Comparative Evaluation of Superb Microvascular Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Differentiating Benign and Malignant Breast Masses

被引:0
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作者
Yitik, Ahmet Yasin [1 ]
Sabir, Nuran [1 ]
Yilmaz, Sevda [2 ]
机构
[1] Pamukkale Univ, Med Fac Hosp, Dept Radiol, Denizli, Turkiye
[2] Pamukkale Univ, Med Fac Hosp, Dept Gen Surg, Denizli, Turkiye
关键词
breast cancer; breast imaging; magnetic resonance imaging; superb microvascular imaging; vascular index; SHEAR-WAVE ELASTOGRAPHY; VASCULAR INDEX; MRI; PARAMETERS; DIAGNOSIS;
D O I
10.1002/jum.16664
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Objectives Our study aims to compare the diagnostic performance of superb microvascular imaging (SMI) and dynamic contrast-enhanced magnetic resonance imaging (MRI) in differentiating benign from malignant breast masses, using histopathological findings as the reference standard. Methods This prospective study was conducted from April 2022 to March 2024. A total of 112 breast lesions from 110 patients were evaluated using gray-scale ultrasonography, SMI, and dynamic contrast-enhanced MRI. The vascular index (VI) obtained during SMI examination and kinetic curve patterns from MRI were analyzed. Results Histopathological analysis revealed 62 benign and 50 malignant lesions. The VI showed a statistically significant difference between benign and malignant lesions, with a mean VI of 5.12 +/- 4.66 in benign masses and 10.13 +/- 5.48 in malignant masses (P < .001). The ROC analysis demonstrated an AUC of 0.79 for SMI with a VI cut-off value of 4.15, yielding a sensitivity of 92%, specificity of 60%, and accuracy of 74%. A statistically significant correlation was found between VI values and MRI contrast enhancement kinetic curve types (P < .05). MRI demonstrated superior diagnostic performance, with an AUC of 0.89 and sensitivity, specificity, and accuracy of 98, 80.65, and 88.39%, respectively. Conclusions SMI, when used in conjunction with conventional ultrasonography and MRI, provides significant diagnostic value in differentiating benign from malignant breast masses. The study supports the potential integration of SMI into routine breast cancer diagnostic workflows, particularly in settings where MRI is less accessible.
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