Las frágiles y peligrosas medusas

International audienceIntroduction: Our aim was to explore the prognostic value of anthropometric parameters in patients treated with nivolumab for stage IV non-small cell lung cancer (NSCLC). Methods: We retrospectively included 55 patients with NSCLC treated by nivolumab with a pretreatment 18FDG positron emission tomography coupled with computed tomography (PET/CT). Anthropometric parameters were measured on the CT of PET/CT by in-house software (Anthropometer3D) allowing an automatic multi-slice measurement of Lean Body Mass (LBM), Fat Body Mass (FBM), Muscle Body Mass (MBM), Visceral Fat Mass (VFM) and Sub-cutaneous Fat Mass (SCFM). Clinical and tumor parameters were also retrieved. Receiver operator characteristics (ROC) analysis was performed and overall survival at 1 year was studied using Kaplan-Meier and Cox analysis. Results: FBM and SCFM were highly correlated (ρ = 0.99). In ROC analysis, only FBM, SCFM, VFM, body mass index (BMI) and metabolic tumor volume (MTV) had an area under the curve (AUC) significantly higher than 0.5. In Kaplan-Meier analysis using medians as cut-offs, prognosis was worse for patients with low SCFM (<5.69 kg/m2; p = 0.04, survivors 41% vs 75%). In Cox univariate analysis using continuous values, BMI (HR = 0.84, p= 0.007), SCFM (HR = 0.75, p = 0.003) and FBM (HR = 0.80, p= 0.004) were significant prognostic factors. In multivariate analysis using clinical parameters (age, gender, WHO performance status, number prior regimens) and SCFM, only SCFM was significantly associated with poor survival (HR = 0.75, p = 0.006). Conclusions: SCFM is a significant prognosis factor of stage IV NSCLC treated by nivolumab

40. 3 juin 1819. Circulaire sur les brevets de capacité et les diplômes de l'enseignement primaire féminin

Decazes Élie. 40. 3 juin 1819. Circulaire sur les brevets de capacité et les diplômes de l'enseignement primaire féminin. In: L'enseignement du Français à l'école primaire – Textes officiels. Tome 1 : 1791-1879. Paris : Institut national de recherche pédagogique, 1992. pp. 77-78. (Bibliothèque de l'Histoire de l'Education, 5

Radiomic and anthropometric analyses in multimodal imaging for exploring predictive and prognostic factors in oncology

Personalized medicine refers to the adaptation of medical treatment to the individual characteristics of each diseaseand each patient. In oncology, this adaptation depends in particular on the prognosis of the disease in order to adapt a treatmentto the severity of the cancer. Medical imaging, represented in particular by the CT scan and the PET scan, allows the extraction andanalysis of morphological and functional characteristics of the cancer, called "radiomics", but also of the patient's characteristics,called "anthropometrics". The objective of this work was to explore the use of radiomic and anthropometric parameters inmultimodal imaging for the exploration of prognostic factors in oncology.For the anthropometric side, we developed and evaluated a software, named "Anthropometer3D", allowing themeasurement of muscle, lean, fat, visceral adipose tissue and subcutaneous adipose tissue masses in a multi-slice and automaticway from PET/CT scans and showed the prognostic value of subcutaneous adipose tissue for stage IV lung cancers treated withimmunotherapy and of muscle mass for lung cancers treated with radio-chemotherapyFor the radiomic side, we have developed and evaluated algorithms for the automatic segmentation and classification ofoncological PET/CT scans and developed a software, named "Oncometer3D", for the extraction of tumor activity, fragmentation,dispersion and massiveness characteristics from PET scans. We showed that one fragmentation parameter, the volume to totaltumor area ratio, was an independent prognostic factor in diffuse large-cell B-cell lymphoma and that several morphological tumorparameters correlated with circulating tumor DNA in B-cell hemopathies.In conclusion, medical imaging participates in the global evaluation of cancer from a macroscopic point of view byallowing a radiomic analysis centered on the tumor but also anthropometrically centered on the patient. Improved prognosticationusing these two approaches could lead to better therapeutic management of patients.Personalized medicine refers to the adaptation of medical treatment to the individual characteristics of each diseaseand each patient. In oncology, this adaptation depends in particular on the prognosis of the disease in order to adapt a treatmentto the severity of the cancer. Medical imaging, represented in particular by the CT scan and the PET scan, allows the extraction andanalysis of morphological and functional characteristics of the cancer, called "radiomics", but also of the patient's characteristics,called "anthropometrics". The objective of this work was to explore the use of radiomic and anthropometric parameters inmultimodal imaging for the exploration of prognostic factors in oncology.For the anthropometric side, we developed and evaluated a software, named "Anthropometer3D", allowing themeasurement of muscle, lean, fat, visceral adipose tissue and subcutaneous adipose tissue masses in a multi-slice and automaticway from PET/CT scans and showed the prognostic value of subcutaneous adipose tissue for stage IV lung cancers treated withimmunotherapy and of muscle mass for lung cancers treated with radio-chemotherapyFor the radiomic side, we have developed and evaluated algorithms for the automatic segmentation and classification ofoncological PET/CT scans and developed a software, named "Oncometer3D", for the extraction of tumor activity, fragmentation,dispersion and massiveness characteristics from PET scans. We showed that one fragmentation parameter, the volume to totaltumor area ratio, was an independent prognostic factor in diffuse large-cell B-cell lymphoma and that several morphological tumorparameters correlated with circulating tumor DNA in B-cell hemopathies.In conclusion, medical imaging participates in the global evaluation of cancer from a macroscopic point of view byallowing a radiomic analysis centered on the tumor but also anthropometrically centered on the patient. Improved prognosticationusing these two approaches could lead to better therapeutic management of patients

Le corps dans l’accompagnement. Du soin médical à la métaphysique : réflexions autour de la téléconsultation en soins palliatifs

Comment une institution peut-elle faire ses premiers pas en téléconsultation ? Certaines consultations de soins palliatifs, dites d’accompagnement, où le médecin n’examine pas le patient, ne pourraient-elles pas être de bonnes candidates pour expérimenter ce nouvel outil ? Cette posture s’entend uniquement si l’accompagnement est une relation désincarnée. Est-ce le cas ? Ou au contraire celui-ci est-il profondément ancré dans le corps ? L’accompagnement en soins palliatifs, se développe en deux strates. La première se situe dans la relation de soin elle-même, une relation de soin qui s’applique à porter attention aux besoins réels et profonds du malade. Or le corps, le corps souffrant porte ces besoins dans la relation entre le médecin de soins palliatifs et son patient. Le corps, les corps, le corps à corps sont sollicités dans ces soins médicaux. Au cours de la seconde strate de l’accompagnement, le soignant se voit entrer avec le patient, dans une expérience d’ordre métaphysique. Cette expérience, dite ici « l’Essentiel », ne se communique pas avec le langage, mais primitivement à lui, elle se partage par le corps. Le corps et ses indices expressifs qui nous font comprendre l’autre ; son propre corps dont les états nous guident dans nos réactions. Alors si l’accompagnement est incarné, celui-ci est-il possible à l’aide de cet outil qu’est la téléconsultation ? Qu’est-il raisonnable ou dangereux de lui demander

Analyses radiomique et anthropométrique en imagerie multimodale pour l'exploration de facteurs prédictifs et pronostiques en oncologie.

Personalized medicine refers to the adaptation of medical treatment to the individual characteristics of each diseaseand each patient. In oncology, this adaptation depends in particular on the prognosis of the disease in order to adapt a treatmentto the severity of the cancer. Medical imaging, represented in particular by the CT scan and the PET scan, allows the extraction andanalysis of morphological and functional characteristics of the cancer, called "radiomics", but also of the patient's characteristics,called "anthropometrics". The objective of this work was to explore the use of radiomic and anthropometric parameters inmultimodal imaging for the exploration of prognostic factors in oncology.For the anthropometric side, we developed and evaluated a software, named "Anthropometer3D", allowing themeasurement of muscle, lean, fat, visceral adipose tissue and subcutaneous adipose tissue masses in a multi-slice and automaticway from PET/CT scans and showed the prognostic value of subcutaneous adipose tissue for stage IV lung cancers treated withimmunotherapy and of muscle mass for lung cancers treated with radio-chemotherapyFor the radiomic side, we have developed and evaluated algorithms for the automatic segmentation and classification ofoncological PET/CT scans and developed a software, named "Oncometer3D", for the extraction of tumor activity, fragmentation,dispersion and massiveness characteristics from PET scans. We showed that one fragmentation parameter, the volume to totaltumor area ratio, was an independent prognostic factor in diffuse large-cell B-cell lymphoma and that several morphological tumorparameters correlated with circulating tumor DNA in B-cell hemopathies.In conclusion, medical imaging participates in the global evaluation of cancer from a macroscopic point of view byallowing a radiomic analysis centered on the tumor but also anthropometrically centered on the patient. Improved prognosticationusing these two approaches could lead to better therapeutic management of patients.Personalized medicine refers to the adaptation of medical treatment to the individual characteristics of each diseaseand each patient. In oncology, this adaptation depends in particular on the prognosis of the disease in order to adapt a treatmentto the severity of the cancer. Medical imaging, represented in particular by the CT scan and the PET scan, allows the extraction andanalysis of morphological and functional characteristics of the cancer, called "radiomics", but also of the patient's characteristics,called "anthropometrics". The objective of this work was to explore the use of radiomic and anthropometric parameters inmultimodal imaging for the exploration of prognostic factors in oncology.For the anthropometric side, we developed and evaluated a software, named "Anthropometer3D", allowing themeasurement of muscle, lean, fat, visceral adipose tissue and subcutaneous adipose tissue masses in a multi-slice and automaticway from PET/CT scans and showed the prognostic value of subcutaneous adipose tissue for stage IV lung cancers treated withimmunotherapy and of muscle mass for lung cancers treated with radio-chemotherapyFor the radiomic side, we have developed and evaluated algorithms for the automatic segmentation and classification ofoncological PET/CT scans and developed a software, named "Oncometer3D", for the extraction of tumor activity, fragmentation,dispersion and massiveness characteristics from PET scans. We showed that one fragmentation parameter, the volume to totaltumor area ratio, was an independent prognostic factor in diffuse large-cell B-cell lymphoma and that several morphological tumorparameters correlated with circulating tumor DNA in B-cell hemopathies.In conclusion, medical imaging participates in the global evaluation of cancer from a macroscopic point of view byallowing a radiomic analysis centered on the tumor but also anthropometrically centered on the patient. Improved prognosticationusing these two approaches could lead to better therapeutic management of patients

Analyses radiomique et anthropométrique en imagerie multimodale pour l'exploration de facteurs prédictifs et pronostiques en oncologie.

Personalized medicine refers to the adaptation of medical treatment to the individual characteristics of each diseaseand each patient. In oncology, this adaptation depends in particular on the prognosis of the disease in order to adapt a treatmentto the severity of the cancer. Medical imaging, represented in particular by the CT scan and the PET scan, allows the extraction andanalysis of morphological and functional characteristics of the cancer, called "radiomics", but also of the patient's characteristics,called "anthropometrics". The objective of this work was to explore the use of radiomic and anthropometric parameters inmultimodal imaging for the exploration of prognostic factors in oncology.For the anthropometric side, we developed and evaluated a software, named "Anthropometer3D", allowing themeasurement of muscle, lean, fat, visceral adipose tissue and subcutaneous adipose tissue masses in a multi-slice and automaticway from PET/CT scans and showed the prognostic value of subcutaneous adipose tissue for stage IV lung cancers treated withimmunotherapy and of muscle mass for lung cancers treated with radio-chemotherapyFor the radiomic side, we have developed and evaluated algorithms for the automatic segmentation and classification ofoncological PET/CT scans and developed a software, named "Oncometer3D", for the extraction of tumor activity, fragmentation,dispersion and massiveness characteristics from PET scans. We showed that one fragmentation parameter, the volume to totaltumor area ratio, was an independent prognostic factor in diffuse large-cell B-cell lymphoma and that several morphological tumorparameters correlated with circulating tumor DNA in B-cell hemopathies.In conclusion, medical imaging participates in the global evaluation of cancer from a macroscopic point of view byallowing a radiomic analysis centered on the tumor but also anthropometrically centered on the patient. Improved prognosticationusing these two approaches could lead to better therapeutic management of patients.Personalized medicine refers to the adaptation of medical treatment to the individual characteristics of each diseaseand each patient. In oncology, this adaptation depends in particular on the prognosis of the disease in order to adapt a treatmentto the severity of the cancer. Medical imaging, represented in particular by the CT scan and the PET scan, allows the extraction andanalysis of morphological and functional characteristics of the cancer, called "radiomics", but also of the patient's characteristics,called "anthropometrics". The objective of this work was to explore the use of radiomic and anthropometric parameters inmultimodal imaging for the exploration of prognostic factors in oncology.For the anthropometric side, we developed and evaluated a software, named "Anthropometer3D", allowing themeasurement of muscle, lean, fat, visceral adipose tissue and subcutaneous adipose tissue masses in a multi-slice and automaticway from PET/CT scans and showed the prognostic value of subcutaneous adipose tissue for stage IV lung cancers treated withimmunotherapy and of muscle mass for lung cancers treated with radio-chemotherapyFor the radiomic side, we have developed and evaluated algorithms for the automatic segmentation and classification ofoncological PET/CT scans and developed a software, named "Oncometer3D", for the extraction of tumor activity, fragmentation,dispersion and massiveness characteristics from PET scans. We showed that one fragmentation parameter, the volume to totaltumor area ratio, was an independent prognostic factor in diffuse large-cell B-cell lymphoma and that several morphological tumorparameters correlated with circulating tumor DNA in B-cell hemopathies.In conclusion, medical imaging participates in the global evaluation of cancer from a macroscopic point of view byallowing a radiomic analysis centered on the tumor but also anthropometrically centered on the patient. Improved prognosticationusing these two approaches could lead to better therapeutic management of patients