Lung CT Scan Analysis of SARS-CoV2 Induced Lung Injury

NCT04395482 | Completed DMC

• 1 other identifier: TAC-COVID19
• Study Type: observational
• Target: 44
• Locations: 2 countries
• Sites: 8

Brief Summary

This is a multicenter observational retrospective cohort study that aims to study the morphological characteristics of the lung parenchyma of SARS-CoV2 positive patients identifiable in patterns through artificial intelligence techniques and their impact on patient outcome.

Conditions

covid19

Keywords

Lung injury; sars-covid-2; coronavirus infection

Outcome Measures

Primary Outcomes (2)

• A qualitative analysis of parenchymal lung damage induced by COVID-19

  Describe the parenchymal lung damage induced by COVID-19 through a qualitative analysis with chest CT through artificial intelligence techniques.

  Until patient discharge from the hospital (approximately 6 months)

• A quantitative analysis of parenchymal lung damage induced by COVID-19

  Describe the parenchymal lung damage induced by COVID-19 through a quantitative analysis with chest CT through artificial intelligence techniques.

  Until patient discharge from the hospital (approximately 6 months)

Secondary Outcomes (6)

• The potential impact of parenchymal morphological CT scans in patients with severe moderate respiratory failure.

  Until patient discharge from the hospital (approximately 6 months)

• The potential impact of parenchymal morphological CT scans in patients with severe moderate respiratory failure.

  Until patient discharge from the hospital (approximately 6 months)

• The potential impact of parenchymal morphological CT scans in patients with severe moderate respiratory failure.

  Until patient discharge from the hospital (approximately 6 months)

• Automated segmentation of lung scans of patients with COVID-19 and ARDS.

  Until patient discharge from the hospital (approximately 6 months)

• Knowledge of chest CT features in COVID-19 patients and their detail through the use of machine learning and other quantitative techniques.

  Until patient discharge from the hospital (approximately 6 months)

Study Arms (1)

covid-19 pneumonia related patients

The study aims to collect the highest number possible of lung CT scan images performed in patients with COVID-19, in order to obtain a large sample size that will allow us to characterize the extent of lung injury, the presence of specific patterns of lung alteration, and their potential association with the outcome of patients - in view of assisting the medical staff in better understanding the grade of the severity impairment in these patients which might be potentially candidates to more intensive therapeutic strategies.

Other: Lung CT scan analysis in COVID-19 patients

Interventions

Lung CT scan analysis in COVID-19 patients OTHER

This research project will evaluate the morphological characteristics of the lung by CT scan analysis in COVID-19 patients which will be identified as specific patterns using artificial intelligence technology and their impact on outcome.

covid-19 pneumonia related patients

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The goal is to collect as many lung CT scan images as possible in patients with COVID-19; according to the preliminary evaluation estimate, a total of 500 patients are expected to be collected.

You may qualify if:

• Patients 18 years old or above;
• Positive confirmation with nucleic acid amplification test or serology of SARS-CoV2 by naso-pharyngeal swab, bronchoaspirate sample or bronchoalveolar lavage;
• Lung CT scan performed within 7 days of hospital admission;
• Patients above 18 years old or above;
• Patients admitted to the hospital with a diagnosis of ARDS according to the Berlin criteria;
• Lung CT scan performed within 7 days of ARDS diagnosis;

You may not qualify if:

• ● Positive confirmation with nucleic acid amplification test or serology of SARS-CoV2 by naso-pharyngeal swab, bronchoaspirate sample or bronchoalveolar lavage

Sponsors & Collaborators

• University of Milano Bicocca: lead

Study Sites (8)

Ospedale Papa Giovanni XXIII

Bergamo, Italy

Location

Policlinico San Marco-San Donato group

Bergamo, Italy

Location

Azienda Ospedaliero-Universitaria di Ferrara

Ferrara, Italy

Location

ASST di Lecco Ospedale Alessandro Manzoni

Lecco, Italy

Location

ASST Melegnano-Martesana, Ospedale Santa Maria delle Stelle

Melzo, Italy

Location

ASST Monza

Monza, Italy

Location

AUSL Romagna-Ospedale Infermi di Rimini

Rimini, Italy

Location

Istituto per la Sicurezza Sociale-Ospedale della Repubblica di San Marino

San Marino, San Marino

Location

Related Publications (24)

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• Zhou S, Wang Y, Zhu T, Xia L. CT Features of Coronavirus Disease 2019 (COVID-19) Pneumonia in 62 Patients in Wuhan, China. AJR Am J Roentgenol. 2020 Jun;214(6):1287-1294. doi: 10.2214/AJR.20.22975. Epub 2020 Mar 5.

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• Xiong Y, Sun D, Liu Y, Fan Y, Zhao L, Li X, Zhu W. Clinical and High-Resolution CT Features of the COVID-19 Infection: Comparison of the Initial and Follow-up Changes. Invest Radiol. 2020 Jun;55(6):332-339. doi: 10.1097/RLI.0000000000000674.

  PMID: 32134800 BACKGROUND

• Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. AJR Am J Roentgenol. 2020 Jul;215(1):87-93. doi: 10.2214/AJR.20.23034. Epub 2020 Mar 14.

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• Dai WC, Zhang HW, Yu J, Xu HJ, Chen H, Luo SP, Zhang H, Liang LH, Wu XL, Lei Y, Lin F. CT Imaging and Differential Diagnosis of COVID-19. Can Assoc Radiol J. 2020 May;71(2):195-200. doi: 10.1177/0846537120913033. Epub 2020 Mar 4.

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• Li Y, Xia L. Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. AJR Am J Roentgenol. 2020 Jun;214(6):1280-1286. doi: 10.2214/AJR.20.22954. Epub 2020 Mar 4.

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• Xie X, Zhong Z, Zhao W, Zheng C, Wang F, Liu J. Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing. Radiology. 2020 Aug;296(2):E41-E45. doi: 10.1148/radiol.2020200343. Epub 2020 Feb 12.

  PMID: 32049601 BACKGROUND

• 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.

  PMID: 32101510 BACKGROUND

• Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, Ji W. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology. 2020 Aug;296(2):E115-E117. doi: 10.1148/radiol.2020200432. Epub 2020 Feb 19. No abstract available.

  PMID: 32073353 BACKGROUND

• Bai HX, Hsieh B, Xiong Z, Halsey K, Choi JW, Tran TML, Pan I, Shi LB, Wang DC, Mei J, Jiang XL, Zeng QH, Egglin TK, Hu PF, Agarwal S, Xie FF, Li S, Healey T, Atalay MK, Liao WH. Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT. Radiology. 2020 Aug;296(2):E46-E54. doi: 10.1148/radiol.2020200823. Epub 2020 Mar 10.

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• Pan F, Ye T, Sun P, Gui S, Liang B, Li L, Zheng D, Wang J, Hesketh RL, Yang L, Zheng C. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 2020 Jun;295(3):715-721. doi: 10.1148/radiol.2020200370. Epub 2020 Feb 13.

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• Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, Cui J, Xu W, Yang Y, Fayad ZA, Jacobi A, Li K, Li S, Shan H. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology. 2020 Apr;295(1):202-207. doi: 10.1148/radiol.2020200230. Epub 2020 Feb 4.

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• Bernheim A, Mei X, Huang M, Yang Y, Fayad ZA, Zhang N, Diao K, Lin B, Zhu X, Li K, Li S, Shan H, Jacobi A, Chung M. Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology. 2020 Jun;295(3):200463. doi: 10.1148/radiol.2020200463. Epub 2020 Feb 20.

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• Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 Feb 15;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5. Epub 2020 Jan 24.

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• Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, Fan Y, Zheng C. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis. 2020 Apr;20(4):425-434. doi: 10.1016/S1473-3099(20)30086-4. Epub 2020 Feb 24.

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• Guo L, Wei D, Zhang X, Wu Y, Li Q, Zhou M, Qu J. Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score. Front Microbiol. 2019 Dec 3;10:2752. doi: 10.3389/fmicb.2019.02752. eCollection 2019.

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• Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585.

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• Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J, Yu T, Zhang X, Zhang L. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020 Feb 15;395(10223):507-513. doi: 10.1016/S0140-6736(20)30211-7. Epub 2020 Jan 30.

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• Rezoagli E, Xin Y, Signori D, Sun W, Gerard S, Delucchi KL, Magliocca A, Vitale G, Giacomini M, Mussoni L, Montomoli J, Subert M, Ponti A, Spadaro S, Poli G, Casola F, Herrmann J, Foti G, Calfee CS, Laffey J, Bellani G, Cereda M; CT-COVID19 Multicenter Study Group. Phenotyping COVID-19 respiratory failure in spontaneously breathing patients with AI on lung CT-scan. Crit Care. 2024 Aug 5;28(1):263. doi: 10.1186/s13054-024-05046-3.

  PMID: 39103945 DERIVED

Related Links

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MeSH Terms

Conditions

COVID-19; Lung Injury; Coronavirus Infections

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases; Thoracic Injuries; Wounds and Injuries

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 18, 2020
• First Posted: May 20, 2020
• Study Start: May 7, 2020
• Primary Completion: June 15, 2021
• Study Completion: March 31, 2022
• Last Updated: July 21, 2022

Record last verified: 2022-07

Data Sharing

• IPD Sharing: Will not share

Locations

IT (7); SA (1)