在临床怀疑患有前列腺癌的情况下进行的前列腺磁共振成像的诊断性能估计。

IF 4.1 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Hirotsugu Nakai, Hiroaki Takahashi, Jordan D LeGout, Akira Kawashima, Adam T Froemming, Derek J Lomas, Mitchell R Humphreys, Chandler Dora, Naoki Takahashi
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引用次数: 0

摘要

目的:通过估算无前列腺病变患者中具有临床意义的前列腺癌(csPCa)的比例,评估前列腺磁共振成像的诊断性能:这项三中心回顾性研究纳入了2018年至2022年间因临床怀疑csPCa(等级组≥2)而进行的前列腺MRI检查。检查分为两组:MRI(MRI 后病理)后 1 年内有病理诊断和无病理诊断。利用从有 MRI 后病理诊断的患者中提取的 11 个常见预测变量建立风险预测模型。然后,通过应用该模型估算出无 MRI 后病变患者的 csPCa 比例。随后,以 PI-RADS ≥ 3 为阳性阈值,计算了有和无 MRI 后前列腺病理(估计统计数据)患者的接收者操作特征曲线下面积(AUC)、敏感性、特异性以及前列腺 MRI 诊断 csPCa 的阳性预测值和阴性预测值(PPV/NPV):在 12,191 名接受检查的患者(平均年龄为 65.7 岁 ± 8.4 [标准差])中,PI-RADS 1-2 的患者最多(55.4%),病理确认率最低,为 14.0-18.2%。在 5670 例(46.5%)检查中发现了 MRI 后前列腺病理。在 PI-RADS评分为 1-2、3、4 和 5 的情况下,各机构的 csPCa 估计比例分别为 12.6-15.3%、18.4-31.4%、45.7-69.9% 和 75.4-88.3%。估计(观察)性能统计如下:AUC,0.78-0.81(0.76-0.79);灵敏度,76.6-77.3%;特异度,67.5-78.6%;PPV,49.8-66.6%(52.0-67.7%);NPV,84.4-87.2%(82.4-86.6%):我们提出了一种方法来估算接受前列腺 MRI 检查的患者罹患 csPCa 的概率,通过这种方法我们可以了解 PI-RADS 诊断性能的几个指标:所报告的性能指标估计值有望帮助了解 PI-RADS 在临床怀疑患有前列腺癌的所有前列腺 MRI 患者中的真正诊断价值:要点:仅对接受前列腺活检的患者计算性能指标可能会因活检选择标准而产生偏差,尤其是在PI-RADS 1-2中。在三家医疗机构中,PI-RADS 在所有前列腺 MRI 患者中的接收器操作特征曲线下的估计面积介于 0.78 到 0.81 之间。估计的统计数据有望帮助我们了解 PI-RADS 的真实表现,并为今后的研究提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimated diagnostic performance of prostate MRI performed with clinical suspicion of prostate cancer.

Purpose: To assess the diagnostic performance of prostate MRI by estimating the proportion of clinically significant prostate cancer (csPCa) in patients without prostate pathology.

Materials and methods: This three-center retrospective study included prostate MRI examinations performed for clinical suspicion of csPCa (Grade group ≥ 2) between 2018 and 2022. Examinations were divided into two groups: pathological diagnosis within 1 year after the MRI (post-MRI pathology) is present and absent. Risk prediction models were developed using the extracted eleven common predictive variables from the patients with post-MRI pathology. Then, the csPCa proportion in the patients without post-MRI pathology was estimated by applying the model. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and positive and negative predictive values (PPV/NPV) of prostate MRI in diagnosing csPCa were subsequently calculated for patients with and without post-MRI prostate pathology (estimated statistics) with a positive threshold of PI-RADS ≥ 3.

Results: Of 12,191 examinations enrolled (mean age, 65.7 years ± 8.4 [standard deviation]), PI-RADS 1-2 was most frequently assigned (55.4%) with the lowest pathological confirmation rate of 14.0-18.2%. Post-MRI prostate pathology was found in 5670 (46.5%) examinations. The estimated csPCa proportions across facilities were 12.6-15.3%, 18.4-31.4%, 45.7-69.9%, and 75.4-88.3% in PI-RADS scores of 1-2, 3, 4, and 5, respectively. The estimated (observed) performance statistics were as follows: AUC, 0.78-0.81 (0.76-0.79); sensitivity, 76.6-77.3%; specificity, 67.5-78.6%; PPV, 49.8-66.6% (52.0-67.7%); and NPV, 84.4-87.2% (82.4-86.6%).

Conclusion: We proposed a method to estimate the probabilities harboring csPCa for patients who underwent prostate MRI examinations, which allows us to understand the PI-RADS diagnostic performance with several metrics.

Clinical relevance statement: The reported estimated performance metrics are expected to aid in understanding the true diagnostic value of PI-RADS in the entire prostate MRI population performed with clinical suspicion of prostate cancer.

Key points: Calculating performance metrics only from patients who underwent prostate biopsy may be biased due to biopsy selection criteria, especially in PI-RADS 1-2. The estimated area under the receiver operating characteristic curve of PI-RADS in the entire prostate MRI population ranged from 0.78 to 0.81 at three facilities. The estimated statistics are expected to help us understand the true PI-RADS performance and serve as a reference for future studies.

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来源期刊
Insights into Imaging
Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
7.30
自引率
4.30%
发文量
182
审稿时长
13 weeks
期刊介绍: Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.
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