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Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases

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Abstract

Objectives

To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth.

Materials and methods

For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE).

Results

SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004)

Conclusion

Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold.

Key Points

• The 95 % percentile APE of a particular nodule can be predicted.

• Estimated 95 % percentile APE can be utilized as an individualized threshold.

• More sensitive diagnosis of metastasis can be made with an individualized threshold.

• Tailored nodule management can be provided during nodule growth follow-up.

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Abbreviations

AP:

Attachment proportion

APE:

Absolute percentage error

CT:

Computed tomography

HU:

Hounsfield unit

RECIST:

Response Evaluation Criteria in Solid Tumours

SVP:

Surface voxel proportion

Vm :

Mean volume of segmented nodule

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Acknowledgements

The scientific guarantor of this publication is Jin Mo Goo. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. This study was supported by grant no. 34-2013-0020 from the SK Telecom Research Fund. One of the authors (Soyeon Ahn) has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. No study subjects or cohorts have been previously reported in the literature. Methodology: prospective, diagnostic or prognostic study, performed at one institution.

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Authors and Affiliations

  1. Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea

    Eui Jin Hwang, Jin Mo Goo, Sang Joon Park & Chang Min Park

  2. Deparment of Radiology, Armed Forces Seoul Hospital, Seoul, Korea

    Eui Jin Hwang

  3. Cancer Research Institute, Seoul National University, Seoul, Korea

    Jin Mo Goo, Sang Joon Park & Chang Min Park

  4. School of Computer Science and Engineering, Seoul National University, Seoul, Korea

    Jihye Kim & Yeong-Gil Shin

  5. Medical Research Collaborating Center, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Korea

    Soyeon Ahn

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  1. Eui Jin Hwang
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  2. Jin Mo Goo
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  3. Jihye Kim
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Correspondence to Jin Mo Goo.

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Hwang, E.J., Goo, J.M., Kim, J. et al. Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases. Eur Radiol 27, 3257–3265 (2017). https://doi.org/10.1007/s00330-016-4713-8

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  • DOI: https://doi.org/10.1007/s00330-016-4713-8

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