LSU Health creates 3D digital models of patients' lungs, chest to diagnose COVID-19

LSU Health New Orleans researchers developed 3D digital models from CT scans of COVID-19 patients to visually evaluate the distribution of the infection in patients' respiratory systems.

The research team used CT scans of three hospitalized patients' lungs and chests to build the models. Two of the patients had tested positive for the virus while one of the patients' reverse transcription chain reaction test came back negative. This result was presumed to be a false negative after the patient's imaging indicated a coronavirus infection.

"The full effect of COVID-19 on the respiratory system remains unknown, but the 3D digital segmented models provide clinicians a new tool to evaluate the extent and distribution of the disease in one encapsulated view," said Bradley Spieler, MD, vice chairman of radiology research at LSU Health, according to the Aug. 19 news release. "This is especially useful in the case where RT-PCR for [COVID-19] is negative but there is strong clinical suspicion for COVID-19."

Dr. Spieler, one of the creators of the 3D models, and his team segmented the patients' CT scans into 3D digital surface models using the scientific visualization program Avizo as well as evolutionary anatomy research techniques. Each of the models shows varying degrees of COVID-19 infection in the respiratory tissues, particularly along the back of the lungs and bottom sections.

The researchers, who published their study in BMJ Case Reports, concluded that the 3D digital models more clearly show COVID-19-related infection in the respiratory system compared to X-rays, CT scans or RT-PCR testing alone.

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