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t2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

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World Journal of Gastrointestinal Oncology 2024年第3期16卷 819-832页

作者： Hui-Da Zheng Qiao-Yi Huang Qi-Ming Huang Xiao-ting Ke Kai Ye Shu Lin Jian-Hua Xu Department of Gastrointestinal Surgery The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Department of Gynaecology and Obstetrics The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Department of Computed tomography/Magnetic Resonance imaging The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Centre of Neurological and Metabolic Research The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Group of Neuroendocrinology Garvan Institute of Medical ResearchSydneyNSW 2010Australia

BACKGROUND the study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported *** a non-invasive model to predict the differentiation grade of CRC is of great *** to develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on t2-weighted images(t2WI).MEtHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July *** were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 *** were delineated layer by layer on high-resolution *** absolute shrinkage and selection operator regression was applied to screen for radiomic *** and clinical models were constructed using the multilayer perceptron(MLP)*** radiomic features and clinically relevant variables(selected based on a significance level of Pthe training set)were used to construct radiomics-clinical *** performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULtS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic *** different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic *** AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation *** AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation *** clinical model achieved an AUC of 0.7

关键词： Radiomics Colorectal cancer Differentiation grade Machine learning t2-weighted imaging

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Comparison of Diagnostic Effects of t2-weighted imaging,DWI,SWI,and DtI in Acute Cerebral Infarction

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Cardiovascular Innovations and Applications 2021年第2期5卷 283-287页

作者： Yu-quan Zheng Xiao-mei Li School of Biomedical Engineering Xinhua College of Sun Yat-Sen UniversityGuangzhou510520China

Objective:to achieve precision medicine,the use of imaging methods to help the clinical detection of cerebral infarction is conducive to the clinical development of a treatment plan and increase of the cure rate and improvement of the prognosis of ***:In this work,t2-weighted imaging(t2WI),diffusion-weighted imaging(DWI),susceptibility-weighted imaging(SWI),and diffusion tensor imaging(DtI)examinations were performed on 34 patients with clinically diagnosed cerebral infarction to measure the difference in signal intensity between the lesion and its mirror area and make a comparative analysis by means of the Student-Newman-Keuls ***:the detection rate of t2WI was 79%(27/34),the detection rate of DWI was 97%(33/34),the detection rate of SWI was 88%(30/34),and the detection rate of DtI was 94%(32/34).Conclusion:the imaging performance was in the order DWI>DtI>SWI>t2WI for the diagnosis of cerebral infarction,and combined imaging is better than single imaging.

关键词： t2-weighted imaging susceptibility-weighted imaging diffusion tensor imaging diffusion-weighted imaging cerebral infarction

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Early brainstem hemorrhage progression:multi-sequence magnetic resonance imaging and histopathology

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Neural Regeneration Research 2023年第1期18卷 170-175页

作者： Xi Guo Jia-Ke Xu Xin Qi Yang Wei Cheng-Wei Wang Hao Li Lu Ma Chao You Meng tian Department of Neurosurgery and Neurosurgery Research Laboratory National Clinical Research Center for GeriatricsWest China HospitalSichuan UniversityChengduSichuan ProvinceChina Department of Integrated traditional and Western Medicine West China HospitalSichuan UniversityChengduSichuan ProvinceChina Department of Rehabilitation People’s Hospital of KaramayKaramayXinjiang Uygur Autonomous RegionChina West China Brain Research Center West China HospitalSichuan UniversityChengduSichuan ProvinceChina

According to clinical statistics,the mortality of patients with early brainstem hemorrhage is *** this study,we established rat models of brainstem hemorrhage by injecting type Ⅶ collagenase into the right basotegmental pontine and investigated the pathological changes of early brainstem hemorrhage using multi-sequence magnetic resonance imaging and histopathological *** found that brainstem hematoma gradually formed in the injured rats over the first 3 days and then reduced after 7 *** edema that occurred was mainly of the vasogenic *** complete myelin sheath structure was found around the focus of the brainstem *** integrity and continuity of nerve fibers gradually deteriorated over the first 7 *** degeneration was mild in the first 3 days and then obviously aggravated on the 7^(th)*** cytokines,interleukin-1β,and tumor necrosis factorαappeared on the 1st day after intracerebral hemorrhage,reached peak levels on the 3^(rd)day,and decreased from the 7^(th)*** findings show the characteristics of the progression of early brainstem hemorrhage.

关键词： brainstem hemorrhage diffuse tensor imaging diffusion-weighted imaging Fluoro-Jade C staining hematoxylin-eosin staining interleukin-1β luxol fast blue rat model t2-weighted imaging tumor necrosis factor-α

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Using endogenous glycogen as relaxation agent for imaging liver metabolism by MRI

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Fundamental Research 2023年第4期3卷 481-487页

作者： Shizhen Chen Mou Jiang Yaping Yuan Baolong Wang Yu Li Lei Zhang Zhong-Xing Jiang Chaohui Ye Xin Zhou State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in WuhanWuhan Institute of Physics and MathematicsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430071China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China University of Chinese Academy of Sciences Beijing 100049China

Glycogen plays essential roles in glucose *** glycogen in the liver,the major glycogen reservoir in the body,may shed new light on many metabolic disorders.^(13)C magnetic resonance spectroscopy(MRS)has become the mainstream method for monitoring glycogen in the ***,the equipment of special hard-ware to standard clinical magnetic resonance imaging(MRI)scanners limits its clinical ***,we utilized endogenous glycogen as a t_(2)-based relaxation contrast agent for imaging glycogen metabolism in the liver in *** in vitro results demonstrated that the transverse relaxation rate of glycogen strongly correlates with the concentration,pH,and field *** on the Swift-Connick theory,we characterized the exchange property of glycogen and measured the exchange rate of glycogen as 31,847 Hz at 37°***,the viscosity and echo spacing showed no apparent effect on the transverse relaxation *** unique feature enables vi-sualization of glycogen signaling in vivo through t_(2)-weighted *** hours-post intraperitoneal injection of glucagon,a clinical drug to promote glycogenolysis and gluconeogenesis,the signal intensity of the mice’s liver increased by 1.8 times from the t_(2)-weighted imaging experiment due to the decomposition of *** study provides a convenient imaging strategy to non-invasively investigate glycogen metabolism in the liver,which may find clinical applications in metabolic diseases.

关键词： Glycogen Magnetic resonance imaging Liver t2-weighted imaging transverse relaxation

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腰椎间盘髓核退变的MRI研究(英文)

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中华临床医师杂志（电子版） 2011年第21期5卷 6351-6357页

作者：孔庆奎张立涛谢元忠付孟莉武玉恒程琮陈绪珠 Department of Medical imaging Tai'an Central Hospital School of Public Health Taishan Medical University Department of Neuroimaging Beijing Tiantan HospitalCapital Medical University

Objective the purpose of this study was to correlate t2 signal intensity values in nucleus pulposus of lumbar discs with patient age,gender and stage of nucleus pulposus *** Lumbar imaging findings of 422 cases subjects were retrospectively reviewed through t2 signal intensity values of nucleus pulposus evaluated based on the signal intensity values of MR t2-weighted mid-sagittal images of the lumbar spine,the t2 signal intensity values at all five lumbar levels (from L5-S1 to L1-L2) between male and female were used independent sample t-test and the Spearman correlation *** age and grade of nucleus pulposus of disc degeneration and t2 signal intensity values were estimated by calculating and Chi-square test and the Spearman correlation *** t-test was used to correlate the different anatomic levels of disc degeneration;t2 signal intensity values among the five different anatomic levels using non-parametric correlation *** there were significantly differences in t2 signal intensity values of nucleus pulposus at the same grade and anatomic level between male and *** with age,t2 signal intensity values of nucleus pulposus decreased and stage of disc degeneration increased accordingly.t2 signal intensity values may represent the nucleus pulposus degeneration of interverterbral disc.L4-L5 was the highest incidence among the nucleus pulposus degeneration of intervertebral *** the t2 signal intensity values based approach may be a feasible and practical tool to determine nucleus pulposus degeneration.t2 signal intensity values of nucleus pulposus of lumbar intervertebral disc are correlated with grade of degeneration and patient age.

关键词： Magnetic resonance imaging t2-weighted imaging Nucleus pulposus degeneration

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