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Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis

Fabien Maldonado, Teng Moua, Srinivasan Rajagopalan, Ronald A. Karwoski, Sushravya Raghunath, Paul A. Decker, Thomas E. Hartman, Brian J. Bartholmai, Richard A. Robb, Jay H. Ryu
European Respiratory Journal 2014 43: 204-212; DOI: 10.1183/09031936.00071812
Fabien Maldonado
1Division of Pulmonary and Critical Care, Mayo Clinic Rochester, Rochester, MN
5These authors contributed equally
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  • For correspondence: Maldonado.Fabien@mayo.edu
Teng Moua
1Division of Pulmonary and Critical Care, Mayo Clinic Rochester, Rochester, MN
5These authors contributed equally
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Srinivasan Rajagopalan
2Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN
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Ronald A. Karwoski
2Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN
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Sushravya Raghunath
2Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN
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Paul A. Decker
3Dept of Biomedical Statistics and Informatics, Mayo Clinic Rochester, Rochester, MN
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Thomas E. Hartman
4Division of Radiology, Mayo Clinic Rochester, Rochester, MN, USA
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Brian J. Bartholmai
4Division of Radiology, Mayo Clinic Rochester, Rochester, MN, USA
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Richard A. Robb
2Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN
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Jay H. Ryu
1Division of Pulmonary and Critical Care, Mayo Clinic Rochester, Rochester, MN
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  • Figure 1–
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    Figure 1–

    Computed tomography images demonstrating a) normal appearance and various visual manifestations of diffuse lung disease: b) ground glass, c) reticular changes (arrows), d) honeycombing (arrows) and e) emphysema (arrow)). In training datasets, the consensus of four thoracic radiologists was used to identify multiple volumes of interest of 15×15×15 pixels corresponding to normal, ground-glass density, reticular abnormalities, honeycombing and emphysema.

  • Figure 2–
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    Figure 2–

    Representative results from the quantitative analysis of CALIPER. The two rows (a–c) and (d–f) correspond to the two time-points from one of the patients. The individual voxels of the lung regions in the original sections (a and d) are classified and colour-coded into one of the classes of visible abnormalities (b and e). c and f) Three-dimensional maximum feature projections. CALIPER quantification and radiologist reviews were both indicative of an overall increase in ground-glass opacities, reticular abnormalities and honeycombing.

Tables

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  • Table 1– Demographic data#
    Age years72.4±6.9
    Females/males28 (51)/27 (49)
    Height cm168.0±9.4
    Smoking history
     Active1 (2)
     Previous34 (62)
     Never20 (36)
    Transplanted2 (4)
    Surgical lung biopsy confirmation31 (56)
    Mean interval between HRCT scans days289.2±109.7 (55–540)
    Median follow-up years (range)2.4 (0.1–8.5)
    Deaths37 (67)
    Scan type 110 HRCT scans
     GE 8375
     Siemens 2725
    • Data are presented as mean±sd, n (%), mean±sd (range) or n, unless otherwise stated. HRCT: high-resolution computed tomography. #: total subjects n=55.

  • Table 2– Raw and % predicted pulmonary function test values corresponding with computed tomography scans at time-points 1 and 2
    ParameterTime-point 1Time-point 2Difference±sd
    TLC % pred67.3±9.665.9±9.7-3.4±5.6
    TLC L3.9±0.83.9±0.8-0.2±0.3
    FVC % pred67.5±14.164.1±16.8-3.4±8.2
    FVC L2.4±0.82.3±0.8-0.1±0.3
    FEV1 % pred72.0±14.768.9±16.9-3.1±8.5
    FEV1 L2.0±0.61.9±0.6-0.1±0.2
    DLCO % pred50.6±14.545.7±12.4-7.0±11.6
    DLCO mL·min−1·mmHg−111.7±4.010.7±3.0-1.5±2.6
    • Data are presented as mean±sd. TLC: total lung capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; DLCO: diffusing capacity of the lung for carbon monoxide.

  • Table 3– Mean volumetric measurements and changes for computed tomography findings at time-points 1 and 2
    FindingTime-point 1Time-point 2Difference±sd
    Total normal L2.5±1.02.2±1.1-0.3±0.6
    Total emphysema L0.02±0.040.01±0.03-0.002±0.03
    Total emphysema %0.4±1.20.4±1.00.0±0.9
    Total GGO L0.3±0.30.4±0.40.08±0.3
    Total GGO# %10.2±10.613.3±12.83.2±9.8
    Total reticular L0.5±0.30.6±0.40.06±0.2
    Total reticular# %15.1±9.918.1±12.43.0±6.4
    Total honeycombing L0.2±0.30.2±0.3-0.01±0.2
    Total honeycombing# %6.0±6.96.0±8.8-0.1±6.3
    Total ILD L1.1±0.61.2±0.60.1±0.4
    Total ILD# %31.3±16.837.4±22.16.1±13.0
    Total lung volume L3.6±0.83.5±0.9-0.2±0.4
    • Data are presented as mean±sd, unless otherwise stated. GGO: ground-glass opacities; ILD: interstitial lung disease (ground glass + reticular + honeycombing). #: % of total lung volume.

  • Table 4– Radiologists' assessment of computed tomography findings at time-points 1 and 2
    FindingTime-point 1Time-point 2Difference±sd
    Radiologist 1
     Total emphysema %1.3±4.01.3±3.90.0±0.7
     Total GGO %14.9±17.517.5±20.72.6±8.5
     Total reticular %17.6±9.619.9±10.92.3±4.6
     Total honeycombing %3.5±7.93.7±8.40.2±1.0
    Radiologist 2
     Total emphysema %1.3±3.91.4±3.90.1±0.5
     Total GGO %22.2±20.324.8±24.42.6±11.0
     Total reticular %18.2±8.218.6±8.50.4±1.9
     Total honeycombing %1.7±6.21.7±6.30.1±0.5
    • Data are presented as mean±sd, unless otherwise stated. GGO: ground-glass opacities.

  • Table 5– Survival analysis of pulmonary function tests and CALIPER measurement
    DifferenceUnivariableAdjusted
    HR95% CIp-valueHR95% CIp-value
    TLC % pred#1.190.67–2.120.554.171.42–12.00.009
    FVC % pred#1.100.76–1.620.601.540.95–2.510.081
    FEV1 % pred#1.210.82–1.790.331.460.93–2.290.099
    DLCO % pred#1.420.93–2.160.112.141.27–3.600.004
    Total emphysema¶1.190.87–1.650.281.290.92–1.790.14
    Total emphysema¶ %1.100.85–1.410.481.160.87–1.540.32
    Total GG¶1.401.05–1.850.0221.300.88–1.900.19
    Total GG¶ %1.290.98–1.700.0721.210.85–1.730.28
    Total reticular¶1.350.91–1.990.141.911.21–3.00.006
    Total reticular¶ %1.381.03–1.840.0321.931.30–2.890.001
    Total honeycombing¶0.950.74–1.210.681.030.80–1.310.84
    Total honeycombing¶ %0.940.74–1.200.621.020.80–1.290.90
    Total ILD¶1.471.08–2.00.0161.701.19–2.430.003
    Total ILD¶ %1.300.99–1.710.0621.521.08–2.150.017
    Emphysema radiologist 1¶1.320.89–1.970.171.320.88–1.980.18
    Emphysema radiologist 2¶0.820.52–1.290.381.480.79–2.770.22
    GG radiologist 1¶1.160.86–1.570.321.400.97–2.020.070
    GG radiologist 2¶1.020.77–1.350.881.240.92–1.670.16
    Honeycombing radiologist 1¶1.070.74–1.540.731.120.72–1.750.61
    Honeycombing radiologist 2¶1.100.79–1.540.561.110.75–1.650.60
    Reticular radiologist 1¶1.110.84–1.470.461.200.87–1.640.27
    Reticular radiologist 2¶1.140.70–1.840.601.030.63–1.680.92
    Change radiologist 1
     Improved/stableRef.Ref.
     Worse2.11.09–4.040.0262.221.08–4.560.029
    Change radiologist 2
     Improved/stableRef.Ref.
     Worse1.860.96–3.610.0662.501.12–5.540.025
    • CALIPER: Computer-Aided Lung Informatics for Pathology, Evaluation and Ratings; HR: hazard ratio; TLC: total lung capacity; % pred; % predicted; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 second; DLCO: diffusing capacity of the lung for carbon monoxide; ILD: interstitial lung disease (ground glass (GG) + reticular + honeycombing); Ref: reference.#: HRs are for a 15-unit change in DLCO % pred and a 10-unit change in FEV1 % pred, FVC % pred and TLC % pred; ¶: HRs are for a sd change.

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    Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

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  • Supplementary material

    Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

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    • Supplementary material -
      1. Texture Feature extraction
      1.1 Training set generation
      1.2 Visualization of VOI similarities
      1.3 Assessing separability quality of CVM similarity metric
      1.4 Identification of exemplar VOIs
      2. Data Processing
      2.1 Lung Segmentation
      2.2 Airway extraction
      2.3 Lung Separation
      2.4 Vessel Extraction
      2.5 Parenchymal Classification
      3. Variations in Parenchymal Classification due to slice thickness
  • Disclosures

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Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis
Fabien Maldonado, Teng Moua, Srinivasan Rajagopalan, Ronald A. Karwoski, Sushravya Raghunath, Paul A. Decker, Thomas E. Hartman, Brian J. Bartholmai, Richard A. Robb, Jay H. Ryu
European Respiratory Journal Jan 2014, 43 (1) 204-212; DOI: 10.1183/09031936.00071812

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Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis
Fabien Maldonado, Teng Moua, Srinivasan Rajagopalan, Ronald A. Karwoski, Sushravya Raghunath, Paul A. Decker, Thomas E. Hartman, Brian J. Bartholmai, Richard A. Robb, Jay H. Ryu
European Respiratory Journal Jan 2014, 43 (1) 204-212; DOI: 10.1183/09031936.00071812
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