Intra-tumor flow index can predict the malignant potential of breast tumor: dependent on age and volume

Modulation of mammary tumor vascularization by mast cells: Ultrasonographic and histopathological approaches

AIMS

The inhibition of mast cells' degranulation may be an approach to prevent the formation of new vessels during the mammary carcinogenesis.

MATERIALS AND METHODS

Female Sprague-Dawley rats were randomly divided into five experimental groups. Mammary tumors were induced by intraperitoneal injection of N-methyl-N-nitrosourea (MNU). Animals from group II were treated with ketotifen for 18weeks immediately after the MNU administration, while animals from group III only received the ketotifen after the development of the first mammary tumor. Mammary tumors vascularization was assessed by ultrasonography (Doppler, B Flow and contrast-enhanced ultrasound) and immunohistochemistry (vascular endothelial growth factor-A).

KEY FINDINGS AND SIGNIFICANCE

Similar to what occurs in women with breast cancer, the majority of MNU-induced mammary tumors exhibited a centripetal enhancement order of the contrast agent, clear margin and heterogeneous enhancement. Ultrasonographic and immunohistochemical data suggest that the inhibition of mast cells' degranulation did not change the mammary tumors vascularization.

Influence of Pulse Repetition Frequency on 3-D Power Doppler Quantification

Three-dimensional power Doppler quantification has limited application because of its high dependency on attenuation. The purpose of the study described here was to assess if different degrees of attenuation, depending on pulse repetition frequency (PRF) adjustment, alter 3-D power Doppler quantification in a region of 100% moving blood when using vascularization index, flow index and vascularization flow index (VFI). A cubic-shaped gelatin phantom with a 1.8-mm-internal-diameter silicon tube was used. The tube, placed at 45° to the phantom's surface, was filled with blood-mimicking fluid with as constant maximum velocity of 30 cm/s. Two different attenuation blocks (low and high attenuation) were alternatively placed between the phantom and the transvaginal transducer. One single observer acquired 10 data sets for each PRF level from 0.3 to 7.5 kHz, using the high- and low-attenuation blocks, for a total of 200 3-D power Doppler data sets. We assessed VFI from 1.5-mm-diameter spherical samples, virtually placed inside the tube, always at the same position. No difference was noted between high- and low-attenuation VFI values when using a PRF of 0.3 kHz. As PRF increased, it was observed that VFI quantification progressively differed between low and high attenuation. Also, a slope on VFI values for both high- and low-attenuation models could be observed when increasing PRF, particularly above 4.0 kHz. We concluded that PRF adjustment is very relevant when using VFI to quantify 3-D power Doppler signal.

Role of 3D power Doppler ultrasound in the further characterization of suspicious breast masses

PURPOSE

To investigate effectiveness of vascular indices obtained with 3D power Doppler ultrasound in the further characterization of breast masses and prevention of unnecessary biopsies.

MATERIALS AND METHODS

Between April 2013 and March 2014, 109 patients (age range, 17-85 years; mean age, 47 years) with 117 radiologically or clinically suspicious breast masses were prospectively evaluated with 3DPDUS before biopsy. Mass volume (MV), vascularization index (VI), flow index (FI) and vascularization flow index (VFI) were calculated using Virtual Organ Computer-aided Analysis (VOCAL) software and they were correlated with the final diagnosis. Cutoff values of vascular indices were determinated and diagnostic efficacy was calculated with receiver operating curve (ROC) analysis.

RESULTS

All vascular indices, age of patients and tumor volume were significantly lower in benign masses compared with malignant ones (p<0.001). AUCs were 0.872, 0.867 and 0.789 for VI, VFI and FI, respectively. The diagnostic efficacy of VI (for cutoff 1.1; 83% sensitivity, 82% specificity and 82% accuracy) and VFI (for cutoff 0.4; 80% sensitivity, 83% specificity and 80% accuracy) were significantly higher than FI (for cutoff 33,9; 73% sensitivity, 69% specificity and 71% accuracy). It was found that with the use of vascular indices of 3DPDUS in the further characterization of suspicious breast masses between 24% to 37% of unnecessary biopsies could have been avoided.

CONCLUSION

The vascular indices obtained with 3DPDUS seem reliable in the further characterization of suspicious breast masses and might be used to decrease unnecessary biopsies.

Diagnosis of solid breast tumors using vessel analysis in three-dimensional power Doppler ultrasound images

This study aims to evaluate whether the distribution of vessels inside and adjacent to tumor region at three-dimensional (3-D) power Doppler ultrasonography (US) can be used for the differentiation of benign and malignant breast tumors. 3-D power Doppler US images of 113 solid breast masses (60 benign and 53 malignant) were used in this study. Blood vessels within and adjacent to tumor were estimated individually in 3-D power Doppler US images for differential diagnosis. Six features including volume of vessels, vascularity index, volume of tumor, vascularity index in tumor, vascularity index in normal tissue, and vascularity index in surrounding region of tumor within 2 cm were evaluated. Neural network was then used to classify tumors by using these vascular features. The receiver operating characteristic (ROC) curve analysis and Student's t test were used to estimate the performance. All the six proposed vascular features are statistically significant (p < 0.001) for classifying the breast tumors as benign or malignant. The A Z (area under ROC curve) values for the classification result were 0.9138. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the diagnosis performance based on all six proposed features were 82.30 (93/113), 86.79 (46/53), 78.33 (47/60), 77.97 (46/59), and 87.04 % (47/54), respectively. The p value of A Z values between the proposed method and conventional vascularity index method using z test was 0.04.

Vascular morphology and tortuosity analysis of breast tumor inside and outside contour by 3-D power Doppler ultrasound

This study aimed to evaluate morphologic and tortuous features of vessels inside and outside the tumor region on three-dimensional power Doppler ultrasonography (PDUS) in 113 breast mass lesions, including 60 benign and 53 malignant tumors. Compared with benign lesions, malignant breast lesions had significantly larger values of vascular morphologic and tortuous features and larger tumor sizes. The receiver operating characteristic curve analysis and Student's t-test were used to estimate the performance of a proposed classification system using 13 vascular features and tumor size selected by the neural network. Accuracy, sensitivity, specificity, positive predictive value, negative predictive value and the A(Z) value of the diagnosis performance based on 14 features were 89.38% (101/113), 84.91% (45/53), 93.33% (56/60), 91.84% (45/49), 87.50% (56/64) and 0.9188, respectively. The three-dimensional PDUS morphologic and tortuous characteristics of blood vessels inside and outside breast mass lesions can be effectively used to classify benign and malignant tumors.

Computer-aided diagnosis for breast tumors by using vascularization of 3-D power Doppler ultrasound

This study assessed the accuracy of three-dimensional (3-D) power Doppler ultrasound in differentiating between benign and malignant breast tumors by using a support vector machine (SVM). A 3-D power Doppler ultrasonography was performed on 164 patients with 86 benign and 78 malignant breast tumors. The volume-of-interest (VOI) in 3-D ultrasound images was automatically generated from three rectangular regions-of-interest (ROI). The vascularization index (VI), flow index (FI) and vascularization-flow index (VFI) on 3-D power-Doppler ultrasound images were evaluated for the entire volume area, computer extracted VOI area and the area outside the VOI. Furthermore, patient's age and VOI volume were also applied for breast tumor classifications. Each ultrasonography in this study was classified as benign or malignant based on the features using the SVM model. All the tumors were sampled using k-fold cross-validation (k=10) to evaluate the diagnostic performance with receiver operating characteristic (ROC) curves. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of SVM for classifying malignancies were 94%, 69%, 73%, 92% and 81%, respectively. The classification performance in terms of Az value for the ROC curve of the features derived from 3-D power Doppler is 0.91. This study indicates that combining 3-D power Doppler vascularity with patient's age and tumor size offers a good method for differentiating benign and malignant breast tumors.

Comparative analysis of logistic regression, support vector machine and artificial neural network for the differential diagnosis of benign and malignant solid breast tumors by the use of three-dimensional power Doppler imaging

Objective

Logistic regression analysis (LRA), Support Vector Machine (SVM) and a neural network (NN) are commonly used statistical models in computer-aided diagnostic (CAD) systems for breast ultrasonography (US). The aim of this study was to clarify the diagnostic ability of the use of these statistical models for future applications of CAD systems, such as three-dimensional (3D) power Doppler imaging, vascularity evaluation and the differentiation of a solid mass.

Materials and Methods

A database that contained 3D power Doppler imaging pairs of non-harmonic and tissue harmonic images for 97 benign and 86 malignant solid tumors was utilized. The virtual organ computer-aided analysis-imaging program was used to analyze the stored volumes of the 183 solid breast tumors. LRA, an SVM and NN were employed in comparative analyses for the characterization of benign and malignant solid breast masses from the database.

Results

The values of area under receiver operating characteristic (ROC) curve, referred to as Az values for the use of non-harmonic 3D power Doppler US with LRA, SVM and NN were 0.9341, 0.9185 and 0.9086, respectively. The Az values for the use of harmonic 3D power Doppler US with LRA, SVM and NN were 0.9286, 0.8979 and 0.9009, respectively. The Az values of six ROC curves for the use of LRA, SVM and NN for non-harmonic or harmonic 3D power Doppler imaging were similar.

Conclusion

The diagnostic performances of these three models (LRA, SVM and NN) are not different as demonstrated by ROC curve analysis. Depending on user emphasis for the use of ROC curve findings, the use of LRA appears to provide better sensitivity as compared to the other statistical models.