Skip to main content
  • Poster presentation
  • Open access
  • Published:

Potential influence of automated volumetry on treatment response classifications in lung cancer lesions

Purpose

To evaluate the potential influence of automated volumetry on treatment response classifications in lung cancer in comparison to manual unidimensional measurements.

Material and methods

  1. 60

    patients (41 men, 19 women, mean age 61.8 ± 9.4 years) with histopathologically verified lung cancer were included in this retrospective study.

For each patient, up to 2 target lesions were quantitatively evaluated in a baseline and two follow-up CT scans (77 lesions, 154 response classifications) by two independent radiologists. Hilar and mediastinal masses, as well as lesions surrounded by atelectasis were excluded.

For each lesion a unidimensional diameter measurement, as well as an automated CT-volumetry was performed. In the follow-up studies, the response evaluation was assessed using RECIST compared to volume equivalents of RECIST with converted thresholds (-65/+73%).

Results

The results of the manual one-dimensional measurements varied between the two observers by 6.34 ± 17.12%, affecting the volume to the power of 3, whereas the volumetric measurements varied only by 3.33 ± 6.66%.

In 16.9% (26/154) of the cases the volumetric assessment led to a different response classification.

In 13% (20/154) of the cases the different response classification would have an effect on therapeutic decisions.

Conclusion

The volumetric assessment of lung cancer lesions can reflect the tumour burden more appropriately and therefore has a significant effect on response classifications and therapeutic decisions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kaveh Akbari.

Rights and permissions

Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

The Creative Commons Public Domain Dedication waiver (https://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Akbari, K., Barthol, A., Schnauder, I. et al. Potential influence of automated volumetry on treatment response classifications in lung cancer lesions. cancer imaging 14 (Suppl 1), P30 (2014). https://doi.org/10.1186/1470-7330-14-S1-P30

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/1470-7330-14-S1-P30

Keywords