Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
466-02-009 ISMRM Abstract

Predicting Induction Chemotherapy Response Based on Tumor-stroma ratio Pretreatment Synthetic MRI in Nasopharyngeal Carcinoma

Accepted
Huanhuan Ren 1, Yulin Wang2, Qian Xu2, Daihong Liu1, Xinyu Chen3, Junhao Huang4, 菁 张4, Hong Yu5, Yong Tan4, Lisha Nie6, Jiuquan Zhang5
1Department of Radiology Chongqing University Cancer Hospital, Chongqing, chongqing, China
2School of Medicine, School of Medicine, Chongqing University, China
3Department of Pathology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, ChongQing, China
4Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, ChongQing, China
5Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, ChongQing, China
6GE Healthcare, MR Research China, Beijing, China
Presenting Author: Huanhuan Ren

Synopsis

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References

1. Tang QN, Liu LT, Qi B, et al. Effect of Concurrent Chemoradiotherapy With Nedaplatin vs Cisplatin on the Long-term Outcomes of Survival and Toxic Effects Among Patients With Stage II to IVB Nasopharyngeal Carcinoma: A 5-Year Follow-up Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open. 2021;4(12):e2138470. Published 2021 Dec 1. doi:10.1001/jamanetworkopen.2021.38470 [doi]
2. Liu T, Liu LT, Lin JY et al (2021) Management of suboptimal response to induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma: Re-induction therapy or direct to Radiotherapy? Radiother Oncol 163:185-191
3. Guo, Y., Dai, G., Xiong, X et al (2023) Intravoxel incoherent motion radiomics nomogram for predicting tumor treatment responses in nasopharyngeal carcinoma. Translational oncology 31:101648
4. Liu W, Wang X, Xie S et al (2023) Amide proton transfer (APT) and magnetization transfer (MT) in predicting short-term therapeutic outcome in nasopharyngeal carcinoma after chemoradiotherapy: a feasibility study of three-dimensional chemical exchange saturation transfer (CEST) MRI. Cancer Imaging 23:80
5. Cui Y, Zhao K, Meng X et al (2024) A computed tomography-based multitask deep learning model for predicting tumour stroma ratio and treatment outcomes in patients with colorectal cancer: a multicentre cohort study. Int J Surg 110:2845-2854
6. Hagiwara A, Fujimoto K, Kamagata K et al (2021) Age-Related Changes in Relaxation Times, Proton Density, Myelin, and Tissue Volumes in Adult Brain Analyzed by 2-Dimensional Quantitative Synthetic Magnetic Resonance Imaging. Invest Radiol 56:163-172
7. Ren J, Ding L, Zhang D et al (2018) Carcinoma-associated fibroblasts promote the stemness and chemoresistance of colorectal cancer by transferring exosomal lncRNA H19. Theranostics 8:3932-39487
8. Wu A, Loutherback K, Lambert G et al (2013) Cell motility and drug gradients in the emergence of resistance to chemotherapy. Proc Natl Acad Sci U S A 110:16103-16108
9. Iafrate F, Ciccarelli F, Masci GM et al (2023) Predictive role of diffusion-weighted MRI in the assessment of response to total neoadjuvant therapy in locally advanced rectal cancer. Eur Radiol 33:854-862

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