Pancreas CancerPANC-O-MICSNCT06144762
Precision Imaging for Early Detection and Targeted Treatment Monitoring in Pancreatic Cancer
A study testing Biological/Vaccine: Blood sample and tissue sample in people with Pancreas Cancer, run by Institut du Cancer de Montpellier - Val d'Aurelle at 1 site in France.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pancreas Cancer
- What is being tested?
- Biological/Vaccine: Blood sample and tissue sample
- Type of treatment
- Vaccines
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 150 participants
- Where
- 1 siteFrance
- Study dates
- 19 Dec 2023to Oct 2029
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site, 1 recruiting
- Recruiting
NOUGARET Stephanie
Montpellier, 34298
NOUGARET Stephanie, MD, stephanie.nougaret@icm.unicancer.fr
About this study
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.
Read the detailed description
With a five-year survival rate of only 3% for the majority of patients, pancreatic cancer is a global healthcare challenge. By the time of diagnosis over half of pancreatic cancers are metastasized. The dire disease situation reflects our inability to diagnose pancreatic cancer early and to effectively treat it. Our failure to diagnose the disease early results in part from the inaccessibility of the organ, difficulties in detecting small pancreatic lesions by conventional imaging approaches, and a poor understanding of the spectrum of heterogeneity in pancreatic cancer. Single time point, single site biopsies cannot assess entire tumor while multiple biopsies at several time points are not feasible in clinical routine. Limitations of invasive sampling may be addressed with non-invasive imaging that captures morphologic and functional information about the entire tumor in space and, if repeated, in time. Radiomics has the potential for "whole tumour virtual sampling" using a single or serial non-invasive examinations in place of biopsies. By approaching images as data able to be mined, instead of merely pictures in conventional radiology, quantitative imaging allows for further information to be extracted from medical images as well as for global assessments across large patient populations. Therefore, these new quantitative approaches hold the promise of detecting pancreatic cancer characteristics that the naked eye alone cannot perceive from conventional medical imaging, opening new doors for personalized medicine in pancreatic cancer. To date, no study has evaluated the value of radiomics at macroscopic (in vivo 1.5T/3TMRI) and microscopic (ex vivo 9.4TMRI) scale for early cancer detection and targeted treatment monitoring. Specifically, in this project, the objective will be developpe 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
- Being tested
- Biological/Vaccine: Blood sample and tissue sample
- Keywords
- Radiomics, Ovarian cancer, Genomics, Proteomics, Immune Tumor Microenvironment
- Medical subject headings
- Pancreatic Neoplasms, Ovarian Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Biological/Vaccine: Blood sample and tissue sampleBiological
During the surgery :
Tissus sample : primary tumor and metastasis blood sample : 3 EDTA tubes ex vivo MRI data
| Study group | Role | What they receive |
|---|---|---|
| Blood sample and tissue sample | Experimental | Blood sample and tissue sample Receives: Biological: Biological/Vaccine: Blood sample and tissue sample |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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
Correlation between radiomic maps and pathogenic maps of heterogeneity,
Measured: 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,
Correlation between radiomic algorithms and i/underlying histology (proportion of tumor stroma and density of tumor-infiltrating lymphocytes) (tumor detection and response) ii/ genomics
Measured: The day of the surgery
the heterogeneity of tumor biology via non-invasive imaging of different portions of the tumor,
Correlation between radiomic maps and tumour biology (CYTOF, proteomics and transcriptomics),
Measured: The day of the surgery
Correlate MRI results with hematological molecular biology results.
Correlation between radiomic algorithms for tumor detection and cDNA assay
Measured: The day of the surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Nov 2023
- Study start19 Dec 2023
- Primary completionOct 2029 (estimated)
- Study completionOct 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (18)Papers the sponsor has linked to this study.
- Other trials for Pancreas CancerStudies of the same condition, open and under way.
- More trials run by Institut du Cancer de Montpellier - Val d'AurelleThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- NOUGARET Stephanie, Study director, INSTITUT REGIONAL DU CANCER DE MONTPELLIER Cancer de Montpellier
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06144762
- Sponsor's protocol ID
- PROICM 2023-03 PAN
- Acronym
- PANC-O-MICS
- Status last verified
- Feb 2025
- First submitted
- 13 Nov 2023
- Last updated
- 12 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 35347481Soyer 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.
PubMed 35183485Tardieu 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.
PubMed 35127479Sadowski 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.
PubMed 35040672Shinagare 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.
PubMed 34846566Tibermacine 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.
PubMed 34423347Nougaret 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.
PubMed 34415200Rouanet 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.
PubMed 34759247Nougaret 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.
PubMed 31240403Weigelt 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.
PubMed 32914032Dextraze 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.
PubMed 29348883Chu 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.
PubMed 31012758Zhang 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.
PubMed 33018193Chu 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.
PubMed 31492412Gillies 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.
PubMed 26579733
Study at a glance
From the registry record, last updated by the sponsor on 12 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Precision Imaging for Early Detection and Targeted Treatment Monitoring in Pancreatic Cancer
- ClinicalTrials.gov ID
- NCT06144762
- Acronym / sponsor ID
- PANC-O-MICS / PROICM 2023-03 PAN
- Conditions
- Pancreas Cancer
- Keywords
- Radiomics, Ovarian cancer, Genomics, Proteomics, Immune Tumor Microenvironment
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Institut du Cancer de Montpellier - Val d'AurelleUniversity, hospital or other
- Study start
- 19 Dec 2023 (actual)
- Primary completion
- Oct 2029 (estimated)
- Study completion
- Oct 2029 (estimated)
- First posted
- 22 Nov 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
With a five-year survival rate of only 3% for the majority of patients, pancreatic cancer is a global healthcare challenge. By the time of diagnosis over half of pancreatic cancers are metastasized. The dire disease situation reflects our inability to diagnose pancreatic cancer early and to effectively treat it. Our failure to diagnose the disease early results in part from the inaccessibility of the organ, difficulties in detecting small pancreatic lesions by conventional imaging approaches, and a poor understanding of the spectrum of heterogeneity in pancreatic cancer. Single time point, single site biopsies cannot assess entire tumor while multiple biopsies at several time points are not feasible in clinical routine. Limitations of invasive sampling may be addressed with non-invasive imaging that captures morphologic and functional information about the entire tumor in space and, if repeated, in time. Radiomics has the potential for "whole tumour virtual sampling" using a single or serial non-invasive examinations in place of biopsies. By approaching images as data able to be mined, instead of merely pictures in conventional radiology, quantitative imaging allows for further information to be extracted from medical images as well as for global assessments across large patient populations. Therefore, these new quantitative approaches hold the promise of detecting pancreatic cancer characteristics that the naked eye alone cannot perceive from conventional medical imaging, opening new doors for personalized medicine in pancreatic cancer. To date, no study has evaluated the value of radiomics at macroscopic (in vivo 1.5T/3TMRI) and microscopic (ex vivo 9.4TMRI) scale for early cancer detection and targeted treatment monitoring. Specifically, in this project, the objective will be developpe 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.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Blood sample and tissue sample | Experimental | Biological: Biological/Vaccine: Blood sample and tissue sampleBlood sample and tissue sample |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- 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.
Key exclusion criteria (4 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Biological/Vaccine: Blood sample and tissue sampleDuring the surgery : Tissus sample : primary tumor and metastasis blood sample : 3 EDTA tubes ex vivo MRI data | Biological | Blood sample and tissue sample |
Primary outcome
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
Time frame: The day of the surgery
The diagnostic performance of the radiomic and multiomic algorithm in pancreatic cancer detection and therapeutic response monitoring.
4 secondary outcomes
the imaging phenotype of tumor heterogeneity with a multi-scale radiomic approach by obtaining the image mirror tumor at the in vivo scale
Time frame: 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,
Time frame: The day of the surgery
the heterogeneity of tumor biology via non-invasive imaging of different portions of the tumor,
Time frame: The day of the surgery
Correlate MRI results with hematological molecular biology results.
Time frame: The day of the surgery
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Feb 2025.
- Background: PubMed 35347481Nougaret 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.
- Background: PubMed 35183485Soyer 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.
- Background: PubMed 35127479Tardieu 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.
- Background: PubMed 35040672Sadowski 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.
- Background: PubMed 34846566Shinagare 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.
- Background: PubMed 34423347Tibermacine 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.
- Background: PubMed 34415200Nougaret 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.
- Background: PubMed 34759247Rouanet 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.
- Background: PubMed 31240403Nougaret 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.
- Background: PubMed 32914032Weigelt 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.
- Background: PubMed 29348883Dextraze 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.
- Background: PubMed 31012758Chu 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
NOUGARET Stephanie study director
INSTITUT REGIONAL DU CANCER DE MONTPELLIER Cancer de Montpellier
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Biological/Vaccine: Blood sample and tissue sample in people with Pancreas Cancer, run by Institut du Cancer de Montpellier - Val d'Aurelle at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Feb 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact MOUSSION Aurore (0467613102 ext. +33, aurore.moussion@icm.unicancer.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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 (time frame: The day of the surgery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06144762, which also lists 18 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Feb 2025.