Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression
Objectives: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.
Materials and Methods: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.
Results: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p<0.001) and VfSAD (β of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.
Conclusions: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.
| Errataetall: |
UpdateIn: Respir Res. 2024 Feb 28;25(1):106. - PMID 38419014 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2023 |
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| Enthalten in: |
medRxiv : the preprint server for health sciences - (2023) vom: 20. Nov. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Bell, Alexander J [VerfasserIn] |
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| Links: |
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| Themen: |
Chronic obstructive pulmonary disease |
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| Anmerkungen: |
Date Revised 11.03.2024 published: Electronic UpdateIn: Respir Res. 2024 Feb 28;25(1):106. - PMID 38419014 Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1101/2023.05.26.23290532 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM358349354 |
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| 100 | 1 | |a Bell, Alexander J |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
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| 500 | |a Date Revised 11.03.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a UpdateIn: Respir Res. 2024 Feb 28;25(1):106. - PMID 38419014 | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Objectives: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline | ||
| 520 | |a Materials and Methods: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model | ||
| 520 | |a Results: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p<0.001) and VfSAD (β of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69 | ||
| 520 | |a Conclusions: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression | ||
| 650 | 4 | |a Preprint | |
| 650 | 4 | |a chronic obstructive pulmonary disease | |
| 650 | 4 | |a computed tomography of the chest | |
| 650 | 4 | |a emphysema | |
| 650 | 4 | |a machine learning | |
| 650 | 4 | |a parametric response mapping | |
| 650 | 4 | |a small airways disease | |
| 700 | 1 | |a Pal, Ravi |e verfasserin |4 aut | |
| 700 | 1 | |a Labaki, Wassim W |e verfasserin |4 aut | |
| 700 | 1 | |a Hoff, Benjamin A |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Jennifer M |e verfasserin |4 aut | |
| 700 | 1 | |a Murray, Susan |e verfasserin |4 aut | |
| 700 | 1 | |a Kazerooni, Ella A |e verfasserin |4 aut | |
| 700 | 1 | |a Galban, Stefanie |e verfasserin |4 aut | |
| 700 | 1 | |a Lynch, David A |e verfasserin |4 aut | |
| 700 | 1 | |a Humphries, Stephen M |e verfasserin |4 aut | |
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| 700 | 1 | |a Hatt, Charles R |e verfasserin |4 aut | |
| 700 | 1 | |a Han, MeiLan K |e verfasserin |4 aut | |
| 700 | 1 | |a Ram, Sundaresh |e verfasserin |4 aut | |
| 700 | 1 | |a Galban, Craig J |e verfasserin |4 aut | |
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