Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode.

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode.
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DOI:
10.1016/j.ultrasmedbio.2020.08.022
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发表时间:
2020-12
影响因子:
2.9
通讯作者:
Nightingale KR
Nightingale KR
中科院分区:
医学3区
文献类型:
--
作者:
Morris DC;Chan DY;Lye TH;Chen H;Palmeri ML;Polascik TJ;Foo WC;Huang J;Mamou J;Nightingale KR

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由于B型成像的灵敏度和特异性限制,通过标准经直肠超声(TRUS)引导活检诊断前列腺癌(PCa)具有挑战性。我们使用线性支持向量机(SVM)将标准TRUS成像数据与声辐射力脉冲(ARFI)成像数据、剪切波弹性成像(SWEI)数据和定量超声(QUS)中带拟合(MF)数据进行联合收割机组合,以增强合成多参数超声(mpUS)体积中的病变对比度。该SVM使用20名患者的子集进行训练和验证,并在10名患者的第二子集上进行测试。与标准TRUS B模式和SWEI相比,mpUS导致对比度、对比度噪声比(CNR)和广义CNR(gCNR)统计学显著改善;与MF相比,mpUS导致对比度和CNR统计学显著改善;与ARFI相比,mpUS导致CNR统计学显著改善。相比之下,ARFI、MF和SWEI也优于TRUS B模式,MF在CNR和gCNR中也优于B模式。与TRUS B模式相比,ARFI仅在对比度方面产生统计学显著差异,但捕获了用于病变识别的关键定性特征。MpUS增强了病变可见性指标,是未来靶向TRUS引导前列腺活检的一种有前途的技术。
Diagnosing prostate cancer (PCa) through standard transrectal ultrasound (TRUS) guided biopsy is challenging due to the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit (MF) data to enhance lesion contrast into a synthesized multiparametric ultrasound (mpUS) volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. mpUS led to a statistically significant improvement in contrast, contrast-to-noise ratio (CNR), and generalized CNR (gCNR) when compared to standard TRUS B-mode and SWEI; contrast and CNR when compared to MF; and CNR when compared with ARFI. ARFI, MF, and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, while only yielding statistically significant differences in contrast compared to TRUS B- mode, captured critical qualitative features for lesion identification. MpUS enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.
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