Clinical trial · Interventional
The Prediction Model of NAC Response for Breast Cancer Based on The Parametric Dynamics Features.
The Prediction Model of Neoadjuvant Chemotherapy Response for Breast Cancer Based on The Parametric Dynamics Features of The Pretreatment and Early-Treatment MR-PET and QDS-IR Images.
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The main purpose of this study is to develop a computer-aided prediction model for NAC treatment response. Based on the heterogeneity of internal parametric tumor composition commonly observed, this study will utilize the histologic characteristics and treatment response to investigate the image features as input data for predicting treatment response using Deep Learning technology. Using this technique, preoperative treatment evaluation may be facilitated by tumor heterogeneity analysis from developed dynamic radiomics, and the possibility of personal medicine can be realized not far ahead. In the first two years of this study using images from DCE-MRI, PET/CT and QDS-IR, we plan to develop the image processing algorithms, including segmenting breast and tumor region, extracting image feature which reflects angiogenic properties and permeability of tumor, which are highly correlated with NAC treatment response. During the third year of the project, the morphology and texture features from first two years can be combined for PET/MRI and prediction model can be achieved in accordance with the features extracted from dynamic features extraction using longitudinal images of PET/MRI.
Conditions
Conditions (5)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Cancer | Malignant Breast Neoplasm | CURATED_EXACT | 0.92 |
| Chemotherapy Effect | — | UNRESOLVED | — |
| Diffusion Weighted MRI | — | UNRESOLVED | — |
| Multiparametric Magnetic Resonance Imaging | — | UNRESOLVED | — |
| PET Imaging | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Whole body 18F-FDG Positron Emission Tomography | Radiation | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- OTHER
- label
- PET/MR scanning for neoadjuvant chemotherapy breast cancer patients
- description
- From April 2015 to June 2019, women with breast cancer who underwent neoadjuvant chemotherapy were enrolled. Arranged for at least three PET/MR scans during NAC: the first \[R0\], pre-treatment; and the second\[R1\], after two cycles of chemotherapy (post-treatment) and the third \[R2\] before surgery.
- interventionNames
- Radiation: Whole body 18F-FDG Positron Emission Tomography
Primary outcomes (2)
- measure
- Model Prediction power of pathological complete response(pCR)
- timeFrame
- an average of four months
- description
- Comparison of different of prediction models derived from MR/PET and QDS-IR in terms of AUCs.
- measure
- Comparison of models in prediction of pathological complete response(pCR)
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 20 Years
Show eligibility criteria text
Inclusion Criteria: * (a) were \> 20 years of age, * (b) with pathologically confirmed breast cancer with core needle biopsy * (c) were willing to undergo NAC * (d) were eligible for surgery after NAC * (e) were willing to undergo at least three PET/MR scans during NAC: the first \[R0\], pre-treatment; and the second \[R1\], after two cycles of chemotherapy (post-treatment) and before surgery \[R2\] Exclusion Criteria: * (a) distant metastases or recurrent breast cancer. * (b) unable to comply with sequential PET/MR scanning schedule. * (c) Impaired renal function, CCR\>30ml/min. * (d) Known aller
References
Publications (16)
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- BACKGROUNDDavnall F, Yip CS, Ljungqvist G, Selmi M, Ng F, Sanghera B, Ganeshan B, Miles KA, Cook GJ, Goh V. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging. 2012 Dec;3(6):573-89. doi: 10.1007/s13244-012-0196-6. Epub 2012 Oct 24. PMID 23093486
- BACKGROUNDGillies RJ, Schornack PA, Secomb TW, Raghunand N. Causes and effects of heterogeneous perfusion in tumors. Neoplasia. 1999 Aug;1(3):197-207. doi: 10.1038/sj.neo.7900037. PMID 10935474
- BACKGROUNDvon Minckwitz G, Rezai M, Loibl S, Fasching PA, Huober J, Tesch H, Bauerfeind I, Hilfrich J, Eidtmann H, Gerber B, Hanusch C, Kuhn T, du Bois A, Blohmer JU, Thomssen C, Dan Costa S, Jackisch C, Kaufmann M, Mehta K, Untch M. Capecitabine in addition to anthracycline- and taxane-based neoadjuvant treatment in patients with primary breast cancer: phase III GeparQuattro study. J Clin Oncol. 2010 Apr 20;28(12):2015-23. doi: 10.1200/JCO.2009.23.8303. Epub 2010 Mar 22.