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Akademický článek

Deep learning and radiomics to predict the mitotic index of gastrointestinal stromal tumors based on multiparametric MRI

Autor: Linsha Yang, Dan Du, Tao Zheng, Lanxiang Liu, Zhanqiu Wang, Juan Du, Huiling Yi, Yujie Cui, Defeng Liu, Yuan Fang

Publikováno v: Frontiers in Oncology, Vol 12 (2022)

IntroductionPreoperative evaluation of the mitotic index (MI) of gastrointestinal stromal tumors (GISTs) represents the basis of individualized treatment of patients. However, the accuracy of conventional preoperative imaging methods is limited. The

Externí odkaz: https://doaj.org/article/88b38df1065e48bc9647661f193a600b

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Akademický článek

The Value of First-Order Features Based on the Apparent Diffusion Coefficient Map in Evaluating the Therapeutic Effect of Low-Intensity Pulsed Ultrasound for Acute Traumatic Brain Injury With a Rat Model

Autor: Dan Du, Yajuan Gao, Tao Zheng, Linsha Yang, Zhanqiu Wang, Qinglei Shi, Shuo Wu, Xin Liang, Xinyu Yao, Jiabin Lu, Lanxiang Liu

Publikováno v: Frontiers in Computational Neuroscience, Vol 16 (2022)

PurposeIn order to evaluate the neuroprotective effect of low-intensity pulsed ultrasound (LIPUS) for acute traumatic brain injury (TBI), we studied the potential of apparent diffusion coefficient (ADC) values and ADC-derived first-order features reg

Externí odkaz: https://doaj.org/article/5becb7a4d29142db9034ba1a156aae99

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Akademický článek

Multi-Parameter MR Radiomics Based Model to Predict 5-Year Progression-Free Survival in Endometrial Cancer

Autor: Defeng Liu, Linsha Yang, Dan Du, Tao Zheng, Lanxiang Liu, Zhanqiu Wang, Juan Du, Yanchao Dong, Huiling Yi, Yujie Cui

Publikováno v: Frontiers in Oncology, Vol 12 (2022)

BackgroundRelapse is the major cause of mortality in patients with resected endometrial cancer (EC). There is an urgent need for a feasible method to identify patients with high risk of relapse.PurposeTo develop a multi-parameter magnetic resonance i

Externí odkaz: https://doaj.org/article/d7961f34e4314c14a7822a0ddc407106

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Akademický článek

Combination Analysis of a Radiomics-Based Predictive Model With Clinical Indicators for the Preoperative Assessment of Histological Grade in Endometrial Carcinoma

Autor: Tao Zheng, Linsha Yang, Juan Du, Yanchao Dong, Shuo Wu, Qinglei Shi, Xiaohan Wang, Lanxiang Liu

Publikováno v: Frontiers in Oncology, Vol 11 (2021)

BackgroundHistological grade is one of the most important prognostic factors of endometrial carcinoma (EC) and when selecting preoperative treatment methods, conducting accurate preoperative grading is of great significance.PurposeTo develop a magnet

Externí odkaz: https://doaj.org/article/972dbe3704c6473fab8dac61416c587c

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Evaluation of risk classifications for gastrointestinal stromal tumor using multi-parameter Magnetic Resonance analysis

Autor: Defeng Liu, Tao Zheng, Qinglei Shi, Zhanqiu Wang, Xiaohan Wang, Shuo Wu, Lanxiang Liu, Juan Du, Yanchao Dong, Linsha Yang

Publikováno v: Abdominal Radiology. 46:1506-1518

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal malignancy of the gastrointestinal tract. At present, it is generally believed that the prognosis of GIST is closely related to its risk classification. It may add value to correctl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7719861844656a24b8c08224806c73a7
https://doi.org/10.1007/s00261-020-02813-y

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MRI Texture‐Based Models for Predicting Mitotic Index and Risk Classification of Gastrointestinal Stromal Tumors

Autor: Qinglei Shi, Shuo Wu, Tao Zheng, Juan Du, Defeng Liu, Zhanqiu Wang, Linsha Yang, Yanchao Dong, Lanxiang Liu

Publikováno v: Journal of Magnetic Resonance Imaging. 53:1054-1065

Background Treatment regimens and prognoses of gastrointestinal stromal tumors (GIST) are quite different for tumors in different risk categories. Accurate preoperative grading of tumors is important for avoiding under- or overtreatment. Purpose To d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::517d410b4d518bdbb02886545d56d8cb
https://doi.org/10.1002/jmri.27390

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