Evidence map›Paper›PMID 42376199›Full record

ArticleEuropean journal of radiology open2026

Role of apparent diffusion coefficient (ADC) and MRI-derived parameters in identifying p53-abnormal subtypes of endometrial cancer.

Sara Parviz, Shahrzad Sepidbar, Soheila Sarmadi, Fatemeh Nili, Fahimeh Zeinalkhani, Mohammadreza Tahamtan, Madjid Shakiba, Mahrooz Malek

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Article in European journal of radiology open, 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

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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

8 authors.

Sara ParvizTehran University of Medical Sciences (TUMS) Department of Radiology, Medical Imaging Center, Imam Khomeini Hospital Complex (IKHC) Musculoskeletal Imaging Center (MIRC), Iran.
Shahrzad SepidbarTehran University of Medical Sciences (TUMS) Department of Radiology, Medical Imaging Center, Imam Khomeini Hospital Complex (IKHC), Iran.
Soheila SarmadiDepartment of Pathology, Yas Hospital Complex, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Fatemeh NiliDepartment of pathology, Tehran university of medical sciences, IKHC, Tehran, Iran.
Fahimeh ZeinalkhaniAdvanced Diagnostic and Interventional Radiology Research Center (ADIR), Department of Radiology, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Mohammadreza TahamtanAdvanced Diagnostic and Interventional Radiology Research Center (ADIR), Department of Radiology, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Madjid ShakibaDepartment of Radiology, Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Mahrooz MalekDepartment of Radiology, Medical Imaging Center, Imam Khomeini Hospital Complex (IKHC) Musculoskeletal Imaging Center (MIRC), Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-invasive imaging techniques such as magnetic resonance imaging (MRI) offer advantages over repeated biopsies for assessing tumor characteristics, though histological and molecular analysis remain the diagnostic gold standard. Since P53 expression is an important prognostic factor linked to the histopathological patterns of endometrial cancer (EC), using MRI-derived indices to distinguish between TP53-mutated (P53abn) and non-P53abn subtypes is clinically practical. This study aimed to determine the predictive value of MRI-based markers, especially apparent diffusion coefficients (ADC), for differentiating P53abn and non-P53abn subtypes in patients with EC. Methods: This retrospective study was performed on 115 patients with known EC. All MR imaging studies were performed on 1.5 T MR imaging units. The presence of p53abn subtype was determined by immunohistochemical staining (IHC). Data were analyzed using R version 4.4.1. Results: A statistically significant difference was observed in mean ADC values between patients with and without p53abn by IHC, with notably lower ADC values in the P53abn group. However, no significant association was identified between P53abn status and other imaging parameters, such as mass T2, outer myometrium T2, or the mass-to-psoas intensity ratio. Multivariable logistic regression analysis identified ADC value and tumor's histological subtype as the primary determinants of p53abn EC. ROC curve analysis further demonstrated that ADC measurement could effectively predict p53abn. The best cutoff point of ADC to discrimination was 695, yielding a sensitivity of 100% and specificity of 83%. Conclusion: In patients with EC, assessing tumor ADC values on MRI can serve as a valuable tool for predicting p53abn subtype.

Indexed as

Apparent diffusion coefficientsEndometrial cancerMagnetic resonance imagingP53

Identifiers

PMID42376199
PMCPMC13311172

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