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Persistent pulmonary subsolid nodules: model-based iterative reconstruction for nodule classification and measurement variability on low-dose CT

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Abstract

Objectives

To compare the pulmonary subsolid nodule (SSN) classification agreement and measurement variability between filtered back projection (FBP) and model-based iterative reconstruction (MBIR).

Methods

Low-dose CTs were reconstructed using FBP and MBIR for 47 patients with 47 SSNs. Two readers independently classified SSNs into pure or part-solid ground-glass nodules, and measured the size of the whole nodule and solid portion twice on both reconstruction algorithms. Nodule classification agreement was analyzed using Cohen’s kappa and compared between reconstruction algorithms using McNemar’s test. Measurement variability was investigated using Bland–Altman analysis and compared with the paired t-test.

Results

Cohen’s kappa for inter-reader SSN classification agreement was 0.541–0.662 on FBP and 0.778–0.866 on MBIR. Between the two readers, nodule classification was consistent in 79.8 % (75/94) with FBP and 91.5 % (86/94) with MBIR (p = 0.027). Inter-reader measurement variability range was -5.0–2.1 mm on FBP and -3.3–1.8 mm on MBIR for whole nodule size, and was -6.5–0.9 mm on FBP and -5.5–1.5 mm on MBIR for solid portion size. Inter-reader measurement differences were significantly smaller on MBIR (p = 0.027, whole nodule; p = 0.011, solid portion).

Conclusions

MBIR significantly improved SSN classification agreement and reduced measurement variability of both whole nodules and solid portions between readers.

Key Points

• Low-dose CT using MBIR algorithm improves reproducibility in the classification of SSNs.

• MBIR would enable more confident clinical planning according to the SSN type.

• Reduced measurement variability on MBIR allows earlier detection of potentially malignant nodules.

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Abbreviations

SSN:

Subsolid nodule

IR:

Iterative reconstruction

CT:

Computed tomography

MBIR:

Model-based iterative reconstruction

FBP:

Filtered back projection

GGN:

Ground-glass nodule

CTDIvol :

Volume CT dose index

DLP:

Dose-length product

SSDE:

Size-specific dose estimate

ED:

Effective dose

ICRP:

International Commission on Radiological Protection

PACS:

Picture archiving and communication system

HU:

Hounsfield unit

CI:

Confidence interval

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Acknowledgements

The scientific guarantor of this publication is Chang Min Park, MD, PhD. The authors of this manuscript declare no relationship with any companies whose products or services may be related to the subject matter of the article. No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Study subjects have not been previously reported in other journals. Methodology: retrospective diagnostic study, performed at one institution.

This study was supported by a research grant from the Korean Foundation for Cancer Research (grant number: CB-2011-02-01).

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Authors and Affiliations

  1. Department of Radiology, Seoul National University College of Medicine, 101 Daehangno, Jongno-gu, Seoul, 110-744, South Korea

    Hyungjin Kim, Chang Min Park, Seong Ho Kim, Sang Min Lee, Sang Joon Park, Kyung Hee Lee & Jin Mo Goo

  2. Institute of Radiation Medicine, Seoul National University Medical Research Center, 101 Daehangno, Jongno-gu, Seoul, 110-744, South Korea

    Hyungjin Kim, Chang Min Park, Seong Ho Kim, Sang Min Lee, Sang Joon Park, Kyung Hee Lee & Jin Mo Goo

  3. Cancer Research Institute, Seoul National University, 101, Daehangno, Jongno-gu, Seoul, 110-744, South Korea

    Chang Min Park, Sang Joon Park & Jin Mo Goo

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  1. Hyungjin Kim
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Correspondence to Chang Min Park.

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Kim, H., Park, C.M., Kim, S.H. et al. Persistent pulmonary subsolid nodules: model-based iterative reconstruction for nodule classification and measurement variability on low-dose CT. Eur Radiol 24, 2700–2708 (2014). https://doi.org/10.1007/s00330-014-3306-7

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  • DOI: https://doi.org/10.1007/s00330-014-3306-7

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