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CT-Based Radiomics Analysis Before Thermal Ablation to Predict Local Tumor Progression for Colorectal Liver Metastases

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  • Imaging
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Abstract

Purpose

Predicting early local tumor progression after thermal ablation treatment for colorectal liver metastases patients is critical for the decision of subsequent follow-up and treatment. Radiomics features derived from medical images show great potential for prediction and prognosis. The aim is to develop and validate a machine learning radiomics model to predict local tumor progression based on the pre-ablation CT scan of colorectal liver metastases patients.

Materials and Methods

Ninety patients with colorectal liver metastases (140 lesions) treated by ablation were included in the study and were randomly divided into a training (n = 63 patients/n = 94 lesions) and validation (n = 27 patients/n = 46 lesions) cohort. After manual lesion volume segmentation and preprocessing, 1593 radiomics features were extracted for each lesion. Three machine learning survival models were constructed based on (1) radiomics features, (2) clinical features and (3) a combination of clinical and radiomics features to predict local tumor progression free survival. Feature reduction and machine learning modeling were performed and optimized with sequential model-based optimization.

Results

Median follow-up was 24 months (range 6–115). Thirty-one (22%) lesions developed local tumor progression. The concordance index in the validation set to predict local tumor progression free survival was 0.78 (95% confidence interval [CI]: 0.77–0.79) for the radiomics model, 0.56 (95%CI: 0.55–0.57) for the clinical model and 0.79 (95%CI: 0.78–0.80) for the combined model.

Conclusion

A machine learning-based radiomics analysis of routine clinical CT imaging pre-ablation could act as a valuable biomarker model to predict local tumor progression with curative intent for colorectal liver metastases patients.

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Abbreviations

CRC:

Colorectal cancer

CRLM:

Colorectal liver metastases

ML:

Machine learning

CI:

Confidence interval

LTP:

Local tumor progression

RFA:

Radiofrequency ablation

MWA:

Microwave ablation

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Funding

This study was not supported by any funding.

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Authors and Affiliations

  1. Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Marjaneh Taghavi, Femke Staal, Fernando Gomez Munoz, Farshad Imani, David B. Meek, Lisa G. Klompenhouwer, Regina G. H. Beets-Tan & Monique Maas

  2. GROW School of Oncology and Developmental Biology, Maastricht, The Netherlands

    Marjaneh Taghavi, Femke Staal & Regina G. H. Beets-Tan

  3. Department of Radiology, Hospital Clinic of Barcelona, Barcelona, Spain

    Fernando Gomez Munoz

  4. Department of Radiotherapy, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Rita Simões & Uulke A. van der Heide

Authors
  1. Marjaneh Taghavi
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  2. Femke Staal
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  3. Fernando Gomez Munoz
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  4. Farshad Imani
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  7. Lisa G. Klompenhouwer
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Correspondence to Monique Maas.

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For this type of study, formal consent is not required. IRB statement: This application reviewed by the IRB does not meet the WMO criteria and can be considered as a non‐WMO statement.

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Taghavi, M., Staal, F., Gomez Munoz, F. et al. CT-Based Radiomics Analysis Before Thermal Ablation to Predict Local Tumor Progression for Colorectal Liver Metastases. Cardiovasc Intervent Radiol 44, 913–920 (2021). https://doi.org/10.1007/s00270-020-02735-8

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  • DOI: https://doi.org/10.1007/s00270-020-02735-8

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