- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05550090
Dynamic Contrast-enhanced MRI Combined With IVIM-DWI for Early Prediction of Chemosensitivity in Liver MBC (DreaminLMBC)
Clinical Study of Dynamic Contrast-enhanced Magnetic Resonance Imaging Combined With IVIM-DWI for Early Prediction of Chemosensitivity in Liver Metastasis of Breast Cance
The purpose of this study is to further use DCE-MRI and ivim-dwi to predict the chemotherapy sensitivity of liver metastasis of breast cancer at an early stage, and to predict the treatment response of tumor at an early stage by using the changes of their functional parameters, and to compare the efficacy and advantages of IVIM functional parameters and DCE-MRI parameters in predicting the efficacy.To explore the efficacy of "perfusion" and "diffusion" parameters of magnetic resonance imaging as "biomarkers" for early prediction of chemotherapy response and prognosis of breast cancer patients with liver metastasis. And to provide guidance for optimizing the clinical treatment scheme of breast cancer patients with liver metastasis.
At the same time, this study will use the method of artificial intelligence to deeply mine the images, and further find out the indicators for early prediction of the therapeutic effect of liver metastasis of breast cancer.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Study Type
Enrollment (Anticipated)
Contacts and Locations
Study Contact
- Name: Ping Huang
- Phone Number: +8613685766632
- Email: zlyyhp@163.com
Study Contact Backup
- Name: Xiaojia Wang
- Phone Number: +8613906500190
- Email: wxiaojia0803@163.com
Study Locations
-
-
Zhejiang
-
Hangzhou, Zhejiang, China, 310022
- Recruiting
- Zhejiang Cancer Hospital
-
Contact:
- Ping Huang
- Phone Number: +86-13685766632
- Email: zlyyhp@163.com
-
Principal Investigator:
- Ping Huang
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- The primary lesion was pathologically confirmed to be breast cancer, and the patients diagnosed by two imaging methods or pathologically confirmed to be liver metastasis of breast cancer had at least one liver metastasis with the longest diameter ≥ 10mm;
- No second primary malignant tumor;
- ECOG score, 0-2 ;
- The organ function is normal and can tolerate chemotherapy and other anti-tumor treatments;
- The patient plans to receive systemic chemotherapy or systemic anti-tumor treatment, and the whole process of cooperative treatment. The patient has good compliance with the planned treatment and follow-up, can understand the research process of this study and sign a written informed consent;
- Contraception during the study period and within 6 months after treatment, non lactation period.
Exclusion Criteria:
- For patients contraindicated to MR examination, such as built-in metal instruments and allergy to contrast agents;
- The patient had diffuse liver metastasis or the number of liver metastatic tumors was more than 5;
- Patients who cannot complete 2 cycles of chemotherapy or systemic anti-tumor treatment;
- Unable to cooperate with follow-up;
- Patients who are not suitable for the study according to the investigator.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Patients with liver metastasis from breast cancer requiring antitumor therapy
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All patients were given 2 cycles of chemotherapy, including the chemotherapy recommended by the clinical treatment guidelines for advanced metastatic breast cancer, which can be combined with targeted or immune or endocrine therapy.
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Correlation between DCE-MRI parameters combined with IVIM parameters and short-term efficacy of chemotherapy in patients with liver metastasis of breast cancer
Time Frame: September 2025
|
Correlation between DCE-MRI parameters (Ktrans, Ve, Kep) combined with IVIM parameters (D*, D, f) and short-term efficacy of chemotherapy in patients with liver metastasis of breast cancer
|
September 2025
|
|
Correlation between DCE-MRI parameters combined with IVIM parameters and long-term efficacy of chemotherapy in patients with liver metastasis of breast cancer
Time Frame: September 2025
|
Correlation between DCE-MRI parameters (Ktrans, Ve, Kep) combined with IVIM parameters (D*, D, f) and long-term efficacy of chemotherapy in patients with liver metastasis of breast cancer
|
September 2025
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
The consistency of DCE-MRI parameters and IVIM parameters between different observers and the same observer.
Time Frame: September 2025
|
The consistency of DCE-MRI parameters and IVIM parameters between different observers and the same observer.
|
September 2025
|
|
Using artificial intelligence method to deeply mine images, find out new indicators to predict the curative effect of liver metastasis treatment of breast cancer in early stage.
Time Frame: September 2025
|
Using artificial intelligence method to deeply mine images, find out new indicators to predict the curative effect of liver metastasis treatment of breast cancer in early stage.
|
September 2025
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Ping Huang, Zhejiang Cancer Hospital
Publications and helpful links
General Publications
- Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol. 2007 Jun;188(6):1622-35. doi: 10.2214/AJR.06.1403.
- Ruiz A, Sebagh M, Wicherts DA, Castro-Benitez C, van Hillegersberg R, Paule B, Castaing D, Vibert E, Cunha AS, Cherqui D, Morere JF, Adam R. Long-term survival and cure model following liver resection for breast cancer metastases. Breast Cancer Res Treat. 2018 Jul;170(1):89-100. doi: 10.1007/s10549-018-4714-1. Epub 2018 Feb 20.
- Holm J, Li J, Darabi H, Eklund M, Eriksson M, Humphreys K, Hall P, Czene K. Associations of Breast Cancer Risk Prediction Tools With Tumor Characteristics and Metastasis. J Clin Oncol. 2016 Jan 20;34(3):251-8. doi: 10.1200/JCO.2015.63.0624. Epub 2015 Nov 30.
- Kennecke H, Yerushalmi R, Woods R, Cheang MC, Voduc D, Speers CH, Nielsen TO, Gelmon K. Metastatic behavior of breast cancer subtypes. J Clin Oncol. 2010 Jul 10;28(20):3271-7. doi: 10.1200/JCO.2009.25.9820. Epub 2010 May 24.
- Golse N, Adam R. Liver Metastases From Breast Cancer: What Role for Surgery? Indications and Results. Clin Breast Cancer. 2017 Jul;17(4):256-265. doi: 10.1016/j.clbc.2016.12.012. Epub 2017 Jan 9.
- Varoquaux A, Rager O, Lovblad KO, Masterson K, Dulguerov P, Ratib O, Becker CD, Becker M. Functional imaging of head and neck squamous cell carcinoma with diffusion-weighted MRI and FDG PET/CT: quantitative analysis of ADC and SUV. Eur J Nucl Med Mol Imaging. 2013 Jun;40(6):842-52. doi: 10.1007/s00259-013-2351-9. Epub 2013 Feb 22.
- Pieper CC, Willinek WA, Meyer C, Ahmadzadehfar H, Kukuk GM, Sprinkart AM, Block W, Schild HH, Murtz P. Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging for Prediction of Early Arterial Blood Flow Stasis in Radioembolization of Breast Cancer Liver Metastases. J Vasc Interv Radiol. 2016 Sep;27(9):1320-1328. doi: 10.1016/j.jvir.2016.04.018. Epub 2016 Jul 9.
- Mungai F, Pasquinelli F, Mazzoni LN, Virgili G, Ragozzino A, Quaia E, Morana G, Giovagnoni A, Grazioli L, Colagrande S. Diffusion-weighted magnetic resonance imaging in the prediction and assessment of chemotherapy outcome in liver metastases. Radiol Med. 2014 Aug;119(8):625-33. doi: 10.1007/s11547-013-0379-3. Epub 2014 Jan 10.
- Doudou NR, Kampo S, Liu Y, Ahmmed B, Zeng D, Zheng M, Mohamadou A, Wen QP, Wang S. Monitoring the Early Antiproliferative Effect of the Analgesic-Antitumor Peptide, BmK AGAP on Breast Cancer Using Intravoxel Incoherent Motion With a Reduced Distribution of Four b-Values. Front Physiol. 2019 Jun 21;10:708. doi: 10.3389/fphys.2019.00708. eCollection 2019.
- Pieper CC, Meyer C, Sprinkart AM, Block W, Ahmadzadehfar H, Schild HH, Murtz P, Kukuk GM. The value of intravoxel incoherent motion model-based diffusion-weighted imaging for outcome prediction in resin-based radioembolization of breast cancer liver metastases. Onco Targets Ther. 2016 Jul 5;9:4089-98. doi: 10.2147/OTT.S104770. eCollection 2016.
- Bai G, Wang Y, Zhu Y, Guo L. Prediction of Early Response to Chemotherapy in Breast Cancer Liver Metastases by Diffusion-Weighted MR Imaging. Technol Cancer Res Treat. 2019 Jan 1;18:1533033819842944. doi: 10.1177/1533033819842944.
- Cho N, Im SA, Park IA, Lee KH, Li M, Han W, Noh DY, Moon WK. Breast cancer: early prediction of response to neoadjuvant chemotherapy using parametric response maps for MR imaging. Radiology. 2014 Aug;272(2):385-96. doi: 10.1148/radiol.14131332. Epub 2014 Apr 13.
- Jun W, Cong W, Xianxin X, Daqing J. Meta-Analysis of Quantitative Dynamic Contrast-Enhanced MRI for the Assessment of Neoadjuvant Chemotherapy in Breast Cancer. Am Surg. 2019 Jun 1;85(6):645-653.
- Kannan P, Kretzschmar WW, Winter H, Warren D, Bates R, Allen PD, Syed N, Irving B, Papiez BW, Kaeppler J, Markelc B, Kinchesh P, Gilchrist S, Smart S, Schnabel JA, Maughan T, Harris AL, Muschel RJ, Partridge M, Sharma RA, Kersemans V. Functional Parameters Derived from Magnetic Resonance Imaging Reflect Vascular Morphology in Preclinical Tumors and in Human Liver Metastases. Clin Cancer Res. 2018 Oct 1;24(19):4694-4704. doi: 10.1158/1078-0432.CCR-18-0033. Epub 2018 Jun 29.
- De Bruyne S, Van Damme N, Smeets P, Ferdinande L, Ceelen W, Mertens J, Van de Wiele C, Troisi R, Libbrecht L, Laurent S, Geboes K, Peeters M. Value of DCE-MRI and FDG-PET/CT in the prediction of response to preoperative chemotherapy with bevacizumab for colorectal liver metastases. Br J Cancer. 2012 Jun 5;106(12):1926-33. doi: 10.1038/bjc.2012.184. Epub 2012 May 17.
- Yu J, Xu Q, Huang DY, Song JC, Li Y, Xu LL, Shi HB. Prognostic aspects of dynamic contrast-enhanced magnetic resonance imaging in synchronous distant metastatic rectal cancer. Eur Radiol. 2017 May;27(5):1840-1847. doi: 10.1007/s00330-016-4532-y. Epub 2016 Sep 5.
- Allarakha A, Gao Y, Jiang H, Wang GL, Wang PJ. Predictive ability of DWI/ADC and DCE-MRI kinetic parameters in differentiating benign from malignant breast lesions and in building a prediction model. Discov Med. 2019 Mar;27(148):139-152.
- Allarakha A, Gao Y, Jiang H, Wang PJ. Prediction and prognosis of biologically aggressive breast cancers by the combination of DWI/DCE-MRI and immunohistochemical tumor markers. Discov Med. 2019 Jan;27(146):7-15.
Study record dates
Study Major Dates
Study Start (Anticipated)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- ZCHBC022
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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