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European Radiology

Erschienen in:

31.05.2022 | Imaging Informatics and Artificial Intelligence

Importance of CT image normalization in radiomics analysis: prediction of 3-year recurrence-free survival in non-small cell lung cancer

verfasst von: Doohyun Park, Daejoong Oh, MyungHoon Lee, Shin Yup Lee, Kyung Min Shin, Johnson SG Jun, Dosik Hwang

Erschienen in: European Radiology | Ausgabe 12/2022

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Abstract

Objectives

To analyze whether CT image normalization can improve 3-year recurrence-free survival (RFS) prediction performance in patients with non-small cell lung cancer (NSCLC) relative to the use of unnormalized CT images.

Methods

A total of 106 patients with NSCLC were included in the training set. For each patient, 851 radiomic features were extracted from the normalized and the unnormalized CT images, respectively. After the feature selection, random forest models were constructed with selected radiomic features and clinical features. The models were then externally validated in the test set consisting of 79 patients with NSCLC.

Results

The model using normalized CT images yielded better performance than the model using unnormalized CT images (with an area under the receiver operating characteristic curve of 0.802 vs 0.702, p = 0.01), with the model performing especially well among patients with adenocarcinoma (with an area under the receiver operating characteristic curve of 0.880 vs 0.720, p < 0.01).

Conclusions

CT image normalization may improve prediction performance among patients with NSCLC, especially for patients with adenocarcinoma.

Key Points

• After CT image normalization, more radiomic features were able to be identified.

• Prognostic performance in patients was improved significantly after CT image normalization compared with before the CT image normalization.

• The improvement in prognostic performance following CT image normalization was superior in patients with adenocarcinoma.

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Titel: Importance of CT image normalization in radiomics analysis: prediction of 3-year recurrence-free survival in non-small cell lung cancer
verfasst von: Doohyun Park
Daejoong Oh
MyungHoon Lee
Shin Yup Lee
Kyung Min Shin
Johnson SG Jun
Dosik Hwang
Publikationsdatum: 31.05.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 12/2022
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-022-08869-2

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Importance of CT image normalization in radiomics analysis: prediction of 3-year recurrence-free survival in non-small cell lung cancer

Abstract

Objectives

Methods

Results

Conclusions

Key Points

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Abstract

Objectives

Methods

Results

Conclusions

Key Points

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