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

• Published in: European radiology Vol. 28; no. 7; pp. 2801 - 2811
• Main Authors: Hocquelet, Arnaud, Auriac, Thibaut, Perier, Cynthia, Dromain, Clarisse, Meyer, Marie, Pinaquy, Jean-Baptiste, Denys, Alban, Trillaud, Hervé, Denis De Senneville, Baudouin, Vendrely, Véronique
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2018; Springer Nature B.V; Springer Verlag
• Subjects: Aged; Anal cancer; Anus; Anus Neoplasms - mortality; Anus Neoplasms - pathology; Anus Neoplasms - therapy; Biomarkers; Carcinoma, Squamous Cell - mortality; Carcinoma, Squamous Cell - pathology; Carcinoma, Squamous Cell - therapy; Chemoradiotherapy; Chemoradiotherapy - methods; Chemoradiotherapy - mortality; Chemotherapy; Colorectal cancer; Diagnostic Radiology; Disease-Free Survival; Engineering Sciences; Feature maps; Female; Humans; Image processing; Imaging; Internal Medicine; Interventional Radiology; Magnetic Resonance; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical prognosis; Medicine; Medicine & Public Health; Metastases; Middle Aged; Neuroradiology; Progressions; Radiation therapy; Radiology; Regression analysis; Retrospective Studies; Signal and Image processing; Squamous cell carcinoma; Statistical analysis; Survival; Texture; Treatment Outcome; Tumor Burden; Tumors; Ultrasound; Texture analysis; Anal squamous cell carcinoma; Magnetic resonance imaging; Definitive chemoradiotherapy; Imaging biomarkers
• ISSN: 0938-7994; 1432-1084
• DOI: 10.1007/s00330-017-5284-z

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 .