1.Magnetic resonance compatibility research for coronary mental stents.
Ying WANG ; Li LIU ; Shuo WANG ; Ruyao SHANG ; Chunren WANG
Chinese Journal of Medical Instrumentation 2015;39(1):61-63
The objective of this article is to research magnetic resonance compatibility for coronary mental stents, and to evaluate the magnetic resonance compatibility based on laboratory testing results. Coronary stents magnetic resonance compatibility test includes magnetically induced displacement force test, magnetically induced torque test, radio frequency induced heating and evaluation of MR image. By magnetic displacement force and torque values, temperature, and image distortion values to determine metal coronary stent demagnetization effect. The methods can be applied to test magnetic resonance compatibility for coronary mental stents and evaluate its demagnetization effect.
Equipment Design
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Magnetic Resonance Imaging
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Magnetics
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Metals
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Radio Waves
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Stents
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standards
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Temperature
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Torque
2.Primary exploration of energy spectral CT water -based material decomposition technology for the detection of bone marrow edema in sacroiliitis
Zhongjie HUANG ; Fenxiong LIANG ; Ruyao ZHUANG ; Zhengyu XIAO ; Yuan LIU
Chinese Journal of Primary Medicine and Pharmacy 2017;24(4):481-484
Objective To explore the value of water -based material decomposition images for detection of bone marrow edema (BME)in sacroiliitis with energy spectral CT.Methods The sacroiliac (SI)joints of nine spondyloarthropathy patients with sacroiliitis (the research group)and eight healthy volunteers (the control group) were underwent MRI and energy spectral CT.The mixed energy image of energy spectral CT was reconstructed to be mono energy image.Then,the mono image was divided into water -based image and calcium image by material divid-ed and analyzed software.The SI para -articular marrow region water -calcium relative concentration of research group was compared with that of control group.The BME diagnosis efficiency and optimal water -based concentration of energy spectral CT was analyzed by receiver operating characteristic (ROC)curve.Then,the sensitivity,specificity, positive likelihood ratio and negative likelihood ration were calculated.Results The water -based concentration of BME in research group (1 067.43 ±10.84)g/L was higher than that of control group (1 039.43 ±8.01)g/L(t =-3.14,P =0.003).Meanwhile,the calcium -based concentration of research group (68.98 ±20.53)g/L was not different from control group (78.03 ±26.39)g/L(t =1.88,P =0.066).ROC curve showed that the diagnosis efficiency was medium as the area of under curve was 0.75.When the optimal concentration of water -based was 1 052.00g/L,the diagnosis efficiency was the best.The sensitivity and specificity was 84.00%,62.50% respectively. Conclusion There are reference value and potential clinical value with energy spectral CT water -based concentra-tion detection for diagnosis BME in patients with sacroiliitis.
3.Evaluation of DWI in detecting active sacroiliitis in patients with axial spondyloarthritis
Ruyao ZHUANG ; Shitao GUO ; Zhongjie HUANG ; Zhengyu XIAO ; Yuan LIU
Chinese Journal of Primary Medicine and Pharmacy 2014;(19):2890-2893
Objective To evaluate the value of DWI in detecting active sacroiliitis in patients with axial spondyloarthritis ( SpA) .Methods DWI and conventional MRI examinations were done oblique coronary on bilateral SIJs of 19 participants,involving 8 patients (the case group) underwent clinical and conventional MRI evaluation for axial SpA active sacroiliitis and 11 healthy volunteers(the control group).The conventional MRI,DWI,ADC,EADC images were transmitted to two experienced radiologists respectively to read ,evaluate and measure ( the ADC values and EADC values ) at the workstation under the blind method .The experimental data were inputted and analyzed by statistics software .Results In the control group ,the periarticular bone marrow in the SIJ showed hopyintense signal on the DWI image ,hypointense signal on the ADC image and hyperintense signal on the EADC image .The periarticu-lar bone marrow oedema showed hyperintense signal on the DWI and ADC images , while hopyintense signal on the EADC image.At b values of 300s/mm2 ,the ADC values of the periarticular bone marrow oedema at each side in the case group were significantly higher than those in the control group , while EADC values were lower , the difference were statistically significant(Z=-3.115,-2.814,-3.002,-3.115,-3.115,-2.714,-2.889,-3.115,all P<0.05).Conclusion DWI can directly detect the signal changes ,extent of the periarticular bone marrow oedema , and analyze the severity of oedema quantitively ,which shows the utility in determining the activity and early diagnosis .
4.Clinical and imaging analysis on meningiomas initially manifesting as intracranial hemorrhage in 19 cases
Ruibin HUANG ; Shuyan SU ; Huanpeng WANG ; Ruyao ZHUANG ; Yuan LIU
Chinese Journal of Primary Medicine and Pharmacy 2022;29(12):1783-1788
Objective:To investigate the main clinical characteristics, imaging features, diagnosis, and treatment of meningiomas initially manifesting as spontaneous intracranial hemorrhage.Methods:The clinical characteristics, imaging features, treatment, and follow-up data of 19 patients with meningiomas initially manifesting as spontaneous intracranial hemorrhage who received treatment in The First Affiliated Hospital of Shantou University Medical College from January 2011 to December 2020 were retrospectively analyzed.Results:Among the 19 patients, there were 6 males and 13 females, with an average age of (53 ± 14) years. The onset manifestations were sudden and severe headache and vomiting in 6 cases, progressive coma in 4 cases, and hemiplegia in 9 cases. Among the 19 patients, 15 patients showed irregular tumor shape and mixed hyperintense signal in CT, and 4 patients showed a homogeneous hyperintense signal. Eighteen patients showed peritumoral edema. Three patients showed intratumoral calcification. One patient showed an intratumoral fluid level. Fourteen patients showed isointense to hypointense signals on T1WI images and isointense to hyperintense signals on T 2WI images. Five patients showed mixed isointense and hyperintense signals on T 1WI images and mixed hypointense and hyperintense signals on T 2WI images. Heterogeneous enhancement was found in 18 patients, intratumoral cystic necrosis was found in 15 patients, and the meningeal tail sign was found in 16 patients. Preoperative imaging misdiagnosis occurred in 4 patients. Before surgery, all patients underwent surgery to resect the tumor and remove the hematoma. No patients died because of surgery. After surgery, muscle strength was improved compared with that before surgery. The average follow-up time was (46.5 ± 28.4) months. Tumor recurrence occurred in two patients. The Karnofsky Performance Scale score at the last follow-up, at discharge, and before surgery was (73.7 ± 3.4) points, (61.1 ± 5.5) points, and (49.5 ± 5.6) points, respectively ( F = 21.06, P < 0.01). The Karnofsky Performance Scale score at the last follow-up was significantly increased compared with that at discharge and before surgery ( F = 13.13, P < 0.01). Conclusion:Spontaneous hemorrhagic meningioma is rare and has a sudden onset. It is easily misdiagnosed before surgery. Skull CT, skull CT angiography, and enhanced magnetic resonance imaging examination in combination can increase the preoperative diagnosis rate. Early surgical resection of tumors and removal of hematoma can acquire good clinical efficacy.
5.A nomogram model for predicting malnutrition after a tracheotomy
Ang CAI ; Junfeng YANG ; Ruyao LIU ; Le WANG ; Yi LI ; Liugen WANG ; Heping LI ; Xi ZENG
Chinese Journal of Physical Medicine and Rehabilitation 2024;46(3):199-204
Objective:To explore the risk factors for malnutrition after a tracheotomy and to construct a predictive model useful for its prevention through early intervention.Methods:Clinical data describing 440 tracheotomy patients were subjected to a retrospective analysis. The variables examined were age, sex, etiology, Glasgow Coma Score (GCS), activities of daily living (ADL) score, age-corrected Charlson comorbidity index (aCCI), food intake, swallowing function, incidence of infections, as well as any history of diabetes mellitus, hypertension, smoking or alcohol consumption. Patients identified as being at risk of malnutrition (NRS-2002≥3) were screened using the Nutritional Risk Screening tool (NRS-2002) and the European Society of Clinical Nutrition and Metabolism′s ESPEN2015 criteria. The subjects were thus categorized into a malnutrition group of 343 and a control group of 97. Unifactorial and multifactorial logistic regression analyses were performed, and stepwise regression was applied to include the factors found significant in the unifactorial analysis into the multifactorial logistic regression analysis, and to construct a column-line graph prediction model. The clinical utility of the model was assessed by applying the receiver operator characteristics (ROC) curves, calibration plots and decision curve analysis (DCA).Results:Of the 440 persons studied, 343 (78%) were malnourished. The multivariate logistic regression analysis showed that pulmonary infection, dysphagia, low GCS score and high aCCI score were significant risk factors for malnutrition after a tracheotomy. A prediction nomograph was constructed. After fitting and correcting, the area under the curve (AUC) of the prediction model′s ROC curve was 0.911, the specificity was 80.4%, and the sensitivity was 91.3%. That was significantly higher than the AUCs for pulmonary infection (0.809), dysphagia (0.697), aCCI (0.721) and GCS (0.802). Bootstrap self-sampling was used to verify the model internally. After 1000 samples the average absolute error between the predicted risk and the actual risk was 0.013, indicating good prediction ability. The DCA results demonstrated that the model has substantial clinical applicability across a range of nutritional interventions, particularly for threshold probability values ranging from 0 to 0.96.Conclusion:Pulmonary infection, dysphagia, low GCS score, and high aCCI score are risk factors for malnutrition among tracheotomy patients. The nomogram model constructed in this study has good predictive value for the occurrence of malnutrition among such patients.