Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities

Research advances and trends in anatomy from 2013 to 2023: A visual analysis based on CiteSpace and VOSviewer

As the cornerstone of medicine, the development of anatomy is related to many disciplines and fields and has received extensive attention from researchers. How to integrate and grasp the cutting-edge information in this field quickly is a challenge for researchers, so the aim of this study is to analyze research in anatomy using CiteSpace and VOSviewer in order to identify research hotspots and future directions. To offer a fresh viewpoint for assessing the academic influences of researchers, nations, or institutions on anatomy, and to examine the development of hotspots in anatomical study and to forecast future trends. A total of 4637 anatomy-related publications from 2013 to 2023 were collected from Web of Science Core Collection databases. Their temporal distribution, spatial distribution, cited authors, co-cited journals, keywords, and disciplinary connections in the literature were analyzed using CiteSpace and VOSviewer, and a knowledge graph was constructed. The temporal distribution shows a general fluctuation in the amount of literature published from 2013 to 2023. In spatial distribution, the total number of published articles was highest in the United States, the United Kingdom, and China, the United States leading. Tubbs, Rhoton, Iwanaga, and LaPrade are important authors in anatomy. Clinical Anatomy, Surgical and Radiologic Anatomy, and Journal of Anatomy were the most highly cited journals. Analysis of keywords and citation emergence showed that the research hotspots and trends in anatomy focused mainly on anatomy education, digital technology, and surgical management. At the same time, anatomy showed a trend toward multidisciplinary crossover, developing closer relationships with molecular biology, immunology, and clinical medicine. Current research in anatomy focuses on innovative reform of the educational model and the application and promotion of digital technology. Also, multidisciplinary cross-fertilization is an inevitable trend for the future development of anatomy.

Challenges involved in the application of artificial intelligence in gastroenterology: The race is on!

Gastroenterology is a particularly data-rich field, generating vast repositories of data that are a fruitful ground for artificial intelligence (AI) and machine learning (ML) applications. In this opinion review, we initially elaborate on the current status of the application of AI/ML-based software in gastroenterology. Currently, AI/ML-based models have been developed in the following applications: Models integrated into the clinical setting following real-time patient data flagging patients at high risk for developing a gastrointestinal disease, models employing non-invasive parameters that provide accurate diagnoses aiming to either replace, minimize, or refine the indications of endoscopy, models utilizing genomic data to diagnose various gastrointestinal diseases, computer-aided diagnosis systems facilitating the interpretation of endoscopy images, models to facilitate treatment allocation and predict the response to treatment, and finally, models in prognosis predicting complications, recurrence following treatment, and overall survival. Then, we elaborate on several challenges and how they may negatively impact the widespread application of AI in healthcare and gastroenterology. Specifically, we elaborate on concerns regarding accuracy, cost-effectiveness, cybersecurity, interpretability, oversight, and liability. While AI is unlikely to replace physicians, it will transform the skillset demanded by future physicians to practice. Thus, physicians are expected to engage with AI to avoid becoming obsolete.

Three-Dimensional Printing and Bioprinting in Renal Transplantation and Regenerative Medicine: Current Perspectives

For patients with end-stage kidney disease (ESKD), renal transplantation is the treatment of choice, constituting the most common solid organ transplantation. This study aims to provide a comprehensive review regarding the application of three-dimensional (3D) printing and bioprinting in renal transplantation and regenerative medicine. Specifically, we present studies where 3D-printed models were used in the training of surgeons through renal transplantation simulations, in patient education where patients acquire a higher understanding of their disease and the proposed operation, in the preoperative planning to facilitate decision-making, and in fabricating customized, tools and devices. Three-dimensional-printed models could transform how surgeons train by providing surgical rehearsal platforms across all surgical specialties, enabling training with tissue realism and anatomic precision. The use of 3D-printed models in renal transplantations has shown a positive impact on surgical outcomes, including the duration of the operation and the intraoperative blood loss. Regarding 3D bioprinting, the technique has shown promising results, especially in the field of microfluidic devices, with the development of tissue demonstrating proximal tubules, glomerulus, and tubuloinerstitium function, and in renal organoid development. Such models can be applied for renal disease modeling, drug development, and renal regenerative medicine.

Application of 3D Bioprinting in Liver Diseases

Liver diseases are the primary reason for morbidity and mortality in the world. Owing to a shortage of organ donors and postoperative immune rejection, patients routinely suffer from liver failure. Unlike 2D cell models, animal models, and organoids, 3D bioprinting can be successfully employed to print living tissues and organs that contain blood vessels, bone, and kidney, heart, and liver tissues and so on. 3D bioprinting is mainly classified into four types: inkjet 3D bioprinting, extrusion-based 3D bioprinting, laser-assisted bioprinting (LAB), and vat photopolymerization. Bioinks for 3D bioprinting are composed of hydrogels and cells. For liver 3D bioprinting, hepatic parenchymal cells (hepatocytes) and liver nonparenchymal cells (hepatic stellate cells, hepatic sinusoidal endothelial cells, and Kupffer cells) are commonly used. Compared to conventional scaffold-based approaches, marked by limited functionality and complexity, 3D bioprinting can achieve accurate cell settlement, a high resolution, and more efficient usage of biomaterials, better mimicking the complex microstructures of native tissues. This method will make contributions to disease modeling, drug discovery, and even regenerative medicine. However, the limitations and challenges of this method cannot be ignored. Limitation include the requirement of diverse fabrication technologies, observation of drug dynamic response under perfusion culture, the resolution to reproduce complex hepatic microenvironment, and so on. Despite this, 3D bioprinting is still a promising and innovative biofabrication strategy for the creation of artificial multi-cellular tissues/organs.