Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Lack of background parenchymal enhancement suppression at breast MRI during neoadjuvant chemotherapy may indicate inferior treatment response in hormone receptor–positive breast cancer. Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed ...

Invasive lobular carcinomas have an atypical clinical manifestation and imaging appearance, and mammographic, US, and MRI findings can help radiologists accurately assess tumor size and evaluate fo...

Ultrasound microbubbles are contrast agents used for diagnostic ultrasound imaging and as carriers for noninvasive payload delivery. Understanding the acoustic properties of individual microbubble formulations is important for optimizing the ultrasound imaging parameters for improved image contrast and efficient payload delivery. We report here a practical and simple optical tool for direct real-time characterization of ultrasound contrast microbubble dynamics based on light scattering. Fourier transforms of raw linear and nonlinear acoustic oscillations, and microbubble cavitations are directly recorded. Further, the power of this tool is demonstrated by comparing clinically relevant microbubble cycle-to-cycle dynamics and their corresponding Fourier transforms.