ObjectiveTo summarize current patient-derived organoids as preclinical cancer models, and its potential clinical application prospects. MethodsCurrent patient-derived organoids as preclinical cancer models were reviewed according to the results searched from PubMed database. In addition, how cancer-derived human tumor organoids of pancreatic cancer could facilitate the precision cancer medicine were discussed. ResultsThe cancer-derived human tumor organoids show great promise as a tool for precision medicine of pancreatic cancer, with potential applications for oncogene modeling, gene discovery and chemosensitivity studies. ConclusionThe cancer-derived human tumor organoids can be used as a tool for precision medicine of pancreatic cancer.
This article introduces the exploration and establishment of “grass-roots Party building + targeted poverty alleviation” model by the Party Branch of Emergency Department of West China Hospital of Sichuan University, and discusses how to establish the “trinity mode” of management support, personnel training, and on-site guidance under the leading of grass-roots Party building through a series of the branches combined activities, according to the core idea of “strengthening the Party construction, bringing people closer together, and promoting development”. The aim is to form a long-term mechanism of grass-roots Party building and targeted medical poverty alleviation through continuously implementing this model, which can benefit more people in remote and ethnic minority areas and contribute to “Healthy China 2030”.
Mixed reality technology is new digital holographic imaging technology that generates three-dimensional simulation images through computers and anchors the virtual images to the real world. Compared with traditional imaging diagnosis and treatment methods, mixed reality technology is more conducive to the advantages of precision medicine, helps to promote the development of medical clinical application, teaching and scientific research in the field of orthopedics, and will further promote the progress of clinical orthopedics toward standardization, digitization and precision. This article briefly introduces the mixed reality technology, reviews its application in the perioperative period, teaching and diagnosis and treatment standardization and dataization in the field of orthopedics, and discusses its technical advantages, aiming to provide a reference for the better use of mixed reality technology in orthopedics.
With the advancement of thyroid tumor treatment concepts and the progress of standardized treatment processes nationwide, the 5-year survival rate of thyroid tumors in China has risen from 67.5% in 2003 to 84.3% in 2015. As China has been continuously enriching its treatment options for advanced thyroid cancer in recent years, gradually improving the standardized treatment system for early and intermediate thyroid cancer, enhancing multidisciplinary collaboration methods and concepts, and regularizing scientific statistics, the survival rate of thyroid tumors continues to improve. We still need to consider the future development direction and core driving force of China’s thyroid discipline, correctly view the “prosperous” stage of domestic thyroid discipline development, and actively review the future development direction of China’s thyroid discipline.
Non-small cell lung cancer is one of the cancers with the highest incidence and mortality rate in the world, and precise prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning as a breakthrough technology of artificial intelligence has shown good performance and great potential in the application of non-small cell lung cancer prognosis model. The research on the application of deep learning in survival and recurrence prediction, efficacy prediction, distant metastasis prediction, and complication prediction of non-small cell lung cancer has made some progress, and it shows a trend of multi-omics and multi-modal joint, but there are still shortcomings, which should be further explored in the future to strengthen model verification and solve practical problems in clinical practice.
Lung cancer is a leading cause of cancer-related deaths worldwide, with its high mortality rate primarily attributed to delayed diagnosis. Radiomics, by extracting abundant quantitative features from medical images, offers novel possibilities for early diagnosis and precise treatment of lung cancer. This article reviewed the latest advancements in radiomics for lung cancer management, particularly its integration with artificial intelligence (AI) to optimize diagnostic processes and personalize treatment strategies. Despite existing challenges, such as non-standardized image acquisition parameters and limitations in model reproducibility, the incorporation of AI significantly enhanced the precision and efficiency of image analysis, thereby improving the prediction of disease progression and the formulation of treatment plans. We emphasized the critical importance of standardizing image acquisition parameters and discussed the role of artificial intelligence in advancing the clinical application of radiomics, alongside future research directions.
ObjectiveTo review the progress of radiomics in the field of colorectal cancer in recent years and summarize its value in the imaging diagnosis of colorectal cancer.MethodsEighty English and seven Chinese articles were retrieved through PUBMED, OVID, CNKI, Weipu and Wanfang. The structure and content of these literatures were classified and analyzed.ResultsIn five studies predicting the preoperative stages of colorectal cancer based on CT radiomics, the area under curve (AUC) ranged from 0.736 to 0.817; in two studies predicting the preoperative stages of colorectal cancer based on MRI radiomics, the AUC were 0.87 and 0.827 respectively. In two studies about radiomics analysis for evaluation of pathological complete response to neoadjuvant chemoradiotherapy based on CT, the AUC were 0.79 and 0.72 respectively; in four studies about radiomics analysis for evaluation of pathological complete response to neoadjuvant chemoradiotherapy based on MRI, the AUC ranged from 0.84 to 0.979. In one study evaluating the sensitivity of neoadjuvant chemotherapy based on MRI radiomics, the AUC was 0.79. In one study predicting the postoperative survival rate based on MRI radiomics, the AUC value of the final model was 0.827. In one study, the accuracy of the model based on PET/CT radiomics in 4-year disease-free survival (DSS), progression-free survival (DFS) and overall survival (OS) were 0.87, 0.79 and 0.79 respectively.ConclusionAt present, radiomics has a valuable impact on preoperative staging, neoadjuvant therapy evaluation, and survival analysis of colorectal cancer.
ObjectiveTo summarize the application of circulating free DNA (cfDNA) in the diagnosis and treatment of hepatocellular carcinoma (HCC). MethodThe relevant literature on the application of cfDNA in the diagnosis and treatment of HCC both domestic and international was reviewed and summarized. ResultsThe cfDNA is an emerging biomarker in recent years. At present, the different detection methods had been reported in a large number of studies to detect abnormal methylation, hot spot mutation, gene copy number variation, quantitative detection of cfDNA concentration, etc. It was found that the cfDNA could be used in the management process of early diagnosis, treatment guidance, and efficacy evaluation of HCC patients. ConclusionscfDNA detection is a good tool in the diagnosis and treatment of HCC, which can help clinicians make-decisions and bring more possibilities for the diagnosis and treatment of HCC, which is of great significance for changing the current diagnosis and treatment of HCC. However, there are still many challenges in cost control, technology optimization, and standardization of evaluation indicators. With the continuous progress of molecular biology technology and artificial intelligence, the application of cfDNA in diagnosis and treatment of HCC will be further expanded, its advantages will be better played, and the related shortcomings will be gradually solved.
Against the backdrop of medical digital transformation, West China Hospital of Sichuan University has conducted a 30-year exploration and practice of colorectal cancer data engineering. This study focuses on the integration of special disease digitization and value-based healthcare, achieving standardized management and in-depth mining of colorectal cancer diagnosis and treatment data through constructing a full-life cycle data governance system, multi-center data platform, and intelligent application scenarios (such as clinical decision support systems). The practical results show that this data engineering has formed a specialized disease database containing more than 9 500 cases of structured data, and promoted the collaborative development of the entire chain of “production–study–research–business–government”, providing a learnable digital paradigm for improving diagnostic and treatment accuracy and optimizing medical resource allocation. The study indicates that special disease digitization is a key path to achieving value-based healthcare, and its experience in data standardization and medical-engineering cross-innovation is of reference significance for other disease fields.
Tuberculosis (TB) is one of the major public health concerns worldwide. Since the development of precision medicine, the filed regarding TB control and prevention has been brought into the era of precision medicine. Although great progress has been achieved in the accurate diagnosis, treatment and management of TB patients, we have to face several challenges. We should seize the opportunity, and develop and improve novel measures in TB prevention on the basis of precision medicine. The accurate diagnosis criteria, treatment regimen and management of TB patients should be carried out according to the standard of precision medicine. We aim to improve the treatment of TB patients and prevent the transmission of TB in the community, thereby contributing to the achievement of the End TB Strategy by 2035.