Precision Imaging for Early Detection and Targeted Treatment Monitoring in Pancreatic Cancer

NCT06144762 | Recruiting

• 1 other identifier: PROICM 2023-03 PAN
• Study Type: interventional
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

Specifically, in this project, the objective will be developped a model to capture imaging-based tumor heterogeneity with multiscale radiomics approach by obtaining the mirror tumor image at in vivo MRI, ex vivo MRI at histology. This imaging model giving a perfect virtual histology tumor representation will be secondary implemented on routine in vivo clinical MRI for early cancer detection and treatment monitoring. Successful completion of this proposal will lead to a comprehensive non invasive characterisation of pancreatic cancer and will be a game changer in patient management.

Conditions

Pancreas Cancer

Keywords

Radiomics; Ovarian cancer; Genomics; Proteomics; Immune Tumor Microenvironment

Outcome Measures

Primary Outcomes (1)

• the integration of in vivo and ex vivo MRI with histology and molecular caracteristic in order to increase the pancreatic cancer detection and therapeutic response monitoring

  The diagnostic performance of the radiomic and multiomic algorithm in pancreatic cancer detection and therapeutic response monitoring.

  The day of the surgery

Secondary Outcomes (4)

• the imaging phenotype of tumor heterogeneity with a multi-scale radiomic approach by obtaining the image mirror tumor at the in vivo scale

  The day of the surgery

• tumor heterogeneity in artificial intelligence-based imaging reflects and can predict underlying histology (proportion of tumor stroma and density of tumor-infiltrating lymphocytes) (tumor detection and response) and genomics,

  The day of the surgery

• the heterogeneity of tumor biology via non-invasive imaging of different portions of the tumor,

  The day of the surgery

• Correlate MRI results with hematological molecular biology results.

  The day of the surgery

Study Arms (1)

Blood sample and tissue sample

EXPERIMENTAL

Blood sample and tissue sample

Biological: Biological/Vaccine: Blood sample and tissue sample

Interventions

Biological/Vaccine: Blood sample and tissue sample BIOLOGICAL

During the surgery : Tissus sample : primary tumor and metastasis blood sample : 3 EDTA tubes ex vivo MRI data

Blood sample and tissue sample

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patient aged \>18 2.
• Pathologically proven pancreatic cancer which can beneficiate of upfront surgery or delayed surgery followed by neoadjuvant chemotherapy.
• Negative pregnancy test for women of childbearing potential
• Patients affiliated to a social protection system
• Written informed consent signed before project onset.

You may not qualify if:

• presence of metastases,
• Patient who will not have surgery
• Pregnant or breastfeeding women
• Mental or psychological state, physical or legal incapacity preventing participation in the project.

Sponsors & Collaborators

• Institut du Cancer de Montpellier - Val d'Aurelle: lead

Study Sites (1)

NOUGARET Stephanie

Montpellier, 34298, France

RECRUITING

Related Publications (18)

• Nougaret S, Lakhman Y, Gourgou S, Kubik-Huch R, Derchi L, Sala E, Forstner R; European Society of Radiology (ESR) and the European Society of Urogenital Radiology (ESUR). MRI in female pelvis: an ESUR/ESR survey. Insights Imaging. 2022 Mar 28;13(1):60. doi: 10.1186/s13244-021-01152-w.

  PMID: 35347481 BACKGROUND

• Soyer P, Revel MP, Dohan A, Vernhet-Kovacsik H, Nougaret S, Hoeffel C. Gender diversity in authorship in Diagnostic & Interventional Imaging: Where are we now? Diagn Interv Imaging. 2022 May;103(5):237-239. doi: 10.1016/j.diii.2022.02.001. Epub 2022 Feb 17. No abstract available.

  PMID: 35183485 BACKGROUND

• Tardieu M, Lakhman Y, Khellaf L, Cardoso M, Sgarbura O, Colombo PE, Crispin-Ortuzar M, Sala E, Goze-Bac C, Nougaret S. Assessing Histology Structures by Ex Vivo MR Microscopy and Exploring the Link Between MRM-Derived Radiomic Features and Histopathology in Ovarian Cancer. Front Oncol. 2022 Jan 19;11:771848. doi: 10.3389/fonc.2021.771848. eCollection 2021.

  PMID: 35127479 BACKGROUND

• Sadowski EA, Thomassin-Naggara I, Rockall A, Maturen KE, Forstner R, Jha P, Nougaret S, Siegelman ES, Reinhold C. O-RADS MRI Risk Stratification System: Guide for Assessing Adnexal Lesions from the ACR O-RADS Committee. Radiology. 2022 Apr;303(1):35-47. doi: 10.1148/radiol.204371. Epub 2022 Jan 18.

  PMID: 35040672 BACKGROUND

• Shinagare AB, Sadowski EA, Park H, Brook OR, Forstner R, Wallace SK, Horowitz JM, Horowitz N, Javitt M, Jha P, Kido A, Lakhman Y, Lee SI, Manganaro L, Maturen KE, Nougaret S, Poder L, Rauch GM, Reinhold C, Sala E, Thomassin-Naggara I, Vargas HA, Venkatesan A, Nikolic O, Rockall AG. Ovarian cancer reporting lexicon for computed tomography (CT) and magnetic resonance (MR) imaging developed by the SAR Uterine and Ovarian Cancer Disease-Focused Panel and the ESUR Female Pelvic Imaging Working Group. Eur Radiol. 2022 May;32(5):3220-3235. doi: 10.1007/s00330-021-08390-y. Epub 2021 Nov 30.

  PMID: 34846566 BACKGROUND

• Tibermacine H, Rouanet P, Sbarra M, Forghani R, Reinhold C, Nougaret S; GRECCAR Study Group. Radiomics modelling in rectal cancer to predict disease-free survival: evaluation of different approaches. Br J Surg. 2021 Oct 23;108(10):1243-1250. doi: 10.1093/bjs/znab191.

  PMID: 34423347 BACKGROUND

• Nougaret S, Vargas HA, Sala E. BJR female genitourinary oncology special feature: introductory editorial. Br J Radiol. 2021 Sep 1;94(1125):20219003. doi: 10.1259/bjr.20219003. No abstract available.

  PMID: 34415200 BACKGROUND

• Rouanet P, Rullier E, Lelong B, Maingon P, Tuech JJ, Pezet D, Castan F, Nougaret S; GRECCAR Study Group*. Tailored Strategy for Locally Advanced Rectal Carcinoma (GRECCAR 4): Long-term Results From a Multicenter, Randomized, Open-Label, Phase II Trial. Dis Colon Rectum. 2022 Aug 1;65(8):986-995. doi: 10.1097/DCR.0000000000002153. Epub 2022 Jul 5.

  PMID: 34759247 BACKGROUND

• Nougaret S, Tibermacine H, Tardieu M, Sala E. Radiomics: an Introductory Guide to What It May Foretell. Curr Oncol Rep. 2019 Jun 25;21(8):70. doi: 10.1007/s11912-019-0815-1.

  PMID: 31240403 BACKGROUND

• Weigelt B, Vargas HA, Selenica P, Geyer FC, Mazaheri Y, Blecua P, Conlon N, Hoang LN, Jungbluth AA, Snyder A, Ng CKY, Papanastasiou AD, Sosa RE, Soslow RA, Chi DS, Gardner GJ, Shen R, Reis-Filho JS, Sala E. Radiogenomics Analysis of Intratumor Heterogeneity in a Patient With High-Grade Serous Ovarian Cancer. JCO Precis Oncol. 2019 Jun 6;3:PO.18.00410. doi: 10.1200/PO.18.00410. eCollection 2019. No abstract available.

  PMID: 32914032 BACKGROUND

• Dextraze K, Saha A, Kim D, Narang S, Lehrer M, Rao A, Narang S, Rao D, Ahmed S, Madhugiri V, Fuller CD, Kim MM, Krishnan S, Rao G, Rao A. Spatial habitats from multiparametric MR imaging are associated with signaling pathway activities and survival in glioblastoma. Oncotarget. 2017 Dec 5;8(68):112992-113001. doi: 10.18632/oncotarget.22947. eCollection 2017 Dec 22.

  PMID: 29348883 BACKGROUND

• Chu LC, Park S, Kawamoto S, Fouladi DF, Shayesteh S, Zinreich ES, Graves JS, Horton KM, Hruban RH, Yuille AL, Kinzler KW, Vogelstein B, Fishman EK. Utility of CT Radiomics Features in Differentiation of Pancreatic Ductal Adenocarcinoma From Normal Pancreatic Tissue. AJR Am J Roentgenol. 2019 Aug;213(2):349-357. doi: 10.2214/AJR.18.20901. Epub 2019 Apr 23.

  PMID: 31012758 BACKGROUND

• Zhang Z, Li S, Wang Z, Lu Y. A Novel and Efficient Tumor Detection Framework for Pancreatic Cancer via CT Images. Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:1160-1164. doi: 10.1109/EMBC44109.2020.9176172.

  PMID: 33018193 BACKGROUND

• Chu LC, Park S, Kawamoto S, Wang Y, Zhou Y, Shen W, Zhu Z, Xia Y, Xie L, Liu F, Yu Q, Fouladi DF, Shayesteh S, Zinreich E, Graves JS, Horton KM, Yuille AL, Hruban RH, Kinzler KW, Vogelstein B, Fishman EK. Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. J Am Coll Radiol. 2019 Sep;16(9 Pt B):1338-1342. doi: 10.1016/j.jacr.2019.05.034. No abstract available.

  PMID: 31492412 BACKGROUND

• Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016 Feb;278(2):563-77. doi: 10.1148/radiol.2015151169. Epub 2015 Nov 18.

  PMID: 26579733 BACKGROUND

• Himoto Y, Veeraraghavan H, Zheng J, Zamarin D, Snyder A, Capanu M, Nougaret S, Vargas HA, Shitano F, Callahan M, Wang W, Sala E, Lakhman Y. Computed Tomography-Derived Radiomic Metrics Can Identify Responders to Immunotherapy in Ovarian Cancer. JCO Precis Oncol. 2019 Aug 15;3:PO.19.00038. doi: 10.1200/PO.19.00038. eCollection 2019.

  PMID: 32914033 BACKGROUND

• Meier A, Veeraraghavan H, Nougaret S, Lakhman Y, Sosa R, Soslow RA, Sutton EJ, Hricak H, Sala E, Vargas HA. Association between CT-texture-derived tumor heterogeneity, outcomes, and BRCA mutation status in patients with high-grade serous ovarian cancer. Abdom Radiol (NY). 2019 Jun;44(6):2040-2047. doi: 10.1007/s00261-018-1840-5.

  PMID: 30474722 BACKGROUND

• Vargas HA, Veeraraghavan H, Micco M, Nougaret S, Lakhman Y, Meier AA, Sosa R, Soslow RA, Levine DA, Weigelt B, Aghajanian C, Hricak H, Deasy J, Snyder A, Sala E. A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome. Eur Radiol. 2017 Sep;27(9):3991-4001. doi: 10.1007/s00330-017-4779-y. Epub 2017 Mar 13.

  PMID: 28289945 BACKGROUND

MeSH Terms

Conditions

Pancreatic Neoplasms; Ovarian Neoplasms

Interventions

Biological Products; Histocompatibility Testing

Condition Hierarchy (Ancestors)

Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Endocrine Gland Neoplasms; Digestive System Diseases; Pancreatic Diseases; Endocrine System Diseases; Ovarian Diseases; Adnexal Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Neoplasms, Female; Urogenital Neoplasms; Genital Diseases; Gonadal Disorders

Intervention Hierarchy (Ancestors)

Complex Mixtures; Immunologic Tests; Clinical Laboratory Techniques; Diagnostic Techniques and Procedures; Diagnosis; Investigative Techniques; Immunologic Techniques

Study Officials

• NOUGARET Stephanie

  INSTITUT REGIONAL DU CANCER DE MONTPELLIER Cancer de Montpellier

  STUDY DIRECTOR

Central Study Contacts

MOUSSION Aurore

CONTACT

0467613102; aurore.moussion@icm.unicancer.fr

Texier Emmanuelle

CONTACT

0467613102; emmanuelle.texier@icm.unicancer.fr

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 13, 2023
• First Posted: November 22, 2023
• Study Start: December 19, 2023
• Primary Completion (Estimated): October 1, 2029
• Study Completion (Estimated): October 1, 2029
• Last Updated: February 12, 2025

Record last verified: 2025-02

Data Sharing

• IPD Sharing: Will not share

Locations

FR (1)