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European Radiology

, Volume 28, Issue 7, pp 2801–2811 | Cite as

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

  • Arnaud HocqueletEmail author
  • Thibaut Auriac
  • Cynthia Perier
  • Clarisse Dromain
  • Marie Meyer
  • Jean-Baptiste Pinaquy
  • Alban Denys
  • Hervé Trillaud
  • Baudouin Denis De Senneville
  • Véronique Vendrely
Magnetic Resonance

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.

Keywords

Anal squamous cell carcinoma Magnetic resonance imaging Texture analysis Definitive chemoradiotherapy Imaging biomarkers 

Abbreviations and acronyms

ASCC

Anal squamous s cell cancer

CRT

Chemoradiotherapy

GLCM

Grey-level co-occurrence matrix

HR

Hazard ratio

T2WI

T2-weighted images

Notes

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.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Arnaud Hocquelet.

Conflict of interest

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.

Statistics and biometry

One of the authors has significant statistical expertise.

Ethical approval

Institutional Review Board approval was obtained.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

Supplementary material

330_2017_5284_MOESM1_ESM.xlsx (32 kb)
ESM 1 (XLSX 31 kb)

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Arnaud Hocquelet
    • 1
    • 2
    • 3
    Email author
  • Thibaut Auriac
    • 2
  • Cynthia Perier
    • 4
  • Clarisse Dromain
    • 1
  • Marie Meyer
    • 5
  • Jean-Baptiste Pinaquy
    • 5
  • Alban Denys
    • 1
  • Hervé Trillaud
    • 2
    • 3
  • Baudouin Denis De Senneville
    • 4
  • Véronique Vendrely
    • 6
  1. 1.Department of Radiodiagnostic and Interventional RadiologyCentre Hospitalier Universitaire Vaudois (CHUV) and University of LausanneLausanneSwitzerland
  2. 2.Department of Diagnostic and Interventional Radiology, Hopital Haut LévêqueCentre Hospitalier Universitaire de BordeauxPessacFrance
  3. 3.EA IMOTION (Imagerie Moléculaire et Thérapies Innovantes en Oncologie) Université de BordeauxBordeauxFrance
  4. 4.Institut de Mathématiques de Bordeaux (IMB), UMR 5251 CNRS/UnivTalenceFrance
  5. 5.Department of Nuclear MedicineCHU de BordeauxBordeauxFrance
  6. 6.Departement of Radiotherapy, Hopital Haut LévêqueCHU de BordeauxPessacFrance

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