Portrait stylized rendering for 3D light-field display based on radiation field and example guide.

With the development of three-dimensional (3D) light-field display technology, 3D scenes with correct location information and depth information can be perceived without wearing any external device. Only 2D stylized portrait images can be generated with traditional portrait stylization methods and it is difficult to produce high-quality stylized portrait content for 3D light-field displays. 3D light-field displays require the generation of content with accurate depth and spatial information, which is not achievable with 2D images alone. New and innovative portrait stylization techniques methods should be presented to meet the requirements of 3D light-field displays. A portrait stylization method for 3D light-field displays is proposed, which maintain the consistency of dense views in light-field display when the 3D stylized portrait is generated. Example-based portrait stylization method is used to migrate the designated style image to the portrait image, which can prevent the loss of contour information in 3D light-field portraits. To minimize the diversity in color information and further constrain the contour details of portraits, the Laplacian loss function is introduced in the pre-trained deep learning model. The three-dimensional representation of the stylized portrait scene is reconstructed, and the stylized 3D light field image of the portrait is generated the mask guide based light-field coding method. Experimental results demonstrate the effectiveness of the proposed method, which can use the real portrait photos to generate high quality 3D light-field portrait content.

The reliability and integrity of overall survival data based on follow-up records only and potential solutions to the challenges.

Overall survival (OS) is considered the standard clinical endpoint to support effectiveness claims in new drug applications globally, particularly for lethal conditions such as cancer. However, the source and reliability of OS in the setting of clinical trials have seldom been doubted and discussed. This study first raised the common issue that data integrity and reliability are doubtful when we collect OS information or other time-to-event endpoints based solely on simple follow-up records by investigators without supporting material, especially since the 2019 COVID-19 pandemic. Then, two rounds of discussions with 30 Chinese experts were held and 12 potential source scenarios of three methods for obtaining the time of death of participants, including death certificate, death record and follow-up record, were sorted out and analysed. With a comprehensive assessment of the 12 scenarios by legitimacy, data reliability, data acquisition efficiency, difficulty of data acquisition, and coverage of participants, both short-term and long-term recommended sources, overall strategies and detailed measures for improving the integrity and reliability of death date are presented. In the short term, we suggest integrated sources such as public security systems made available to drug inspection centres appropriately as soon as possible to strengthen supervision. Death certificates provided by participants' family members and detailed standard follow-up records are recommended to investigators as the two channels of mutual compensation, and the acquisition of supporting materials is encouraged as long as it is not prohibited legally. Moreover, we expect that the sharing of electronic medical records and the legal disclosure of death records in established health registries can be realized with the joint efforts of the whole industry in the long-term. The above proposed solutions are mainly based on the context of China and can also provide reference for other countries in the world.

Real-time dense-view imaging for three-dimensional light-field display based on image color calibration and self-supervised view synthesis.

Three-Dimensional (3D) light-field display has achieved promising improvement in recent years. However, since the dense-view images cannot be collected fast in real-world 3D scenes, the real-time 3D light-field display is still challenging to achieve in real scenes, especially at the high-resolution 3D display. Here, a real-time 3D light-field display method with dense-view is proposed based on image color correction and self-supervised optical flow estimation, and a high-quality and high frame rate of 3D light-field display can be realized simultaneously. A sparse camera array is firstly used to capture sparse-view images in the proposed method. To eliminate the color deviation of the sparse views, the imaging process of the camera is analyzed, and a practical multi-layer perception (MLP) network is proposed to perform color calibration. Given sparse views with consistent color, the optical flow can be estimated by a lightweight convolutional neural network (CNN) at high speed, which uses the input image pairs to learn the optical flow in a self-supervised manner. With inverse warp operation, dense-view images can be synthesized in the end. Quantitative and qualitative experiments are performed to evaluate the feasibility of the proposed method. Experimental results show that over 60 dense-view images at a resolution of 1024 × 512 can be generated with 11 input views at a frame rate over 20 fps, which is 4× faster than previous optical flow estimation methods PWC-Net and LiteFlowNet3. Finally, large viewing angles and high-quality 3D light-field display at 3840 × 2160 resolution can be achieved in real-time.

Automatic co-design of light field display system based on simulated annealing algorithm and visual simulation.

Accurate, fast, and reliable modeling and optimization methods play a crucial role in designing light field display (LFD) system. Here, an automatic co-design method of LFD system based on simulated annealing and visual simulation is proposed. The process of LFD content acquisition and optical reconstruction are modeled and simulated, the objective function for evaluating the display effect of the LFD system is established according to the simulation results. In case of maximum objective function, the simulated annealing optimization method is used to find the optimal parameters of the LFD system. The validity of the proposed method is confirmed through optical experiments.

KRAS Mutation in Rare Tumors: A Landscape Analysis of 3453 Chinese Patients.

KRAS is the most commonly mutated oncogene in human cancers. Targeted therapy and immunotherapy for this gene have made remarkable progress in recent years. However, comprehensive molecular landscape analysis of KRAS in rare tumors is lacking. Retrospective analysis was performed on clinical samples from patients with rare tumors collected between September 2015 and September 2021, using hybrid-capture-based next-generation sequencing for genomic profiling and immunohistochemistry assay for PD-L1. Of the 3,453 patients included in analysis, KRAS mutations were identified in 8.7% patients in overall; mutation rate and mutation subtypes varied widely across tumor systems and subtypes. KRAS mutations included 21 missense mutations, of which G12D (29.2%), G12V (24.6%), and G13D (10.8%) were most common. Interestingly, KRAS G12C was observed in 0.6% patients overall, and in 5.7% of sarcomatoid carcinoma of the lung and 5.4% of clear cell ovarian cancer tumors, but none in small-bowel cancer tumors. 31.8% KRAS mutations and 36.4% KRAS G12C mutations co-occurred with other targetable alterations. No significant correlation was observed between TMB-H, MSI-H, PD-L1 status, and KRAS mutation status, which may be related to the high proportion of G12D. This study is the first KRAS mutation landscape study in rare tumors of large sample size in China and worldwide. Our results suggest that targeted therapy and immunotherapy are both feasible, albeit complex, in these patients. This information may have significant impact on the operation of clinical trials for rare tumor patients with KRAS mutations in China.

Real-time optical reconstruction for a three-dimensional light-field display based on path-tracing and CNN super-resolution.

Three-Dimensional (3D) light-field display plays a vital role in realizing 3D display. However, the real-time high quality 3D light-field display is difficult, because super high-resolution 3D light field images are hard to be achieved in real-time. Although extensive research has been carried out on fast 3D light-field image generation, no single study exists to satisfy real-time 3D image generation and display with super high-resolution such as 7680×4320. To fulfill real-time 3D light-field display with super high-resolution, a two-stage 3D image generation method based on path tracing and image super-resolution (SR) is proposed, which takes less time to render 3D images than previous methods. In the first stage, path tracing is used to generate low-resolution 3D images with sparse views based on Monte-Carlo integration. In the second stage, a lite SR algorithm based on a generative adversarial network (GAN) is presented to up-sample the low-resolution 3D images to high-resolution 3D images of dense views with photo-realistic image quality. To implement the second stage efficiently and effectively, the elemental images (EIs) are super-resolved individually for better image quality and geometry accuracy, and a foreground selection scheme based on ray casting is developed to improve the rendering performance. Finally, the output EIs from CNN are used to recompose the high-resolution 3D images. Experimental results demonstrate that real-time 3D light-field display over 30fps at 8K resolution can be realized, while the structural similarity (SSIM) can be over 0.90. It is hoped that the proposed method will contribute to the field of real-time 3D light-field display.

The state of the art of bispecific antibodies for treating human malignancies.

Bispecific antibodies (bsAb) that target two independent epitopes or antigens have been extensively explored in translational and clinical studies since they were first developed in the 1960s. Many bsAbs are being tested in clinical trials for treating a variety of diseases, mostly cancer. Here, we provide an overview of various types of bsAbs in clinical studies and discuss their targets, safety profiles, and efficacy. We also highlight the current challenges, potential solutions, and future directions of bsAb development for cancer treatment.

Perspectives of tumor-infiltrating lymphocyte treatment in solid tumors.

Tumor-infiltrating lymphocyte (TIL) therapy is a type of adoptive cellular therapy by harvesting infiltrated lymphocytes from tumors, culturing and amplifying them in vitro and then infusing back to treat patients. Its diverse TCR clonality, superior tumor-homing ability, and low off-target toxicity endow TIL therapy unique advantages in treating solid tumors compared with other adoptive cellular therapies. Nevertheless, the successful application of TIL therapy currently is still limited to several types of tumors. Herein in this review, we summarize the fundamental work in the field of TIL therapy and the current landscape and advances of TIL clinical trials worldwide. Moreover, the limitations of the current TIL regimen have been discussed and the opportunities and challenges in the development of next-generation TIL are highlighted. Finally, the future directions of TIL therapy towards a broader clinical application have been proposed.

Platform study of genotyping-guided precision medicine for rare solid tumours: a study protocol for a phase II, non-randomised, 18-month, open-label, multiarm, single-centre clinical trial testing the safety and efficacy of multiple Chinese-approved targeted drugs and PD-1 inhibitors in the treatment of metastatic rare tumours.

INTRODUCTION: Limited clinical studies have been conducted on rare solid tumours, and there are few guidelines on the diagnosis and treatment, including experiences with targeted therapy and immunotherapy, of rare solid tumours in China, resulting in limited treatment options and poor outcomes. This study first proposes a definition of rare tumours and is designed to test the preliminary efficacy of targeted and immunotherapy drugs for the treatment of rare tumours. METHODS AND ANALYSIS: This is a phase II, open-label, non-randomised, multiarm, single-centre clinical trial in patients with advanced rare solid tumours who failed standard treatment; the study aims to evaluate the safety and efficacy of targeted drugs in patients with advanced rare solid tumours with corresponding actionable alterations, as well as the safety and efficacy of immune checkpoint (programmed death receptor inhibitor 1, PD-1) inhibitors in patients with advanced rare solid tumours without actionable alterations. Patients with advanced rare tumours who fail standardised treatment and carry actionable alterations (Epidermal growth factor receptor (EGFR) mutations, ALK gene fusions, ROS-1 gene fusions, C-MET gene amplifications/mutations, BRAF mutations, CDKN2A mutations, BRCA1/2 mutations, HER-2 mutations/overexpressions/amplifications or C-KIT mutations) will be enrolled in the targeted therapy arm and be given the corresponding targeted drugs. Patients without actionable alterations will be enrolled in the PD-1 inhibitor arm and be treated with sintilimab. After the patients treated with vemurafenib, niraparib and palbociclib acquire resistance, they will receive combination treatment with sintilimab or atezolizumab. With the use of Simon's two-stage Minimax design, and the sample size was estimated to be 770. The primary endpoint of this study is the objective response rate. The secondary endpoints are progression-free survival in the targeted treatment group and single-agent immunotherapy group; the duration of response in the targeted therapy and single-agent immunotherapy groups; durable clinical benefit in the single-agent immunotherapy group; and the incidence of adverse events. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Chinese Academy of Medical Sciences (ID: 20/132-2328). The results from this study will be actively disseminated through manuscript publications and conference presentations. TRIAL REGISTRATION NUMBERS: NCT04423185; ChiCTR2000039310.

Comprehensive Genomic Profiling of Rare Tumors in China: Routes to Immunotherapy.

Treatment options for rare tumors are limited, and comprehensive genomic profiling may provide useful information for novel treatment strategies and improving outcomes. The aim of this study is to explore the treatment opportunities of patients with rare tumors using immune checkpoint inhibitors (ICIs) that have already been approved for routine treatment of common tumors. We collected immunotherapy-related indicators data from a total of 852 rare tumor patients from across China, including 136 programmed cell death ligand-1 (PD-L1) expression, 821 tumors mutational burden (TMB), 705 microsatellite instability (MSI) and 355 human leukocyte antigen class I (HLA-I) heterozygosity reports. We calculated the positive rates of these indicators and analyzed the consistency relationship between TMB and PD-L1, TMB and MSI, and HLA-I and PD-L1. The prevalence of PD-L1 positive, TMB-H, MSI-, and HLA-I -heterozygous was 47.8%, 15.5%, 7.4%, and 78.9%, respectively. The consistency ratio of TMB and PD-L1, TMB and MSI, and HLA-I and PD-L1 was 54.8% (78/135), 87.3% (598/685), and 47.4% (54/114), respectively. The prevalence of the four indicators varied widely across tumors systems and subtypes. The probability that neuroendocrine tumors (NETs) and biliary tumors may benefit from immunotherapy is high, since the proportion of TMB-H is as high as 50% and 25.4% respectively. The rates of PD-L1 positivity, TMB-H and MSI-H in carcinoma of unknown primary (CUP) were relatively high, while the rates of TMB-H and MSI-H in soft tissue tumors were both relatively low. Our study revealed the distribution of immunotherapeutic indicators in patients with rare tumors in China. Comprehensive genomic profiling may offer novel therapeutic modalities for patients with rare tumors to solve the dilemma of limited treatment options.

Parallel multi-view polygon rasterization for 3D light field display.

Three-dimensional (3D) light field displays require samples of image data captured from a large number of regularly spaced camera images to produce a 3D image. Generally, it is inefficient to generate these images sequentially because a large number of rendering operations are repeated in different viewpoints. The current 3D image generation algorithm with traditional single viewpoint computer graphics techniques is not sufficiently well suited to the task of generating images for the light field displays. A highly parallel multi-view polygon rasterization (PMR) algorithm for 3D multi-view image generation is presented. Based on the coherence of the triangular rasterization calculation among different viewpoints, the related rasterization algorithms including primitive setup, plane function, and barycentric coordinate interpolation in the screen space are derived. To verify the proposed algorithm, a hierarchical soft rendering pipeline with GPU is designed and implemented. Several groups of images of 3D objects are used to verify the performance of the PMR method, and the correct 3D light field image can be achieved in real time.

Backward ray tracing based high-speed visual simulation for light field display and experimental verification.

The exiting simulation method is not capable of achieving three-dimensional (3D) display result of the light field display (LFD) directly, which is important for design and optimization. Here, a high-speed visual simulation method to calculate the 3D image light field distribution is presented. Based on the backward ray tracing technique (BRT), the geometric and optical models of the LFD are constructed. The display result images are obtained, and the field of view angle (FOV) and depth of field (DOF) can be estimated, which are consistent with theoretical results and experimental results. The simulation time is 1s when the number of sampling rays is 3840×2160×100, and the computational speed of the method is at least 1000 times faster than that of the traditional physics-based renderer. A prototype was fabricated to evaluate the feasibility of the proposed method. From the results, our simulation method shows good potential for predicting the displayed image of the LFD for various positions of the observer's eye with sufficient calculation speed.

Real-time optical 3D reconstruction based on Monte Carlo integration and recurrent CNNs denoising with the 3D light field display.

A general integral imaging generation method based on the path-traced Monte Carlo (MC) method and recurrent convolutional neural networks denoising is presented. According to the optical layer structure of the three-dimensional (3D) light field display, screen pixels are encoded to specific viewpoints, then the directional rays are cast from viewpoints to screen pixels to preform the path integral. In the process of the integral, advanced illumination is used for high-quality elemental image array (EIA) generation. Recurrent convolutional neural networks are implemented as an auxiliary post-processing for the EIA to eliminate the noise of the 3D image in MC integration. 4K (3840 × 2160) resolution, 2 sample/pixel and the ray path tracing method are realized in the experiment. Experimental results demonstrate that the structural similarity metric (SSIM) value and peak signal-to-noise ratio (PSNR) gain of the reconstructed 3D image and target 3D image exceed 90% and 10 dB within 10 frames, respectively. Besides, real-time frame rate is more than 30 fps, showing the super efficiency and quality in optical 3D reconstruction.

Interactive floating full-parallax digital three-dimensional light-field display based on wavefront recomposing.

Advanced three-dimensional (3D) imaging techniques can acquire high-resolution 3D biomedical and biological data, but available digital display methods show this data in restricted two dimensions. 3D light-field displays optically reconstruct realistic 3D image by carefully tailoring light fields, and a natural and comfortable 3D sense of real objects or scenes is expected. An interactive floating full-parallax 3D light-field display with all depth cues is demonstrated with 3D biomedical and biological data, which are capable of achieving high efficiency and high image quality. A compound lens-array with two pieces of lens in each lens unit is designed and fabricated to suppress the aberrations and increase the viewing angle. The optimally designed holographic functional screen is used to recompose the light distribution from the lens-array. The imaging distortion can be decreased to less than 1.9% from more than 20%. The real time interactive floating full-parallax 3D light-field image with the clear displayed depth of 30 cm can be perceived with the right geometric occlusion and smooth parallax in the viewing angle of 45°, where 9216 viewpoints are used.

High-efficient computer-generated integral imaging based on the backward ray-tracing technique and optical reconstruction.

A high-efficient computer-generated integral imaging (CGII) method is presented based on the backward ray-tracing technique. In traditional CGII methods, the total rendering time is long, because a large number of cameras are established in the virtual world. The ray origin and the ray direction for every pixel in elemental image array are calculated with the backward ray-tracing technique, and the total rendering time can be noticeably reduced. The method is suitable to create high quality integral image without the pseudoscopic problem. Real time and non-real time CGII rendering images and optical reconstruction are demonstrated, and the effectiveness is verified with different types of 3D object models. Real time optical reconstruction with 90 × 90 viewpoints and the frame rate above 40 fps for the CGII 3D display are realized without the pseudoscopic problem.