| Part 1 Comparative Analysis of Contrast-Enhanced Cone Beam Breast CT,MRI and Digital Mammography in the Diagnosis of Non-mass Enhancement Breast LesionsObjective: To investigate the difference between contrast enhanced cone beam breast CT(CE-CBBCT)and breast MRI in visualizing the enhancement distribution and internal enhancement characteristics of non-mass enhancement lesions(NMELs).To investigate whether the digital mammography(DM)description on the distribution and calcification characteristics was also applicable to CBBCT.And to compare the accuracy of CBBCT,MRI and DM in the measurement of preoperative tumor sizes of NMELs.Methods: In this retrospective study,the study cohort included 84 patients acquired between July 2019 and December 2019 with histopathologic confirmed NMEL findings.1.48 patients in the cohort underwent both CE-CBBCT and MRI.The enhancement distribution type and internal enhancement characteristics of NMELs were compared between CE-CBBCT and MRI images.2.26 patients in the cohort had NMELs with calcifications and underwent both DM and CECBBCT.The calcification distribution morphology and characteristics were compared between DM and CE-CBBCT images.3.37 patients in the cohort underwent all three modalities(CE-CBBCT,DM,and MRI).The sizes of NMELs measured from the three imaging modalities were compared using surgical pathology measurements as gold standard.The intergroup relationship was evaluated with ?2 test.The intergroup agreement was evaluated with Kappa coefficient.Spearman coefficient was used to analyze the correlation between the sizes measured from images and pathological specimens.Results: 1.In 48 patients with CE-CBBCT and MRI,the compliance rate of enhancement distribution and internal enhancement features was 89.58%(Kappa= 0.847)and 87.50%(Kappa= 0.812).There was a very high degree of concordance among the two modalities,and the result was statistically significant(P< 0.001).2.In 26 patients with CBBCT and DM,the compliance rate of calcification distribution and calcification features was 84.62%(Kappa= 0.774)and 82.93%(Kappa= 0.769),there was a high degree of concordance among the two groups,and the result was statistically significant(P< 0.001).3.The maximum diameters of CBBCT,MRI,DM and pathology specimen were(4.60 ± 1.70)cm,(4.70 ± 2.12)cm,(5.75 ± 2.33)cm and(4.50 ± 2.12)cm,respectively.The sizes of three imaging methods were larger than pathological specimens.The correlation coefficients(r)between the three imaging methods and pathology were 0.941,0.846 and 0.609,respectively(P< 0.001),CBBCT had the highest correlation with pathology.Conclusion: BI-RADS-MRI can be used to effectively describe the CE-CBBCT enhancement distribution and internal enhancement features in NMELs.BIRADS-DM can be used to describe CE-CBBCT calcification distribution and morphology in NMELs.CE-CBBCT is more accurate than MRI and DM in evaluating the sizes of NMELs.Part 2 The Malignancy Characteristics of Non-mass Enhancement Lesions on Cone Beam Breast Computed TomographyObjective: To find characteristics of non-mass enhancement lesions(NMELs)on cone-beam breast computed tomography(CBBCT)and to identify the characteristics that distinguish malignant and benign lesions.Methods: CBBCT images of 84 NMELs(69 malignant and 15 benign)in 84 patients were analyzed.Internal enhancement distribution and features,calcification distribution and suspicious morphology,and enhancement ?HU were compared between postcontrast and precontrast scans in both malignant and benign lesions.SPSS 25.0 software was used to carry out univariate and multivariate binary Logistic analysis to establish a regression equation.Univariate analyses were applied to find the strongest indicators of malignancy.Logistic regression analysis was used to develop a fitting equation for the combined diagnostic model.Results: In the 84 NMELs,the indicators of malignancy were as follows: segmental enhancement distribution(P= 0.011,53.62% sensitivity,86.67% specificity,94.87% positive predictive value(PPV),and 28.89% negative predictive value(NPV)),clumped internal enhancement(P= 0.017,50.72% sensitivity,86.67% specificity,94.59% PPV,and 27.66% NPV),enhancement ?HU ?93.57 Hounsfield units(Hu)(P= 0.004,66.67% sensitivity,73.33% specificity,92.00% PPV,and 32.35% NPV),and NMELs with calcification(P= 0.002,36.23% sensitivity,20.00% specificity,82.14% PPV,and 67.57% NPV).The fitting equation for the combined diagnostic model was as follows: Logit(P)=-0.579+ 1.318× enhancement distribution+ 1.000× internal enhancement+ 1.539× enhancement ?HU + 1.641× NMELs type.The sensitivity,specificity,PPV,NPV,and area under the curve(AUC)were 95.65%,60.00%,91.70%,75.00%,and 0.843,respectively.Conclusion: Individual diagnostic criteria based on CBBCT characteristics(segmental enhancement distribution,clumped internal enhancement features,enhancement ?HU greater than 93.57 Hu,and NMELs with calcification)had high diagnostic efficiency;when combined,they had higher diagnostic efficiency.Part 3 Cone Beam Breast Computed Tomography Imaging Features on Non-mass Enhancement Breast Cancer: Correlation with Immunohistochemical FactorsObjective: The purpose of our study was to explore the relationship between cone beam breast computed tomography(CBBCT)imaging features and immunohistochemical(IHC)factors in non-mass enhancement(NME)breast cancer.The correlation between enhancement ?HU and IHC factors in NME breast cancer was also investigated.Methods: A total of 69 female patients with NME breast cancer were included.CBBCT features(internal enhancement distribution and pattern,calcification distribution and suspicious morphology,and tumor size)were compared with HER2 status.The relationship between enhancement ?HU and pathological grade,IHC factors(including estrogen receptor(ER),progesterone receptor(PR),HER2,and Ki67 index)and breast cancer subtypes(including luminal A,luminal B,triple negative and HER2-enriched)were also explored.Results: Clumped internal enhancement was related to HER2-positive tumors,and heterogeneous internal enhancement was related to HER2-negative tumors(P=0.004).Segmental calcification distribution was also linked to HER2-positive tumors,grouped calcification distribution was related to HER2-negative tumors(P =0.041).The sizes of HER2-positive tumors were larger than that of HER2-negative ones(4.78±1.88 cm us.3.47±1.85 cm,r=0.291,P =0.004).Segmental internal enhancement distribution was the common distribution pattern associated with both HER2-positive and HER2-negative tumors,and the difference between the two was not statistically significant(P =0.064).The difference between the two groups in calcification suspicious morphology was not statistically significant(P =0.878).PR positive,ER positive,HER2 positive,high Ki67,HER2-enriched subtype and high grade tumors demonstrated slightly higher contrast enhancement than other lesions,but,once again,the differences were not statistically significant(P>0.05).Conclusion: Clumped internal enhancement,segmental calcification distribution features,and larger tumor size on CBBCT were associated with HER2-positive NME breast cancer.These results suggest that CBBCT imaging features can play a role in predicting prognosis of patients with NME breast cancer. |
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