A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis
Conference paper
Iacucci, M., Cannatelli, R., Parigi, T.L., Buda, A., Labarile, N., Nardone, O.M., Tontini, G.E., Rimondi, A., Bazarova, A., Bhandari, P., Bisschops, R., De Hertogh, G., del Amor, R., Ferraz, J.G, Goetz, M., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Naranjo, V., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Røyset, E.S, Vieth, M., Villanacci, V., Zardo, D., Ghosh, S. and Grisan, E. (2022). A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis. ESGE Days 2022. 28 Apr 2022 Georg Thieme Verlag KG. https://doi.org/10.1055/s-0042-1744593
| Authors | Iacucci, M., Cannatelli, R., Parigi, T.L., Buda, A., Labarile, N., Nardone, O.M., Tontini, G.E., Rimondi, A., Bazarova, A., Bhandari, P., Bisschops, R., De Hertogh, G., del Amor, R., Ferraz, J.G, Goetz, M., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Naranjo, V., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Røyset, E.S, Vieth, M., Villanacci, V., Zardo, D., Ghosh, S. and Grisan, E. |
|---|---|
| Type | Conference paper |
| Abstract | Aims We aimed to develop an artificial intelligence (AI) system to assess endoscopic remission (ER) and histologic remission (HR) of ulcerative colitis (UC) in both white light (WL, using Ulcerative Colitis Endoscopic Index of Severity [UCEIS]) and virtual chromoendoscopy (VCE, using Paddington International Virtual ChromoendoScopy ScOre [PICaSSO]). Methods A convolutional neural network (CNN) was developed based on 559 endoscopy videos, from 302 UC patients prospectively included in the PICaSSO multicentre study. The videos were divided in training (254), validation (62), and testing (243), and comprised 67280 frames in total. The CNN was trained to predict both ER (defined as UCEIS≤1 in WL and as PICaSSO≤3 in VCE) and HR (defined as Robarts Histological Index ≤ 3 with no neutrophils in lamina propria or epithelium) in video clips. Results In the validation cohort, our system predicted ER in WL videos with 82% sensitivity, 94% specificity and an area under the ROC curve (AUROC) of 0.92. In VCE, sensitivity was 74%, specificity 95%, and AUROC 0.95. In the testing cohort, the diagnostic performance remained similar. The diagnostic performance for the prediction of HR in the validation set had sensitivity, specificity, and accuracy of 92%, 83%, and 85%, respectively, using VCE; and 83%, 87%, and 86% respectively, with WL. In the testing set, these metrics declined modestly while remaining good. Of note, the algorithm’s prediction of histology was similar with VCE and WL videos. Conclusions Our AI system accurately recognizes ER in videos and predicts HR equally well. |
| Year | 2022 |
| Publisher | Georg Thieme Verlag KG |
| Journal citation | 54, pp. 18-19 |
| ISSN | 1438-8812 |
| Digital Object Identifier (DOI) | https://doi.org/10.1055/s-0042-1744593 |
| Web address (URL) | https://www.thieme-connect.de/products/ejournals/abstract/10.1055/s-0042-1744593 |
| Accepted author manuscript | License File Access Level Open |
| Publication dates | |
| Online | 14 Apr 2022 |
| Publication process dates | |
| Deposited | 13 Jul 2022 |
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| A VIRTUAL CHROMOENDOSCOPY ARTIFICIAL INTELLIGENCE SYSTEM TO DETECT ENDOSCOPIC AND HISTOLOGIC REMISSION IN ULCERATIVE COLITIS.docx | ||
| License: CC BY 4.0 | ||
| File access level: Open | ||
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Gadaleta, M., Facchinetti, A., Grisan, E. and Rossi, M. (2019). Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal. IEEE Journal of Biomedical and Health Informatics. 23 (2). https://doi.org/10.1109/JBHI.2018.2823763Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves
Stanziola, A., Toulemonde, M., Papadopoulou, V., Corbett, R., Duncan, N., Grisan, E. and Tang, M-X. (2019). Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves. IEEE International Ultrasonics Symposium 2019. Glasgow 09 2009 - 06 Oct 2019 Institute of Electrical and Electronics Engineers (IEEE).Super resolution ultrasound image filtering with machine learning to reduce the localization error
Harput, S., Fong, L.H., Stanziola, A., Zhang, G., Toulemonde, M., Zhou, J., Christensen-Jeffries, K., Brown, J., Eckersley, R., Grisan, E., Dunsby, C. and Tang, M. (2019). Super resolution ultrasound image filtering with machine learning to reduce the localization error. IEEE International Ultrasonics Symposium 2019. Glasgow 09 2009 - 06 Oct 2019 Institute of Electrical and Electronics Engineers (IEEE).Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound
Savioli, N., Visentin, S., Cosmi, E., Grisan, E., Lamata, P. and Montana, G. (2018). Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. Artificial Neural Networks and Machine Learning – ICANN 2018. Rhodes, Greece 04 - 07 Oct 2018 Springer. https://doi.org/10.1007/978-3-030-01421-6_15Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints
Fiocco, U, Stramare, R, Martini, V, Coran, A, Caso, F, Costa, L, Felicetti, M, Rizzo, G, Tonietto, M, Scanu, A, Oliviero, F, Raffeiner, B, Vezzù, M, Lunardi, F, Scarpa, R, Sacerdoti, D, Rubaltelli, L, Punzi, L, Doria, A and Grisan, E (2017). Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints. Clinical Rheumatology. 36 (2), pp. 391-399. https://doi.org/10.1007/s10067-016-3500-xBoosting the Battery Life of Wearables for Health Monitoring Through the Compression of Biosignals
Hooshmand, M, Zordan, D, Del Testa, D, Grisan, E and Rossi, M (2017). Boosting the Battery Life of Wearables for Health Monitoring Through the Compression of Biosignals. IEEE Internet of Things Journal. 4, pp. 1647-1662. https://doi.org/10.1109/JIOT.2017.2689164Detection of a slow-flow component in contrast-enhanced ultrasound of the synovia for the differential diagnosis of arthritis
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Detection of a slow-flow component in contrast-enhanced ultrasound of the synovia for the differential diagnosis of arthritis. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250818Improving the quantification of contrast enhanced ultrasound using a Bayesian approach
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Improving the quantification of contrast enhanced ultrasound using a Bayesian approach. SPIE Medical Imaging. Orlando, FL , USA 16 2016 - 11 Feb 2017 SPIE. https://doi.org/10.1117/12.2250195Superpixel-based classification of gastric chromoendoscopy images
Boschetto, D and Grisan, E (2017). Superpixel-based classification of gastric chromoendoscopy images. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2254187Boosted learned kernels for data-driven vesselness measure
Grisan, E (2017). Boosted learned kernels for data-driven vesselness measure. Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101370Z (2017). Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250370Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling
Palombit, A, Castellaro, M, Calabrese, M, Romualdi, C, Pizzini, FB, Montemezzi, S, Grisan, E and Bertoldo, A (2017). Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 18 - 21 Apr 2017 pp. 792-795 https://doi.org/10.1109/ISBI.2017.7950637From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis
Grisan, E, Rizzo, G, Tonietto, M, Coran, A, Raffeiner, B, Scanu, A, Martini, V, Stramare, R and Fiocco, U (2017). From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 17 - 21 Apr 2017 Institute of Electrical and Electronics Engineers (IEEE). pp. 899-902 https://doi.org/10.1109/ISBI.2017.7950661Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α
Raffeiner, B, Grisan, E, Botsios, C, Stramare, R, Rizzo, G, Bernardi, L, Punzi, L, Ometto, F and Doria, A (2017). Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α. Rheumatology (United Kingdom). 56, pp. 1320-1325. https://doi.org/10.1093/rheumatology/kex084