In our last blog we discussed the need to search beyond the proverbial streetlight in medical imaging and presented two of Zebra’s first automatic imaging algorithms: coronary calcium quantification and liver density measurement. In that blog post, we pointed out that CT-chest lung cancer screening gained approval by demonstrating a 20% reduction of lung cancer deaths in the National Lung Cancer Screening Trial (NLCST). We argued that the merits of CT chest screening for long—term smokers might be markedly underestimated: more people in the NLCST died of cardiovascular disease than lung cancer, and the most powerful predictors of cardiovascular disease and mortality are coronary calcium and visceral fat, both of which can be screened for using the same Chest CT (hence our rationale for developing these fully automatic algorithms). Now we look even farther beyond the streetlight and mortality statistics to examine the factors most predictive of how well people live.
Smokers are at 13x increased risk of developing chronic obstructive lung disease (COPD); fully half of smokers develop some degree of COPD. For a person with COPD, life is defined mainly by how well they can breathe – “just” breathe. For healthcare providers, COPD is a mighty foe – prevalent, powerful and unpredictable. COPD exacerbations account for more than 12% of all ER admissions and 10% of inpatient hospital beds but those numbers can change precipitously: seasonal and even sporadic fluctuations of COPD exacerbations can overwhelm hospital wards . The hospitalization course of any individual with COPD is just as precarious: according to the Royal College of Physicians , nearly 1 in 12 hospital admissions for COPD exacerbation resulted in death during that admission and 1 in 4 were associated with death within that year. The same study found that fully 30% of patients admitted with acute COPD required repeated hospitalization within 3 months.
After cardiovascular disease (25%) and lung cancer (24%), the next distinct cause of death among the NLCST population was lung disease (11%). Could the same screening CT data be used to change not only who dies of lung disease but, perhaps more important, how those with chronic lung disease live? Indeed, distinct CT- identifiable patterns of lung architecture have been correlated to different risks of clinical deterioration and can even be used to predict which of various therapy options would be most effective ,    .
Interestingly, a single measurement of the size of the pulmonary artery on CT is the most powerful predictor of hospitalization and mortality in COPD patients, . In fact, finding a pulmonary artery diameter which is larger than that of the adjacent aorta is associated with a greater than 3x risk of requiring hospitalization for acute respiratory failure within twelve months. Although this finding is rare among the general population, it is seen in 10% – 30% of individuals with longstanding lung disease. Combining these two assessments of lung texture and pulmonary artery diameter could identify those in greatest risk of disease progression in order to more effectively deliver preventative and maintenance care .
COPD is a mighty foe – its prevalence will only increase in the next decades while resources to treat it remain relatively static. But COPD is not one disease – not a single diagnosis that follows a single predictable clinical trajectory. Its precariousness may be its greatest threat – and hence our target: to define the key features of COPD most predictive of disease course so that we can prevent and treat those who need it first. Two more automatic insights which every Chest CT should include: emphysema quantification and pulmonary artery diameter. To be continued…
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