News|Coronavirus (COVID-19)| September 03, 2021

Researchers use AI to Predict which COVID-19 Patients Will Need a Ventilator

Case Western Reserve University lab reports 84% accuracy in predicting from initial chest scan which patients will need breathing help; planning website for UH, Cleveland VA physicians to upload scans

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September 3, 2021 — Researchers atCase Western Reserve Universityhave developed an online tool to help medical staff quickly determine whichCOVID-19病人需要呼吸机帮助呼吸。

The tool, developed through analysis ofcomputed tomography(CT) scans from nearly 900 COVID-19 patients diagnosed in 2020, was able to predict ventilator need with 84% accuracy.

“That could be important for physicians as they plan how to care for a patient—and, of course, for the patient and their family to know,” said Anant Madabhushi, the Donnell Institute Professor of Biomedical Engineering at Case Western Reserve and head of theCenter for Computational Imaging and Personalized Diagnostics(CCIPD). “It could also be important for hospitals as they determine how many ventilators they’ll need.”

Next, Madabhushi said he hopes to use those results to try out the computational tool in real time at University Hospitals and Louis Stokes Cleveland VA Medical Center with COVID-19 patients.

If successful, he said medical staff at the two hospitals could upload a digitized image of the chest scan to a cloud-based application, where the AI at Case Western Reserve would analyze it and predict whether that patient would likely need a ventilator.

Dire Need for Ventilators

Among the more common symptoms of severe COVID-19 cases is the need for patients to be placed on ventilators to ensure they will be able to continue to take in enough oxygen as they breathe.

然而，几乎从大流行一开始，支持这些病人所需的呼吸机数量就远远超过了现有的供应，以至于医院开始“分裂”呼吸机，即一台呼吸机帮助不止一个病人。

While 2021’s climbing vaccination rates dramatically reduced COVID-19 hospitalization rates—and, in turn, the need for ventilators—the recent emergence of the Delta variant has again led to shortages in some areas of the United States在其他国家也是如此。

Madabhushi说:“对于医院来说，这可能是一个痛苦的决定——决定谁将得到最大的帮助来对抗一种侵袭性疾病。”

To date, physicians have lacked a consistent and reliable way to identify which newly admitted COVID-19 patients are likely to need ventilators—information that could prove invaluable to hospitals managing limited supplies.

Researchers in Madabhushi’s lab began their efforts to provide such a tool by evaluating the initial scans taken in 2020 from nearly 900 patients from the U.S. and from Wuhan, China—among the first known cases of the disease caused by the novel coronavirus.

Madabhushi said those CT scans revealed—with the help of deep-learning computers, or Artificial Intelligence (AI)—distinctive features for patients who later ended up in the intensive care unit (ICU) and needed help breathing.

The research behind the toolappeared this month in theIEEE Journal of Biomedical and Health Informatics.

Amogh Hiremath, a graduate student in Madabhushi’s lab and lead author on the paper, said patterns on the CT scans couldn’t be seen by the naked eye, but were revealed only by the computers.

“This tool would allow for medical workers to administer medications or supportive interventions sooner to slow down disease progression,” Hiremath said. “And it would allow for early identification of those at increased risk of developing severe acute respiratory distress syndrome—or death. These are the patients who are ideal ventilator candidates.”

Further Research Into ‘Immune Architecture’

Madabhushi’s lab alsorecently published research comparing autopsy tissues scans取自死于H1N1病毒(猪流感)和死于COVID-19的患者。虽然结果是初步的，但它们似乎揭示了Madabhushi所称的人体应对病毒的“免疫架构”的信息。

“This is important because the computer has given us information that enriches our understanding of the mechanisms in the body against viruses,” he said. “That can play a role in how we develop vaccines, for example.”

Germán Corredor Prada, a research associate in Madabhushi’s lab who was the primary author on the paper, said computer vision and AI techniques allowed the scientists to study how certain immune cells organize in the lung tissue of some patients.

Corredor说:“这让我们能够发现通过简单的视觉检查样本可能不明显的信息。”“这些covid -19相关的模式似乎不同于其他疾病，如H1N1，一种类似的病毒性疾病。”

Eventually, when combined with other clinical work and further tests in larger sets of patients, this discovery could serve to improve the world’s understanding of these diseases and maybe others, he said.

Madabhushi established the CCIPD at Case Western Reserve in 2012. The lab now includes more than 60 researchers. Some were involved in this most recent COVID-19 work, including graduate students Hiremath, Pranjal Vaidya; research associates Corredor and Paula Toro; and research faculty Cheng Lu and Mehdi Alilou.

For more information:case.edu