doi:10.3969/j.issn.1004-583X.2025.06.012

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作者	发布时间	样本量	影像学方法	网络方法	检测性能	临床应用
Loch等^[19-21]	1999	患者数61 病理数289 影像数500	TRUS	ANN	假阳性率1% 假阴性率21%	良恶鉴别
	2000					良恶鉴别、Gleason分级
	2004	阴性患者数132	TRUS-Bx	ANN	新检出率50%	良恶鉴别、引导活检
Lawrentschuk等^[22]	2011	患者数3025	TRUS-Bx	PR、ANN	PR准确率55% ANN准确率57%	引导活检
Wildeboer等^[23]	2020	患者数50	B型超声、SWE和 DCE-US	RF	所有PCa:AUC:0.75 显著性PCa:AUC:0.90	良恶鉴别、病灶定位
Wang等^[24]	2023	TRUS-SB组:133 mpMRI组:134 AIUSP组:133	TRUS-SB、mpMRI、 AIUSP	ANN	AIUSP检出率49.6% TRUS-SB检出率34.6% mpMRI检出率35.8%	引导活检
Zhang等^[25]	2023	患者数639	TRUS	ANN、LR、SVM、DT、 RF和KNN	AUC(ANN):0.855 AUC(SVM):0.845	良恶鉴别、病灶定位

作者	发布时间	样本量	影像学方法	网络方法	检测性能	临床应用
Loch等^[19-21]	1999	患者数61 病理数289 影像数500	TRUS	ANN	假阳性率1% 假阴性率21%	良恶鉴别
	2000					良恶鉴别、Gleason分级
	2004	阴性患者数132	TRUS-Bx	ANN	新检出率50%	良恶鉴别、引导活检
Lawrentschuk等^[22]	2011	患者数3025	TRUS-Bx	PR、ANN	PR准确率55% ANN准确率57%	引导活检
Wildeboer等^[23]	2020	患者数50	B型超声、SWE和 DCE-US	RF	所有PCa:AUC:0.75 显著性PCa:AUC:0.90	良恶鉴别、病灶定位
Wang等^[24]	2023	TRUS-SB组:133 mpMRI组:134 AIUSP组:133	TRUS-SB、mpMRI、 AIUSP	ANN	AIUSP检出率49.6% TRUS-SB检出率34.6% mpMRI检出率35.8%	引导活检
Zhang等^[25]	2023	患者数639	TRUS	ANN、LR、SVM、DT、 RF和KNN	AUC(ANN):0.855 AUC(SVM):0.845	良恶鉴别、病灶定位

作者	发布时间	样本量	影像学方法	网络方法	检测性能	临床应用
Azizi等^[34-36]	2017	患者数:132 病理数:197	TeUS、RF和 mp-MRI	DBN	AUC(TeUS):0.69 AUC(TeUS+mp-MRI):0.82	良恶鉴别、 Gleason分级
	2018	患者数:157 病理数:255	TeUS	深度RNN	AUC:0.96	良恶鉴别
	2018	患者数:157 病理数:255	TeUS和mp-MRI	RNN、ResNet	AUC:0.94	图像分割、良恶鉴别
		患者数:6 病理数:21			AUC:0.85
Zhang等^[37]	2020	患者数:103 影像数:313	B型超声和SWE	PGBM-RBM	AUC:0.851	良恶鉴别
Hassan等^[38]	2022	患者数:1151 影像数:61,1119	US和MRI	CNN、SVM、KNN、RF等	US准确率达99% MRI准确率从80%提高到88%	良恶鉴别
Lu等^[39]	2022	影像数:525	TRUS	基于CNN的:RLOD网络、GNet网络	Dice系数:0.815 平均精度:0.830	PCa分类、 Gleason分级
Huang等^[40]	2023	1380张PCa和1530张良性前列腺增生的TRUS图像	TRUS	基于CNN的神经网络	准确率:0.9987 敏感度和特异度均0.9980	良恶鉴别

作者	发布时间	样本量	影像学方法	网络方法	检测性能	临床应用
Azizi等^[34-36]	2017	患者数:132 病理数:197	TeUS、RF和 mp-MRI	DBN	AUC(TeUS):0.69 AUC(TeUS+mp-MRI):0.82	良恶鉴别、 Gleason分级
	2018	患者数:157 病理数:255	TeUS	深度RNN	AUC:0.96	良恶鉴别
	2018	患者数:157 病理数:255	TeUS和mp-MRI	RNN、ResNet	AUC:0.94	图像分割、良恶鉴别
		患者数:6 病理数:21			AUC:0.85
Zhang等^[37]	2020	患者数:103 影像数:313	B型超声和SWE	PGBM-RBM	AUC:0.851	良恶鉴别
Hassan等^[38]	2022	患者数:1151 影像数:61,1119	US和MRI	CNN、SVM、KNN、RF等	US准确率达99% MRI准确率从80%提高到88%	良恶鉴别
Lu等^[39]	2022	影像数:525	TRUS	基于CNN的:RLOD网络、GNet网络	Dice系数:0.815 平均精度:0.830	PCa分类、 Gleason分级
Huang等^[40]	2023	1380张PCa和1530张良性前列腺增生的TRUS图像	TRUS	基于CNN的神经网络	准确率:0.9987 敏感度和特异度均0.9980	良恶鉴别

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