Institute of Radiology, Department of Medicine (DMED), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy.
UOC Radiologia, Ospedale Civile SS. Giovanni e Paolo, ULSS 3 Serenissima, 6776 - 30122, Castello, Venezia, Italy.
Abdom Radiol (NY). 2024 Dec;49(12):4273-4285. doi: 10.1007/s00261-024-04506-2. Epub 2024 Jul 30.
To retrospectively investigate whether a case-by-case combination of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS) with the Likert score improves the diagnostic performance of mpMRI for clinically significant prostate cancer (csPCa), especially by reducing false-positives.
One hundred men received mpMRI between January 2020 and April 2021, followed by prostate biopsy. Reader 1 (R1) and reader 2 (R2) (experience of > 3000 and < 200 mpMRI readings) independently reviewed mpMRIs with the PI-RADS version 2.1. After unveiling clinical information, they were free to add (or not) a Likert score to upgrade or downgrade or reinforce the level of suspicion of the PI-RADS category attributed to the index lesion or, rather, identify a new index lesion. We calculated sensitivity, specificity, and predictive values of R1/R2 in detecting csPCa when biopsying PI-RADS ≥ 3 index-lesions (strategy 1) versus PI-RADS ≥ 3 or Likert ≥ 3 index-lesions (strategy 2), with decision curve analysis to assess the net benefit. In strategy 2, the Likert score was considered dominant in determining biopsy decisions.
csPCa prevalence was 38%. R1/R2 used combined PI-RADS and Likert categorization in 28%/18% of examinations relying mainly on clinical features such as prostate specific antigen level and digital rectal examination than imaging findings. The specificity/positive predictive values were 66.1/63.1% for R1 (95%CI 52.9-77.6/54.5-70.9) and 50.0/51.6% (95%CI 37.0-63.0/35.5-72.4%) for R2 in the case of PI-RADS-based readings, and 74.2/69.2% for R1 (95%CI 61.5-84.5/59.4-77.5%) and 56.6/54.2% (95%CI 43.3-69.0/37.1-76.6%) for R2 in the case of combined PI-RADS/Likert readings. Sensitivity/negative predictive values were unaffected. Strategy 2 achieved greater net benefit as a trigger of biopsy for R1 only.
Case-by-case combination of the PI-RADS version 2.1 with Likert score translated into a mild but measurable impact in reducing the false-positives of PI-RADS categorization, though greater net benefit in reducing unnecessary biopsies was found in the experienced reader only.
回顾性研究前列腺影像报告和数据系统第 2.1 版(PI-RADS)与 Likert 评分相结合是否能提高磁共振成像(mpMRI)对临床显著前列腺癌(csPCa)的诊断性能,特别是减少假阳性。
100 名男性在 2020 年 1 月至 2021 年 4 月期间接受了 mpMRI 检查,随后进行了前列腺活检。读者 1(R1)和读者 2(R2)(经验超过 3000 次和少于 200 次 mpMRI 阅读)分别使用 PI-RADS 第 2.1 版独立评估了 mpMRI。在揭示临床信息后,他们可以自由地(或不)添加 Likert 评分,以升级或降级或强化分配给索引病变的 PI-RADS 类别,或者识别新的索引病变。我们计算了 R1/R2 在检测 PI-RADS≥3 个指数病变(策略 1)与 PI-RADS≥3 或 Likert≥3 个指数病变(策略 2)时检测 csPCa 的敏感性、特异性和预测值,并通过决策曲线分析评估净获益。在策略 2 中,Likert 评分在决定活检决策方面被认为是占主导地位的。
csPCa 患病率为 38%。R1/R2 在 28%/18%的检查中结合使用 PI-RADS 和 Likert 分类,主要依赖于临床特征,如前列腺特异性抗原水平和直肠指检,而不是影像学发现。R1 的特异性/阳性预测值分别为 66.1%/63.1%(95%CI 52.9-77.6/54.5-70.9),R2 为 50.0%/51.6%(95%CI 37.0-63.0/35.5-72.4%),用于基于 PI-RADS 的阅读,而 R1 的敏感性/阴性预测值分别为 74.2%/69.2%(95%CI 61.5-84.5/59.4-77.5%),R2 为 56.6%/54.2%(95%CI 43.3-69.0/37.1-76.6%),用于结合 PI-RADS/Likert 阅读。敏感性/阴性预测值不受影响。策略 2 作为活检触发因素,仅对 R1 产生了更大的净获益。
PI-RADS 第 2.1 版与 Likert 评分的个案结合,在减少 PI-RADS 分类的假阳性方面产生了轻微但可衡量的影响,但只有经验丰富的读者才能发现减少不必要活检的更大净获益。