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4D CT lung ventilation images are affected by the 4D CT sorting method.

Tokihiro Yamamoto1, Sven Kabus, Cristian Lorenz

  • 1Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305-5847 and Department of Radiation Oncology, University of California Davis School of Medicine, Sacramento, California 95817.

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Summary

Four-dimensional computed tomography (4D CT) sorting methods impact lung ventilation imaging accuracy. Anatomic similarity-based sorting reduces artifacts and improves physiologic accuracy compared to phase-based sorting.

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Area of Science:

  • Medical Imaging
  • Pulmonary Function Analysis
  • Radiology

Background:

  • Four-dimensional computed tomography (4D CT) is a promising technique for lung functional imaging.
  • Current phase-based sorting methods for 4D CT can introduce artifacts, potentially compromising ventilation imaging accuracy.
  • Artifacts in 4D CT imaging can lead to inaccurate assessments of lung function.

Purpose of the Study:

  • To quantify the variability in four-dimensional computed tomography (4D CT) ventilation imaging caused by different 4D CT sorting techniques.
  • To compare the artifact reduction and accuracy of anatomic similarity-based sorting versus phase-based sorting for 4D CT ventilation imaging.

Main Methods:

  • 4D CT datasets from nine lung cancer patients were processed using both phase-based and anatomic similarity-based sorting methods.
  • Artifacts were quantified using an artifact score based on normalized cross-correlation of CT slices.
  • Ventilation variation was assessed using voxel-based Spearman rank correlation and Dice similarity coefficients (DSC).
  • Correlation with single-photon emission CT (SPECT) ventilation images was evaluated for physiologic accuracy.

Main Results:

  • Anatomic similarity-based sorting demonstrated a trend towards reduced artifacts compared to phase-based sorting.
  • Voxel-based correlation between ventilation images from the two methods averaged 0.69, with significant variability.
  • Anatomic similarity-based sorting resulted in fewer voxels with paradoxical negative ventilation (5.0% vs 9.7%) and improved regional correlation with SPECT.
  • Dice similarity coefficients (DSC) averaged 0.71, indicating moderate spatial overlap.

Conclusions:

  • Variability in 4D CT ventilation imaging due to sorting methods is significant, highlighting the impact of 4D CT artifacts.
  • Reducing 4D CT artifacts through methods like anatomic similarity-based sorting can lead to more physiologically accurate ventilation estimates.
  • Further research is necessary to validate these findings and optimize 4D CT sorting for improved lung functional imaging.