Computed Tomography (CT)-derived biomarkers like Pi10 and PiSlope are vital tools for non-invasively assessing airway remodeling in Chronic Obstructive Pulmonary Disease (COPD). Pi10 represents the average wall thickness of a theoretical airway with a 10 mm lumen perimeter. Therefore, it is a key metric in characterizing airway-dominant phenotypes. Understanding the reliability of the Pi10 COPD biomarker is essential for clinical practice. Researchers compared ten different calculation methods for both Pi10 and PiSlope, evaluating their consistency and association with lung function.
Impact of Airway Count on Pi10 COPD Reliability
Studies revealed substantial variability in Pi10 values due to differing calculation methodologies. This new analysis evaluated the reliability among ten established methods. Scientists used the intraclass correlation (ICC) to assess consistency across these different approaches. Furthermore, they tested the associations between each method’s results and key lung function metrics like FEV1 and FEV1/FVC. The findings were clear and statistically significant.
Airway Count Drives Consistency in CT Biomarkers
Methods that included a higher count of segmented airways demonstrated excellent reliability. Specifically, the Patel, Nakano, Smith, Jobst, and Bhatt methods achieved an ICC of 0.90 or higher. Conversely, methods focusing on fewer, more specific airway generations—such as the Gietema, Park, and Telenga approaches—displayed moderate to poor reliability. Consequently, this lower reliability resulted in less consistent associations with lung function. We know Pi10 predicts disease severity and mortality in COPD patients. Therefore, researchers must choose a consistent calculation method. Only the more robust methods maintain a consistently strong, negative correlation with FEV1 and FEV1/FVC.
Evaluating PiSlope and its Role in COPD Airway Remodeling
PiSlope, which is the slope of the wall area/perimeter plot, also serves as a CT-derived biomarker. Interestingly, PiSlope generally demonstrated better consistency across the ten methods tested than Pi10. It also showed uniformly stronger and more consistent negative associations with FEV1 and FEV1/FVC across all calculation methods, regardless of the airway count used. PiSlope measures a different aspect of airway thickening variability than Pi10. Therefore, incorporating both Pi10 and PiSlope may provide a more comprehensive characterization of airway remodeling. Doctors should recognize that the method used to derive these CT biomarkers significantly impacts their clinical utility.
Frequently Asked Questions
Q1: What are Pi10 and PiSlope?
Both Pi10 and PiSlope are CT-derived biomarkers that help quantify airway remodeling in COPD. Pi10 measures the standardized airway wall thickness at a 10 mm perimeter. Conversely, PiSlope measures the slope relating the airway wall area to its perimeter.
Q2: Which Pi10 calculation methods offer the best reliability?
The calculation methods that incorporate a higher total count of segmented airways consistently showed the best reliability. These include the methods developed by Patel, Nakano, Smith, Jobst, and Bhatt, all demonstrating excellent reliability (ICC ≥ 0.90).
Q3: Why does the calculation method affect the Pi10 value?
The different methods vary primarily in the range of airway sizes or generations they include in the regression calculation. Consequently, methods that limit measurements to only a few airway generations or specific sizes result in inconsistent Pi10 values and weaker associations with lung function metrics.
References
- Enjilela R et al. Comparison of Pi10 and PiSlope calculation methods and association with lung function. Eur Radiol. 2025 Dec 21. doi: 10.1007/s00330-025-12226-4. PMID: 41422440.
- Kahnert K et al. Standardized airway wall thickness Pi10 from routine CT scans of COPD patients as imaging biomarker for disease severity, lung function decline, and mortality. Ther Adv Respir Dis. 22 Dec 2022;17:17534666221148663.
- Bhatt SP et al. PiSlope: A New CT Metric for Quantifying Airway Remodeling in Chronic Obstructive Pulmonary Disease. Radiology. 2024 Nov 26.