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The value of texture analysis combined with TIC in the differential diagnosis of breast invasive ductal carcinoma and fibroadenoma
WANG Liang  MEI Haiqing  PENG Hongfeng  ZHANG Dongyou  HAN Rui 

Cite this article as: Wang L, Mei HQ, Peng HF, et al. The value of texture analysis combined with TIC in the differential diagnosis of breast invasive ductal carcinoma and fibroadenoma[J]. Chin J Magn Reson Imaging, 2021, 12(10): 53-56. DOI:10.12015/issn.1674-8034.2021.10.012.


[Abstract] Objective To study the value of texture analysis combined with time-intensity curve (TIC) in the differential diagnosis of breast invasive ductal carcinoma and fibroadenoma. Materials andMethods The MRI images of 75 female patients (48 cases of breast invasive ductal carcinoma and 27 cases of breast fibroadenoma) confirmed by pathology were collected by retrospective method. The TIC were drawn and the five analysis methods of histogram, absolute gradient, run matrix, co-occurrence matrix and autoregressive model in texture analysis software were used to extract texture features of breast lesions on enhanced image, and obtain 306 texture feature parameters; using three statistical methods: Fisher coefficient (Fisher), classification error probability and average correlation coefficients (POE+ACC) and mutual information coefficient (MI), 10 optimal texture parameters were selected to distinguish breast invasive ductal carcinoma and fibroadenoma. The principal component analysis (PCA), linear discriminant analysis (LDA) and non-linear discriminant analysis (NDA) of B11 program were used to reduce the dimension and classify the 10 optimal texture parameters, and the minimum error rate of lesions under the optimal texture parameters was calculated. The sensitivity, specificity and accuracy of TIC method, texture analysis method and the combination of the two methods were analyzed.Results Fisher+NDA or POE+ACC+NDA combination had the lowest misjudgment rate (4%), and the 10 best texture parameters for modeling were: Fisher+NDA were GeoW1, S (5, -5) Entropy, S (5, 5) Correlat, S (4, -4) Entropy, S (5, 0) Entropy, S (5, 5) Entropy, eta2, S (4, 0) Entropy, Teta3, S (3, -3) Entropy;Poe+ACC+NDA were GeoYo, Vertl_Fraction, GeoW5b, GeoW4, S (5, 5) CorrelatTeta1, Vertl_ShrtREmp, GeoNx, GeoAox, GeoX. The sensitivity of TIC, texture analysis and the combination of the two methods were 87.5%, 93.8%, 97.9%; the specificity were 29.6%, 11.1%, 14.8%; the accuracy were 66.7%, 64.0%, 68.0%.Conclusion On the basis of routine MRI examination and enhancement, the sensitivity and accuracy of breast invasive ductal carcinoma and breast fibroadenoma can be improved by using TIC and MRI texture parameter analysis, which has certain value in the differential diagnosis of breast fibroadenoma and invasive ductal carcinoma.
[Keywords] breast tumor；breast fibroadenoma；breast invasive ductal carcinoma；differential diagnosis；magnetic resonance imaging；texture analysis；time-intensity curve

WANG Liang   MEI Haiqing   PENG Hongfeng   ZHANG Dongyou   HAN Rui*  

Department of Radiology, Wuhan No.1 Hospital, Wuhan 430022, China

Han R, E-mail: 1021779149@qq.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Wuhan Medical Research Project General Project-Key Project (WX18B08).
Received  2021-04-12
Accepted  2021-06-28
DOI: 10.12015/issn.1674-8034.2021.10.012
Cite this article as: Wang L, Mei HQ, Peng HF, et al. The value of texture analysis combined with TIC in the differential diagnosis of breast invasive ductal carcinoma and fibroadenoma[J]. Chin J Magn Reson Imaging, 2021, 12(10): 53-56. DOI:10.12015/issn.1674-8034.2021.10.012.

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