NCT05550090

Brief Summary

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.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
40

participants targeted

Target at P25-P50 for all trials

Timeline
Completed

Started Sep 2022

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

September 16, 2022

Completed
2 days until next milestone

First Submitted

Initial submission to the registry

September 18, 2022

Completed
4 days until next milestone

First Posted

Study publicly available on registry

September 22, 2022

Completed
3 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 16, 2025

Completed
4 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 30, 2025

Completed
Last Updated

September 27, 2022

Status Verified

September 1, 2022

Enrollment Period

3 years

First QC Date

September 18, 2022

Last Update Submit

September 23, 2022

Conditions

Keywords

Liver metastasisBreast cancerEfficacy prediction

Outcome Measures

Primary Outcomes (2)

  • Correlation between DCE-MRI parameters combined with IVIM parameters and short-term efficacy of chemotherapy in patients with liver metastasis of breast cancer

    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

    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 Outcomes (2)

  • 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.

    September 2025

Study Arms (1)

Patients with liver metastasis from breast cancer requiring antitumor therapy

Patients with liver metastasis from breast cancer requiring antitumor therapy

Drug: Chemotherapy

Interventions

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.

Also known as: Chemotherapy can be combined with targeted or immunotherapy or endocrine therapy.
Patients with liver metastasis from breast cancer requiring antitumor therapy

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Patients with liver metastasis from breast cancer requiring at least 2 cycles of systemic chemotherapy

You may qualify if:

  • 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.

You may not qualify if:

  • 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.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Zhejiang Cancer Hospital

Hangzhou, Zhejiang, 310022, China

RECRUITING

Related Publications (18)

  • 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.

  • 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.

  • 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.

MeSH Terms

Conditions

Breast Neoplasms

Interventions

Drug TherapyImmunotherapy

Condition Hierarchy (Ancestors)

Neoplasms by SiteNeoplasmsBreast DiseasesSkin DiseasesSkin and Connective Tissue Diseases

Intervention Hierarchy (Ancestors)

TherapeuticsImmunomodulationBiological Therapy

Study Officials

  • Ping Huang

    Zhejiang Cancer Hospital

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Clinical Professor

Study Record Dates

First Submitted

September 18, 2022

First Posted

September 22, 2022

Study Start

September 16, 2022

Primary Completion

September 16, 2025

Study Completion

December 30, 2025

Last Updated

September 27, 2022

Record last verified: 2022-09

Locations