Yini Huang

Introduction: Preoperatively distinguishing pure ductal carcinoma in situ (DCIS) from upstaged DCIS is important for deciding optimal surgical strategies. However, it is hard to preoperatively predict the upstaging of biopsy‐proven DCIS. This study aims to develop an effective radiomics model for predicting the upstaging of DCIS based on super‐resolution (SR) ultrasound images. Methods: In this multicentre retrospective study, patients with biopsy‐proven DCIS who underwent ultrasound examination were included. A super‐resolution reconstruction algorithm was used to enhance the resolution of original high resolution (HR) ultrasound images and obtain SR images. Pyradiomics was used for feature extraction. The selected HR radiomics features and SR radiomics features were combined with clinical features to construct the HR fusion model and SR fusion model, respectively. The area under the receiver operating characteristic curve (AUC) of the models and radiologists was analyzed and compared by the Delong test. Results: A total of 681 women (median age, 47 years; interquartile range, 42–54) with 681 biopsy‐proven DCIS lesions were included, with 422 lesions in the training set, 106 lesions in the validation set, and 153 lesions in the external test set. The SR Fusion model achieved an AUC of 0.819 (0.732–0.887) in the validation set and 0.800 (95% CI 0.728–0.860) in the external test set. It outperformed the radiologists (AUC = 0.603–0.627; p < 0.001) in the validation set. Additionally, it surpassed the clinical model (AUC = 0.682, 95% CI 0.602–0.755; p = 0.02) and the HR Fusion model (AUC = 0.724, 95% CI 0.646–0.793; p = 0.03) in the external test set. Conclusion: The SR Fusion model integrating SR features and clinical features can effectively predict the upstaging of DCIS.

Purpose To investigate the feasibility of post-vascular phase imaging on contrast-enhanced ultrasound (CEUS) with perfluorobutane for diagnosing axillary lymph node metastasis (ALNM) and prediction of metastatic burden in early-stage breast cancer. Material and methods The prospective study enrolled patients with early-stage invasive breast cancer and non-palpable axillary lymph node (ALN) from November 2022 to June 2023. All participants of the entire cohort were scheduled for both conventional ultrasound (US) and CEUS with perfluorobutane examination immediately followed by US-guided core-needle biopsy basing on the guidance of CEUS result. The main features of US, vascular phase imaging, and post-vascular phase imaging were selected according to comparison between positive and negative ALNM using the Chi-square or Fisher exact test, of which diagnostic performance of different combinations on ALNM was calculated and compared for determining optimal diagnostic criteria. As for burden analysis, the predictive power of number of lymph nodes with post-vascular defect for metastatic burden was also estimated among surgery cohort who underwent axillary surgery without neoadjuvant chemotherapy. Results A total of 146 female patients (median age, 51 [42–58] years) with 146 target ALNs (median size, 16 [13–21] mm; 82 positive ALNM and 64 negative ALNM) were enrolled in the entire cohort. The post-vascular phase finding “post-vascular defect” had an AUC of 0.92 (95% CI 0.86, 0.97) and sensitivity of 99% (95% CI 93%, 100%) with a negative predictive value of 98% (95% CI 90%, 100%) for the diagnosis of positive ALNM. Overall, the post-vascular phase finding performed better than that of US (AUC, 0.77, 95% CI 0.69, 0.85, P < 0.001) and vascular phase findings (AUC, 0.85, 95% CI 0.78, 0.91, P < 0.001). As for burden analysis among surgery cohort with 89 patients, the number of lymph nodes with post-vascular defect was highly predictive of metastatic burden, with AUC of 0.90 (95% CI 0.82, 0.97) for predicting disease-free axilla and AUC of 0.75 (95% CI 0.60, 0.89) for discriminating between low and heavy metastatic burden. Conclusion Post-vascular phase imaging on CEUS with perfluorobutane demonstrated good performance for preoperatively assessing the ALN status in patients with early-stage invasive breast cancer. Chinese Clinical Trial Registry No. ChiCTR2400080297.

Objective: To evaluate the correlation between elastic heterogeneity (EH) and lymphovascular invasion (LVI) in breast cancers and assess the clinical value of using EH to predict LVI pre-operatively. Methods: This retrospective study consisted of 376 patients with breast cancers that had undergone shear wave elastography (SWE) with virtual touch tissue imaging quantification between June 2017 and June 2018. The EH was determined as the difference between the averaged three highest and three lowest shear wave value. Clinicalpathological parameters including histological type and grades, LVI, axillary lymph node status and molecular markers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 and Ki-67) were reviewed and recorded. Relationship EH and clinicalpathological parameters was investigated respectively. The diagnostic performance of EH in distinguishing LVI or not was analyzed. Results: At multivariate regression analysis, only EH (p = 0.017) was positively correlated with LVI in all tumors. EH (p = 0.003) and Ki-67 (p = 0.025) were positively correlated with LVI in tumors ≤ 2 cm. None of clinicalpathological parameters were correlated with LVI in tumors > 2 cm (p > 0.05 for all). Using EH to predict LVI in tumors ≤ 2 cm, the sensitivity and negative predictive value were 93 and 89% respectively. Conclusion: EH has the potential to be served as an imaging biomarker to predict LVI in breast cancer especially for tumors ≤ 2 cm. Advances in knowledge: There was no association between LVI and other most commonly used elastic features such as SWV_mean and SWV_max. Elastic heterogeneity is an independent predictor of LVI, so it can provide additional prognostic information for routine preoperative breast cancer assessment. For tumors ≤ 2cm, using EH value higher than 1.36 m/s to predict LVI involvement, the sensitivity and negative predictive value can reach to 93% and 89%, respectively, suggesting that breast cancer with negative EH value was more likely to be absent of LVI.

This study was aimed to assess whether ultrasonic spectrum analysis of radiofrequency (RF) time series using a clinical ultrasound system allows for early differentiating between the chemotherapy responders and nonresponders in human breast cancer xenografts that imitate clinical responding and nonresponding tumors. Clinically responding (n = 20; MCF-7) and nonresponding (n = 20; MBA-MD-231) breast cancer xenografts were established in 40 nude mice. Ten mice from each group received either chemotherapy (adriamycin, 4 mg/kg) or saline as controls. Each tumor was imaged longitudinally with a clinical ultrasound scanner at baseline (day 0) and subsequently on days 2, 4, 6, 8 and 12 following treatment, and the corresponding RF time-series data were collected. Changes in six RF time-series parameters (slope, intercept, S1, S2, S3 and S4) were compared with the measurement of the tumor cell density, and their differential performances of the treatment response were analyzed. Adriamycin significantly inhibited tumor growth and decreased the cancer cell density in responders (P < 0.001) but not in nonresponders (P > 0.05). Fold changes of slope were significantly increased in responders two days after adriamycin treatment (P = 0.002), but not in nonresponders (P > 0.05). Early changes in slope on day 2 could differentiate the treatment response in 100% of both responders (95% CI, 62.9–100.0%) and nonresponders (95% CI, 88.4–100%). Ultrasonic RF time series allowed for the monitoring of the tumor response to chemotherapy and could further serve as biomarkers for early differentiating between the treatment responders and nonresponders.