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Pre-treatment magnetic resonance-based texture features as potential imaging biomarkers for predicting event free survival in anal cancer treated by chemoradiotherapy

  • Magnetic Resonance
  • Published:
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Abstract

Aim

To assess regular MRI findings and tumour texture features on pre-CRT imaging as potential predictive factors of event-free survival (disease progression or death) after chemoradiotherapy (CRT) for anal squamous cell carcinoma (ASCC) without metastasis.

Materials and methods

We retrospectively included 28 patients treated by CRT for pathologically proven ASCC with a pre-CRT MRI. Texture analysis was carried out with axial T2W images by delineating a 3D region of interest around the entire tumour volume. First-order analysis by quantification of the histogram was carried out. Second-order statistical texture features were derived from the calculation of the grey-level co-occurrence matrix using a distance of 1 (d1), 2 (d2) and 5 (d5) pixels. Prognostic factors were assessed by Cox regression and performance of the model by the Harrell C-index.

Results

Eight tumour progressions led to six tumour-specific deaths. After adjusting for age, gender and tumour grade, skewness (HR = 0.131, 95% CI = 0-0.447, p = 0.005) and cluster shade_d1 (HR = 0.601, 95% CI = 0-0.861, p = 0.027) were associated with event occurrence. The corresponding Harrell C-indices were 0.846, 95% CI = 0.697-0.993, and 0.851, 95% CI = 0.708-0.994.

Conclusion

ASCC MR texture analysis provides prognostic factors of event occurrence and requires additional studies to assess its potential in an “individual dose” strategy for ASCC chemoradiation therapy.

Key Points

• MR texture features help to identify tumours with high progression risk.

• Texture feature maps help to identify intra-tumoral heterogeneity.

• Texture features are a better prognostic factor than regular MR findings.

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Abbreviations

ASCC:

Anal squamous s cell cancer

CRT:

Chemoradiotherapy

GLCM:

Grey-level co-occurrence matrix

HR:

Hazard ratio

T2WI:

T2-weighted images

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Acknowledgments

This study was achieved within the context of the Laboratory of Excellence TRAIL ANR-10-LABX-57

Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Department of Radiodiagnostic and Interventional Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland

    Arnaud Hocquelet, Clarisse Dromain & Alban Denys

  2. Department of Diagnostic and Interventional Radiology, Hopital Haut Lévêque, Centre Hospitalier Universitaire de Bordeaux, 33600, Pessac, France

    Arnaud Hocquelet, Thibaut Auriac & Hervé Trillaud

  3. EA IMOTION (Imagerie Moléculaire et Thérapies Innovantes en Oncologie) Université de Bordeaux, 146 rue Leo Saignat, Case 127, 33076, Bordeaux, France

    Arnaud Hocquelet & Hervé Trillaud

  4. Institut de Mathématiques de Bordeaux (IMB), UMR 5251 CNRS/Univ, Bordeaux, 351 cours de la Libération, 33405, Talence, France

    Cynthia Perier & Baudouin Denis De Senneville

  5. Department of Nuclear Medicine, CHU de Bordeaux, 33000, Bordeaux, France

    Marie Meyer & Jean-Baptiste Pinaquy

  6. Departement of Radiotherapy, Hopital Haut Lévêque, CHU de Bordeaux, 33600, Pessac, France

    Véronique Vendrely

Authors
  1. Arnaud Hocquelet
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  2. Thibaut Auriac
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  3. Cynthia Perier
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  4. Clarisse Dromain
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  6. Jean-Baptiste Pinaquy
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  7. Alban Denys
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  9. Baudouin Denis De Senneville
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  10. Véronique Vendrely
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Corresponding author

Correspondence to Arnaud Hocquelet.

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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.

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Hocquelet, A., Auriac, T., Perier, C. et al. Pre-treatment magnetic resonance-based texture features as potential imaging biomarkers for predicting event free survival in anal cancer treated by chemoradiotherapy. Eur Radiol 28, 2801–2811 (2018). https://doi.org/10.1007/s00330-017-5284-z

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