Imaging Biomarkers to Stratify the Risk of Barotrauma in ARDS

Официальное название

Artificial Intelligence-based Identification of Imaging Biomarkers of Lung FRAILty in Patients With Acute Respiratory Distress Syndrome.

Обзор

The high incidence of barotrauma in patients with COVID-19-related acute respiratory distress syndrome (ARDS) (16.1%, with a mortality rate \>60%) provides rationale for considering COVID-19 ARDS a paradigm for lung frailty. The investigators recently discovered that the Macklin effect is an impressive radiological predictor of barotrauma in COVID-19 ARDS. Since lung frailty is a major issue also in non-COVID-19 ARDS (6% barotrauma, with a mortality rate of 46% ) the investigators want to confirm the importance of Macklin effect in non-COVID-19 ARDS. Using artificial intelligence-based approaches the investigators also want to identify imaging biomarkers to non-invasively assess lung frailty in a mixed cohort of COVID-19/non-COVID-19 ARDS patients. Furthermore, the investigators want to prospectively validate these biomarkers in a cohort of ARDS patients. This will provide a therapeutic algorithm for ARDS patients at high-risk for barotrauma, identifying those most likely to benefit from hyper protective strategies.

Подробное описание

Development of barotrauma, spanning from asymptomatic air leakage within lung parenchyma to life-threatening conditions such as tension pneumothorax, is frequent in acute respiratory distress syndrome (ARDS), with a difficult, non-standardized management, resulting in high mortality rates (greater than 60% in coronavirus disease 2019 \[COVID-19\] ARDS patients, around 46% in non-COVID-19 ARDS patients). Of note, barotrauma occurs also in spontaneously breathing patients with COVID-19 ARDS. Frailty of lung parenchyma represents indeed a major issue in ARDS. In addition, in high-risk patients, mechanical ventilation may exacerbate pulmonary damage (ventilator-induced lung injury) and potentially induce barotrauma despite use of protective mechanical ventilation. Early assessment of lung frailty could therefore allows early risk stratification in terms of barotrauma susceptibility amongst ARDS patients, providing rationale for the deployment of lung protective management strategies in those at high-risk for barotrauma. Macklin effect, firstly intended to allow proper differentiation between respiratory and other causes of air leakage in the mediastinum (such as tracheobronchial/oesophageal injury), has been recently proved by our group to be a consistent, very accurate radiological predictor of barotrauma development in COVID-19 ARDS patients (sensitivity: 89.2%; specificity: 95.6%), anticipating by 12 days the occurrence of clinically overt barotrauma. These results have been confirmed, and even improved by multicentre findings, which report, on a large cohort of COVID-19 patients (almost 700), an impressive, almost perfect overall accuracy (99.8%) of the Macklin effect in predicting barotrauma development. Furthermore, data from our group suggest that early application of awake veno/venous extracorporeal membrane oxygenation (ECMO) without invasive mechanical ventilation in COVID-19 severe ARDS patients at high-risk for barotrauma (those with Macklin effect on chest CT imaging) is feasible and may result in no barotrauma events and low intubation rate. In this respect, confirmation of Macklin effect role and identification of further, novel quantitative imaging biomarkers could unveil biological bases of lung frailty in course of ARDS and provide instruments for early risk stratification before barotrauma occurrence.

Our group also implemented original in-house facilities consisting of densitometry, machine learning and artificial intelligence-based approaches to assess lung composition in COVID-19 patients throughout a fully automated workflow; recently, the investigators highlighted the outstanding clinical significance of this methodological approach in predicting patients' prognosis, as well as its great reproducibility. Preliminary, yet unpublished findings suggest that lung frailty has a specific densitometric signature, being a possible marker for hyper protective management strategies; few, highly robust radiomic features seem to corroborate the same result.

Accordingly, the driving hypotheses of this retrospective/prospective study are that, irrespective of COVID-19 status, in ARDS patients, i) lung frailty has a specific pattern of imaging biomarkers, and that ii) a more accurate selection of patients could limit the problem of barotrauma associated with mechanical ventilation.

Вмешательства

• Диагностический тест Chest Computed Tomography Scan per normal clinical practice
  Normal Clinical practice

Первичные конечные точки

• Rate of clinically relevant barotrauma [Срок оценки: 30 days or until hospital discharge. Specifically, from date of basal CT scan until the date of first radiologically documented barotrauma.]

Критерии участия

Критерии включения

• Clinical and radiological signs of ARDS, according to Berlin criteria \[14\], requiring ICU admission;
• Obtain duly signed informed consent.

Критерии исключения

• Poor quality imaging (because of motion/respiratory artefacts).

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Италия · 2 центра

• Ospedale Mater Domini — Catanzaro
• IRCCS San Raffaele Scientific Institute — Milan

Публикации

• Belletti A, Todaro G, Valsecchi G, Losiggio R, Palumbo D, Landoni G, Zangrillo A. Barotrauma in Coronavirus Disease 2019 Patients Undergoing Invasive Mechanical Ventilation: A Systematic Literature Review. Crit Care Med. 2022 Mar 1;50(3):491-500. doi: 10.1097/CCM.0000000000005283. PMID 34637421
• Palumbo D, Campochiaro C, Belletti A, Marinosci A, Dagna L, Zangrillo A, De Cobelli F; COVID-BioB Study Group. Pneumothorax/pneumomediastinum in non-intubated COVID-19 patients: Differences between first and second Italian pandemic wave. Eur J Intern Med. 2021 Jun;88:144-146. doi: 10.1016/j.ejim.2021.03.018. Epub 2021 Mar 19. No abstract available. PMID 33820685
• Sakai M, Murayama S, Gibo M, Akamine T, Nagata O. Frequent cause of the Macklin effect in spontaneous pneumomediastinum: demonstration by multidetector-row computed tomography. J Comput Assist Tomogr. 2006 Jan-Feb;30(1):92-4. doi: 10.1097/01.rct.0000187416.07698.8d. PMID 16365580
• Murayama S, Gibo S. Spontaneous pneumomediastinum and Macklin effect: Overview and appearance on computed tomography. World J Radiol. 2014 Nov 28;6(11):850-4. doi: 10.4329/wjr.v6.i11.850. PMID 25431639
• Russell DW, Watts JR Jr, Powers TA. Searching for the Source of the Leak: PIE and the Macklin Effect. Ann Am Thorac Soc. 2018 Nov;15(11):1354-1356. doi: 10.1513/AnnalsATS.201803-200CC. No abstract available. PMID 30382777
• Belletti A, Palumbo D, Zangrillo A, Fominskiy EV, Franchini S, Dell'Acqua A, Marinosci A, Monti G, Vitali G, Colombo S, Guazzarotti G, Lembo R, Maimeri N, Faustini C, Pennella R, Mushtaq J, Landoni G, Scandroglio AM, Dagna L, De Cobelli F; COVID-BioB Study Group. Predictors of Pneumothorax/Pneumomediastinum in Mechanically Ventilated COVID-19 Patients. J Cardiothorac Vasc Anesth. 2021 Dec;35(12):3 PMID 33678544
• Palumbo D, Zangrillo A, Belletti A, Guazzarotti G, Calvi MR, Guzzo F, Pennella R, Monti G, Gritti C, Marmiere M, Rocchi M, Colombo S, Valsecchi D, Scandroglio AM, Dagna L, Rovere-Querini P, Tresoldi M, Landoni G, De Cobelli F; COVID-BioB Study Group. A radiological predictor for pneumomediastinum/pneumothorax in COVID-19 ARDS patients. J Crit Care. 2021 Dec;66:14-19. doi: 10.1016/j.jcrc.2021.07.02 PMID 34392131
• Paternoster G, Belmonte G, Scarano E, Rotondo P, Palumbo D, Belletti A, Corradi F, Bertini P, Landoni G, Guarracino F; COVID-Macklin Study Group. Macklin effect on baseline chest CT scan accurately predicts barotrauma in COVID-19 patients. Respir Med. 2022 Jun;197:106853. doi: 10.1016/j.rmed.2022.106853. Epub 2022 Apr 20. PMID 35512457

Идентификаторы

NCT: NCT05816954 · FRAIL ARDS - 49/INT/2022

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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