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Factors in Pi-Rads 3 and 4 Prostate Lesions that Predict The Risk of Clinically Significant Cancer

机译：Pi-rads 3和4前列腺病变中的因素预测临床显着癌症的风险

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作者
Swallow, Matthew.;
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作者单位

Yale University.;

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授予单位 Yale University.;
学科
学位 M.D.
年度 2019
页码 48 p.
总页数 48
原文格式 PDF
正文语种 eng
中图分类 AAI13856980;
关键词
Prostate Lesions; Cancer;

机译：前列腺病变;癌症;

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1. Which clinical and radiological characteristics can predict clinically significant prostate cancer in PI-RADS 3 lesions? A retrospective study in a high-volume academic center [J] . Hermie Isabeau, Van Besien Jeroen, De Visschere Pieter, European Journal of Radiology . 2019,第期

机译：哪种临床和放射性特征可以预测PI-rads 3病变中的临床显着的前列腺癌？高批量学术中心的回顾性研究
2. Prostate cancer gene 3 (PCA3) is of additional predictive value in patients with PI-RADS grade III (intermediate) lesions in the MR-guided re-biopsy setting for prostate cancer [J] . Kaufmann S., Bedke J., Gatidis S., World journal of urology . 2016,第4期

机译：前列腺癌的MR引导下再活检设置中，前列腺癌基因3（PCA3）对于PI-RADS III级（中度）病变的患者具有额外的预测价值
3. Impact of PI-RADS Category 3 lesions on the diagnostic accuracy of MRI for detecting prostate cancer and the prevalence of prostate cancer within each PI-RADS category: A systematic review and meta-analysis [J] . Wadera Akshay, Alabousi Mostafa, Pozdnyakov Alex, British Journal of Radiology . 2021,第1118期

机译：Pi-rads类别3病变对每个PI-RAD碱解前列腺癌及前列腺癌患病率的MRI诊断准确性的影响：系统审查和荟萃分析
4. Comparison between 3D ARFI imaging and mpMRI in detecting clinically-significant prostate cancer lesions [C] . Mark Palmeri, Tyler Glass, Rajan Gupta, IEEE International Ultrasonics Symposium . 2016

机译：3D ARFI成像和mpMRI在检测具有临床意义的前列腺癌病变中的比较
5. Predicting Imminent Suicide Risk among U.S. Military Veterans: Incremental Predictive Validity of the Brief Agitation Measure over Traditional Risk Factors and Clinical Judgment [D] . Akins, Christopher F. 2019

机译：预测美国军事退伍军人之间的迫在眉睫的自杀风险：对传统风险因素和临床判断的简要激动措施的增量预测有效性
6. Predicting clinically significant prostate cancer from quantitative image features including compressed sensing radial MRI of prostate perfusion using machine learning: comparison with PI-RADS v2 assessment scores [O] . David Jean Winkel, Hanns-Christian Breit, Bibo Shi, 2020

机译：使用机器学习从定量图像特征（包括前列腺灌注的压缩传感放射线MRI）定量图像特征预测具有临床意义的前列腺癌：与PI-RADS v2评估得分的比较
7. MP24-12 PSA DERIVED BIOMARKERS PREDICT CLINICALLY SIGNIFICANT CANCER ON POST-MRI BIOPSY IN PATIENTS WITH PROSTATE IMAGING REPORTING AND DATA SYSTEM (PI-RADS) CATEGORY 3 LESIONS [O] . Andrew M Wood*, Andre Perez-Orozco, Daniel Rabinowitz, 2019

机译：MP24-12 PSA衍生的生物标志物预测前列腺成像报告和数据系统（PI-RADS）第3类病变患者的MRI活检临床显着癌症

Factors in Pi-Rads 3 and 4 Prostate Lesions that Predict The Risk of Clinically Significant Cancer

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