Rémy Barbé
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Rémy Barbé has a total of 120 co-authors. Here are the top co-authors by number of shared publications:
- Antoine Hollebecque
Gustave Roussy, Villejuif, France
23 shared publications - Cristina Smolenschi
Institut Gustave Roussy, Villejuif, France
22 shared publications - Damien Vasseur
Department of Medical Biology and Pathology, Gustave Roussy, Villejuif, France
22 shared publications - Lambros Tselikas
Département d’Anesthésie, Chirurgie et Interventionnel (DACI), Service de Radiologie Interventionnelle, Gustave Roussy, Villejuif, France
22 shared publications - Antoine Italiano
Medical Oncology Department, Institut Bergonié, Bordeaux, France
21 shared publications - Catline Nobre
Université Paris-Saclay, Gustave Roussy, Inserm U981, Villejuif, France
21 shared publications
Latest Publications
- Open Access
- 16 October 2026
- Published by MDPI AG in Diagnostics
- Vol. 16 (20) , 3372
Optimizing Portal Venous Phase Acquisition Quality of Contrast-Enhanced CT in Oncology
Background: Portal venous phase (PVP) contrast-enhanced CT is a cornerstone for response assessment in early-phase oncology trials, yet contrast-enhancement phase timing remains insufficiently monitored across sites. We assessed PVP timing using a validated artificial intelligence (AI) quality control tool (CECT-QC). Methods: In this retrospective multicenter study, 402 CT examinations from 402 patients enrolled in phase I oncology trials across three European institutions were analyzed using CECT-QC, which quantifies aortic and portal venous enhancement to classify contrast-enhancement phase. The primary analysis included 335 standard CT examinations. Optimal PVP classification was compared (i) across institutions, (ii) before vs. after French regulatory changes impacting contrast delivery, and (iii) across scanner technologies (photon-counting CT [PCCT] vs. standard CT). Results: Among the 335 standard CT examinations included in the primary analysis, 53.1% (178/335) were classified by CECT-QC as optimal PVP. Optimal PVP rates were 39.0% (32/82) at Institution A, 56.9% (87/153) at Institution B, and 59.0% (59/100) at Institution C, with a significant adjusted institutional association (p = 0.039). No significant temporal association was observed before versus after the legislative change (p = 0.716). At Institution A, standard CT was associated with higher odds of optimal PVP classification than PCCT (OR 2.24, 95% CI 1.07–4.68; p = 0.031), while PCCT showed higher aortic and portal venous attenuation (both p < 0.001). Conclusions: Approximately half of standard CT examinations in phase I oncology trials were classified as optimal PVP. Classification varied significantly across institutions and by scanner technology, whereas no significant temporal association was observed before versus after the legislative change. These findings support continued quality-control monitoring, protocol harmonization, and adaptation of classification tools to emerging CT platforms.
- 16 October 2026
- Published by MDPI AG in Diagnostics
- Vol. 16 (20) , 3372
Open AccessOptimizing Portal Venous Phase Acquisition Quality of Contrast-Enhanced CT in Oncology
Background: Portal venous phase (PVP) contrast-enhanced CT is a cornerstone for response assessment in early-phase oncology trials, yet contrast-enhancement phase timing remains insufficiently monitored across sites. We assessed PVP timing using a validated artificial intelligence (AI) quality control tool (CECT-QC). Methods: In this retrospective multicenter study, 402 CT examinations from 402 patients enrolled in phase I oncology trials across three European institutions were analyzed using CECT-QC, which quantifies aortic and portal venous enhancement to classify contrast-enhancement phase. The primary analysis included 335 standard CT examinations. Optimal PVP classification was compared (i) across institutions, (ii) before vs. after French regulatory changes impacting contrast delivery, and (iii) across scanner technologies (photon-counting CT [PCCT] vs. standard CT). Results: Among the 335 standard CT examinations included in the primary analysis, 53.1% (178/335) were classified by CECT-QC as optimal PVP. Optimal PVP rates were 39.0% (32/82) at Institution A, 56.9% (87/153) at Institution B, and 59.0% (59/100) at Institution C, with a significant adjusted institutional association (p = 0.039). No significant temporal association was observed before versus after the legislative change (p = 0.716). At Institution A, standard CT was associated with higher odds of optimal PVP classification than PCCT (OR 2.24, 95% CI 1.07–4.68; p = 0.031), while PCCT showed higher aortic and portal venous attenuation (both p < 0.001). Conclusions: Approximately half of standard CT examinations in phase I oncology trials were classified as optimal PVP. Classification varied significantly across institutions and by scanner technology, whereas no significant temporal association was observed before versus after the legislative change. These findings support continued quality-control monitoring, protocol harmonization, and adaptation of classification tools to emerging CT platforms.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S1 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Hallmarks from gene set enrichment analysis (GSEA) of bulk RNA sequencing from tissue biopsies of FGFR inhibitor-naïve patients.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S1 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Hallmarks from gene set enrichment analysis (GSEA) of bulk RNA sequencing from tissue biopsies of FGFR inhibitor-naïve patients.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Table S3 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular characteristics of FGFR inhibitor-naïve patients experiencing acquired resistance to lirafugratinib with off-target alterations only.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Table S3 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular characteristics of FGFR inhibitor-naïve patients experiencing acquired resistance to lirafugratinib with off-target alterations only.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S3 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular evolution of patient ST2726.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S3 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular evolution of patient ST2726.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S2 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Primary resistance to lirafugratinib in FGFR inhibitor-naïve patients.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S2 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Primary resistance to lirafugratinib in FGFR inhibitor-naïve patients.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S5 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Differential impact on intracellular signaling exerted by lirafugratinib and futibatinib in FGFR2::BICC1 Ba/F3 with a kinase domain with no mutations (wild-type, WT), and with M538I or L618F mutations.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S5 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Differential impact on intracellular signaling exerted by lirafugratinib and futibatinib in FGFR2::BICC1 Ba/F3 with a kinase domain with no mutations (wild-type, WT), and with M538I or L618F mutations.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure 6 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
In vivo evaluation of lirafugratinib and futibatinib in ST4193 PDX.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure 6 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
In vivo evaluation of lirafugratinib and futibatinib in ST4193 PDX.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Table S1 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular evolution of patients pretreated with a FGFR inhibitor before undergoing lirafugratinib.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Table S1 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular evolution of patients pretreated with a FGFR inhibitor before undergoing lirafugratinib.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S4 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular evolution of patient ST3549.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S4 from Recurrent Resistance Mutations to Lirafugratinib Inform Treatment Sequencing in FGFR2-Driven Tumors
Clinical and molecular evolution of patient ST3549.