Yongqi Chen

Yongqi Chen

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Yongqi Chen has a total of 12 co-authors. Here are the top co-authors by number of shared publications:

  • Bin Chang

    Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China

    1 shared publication
  • Bin Song

    Department of Radiology, Minhang Hospital, Fudan University

    1 shared publication
  • Hao Wang

    Department of Radiology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China

    1 shared publication
  • Hua Sui

    Medical Experiment Center, Jiading Branch of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201803, China

    1 shared publication
  • Jiao Meng

    Department of Pathology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China

    1 shared publication
  • Qing Ji

    Department of Medical Oncology & Cancer Institute of Integrative Medicine, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China

    1 shared publication

Latest Publications

  • Zuojin Wan reverses cetuximab resistance in KRAS-mutant colorectal cancer via the NRF2-GCH1/CoQ and DHODH/CoQ axes

    by Xiaodie Liu, Yongqi Chen, Yulang Jiang, Hua Sui, Tingyu Liang, Jiao Meng, Bin Chang, Qing Ji, Ziyuan Wang

  • Open Access

    Diagnostic efficacy of multiple MRI parameters in differentiating benign vs. malignant thyroid nodules

    by Hao Wang, Ran Wei, Weiyan Liu, Yongqi Chen, Bin Song

    Diffusion weighted imaging (DWI) has a good diagnostic value for malignant thyroid nodules, but the published protocols suffer from flaws and focus on the apparent diffusion coefficient (ADC). This study investigated the diagnostic performance of multiple MRI parameters in differentiating malignant from benign thyroid nodules. This was a retrospective study of 181 consecutive patients (148 benign and 111 malignant nodules, confirmed by pathological results). The patients underwent conventional MRI, DWI, and dynamic contrast-enhanced MRI before surgery. The chi-square test and the Student t test were used to compare the conventional features and ADC value between malignant and benign groups. Multivariate logistic regression was used to identify the independent predictors and to construct a model. Receiver operator characteristic (ROC) curve analysis was used to assess the diagnostic performance of the independent variables and model. Tumor diameter, ADC value, cystic degeneration, pseudocapsule sign, high signal cystic area on T1-weighted imaging, ring sign in the delayed phase, and irregular shape showed significant differences between two groups (all P < 0.05). The multivariable analysis revealed that ADC value (OR = 694.006, P < 0.001), irregular shape (OR = 32.798, P < 0.001), ring sign in the delayed phase (OR = 20.381, P = 0.004), and cystic degeneration (OR = 8.468, P = 0.016) were independent predictors. Among them, ADC performed the best in discriminating benign from malignant nodules, with an area under the curve (AUC) of 0.95, 0.90 sensitivity, and 0.91 specificity. When the independent factors were combined, the diagnostic performance was improved with an AUC of 0.99, 0.97 sensitivity, and 0.95 specificity. ADC value could discriminate between benign and malignant thyroid nodules with a good performance. Subjective features such as the ring sign, irregular shape, and cystic degeneration associated with malignant thyroid nodules could provide complementary information for differentiation.