scholarly journals Topological Parametric Response Mapping (PRM) Analysis for Spatially Localized Parenchymal Characterization in COPD: A COPDGene Study

Author(s):  
A.J. Bell ◽  
S. Ram ◽  
W.W. Labaki ◽  
S. Murray ◽  
E. Kazerooni ◽  
...  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thao Thi Ho ◽  
Taewoo Kim ◽  
Woo Jin Kim ◽  
Chang Hyun Lee ◽  
Kum Ju Chae ◽  
...  

AbstractChronic obstructive pulmonary disease (COPD) is a respiratory disorder involving abnormalities of lung parenchymal morphology with different severities. COPD is assessed by pulmonary-function tests and computed tomography-based approaches. We introduce a new classification method for COPD grouping based on deep learning and a parametric-response mapping (PRM) method. We extracted parenchymal functional variables of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%) with an image registration technique, being provided as input parameters of 3D convolutional neural network (CNN). The integrated 3D-CNN and PRM (3D-cPRM) achieved a classification accuracy of 89.3% and a sensitivity of 88.3% in five-fold cross-validation. The prediction accuracy of the proposed 3D-cPRM exceeded those of the 2D model and traditional 3D CNNs with the same neural network, and was comparable to that of 2D pretrained PRM models. We then applied a gradient-weighted class activation mapping (Grad-CAM) that highlights the key features in the CNN learning process. Most of the class-discriminative regions appeared in the upper and middle lobes of the lung, consistent with the regions of elevated fSAD% and Emph% in COPD subjects. The 3D-cPRM successfully represented the parenchymal abnormalities in COPD and matched the CT-based diagnosis of COPD.


PET Clinics ◽  
2013 ◽  
Vol 8 (2) ◽  
pp. 201-217 ◽  
Author(s):  
Benjamin M. Ellingson ◽  
Wei Chen ◽  
Robert J. Harris ◽  
Whitney B. Pope ◽  
Albert Lai ◽  
...  

Bone ◽  
2012 ◽  
Vol 51 (1) ◽  
pp. 78-84 ◽  
Author(s):  
Benjamin A. Hoff ◽  
Kenneth M. Kozloff ◽  
Jennifer L. Boes ◽  
Jean-Christophe Brisset ◽  
Stefanie Galbán ◽  
...  

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Rachel N. Criner ◽  
Charles R. Hatt ◽  
Craig J. Galbán ◽  
Ella A. Kazerooni ◽  
David A. Lynch ◽  
...  

Abstract Impaired single breath carbon monoxide diffusing capacity (DLCO) is associated with emphysema. Small airways disease (SAD) may be a precursor lesion to emphysema, but the relationship between SAD and DLCO is undescribed. We hypothesized that in mild COPD, functional SAD (fSAD) defined by computed tomography (CT) and Parametric Response Mapping methodology would correlate with impaired DLCO. Using data from ever-smokers in the COPDGene cohort, we established that fSAD correlated significantly with lower DLCO among both non-obstructed and GOLD 1–2 subjects. The relationship between DLCO with CT-defined emphysema was present in all GOLD stages, but most prominent in severe disease. Trial registration NCT00608764. Registry: COPDGene. Registered 06 February 2008, retrospectively registered.


Author(s):  
Craig Galban ◽  
Ryan Chamberlain ◽  
Benjamin Hoff ◽  
Timothy Johnson ◽  
Ella Kazerooni ◽  
...  

2017 ◽  
Vol 195 (7) ◽  
pp. 942-952 ◽  
Author(s):  
Elizabeth A. Belloli ◽  
Irina Degtiar ◽  
Xin Wang ◽  
Gregory A. Yanik ◽  
Linda J. Stuckey ◽  
...  

2020 ◽  
Vol 129 (3) ◽  
pp. 583-590 ◽  
Author(s):  
Sylvia A.B. Verbanck ◽  
Mathias Polfliet ◽  
Daniel Schuermans ◽  
Bart Ilsen ◽  
Johan de Mey ◽  
...  

A head-on comparison between imaging and multiple breath washout in supine smokers shows that computer tomography-measured unequal local lung expansion accounts for 50% or less of smoking-induced increase in ventilation heterogeneity. The contributions from unequal lung expansion and peripheral structure to the two main washout indices also explain their respective association with parametric response mapping indices.


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