Diagnostic performance of kinetic parameters derived from ultrafast breast MRI in characterizing benign and malignant breast lesions: the added value of the semiautomatically based parameters

Adding semiautomatic ultrafast parameters to the MS and TTE improves the overall performance in characterizing breast lesions. The combined ultrafast parameters provide the highest discriminating power between benign and malignant breast lesions. Ultrafast MRI showed comparable performance to conventional dynamic contrast-enhanced MRI in the discrimination between benign and malignant breast lesions.

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Publication Details

Journal
Insights into Imaging
Published
2025-12-22
DOI
https://doi.org/10.1186/s13244-025-02162-8
Primary Topic
MRI in cancer diagnosis
Type
article
Field-Weighted Citation Impact
0.00
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article

Diagnostic performance of kinetic parameters derived from ultrafast breast MRI in characterizing benign and malignant breast lesions: the added value of the semiautomatically based parameters

Omar Hamdy, Ali H. Elmokadem, Rasha Karam, Dalia Bayoumi et al.
Insights into Imaging
MRI in cancer diagnosis
article

Diagnostic performance of kinetic parameters derived from ultrafast breast MRI in characterizing benign and malignant breast lesions: the added value of the semiautomatically based parameters

Omar Hamdy, Ali H. Elmokadem, Rasha Karam, Dalia Bayoumi, Farah Ahmed Shokeir, Ahmed Abdallah
article en

Abstract

Adding semiautomatic ultrafast parameters to the MS and TTE improves the overall performance in characterizing breast lesions. The combined ultrafast parameters provide the highest discriminating power between benign and malignant breast lesions. Ultrafast MRI showed comparable performance to conventional dynamic contrast-enhanced MRI in the discrimination between benign and malignant breast lesions.

Insights into ImagingVol. 16(1)
Mansoura University (EG)
Reduced inequalities
Openalex Percentile: Top 32%
MRI in cancer diagnosis
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Diagnostic performance of kinetic parameters derived from ultrafast breast MRI in characterizing benign and malignant breast lesions: the added value of the semiautomatically based parameters — Omar Hamdy, Ali H. Elmokadem, et al. · Insights into Imaging (2025) | TGRS Research Map | TGRS