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Classification of breast masses in greyscale ultrasound images is undertaken using a multiparameter approach. Five parameters reflecting the non-Rayleigh nature of the backscattered echo were used. These parameters, based mostly on the Nakagami and K distributions, were extracted from the envelope of the echoes at the site, boundary, spiculated region and shadow of the mass. They were combined to create a linear discriminant. The performance of this discriminant for the classification of breast masses was studied using a data set consisting of 70 benign and 29 malignant cases. The Az value for the discriminant was 0.96 +/- 0.02, showing great promise in the classification of masses into benign and malignant ones. The discriminant was combined with the level of suspicion values of the radiologist leading to an Az value of 0.97 +/- 0.014. The parameters used here can be calculated with minimal clinical intervention, so the method proposed here may therefore be easily implemented in an automated fashion. These results also support the recent reports suggesting that ultrasound may help as an adjunct to mammography in breast cancer diagnostics to enhance the classification of breast masses.

Breast cancer diagnosis through ultrasound tissue characterization was studied using receiver operating characteristic (ROC) analysis of combinations of acoustic features, patient age, and radiological findings. A feature fusion method was devised that operates even if only partial diagnostic data are available. The ROC methodology uses ordinal dominance theory and bootstrap resampling to evaluate A(z) and confidence intervals in simple as well as paired data analyses. The combined diagnostic feature had an A(z) of 0.96 with a confidence interval of at a significance level of 0.05. The combined features show statistically significant improvement over prebiopsy radiological findings. These results indicate that ultrasound tissue characterization, in combination with patient record and clinical findings, may greatly reduce the need to perform biopsies of benign breast lesions.

BackgroundDespite dosimetric benefits of volumetric modulated arc therapy (VMAT) in breast cancer patients with implant reconstruction receiving regional nodal irradiation (RNI), low dose to the thoracic structures remains a concern. Our goal was to report dosimetric effects of adding deep inspiration breath hold (DIBH) to VMAT in left-sided breast cancer patients with tissue expander (TE)/permanent implant (PI) reconstruction receiving RNI.MethodsTen consecutive breast cancer patients with unilateral or bilateral TE/PI reconstruction who were treated with a combination of VMAT and DIBH to the left reconstructed chest wall and regional nodes were prospectively identified. Free breathing (FB) and DIBH CT scans were acquired for each patient. VMAT plans for the same arc geometry were compared for FB versus DIBH. Prescription dose was 50 Gy in 25 fractions. Dosimetric differences were tested for statistical significance.ResultsFor comparable coverage and target dose homogeneity, the mean dose to the heart reduced on average by 2.9 Gy (8.2 to 5.3 Gy), with the addition of DIBH (p < 0.05). The maximum dose to the left anterior descending (LAD) artery was reduced by 9.9 Gy (p < 0.05), which related closely to the reduction in the maximum heart dose (9.4 Gy). V05 Gy to the heart, ipsilateral lung, contralateral lung and total lung (p < 0.05) decreased on average by 29.6%, 5.8%, 15.4% and 10.8% respectively. No significant differences were seen in the ipsilateral lung V20 Gy or mean dose as well as in the mean contralateral breast/implant dose. However, V04 Gy and V03 Gy of the contralateral breast/implant were respectively reduced by 13.2% and 18.3% using DIBH (p < 0.05).ConclusionCombination of VMAT and DIBH showed significant dosimetric gains for low dose to the heart, lungs and contralateral breast/implant. Not surprisingly, the mean and maximum dose to the heart and to the LAD were also reduced. DIBH should be considered with the use of VMAT in breast cancer patients with implant reconstructions receiving RNI.

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