Yingyan Zheng

Children's Hospital of Fudan University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Qingwu Jiang

Fudan University

Yibiao Zhou

Fudan University

Dairong Cao

First Affiliated Hospital of Fujian Medical University

Dejun She

First Affiliated Hospital of Fujian Medical University

Bo Yin

Fudan University

Yiping Lu

Second Affiliated Hospital of Nanchang University

Zebin Xiao

University of Pennsylvania

Yingjian Wang

Army Medical University

Yueqin Shao

Shanghai Municipal Center For Disease Control Prevention

Ying Shi

Zhejiang University

Cooperative Institutions

Fudan University

Fujian Medical University

Huashan Hospital

Chinese Academy of Sciences

First Affiliated Hospital of Fujian Medical University

Chinese Academy of Medical Sciences & Peking Union Medical College

Peking University

University of Chinese Academy of Sciences

Nanjing Medical University

Sun Yat-sen University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Machine learning algorithms to predict the 1 year unfavourable prognosis for advanced schistosomiasis

International Journal for Parasitology (2021)

Honglin Jiang Weicheng Deng Jie Zhou Guang-hui Ren Cai Xin-Ting

10.1016/j.ijpara.2021.03.004

Cite

Citations (17)

The Evaluation of Radiomic Models in Distinguishing Pilocytic Astrocytoma From Cystic Oligodendroglioma With Multiparametric MRI

Journal of Computer Assisted Tomography (2020)

Yajing Zhao Yiping Lu Xuanxuan Li Yingyan Zheng Bo Yin

Purpose To assess whether a machine-learning model based on texture features extracted from multiparametric magnetic resonance imaging could yield an accurate diagnosis in differentiating pilocytic astrocytoma from cystic oligodendrogliomas. Materials and Methods The preoperative images from multisequences were used for tumor segmentation. Radiomic features were extracted and selected for machine-learning models. Semantic features and selected radiomic features from training data set were built, and the performance of each model was evaluated by receiver operating characteristic curve and accuracy from isolated testing data set. Results In terms of different sequences, the best classifier was built by radiomic features extracted from enhanced T1WI-based classifier. The best model in our study turned out to be the gradient boosted trees classifier with an area under curve value of 0.99. Conclusion Our study showed that gradient boosted trees based on texture features extracted from enhanced T1WI could become an additional tool for improving diagnostic accuracy to differentiate pilocytic astrocytoma from cystic oligodendroglioma.

Pilocytic astrocytoma

10.1097/rct.0000000000001088

Cite

Citations (7)

Characterization of parotid gland tumors: Whole-tumor histogram analysis of diffusion weighted imaging, diffusion kurtosis imaging, and intravoxel incoherent motion – A pilot study

European Journal of Radiology (2023)

Yu Chen Nan Huang Yingyan Zheng Feng Wang Dairong Cao

Intravoxel incoherent motion

Kurtosis

10.1016/j.ejrad.2023.111199

Cite

Citations (1)

Benign and malignant skull-involved lesions: discriminative value of conventional CT and MRI combined with diffusion-weighted MRI

Acta Radiologica (2018)

Zhanhai Tu Zebin Xiao Yingyan Zheng Hongjie Huang Libin Yang

Background Little is known about the value of computed tomography (CT) and magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in distinguishing malignant from benign skull-involved lesions. Purpose To evaluate the discriminative value of DWI combined with conventional CT and MRI for differentiating between benign and malignant skull-involved lesions. Material and Methods CT and MRI findings of 58 patients with pathologically proven skull-involved lesions (43 benign and 15 malignant) were retrospectively reviewed. Conventional CT and MRI characteristics and apparent diffusion coefficient (ADC) value of the two groups were evaluated and compared. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter separately and together. Results The presence of cortical defects or break-through and ill-defined margins were associated with malignant skull-involved lesions (both P < 0.05). Malignant skull-involved lesions demonstrated a significantly lower ADC ( P = 0.016) than benign lesions. ROC curve analyses indicated that a combination of CT, MRI, and DWI with an ADC ≤ 0.703 × 10 –3 mm 2 /s showed optimal sensitivity, while DWI along showed optimal specificity of 88.4% in differentiating between benign and malignant skull-involved lesions. Conclusion The combination of CT, MRI, and DWI can help to differentiate malignant from benign skull-involved lesions. CT + MRI + DWI offers optimal sensitivity, while DWI offers optimal specificity.

10.1177/0284185118773541

Cite

Citations (9)

A cation exchange strategy to construct a targeting nanoprobe for enhanced T₁-weighted MR imaging of tumors

Journal of Materials Chemistry B (2020)

Siyu Chen Qin Zhang Haitao Sun Yingyan Zheng Qian Chen

Excellent imaging performance and good biocompatibility of contrast agents are considered as prerequisites for accurate tumor diagnosis. In this study, a novel imaging nanoprobe with actively targeting performance based on ultrasmall paramagnetic iron oxide (USPIO) nanoparticles was constructed by a facile cation exchange strategy followed by conjugation with transferrin (Tf). The stable gadolinium (Gd3+) chelation endows the nanoparticles (NPs) with a low value of r2/r1 (1.28) and a relatively high r1 value of 3.2 mM-1 s-1, enabling their use for T1-weighted positive magnetic resonance (MR) imaging. This constructed transferrin modified gadolinium-iron chelate nanoprobe, named as TUG, shows high biocompatibility within a given dose range. More importantly, compared with clinically used Gd-based small molecule contrast agents, the obtained TUG can be more engulfed by breast cancer cells, showing much enhanced T1-weighted positive MR imaging in both subcutaneous and orthotopic tumor models of breast cancer. This novel nanoprobe holds great promise to be utilized as a targeting contrast agent with high efficacy for T1-weighted positive MR imaging.

Nanoprobe

Biocompatibility

10.1039/d0tb01632b

Cite

Citations (5)

Impact of vascular supply variability on the prognosis of meningioma patients: a retrospective study based on territory arterial spin labeling

Quantitative Imaging in Medicine and Surgery (2024)

Yuqi Zhu Xiaoyu Gu Mengdi Gao Xuanxuan Li Yajing Zhao

Territorial arterial spin labelling (t-ASL) could be an alternative method to digital subtraction angiography (DSA) when evaluating feeding arteries by previous reports, however, blood supply variations on meningioma prognosis remains unclear. In this study, the prognosis of meningiomas mainly supplied by the internal carotid artery (ICA) and external carotid artery (ECA) was compared, and relevant clinical factors were investigated.

Blood supply

10.21037/qims-24-1010

Cite

Citations (0)

Performances of Clinical Characteristics and Radiological Findings in Identifying COVID- 19 From Suspected Cases

Research Square (Research Square) (2021)

Xuanxuan Li Yajing Zhao Yiping Lu Yingyan Zheng Nan Mei

Abstract Background: To identify effective factors and establish a model to distinguish COVID-19 patients from suspected cases. Methods: The clinical characteristics, laboratory results and initial chest CT findings of suspected COVID-19 patients in 3 institutions were retrospectively reviewed. Univariate and multivariate logistic regression were performed to identify significant features. A nomogram was constructed, with calibration validated internally and externally. Results: 239 patients from 2 institutions were enrolled in the primary cohort including 157 COVID-19 and 82 non-COVID-19 patients. 11 features were included for multivariate logistic regression analysis after LASSO selection. We found that the COVID-19 group are more likely to have fever (OR, 4.22), contact history (OR, 284.73), lower WBC count (OR, 0.63), left lower lobe involvement (OR, 9.42), multifocal lesions (OR, 8.98), pleual thickening (OR, 5.59), peripheral distribution (OR, 0.09), and less mediastinal lymphadenopathy (OR, 0.037). The nomogram developed accordingly for clinical practice showed satisfactory internal and external validation. Conclusions: In conclusion, fever, contact history, decreased WBC count, left lower lobe involvement, pleural thickening, multifocal lesions, peripheral distribution and absence of mediastinal lymphadenopathy are able to distinguish COVID-19 patients from other suspected patients. The corresponding nomogram is a useful tool in clinical practice.

Nomogram

Univariate

Univariate analysis

Mediastinal lymphadenopathy

10.21203/rs.3.rs-1077250/v1

Cite

Citations (0)

Prognostic value of pretreatment MRI texture features in breast cancer brain metastasis treated with Gamma Knife radiosurgery

Acta Radiologica (2020)

Yingyan Zheng Daoying Geng Tonggang Yu Wei Xia Dejun She

Background Gamma Knife radiosurgery (GKS) was recommended for treating patients with breast cancer brain metastasis (BCBM), but predictions of the existing prognostic models for therapeutic responsiveness vary substantially. Purpose To investigate the prognostic value of pretreatment clinical, MRI radiologic, and texture features in patients with BCBM undergoing GKS. Material and Methods The data of 81 BCBMs in 44 patients were retrospectively reviewed. Progressive disease was defined as an increase of at least 20% in the longest diameter of the target lesion or the presence of new intracranial lesions on contrast-enhanced T1-weighted (CE-T1W) imaging. Radiomic features were extracted from pretreatment CE-T1W images, T2-weighted (T2W) images, and ADC maps. Cox proportional hazard analyses were performed to identify independent predictors associated with BCBM-specific progression-free survival (PFS). A nomogram was constructed and its calibration ability was assessed. Results The cumulative BCBM-specific PFS was 52.27% at six months and 11.36% at one year, respectively. Age (hazard ratio [HR] 1.04; 95% confidence interval [CI] 1.01–1.06; P = 0.004) and CE-T1W-based kurtosis (HR 0.72; 95% CI 0.57–0.92; P = 0.008) were the independent predictors. The combination of CE-T1W-based kurtosis and age displayed a higher C-index (C-index 0.70; 95% CI 0.63–0.77) than did CE-T1W-based kurtosis (C-index 0.65; 95% CI 0.57–0.73) or age (C-index 0.63; 95% CI 0.56–0.70) alone. The nomogram based on the combinative model provided a better performance over age ( P < 0.05). The calibration curves elucidated good agreement between prediction and observation for the probability of 7- and 12-month BCBM-specific PFS. Conclusion Pretreatment CE-T1W-based kurtosis combined with age could improve prognostic ability in patients with BCBM undergoing GKS.

Nomogram

Kurtosis

10.1177/0284185120956296

Cite

Citations (7)

Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging

Neuroradiology (2019)

Tanhui Chen Jiang Bing-qing Yingyan Zheng Dejun She Hua Zhang

Susceptibility Weighted Imaging

Neuroradiology

Hemangiopericytoma

10.1007/s00234-019-02307-9

Cite

Citations (46)

MRI characteristics predict BRAF V600E status in gangliogliomas and pleomorphic xanthoastrocytomas and provide survival prognostication

Acta Radiologica (2023)

Jiang Bing-qing Yingyan Zheng Dejun She Zhen Xing Dairong Cao

Background BRAF V600E mutation is a common genomic alteration in gangliogliomas (GGs) and pleomorphic xanthoastrocytomas (PXAs) with prognostic and therapeutic implications. Purpose To investigate the ability of magnetic resonance imaging (MRI) features to predict BRAF V600E status in GGs and PXAs and their prognostic values. Material and Methods A cohort of 44 patients with histologically confirmed GGs and PXAs was reviewed retrospectively. BRAF V600E status was determined by immunohistochemistry (IHC) staining and fluorescence quantitative polymerase chain reaction (PCR). Demographics and MRI characteristics of the two groups were evaluated and compared. Univariate and multivariate Cox regression analyses were performed to identify MRI features that were prognostic for progression-free survival (PFS). Results T1/FLAIR ratio, enhancing margin, and mean relative apparent diffusion coefficient (rADC mea ) value showed significant differences between the BRAF V600E-mutant and BRAF V600E-wild groups (all P < 0.05). Binary logistic regression analysis revealed only rADC mea value was the independent predictive factor for BRAF V600E status ( P = 0.027). Univariate Cox regression analysis showed age at diagnosis ( P = 0.032), WHO grade ( P = 0.020), enhancing margin ( P = 0.029), and rADC mea value ( P = 0.005) were significant prognostic factors for PFS. In multivariate Cox regression analysis, increasing age ( P = 0.040, hazard ratio [HR] = 1.04, 95% confidence interval [CI] = 1.002–1.079) and lower rADC mea values ( P = 0.021, HR = 0.036, 95% CI = 0.002–0.602) were associated with poor PFS in GGs and PXAs. Conclusion Imaging features are potentially predictive of BRAF V600E status in GGs and PXAs. Furthermore, rADC mea value is a valuable prognostic factor for patients with GGs or PXAs.

Univariate analysis

10.1177/02841851231183868

Cite

Citations (1)