Evidence map›Paper›PMID 41733841›Full record

ArticleEuropean radiology experimental2026

Predicting induction chemotherapy response based on tumor-stroma ratio and pretreatment synthetic MRI in nasopharyngeal carcinoma.

Huanhuan Ren, Xin Zhang, Qian Xu, Daihong Liu, Xinyu Chen, Yao Huang, Hua Lan, Lifeng Li, Yuanyuan Li, Haiping Huang and 12 more

Abstract read
In one paragraph

Article in European radiology experimental, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Huanhuan Ren *Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Xin Zhang *Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
Qian XuSchool of Medicine, Chongqing University, Chongqing, China.
Daihong LiuDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Xinyu ChenDepartment of Pathology, Chongqing University Cancer Hospital, Chongqing, China.
Yao HuangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Hua LanDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Lifeng LiThe School of Medical Imaging, Changsha Medical University, Changsha, China.
Yuanyuan LiThe School of Medical Imaging, Changsha Medical University, Changsha, China.
Haiping HuangDepartment of Pathology, Chongqing University Cancer Hospital, Chongqing, China.
Jiangdong SuiRadiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
Junhao HuangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Xinying RenDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Yao HuangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Yong TanDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Hong YuDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Xiaolei ShuRadiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
Yuwei WangRadiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
Huan ZhangRadiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
Dan LiRadiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
Lisha NieGE HealthCare MR Research, Beijing, China.
Jiuquan ZhangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing, China. zhangjq_radiol@foxmail.com.ORCID http://orcid.org/0000-0003-0239-6988

Funding

Chongqing Distinguished Youth Science Foundation Project No.CSTB2024NSCQ JQX0025Chongqing Medical Research Project of Combination of Science and Medicine No. 2024MSXM036Chongqing Shapingba District Technology Innovation and Application Development Project No. 2024108Natural Science Foundation of Chongqing Municipality No. CSTB2024NSCQ-MSX0899Natural Science Foundation of Chongqing Municipality No.CSTB2024NSCQ-MSX0944the National Natural Science Foundation of China No. 82071883the National Natural Science Foundation of China No. 82371937
6 · The paper itself

Abstract

objectiveThere is no satisfactory model for predicting the therapeutic response to chemotherapy of nasopharyngeal carcinoma (NPC). We developed a nomogram using tumor-stroma ratio (TSR) and histogram features from pretreatment synthetic magnetic resonance MRI (SyMRI) to assess induction chemotherapy (IC) response in NPC. MATERIALS AND

methodsData from 185 NPC patients were retrospectively collected from July 2022 to November 2023 (training cohort), and 82 NPC patients were prospectively enrolled from December 2023 to July 2024 (test cohort). A nomogram was developed to predict IC response using logistic regression based on clinicopathological and imaging features from SyMRI T1-, T2-, and proton density (PD)-weighted images, and apparent diffusion coefficient (ADC) maps. The nomogram was validated in the test cohort.

resultsAmong the 267 patients (187 males, 80 females), with a mean age of 52.2 years (ranging 43.5-58.7), 181 were responders. Histogram features from ADC and T2-map did not differentiate non-responders (all p ≥ 0.220). A clinicopathological model based on TSR and a SyMRI model using T1map_mean and PDmap_Kurtosis were developed. In the test cohort, The nomogram, combining TSR, T1map_mean, and PDmap_Kurtosis, achieved an area under the curve (AUC) of 0.836 (95% CI: 0.690-0.914), outperforming the clinicopathological model (AUC of 0.711, 95% CI: 0.577-0.809, p = 0.015) and SyMRI model (AUC of 0.774, 95% CI: 0.623-0.822, p = 0.003).

conclusionThe nomogram combining TSR and histogram parameters from pretreatment SyMRI showed a good performance in predicting IC response for NPC, superior to those of clinicopathological and SyMRI models. RELEVANCE STATEMENT: A nomogram based on pretreatment synthetic MRI and clinicopathological features can help in selecting patients as candidates for IC. KEY POINTS: NPC patients with high TSR demonstrated sensitivity to IC. The nomogram, integrating TSR and synthetic MRI parameters, achieved a significantly high predictive performance. The nomogram may be a reliable tool for predicting the response to IC.

Indexed as

Induction ChemotherapyMagnetic Resonance ImagingNasopharyngeal CarcinomaNasopharyngeal NeoplasmsAdultFemaleHumansMaleMiddle AgedNomogramsRetrospective StudiesStromal CellsTreatment OutcomeInduction chemotherapyMagnetic resonance imagingNasopharyngeal carcinomaNomogramPatient selection

Identifiers

PMID41733841
PMCPMC12932746

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.