Background: Multi-b-value diffusion-weighted MRI holds potential for noninvasively predicting p53 abnormality and microsatellite instability (MSI) in endometrial cancer (EC), but the optimal diffusion model and region of interest (ROI) strategy remain undetermined. This study aims to identify the optimal diffusion model-ROI strategy combination for predicting p53 abnormality and MSI status by comparing diffusion MRI-derived parameters from three ROI approaches.
Methods: This retrospective study included patients with EC who underwent preoperative multi-b-value diffusion MRI between December 2020 and June 2025. Two radiologists independently quantified apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) parameters using three ROI strategies (single-slice ROI [ssROI], three-slice ROI [tsROI], and whole-tumor volume ROI [wtROI]. Multivariable logistic regression identified parameters associated with p53 abnormality and MSI. Diagnostic performance was assessed using the receiver operating characteristic curve and compared with the DeLong test. Additionally, the reproducibility of the parameters was evaluated.
Results: Among 143 enrolled patients (mean age, 57.73years ± 10.01[SD]), 136 were assessed for p53 status (37 abnormal) and 109 for mismatch repair status (17 MSI). All parameters showed good-to-excellent reproducibility. Elevated D* and lower MD in ssROI, lower D in tsROI, and decreased MD in wtROI were associated with p53 abnormality. Lower ADC across all ROIs was associated with MSI. For predicting p53 abnormality, ssROI-MD yielded the highest AUC of 0.711 (95% CI: 0.627, 0.785), which showed similar performance to other parameter-ROI combinations. For predicting MSI, tsROI-ADC (AUC,0.755 [95%CI:0.646, 0.844]) and wtROI-ADC (AUC,0.758 [95%CI:0.649, 0.846]) significantly outperformed ssROI-ADC (AUC,0.700 [95%CI:0.587, 0.797]; p = 0.006 and 0.025, respectively), with wtROI-ADC showing higher sensitivity (90.9%).
Conclusions: MD from a single-slice ROI is optimal for the identification of p53 abnormality, combining diagnostic performance with operational simplicity and high reproducibility. For MSI prediction, ADC from a whole-tumor ROI is preferred due to its superior sensitivity and excellent reproducibility.
{"title":"Comparing multi-b-value diffusion models and ROI delineation strategies for prediction of p53 abnormality and microsatellite instability in endometrial cancer.","authors":"Yi Li, Xuemei Wang, Kaiming Xue, Yunhai Mao, Wenchao Wang, Xiaoming Liu, Wei Wang, Mengchao Zhang","doi":"10.1186/s12880-026-02277-4","DOIUrl":"https://doi.org/10.1186/s12880-026-02277-4","url":null,"abstract":"<p><strong>Background: </strong>Multi-b-value diffusion-weighted MRI holds potential for noninvasively predicting p53 abnormality and microsatellite instability (MSI) in endometrial cancer (EC), but the optimal diffusion model and region of interest (ROI) strategy remain undetermined. This study aims to identify the optimal diffusion model-ROI strategy combination for predicting p53 abnormality and MSI status by comparing diffusion MRI-derived parameters from three ROI approaches.</p><p><strong>Methods: </strong>This retrospective study included patients with EC who underwent preoperative multi-b-value diffusion MRI between December 2020 and June 2025. Two radiologists independently quantified apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) parameters using three ROI strategies (single-slice ROI [ssROI], three-slice ROI [tsROI], and whole-tumor volume ROI [wtROI]. Multivariable logistic regression identified parameters associated with p53 abnormality and MSI. Diagnostic performance was assessed using the receiver operating characteristic curve and compared with the DeLong test. Additionally, the reproducibility of the parameters was evaluated.</p><p><strong>Results: </strong>Among 143 enrolled patients (mean age, 57.73years ± 10.01[SD]), 136 were assessed for p53 status (37 abnormal) and 109 for mismatch repair status (17 MSI). All parameters showed good-to-excellent reproducibility. Elevated D* and lower MD in ssROI, lower D in tsROI, and decreased MD in wtROI were associated with p53 abnormality. Lower ADC across all ROIs was associated with MSI. For predicting p53 abnormality, ssROI-MD yielded the highest AUC of 0.711 (95% CI: 0.627, 0.785), which showed similar performance to other parameter-ROI combinations. For predicting MSI, tsROI-ADC (AUC,0.755 [95%CI:0.646, 0.844]) and wtROI-ADC (AUC,0.758 [95%CI:0.649, 0.846]) significantly outperformed ssROI-ADC (AUC,0.700 [95%CI:0.587, 0.797]; p = 0.006 and 0.025, respectively), with wtROI-ADC showing higher sensitivity (90.9%).</p><p><strong>Conclusions: </strong>MD from a single-slice ROI is optimal for the identification of p53 abnormality, combining diagnostic performance with operational simplicity and high reproducibility. For MSI prediction, ADC from a whole-tumor ROI is preferred due to its superior sensitivity and excellent reproducibility.</p>","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147455566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-13DOI: 10.1186/s12880-026-02282-7
Yingying Liu, Yafang Dou, Wenning Yuan, Shiman Wu, Zhenwei Yao
{"title":"Are 2D MRI slices equally important in microvascular invasion prediction: a study based on multiple instance learning with attention.","authors":"Yingying Liu, Yafang Dou, Wenning Yuan, Shiman Wu, Zhenwei Yao","doi":"10.1186/s12880-026-02282-7","DOIUrl":"https://doi.org/10.1186/s12880-026-02282-7","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147455521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-12DOI: 10.1186/s12880-026-02271-w
Yanan Jin, Yong Zhang, Jingliang Cheng, Xiaoning Shao, Yan Zhang
{"title":"Diagnostic utility of cardiac magnetic resonance-derived myocardial strain and fractal analysis in differentiating left ventricular noncompaction from dilated cardiomyopathy.","authors":"Yanan Jin, Yong Zhang, Jingliang Cheng, Xiaoning Shao, Yan Zhang","doi":"10.1186/s12880-026-02271-w","DOIUrl":"https://doi.org/10.1186/s12880-026-02271-w","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147442466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intratumoral and peritumoral habitat imaging based on multiparametric MRI to predict HER2-negative breast cancer subtypes: a multicenter study.","authors":"Hongli Pan, Qun Wang, Chang Rong, Ying Zhang, Xiaoyu Zhang, Xiaohu Li, Xingwang Wu, Weishu Hou, Yongqiang Yu","doi":"10.1186/s12880-026-02261-y","DOIUrl":"https://doi.org/10.1186/s12880-026-02261-y","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147430602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-11DOI: 10.1186/s12880-026-02272-9
Chuge Zhang, Gengyun Miao, Mengsu Zeng, Mingliang Wang
{"title":"CT and MRI findings of intraductal tubulopapillary neoplasm of the pancreas.","authors":"Chuge Zhang, Gengyun Miao, Mengsu Zeng, Mingliang Wang","doi":"10.1186/s12880-026-02272-9","DOIUrl":"https://doi.org/10.1186/s12880-026-02272-9","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147430623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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