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Objective:To evaluate the value of 18F-FDG PET/CT for preoperative localization of epileptogenic foci in refractory epilepsy patients with negative MRI. Methods:Clinical data (550 lobes) of 55 epilepsy patients (38 males, 17 females, age (20.0±8.1) years) with negative MRI who underwent preoperative 18F-FDG PET/CT-MRI between January 2014 and June 2020 at the First Affiliated Hospital of Jinan University were retrospectively analyzed. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of 18F-FDG PET/CT, video electroencephalogram (VEEG), PET/CT+ VEEG and PET/CT-VEEG for localizing epileptogenic foci were calculated using stereoelectroencephalography (SEEG) and the outcomes of at least 1 year of postoperative follow-up as reference standards. χ2 test was used to compare the efficiencies of different examination modalities for unilobar, multilobar and all patients. Results:The correct lateralization rate of epileptogenic foci was 92.6%(25/27) using PET/CT. The sensitivity, specificity, accuracy, PPV and NPV of PET/CT for localization of epileptogenic foci were 65.1%(54/83), 77.9%(364/467), 76.0%(418/550), 34.4%(54/157) and 92.6%(364/393), respectively. The sensitivities of PET/CT-VEEG for localization of epileptogenic foci in all patients and patients with multilobar epilepsy were higher than those of VEEG alone (75.9%(63/83) vs 45.8%(38/83), 68.6%(35/51) vs 31.4%(16/51); χ2 values: 15.80, 14.16, both P<0.001). The specificities of PET/CT+ VEEG for localization of epileptogenic foci in all patients and patients with unilobar epilepsy were higher than those of VEEG alone (97.6%(456/467) vs 94.6%(442/467), 97.9%(282/288) vs 94.1%(271/288); χ2 values: 5.66, 5.48; P values: 0.017, 0.019). The sensitivity of PET/CT-VEEG (PET/CT and VEEG concordance) for localization of epileptogenic foci was higher than that of PET/CT+ VEEG (PET/CT and VEEG discordance) (8/9 vs 28.4%(21/74); χ2=10.40, P=0.001), and its specificity and accuracy were higher than those of PET/CT-VEEG (PET/CT and VEEG discordance) (93.4%(57/61) vs 71.7%(291/406), 92.9%(65/70) vs 72.1%(346/480); χ2 values: 13.23, 13.96; both P<0.001). Conclusions:18F-FDG PET/CT can localize and lateralize epileptogenic foci in patients with negative MRI. The combination of 18F-FDG PET/CT and VEEG improves the sensitivity, specificity, and accuracy for epileptogenic foci detection. 18F-FDG PET/CT is more accurate in detecting epileptogenic foci when it is concordant with VEEG.
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Objective:To predict the short-term postoperative recurrence status of patients with refractory temporal lobe epilepsy (TLE) by analyzing preoperative 18F-FDG PET images and patients′ clinical characteristics based on deep residual neural network (ResNet). Methods:Retrospective analysis was conducted on preoperative 18F-FDG PET images and clinical data of 220 patients with refractory TLE (132 males and 88 females, age 23.0(20.0, 30.2) years)) in the First Affiliated Hospital of Jinan University between January 2014 and June 2020. ResNet was used to perform high-throughput feature extraction on preprocessed PET images and clinical features, and to perform a postoperative recurrence prediction task for differentiating patients with TLE. The predictive performance of ResNet model was evaluated by ROC curve analysis, and the AUC was compared with that of classical Cox proportional risk model using Delong test. Results:Based on PET images combined with clinical feature training, AUCs of the ResNet in predicting 12-, 24-, and 36-month postoperative recurrence were 0.895±0.073, 0.861±0.058 and 0.754±0.111, respectively, which were 0.717±0.093, 0.697±0.081 and 0.645±0.087 for Cox proportional hazards model respectively ( z values: -3.00, -2.98, -1.09, P values: 0.011, 0.018, 0.310). The ResNet showed best predictive effect for recurrence events within 12 months after surgery. Conclusion:The ResNet model is expected to be used in clinical practice for postoperative follow-up of patients with TLE, helping for risk stratification and individualized management of postoperative patients.
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Diabetes mellitus is a chronic disease, it is thus necessary for its patients to participate in its treatment and self-management. The emerging foreign and domestic methods for self-management of diabetes mellitus pa-tients were detected on different Websites and suggestions were proposed for its treatment and self-management in order to improve the quality of life in diabetes mellitus patients.
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Using the concept and method of evidence-based medicine,the paper systematically analyzes the functions and shortage of intelligent health Application (App) in disease diagnosis,treatment and self-management,and describes the functions of health and disease management App,so as to promote the development of App and enable App to better assist in health management.
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How to effectively using the electronic health records (EHR) in contracted family doctors service was studied according to the new model of HER-based community medical service with community health service station as a center in combination with large hospitals,and suggestions were put forward for the solution of problems in contracted family doctor service,namely establishing and perfecting the community health service system,enlarging the scale of HER,strengthening the construction of general doctors team,and training the technically competent community health service staff.