Unlocking the potential of bispecific ADCs for targeted cancer therapy.

Antibody-drug conjugates (ADCs) are biologically targeted drugs composed of antibodies and cytotoxic drugs connected by linkers. These innovative compounds enable precise drug delivery to tumor cells, minimizing harm to normal tissues and offering excellent prospects for cancer treatment. However, monoclonal antibody-based ADCs still present challenges, especially in terms of balancing efficacy and safety. Bispecific antibodies are alternatives to monoclonal antibodies and exhibit superior internalization and selectivity, producing ADCs with increased safety and therapeutic efficacy. In this review, we present available evidence and future prospects regarding the use of bispecific ADCs for cancer treatment, including a comprehensive overview of bispecific ADCs that are currently in clinical trials. We offer insights into the future development of bispecific ADCs to provide novel strategies for cancer treatment.

Anatomical Prior and Inter-Slice Consistency for Semi-Supervised Vertebral Structure Detection in 3D Ultrasound Volume.

Three-dimensional (3D) ultrasound imaging technique has been applied for scoliosis assessment, but the current assessment method only uses coronal projection images and cannot illustrate the 3D deformity and vertebra rotation. The vertebra detection is essential to reveal 3D spine information, but the detection task is challenging due to complex data and limited annotations. We propose VertMatch to detect vertebral structures in 3D ultrasound volume containing a detector and classifier. The detector network finds the potential positions of structures on transverse slice globally, and then the local patches are cropped based on detected positions. The classifier is used to distinguish whether the patches contain real vertebral structures and screen the predicted positions from the detector. VertMatch utilizes unlabeled data in a semi-supervised manner, and we develop two novel techniques for semi-supervised learning: 1) anatomical prior is used to acquire high-quality pseudo labels; 2) inter-slice consistency is used to utilize more unlabeled data by inputting multiple adjacent slices. Experimental results demonstrate that VertMatch can detect vertebra accurately in ultrasound volume and outperforms state-of-the-art methods. Moreover, VertMatch is also validated in automatic spinous process angle measurement on forty subjects with scoliosis, and the results illustrate that it can be a promising approach for the 3D assessment of scoliosis.

Recent progress in antibody-based therapeutics for triple-negative breast cancer.

INTRODUCTION: Triple-negative breast cancer (TNBC) is a subtype of severely aggressive breast cancer that lacks the expression of oestrogen receptor (ER), progesterone receptor and human epidermal growth factor receptor 2 (HER2) and is highly metastatic and related to a poor prognosis. Current standard treatments are still limited to systemic chemotherapy, radiotherapy, and surgical resection. More effective treatments are urgently needed. AREAS COVERED: The immunogenicity of TNBC has provided opportunities for the development of targeted immunotherapy. In this review, we focus on the recent development in antibody-based drug modalities, including angiogenesis inhibitors, immune checkpoint inhibitors, antibody-drug conjugates, immunoconjugates, T cell-redirecting bispecific antibodies and CAR-T cells, and their mechanisms of action in TNBC. EXPERT OPINION: At present, the treatment of TNBC is still a major challenge that needs to be addressed. Novel immunotherapies are promising opportunities for improving the management of this aggressive disease.

Improvement of 3-D Ultrasound Spine Imaging Technique Using Fast Reconstruction Algorithm.

Three-dimensional (3-D) freehand ultrasound (US) imaging has been applied to the investigation of spine deformity. However, it is a challenge for the current 3-D imaging reconstruction algorithms to achieve a balance between image quality and computation time. The objectives of this article are to implement a new fast reconstruction algorithm that can fulfill the request of immediate demonstration and processing for high-quality 3-D spine imaging, and to evaluate the reliability and accuracy of scoliotic curvature measurement when using the algorithm. The fast dot-projection (FDP) algorithm was applied for voxel-based nearest neighbor (VNN), multiple plane interpolation (MPI), and pixel nearest neighbor (PNN) protocols to reduce the reconstruction time. The 3-D image volume was reconstructed from the datasets acquired from scoliotic subjects. The computational cost, image characteristics, and statistical analyses of curve measurements were compared and evaluated among different reconstruction protocols. The results illustrated that the 3-D spine images using the FDP-MPI4 algorithm showed higher brightness (20%), contrast (14%), and signal-to-noise ratio (SNR) (26%) than FDP-VNN. The measurement performed by trainee rater exhibited significant improvement in measurement reliability and accuracy using FDP-MPI4 in comparison with FDP-VNN ( ), and the intraclass correlation coefficient (ICC) of interrater measurement increased from 0.88 to 0.96. The FDP-PNN method could acquire and reconstruct spine images simultaneously and present the results in 1-2 min, which showed the potential to provide the approximate real-time visualization for fast screening.

Automatic Detection and Measurement of Spinous Process Curve on Clinical Ultrasound Spine Images.

The ultrasound (US) imaging technique has been applied to scoliosis assessment, and the proxy Cobb angle can be acquired on the US coronal images. The spinous process angle (SPA) is a valuable parameter to indicate 3-D deformity of spine. However, the SPA cannot be measured on US images since the spinous process (SP) is merged in the soft tissue layer and impossible to be identified on the coronal view directly. A new method based on the gradient vector flow (GVF) snake model was proposed to automatically locate SP position on the US transverse images, and the density-based spatial clustering of application with noise (DBSCAN) was used to remove the outliers out of the detected location results. With marking the SP points on the US coronal image, the SP curve was interpolated and the SPA was measured. The algorithm was evaluated on 50 subjects with various severity of scoliosis, and two raters measured the SPA on both US images and radiographs manually. The mean absolute differences (MADs) of SPAs obtained from the two modalities were 3.4° ± 2.4° and 3.6° ± 2.8° for the two raters, respectively, which were less than the clinical acceptance error (5°), and the results reported a good linear correlation ( ) between the US method and radiography. It indicates that the proposed method can be a promising approach for SPA measurement using the US imaging technique.

Automatic Measurement of Spinous Process Angles on Ultrasound Spine Images.

Ultrasound (US) imaging technique has been applied to measure the proxy Cobb angle and spinous process angle (SPA) for spinal curvatures of scoliosis. However manual measurement of ultrasound images is time consuming and greatly relying on the experience of raters. The objectives of this work are to develop an automatic measurement method to assess SPA of spine curves and to evaluate the accuracy and reliability of the method. The spinous process curves were identified and fitted on US images, and the automatically measured SPA were compared with the results from US manual and radiographic measurements. It illustrates that the US-auto measurement of SPA presents higher correlation and smaller difference with clinical standard radiographic results than the US-manual measurement.