Artificial Intelligence enabled histological prediction of remission or activity and clinical outcomes in ulcerative colitis

Journal article

Iacucci, M., Parigi, T.L., del Amor, R., Meseguer, P., Mandelli, G., Bozzola, A., Bazarova, A., Bhandari, P., Bisschops, R., Danese, S., De Hertogh, G., Ferraz, J.G., Goetz, M., Grisan, E., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Royset, E.S., Tontini, G.E., Vath, M., Zardo, D., Ghosh, S., Naranjo, V. and Villanacci, V. (2023). Artificial Intelligence enabled histological prediction of remission or activity and clinical outcomes in ulcerative colitis. Gastroenterology. https://doi.org/10.1053/j.gastro.2023.02.031
AuthorsIacucci, M., Parigi, T.L., del Amor, R., Meseguer, P., Mandelli, G., Bozzola, A., Bazarova, A., Bhandari, P., Bisschops, R., Danese, S., De Hertogh, G., Ferraz, J.G., Goetz, M., Grisan, E., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Royset, E.S., Tontini, G.E., Vath, M., Zardo, D., Ghosh, S., Naranjo, V. and Villanacci, V.
Abstract

Background
Microscopic inflammation has significant prognostic value in ulcerative colitis (UC); however, its assessment is complex with high interobserver variability. We aimed to develop and validate an artificial intelligence (AI) Computer-Aided Diagnosis System to evaluate UC biopsies and predict prognosis.
Methods
535 digitalized biopsies (273 patients) were graded according to the PICaSSO Histologic Remission Index (PHRI), Robarts’ (RHI), and Nancy Histological Index (NHI). A convolutional neural network classifier was trained to distinguish remission from activity on a subset of 118 biopsies, calibrated on 42 and tested on 375. The model was additionally tested to predict the corresponding endoscopic assessment and occurrence of flares at 12 months. The system output was compared with human assessment. Diagnostic performance was reported as sensitivity, specificity; prognostic prediction through Kaplan-Meier and hazard ratios of flares between active and remission groups. We externally validated the model in 154 biopsies (58 patients) with similar characteristics but more histologically active patients.
Results
The system distinguished histological activity/remission with sensitivity and specificity of 89% and 85% (PHRI), 94% and 76% (RHI), and 89% and 79% (NHI). The model predicted the corresponding endoscopic remission/activity with 79% and 82% accuracy for UCEIS and PICaSSO, respectively. The hazard ratio for disease flare-up between histological activity/remission groups according to pathologist-assessed PHRI was 3.56, and 4.64 for AI-assessed PHRI. Both histology and outcome prediction were confirmed in the external validation cohort.
Conclusion
We developed and validated an AI model that distinguishes histological remission/activity in biopsies of UC and predicts flare-ups. This can expedite, standardize and enhance histological assessment in practice and trials.

KeywordsUlcerative Colitis ; Picasso Histologic Remission Index ; Computer-aided diagnosis ; Convolutional Neural Network ; Robarts Histopathology index
Year2023
JournalGastroenterology
PublisherElsevier
ISSN0016-5085
Digital Object Identifier (DOI)https://doi.org/10.1053/j.gastro.2023.02.031
Publication dates
Print03 Mar 2023
Publication process dates
Accepted15 Feb 2023
Deposited14 Mar 2023
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Grisan, E., Zandon`a, A. and Di Camillo, B. (2019). Deep Convolutional Neural Network for Survival Estimation of Amyotrophic Lateral Sclerosis patients. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium 24 - 26 Apr 2019 i6doc.
Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal
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.2018.2823763
Sparse 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_15
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
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-x
Boosting 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.2017.2689164
Detection 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/10.1117/12.2250818
Improving 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/10.1117/12.2250195
Superpixel-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/10.1117/12.2254187
Boosted 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/10.1117/12.2250370
Cortical 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.2017.7950637
From 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.2017.7950661
Grade 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
Bayesian Quantification of Contrast-Enhanced Ultrasound Images with Adaptive Inclusion of an Irreversible Component
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Bayesian Quantification of Contrast-Enhanced Ultrasound Images with Adaptive Inclusion of an Irreversible Component. IEEE Transactions on Medical Imaging. 36, pp. 1027-1036. https://doi.org/10.1109/TMI.2016.2637698
Tcf7l2 plays pleiotropic roles in the control of glucose homeostasis, pancreas morphology, vascularization and regeneration
Facchinello, N, Tarifeño-Saldivia, E, Grisan, E, Schiavone, M, Peron, M, Mongera, A, Ek, O, Schmitner, N, Meyer, D, Peers, B, Tiso, N and Argenton, F (2017). Tcf7l2 plays pleiotropic roles in the control of glucose homeostasis, pancreas morphology, vascularization and regeneration. Scientific Reports. 7. https://doi.org/10.1038/s41598-017-09867-x
Growth abnormalities of fetuses and infants
Cosmi, E, Grisan, E, Fanos, V, Rizzo, G, Sivanandam, S and Visentin, S (2017). Growth abnormalities of fetuses and infants. BioMed Research International. 2017. https://doi.org/https://www.doi.org/10.1155/2017/3191308
A possible new approach in the prediction of late gestational hypertension: The role of the fetal aortic intima-media thickness
Visentin, S, Londero, AP, Camerin, M, Grisan, E and Cosmi, E (2017). A possible new approach in the prediction of late gestational hypertension: The role of the fetal aortic intima-media thickness. Medicine (United States). 96. https://doi.org/https://www.doi.org/10.1097/MD.0000000000005515
Automatic classification of small bowel mucosa alterations in celiac disease for confocal laser endomicroscopy
Boschetto, D, Di Claudio, G, Mirzaei, H, Leong, R and Grisan, E (2016). Automatic classification of small bowel mucosa alterations in celiac disease for confocal laser endomicroscopy. Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, United States 27 Feb - 03 Mar 2016 SPIE. https://doi.org/10.1117/12.2217183
Automatic classification of endoscopic images for premalignant conditions of the esophagus
Boschetto, D, Gambaretto, G and Grisan, E (2016). Automatic classification of endoscopic images for premalignant conditions of the esophagus. Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, United States 27 Feb - 03 Mar 2016 https://doi.org/10.1117/12.2216826
Superpixel-based automatic segmentation of villi in confocal endomicroscopy
Boschetto, D, Mirzaei, H, Leong, RWL and Grisan, E (2016). Superpixel-based automatic segmentation of villi in confocal endomicroscopy. 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). Las Vegas, NV, USA 24 - 27 Feb 2016 pp. 168-171 https://doi.org/10.1109/BHI.2016.7455861
Quantification of kidneys from 3D ultrasound in pediatric hydronephrosis
Cerrolaza, J.J., Grisan, E., Safdar, N., Myers, E., Jago, J., Peters, C.A. and Linguraru, M.G. (2015). Quantification of kidneys from 3D ultrasound in pediatric hydronephrosis. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/embc.2015.7318324