根据不同MRI序列的关节强度分布计算的纹理特征能否准确预测前列腺癌症分级?

V. Stavrinides, L. C. Echeverria, H. Whitaker
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引用次数: 0

摘要

从前列腺特异性抗原(PSA)检测到允许疾病可视化的令人兴奋的新技术,从随机采样到靶向活检,癌症的诊断格局已经迅速发展。多参数磁共振成像(mpMRI)是一种新的模式,它结合了T2加权(T2W)、扩散加权(DW)和动态对比增强(DCE)序列,每种序列都旨在揭示通常与恶性肿瘤相关的特定微观结构特征,如血管和细胞增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Can texture features computed from the joint intensity distribution of different MRI sequences accurately predict prostate cancer grade?
The diagnostic landscape of prostate cancer has evolved rapidly, from prostate-specific antigen (PSA) testing to exciting new technologies that allow visualization of the disease, moving away from random sampling to targeted biopsies. Multiparametric magnetic resonance imaging (mpMRI) is a new modality that combines T2-weighted (T2W), diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) sequences, each designed to reveal specific microstructural features typically associated with malignancy such as increased vascularity and cellularity.
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CiteScore
2.30
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