A5016449672- Cancer Immunotherapy and Biomarkers
- Radiomics and Machine Learning in Medical Imaging
- Immunotherapy and Immune Responses
- Cancer Genomics and Diagnostics
- Monoclonal and Polyclonal Antibodies Research
- Hepatocellular Carcinoma Treatment and Prognosis
- Lung Cancer Diagnosis and Treatment
- Lymphoma Diagnosis and Treatment
- AI in cancer detection
- Colorectal Cancer Treatments and Studies
- Lung Cancer Treatments and Mutations
- Lung Cancer Research Studies
- Medical Imaging Techniques and Applications
- Nutrition and Health in Aging
- Colorectal and Anal Carcinomas
- MRI in cancer diagnosis
- Glioma Diagnosis and Treatment
- Medical Imaging and Pathology Studies
- Advanced X-ray and CT Imaging
- Pancreatic and Hepatic Oncology Research
- Cancer Diagnosis and Treatment
- Chemotherapy-induced cardiotoxicity and mitigation
- Artificial Intelligence in Healthcare and Education
- Bladder and Urothelial Cancer Treatments
- Ferroptosis and cancer prognosis
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
2022-2024
CEA Paris-Saclay
2022-2024
Centre National de la Recherche Scientifique
2022-2024
Inserm
2022-2024
Université Paris-Saclay
2022-2024
Institut d'Imagerie Biomédicale
2022-2024
Institut Gustave Roussy
2022-2024
Guerbet (France)
2024
Laboratoire d’Imagerie Biomédicale
2022-2023
Gliomas are among the most common types of central nervous system (CNS) tumors. A prompt diagnosis glioma subtype is crucial to estimate prognosis and personalize treatment strategy. The objective this study was develop a radiomics pipeline based on clinical Magnetic Resonance Imaging (MRI) scans noninvasively predict subtype, as defined tumor grade, isocitrate dehydrogenase (IDH) mutation status, 1p/19q codeletion status. total 212 patients from public retrospective Cancer Genome Atlas Low...
Tumor fraction at liquid biopsy was weakly correlated with the total tumor volume contrast-enhanced CT and did not accurately reflect burden CT.
Background Our aim was to explore the prognostic value of anthropometric parameters in a large population patients treated with immunotherapy. Methods We retrospectively included 623 advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) by an immune-checkpoint-inhibitor having pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort 55 NSCLC used. Anthropometric were measured three-dimensionally (3D) deep learning software (Anthropometer3DNet) allowing...
Background: Body composition could help to better define the prognosis of cancers treated with anti-angiogenics. The aim this study is evaluate prognostic value 3D and 2D anthropometric parameters in patients given anti-angiogenic treatments. Methods: 526 different types were retrospectively included. software Anthropometer3DNet was used measure automatically fat body mass (FBM3D), muscle (MBM3D), visceral (VFM3D) subcutaneous (SFM3D) computed tomography. For comparison, equivalent...
Anti-PD-(L)1 treatment is indicated for patients with mismatch repair-deficient (MMRD) tumors, regardless of tumor origin. However, the response rate highly heterogeneous across MMRD tumors. The objective study to find a score that predicts anti-PD-(L)1 in Sixty-one various origin tumors and treated were retrospectively included this study. An expert radiologist annotated all present at baseline first evaluation CT-scans by circumscribing them on their largest axial axis (single slice),...
Abstract Purpose: The objective of the study is to propose immunotherapy progression decision (iPD) score, a practical tool based on patient features that are available at first evaluation treatment, help oncologists decide whether continue treatment or switch rapidly another therapeutic line when facing progressive disease evaluation. Experimental Design: This retrospective included 107 patients with according RECIST 1.1. Clinical, radiological, and biological data baseline were analyzed....
Antibody drug conjugates (ADCs) have revolutionized the treatment of many solid tumours and hematological diseases. Little is known about influence body composition on efficacy safety ADCs. All patients treated with ADCs in early phase clinical trials between 03/2015 03/2023 at Gustave Roussy were retrospectively included. A deep learning software (Anthropometer3DNet) automatically measured anthropometric parameters 3D pretreatment scans, allowing multi-slice measurements muscle mass (MBM),...
Abstract Background: Antibody drug conjugates (ADCs) have revolutionized the treatment of many solid tumours and hematological diseases. Little is known about influence body composition on efficacy safety ADCs. Methods: All patients treated with ADCs in early phase clinical trials between 03/2015 03/2023 at Drug Development Department Gustave Roussy were retrospectively included analysis. A deep learning software (Anthropometer3DNet) automatically measured anthropometric parameters 3D...
The objective of our study is to propose fast, cost-effective, convenient, and effective biomarkers using the perfusion parameters from dynamic contrast-enhanced ultrasound (DCE-US) for evaluation immune checkpoint inhibitors (ICI) early response. retrospective cohort used in this included 63 patients with metastatic cancer eligible immunotherapy. DCE-US was performed at baseline, day 8 (D8), 21 (D21) after treatment onset. A tumor curve modeled on these three dates, change seven measured...
<div>AbstractPurpose:<p>The objective of the study is to propose immunotherapy progression decision (iPD) score, a practical tool based on patient features that are available at first evaluation treatment, help oncologists decide whether continue treatment or switch rapidly another therapeutic line when facing progressive disease evaluation.</p>Experimental Design:<p>This retrospective included 107 patients with according RECIST 1.1. Clinical, radiological, and...
<p>Distribution of primary cancer types in the development set (n=107).</p>
<p>InterpretML Overall Importance using Explainable Boosting Machines (EBM). The mean absolute score reflects the overall importance assigned by model to predict each patient's category. All features appear important, with number of organs affected metastasis and emergence new lesions as most important ones</p>
<p>Log hazard ratios (HR) computed by cox model. The variables studied were: GRIm, RMH, NLR BL & the iPD score. only significant variable was score (HR = 2, p < 0.005).</p>
<p>Survival of pseudo-PD vs confirmed PD in our cohort.</p>
<p>InterpretML Overall Importance using Explainable Boosting Machines (EBM). The mean absolute score reflects the overall importance assigned by model to predict each patient's category. All features appear important, with number of organs affected metastasis and emergence new lesions as most important ones.</p>
<p>Organ involvement's impact on survival. The organs selected were the ones most affected in our study's patients. tests are for survival of patients whether an organ has a tumor or not. were: A) Liver; B) Lung; C) Subdiaphragm lymph nodes; D) Supra Diaphragm E) Peritoneal Carcinosis; and F) Bone.</p>
<p>Survival of pseudo-PD vs confirmed PD in our cohort.</p>