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Comparison of mammography with automated breast ultrasound system for detecting breast lesions / 中国肿瘤临床
Chinese Journal of Clinical Oncology ; (24): 969-972, 2017.
Artigo em Chinês | WPRIM | ID: wpr-666952
ABSTRACT

Objective:

To compare the clinical utility of mammography with automated breast ultrasound system (ABUS) for detecting breast lesions.

Methods:

Data of 142 patients with 149 breast lesions who underwent both mammography and ABUS in Tianjin Medi-cal University Cancer Institute and Hospital were collected from Jnly 2016 to September 2016. The detection rates of the two methods were then determined.

Results:

The overall detection rate using ABUS was significantly higher than that of mammography (mammog-raphy 87.2% vs. ABUS 98.0%, P<0.05). However, no significant difference was observed in breast cancer detection rates between mammography and ABUS (mammography91.1%vs. ABUS97.0%, P<0.05). Moreover, the benign lesion detection rate was significant-ly higher in ABUS than in mammography (mammography79.2%, vs. ABUS100%, P<0.05). In dense breasts, the detection rates of overall lesions, breast cancers, and benign lesions for ABUS were 97.7%, 96.5%, and 100.0%, respectively;whereas those for mammog-raphy were 86.0%, 90.6%, and 77.3%, respectively (P<0.05). Owing to overlapping dense breast tissue and deep anatomic location, sev-eral lesions were missed on mammography. Conversely, most lesions missed on ABUS presented as calcifications.

Conclusion:

Com-pared with mammography, ABUS can detect more lesions especially in dense breasts. However, ABUS failed to detect calcifications, whereas mammography had distinct advantages in this regard. Overall, the two methods had potential supplementary value for breast cancer screening.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Clinical Oncology Ano de publicação: 2017 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Clinical Oncology Ano de publicação: 2017 Tipo de documento: Artigo