-reference and describes CRP images acquired with white light (WL), blue light imaging (BLI) and linked color imaging (LCI). An image feature encoder and a BERT module are employed to build the AI model and an external test set is used to evaluate the results and compute the linguistic metrics. The experimental results show the construction of complete sentences with an established metric scores of BLEU-1 = 0.67, ROUGE-L = 0.83 and METEOR = 0.50. The developed CADx system for automatic CRP image captioning facilitates future advances towards automatic reporting and may help reduce time-consuming histology assessment.
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Affiliation(s)
- Roger Fonollà
- Department of Electrical Engineering, Video Coding and Architectures (VCA), Eindhoven University of Technology, Eindhoven, Noord-Brabant, the Netherlands.
| | - Quirine E W van der Zander
- Division of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht, the Netherlands; GROW, School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands
| | - Ramon M Schreuder
- Department of Gastroenterology and Hepatology, Catharina Hospital, Eindhoven, Noord-Brabant, the Netherlands
| | - Sharmila Subramaniam
- Department of Gastroenterology, Portsmouth Hospitals University NHS Trust, Portsmouth, United Kingdom
| | - Pradeep Bhandari
- Department of Gastroenterology, Portsmouth Hospitals University NHS Trust, Portsmouth, United Kingdom
| | - Ad A M Masclee
- Division of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht, the Netherlands; NUTRIM, School of Nutrition & Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Erik J Schoon
- Department of Gastroenterology and Hepatology, Catharina Hospital, Eindhoven, Noord-Brabant, the Netherlands
| | - Fons van der Sommen
- Department of Electrical Engineering, Video Coding and Architectures (VCA), Eindhoven University of Technology, Eindhoven, Noord-Brabant, the Netherlands
| | - Peter H N de With
- Department of Electrical Engineering, Video Coding and Architectures (VCA), Eindhoven University of Technology, Eindhoven, Noord-Brabant, the Netherlands
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13
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Li JW, Ang TL. Colonoscopy and artificial intelligence: Bridging the gap or a gap needing to be bridged? Artif Intell Gastrointest Endosc 2021; 2:36-49. [DOI: 10.37126/aige.v2.i2.36] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 03/27/2021] [Accepted: 04/20/2021] [Indexed: 02/06/2023] Open
Abstract
Research in artificial intelligence (AI) in gastroenterology has increased over the last decade. Colonoscopy represents the most widely published field with regards to its use in gastroenterology. Most studies to date center on polyp detection and characterization, as well as real-time evaluation of adequacy of mucosal exposure for inspection. This review article discusses how advances in AI has bridged certain gaps in colonoscopy. In addition, the gaps formed with the development of AI that currently prevent its routine use in colonoscopy will be explored.
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Affiliation(s)
- James Weiquan Li
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore 529889, Singapore
| | - Tiing Leong Ang
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore 529889, Singapore
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14
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He Z, Wang P, Liang Y, Fu Z, Ye X. Clinically Available Optical Imaging Technologies in Endoscopic Lesion Detection: Current Status and Future Perspective. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:7594513. [PMID: 33628407 PMCID: PMC7886528 DOI: 10.1155/2021/7594513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 01/13/2021] [Accepted: 01/27/2021] [Indexed: 01/02/2023]
Abstract
Endoscopic optical imaging technologies for the detection and evaluation of dysplasia and early cancer have made great strides in recent decades. With the capacity of in vivo early detection of subtle lesions, they allow modern endoscopists to provide accurate and effective optical diagnosis in real time. This review mainly analyzes the current status of clinically available endoscopic optical imaging techniques, with emphasis on the latest updates of existing techniques. We summarize current coverage of these technologies in major hospital departments such as gastroenterology, urology, gynecology, otolaryngology, pneumology, and laparoscopic surgery. In order to promote a broader understanding, we further cover the underlying principles of these technologies and analyze their performance. Moreover, we provide a brief overview of future perspectives in related technologies, such as computer-assisted diagnosis (CAD) algorithms dealing with exploring endoscopic video data. We believe all these efforts will benefit the healthcare of the community, help endoscopists improve the accuracy of diagnosis, and relieve patients' suffering.
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Affiliation(s)
- Zhongyu He
- Biosensor National Special Laboratory, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Peng Wang
- Biosensor National Special Laboratory, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Yuelong Liang
- Department of General Surgery, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou 310016, China
| | - Zuoming Fu
- Biosensor National Special Laboratory, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Xuesong Ye
- Biosensor National Special Laboratory, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
- State Key Laboratory of CAD and CG, Zhejiang University, Hangzhou 310058, China
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15
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Rondonotti E, Hassan C, Andrealli A, Paggi S, Amato A, Scaramella L, Repici A, Radaelli F. Clinical Validation of BASIC Classification for the Resect and Discard Strategy for Diminutive Colorectal Polyps. Clin Gastroenterol Hepatol 2020; 18:2357-2365.e4. [PMID: 31923641 DOI: 10.1016/j.cgh.2019.12.028] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 12/23/2019] [Accepted: 12/25/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Blue-light imaging (BLI) is a chromoendoscopy technique that uses direct (not filtered) emission of blue light with short wavelength (410 nm) to increase visibility of microvascular pattern and superficial mucosa. A BLI-based classification system for colorectal polyps (also called BLI Adenomas Serrated International Classification, BASIC) has been created and was validated using still images or short videos. We aimed to validate BASIC in a clinical practice setting, using thresholds recommended by the American Society for Gastrointestinal Endoscopy for the resect and discard strategy as the reference standard. METHODS We studied 333 patients (mean age, 62.7±8.1 y; 176 men) who underwent screening colonoscopy from January through July 2019. Six endoscopists trained in BASIC participated in the study. All detected diminutive polyps were characterized by real-time BLI and categorized as adenoma or non-adenoma according to BASIC. All polyps were removed and evaluated by histopathology. The BLI-directed surveillance intervals (based on high-confidence characterization of polyps 5 mm or smaller and pathology feature for others) were compared with histology-directed surveillance intervals, according to United States Multi-society Task Force and European Society of Gastrointestinal Endoscopy recommendations. We calculated negative-predictive values of optical real-time analysis of diminutive rectosigmoid adenomas. RESULTS When we applied BASIC, 748 polyps smaller than 5 mm were categorized with 89% accuracy (95% CI, 85.9%-90.6%). BLI-directed surveillance was correct for 90% of patients according to the United States Multi-society task force criteria (95% CI, 86%-93%) and for 96% of patients according to European Society of Gastrointestinal Endoscopy criteria (95% CI, 93%-97%). The negative-predictive value for 302 polyps smaller than 5 mm, located in the rectosigmoid colon and evaluated with high confidence, based on histologic features of adenomatous polyps, was 91% (95% CI, 85%-95%). CONCLUSIONS Our analysis of data from 333 patients undergoing screen colonoscopies supports the validity of BASIC discriminating diminutive colorectal polyps with histologic features of adenomas from non-adenomas. This allows for the implementation of the resect and discard strategy based on BLI in clinical practice. ClinicalTrials.gov no: NCT03746171.
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Affiliation(s)
| | - Cesare Hassan
- Digestive Endoscopy, Nuovo Regina Margherita Hospital, Rome, Italy
| | | | - Silvia Paggi
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | - Arnaldo Amato
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | - Lucia Scaramella
- Gastroenterology Unit, Valduce Hospital, Como, Italy; Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Milano, Italy
| | - Alessandro Repici
- Digestive Endoscopy Unit, Division of Gastroenterology, Humanitas Clinical and Research Center and Humanitas University, Rozzano, Italy
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16
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A CNN CADx System for Multimodal Classification of Colorectal Polyps Combining WL, BLI, and LCI Modalities. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10155040] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Colorectal polyps are critical indicators of colorectal cancer (CRC). Blue Laser Imaging and Linked Color Imaging are two modalities that allow improved visualization of the colon. In conjunction with the Blue Laser Imaging (BLI) Adenoma Serrated International Classification (BASIC) classification, endoscopists are capable of distinguishing benign and pre-malignant polyps. Despite these advancements, this classification still prevails a high misclassification rate for pre-malignant colorectal polyps. This work proposes a computer aided diagnosis (CADx) system that exploits the additional information contained in two novel imaging modalities, enabling more informative decision-making during colonoscopy. We train and benchmark six commonly used CNN architectures and compare the results with 19 endoscopists that employed the standard clinical classification model (BASIC). The proposed CADx system for classifying colorectal polyps achieves an area under the curve (AUC) of 0.97. Furthermore, we incorporate visual explanatory information together with a probability score, jointly computed from White Light, Blue Laser Imaging, and Linked Color Imaging. Our CADx system for automatic polyp malignancy classification facilitates future advances towards patient safety and may reduce time-consuming and costly histology assessment.
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17
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Yoshida N, Dohi O, Inoue K, Sugino S, Yasuda R, Hirose R, Naito Y, Inada Y, Murakami T, Ogiso K, Morinaga Y, Kishimoto M, Itoh Y. The efficacy of tumor characterization and tumor detectability of linked color imaging and blue laser imaging with an LED endoscope compared to a LASER endoscope. Int J Colorectal Dis 2020; 35:815-825. [PMID: 32088738 DOI: 10.1007/s00384-020-03532-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/07/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVES An endoscope with a light-emitting diode (LED) light source which has a 2-mm close-distance observation function without magnification, has been marketed, enabling linked color imaging (LCI) and blue laser imaging (BLI) for tumor detection and characterization. We analyzed the efficacy of a LED endoscope compared to a LASER endoscope. METHODS We retrospectively reviewed 272 lesions observed using the LED endoscopic system (Fujifilm Co., Tokyo, Japan) from May 2018 to September 2019. The Japanese NBI Classification was used for tumor characterization. We analyzed the diagnostic accuracy and confidence level. Sixty-one lesions observed with both the LED and magnified LASER endoscopes were also analyzed to compare the diagnostic accuracy. Regarding the tumor detectability, we calculated color difference values (CDVs) and brightness values (BVs) of white-light imaging, BLI, and LCI modes between the two endoscopes for each tumor. RESULTS The mean polyp size was 9.2 ± 11.3 mm. Histology showed 71 sessile serrated lesions, 193 adenoma and high-grade dysplasias, and 8 T1 cancers. The diagnostic accuracy of tumors ≥ 10 and < 10 mm was 72.0% and 92.9% (p < 0.001), respectively and the high confidence rate was 93.8%. The diagnostic accuracy of LED (77.0%) was a little higher than that of LASER without magnification (65.6%, p = 0.16) but was not inferior to that of LASER with magnification (82.0%, p = 0.50). The respective CDVs of LED and LASER endoscopes were 20.6 ± 11.2 and 21.6 ± 11.2 for LCI (p = 0.30), and the respective BVs were 210.0 ± 24.2 and 175.9 ± 21.1 (p < 0.001). CONCLUSIONS A LED endoscope with close-distance observation improved tumor detection and characterization due to high brightness.
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Affiliation(s)
- Naohisa Yoshida
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
| | - Osamu Dohi
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Ken Inoue
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Satoshi Sugino
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Ritsu Yasuda
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Ryohei Hirose
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yuji Naito
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yutaka Inada
- Department of Gastroenterology
- , Fukuchiyama City Hospital, Kyoto, Japan
| | - Takaaki Murakami
- Department of Gastroenterology, JCHO Kyoto Kuramaguchi Medical Center, Kyoto, Japan
| | - Kiyoshi Ogiso
- Department of Gastroenterology, Osaka General Hospital of West Japan Railway Company, Osaka, Japan
| | - Yukiko Morinaga
- Department of Surgical Pathology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Mitsuo Kishimoto
- Department of Surgical Pathology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yoshito Itoh
- Department of Molecular Gastroenterology and Hepatology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
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18
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Djinbachian R, Dubé AJ, von Renteln D. Optical Diagnosis of Colorectal Polyps: Recent Developments. ACTA ACUST UNITED AC 2019; 17:99-114. [PMID: 30746593 DOI: 10.1007/s11938-019-00220-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW Optical diagnosis of diminutive colorectal polyps has been recently proposed as an alternative to histopathologic diagnosis. Recent developments in imaging techniques, new classification systems, and the use of artificial intelligence have allowed for increased viability of optical diagnosis. This review provides an up-to-date overview of optical diagnosis recommendations, classifications, outcomes, and recent developments. RECENT FINDINGS There are currently seven major classification systems and three major society recommendations for quality benchmarks for optical diagnosis of diminutive polyps. The NICE classification has been extensively studied and meets quality benchmarks for most imaging techniques but does not allow for the diagnosis of sessile serrated polyps (SSPs). The SIMPLE classification has met quality benchmarks for NBI and i-Scan and allows for the diagnosis of SSPs. Other classification systems need to be further studied to validate effectiveness. Computer-assisted diagnosis of colorectal polyps is a very promising recent development with first studies showing that society-recommended quality benchmarks for real-time colonoscopies on patients are being met. Limitations include a non-negligible percentage of failure to diagnose, low specificity, and low number of real-time diagnostic studies. More research needs to be performed to further understand the value of artificial intelligence for optical polyp diagnosis. Optical diagnosis of diminutive colorectal polyps is currently a viable strategy for experienced endoscopists using validated classifications and imaging-enhanced endoscopy. Artificial intelligence-based diagnosis could make optical diagnosis widely applicable but is currently in its early developmental stage.
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Affiliation(s)
- Roupen Djinbachian
- Faculty of Medicine, University of Montreal, Montreal, Canada.,Montreal University Hospital Research Center (CRCHUM), Montreal, Canada
| | - Anne-Julie Dubé
- Faculty of Medicine, University of Montreal, Montreal, Canada.,Montreal University Hospital Research Center (CRCHUM), Montreal, Canada
| | - Daniel von Renteln
- Montreal University Hospital Research Center (CRCHUM), Montreal, Canada. .,Division of Gastroenterology, Montreal University Hospital Center (CHUM), Montreal, Canada.
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