Nanodroplet-Based Super-Resolution Ultrasound Localization Microscopy.

Over the past decade, super-resolution ultrasound localization microscopy (SR-ULM) has revolutionized ultrasound imaging with its capability to resolve the microvascular structures below the ultrasound diffraction limit. The introduction of this imaging technique enables the visualization, quantification, and characterization of tissue microvasculature. The early implementations of SR-ULM utilize microbubbles (MBs) that require a long image acquisition time due to the requirement of capturing sparsely isolated microbubble signals. The next-generation SR-ULM employs nanodroplets that have the potential to significantly reduce the image acquisition time without sacrificing the resolution. This review discusses various nanodroplet-based ultrasound localization microscopy techniques and their corresponding imaging mechanisms. A summary is given on the preclinical applications of SR-ULM with nanodroplets, and the challenges in the clinical translation of nanodroplet-based SR-ULM are presented while discussing the future perspectives. In conclusion, ultrasound localization microscopy is a promising microvasculature imaging technology that can provide new diagnostic and prognostic information for a wide range of pathologies, such as cancer, heart conditions, and autoimmune diseases, and enable personalized treatment monitoring at a microlevel.

The feasibility and satisfaction study of 5G-based robotic teleultrasound diagnostic system in health check-ups.

Objective: Regular check-up with ultrasound in underserved rural and/or remote areas is hampered due to the limited availability of sonologists and ultrasound devices. This study aimed to assess the feasibility and satisfaction of health check-ups with a 5G-based robotic teleultrasound diagnostic system. Methods: In this prospective study, sonologists from two hospitals manipulated the telerobotic ultrasound system to perform teleultrasound check-ups of the liver, gallbladder, pancreas, spleen, kidneys, bladder, prostate (male), uterus and ovaries (female) for the subjects. The feasibility and satisfaction of health check-ups with a 5G-based robotic teleultrasound diagnostic system were evaluated in terms of examination results, examination duration, and satisfaction questionnaire survey. Results: A total of 546 subjects were included with the most frequently diagnosed being abdominal disorders (n = 343) and male reproductive illnesses (n = 97), of which fatty liver (n = 204) and prostatic calcification (n = 54) were the most. The median teleultrasound examination duration (interquartile range) for men and women was 9 (9-11) min and 9 (7-11) min (p = 0.236), respectively. All the subjects were satisfied with this new type of telerobotic ultrasound check-ups and 96% reported no fear of the robotic arm during the examination. Conclusion: The 5G-based teleultrasound robotic diagnostic system in health check-ups is feasible and satisfactory, indicating that this teleultrasound robot system may have significant application value in underserved rural and/or remote areas to mitigate disparity in achieving health equity.

High-Indexed Intermetallic Pt3Sn Nanozymes with High Activity and Specificity for Sensitive Immunoassay.

Great efforts have been made to expand the application fields of nanozymes, which puts forward requirements for nanozymes with both superior catalytic activity and specificity. Herein, we reported the high-indexed intermetallic Pt3Sn (H-Pt3Sn) with high peroxidase-like activity and specificity. The resultant H-Pt3Sn exhibits a specific activity of 345.3 U/mg, which is 1.82 times higher than Pt. Moreover, H-Pt3Sn possesses negligible oxidase-like and catalase-like activities, achieving superior catalytic specificity toward H2O2 activation. Experimental and theoretical calculations reveal both the splitting energy for adsorbed H2O2 and the energy barrier for the rate-determining step of H-Pt3Sn are significantly decreased compared with Pt3Sn and Pt. Finally, a nanozyme-linked immunosorbent assay is successfully developed, achieving the sensitive and accurate colorimetric detection for carcinoembryonic antigen with a low detection limit of 0.49 pg/mL and showing practical feasibility in serum sample detection.

Ultrasound super-resolution imaging for the differential diagnosis of thyroid nodules: A pilot study.

Objective: Ultrasound imaging provides a fast and safe examination of thyroid nodules. Recently, the introduction of super-resolution imaging technique shows the capability of breaking the Ultrasound diffraction limit in imaging the micro-vessels. The aim of this study was to evaluate its feasibility and value for the differentiation of thyroid nodules. Methods: In this study, B-mode, contrast-enhanced ultrasound, and color Doppler flow imaging examinations were performed on thyroid nodules in 24 patients. Super-resolution imaging was performed to visualize the microvasculature with finer details. Microvascular flow rate (MFR) and micro-vessel density (MVD) within thyroid nodules were computed. The MFR and MVD were used to differentiate the benign and malignant thyroid nodules with pathological results as a gold standard. Results: Super-resolution imaging (SRI) technique can be successfully applied on human thyroid nodules to visualize the microvasculature with finer details and obtain the useful clinical information MVD and MFR to help differential diagnosis. The results suggested that the mean value of the MFR within benign thyroid nodule was 16.76 ± 6.82 mm/s whereas that within malignant thyroid was 9.86 ± 4.54 mm/s. The mean value of the MVD within benign thyroid was 0.78 while the value for malignant thyroid region was 0.59. MFR and MVD within the benign thyroid nodules were significantly higher than those within the malignant thyroid nodules respectively (p < 0.01). Conclusions: This study demonstrates the feasibility of ultrasound super-resolution imaging to show micro-vessels of human thyroid nodules via a clinical ultrasound platform. The important imaging markers, such as MVD and MFR, can be derived from SRI to provide more useful clinical information. It has the potential to be a new tool for aiding differential diagnosis of thyroid nodules.

Ultrasound super-resolution imaging for differential diagnosis of breast masses.

Objective: Ultrasound imaging has been widely used in breast cancer screening. Recently, ultrasound super-resolution imaging (SRI) has shown the capability to break the diffraction limit to display microvasculature. However, the application of SRI on differential diagnosis of breast masses remains unknown. Therefore, this study aims to evaluate the feasibility and clinical value of SRI for visualizing microvasculature and differential diagnosis of breast masses. Methods: B mode, color-Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS) images of 46 patients were collected respectively. SRI were generated by localizations of each possible contrast signals. Micro-vessel density (MVD) and microvascular flow rate (MFR) were calculated from SRI and time to peak (TTP), peak intensity (PI) and area under the curve (AUC) were obtained by quantitative analysis of CEUS images respectively. Pathological results were considered as the gold standard. Independent chi-square test and multivariate logistic regression analysis were performed using these parameters to examine the correlation. Results: The results showed that SRI technique could be successfully applied on breast masses and display microvasculature at a significantly higher resolution than the conventional CDFI and CEUS images. The results showed that the PI, AUC, MVD and MFR of malignant breast masses were significantly higher than those of benign breast masses, while TTP was significantly lower than that of benign breast masses. Among all five parameters, MVD showed the highest positive correlation with the malignancy of breast masses. Conclusions: SRI is able to successfully display the microvasculature of breast masses. Compared with CDFI and CEUS, SRI can provide additional morphological and functional information for breast masses. MVD has a great potential in assisting the differential diagnosis of breast masses as an important imaging marker.

Ultrasound Molecular Imaging and Its Applications in Cancer Diagnosis and Therapy.

Ultrasound imaging is regarded as a highly sensitive imaging modality used in routine clinical examinations. Over the last several decades, ultrasound contrast agents have been widely applied in ultrasound molecular cancer imaging to improve the detection, characterization, and quantification of tumors. To date, a few new potential preclinical and clinical applications regarding ultrasound molecular cancer imaging are being investigated. This review presents an overview of the various kinds of ultrasound contrast agents employed in ultrasound molecular imaging and advanced imaging techniques using these contrast agents. Additionally, we discuss the recent enormous development of ultrasound contrast agents in the relevant preclinical and clinical applications, highlight the recent challenges which need to be overcome to accelerate the clinical translation, and discuss the future perspective of ultrasound molecular cancer imaging using various contrast agents. As a highly promising and valuable tumor-specific imaging technique, it is believed that ultrasound molecular imaging will pave an accurate and efficient way for cancer diagnosis.

Ultrathin Ruthenium Nanosheets with Crystallinity-Modulated Peroxidase-like Activity for Protein Discrimination.

Noble-metal-based nanozymes have attracted great interest as enzyme mimics because of their unique properties. To modulate the performance and meet the requirements of practical biosensing applications, phase engineering is promising for the design of novel noble-metal-based nanomaterials. Herein, a simple salt-assist strategy was employed for the synthesis of Ru nanosheets (NSs) with the controlled crystalline degree. The crystalline degree plays a significant role in tuning peroxidase-like activity by optimizing the affinity toward the catalytic substrate. Furthermore, the inhibition effect of mercapto molecules on the peroxidase-like activity of Ru NSs was investigated. As a proof-of-concept, the Ru NSs-based colorimetric sensing arrays were developed to distinguish mercapto molecules, and five model molecules were well classified according to the different inhibition effects. Given the complexity of practical conditions, the sensing array was further applied to discriminate proteins possessing rich mercapto groups. This work not only provides an effective strategy for the design of highly active nanozymes but also achieves promising sensing arrays for practical needs.

Artificial Intelligence in Medical Imaging of the Breast.

Artificial intelligence (AI) has invaded our daily lives, and in the last decade, there have been very promising applications of AI in the field of medicine, including medical imaging, in vitro diagnosis, intelligent rehabilitation, and prognosis. Breast cancer is one of the common malignant tumors in women and seriously threatens women's physical and mental health. Early screening for breast cancer via mammography, ultrasound and magnetic resonance imaging (MRI) can significantly improve the prognosis of patients. AI has shown excellent performance in image recognition tasks and has been widely studied in breast cancer screening. This paper introduces the background of AI and its application in breast medical imaging (mammography, ultrasound and MRI), such as in the identification, segmentation and classification of lesions; breast density assessment; and breast cancer risk assessment. In addition, we also discuss the challenges and future perspectives of the application of AI in medical imaging of the breast.

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.

Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve increased accuracy in diagnosis with higher efficiency. Purpose To determine the feasibility of using a DL approach to predict clinically negative axillary lymph node metastasis from US images in patients with primary breast cancer. Materials and Methods A data set of US images in patients with primary breast cancer with clinically negative axillary lymph nodes from Tongji Hospital (974 imaging studies from 2016 to 2018, 756 patients) and an independent test set from Hubei Cancer Hospital (81 imaging studies from 2018 to 2019, 78 patients) were collected. Axillary lymph node status was confirmed with pathologic examination. Three different convolutional neural networks (CNNs) of Inception V3, Inception-ResNet V2, and ResNet-101 architectures were trained on 90% of the Tongji Hospital data set and tested on the remaining 10%, as well as on the independent test set. The performance of the models was compared with that of five radiologists. The models' performance was analyzed in terms of accuracy, sensitivity, specificity, receiver operating characteristic curves, areas under the receiver operating characteristic curve (AUCs), and heat maps. Results The best-performing CNN model, Inception V3, achieved an AUC of 0.89 (95% confidence interval [CI]: 0.83, 0.95) in the prediction of the final clinical diagnosis of axillary lymph node metastasis in the independent test set. The model achieved 85% sensitivity (35 of 41 images; 95% CI: 70%, 94%) and 73% specificity (29 of 40 images; 95% CI: 56%, 85%), and the radiologists achieved 73% sensitivity (30 of 41 images; 95% CI: 57%, 85%; P = .17) and 63% specificity (25 of 40 images; 95% CI: 46%, 77%; P = .34). Conclusion Using US images from patients with primary breast cancer, deep learning models can effectively predict clinically negative axillary lymph node metastasis. Artificial intelligence may provide an early diagnostic strategy for lymph node metastasis in patients with breast cancer with clinically negative lymph nodes. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Bae in this issue.