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CHB-PLATEFORME

Body composition

2021 Prognostic value of low skeletal muscle mass in patient treated by exclusive curative radiochemotherapy for a NSCLC.

In this study, we analyzed the prognostic contribution of two- and three-dimensional body composition determined from PET/CT scans in 93 patients treated with radiochemotherapy for non-small cell lung cancer (NSCLC). Low skeletal muscle mass was found to be a powerful prognostic factor and the automated Anthropometer3D software allows easy identification of at-risk patients who may benefit from tailored therapy.

Mallet R, Decazes P, Modzelewski R, Lequesne J, Vera P, Dubray B, Thureau S. Sci Rep. 2021 May 20;11(1):10628. doi: 10.1038/s41598-021-90187-6. PMID: 34017035

2020 Prognostic value of sarcopenia in patients treated by Radiochemotherapy for locally advanced oesophageal cancer.

In this study, we analyzed the prognostic contribution of two-dimensional body composition determined from PET/CT scan in 97 patients treated with radiochemotherapy for locally advanced esophageal cancer. Sarcopenia was found to be a strong independent prognostic factor associated with increased overall mortality.

Mallet R, Modzelewski R, Lequesne J, Mihailescu S, Decazes P, Auvray H, Benyoucef A, Di Fiore F, Vera P, Dubray B, Thureau S. Radiat Oncol. 2020 May 22;15(1):116. doi: 10.1186/s13014-020-01545-z. PMID: 32443967

2019 Sub-cutaneous Fat Mass measured on multislice computed tomography of pretreatment PET/CT is a prognostic factor of stage IV non-small cell lung cancer treated by nivolumab.

In this study including 55 patients with non-small cell lung cancer (NSCLC) treated with nivolumab (immunotherapy), we analyzed the contribution of body composition determined automatically and three-dimensionally by Anthropometer3D software. We found that body fat, and in particular subcutaneous fat mass, was an independent prognostic factor, more powerful than body mass index (BMI), for these stage IV lung cancers treated with immunotherapy.

Popinat G, Cousse S, Goldfarb L, Becker S, Gardin I, Salaün M, Thureau S, Vera P, Guisier F, Decazes P. Oncoimmunology. 2019 Mar 6;8(5):e1580128. doi: 10.1080/2162402X.2019.1580128. eCollection 2019. PMID: 31069139

2019 Anthropometer3D: Automatic Multi-Slice Segmentation Software for the Measurement of Anthropometric Parameters from CT of PET/CT.

This article describes the development and evaluation of the Anthropometer3D software for automatic three-dimensional measurement of body composition from PET/CT scans. Five parameters are measured: total fat mass, lean body mass, muscle mass, visceral fat mass and subcutaneous fat mass. The results obtained by the Anthropometer3D software are more accurate than those obtained with manual segmentation at the L3 abdominal level.

Decazes P, Tonnelet D, Vera P, Gardin I. J Digit Imaging. 2019 Apr;32(2):241-250. doi: 10.1007/s10278-019-00178-3. PMID: 30756268

2018 Automatic Measurement of the Total Visceral Adipose Tissue From Computed Tomography Images by Using a Multi-Atlas Segmentation Method.

This paper describes the development and evaluation of software for the automatic measurement of visceral fat mass from abdominal-pelvic scans using a multi-atlas segmentation technique.

Decazes P, Rouquette A, Chetrit A, Vera P, Gardin I. J Comput Assist Tomogr. 2018 Jan/Feb;42(1):139-145. Doi: 10.1097/RCT.0000000000000652. PMID: 28708717

2016 A Method to Improve the Semiquantification of 18F-FDG Uptake: Reliability of the Estimated Lean Body Mass Using the Conventional, Low-Dose CT from PET/CT.

This 184-patient study presents the development and evaluation of an algorithm for semi-automated, three-dimensional measurement of lean mass from PET/CT scans. The measurements are more accurate than estimates obtained by predictive equations which may have an impact on the quality of SUL measurement, a quantitative parameter in PET useful for determining therapeutic response.

Decazes P, Métivier D, Rouquette A, Talbot JN, Kerrou K. J Nucl Med. 2016 May;57(5):753-8. doi: 10.2967/jnumed.115.164913. Epub 2015 Dec 30. PMID: 26719376