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Value of magnetic resonance imaging radiomics features in predicting histologic grade of invasive ductal carcinoma of the breast.
Yang, Xin-Lei; Ni, Dong-He; Yu, Yang; Zhao, Jin-Cui; Lin, Rui; Xiu, Chao; Chang, Zhe-Xing.
Afiliação
  • Yang XL; Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China.
  • Ni DH; Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China.
  • Yu Y; Department of Radiology, Jilin Province Integrated Traditional Chinese and Western Medicine Hospital, Jilin, China.
  • Zhao JC; Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China.
  • Lin R; Department of Radiology, Beihua University Affiliated Hospital, Jilin, China.
  • Xiu C; Department of Radiology, Beihua University Affiliated Hospital, Jilin, China.
  • Chang ZX; Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China.
Technol Health Care ; 32(3): 1609-1618, 2024.
Article em En | MEDLINE | ID: mdl-38393931
ABSTRACT

BACKGROUND:

Breast cancer has the second highest mortality rate of all cancers and occurs mainly in women.

OBJECTIVE:

To investigate the relationship between magnetic resonance imaging (MRI) radiomics features and histological grade of invasive ductal carcinoma (IDC) of the breast and to evaluate its diagnostic efficacy.

METHODS:

The two conventional MRI quantitative indicators, i.e. the apparent diffusion coefficient (ADC) and the initial enhancement rate, were collected from 112 patients with breast cancer. The breast cancer lesions were manually segmented in dynamic contrast-enhanced MRI (DCE-MRI) and ADC images, the differences in radiomics features between Grades I, II and III IDCs were compared and the diagnostic efficacy was evaluated.

RESULTS:

The ADC values (0.77 ± 0.22 vs 0.91 ± 0.22 vs 0.92 ± 0.20, F= 4.204, p< 0.01), as well as the B_sum_variance (188.51 ± 67.803 vs 265.37 ± 77.86 vs 263.74 ± 82.58, F= 6.040, p< 0.01), L_energy (0.03 ± 0.02 vs 0.13 ± 0.11 vs 0.12 ± 0.14, F= 7.118, p< 0.01) and L_sum_average (0.78 ± 0.32 vs 16.34 ± 4.23 vs 015.45 ± 3.74, F= 21.860, p< 0.001) values of patients with Grade III IDC were significantly lower than those of patients with Grades I and II IDC. The B_uniform (0.15 ± 0.12 vs 0.11 ± 0.04 vs 0.12 ± 0.03, F= 3.797, p< 0.01) and L_SRE (0.85 ± 0.07 vs 0.78 ± 0.03 vs 0.79 ± 0.32, F= 3.024, p< 0.01) values of patients with Grade III IDC were significantly higher than those of patients with Grades I and II IDC. All differences were statistically significant (p< 0.05). The ADC radiomics signature model had a higher area-under-the-curve value in identifying different grades of IDC than the ADC value model and the DCE radiomics signature model (0.869 vs 0.711 vs 0.682). The accuracy (0.812 vs 0.647 vs 0.710), specificity (0.731 vs 0.435 vs 0.342), positive predictive value (0.815 vs 0.663 vs 0.669) and negative predictive value (0.753 vs 0.570 vs 0.718) of the ADC radiomics signature model were all significantly better than the ADC value model and the DCE radiomics signature model.

CONCLUSION:

ADC values and breast MRI radiomics signatures are significant in identifying the histological grades of IDC, with the ADC radiomics signatures having greater value.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Imageamento por Ressonância Magnética / Carcinoma Ductal de Mama Limite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: Technol Health Care Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Imageamento por Ressonância Magnética / Carcinoma Ductal de Mama Limite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: Technol Health Care Ano de publicação: 2024 Tipo de documento: Article