TY - JOUR
T1 - PICaSSO Histologic Remission Index (PHRI) in ulcerative colitis
T2 - Development of a novel simplified histological score for monitoring mucosal healing and predicting clinical outcomes and its applicability in an artificial intelligence system
AU - Gui, Xianyong
AU - Bazarova, Alina
AU - Amor, Roc o.Del
AU - Vieth, Michael
AU - Hertogh, Gert De
AU - Villanacci, Vincenzo
AU - Zardo, Davide
AU - Parigi, Tommaso Lorenzo
AU - Røyset, Elin Synnøve
AU - Shivaji, Uday N.
AU - Monica, Melissa Anna Teresa
AU - Mandelli, Giulio
AU - Bhandari, Pradeep
AU - Danese, Silvio
AU - Ferraz, Jose G.
AU - Hayee, Bu hussain
AU - Lazarev, Mark
AU - Parra-Blanco, Adolfo
AU - Pastorelli, Luca
AU - Panaccione, Remo
AU - Rath, Timo
AU - Tontini, Gian Eugenio
AU - Kiesslich, Ralf
AU - Bisschops, Raf
AU - Grisan, Enrico
AU - Naranjo, Valery
AU - Ghosh, Subrata
AU - Marietta Iacucci, Marietta
N1 - Publisher Copyright:
© 2022 BMJ Publishing Group. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Histological remission is evolving as an important treatment target in UC. We aimed to develop a simple histological index, aligned to endoscopy,correlated with clinical outcomes, and suited to apply to an artificial intelligence (AI) system to evaluate inflammatory activity. Methods Using a set of 614 biopsies from 307 patients with UC enrolled into a prospective multicentre study, we developed the Paddington International virtual ChromoendoScopy ScOre (PICaSSO) Histologic Remission Index (PHRI).Agreement with multiple other histological indices and validation for inter-reader reproducibility were assessed. Finally, to implement PHRI into a computer-Aided diagnosis system, we trained and tested a novel deep learning strategy based on a CNN architecture to detect neutrophils, calculate PHRI and identify active from quiescent UC using a subset of 138 biopsies. Results PHRI is strongly correlated with endoscopic scores (Mayo Endoscopic Score and UC Endoscopic Index of Severity and PICaSSO) and with clinical outcomes (hospitalisation, colectomy and initiation or changes in medical therapy due to UC flare-up). A PHRI score of 1 could accurately stratify patients risk of adverse outcomes (hospitalisation, colectomy and treatment optimisation due to flare-up) within 12 months. Our inter-reader agreement was high (intraclass correlation 0.84). Our preliminary AI algorithm differentiated active from quiescent UC with 78% sensitivity, 91.7% specificity and 86% accuracy. Conclusions PHRI is a simple histological index in UC, and it exhibits the highest correlation with endoscopic activity and clinical outcomes. A PHRI-based AI system was accurate in predicting histological remission.
AB - Histological remission is evolving as an important treatment target in UC. We aimed to develop a simple histological index, aligned to endoscopy,correlated with clinical outcomes, and suited to apply to an artificial intelligence (AI) system to evaluate inflammatory activity. Methods Using a set of 614 biopsies from 307 patients with UC enrolled into a prospective multicentre study, we developed the Paddington International virtual ChromoendoScopy ScOre (PICaSSO) Histologic Remission Index (PHRI).Agreement with multiple other histological indices and validation for inter-reader reproducibility were assessed. Finally, to implement PHRI into a computer-Aided diagnosis system, we trained and tested a novel deep learning strategy based on a CNN architecture to detect neutrophils, calculate PHRI and identify active from quiescent UC using a subset of 138 biopsies. Results PHRI is strongly correlated with endoscopic scores (Mayo Endoscopic Score and UC Endoscopic Index of Severity and PICaSSO) and with clinical outcomes (hospitalisation, colectomy and initiation or changes in medical therapy due to UC flare-up). A PHRI score of 1 could accurately stratify patients risk of adverse outcomes (hospitalisation, colectomy and treatment optimisation due to flare-up) within 12 months. Our inter-reader agreement was high (intraclass correlation 0.84). Our preliminary AI algorithm differentiated active from quiescent UC with 78% sensitivity, 91.7% specificity and 86% accuracy. Conclusions PHRI is a simple histological index in UC, and it exhibits the highest correlation with endoscopic activity and clinical outcomes. A PHRI-based AI system was accurate in predicting histological remission.
UR - http://www.scopus.com/inward/record.url?scp=85128488166&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85128488166&partnerID=8YFLogxK
U2 - 10.1136/gutjnl-2021-326376
DO - 10.1136/gutjnl-2021-326376
M3 - Article
C2 - 35173041
AN - SCOPUS:85128488166
SN - 0017-5749
VL - 71
SP - 889
EP - 898
JO - Gut
JF - Gut
IS - 5
ER -