Arnaud Hocquelet1,2,3, Thibaut Auriac4, Cynthia Perier5, Clarisse Dromain6, Marie Meyer7, Jean-Baptiste Pinaquy7, Alban Denys6, Hervé Trillaud4,8, Baudouin Denis De Senneville5, Véronique Vendrely9. 1. Department of Radiodiagnostic and Interventional Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland. arnaud.hocquelet@gmail.com. 2. Department of Diagnostic and Interventional Radiology, Hopital Haut Lévêque, Centre Hospitalier Universitaire de Bordeaux, 33600, Pessac, France. arnaud.hocquelet@gmail.com. 3. EA IMOTION (Imagerie Moléculaire et Thérapies Innovantes en Oncologie) Université de Bordeaux, 146 rue Leo Saignat, Case 127, 33076, Bordeaux, France. arnaud.hocquelet@gmail.com. 4. Department of Diagnostic and Interventional Radiology, Hopital Haut Lévêque, Centre Hospitalier Universitaire de Bordeaux, 33600, Pessac, France. 5. Institut de Mathématiques de Bordeaux (IMB), UMR 5251 CNRS/Univ, Bordeaux, 351 cours de la Libération, 33405, Talence, France. 6. Department of Radiodiagnostic and Interventional Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland. 7. Department of Nuclear Medicine, CHU de Bordeaux, 33000, Bordeaux, France. 8. EA IMOTION (Imagerie Moléculaire et Thérapies Innovantes en Oncologie) Université de Bordeaux, 146 rue Leo Saignat, Case 127, 33076, Bordeaux, France. 9. Departement of Radiotherapy, Hopital Haut Lévêque, CHU de Bordeaux, 33600, Pessac, France.
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.
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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