CT perfusion imaging of lung cancer: benefit of motion correction for blood flow estimates

Lisa L. Chu, Robert J. Knebel, Aryan D. Shay, Jonathan Santos, Ramsey D Badawi, David R Gandara, Friedrich D Knollmann

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Purpose: CT perfusion (CTP) imaging assessment of treatment response in advanced lung cancer can be compromised by respiratory motion. Our purpose was to determine whether an original motion correction method could improve the reproducibility of such measurements. Materials and methods: The institutional review board approved this prospective study. Twenty-one adult patients with non-resectable non-small-cell lung cancer provided written informed consent to undergo CTP imaging. A motion correction method that consisted of manually outlining the tumor margins and then applying a rigid manual landmark registration algorithm followed by the non-rigid diffeomorphic demons algorithm was applied. The non-motion-corrected and motion-corrected images were analyzed with dual blood supply perfusion analysis software. Two observers performed the analysis twice, and the intra- and inter-observer variability of each method was assessed with Bland-Altman statistics. Results: The 95% limits of agreement of intra-observer reproducibility for observer 1 improved from −84.4%, 65.3% before motion correction to −33.8%, 30.3% after motion correction (r = 0.86 and 0.97, before and after motion correction, p < 0.0001 for both) and for observer 2 from −151%, 96% to −49 %, 36 % (r = 0.87 and 0.95, p < 0.0001 for both). The 95% limits of agreement of inter-observer reproducibility improved from −168%, 154% to −17%, 25%. Conclusion: The use of a motion correction method significantly improves the reproducibility of CTP estimates of tumor blood flow in lung cancer. Key Points: • Tumor blood flow estimates in advanced lung cancer show significant variability.• Motion correction improves the reproducibility of CT blood flow estimates in advanced lung cancer.• Reproducibility of blood flow measurements is critical to characterize lung tumor biology and the success of treatment in lung cancer.

Original languageEnglish (US)
Pages (from-to)1-7
Number of pages7
JournalEuropean Radiology
DOIs
StateAccepted/In press - Jun 4 2018

Fingerprint

Perfusion Imaging
Lung Neoplasms
Neoplasms
Perfusion
Observer Variation
Research Ethics Committees
Informed Consent
Non-Small Cell Lung Carcinoma
Software
Prospective Studies
Lung

Keywords

  • Cancer
  • Diagnostic imaging
  • Lung
  • Perfusion imaging
  • Tomography, x-ray computed

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

CT perfusion imaging of lung cancer : benefit of motion correction for blood flow estimates. / Chu, Lisa L.; Knebel, Robert J.; Shay, Aryan D.; Santos, Jonathan; Badawi, Ramsey D; Gandara, David R; Knollmann, Friedrich D.

In: European Radiology, 04.06.2018, p. 1-7.

Research output: Contribution to journalArticle

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abstract = "Purpose: CT perfusion (CTP) imaging assessment of treatment response in advanced lung cancer can be compromised by respiratory motion. Our purpose was to determine whether an original motion correction method could improve the reproducibility of such measurements. Materials and methods: The institutional review board approved this prospective study. Twenty-one adult patients with non-resectable non-small-cell lung cancer provided written informed consent to undergo CTP imaging. A motion correction method that consisted of manually outlining the tumor margins and then applying a rigid manual landmark registration algorithm followed by the non-rigid diffeomorphic demons algorithm was applied. The non-motion-corrected and motion-corrected images were analyzed with dual blood supply perfusion analysis software. Two observers performed the analysis twice, and the intra- and inter-observer variability of each method was assessed with Bland-Altman statistics. Results: The 95{\%} limits of agreement of intra-observer reproducibility for observer 1 improved from −84.4{\%}, 65.3{\%} before motion correction to −33.8{\%}, 30.3{\%} after motion correction (r = 0.86 and 0.97, before and after motion correction, p < 0.0001 for both) and for observer 2 from −151{\%}, 96{\%} to −49 {\%}, 36 {\%} (r = 0.87 and 0.95, p < 0.0001 for both). The 95{\%} limits of agreement of inter-observer reproducibility improved from −168{\%}, 154{\%} to −17{\%}, 25{\%}. Conclusion: The use of a motion correction method significantly improves the reproducibility of CTP estimates of tumor blood flow in lung cancer. Key Points: • Tumor blood flow estimates in advanced lung cancer show significant variability.• Motion correction improves the reproducibility of CT blood flow estimates in advanced lung cancer.• Reproducibility of blood flow measurements is critical to characterize lung tumor biology and the success of treatment in lung cancer.",
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T2 - benefit of motion correction for blood flow estimates

AU - Chu, Lisa L.

AU - Knebel, Robert J.

AU - Shay, Aryan D.

AU - Santos, Jonathan

AU - Badawi, Ramsey D

AU - Gandara, David R

AU - Knollmann, Friedrich D

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N2 - Purpose: CT perfusion (CTP) imaging assessment of treatment response in advanced lung cancer can be compromised by respiratory motion. Our purpose was to determine whether an original motion correction method could improve the reproducibility of such measurements. Materials and methods: The institutional review board approved this prospective study. Twenty-one adult patients with non-resectable non-small-cell lung cancer provided written informed consent to undergo CTP imaging. A motion correction method that consisted of manually outlining the tumor margins and then applying a rigid manual landmark registration algorithm followed by the non-rigid diffeomorphic demons algorithm was applied. The non-motion-corrected and motion-corrected images were analyzed with dual blood supply perfusion analysis software. Two observers performed the analysis twice, and the intra- and inter-observer variability of each method was assessed with Bland-Altman statistics. Results: The 95% limits of agreement of intra-observer reproducibility for observer 1 improved from −84.4%, 65.3% before motion correction to −33.8%, 30.3% after motion correction (r = 0.86 and 0.97, before and after motion correction, p < 0.0001 for both) and for observer 2 from −151%, 96% to −49 %, 36 % (r = 0.87 and 0.95, p < 0.0001 for both). The 95% limits of agreement of inter-observer reproducibility improved from −168%, 154% to −17%, 25%. Conclusion: The use of a motion correction method significantly improves the reproducibility of CTP estimates of tumor blood flow in lung cancer. Key Points: • Tumor blood flow estimates in advanced lung cancer show significant variability.• Motion correction improves the reproducibility of CT blood flow estimates in advanced lung cancer.• Reproducibility of blood flow measurements is critical to characterize lung tumor biology and the success of treatment in lung cancer.

AB - Purpose: CT perfusion (CTP) imaging assessment of treatment response in advanced lung cancer can be compromised by respiratory motion. Our purpose was to determine whether an original motion correction method could improve the reproducibility of such measurements. Materials and methods: The institutional review board approved this prospective study. Twenty-one adult patients with non-resectable non-small-cell lung cancer provided written informed consent to undergo CTP imaging. A motion correction method that consisted of manually outlining the tumor margins and then applying a rigid manual landmark registration algorithm followed by the non-rigid diffeomorphic demons algorithm was applied. The non-motion-corrected and motion-corrected images were analyzed with dual blood supply perfusion analysis software. Two observers performed the analysis twice, and the intra- and inter-observer variability of each method was assessed with Bland-Altman statistics. Results: The 95% limits of agreement of intra-observer reproducibility for observer 1 improved from −84.4%, 65.3% before motion correction to −33.8%, 30.3% after motion correction (r = 0.86 and 0.97, before and after motion correction, p < 0.0001 for both) and for observer 2 from −151%, 96% to −49 %, 36 % (r = 0.87 and 0.95, p < 0.0001 for both). The 95% limits of agreement of inter-observer reproducibility improved from −168%, 154% to −17%, 25%. Conclusion: The use of a motion correction method significantly improves the reproducibility of CTP estimates of tumor blood flow in lung cancer. Key Points: • Tumor blood flow estimates in advanced lung cancer show significant variability.• Motion correction improves the reproducibility of CT blood flow estimates in advanced lung cancer.• Reproducibility of blood flow measurements is critical to characterize lung tumor biology and the success of treatment in lung cancer.

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KW - Diagnostic imaging

KW - Lung

KW - Perfusion imaging

KW - Tomography, x-ray computed

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