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ADC full volume histogram analysis in differentiating benign and malignant mass-like breast lesions / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 1499-1503, 2019.
Artigo em Chinês | WPRIM | ID: wpr-861203
ABSTRACT

Objective:

To investigate the value of ADC full volume histogram analysis in differential diagnosis of benign and malignant mass-like breast lesions.

Methods:

Totally 57 cases of malignant mass-like breast lesions and 31 cases of benign mass-like breast lesions confirmed by pathology were analyzed retrospectively. All patients underwent MR examination including plain scan, dynamic contrast enhanced MR and DWI. Conventional average ADC values and ADC full volume histogram parameters (including multiple percent ADC values, ADCmin, ADCmax, ADCmean, skewness, kurtosis, and standard deviation) were measured and recorded. The conventional average ADC values and ADC histogram parameters were compared between benign and malignant lesions, and the ROC curves were used to evaluate the diagnostic efficacy of each parameter.

Results:

There were significant differences in the ADC histogram parameters (ADC values, skewness, kurtosis, standard deviation) and conventional average ADC values between benign and malignant lesions (all P<0.05). The 75th ADC and 90th ADC values had the highest AUC in identifying benign and malignant lesions, which was 0.84. The AUC of the ADCmean, 50th ADC values in identifying benign and malignant lesions were statistically different from the AUC of the conventional average ADC values (both P<0.05).

Conclusion:

ADC full volume histogram can fully reflect the overall information of lesions, and have certain value for identification of benign and malignant mass-like breast lesions.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Medical Imaging Technology Ano de publicação: 2019 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Medical Imaging Technology Ano de publicação: 2019 Tipo de documento: Artigo