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    Research status and development prospect of deep learning in medical imaging
    Bingjie LIN,Meiyun WANG
    Journal of Shandong University (Health Sciences)    2023, 61 (12): 21-29.   DOI: 10.6040/j.issn.1671-7554.0.2023.0774
    Abstract275)   HTML13)    PDF(pc) (1607KB)(175)       Save

    Precision medicine, imaging first; precision imaging, technology first. In recent years, with the rapid development of artificial intelligence, deep learning, as an important branch, has been widely used in many fields such as signal processing, computer vision and natural language processing, etc., among which medical image data segmentation, disease detection and prognosis prediction based on deep learning have become the hot spots of many scholars' research. In this paper, we will briefly outline the current status of deep learning application in the main technical fields of medical imaging, and analyze the challenges and development prospects of its clinical application in medical imaging, aiming to provide reference for the transformation of deep learning algorithms in the clinic.

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    Expert consensus of practical clinical classification system with optimal surgical strategy for cesarean scar pregnancy
    Yanli BAN, Ying Yanli Writing experts: ZHAO, Hua LI, Wei LIU, Fengnian RONG, Shuping ZHAO, Baoxia CUI
    Journal of Shandong University (Health Sciences)    2023, 61 (11): 1-10.   DOI: 10.6040/j.issn.1671-7554.0.2023.0988
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    Cesarean scar pregnancy (CSP) is a special type of ectopic pregnancy in which a pregnancy sac is implanted at the scar of a previous caesarean section. Without appropriate diagnosis or treatment, it can lead to severe morbidity such as life-threatening massive hemorrhage, and uterine rupture, with subsequent effect of fertility, physical and mental health of patients. Although many different treatment options have been described, there is still no consensus on the optimal surgical treatment strategy. In recent years, treatment of CSP based on classification has drawn more and more attention. The practical clinical classification system with optimal surgical strategy for CSP has been widely validated in Shandong Province, which shows good application value and reliable therapeutic effects. Based on this classification system, and combined with clinical experience and the latest clinical research results, the expert consensus of clinical classification system and surgical strategy for CSP is formulated, aiming to standardize the clinical diagnosis and treatment, and to guide clinical work.

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    Progress in the establishment and application of organoids of bladder cancer
    Andong GUO,Sentai DING
    Journal of Shandong University (Health Sciences)    2023, 61 (11): 20-26.   DOI: 10.6040/j.issn.1671-7554.0.2023.0900
    Abstract186)   HTML14)    PDF(pc) (2324KB)(189)       Save

    Bladder cancer is a common disease of the urinary system. Cisplatin-based chemotherapy is the first-line treatment for inoperable and metastatic myometrial invasive bladder cancer. However, due to resistance, a large number of patients fail in chemotherapy, which leads to tumor recurrence and progression. In recent years, organoid models have become a hot spot in the research of pathogenesis, metastasis and drug sensitivity. The successful establishment of bladder cancer organoids is a breakthrough in the clinical treatment of bladder cancer, because organoids and primary tissues have a high degree of genetic and phenotypic consistency, which can help us better understand the genomic changes of bladder cancer, and detect drug sensitivity and resistance. This article aims to review and analyze the construction process, characteristics, advantages and applications of bladder cancer organoids as preclinical models.

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    Technical procedure of CT-guided intratumoral chemotherapy for lung tumor
    Mingyong HAN,Xiaoli YU,Fangping ZENG,Bing XIE,Lan LU,Jiaquan QU,Bifeng JIANG,Sihan TANG,Jie TAN,Jin LIANG,Longhui ZHONG,Liu WANG,Xuanzhi ZHAO
    Journal of Shandong University (Health Sciences)    2023, 61 (11): 11-19.   DOI: 10.6040/j.issn.1671-7554.0.2023.0981
    Abstract183)   HTML42)    PDF(pc) (6630KB)(141)       Save

    The incidence and mortality rates of lung cancer in China rank the first of all tumors. At present, there are many effective treatment methods, including surgery, chemotherapy, radiotherapy, targeted therapy, immunotherapy and other local and systematic treatments. In recent years, intratumoral chemotherapy, which combines the advantages of local therapy and systemic therapy, has gradually become the focus. By using ultrasound, bronchoscope, ultrasonic bronchoscope, endoscopic ultrasonography or CT and other imaging and interventional modalities, chemotherapeutics such as cisplatin, carboplatin, mitomycin, paclitaxel liposomes, fluorouracil in stock or diluted solutions are directly injected into the cancer tissue through the puncture needle. Intratumoral chemotherapy can increase the concentration of chemotherapeutics in the tumor tissue, reduce the systemic toxicity and side effects, and improve the local control rate of cancers. We have carried out clinical application and exploratory research on intratumoral chemotherapy for lung cancer, liver metastasis and bone metastasis, and observed patients' benefits and primary efficacy. This paper will summarize the technical procedure of CT-guided intratumoral chemotherapy.

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    Research progress in the application of artificial intelligence in myocardial imaging
    Pei NIE,Ximing WANG
    Journal of Shandong University (Health Sciences)    2023, 61 (12): 1-6.   DOI: 10.6040/j.issn.1671-7554.0.2023.0773
    Abstract173)   HTML18)    PDF(pc) (1451KB)(152)       Save

    Recently, artificial intelligence (AI) has shown great potential in myocardial imaging. AI algorithms achieve automatic segmentation and measurement of myocardial images thus optimizing the workflow. The quantitative features which characterized the pathological changes of myocardium were extracted through radiomics and deep learning techniques. These features may facilitate precise diagnosis and outcome prediction of ischemic and non-ischemic cardiomyopathies. In this review, we will introduce the research progress of AI in myocardial imaging from several aspects: AI-assisted image analysis, diagnosis and outcome evaluation of cardiomyopathies. The limitations of AI in myocardial imaging will also be discussed. We hope this review may provide references for further clinical application research of AI in myocardial imaging.

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    Advances in the application of artificial intelligence in coronary computed tomography angiography
    Guyue ZHAO,Jin SHANG,Yang HOU
    Journal of Shandong University (Health Sciences)    2023, 61 (12): 30-35.   DOI: 10.6040/j.issn.1671-7554.0.2023.0795
    Abstract145)   HTML6)    PDF(pc) (1479KB)(153)       Save

    With the increasingly widespread application of artificial intelligence in the field of medical imaging, its application in coronary artery CT angiography has shown great potential, which helps to improve image quality, optimize post-processing processes, assist disease detection, evaluate functional status, analyse prognosis, and other aspects. Meanwhile, there arise some problems, and the full inspection process should be further optimized to enhance its practicality and efficiency. This article reviews the research progress, existing problems, and future development of artificial intelligence in coronary artery CT angiography.

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    Innovation and challenge of imaging artificial intelligence in medical field
    Ziliang XU,Minwen ZHENG
    Journal of Shandong University (Health Sciences)    2023, 61 (12): 7-12, 20.   DOI: 10.6040/j.issn.1671-7554.0.2023.0705
    Abstract132)   HTML6)    PDF(pc) (1306KB)(142)       Save

    With the development of science and technology, artificial intelligence (AI) has been applied in the medical imaging field gradually. However, the AI still faces many challenges. In this paper, the imaging application progress of AI in medical field will be reviewed from the aspect of tissue segmentation, auxiliary diagnosis of disease and clinical research, respectively, and the problems in them will also be pointed out. Finally, the challenges of imaging AI in medical field will be discussed.

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    Research advances of artificial intelligence-based medical imaging in the screening, diagnosis and prediction of pneumonia
    Xiao LI,Zhiyuan SUN,Longjiang ZHANG
    Journal of Shandong University (Health Sciences)    2023, 61 (12): 13-20.   DOI: 10.6040/j.issn.1671-7554.0.2023.0803
    Abstract102)   HTML4)    PDF(pc) (1839KB)(128)       Save

    Pneumonia has become the third leading cause of death in the world after ischemic heart disease and cerebrovascular disease, and is a major public health problem that seriously threatens human health. Early, rapid and accurate etiological diagnosis and risk prediction are the primary tasks in the diagnosis, treatment and prevention of pneumonia. However, due to the heavy workload of radiologists and overlapping image manifestations of different types of pneumonia, timely, rapid, and accurate diagnosis and prediction is rather challenging. The rapid development of artificial intelligence (AI) in the imaging field offers hope for solving these clinical challenges. This paper reviews the latest research results of AI in the diagnosis of pneumonia, aiming to discuss the latest progress of AI system in the field of screening, diagnosis and prediction of pneumonia, and provide prospects in the field of pneumonia, so as to provide references for promoting reasonable optimization of clinical management of pneumonia patients in China and improving the level of intelligent diagnosis and treatment of pneumonia.

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