Radiology of Infectious Diseases最新文献

{"title":"Progress of artificial intelligence in imaging for the diagnosis of drug-resistant pulmonary tuberculosis","authors":"Chuanjun Xu, Qiuzhen Xu, Fengli Jiang, Yu Wang","doi":"10.4103/rid.rid_39_22","DOIUrl":"https://doi.org/10.4103/rid.rid_39_22","url":null,"abstract":"Recent technical advances have led to the application of artificial intelligence in many areas of medical science. This approach was applied early on to medical imaging, which involves a large amount of data for diagnosis. The application of artificial intelligence and imaging diagnostics for disease screening, diagnosis, and prognosis prediction is an area of active research. Early diagnosis and effective management of drug-resistant pulmonary tuberculosis (TB) can effectively control the spread of Mycobacterium TB, reduce hospitalization, and improve prognosis. We review the progress of artificial intelligence in assisting imaging-based diagnosis of this disease, and we offer useful perspectives on future research in this area.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"9 1","pages":"86 - 91"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87078057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research progress of artificial intelligence-based imaging diagnosis of infectious diseases","authors":"Lin Guo, Li-Jun Xia, F. Lure, Hongjun Li","doi":"10.4103/rid.rid_30_22","DOIUrl":"https://doi.org/10.4103/rid.rid_30_22","url":null,"abstract":"With the rapid development and progress of theory and technology, artificial intelligence (AI) has overcome many early technical limitations. Remarkable advances have recently been made in the application of AI to various areas of health care, and improvements in the performance of computer-aided diagnostics, such as accuracy, specificity, and processing speed, have been achieved, especially in the classification and identification of lesions. We review the various applications and worldwide progress of AI-based imaging diagnosis of infectious diseases.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"283 1","pages":"92 - 95"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77909203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Death probability analysis in the old aged population and smokers in India owing to COVID-19","authors":"P. Jamdade, Shrinivas G. Jamdade","doi":"10.4103/rid.rid_22_22","DOIUrl":"https://doi.org/10.4103/rid.rid_22_22","url":null,"abstract":"OBJECTIVE: Research has shown that older people and smokers have a higher death probability from coronavirus disease 2019 (COVID-19). Thus, we investigated the effect of COVID-19 on death probability for individuals aged 65–70 years and smokers in India. MATERIALS AND METHODS: We did so using a differential learning (feed-backward) model. In the present study, we examined World Health Organization (WHO) declared COVID-19 data of India. We divided the patients into two groups accordingly: the population aged 65–70 years and female or male smokers. RESULTS: We observed that in the early stages of infection (up to 5 days), there was higher death probability in the older population; among smokers, it occurred in the middle period after infection (5–8 days). We estimated that the death probability among smokers was 1.905 times that of the older population. CONCLUSION: As Government of India, taking various initiatives to curb the spread of COVID-19, but these are not enough, so we suggest measures that should help to reduce COVID-19 infection in India.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"1 1","pages":"79 - 85"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89179462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computed tomography findings and clinical evidence of improvement in coronavirus disease 2019 infection after convalescent plasma therapy in a critically ill patient","authors":"Bangguo Tan, Jing Ou, Rui Li, Fu-lin Lu, Xiaoming Zhang, Tianwu Chen, Hongjun Li","doi":"10.4103/rid.rid_32_22","DOIUrl":"https://doi.org/10.4103/rid.rid_32_22","url":null,"abstract":"The spread of severe acute respiratory syndrome coronavirus 2 worldwide has created a major threat to human life and safety. Antiviral drugs and antibiotics have poor therapeutic effects, and there is no specific treatment for this virus. Chest computed tomography (CT) plays an important role in the diagnosis and management of coronavirus disease 2019 (COVID-19). We report a patient who was critically ill with COVID-19 and recovered after receiving transfusions of convalescent plasma. To evaluate the efficacy of convalescent plasma in the treatment of COVID-19, we compared chest CT findings, clinical manifestations, and laboratory findings before and after treatment with convalescent plasma. After the transfusion of convalescent plasma, clinical manifestations and indicators of inflammation improved, accompanied by an increase in the partial pressure of oxygen and oxygen saturation. Chest CT showed some resolution of the lung lesions, and multiple viral nucleic acid tests were negative. Therefore, the patient's condition was improved after the transfusion of convalescent plasma, suggesting that it may be an effective treatment for patients who are critically ill with COVID-19.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"10 1","pages":"100 - 103"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87917235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advocacy to promote archiving of organ imaging data in Indian tertiary care centers","authors":"J. Prakash, G. Chauhan, P. Bhattacharya, K. Saran","doi":"10.4103/rid.rid_26_22","DOIUrl":"https://doi.org/10.4103/rid.rid_26_22","url":null,"abstract":"","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"1 1","pages":"108 - 109"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83283952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging characteristics of brain abscess in children with congenital heart disease","authors":"Ke Liu, M. Zhu, Sudan Dong","doi":"10.4103/rid.rid_14_22","DOIUrl":"https://doi.org/10.4103/rid.rid_14_22","url":null,"abstract":"BACKGROUND: Brain abscess is a rare disease in childhood requiring prompt medical and/or surgical treatment. The objective was to discuss the head computed tomography and magnetic resonance imaging characteristics of children with brain abscess in congenital heart disease (CHD) group compared with the group without CHD, further comprehend the imaging findings, and assess the severity of brain abscess in children with CHD. MATERIALS AND METHODS: The radiological features of brain abscess in children hospitalized in Shanghai Children's Medical Center between September 2014 and September 2021 were retrospectively reviewed. RESULTS: Forty-four children (14 females, 30 males), with a median age of 8.6 years (range 2–15 years), were enrolled in this study. CHD was found in 22 cases. Twenty-one of these 22 patients were with cyanotic CHD. The remaining 22 cases were without CHD. Among the 22 patients with CHD, superficial abscesses of 2–5 cm in diameter are the main imaging findings, which was the same as in children without CHD. In our study, brain abscesses of CHD are usually single, while other brain abscesses are usually multiple in children without CHD. There was statistically significant difference in the number of abscesses between the group with CHD and the group without CHD (χ2 = 6.3, P = 0.04). Compared with no CHD children, the nearest distance from the ventricular wall to the margin of brain abscess in children with CHD is often <7 mm. CONCLUSIONS: Brain abscesses in children with CHD have some special imaging characteristics. Superficial abscesses of 2–5 cm in diameter are the main imaging findings. Brain abscesses of CHD are usually single, while other brain abscesses are usually multiple in children without CHD. Compared with no CHD children, the nearest distance from the ventricular wall to the margin of brain abscess in children with CHD is shorter.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"12 1","pages":"52 - 57"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83060765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computed tomography-aided diagnosis of COVID-19","authors":"Xiao Chen, Qiuyuan Yang, Haijun He, Caiqiong Wang, Z. Peng, Yingchun Liu, Peiqi Wang, Jialei Wu, Bin Yang","doi":"10.4103/rid.rid_23_22","DOIUrl":"https://doi.org/10.4103/rid.rid_23_22","url":null,"abstract":"Coronavirus disease (COVID-19) is highly infectious, has spread worldwide, and has a relatively high mortality rate. Early diagnosis and timely isolation are essential to control the spread of COVID-19. Computed tomography (CT) is considered to be an effective tool for the rapid diagnosis of COVID-19 and plays a key role in diagnosis, clinical course monitoring, and the evaluation of treatment outcomes. Artificial intelligence (AI) has emerged as a useful technology for early diagnosis, lesion quantification, and prognosis evaluation in patients with COVID-19. In this review, we discuss the role of CT in the diagnosis of COVID-19, typical CT manifestations of COVID-19 throughout the disease course, differential diagnoses, and the application of AI as a diagnostic and therapeutic tool in this patient population.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"128 1","pages":"62 - 67"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79558443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic resonance imaging-based radiomics analysis for the assessment of hepatic alveolar echinococcosis biological activity: A preliminary study","authors":"Z. Miao, Ren Bo, Yuwei Xia, Wenya Liu","doi":"10.4103/rid.rid_21_22","DOIUrl":"https://doi.org/10.4103/rid.rid_21_22","url":null,"abstract":"OBJECTIVE: The objective of this study was to develop and evaluate predictive models based on a combination of T2-weighted images (T2WI) and different machine learning algorithms, and to explore the value of hepatic alveolar echinococcosis (HAE) activity assessment by magnetic resonance imaging (MRI) radiomics. MATERIALS AND METHODS: This retrospective study included 136 patients diagnosed with HAE at the First Affiliated Hospital of Xinjiang Medical University between 2012 and 2020. All subjects underwent MRI and positron emission tomography–computed tomography (PET-CT) before surgery. Taking the PET-CT examination results as the reference standard, patients were divided into active (90 cases) and inactive groups (46 cases). The volume of interest of the lesion was manually delineated on T2WI, and quantitative radiomics features were extracted. Synthetic Minority Oversampling Technology was used to balance the number of patients in the categories. To control for redundancy, the least absolute shrinkage and selection operator was used for feature screening after normalization, and ten optimal features were obtained based on correlation coefficient screening. Three machine learning classifiers were trained using five-fold cross-validation and their performance was compared to establish an optimal HAE activity assessment model. The performance of the classifier was evaluated by area under the receiver operating characteristics curve (AUC), sensitivity, specificity, and accuracy (ACC). The ten optimal features selected from each fold were combined using three machine learning algorithms: logistic regression, multilayer perceptron (MLP), and support vector machine, to establish an HAE activity prediction model. RESULTS: The three machine learning classifiers all showed good prediction performance with a mean AUC on the test set of more than 0.80, and the MLP showing the best performance (AUC = 0.830 ± 0.053, ACC = 0.817, sensitivity = 0.822, and specificity = 0.811). CONCLUSION: HAE activity can be accurately evaluated by a radiomics method using a combination of quantitative T2WI features and machine learning.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"36 1","pages":"37 - 46"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85491516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exophytic cystic gastrointestinal stromal tumor mimics hepatic abscess or tumor","authors":"Guisen Lin, RenHua Wu","doi":"10.4103/rid.rid_8_21","DOIUrl":"https://doi.org/10.4103/rid.rid_8_21","url":null,"abstract":"A middle-aged patient presented with epigastric pain, elevated white blood cell count, and mild anemia. Computed tomography (CT) revealed an exophytic gastric mass that mimicked a hepatic abscess or tumor, with intraperitoneal hemorrhage. The mass had heterogeneous texture, interstitial bleeding, and cystic change that showed delayed mild enhancement on multiphase CT. This was consistent with gastrointestinal stromal tumor that was confirmed by pathological and immunohistochemical analysis.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"6 1","pages":"75 - 78"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91278644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of chest radiography in COVID-19: A retrospective observational study in a tertiary care hospital in Southern India","authors":"Badusha Mohammad, Namratha Nandimandalam, Sampath Yerramsetti, Sravani Penumetcha, Bharghav Bathula","doi":"10.4103/rid.rid_11_22","DOIUrl":"https://doi.org/10.4103/rid.rid_11_22","url":null,"abstract":"OBJECTIVES: The objective of this study is to evaluate the clinical profile of coronavirus disease-2019 (COVID-19) patients admitted to our hospital and to correlate their chest radiographic patterns with disease severity. MATERIALS AND METHODS: We retrospectively reviewed 500 patients with COVID-19 confirmed by reverse transcription-polymerase chain reaction who had abnormal baseline chest X-rays (CXRs) at the time of hospital admission. CXRs were characterized based on the site and nature of the lesions. Disease severity was determined using the Radiographic Assessment of Lung Edema (RALE) score. RESULTS: Significant associations were found between (1) the lesion site and patient outcome (P < 0.00001): patients with diffuse and basal infiltrates had high intensive care unit (ICU) admission rates (55.5% and 40%) and mortality rates (30.5% and 20%); (2) the nature of the lesion and patient outcome: patients with ground-glass opacities and consolidation had high mortality (20% and 18%, respectively); and (3) the RALE score and patient outcome: patients with a RALE score >15 had higher ICU admission and mortality rates. CONCLUSIONS: The CXR distribution patterns helped to triage patients and predict outcomes.","PeriodicalId":101055,"journal":{"name":"Radiology of Infectious Diseases","volume":"88 1","pages":"47 - 51"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89552199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}