Analyze Insights

COVID-19 Lung Damage Measurement

Segmentation and Object MapsCOVID-19, the infectious disease caused by the SARS-CoV-2 virus, continues to impact our daily lives. For those who become seriously ill with severe COVID-19 and require hospitalization, a severe pro-inflammatory condition can cause lung injury via pneumonia, acute respiratory distress syndrome, or sepsis.

As the lungs and heart work together in the body to maintain oxygenation, when the lungs are affected, the heart may be affected also, so one potential complication in patients with COVID-19 is acute cardiac injury. Non-contrast CT imaging data, which can help determine lung damage, is generally more rapidly available during the initial diagnostic procedure than functional cardiac imaging and troponin-I blood measurements, which are used for determining acute cardiac injury.

Researchers from Canada, Taiwan and China recently investigated the diagnostic value of non-contrast CT for detecting acute cardiac injury during the early stage of COVID-19. CT images of 143 COVID-19 patients were retrospectively studied along with their blood test data including troponin-I, a specific marker of cardiac injury.

Analyze 14.0 was used to segment different types of lung parenchyma of non-contrast CT chest images. From each set of images, the left and right lungs across all tomographic slices were delineated via the Threshold Volume function, a semi-automatic segmentation tool in Analyze. The segmentation was modified manually as needed to remove the trachea, bronchi and large pulmonary blood vessels from the segmented lungs. The volume of each lung was calculated and the Hounsfield Unit (HU) range for various lung tissue types(normal lung, moderately abnormal lung, and severely abnormal lung) were determined using the Histogram option in Threshold Volume. The relative volume of normal lung tissue, moderately abnormal lung tissue and severely abnormal lung tissue with respect to the total lung volume (sum of the left and right lung volumes) were calculated accordingly. The presence or absence of acute cardiac injury, as measured by blood testing, were compared to imaging results for each subject.

The study found that the normal, moderately abnormal and severely abnormal lung parenchyma volumes segmented from non-contrast CT chest images were statistically signficiant predictors of acute cardiac injury in COVID-19 patients within a two-week window following SARS-CoV-2 infection. While further study is required, these findings may be useful to inform appropriate treatment strategies to minimize damage to the heart when more specific functional cardiac imaging is unavailable.

The Segment module in Analyze contains more than two dozen automatic, semi-automatic and manual segmentation tools to provide all of the functionality required to effectively segment regions of interest in a 3D volume image. For details on all of these segmentation functions download the Segment chapter of the Analyze User’s Guide.

Additional resources:

>> Analyze 14.0 User’s Guide: Segment.

>> Analyze 14.0 Help Videos: Segment.


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