MRI-based Approaches for Multi-parametric Model to Early Predict Pathological Complete Response to Neoadjuvant Therapy in Breast Cancer

Conditions

Breast Cancer

Keywords

Magnetic resonance imaging (MRI), Neoadjuvant therapy (NAT), therapeutic response, breast cancer, early prediction

Brief summary

The purpose of this clinical research is to evaluate the accuracy of a multi-parametric model based on magnetic resonance imaging (MRI) in predicting pathological complete response (pCR) after the first cycle of neoadjuvant therapy (NAT) given to patients with locally advanced breast cancer, thus allowing early chemotherapy regimen modification to increase number of patients achieving pCR or save patients from toxic effects of ineffective chemotherapy.

Detailed description

Breast cancer is the most prevalent cancer among women worldwide. NAT has been well established in managing breast cancer for patients with locally advanced cancer and early-stage operable breast cancers of specific molecular subtypes. Though pCR has been demonstrated to be associated with better survival, it can only be judged by pathological testing of surgically resected specimens. Thus, predicting pCR earlier during NAT is imperative and can timely switch to a new personalized treatment strategy and exempt from unnecessary chemotherapy toxicity for patients. This is a multicenter, prospective cohort study of 301 patients undergoing MRI after the first cycle of neoadjuvant chemotherapy. This project plans to establish and validate a model for determining pCR during NAT in breast cancer based on clinical information, imaging and pathological information of patients in multiple centers, in order to provide important references for further early diagnosis and personalized treatment. 1. Collecting MRI images data, clinical and pathological information, treatment regimens, and curative effect information to build an MRI-based, multi-parametric model. 2. Evaluating the performance of model through internal and external validation cohort by using the receiver operating characteristic (ROC) curve, the area under the curve (AUC), discrimination and calibration measures.

Liulu Zhang, Zhaowen Zhu, Yuanqi Chen, Yidan Wu, Yongcheng Zhang et al. (8 authors)

Journal of Clinical Oncology2024-05-29

10.1200/jco.2024.42.16_suppl.592

Neoadjuvant Chemotherapy and Neoadjuvant Chemotherapy With Immunotherapy Result in Different Tumor Shrinkage Patterns in Triple-Negative Breast Cancer.

Zou J, Zhang L, Chen Y, Lin Y, Cheng M, Zheng X, Zhuang X, Wang K.

2023-11-177 citations

10.4048/jbc.2023.0136

Neoadjuvant Chemotherapy and Neoadjuvant Chemotherapy With Immunotherapy Result in Different Tumor Shrinkage Patterns in Triple-Negative Breast Cancer

Jiachen Zou, Liulu Zhang, Yuanqi Chen, Yingyi Lin, Minyi Cheng et al. (8 authors)

Journal of Breast Cancer2023-11-173 citations

10.4048/jbc.2023.26.e49

Magnetic resonance imaging tumor regression shrinkage patterns during neoadjuvant chemotherapy versus neoadjuvant immunochemotherapy in triple-negative breast cancer (NeoMDSS-TN-SP): A nonrandomized, prospective cohort study.

Liulu Zhang, Jiachen Zou, Yuanqi Chen, Xinjian Yan, Kun Wang

Journal of Clinical Oncology2023-06-01

10.1200/jco.2023.41.16_suppl.e12601

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

18 Years to No maximum

Healthy volunteers

No

Inclusion criteria

1. For training cohort: Inclusion Criteria: * Age ≥18 years; * Histologically confirmed invasive breast carcinoma; * Clinical stage II-III at presentation; * Complete basic information and image data; * Have MRI imaging data at baseline and after the first cycle of NAC; * Finish the standard NAC treatment and undergo surgery;

Exclusion criteria

* With chemotherapy contraindications; * Multifocal of multicentric lesions; * Poor quality of MRI images; 2. For validation cohort: Inclusion Criteria: * Age ≥18 years; * Complete basic information and image data; * Clinical stage II-III at presentation; * Scheduled for neoadjuvant chemotherapy; * Eastern Cooperative Oncology Group (ECOG) performance status of 0-1. * Signed informed consent;

Design outcomes

Primary

Measure	Time frame	Description
Sensitivity	up to 28 weeks	Testing the sensitivity of NeoMDSS model to predict pCR using the area under receiver operating characteristic curve.

Secondary

Measure	Time frame	Description
Specificity	up to 28 weeks	Testing the sensitivity of NeoMDSS model to predict non-pCR using the area under receiver operating characteristic curve.

Other

Measure	Time frame	Description
Shrinkage pattern	up to 28 weeks	The difference in tumor regression shrinkage patterns between the different treatment groups. Based on the MRI after the first cycle, the tumor SPs were grouped into three categories: CS, diffuse decrease, and no change or enlargement.
correlation between shrinkage patterns and efficacy	up to 28 weeks	The correlation between tumor regression shrinkage patterns and treatment efficacy.

Countries

China

Outcome results