Abstract：
OBJECTIVE: To identify factors influencing the diagnostic performance of the quantitative imaging biomarkers ADC and ADCratio in prostate cancer (PCa) detection.
METHODS: A systematic literature search was conducted in Embase, Medline and Web of Science, for studies evaluating ADC values and ADCratio for PCa diagnosis, using the same patient cohorts and using histopathological references as ground truth. Pooled sensitivities, specificities, summary ROC curves and AUCs were calculated from constructed contingency data tables. Diagnostic performance (AUC) was quantitatively pooled using a bivariate mixed effects model. For identifying influencing factors, subgroup analysis, publication bias and heterogeneity assessment were investigated.
RESULTS: Thirteen studies, involving 1038 patients and 1441 lesions, were included. For ADC, the pooled sensitivity and specificity was 80% (95% CI: 74-85%) and 78% (95% CI: 70-85%), respectively. For ADCratio pooled sensitivity and specificity was 80% (95% CI: 74-84%) and 80% (95% CI: 71-87%). Summary ROC analysis revealed AUCs of 0.86 (95% CI: 0.83-0.89) and 0.86 (95% CI: 0.83-0.89), respectively. Meta-regression showed heterogeneity between both imaging biomarkers. Subgroup analysis showed that ADCratio improved diagnostic performance in comparison to ADC when including both peripheral and transitional zone lesions (AUC: 0.87 [95% CI: 0.84-0.90] and 0.82 [95% CI: 0.79-0.85], respectively).
CONCLUSIONS: Both ADC and ADCratio imaging biomarkers showed good and comparable diagnostic performance in PCa diagnosis. However, ADCratio shows better diagnostic performance than ADC in diagnosing transition zone cancers.
CONCLUSIONS: In quantitative MRI-based PCa diagnosis, the imaging biomarker ADCratio is useful in challenging MRI readings of lesions. Understanding the performance of quantitative imaging biomarkers better can aid diagnostic MRI protocols, enhancing the precision of PCa assessments.
CONCLUSIONS: MRI diffusion-weighted imaging-based ADC and ADCratio have comparable diagnostic performance in PCa assessment. In contrast to ADC, the ADCratio improves diagnostic performance, when assessing whole gland lesions. Compared to ADCratio, the ADC demonstrates enhanced diagnostic performance when evaluating peripheral zone lesions.
METHODS: A systematic literature search was conducted in Embase, Medline and Web of Science, for studies evaluating ADC values and ADCratio for PCa diagnosis, using the same patient cohorts and using histopathological references as ground truth. Pooled sensitivities, specificities, summary ROC curves and AUCs were calculated from constructed contingency data tables. Diagnostic performance (AUC) was quantitatively pooled using a bivariate mixed effects model. For identifying influencing factors, subgroup analysis, publication bias and heterogeneity assessment were investigated.
RESULTS: Thirteen studies, involving 1038 patients and 1441 lesions, were included. For ADC, the pooled sensitivity and specificity was 80% (95% CI: 74-85%) and 78% (95% CI: 70-85%), respectively. For ADCratio pooled sensitivity and specificity was 80% (95% CI: 74-84%) and 80% (95% CI: 71-87%). Summary ROC analysis revealed AUCs of 0.86 (95% CI: 0.83-0.89) and 0.86 (95% CI: 0.83-0.89), respectively. Meta-regression showed heterogeneity between both imaging biomarkers. Subgroup analysis showed that ADCratio improved diagnostic performance in comparison to ADC when including both peripheral and transitional zone lesions (AUC: 0.87 [95% CI: 0.84-0.90] and 0.82 [95% CI: 0.79-0.85], respectively).
CONCLUSIONS: Both ADC and ADCratio imaging biomarkers showed good and comparable diagnostic performance in PCa diagnosis. However, ADCratio shows better diagnostic performance than ADC in diagnosing transition zone cancers.
CONCLUSIONS: In quantitative MRI-based PCa diagnosis, the imaging biomarker ADCratio is useful in challenging MRI readings of lesions. Understanding the performance of quantitative imaging biomarkers better can aid diagnostic MRI protocols, enhancing the precision of PCa assessments.
CONCLUSIONS: MRI diffusion-weighted imaging-based ADC and ADCratio have comparable diagnostic performance in PCa assessment. In contrast to ADC, the ADCratio improves diagnostic performance, when assessing whole gland lesions. Compared to ADCratio, the ADC demonstrates enhanced diagnostic performance when evaluating peripheral zone lesions.
摘要：
目的：确定影响前列腺癌（PCa）定量成像生物标志物ADC和ADCratio诊断性能的因素。
方法：在Embase进行了系统的文献检索，Medline和WebofScience,对于评估PCa诊断的ADC值和ADCratio的研究，使用相同的患者队列，并使用组织病理学参考作为地面实况。集合敏感性，特殊性，总结ROC曲线和AUC由构建的列支数据表计算.使用双变量混合效应模型定量汇集诊断性能(AUC)。为了识别影响因素，亚组分析，研究了发表偏倚和异质性评估。
结果：13项研究，涉及1038名患者和1441个病灶,包括在内。对于ADC，合并的敏感性和特异性分别为80％（95％CI：74-85％）和78％（95％CI：70-85％），分别。对于ADCratio，合并的敏感性和特异性分别为80％（95％CI：74-84％）和80％（95％CI：71-87％）。汇总ROC分析显示AUC为0.86（95％CI：0.83-0.89）和0.86（95％CI：0.83-0.89），分别。Meta回归显示两种成像生物标志物之间的异质性。亚组分析显示，当包括周围区和移行区病变时，与ADC相比，ADC比率提高了诊断性能（AUC：0.87[95％CI：0.84-0.90]和0.82[95％CI：0.79-0.85]，分别)。
结论：ADC和ADCratio成像生物标志物在PCa诊断中均显示出良好且可比的诊断性能。然而,ADCratio在诊断过渡区癌症方面显示出比ADC更好的诊断性能。
结论：在基于MRI的定量PCa诊断中，影像学生物标志物ADCratio可用于具有挑战性的病变MRI读数.更好地了解定量成像生物标志物的性能可以帮助诊断MRI方案，提高PCa评估的准确性。
结论：基于MRI扩散加权成像的ADC和ADCratio在PCa评估中具有相当的诊断性能。与ADC相比，ADCratio提高了诊断性能，当评估整个腺体病变时。与ADCratio相比，在评估外周区病变时,ADC显示出增强的诊断性能.
方法：在Embase进行了系统的文献检索，Medline和WebofScience,对于评估PCa诊断的ADC值和ADCratio的研究，使用相同的患者队列，并使用组织病理学参考作为地面实况。集合敏感性，特殊性，总结ROC曲线和AUC由构建的列支数据表计算.使用双变量混合效应模型定量汇集诊断性能(AUC)。为了识别影响因素，亚组分析，研究了发表偏倚和异质性评估。
结果：13项研究，涉及1038名患者和1441个病灶,包括在内。对于ADC，合并的敏感性和特异性分别为80％（95％CI：74-85％）和78％（95％CI：70-85％），分别。对于ADCratio，合并的敏感性和特异性分别为80％（95％CI：74-84％）和80％（95％CI：71-87％）。汇总ROC分析显示AUC为0.86（95％CI：0.83-0.89）和0.86（95％CI：0.83-0.89），分别。Meta回归显示两种成像生物标志物之间的异质性。亚组分析显示，当包括周围区和移行区病变时，与ADC相比，ADC比率提高了诊断性能（AUC：0.87[95％CI：0.84-0.90]和0.82[95％CI：0.79-0.85]，分别)。
结论：ADC和ADCratio成像生物标志物在PCa诊断中均显示出良好且可比的诊断性能。然而,ADCratio在诊断过渡区癌症方面显示出比ADC更好的诊断性能。
结论：在基于MRI的定量PCa诊断中，影像学生物标志物ADCratio可用于具有挑战性的病变MRI读数.更好地了解定量成像生物标志物的性能可以帮助诊断MRI方案，提高PCa评估的准确性。
结论：基于MRI扩散加权成像的ADC和ADCratio在PCa评估中具有相当的诊断性能。与ADC相比，ADCratio提高了诊断性能，当评估整个腺体病变时。与ADCratio相比，在评估外周区病变时,ADC显示出增强的诊断性能.
