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Featured researches published by Yun Ge.


Journal of Computer Assisted Tomography | 2016

Whole-Lesion Histogram Analysis of Apparent Diffusion Coefficient for the Assessment of Cervical Cancer.

Yue Guan; Hua Shi; Ying Chen; Song Liu; Weifeng Li; Zhuoran Jiang; Huanhuan Wang; Jian He; Zhengyang Zhou; Yun Ge

Objective The aim of this study was to explore the application of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) values of cervical cancer. Methods A total of 54 women (mean age, 53 years) with cervical cancers underwent 3-T diffusion-weighted imaging with b values of 0 and 800 s/mm2 prospectively. Whole-lesion histogram analysis of ADC values was performed. Paired sample t test was used to compare differences in ADC histogram parameters between cervical cancers and normal cervical tissues. Receiver operating characteristic curves were constructed to identify the optimal threshold of each parameter. Results All histogram parameters in this study including ADCmean, ADCmin, ADC10%–ADC90%, mode, skewness, and kurtosis of cervical cancers were significantly lower than those of normal cervical tissues (all P < 0.0001). ADC90% had the largest area under receiver operating characteristic curve of 0.996. Conclusions Whole-lesion histogram analysis of ADC maps is useful in the assessment of cervical cancer.


Journal of Magnetic Resonance Imaging | 2017

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps.

Yujuan Zhang; Jun Chen; Song Liu; Hua Shi; Wenxian Guan; Changfeng Ji; Tingting Guo; Huanhuan Zheng; Yue Guan; Yun Ge; Jian He; Zhengyang Zhou; Xiaofeng Yang; Tian Liu

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer.


European Radiology | 2017

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

S. Liu; Song Liu; Changfeng Ji; Huanhuan Zheng; Xia Pan; Yujuan Zhang; Wenxian Guan; Ling Chen; Yue Guan; Weifeng Li; Jian He; Yun Ge; Zhengyang Zhou

ObjectivesTo explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.MethodsPreoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed.ResultsMean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, −0.231 ~ −0.324, 0.228 ~ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = −0.265, −0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion.ConclusionCT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers.Key Points• CT texture analysis is noninvasive and effective for gastric cancer.• Portal venous CT images correlated significantly with differentiation degree and Lauren classification.• Standard deviation, entropy and minimum attenuation in arterial phase reflect vascular invasion.


Academic Radiology | 2016

Whole-Lesion Apparent Diffusion Coefficient-Based Entropy-Related Parameters for Characterizing Cervical Cancers: Initial Findings.

Yue Guan; Weifeng Li; Zhuoran Jiang; Ying Chen; Song Liu; Jian He; Zhengyang Zhou; Yun Ge

RATIONALE AND OBJECTIVES This study aimed to develop whole-lesion apparent diffusion coefficient (ADC)-based entropy-related parameters of cervical cancer to preliminarily assess intratumoral heterogeneity of this lesion in comparison to adjacent normal cervical tissues. MATERIALS AND METHODS A total of 51 women (mean age, 49 years) with cervical cancers confirmed by biopsy underwent 3-T pelvic diffusion-weighted magnetic resonance imaging with b values of 0 and 800 s/mm2 prospectively. ADC-based entropy-related parameters including first-order entropy and second-order entropies were derived from the whole tumor volume as well as adjacent normal cervical tissues. Intraclass correlation coefficient, Wilcoxon test with Bonferroni correction, Kruskal-Wallis test, and receiver operating characteristic curve were used for statistical analysis. RESULTS All the parameters showed excellent interobserver agreement (all intraclass correlation coefficients  > 0.900). Entropy, entropy(H)0, entropy(H)45, entropy(H)90, entropy(H)135, and entropy(H)mean were significantly higher, whereas entropy(H)range and entropy(H)std were significantly lower in cervical cancers compared to adjacent normal cervical tissues (all P <.0001). Kruskal-Wallis test showed that there were no significant differences among the values of various second-order entropies including entropy(H)0, entropy(H)45, entropy(H)90, entropy(H)135, and entropy(H)mean. All second-order entropies had larger area under the receiver operating characteristic curve than first-order entropy in differentiating cervical cancers from adjacent normal cervical tissues. Further, entropy(H)45, entropy(H)90, entropy(H)135, and entropy(H)mean had the same largest area under the receiver operating characteristic curve of 0.867. CONCLUSION Whole-lesion ADC-based entropy-related parameters of cervical cancers were developed successfully, which showed initial potential in characterizing intratumoral heterogeneity in comparison to adjacent normal cervical tissues.


Journal of Magnetic Resonance Imaging | 2018

Whole-volume apparent diffusion coefficient-based entropy parameters for assessment of gastric cancer aggressiveness

Song Liu; Huanhuan Zheng; Yujuan Zhang; Ling Chen; Wenxian Guan; Yue Guan; Yun Ge; Jian He; Zhengyang Zhou

To explore the role of whole‐volume apparent diffusion coefficient (ADC)‐based entropy parameters in the preoperative assessment of gastric cancers aggressiveness.


PLOS ONE | 2016

Brain Connectivity Variation Topography Associated with Working Memory

Xiaofei Ma; Xiaolin Huang; Yun Ge; Yueming Hu; Wei Chen; Aili Liu; Hongxing Liu; Ying Chen; Bin Li; Xinbao Ning

Brain connectivity analysis plays an essential role in the research of working memory that involves complex coordination of various brain regions. In this research, we present a comprehensive view of trans-states brain connectivity variation based on continuous scalp EEG, extending beyond traditional stimuli-lock averaging or restriction to short time scales of hundreds of milliseconds after stimulus onset. The scalp EEG was collected under three conditions: quiet, memory, and control. The only difference between the memory and control conditions was that in the memory condition, subjects made an effort to retain information. We started our investigation with calibrations of Pearson correlation in EEG analysis and then derived two indices, link strength and node connectivity, to make comparisons between different states. Finally, we constructed and studied trans-state brain connectivity variation topography. Comparing memory and control states with quiet state, we found that the beta topography highlights links between T5/T6 and O1/O2, which represents the visual ventral stream, and the gamma topography conveys strengthening of inter-hemisphere links and weakening of intra-hemisphere frontal-posterior links, implying parallel inter-hemisphere coordination combined with sequential intra-hemisphere coordination when subjects are confronted with visual stimuli and a motor task. For comparison between memory and control states, we also found that the node connectivity of T6 stands out in gamma topography, which provides strong proof from scalp EEG for the information binding or relational processing function of the temporal lobe in memory formation. To our knowledge, this is the first time for any method to effectively capture brain connectivity variation associated with working memory from a relatively large scale both in time (from a second to a minute) and in space (from the scalp). The method can track brain activity continuously with minimal manual interruptions; therefore, it has promising potential in applications such as brain computer interfaces and brain training.


Medical Imaging Physics and Engineering (ICMIPE), 2013 IEEE International Conference on | 2013

A study on the positioning accuracy of patient positioning based on Optical Positioning System for nasopharyngeal carcinoma: Compared with conventional method

Jie Zhang; Yun Ge; Ying Chen; Xiangning Chen

Purpose: The positioning accuracy of cancer center is an important factor for radiotherapy effect. The purpose of this study is to investigate the accuracy of patient positioning with Optical Positioning System(OPS) developed by Nanjing University in China, and show its superiority on positioning accuracy, compared with conventional method. Materials and Methods: 20 patients with nasopharyngeal carcinoma picked randomly were investigated. Before treatment, all received patient positioning with conventional method, and OPSs function of tracking and positioning was triggered in the meantime. After patient positioning using conventional method was finished, the three positioning errors along three directions displayed on OPS were observed. If error along any direction was greater than 1.0mm, every step of patient positioning was checked to find error source. Results: In 20 clinical datasets, 15 datasets needed to be checked to find error source. Results showed that the difference of positioning results between conventional method and OPS-guided positioning method came from error source introduced in conventional method basically. And, about 66% positioning error comes from the manual operation error introduced in conventional method. Conclusion: This study indicates that OPS can eliminate the effect of almost manual error source introduced in conventional method basically and improve positioning accuracy of 2-5mm for patients with nasopharyngeal carcinoma.


Magnetic Resonance Imaging | 2017

Predicting the nodal status in gastric cancers: The role of apparent diffusion coefficient histogram characteristic analysis

Song Liu; Yujuan Zhang; Jie Xia; Ling Chen; Wenxian Guan; Yue Guan; Yun Ge; Jian He; Zhengyang Zhou

PURPOSE To explore the application of histogram analysis in preoperative T and N staging of gastric cancers, with a focus on characteristic parameters of apparent diffusion coefficient (ADC) maps. MATERIALS AND METHODS Eighty-seven patients with gastric cancers underwent diffusion weighted magnetic resonance imaging (b=0, 1000s/mm2), which generated ADC maps. Whole-volume histogram analysis was performed on ADC maps and 7 characteristic parameters were obtained. All those patients underwent surgery and postoperative pathologic T and N stages were determined. RESULTS Four parameters, including skew, kurtosis, s-sDav and sample number, showed significant differences among gastric cancers at different T and N stages. Most parameters correlated with T and N stages significantly and worked in differentiating gastric cancers at different T or N stages. Especially skew yielded a sensitivity of 0.758, a specificity of 0.810, and an area under the curve (AUC) of 0.802 for differentiating gastric cancers with and without lymph node metastasis (P<0.001). All the parameters, except AUClow, showed good or excellent inter-observer agreement with intra-class correlation coefficients ranging from 0.710 to 0.991. CONCLUSION Characteristic parameters derived from whole-volume ADC histogram analysis could help assessing preoperative T and N stages of gastric cancers.


Acta Radiologica | 2017

Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy

Jie Meng; Lijing Zhu; Li Zhu; Yun Ge; Jian He; Zhengyang Zhou; Xiaofeng Yang

Background Apparent diffusion coefficient (ADC) histogram analysis has been widely used in determining tumor prognosis. Purpose To investigate the dynamic changes of ADC histogram parameters during concurrent chemo-radiotherapy (CCRT) in patients with advanced cervical cancers. Material and Methods This prospective study enrolled 32 patients with advanced cervical cancers undergoing CCRT who received diffusion-weighted (DW) magnetic resonance imaging (MRI) before CCRT, at the end of the second and fourth week during CCRT and one month after CCRT completion. The ADC histogram for the entire tumor volume was generated, and a series of histogram parameters was obtained. Dynamic changes of those parameters in cervical cancers were investigated as early biomarkers for treatment response. Results All histogram parameters except AUClow showed significant changes during CCRT (all P < 0.05). There were three variable trends involving different parameters. The mode, 5th, 10th, and 25th percentiles showed similar early increase rates (33.33%, 33.99%, 34.12%, and 30.49%, respectively) at the end of the second week of CCRT. The pre-CCRT 5th and 25th percentiles of the complete response (CR) group were significantly lower than those of the partial response (PR) group. Conclusion A series of ADC histogram parameters of cervical cancers changed significantly at the early stage of CCRT, indicating their potential in monitoring early tumor response to therapy.


Oncotarget | 2017

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT

Jie Meng; Lijing Zhu; Li Zhu; Li Xie; Huanhuan Wang; Song Liu; Jing Yan; Baorui Liu; Yue Guan; Jian He; Yun Ge; Zhengyang Zhou; Xiaofeng Yang

Purpose To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). Methods 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm2) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. Results With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADCmean, 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). Conclusions Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

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