Artificial Intelligence - SARS-CoV-2 Risk Evaluation

Covid19 Clinical Trial

— AI-SCoRE  

Official title:

Artificial Intelligence - SARS-CoV-2 Risk Evaluation

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04834934
• Other study ID #: AI-SCoRE
• Status: Recruiting
• Start date: February 16, 2020
• Est. completion date: June 2021

Study information

• Verified date: April 2021
• Source: IRCCS San Raffaele
• Contact: Antonio Esposito, MD
• Phone: +390226436102
• Email: esposito.antonio[@]unisr.it
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The management of COVID-19 patients in overwhelmed hospital facing the pandemic is a clinical challenge.

The improvement of decision making may allow a better allocation of available resources and a better treatment of patients at higher risk.

Chest CT has been widely adopted for COVID-19 pneumonia diagnosis. Several experiences documented the capability of Artificial Intelligence to improve and fasten COVID-19 pneumonia detection, mainly using chest X-ray.

Aim of the present study was to develop and validate an Artificial Intelligence approach integrating clinical and imaging data (automatically extracted through the adoption of dedicated neural networks) for the creation of a cloud platform capable of performing automatic patients risk stratification. Such an approach could be used for triage of COVID-19 patients in the emergency department, with the aim to improve healthcare personnel decision-making and allocation of resources during health emergencies.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 2000
• Est. completion date: June 2021
• Est. primary completion date: September 30, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 100 Years

Eligibility

Inclusion Criteria:

• confirmed SARS-CoV-2 infection with RT-PCR

• non contrast chest CT scan performed within 72 hours after admission to the emergency department

Exclusion Criteria:

• age < 18 ys

Related Conditions & MeSH terms

• Covid19

Locations

Country	Name	City	State
Italy	IRCCS San Raffaele	Milano

Sponsors (8)

Lead Sponsor	Collaborator
IRCCS San Raffaele	ASST Bergamo Est, Centro Cardiologico Monzino, Microsoft Corporation, NVIDIA Corporation, Orobix Srl, PORINI Srl, Regione Lombardia

Country where clinical trial is conducted

Italy, 

References & Publications (19)

Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, Tao Q, Sun Z, Xia L. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology. 2020 Aug;296(2):E32-E40. doi: 10.1148/radiol.2020200642. Epub 2020 Feb 26. — View Citation

Bai HX, Wang R, Xiong Z, Hsieh B, Chang K, Halsey K, Tran TML, Choi JW, Wang DC, Shi LB, Mei J, Jiang XL, Pan I, Zeng QH, Hu PF, Li YH, Fu FX, Huang RY, Sebro R, Yu QZ, Atalay MK, Liao WH. Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT. Radiology. 2020 Sep;296(3):E156-E165. doi: 10.1148/radiol.2020201491. Epub 2020 Apr 27. Erratum in: Radiology. 2021 Apr;299(1):E225. — View Citation

Cheng FY, Joshi H, Tandon P, Freeman R, Reich DL, Mazumdar M, Kohli-Seth R, Levin M, Timsina P, Kia A. Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients. J Clin Med. 2020 Jun 1;9(6). pii: E1668. doi: 10.3390/jcm9061668. — View Citation

Chorath A, Choi Y, Turkbey EB, Ahlman MA, Sibley CT, Liu S, Bluemke DA, Sandfort V. Coronary CT Angiography and Carotid MRI Improve Phenotyping of Disease Extent Compared with ACC/AHA Risk Score Alone. Radiol Cardiothorac Imaging. 2020 Feb 27;2(1):e190068. doi: 10.1148/ryct.2020190068. — View Citation

Ciceri F, Castagna A, Rovere-Querini P, De Cobelli F, Ruggeri A, Galli L, Conte C, De Lorenzo R, Poli A, Ambrosio A, Signorelli C, Bossi E, Fazio M, Tresoldi C, Colombo S, Monti G, Fominskiy E, Franchini S, Spessot M, Martinenghi C, Carlucci M, Beretta L, Scandroglio AM, Clementi M, Locatelli M, Tresoldi M, Scarpellini P, Martino G, Bosi E, Dagna L, Lazzarin A, Landoni G, Zangrillo A. Early predictors of clinical outcomes of COVID-19 outbreak in Milan, Italy. Clin Immunol. 2020 Aug;217:108509. doi: 10.1016/j.clim.2020.108509. Epub 2020 Jun 12. — View Citation

Emanuel EJ, Persad G, Upshur R, Thome B, Parker M, Glickman A, Zhang C, Boyle C, Smith M, Phillips JP. Fair Allocation of Scarce Medical Resources in the Time of Covid-19. N Engl J Med. 2020 May 21;382(21):2049-2055. doi: 10.1056/NEJMsb2005114. Epub 2020 Mar 23. — View Citation

Esposito A, Palmisano A, Toselli M, Vignale D, Cereda A, Rancoita PMV, Leone R, Nicoletti V, Gnasso C, Monello A, Biagi A, Turchio P, Landoni G, Gallone G, Monti G, Casella G, Iannopollo G, Nannini T, Patelli G, Di Mare L, Loffi M, Sergio P, Ippolito D, Sironi S, Pontone G, Andreini D, Mancini EM, Di Serio C, De Cobelli F, Ciceri F, Zangrillo A, Colombo A, Tacchetti C, Giannini F. Chest CT-derived pulmonary artery enlargement at the admission predicts overall survival in COVID-19 patients: insight from 1461 consecutive patients in Italy. Eur Radiol. 2020 Dec 23. doi: 10.1007/s00330-020-07622-x. [Epub ahead of print] — View Citation

Giannini F, Toselli M, Palmisano A, Cereda A, Vignale D, Leone R, Nicoletti V, Gnasso C, Monello A, Manfrini M, Khokhar A, Sticchi A, Biagi A, Turchio P, Tacchetti C, Landoni G, Boccia E, Campo G, Scoccia A, Ponticelli F, Danzi GB, Loffi M, Muri M, Pontone G, Andreini D, Mancini EM, Casella G, Iannopollo G, Nannini T, Ippolito D, Bellani G, Franzesi CT, Patelli G, Besana F, Costa C, Vignali L, Benatti G, Sverzellati N, Scarnecchia E, Lombardo FP, Anastasio F, Iannaccone M, Vaudano PG, Pacielli A, Baffoni L, Gardi I, Cesini E, Sperandio M, Micossi C, De Carlini CC, Spreafico C, Maggiolini S, Bonaffini PA, Iacovoni A, Sironi S, Senni M, Fominskiy E, De Cobelli F, Maggioni AP, Rapezzi C, Ferrari R, Colombo A, Esposito A. Coronary and total thoracic calcium scores predict mortality and provides pathophysiologic insights in COVID-19 patients. J Cardiovasc Comput Tomogr. 2021 Mar 11. pii: S1934-5925(21)00032-0. doi: 10.1016/j.jcct.2021.03.003. [Epub ahead of print] — View Citation

Li L, Qin L, Xu Z, Yin Y, Wang X, Kong B, Bai J, Lu Y, Fang Z, Song Q, Cao K, Liu D, Wang G, Xu Q, Fang X, Zhang S, Xia J, Xia J. Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy. Radiology. 2020 Aug;296(2):E65-E71. doi: 10.1148/radiol.2020200905. Epub 2020 Mar 19. — View Citation

Liang W, Yao J, Chen A, Lv Q, Zanin M, Liu J, Wong S, Li Y, Lu J, Liang H, Chen G, Guo H, Guo J, Zhou R, Ou L, Zhou N, Chen H, Yang F, Han X, Huan W, Tang W, Guan W, Chen Z, Zhao Y, Sang L, Xu Y, Wang W, Li S, Lu L, Zhang N, Zhong N, Huang J, He J. Early triage of critically ill COVID-19 patients using deep learning. Nat Commun. 2020 Jul 15;11(1):3543. doi: 10.1038/s41467-020-17280-8. — View Citation

Monaco CG, Zaottini F, Schiaffino S, Villa A, Della Pepa G, Carbonaro LA, Menicagli L, Cozzi A, Carriero S, Arpaia F, Di Leo G, Astengo D, Rosenberg I, Sardanelli F. Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study. Eur Radiol Exp. 2020 Dec 15;4(1):68. doi: 10.1186/s41747-020-00195-w. — View Citation

Neri E, Miele V, Coppola F, Grassi R. Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology. Radiol Med. 2020 May;125(5):505-508. doi: 10.1007/s11547-020-01197-9. Epub 2020 Apr 29. — View Citation

Palmisano A, Scotti GM, Ippolito D, Morelli MJ, Vignale D, Gandola D, Sironi S, De Cobelli F, Ferrante L, Spessot M, Tonon G, Tacchetti C, Esposito A. Chest CT in the emergency department for suspected COVID-19 pneumonia. Radiol Med. 2021 Mar;126(3):498-502. doi: 10.1007/s11547-020-01302-y. Epub 2020 Nov 9. — View Citation

Park JH, Lee SG, Ahn S, Kim JY, Song J, Moon S, Cho H. Strategies to prevent COVID-19 transmission in the emergency department of a regional base hospital in Korea: From index patient until pandemic declaration. Am J Emerg Med. 2020 Jul 24. pii: S0735-6757(20)30651-3. doi: 10.1016/j.ajem.2020.07.056. [Epub ahead of print] — View Citation

Patel D, Kher V, Desai B, Lei X, Cen S, Nanda N, Gholamrezanezhad A, Duddalwar V, Varghese B, Oberai AA. Machine learning based predictors for COVID-19 disease severity. Sci Rep. 2021 Feb 25;11(1):4673. doi: 10.1038/s41598-021-83967-7. — View Citation

Schalekamp S, Huisman M, van Dijk RA, Boomsma MF, Freire Jorge PJ, de Boer WS, Herder GJM, Bonarius M, Groot OA, Jong E, Schreuder A, Schaefer-Prokop CM. Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19. Radiology. 2021 Jan;298(1):E46-E54. doi: 10.1148/radiol.2020202723. Epub 2020 Aug 13. — View Citation

Ufuk F, Demirci M, Sagtas E, Akbudak IH, Ugurlu E, Sari T. The prognostic value of pneumonia severity score and pectoralis muscle Area on chest CT in adult COVID-19 patients. Eur J Radiol. 2020 Oct;131:109271. doi: 10.1016/j.ejrad.2020.109271. Epub 2020 Sep 9. — View Citation

Wehbe RM, Sheng J, Dutta S, Chai S, Dravid A, Barutcu S, Wu Y, Cantrell DR, Xiao N, Allen BD, MacNealy GA, Savas H, Agrawal R, Parekh N, Katsaggelos AK. DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set. Radiology. 2021 Apr;299(1):E167-E176. doi: 10.1148/radiol.2020203511. Epub 2020 Nov 24. — View Citation

Wong HYF, Lam HYS, Fong AH, Leung ST, Chin TW, Lo CSY, Lui MM, Lee JCY, Chiu KW, Chung TW, Lee EYP, Wan EYF, Hung IFN, Lam TPW, Kuo MD, Ng MY. Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19. Radiology. 2020 Aug;296(2):E72-E78. doi: 10.1148/radiol.2020201160. Epub 2020 Mar 27. — View Citation

* Note: There are 19 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Training, testing and validation of an AI platform for predicting Italian first wave Covid-19 patients prognosis.		9 months
Secondary	Validation of the developed AI platform on italian second wave of Covid-19 patients		3 months