MRI/ULTASOUND FUSION INCREASE DIAGNOSTIC ACCURACY OF BREAST LESION

Background: Breast cancer is the most common malignancy among women worldwide, and early and accurate detection is critical for effective treatment. While magnetic resonance imaging (MRI) and ultrasound (US) are widely used for breast cancer diagnosis, each modality has inherent limitations. MRI/ultrasound fusion imaging combines the strengths of both techniques, offering enhanced diagnostic capabilities. Objective: This study evaluates the impact of MRI/ultrasound fusion imaging on the diagnostic accuracy of breast cancer, focusing on lesion localization, characterization, and clinical utility in guiding biopsy and treatment planning. Methods: A retrospective analysis was conducted on 59 patients with suspicious breast lesions who underwent both MRI and ultrasound imaging. MRI/ultrasound fusion imaging was performed to combine high-resolution MRI data with real-time ultrasound. Diagnostic accuracy, sensitivity, and specificity were compared across standalone MRI, ultrasound, and fusion imaging. Results: MRI/ultrasound fusion imaging demonstrated significantly higher diagnostic accuracy (89.8%) compared to MRI (84.7%) and ultrasound (81.3%) alone. Sensitivity and specificity for fusion imaging were 97.9% and 58.3%, respectively. It also facilitated real-time targeted biopsy with improved precision. Conclusion: MRI/ultrasound fusion imaging significantly enhances the diagnostic accuracy of breast cancer detection . MRI/ultrasound fusion imaging may be a valuable tool for clinical practice.

Institutions

Publication Details

Journal
Journal of Pharmaceutical and Medical Research
Published
2024-12-20
DOI
https://doi.org/10.61784/jpmr3025
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MRI/ULTASOUND FUSION INCREASE DIAGNOSTIC ACCURACY OF BREAST LESION

Journal of Pharmaceutical and Medical Research
AI in cancer detection
article

MRI/ULTASOUND FUSION INCREASE DIAGNOSTIC ACCURACY OF BREAST LESION

article en

Abstract

Background: Breast cancer is the most common malignancy among women worldwide, and early and accurate detection is critical for effective treatment. While magnetic resonance imaging (MRI) and ultrasound (US) are widely used for breast cancer diagnosis, each modality has inherent limitations. MRI/ultrasound fusion imaging combines the strengths of both techniques, offering enhanced diagnostic capabilities. Objective: This study evaluates the impact of MRI/ultrasound fusion imaging on the diagnostic accuracy of breast cancer, focusing on lesion localization, characterization, and clinical utility in guiding biopsy and treatment planning. Methods: A retrospective analysis was conducted on 59 patients with suspicious breast lesions who underwent both MRI and ultrasound imaging. MRI/ultrasound fusion imaging was performed to combine high-resolution MRI data with real-time ultrasound. Diagnostic accuracy, sensitivity, and specificity were compared across standalone MRI, ultrasound, and fusion imaging. Results: MRI/ultrasound fusion imaging demonstrated significantly higher diagnostic accuracy (89.8%) compared to MRI (84.7%) and ultrasound (81.3%) alone. Sensitivity and specificity for fusion imaging were 97.9% and 58.3%, respectively. It also facilitated real-time targeted biopsy with improved precision. Conclusion: MRI/ultrasound fusion imaging significantly enhances the diagnostic accuracy of breast cancer detection . MRI/ultrasound fusion imaging may be a valuable tool for clinical practice.

Journal of Pharmaceutical and Medical ResearchVol. 6(4)
Shantou University (CN), Yue Bei People's Hospital (CN)
Zero hunger
Openalex Percentile: Top 78%
AI in cancer detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.