Evidence map›Paper›PMID 42273091›Full record

ArticleQuantitative imaging in medicine and surgery2026

Magnetic resonance imaging signal variation for the effective quantitative evaluation of treatment response to neoadjuvant immunotherapy of osteosarcoma: a comparative study with Response Evaluation Criteria in Solid Tumors version 1.1.

Boya Li, Changliang Su, Baocong Liu, Yingchun Zhang, Jun Liu, Qinglian Tang, Ziyang Peng, Guixiao Xu, Lizhi Liu, Fei Ai

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Boya Li *Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Changliang Su *Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Baocong Liu *Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Yingchun ZhangDepartment of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Jun LiuDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Qinglian TangDepartment of Musculoskeletal Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Ziyang PengDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Guixiao XuDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Lizhi LiuDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Fei AiDepartment of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As the application of immunotherapy for osteosarcoma becomes more widespread, the limitations of Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) in evaluating the unique response patterns of treatment efficacy are becoming increasingly apparent. This study aimed to examine the application of quantitative magnetic resonance imaging (MRI) parameters in the assessment of treatment response in patients with osteosarcoma after neoadjuvant immunotherapy (NAIT) with comparison to RECIST 1.1. Methods: This prospective study included 55 patients diagnosed with osteosarcoma (44 males; mean age, 19.45±7.00 years) and treated with NAIT between 2019 and 2022 at a single center. Histogram features (HFs) and the RECIST 1.1 category in pre- and posttreatment MRI [T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced T1WI (T1C)] were analyzed for evaluating posttreatment tumor cell necrosis rate (TCNR), with good response defined as a TCNR ≥90%. Spearman correlation analysis, the Mann-Whitney U test, binary logistic regression, and the receiver operating characteristic (ROC) curve were applied as appropriate. Results: MRI HFs differed significantly between the good- and poor-response groups. Normalized T1WI features (percentiles, kurtosis, and coefficient of variation) showed stronger group differences (P<0.05) than did nonnormalized features. T1WI and T1C features correlated moderately with TCNR, with nonnormalized features being weakly correlated (|r|=0.271-0.293; P<0.05) and normalized features being strongly associated (|r|=0.273-0.428; P<0.05); in particular, T1WI differed significantly between pre- and post-NAIT (|r| Conclusions: Quantitative HFs reflecting MR signal variations allow for the effective evaluation of treatment response in patients with osteosarcoma after NAIT and may provide supplemental information to RECIST 1.1.

Indexed as

histogram analysisimmunotherapymagnetic resonance imaging (MRI)Osteosarcomatreatment responses

Identifiers

PMID42273091
PMCPMC13247897

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