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

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

Getty Images

September 3, 2021 — Researchers at Case Western Reserve University have developed an online tool to help medical staff quickly determine which COVID-19 patients will need help breathing with a ventilator.

The tool, developed through analysis of computed 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 the Center 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.

Yet, almost from the start of the pandemic, the number of ventilators needed to support such patients far outpaced available supplies—to the point that hospitals began “splitting” ventilators—a practice in which a ventilator assists more than one patient.

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 and in other countries.  

“These can be gut-wrenching decisions for hospitals—deciding who is going to get the most help against an aggressive disease,” Madabhushi said.

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 tool appeared this month in the IEEE 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 also recently published research comparing autopsy tissues scans taken from patients who died from the H1N1 virus (Swine Flu) and from COVID-19. While the results are preliminary, they do appear to reveal information about what Madabhushi called the “immune architecture” of the human body in response to the viruses.

“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.

“This allowed us to find information that may not be obvious by simple visual inspection of the samples,” Corredor said. “These COVID-19-related patterns seem to be different from those of other diseases such as H1N1, a comparable viral disease.”

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

Related COVID Radiology Content:

Special Storage and Adverse Reactions for First COVID-19 Vaccine Approved by the FDA

Lung Ultrasounds Could Help Determine COVID-19 Outcome

Johns Hopkins Medicine Expert Weighs Devastating Impact of COVID-19 on Healthcare Workers

CT in a Box Helps Rapidly Boost Imaging Capability at COVID Surge Hospitals

Philips Patient Management Solution keeps patients safe and personalizes care during COVID-19 at leading U.S. medical centers

 

CT Imaging of the 2019 Novel Coronavirus (2019-nCoV) Pneumonia

Infervision in the Frontlines Against the Coronavirus

CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV)

The Cardiac Implications of Coronavirus

 

VIDEO: COVID-19 Pneumonia Chest CT Scan Scroll Through

CT Imaging of the 2019 Novel Coronavirus (2019-nCoV) Pneumonia

Chest CT Can Distinguish Negative From Positive Lab Results for COVID-19

VIDEO: CT Sees Increased Use During COVID-19

 

Radiologists Urge Use of Medical Imaging and AI-Powered Solutions to Manage COVID-19

Stroke Scans Could Reveal COVID-19 Infection

Handheld Ultrasound Used to Monitor COVID-19 Patients With Cardiac Complications

Study Looks at CT Findings of COVID-19 Through Recovery

Using Lung X-rays to Diagnose COVID-19

How COVID-19 Affects the Brain in Neuroimaging
 

VIDEO: Lingering Myocardial Involvement After COVID-19 Infection — Interview with Aaron Baggish, M.D.

COVID-19 Can Impact Hearts in Young Children

VIDEO: What Are The Long-term Cardiac Impacts of COVID-19 Infection — Interview with Todd Hurst, M.D.

Find more related clinical content Coronavirus (COVID-19)

Related Content

First-of-its-kind, power-assisted Free Motion telescoping column reduces lift force by up to 70 percent to significantly reduce musculoskeletal stress and strain injuries that may occur over the course of an X-ray technologist’s career
News | Digital Radiography (DR) | September 01, 2021
September 1, 2021 — GE Healthcare introduced the...
As the world’s first FDA-cleared bedside MRI system, Hyperfine’s portable Swoop system is designed to allow physicians to rapidly understand the current state of injury to make life-saving decisions.

As the world’s first FDA-cleared bedside MRI system, Hyperfine’s portable Swoop system is designed to allow physicians to rapidly understand the current state of injury to make life-saving decisions. Within minutes, the technology can acquire critical images via a wireless tablet, powered by a standard wall outlet at the patient’s bedside. (Photo: Business Wire)

News | Magnetic Resonance Imaging (MRI) | September 01, 2021
September 1, 2021 — ...
As a result of applying budget neutrality, specialties like interventional radiology and radiation oncology — which have high medical supply and equipment costs and lower clinical labor costs — are slated for potentially significant reimbursement reductions.

Getty Images

News | Radiology Business | August 31, 2021
August 31, 2021 — In the...
A new Yale-led study shows that a portable magnetic resonance imaging (MRI) device can help identify such intracranial hemorrhages, potentially life-saving information particularly in areas or scenarios where access to sophisticated brain imaging scans are not readily available.

Getty Images

News | Magnetic Resonance Imaging (MRI) | August 25, 2021
August 25, 2021 — When patients exhibit stroke symptoms, doctors must quickly make a life or death determination: Are
While doctors have used low-intensity ultrasound as a medical imaging tool since the 1950s, experts at the University of Waterloo are using and extending models that help capture how high-intensity focused ultrasound (HIFU) can work on a cellular level.

The InSightec ExAblate focused ultrasound system developed to treat essential tremor. 

News | Focused Ultrasound Therapy | August 24, 2021
August 24, 2021 — Researchers are bringing the use of acoustic waves to target and destroy cancerous tumors closer to
The Telehealth Service Implementation Model (TSIM) is a roadmap for navigating the complexities of establishing a strong and durable telehealth program

Dr. Dee Ford, program director of the National Telehealth Center of Excellence at the Medical University of South Carolina, demonstrates a telehealth visit. Photo courtesy of Medical University of South Carolina, Sarah Pack

News | Teleradiology | August 24, 2021
August 24, 2021 — Telehealth