Value of cone-beam breast CT in differentiating benign from malignant dense breast masses / 中华放射学杂志

Objective:To investigate the value of logistic regression model based on the features of cone-beam breast CT (CBBCT) for the identification of benign and malignant masses in dense breast.Methods:The data of 106 patients (130 masses) with dense breast who underwent contrast-enhanced CBBCT examination and obtained pathological results from May 2011 to August 2020 were retrospectively analyzed as the training set. From August 2020, the data of 49 patients (54 masses) who met the same criteria were prospectively and consecutively collected and used as the validation set. Taking pathological results as the gold standard, the training set was divided into benign and malignant groups. The t-test, χ 2 test and Fisher′s exact test were used to compare the differences in CBBCT image characteristics between the two groups in the training set. A binary logistic regression model was established by multivariate analysis. ROC curves were used to assess the diagnostic efficacy of the model as a whole in the training and validation sets and the diagnostic efficacy of each feature in the model, and the cut-off value of the intensity (ΔCT) value was determined. The H-L method was used to test the goodness of fit of the model. Decision curve analysis (DCA) was drawn to validate the clinical power of the model. Results:Univariate analysis showed that the breast parenchymal background enhancement (BPE), shape, margin, lobulation, spiculation, density, calcifications, ΔCT value, enhancement pattern, non-mass enhancement, ipsilateral increased vascularity (IIV), and peripheral vascular signs had statistical difference between benign group and malignant group ( P<0.05). BPE, margin, ΔCT value and IIV were included in the multivariate analysis, the equation was logit( P′)=-8.510+0.830×BPE+0.822×margin+1.919× ΔCT+1.896 × IIV. The are a under curve of the model in the training set was 0.879 ( P<0.001) and in the validation set was 0.851 ( P=0.001). The are a under curve of BPE, margin, ΔCT value, and IIV in the diagnosis of malignant mass were 0.645, 0.711, 0.712, 0.775 (all P<0.05); the best cut-off value of ΔCT was 50.38 HU. The fit of this model was good ( P = 0.776). The DCA curve showed that when the risk threshold was 0.05-0.97, the net benefit rate was>0, and this model had some clinical value. Conclusion:The logistic regression model based on the features of CBBCT is helpful to distinguish benign and malignant masses in dense breasts.

The accuracy of tumor size evaluation on invasive breast cancer based on cone beam breast CT / 中华放射学杂志

Objective To evaluate the accuracy of cone?beam breast CT (CBBCT) on tumor sizing in patients with invasive breast carcinoma and analyze the influence factors. Methods The preoperative CBBCT images of 82 female patients (85 breast lesions) with invasive breast carcinoma confirmed by pathology from November, 2011 to December, 2017 in Tianjin Medical University Cancer Hospital were included in this retrospective study. All the patients underwent the pathology and immunohistochemical test after operation. Tumor size estimation were performed on preoperative CBBCT images. Referring to tumor size measurement on pathology, all the lesions were divided into two groups. Concordance was defined as the discrepancy in diameter less than 0.5 cm, and the discordance was more than 0.5 cm. Pathology examination was performed after resection, and estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2(HER?2) and Ki?67 result were recorded. All the lesions were classified into molecular subtype, including 14 Luminal A, 50 Luminal B, 11 HER?2?enriched and 10 triple?negative. Intraclass correlation coefficient (ICC) and Pearson correlation coefficient were used to analyze the reliability of CBBCT on tumor sizing. CBBCT?pathology discordance was analyzed based on the clinical, histopathology and CBBCT features by using t test, Chi?square and Fisher exact test. ROC curve was used to analyze the cut?off value between tumor size and CBBCT?pathology discordance. Results The agreement between CBBCT (2.155 ± 0.799) cm and pathology (1.986 ± 0.933) cm measurement was on moderate degree based on the ICC value (ICC=0.781, P<0.01) and had positive correlation (r=0.803, P<0.01). CBBCT?pathology concordance was found in 71 lesions, and discordance in 14 lesions. The factors of family history, symptom, pathology type, molecular subtypes, histological grade, surrounding fat invasion, lymphatic invasion, axillary lymph node metastasis, HER?2 positive and Ki?67 high expression had no significant difference between two groups. ER or PR positive had significant difference, suggesting that the accuracy of evaluation on ER or PR negative lesions could be reduced. The cut?off value of ROC curve between tumor size and CBBCT?pathology discordance was 2.08 cm, and the area under curve was 0.70. In 85 lesions. 66 of 75 mass lesions and 5 of 10 non?mass lesions were consistent. The lesion type had significant difference between two groups (χ2=6.705, P=0.010), which suggested the CBBCT evaluation on non?mass could have discrepancy with pathology. Conclusion CBBCT has high accuracy on tumor size evaluation on invasive carcinoma. ER or PR negative, large lesions or non?tumor lesions should be alert to the impact of CBBCT?pathology discordance before surgery which may cause the alteration of surgical protocols.

Comparison of the diagnostic efficiency in breast malignancy between cone beam breast CT and mammography in dense breast / 中华肿瘤杂志

Objective@#To compare the diagnostic efficiency of lesion in dense breast between cone beam breast computer tomography (CBBCT) and mammography.@*Methods@#From May 2012 to August 2014, 160 patients with 165 breasts who underwent mammography and CBBCT examinations were included in this study. The diagnostic results of CBBCT and mammography were reviewed and compared with pathological results.@*Results@#In the 165 breast, 24 were dense breasts and 141 were dense breasts. The diagnostic results were similar in 109 lesions, but different in 56 lesions. According to the analysis of the 165 breasts using receiver operation characteristics (ROC) curve, the area under the ROC curves (AUC) of CBBCT and mammography were 0.923 (95%CI: 0.878-0.967, P<0.05) and 0.959 (95%CI: 0.926-0.992, P<0.05), respectively. With Breast Imaging-Reporting and Data System (BI-RADS) 4b as the critical value, the sensitivity and specificity were 70.0% and 98.7% using mammography, and 83.3% and 97.3% using CBBCT, respectively. The AUC of CBBCT and mammography of the 141 dense breasts was 0.919(95%CI: 0.868-0.969, P<0.05) and 0.973(95%CI: 0.947-0.999, P<0.05), respectively. With BI-RADS 4b as the critical value, the sensitivity and specificity were 69.0% and 98.6% by mammography, and 83.1% and 98.6% by CBBCT, respectively.@*Conclusions@#CBBCT showed higher sensitivity and specificity in the diagnosis of breast malignant tumors compared to mammography. It is expected to be applied to breast cancer detection in the future, especially in dense breast.

Reliability of breast density estimation based on cone beam breast CT / 中国肿瘤临床

Objective:To investigate the accuracy of a threshold-based segmentation method based on cone beam breast CT(CBBCT) images in breast density measurement,and its value for breast-type classification and breast cancer screening.Methods:A retrospec-tive analysis of 195 patients who had undergone CBBCT examination at Tianjin Medical University Cancer Institute and Hospital be-tween May 2012 and August 2014 was performed.A total of 64 breasts were analyzed.On the basis of the classification criteria for breast density in BI-RADS,they were classified into four types and the majority report was reported.Breast density was measured by the threshold-based segmentation method based on CBBCT images and corrected manually to obtain the corrected breast density.A month later,the procedure was repeated.Intra-class correlation coefficients(ICCs)were used to compare the intra-observer and inter-observer consistencies of threshold-based segmentation and manually corrected breast density measurement results for non-dense and dense breasts.Results:For threshold-based segmentation measurements the intra-observer and inter-observer ICC values were 0.0.9624(95% CI:0.9388~0.9770)and 0.9666(95% CI:0.9500~0.9785).For manually corrected measurements,the intra-observer and inter-observer ICC values were 0.9750 (95% CI: 0.9592~0.9847) and 0.9775 (95% CI: 0.9661~0.9855). The ICC between the threshold-based segmentation method and manual correction was 0.9962 (95% CI: 0.9983~0.9977). The ICC values of threshold-based and manually corrected measurement in non-dense and dense breasts were 0.9497(95% CI:0.7072-0.9914)and 0.9983(95% CI:0.9971-0.9990),respectively.Conclusions:The threshold-based segmentation method based on CBBCT is a reliable and accurate com-puter-aided method of measuring breast density.It is expected to be applied in large-scale screening of breast cancer and to provide more information for predicting the risk of breast cancer.