Researchers at National Jewish Health in Denver have identified varying patterns on lung scans that could reveal disease severity in patients with sarcoidosis. These findings may help physicians better predict risk of progressing fibrosis and formulate more personalized treatment plans.
The National Jewish Health team and collaborating institutions published their results in the paper, “Demographic and Physiological Differences Between Fibrotic and Nonfibrotic CT Subtypes of Sarcoidosis,” in CHEST.
The study included more than 900 patients categorized into three groups based on high-resolution CT scans together with breathing tests: those with fibrotic lung disease, those with nonfibrotic lung abnormalities and those with no visible lung damage. The analysis demonstrated key differences in the groups.
First, patients with fibrotic sarcoidosis were older, had a longer disease history and had significantly worse lung function than patients in the other two groups. Nearly two-thirds of patients with fibrosis also had abnormal breathing tests, compared to approximately one-third of patients without fibrosis.
“Not all sarcoidosis is the same. By looking closely at CT scans, we can begin to identify which patients are at higher risk for more serious lung impairment, specific types of lung function abnormalities and may need closer monitoring or different treatment approaches,” said co-senior author Lisa Maier, MD, in a press release. Dr. Maier is chief of the division of environmental and occupational health sciences and head of the World Association of Sarcoidosis and Granulomatous Disease Sarcoidosis Center of Excellence at National Jewish Health.
In addition, the researchers observed specific patterns within the fibrotic disease matter shown in the imaging scans. They noted that individuals who had large clusters of lung scarring (called conglomerate masses) were significantly more likely to develop restrictive and obstructive pulmonary problems — the combination of which is a more complex and severe form of impairment. Most patients with nonfibrotic lung changes showed normal or mildly affected lung function, which authors said demonstrates the wide variability of the disease.
“These imaging patterns give us valuable clues about what’s happening in the lungs,” said co-senior author David Lynch, MB, a radiologist at National Jewish Health. “They help us connect what we see on scans with how well a patient’s lungs are actually functioning.”
Current clinical guidelines for pulmonary sarcoidosis do not indicate the necessity for CT scans in patient evaluation or their critical diagnostic role in differentiating between fibrotic and nonfibrotic forms of the disease. The new insights could improve sarcoidosis classification and therapeutic decision-making, the authors said.
“Better defining these subtypes is an important step toward more personalized care,” Dr. Maier said.
In a related study out of National Jewish Health, researchers analyzed chest CT scans using the computer-based imaging technique known as radiomics to better understand the different forms of sarcoidosis. The retrospective study, which included 320 patient lung scans, identified subtle patterns and differences and created four imaging profiles across the disease spectrum. This paper, “Radiomic Profiling of Chest CT in a Cohort of Sarcoidosis Cases,” was published in Scientific Reports.
According to co-senior author Tasha Fingerlin, PhD, pulmonary assessments and diagnoses are typically completed with visual review of imaging scans. Radiomics can assist manual evaluation by providing a more objective approach that includes advanced algorithms that measures features and subtle formations that may not be visible to the human eye.
“We found that radiomic analysis of CT scans can reveal distinct patterns of lung abnormalities in sarcoidosis,” said Dr. Fingerlin, who is vice chair of the department of immunology and genomic medicine at National Jewish Health. “These patterns were associated with differences in lung function, suggesting that this approach may help us better understand how the disease varies from patient to patient.”
The researchers analyzed high-resolution CT scans from patients who participated in the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study — one of the biggest and broadest sarcoidosis research cohorts in the United States. The team incorporated machine-learning clustering techniques and identified four patient groups associated with, but not mirroring, Scadding stage and Oberstein score.
“Current staging systems are helpful, but they don’t always capture the full complexity of what we see in the lungs of people with sarcoidosis. Radiomics allows us to quantify those patterns in a more detailed and reproducible way,” said Dr. Fingerlin.
The authors noted that radiomics analysis can be performed quickly and automatically, which could help doctors assess a large number of scans and track disease patterns.
“There is promise for significant impact on patient care, especially in regions where there is no expert in sarcoidosis radiology, which is much of the country and certainly most areas in the far West,” said Dr. Maier, who was co-senior author of this study as well. “Radiomics could also expedite care in clinics with rapid turnaround for patients at specialized centers and revolutionize the way we interpret CT scans for research and clinical trials.”
