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Normalization of Ventilation Data from 4D-CT to Facilitate Comparison between Datasets Acquired at Different Times

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Listed:
  • Kujtim Latifi
  • Vladimir Feygelman
  • Eduardo G Moros
  • Thomas J Dilling
  • Craig W Stevens
  • Geoffrey G Zhang

Abstract

Purpose: The 4D-CT data used for comparing a patient’s ventilation distributions before and after lung radiotherapy are acquired at different times. As a result, an additional variable – the tidal volume (TV) – can alter the results. Therefore, in this paper we propose to normalize the ventilation to the same TV to eliminate that uncertainty. Methods: Absolute ventilation (AV) data were generated for 6 stereotactic body radiation therapy (SBRT) cases before and after treatment, using the direct geometric algorithm and diffeomorphic morphons deformable image registration (DIR). Each pair of AV distributions was converted to TV-normalized, percentile ventilation (PV) and low-dose well-ventilated-normalized ventilation (LDWV) distributions. The ventilation change was calculated in various dose regions based on the treatment plans using the DIR-registered before and after treatment data sets. The ventilation change based on TV-normalized ventilation was compared with the AV as well as the data normalized by PV and LDWV. Results: AV change may be misleading when the TV differs before and after treatment, which was found to be up to 6.7%. All three normalization methods produced a similar trend in ventilation change: the higher the dose to a region of lung, the greater the degradation in ventilation. In low dose regions (

Suggested Citation

  • Kujtim Latifi & Vladimir Feygelman & Eduardo G Moros & Thomas J Dilling & Craig W Stevens & Geoffrey G Zhang, 2013. "Normalization of Ventilation Data from 4D-CT to Facilitate Comparison between Datasets Acquired at Different Times," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    • Handle: RePEc:plo:pone00:0084083
    DOI: 10.1371/journal.pone.0084083
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