MRI-Based Radiomics Input for Prediction of 2-Year Disease Recurrence in Anal Squamous Cell Carcinoma.

anal cancer machine learning magnetic resonance imaging precision medicine prediction medicine radiomics

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
07 Jan 2021
Historique:
received: 15 11 2020
revised: 20 12 2020
accepted: 01 01 2021
entrez: 12 1 2021
pubmed: 13 1 2021
medline: 13 1 2021
Statut: epublish

Résumé

Chemo-radiotherapy (CRT) is the standard treatment for non-metastatic anal squamous cell carcinomas (ASCC). Despite excellent results for T1-2 stages, relapses still occur in around 35% of locally advanced tumors. Recent strategies focus on treatment intensification, but could benefit from a better patient selection. Our goal was to assess the prognostic value of pre-therapeutic MRI radiomics on 2-year disease control (DC). We retrospectively selected patients with non-metastatic ASCC treated at the CHU Bordeaux and in the French FFCD0904 multicentric trial. Radiomic features were extracted from T2-weighted pre-therapeutic MRI delineated sequences. After random division between training and testing sets on a 2:1 ratio, univariate and multivariate analysis were performed on the training cohort to select optimal features. The correlation with 2-year DC was assessed using logistic regression models, with AUC and accuracy as performance gauges, and the prediction of disease-free survival using Cox regression and Kaplan-Meier analysis. A total of 82 patients were randomized in the training ( A mixed model with two clinical and two radiomic features was predictive of 2-year disease control after CRT and could contribute to identify high risk patients amenable to treatment intensification with view of personalized medicine.

Identifiants

pubmed: 33430396
pii: cancers13020193
doi: 10.3390/cancers13020193
pmc: PMC7827348
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Nicolas Giraud (N)

Radiation Oncology Department, Hôpital Haut-Lévêque, CHU Bordeaux, 33600 Pessac, France.
Modelisation in Oncology (MOnc) Team, INRIA Bordeaux-Sud-Ouest, CNRS UMR 5251 and Université de Bordeaux, 33400 Talence, France.

Olivier Saut (O)

Modelisation in Oncology (MOnc) Team, INRIA Bordeaux-Sud-Ouest, CNRS UMR 5251 and Université de Bordeaux, 33400 Talence, France.

Thomas Aparicio (T)

CHU St Louis, 75010 Paris, France.

Philippe Ronchin (P)

Centre Azuréen de Cancérologie, 06250 Mougins, France.

Louis-Arnaud Bazire (LA)

Institut Curie, 75005 Paris, France.

Emilie Barbier (E)

Fédération Francophone de Cancérologie Digestive, 21000 Dijon, France.

Claire Lemanski (C)

Institut du Cancer de Montpellier, 34090 Montpellier, France.

Xavier Mirabel (X)

Centre Oscar Lambret, 59000 Lille, France.

Pierre-Luc Etienne (PL)

Centre Armoricain de Radiothérapie, 22190 Plérin, France.

Astrid Lièvre (A)

CHU Rennes, 35000 Rennes, France.

Wulfran Cacheux (W)

Hôpital Privé Pays de Savoie, 74100 Annemasse, France.

Ariane Darut-Jouve (A)

Institut de Cancérologie de Bourgogne, 21000 Dijon, France.

Christelle De la Fouchardière (C)

Centre Léon Bérard, 69008 Lyon, France.

Arnaud Hocquelet (A)

Radiology Department, CHU Bordeaux, 33000 Bordeaux, France.

Hervé Trillaud (H)

Radiology Department, CHU Bordeaux, 33000 Bordeaux, France.

Thomas Charleux (T)

Radiation Oncology Department, Hôpital Haut-Lévêque, CHU Bordeaux, 33600 Pessac, France.

Gilles Breysacher (G)

Hôpitaux Civils de Colmar, 68000 Colmar, France.

Delphine Argo-Leignel (D)

GH Bretagne Sud, 56100 Lorient, France.

Alexandre Tessier (A)

CH Annecy, 74370 Annecy, France.

Nicolas Magné (N)

Institut de Cancérologie Lucien Neuwirth, 42270 St-Priest-en-Jarez, France.

Meher Ben Abdelghani (M)

Institut de Cancérologie Strasbourg Europe, 67200 Strasbourg, France.

Côme Lepage (C)

CHU Dijon, 21000 Dijon, France.

Véronique Vendrely (V)

Radiation Oncology Department, Hôpital Haut-Lévêque, CHU Bordeaux, 33600 Pessac, France.

Classifications MeSH