The added value of artificial intelligence using Quantib Prostate for the detection of prostate cancer at multiparametric magnetic resonance imaging.

IF 9.7 1区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Radiologia Medica Pub Date : 2025-05-07 DOI:10.1007/s11547-025-02017-8

Tommaso Russo, Leonardo Quarta, Francesco Pellegrino, Michele Cosenza, Enrico Camisassa, Salvatore Lavalle, Giovanni Apostolo, Paolo Zaurito, Simone Scuderi, Francesco Barletta, Clara Marzorati, Armando Stabile, Francesco Montorsi, Francesco De Cobelli, Giorgio Brembilla, Giorgio Gandaglia, Alberto Briganti

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引用次数: 0

Abstract

Purpose: Artificial intelligence (AI) has been proposed to assist radiologists in reporting multiparametric magnetic resonance imaging (mpMRI) of the prostate. We evaluate the diagnostic performance of radiologists with different levels of experience when reporting mpMRI with the support of available AI-based software (Quantib Prostate).

Material and methods: This is a single-center study (NCT06298305) involving 110 patients. Those with a positive mpMRI (PI-RADS ≥ 3) underwent targeted plus systematic biopsy (TBx plus SBx), while those with a negative mpMRI but a high clinical suspicion of prostate cancer (PCa) underwent SBx. Three readers with different levels of experience, identified as R1, R2, and R3 reviewed all mpMRI. Inter-reader agreement among the three readers with or without the assistance of Quantib Prostate as well as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for the detection of clinically significant PCa (csPCa) were assessed.

Results: 102 patients underwent prostate biopsy and the csPCa detection rate was 47%. Using Quantib Prostate resulted in an increased number of lesions identified for R3 (101 vs. 127). Inter-reader agreement slightly increased when using Quantib Prostate from 0.37 to 0.41 without vs. with Quantib Prostate, respectively. PPV, NPV and diagnostic accuracy (measured by the area under the curve [AUC]) of R3 improved (0.51 vs. 0.55, 0.65 vs.0.82 and 0.56 vs. 0.62, respectively). Conversely, no changes were observed for R1 and R2.

Conclusions: Using Quantib Prostate did not enhance the detection rate of csPCa for readers with some experience in prostate imaging. However, for an inexperienced reader, this AI-based software is demonstrated to improve the performance.

Trial registration: Name of registry: clinicaltrials.gov.

Trial registration number: NCT06298305. Date of registration: 2022-09.

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人工智能应用Quantib前列腺多参数磁共振成像检测前列腺癌的附加价值

目的：人工智能（AI）已被提出协助放射科医生报告前列腺的多参数磁共振成像（mpMRI）。在现有的基于人工智能的软件（Quantib前列腺）的支持下，我们评估了具有不同经验水平的放射科医生在报告mpMRI时的诊断表现。材料和方法：这是一项单中心研究（NCT06298305），涉及110例患者。mpMRI阳性（PI-RADS≥3）的患者行定向+系统活检（TBx + SBx）， mpMRI阴性但临床怀疑前列腺癌（PCa）的患者行SBx。三个不同经验水平的读者，分别是R1、R2和R3，回顾了所有的mpMRI。评估三种读卡器在使用或不使用Quantib前列腺辅助下的读卡器间一致性，以及检测临床显著性前列腺癌（csPCa）的敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和诊断准确性。结果：102例患者行前列腺活检，csPCa检出率为47%。使用Quantib前列腺导致R3病变数量增加（101对127）。与使用Quantib前列腺相比，使用Quantib前列腺的读者间一致性略有增加，分别从0.37增加到0.41。R3的PPV、NPV和诊断准确性（通过曲线下面积[AUC]测量）分别提高（0.51 vs. 0.55、0.65 vs.0.82和0.56 vs. 0.62）。相反，R1和R2没有变化。结论：对于有一定前列腺影像学经验的读者，使用Quantib前列腺并不能提高csPCa的检出率。然而，对于一个没有经验的读者来说，这个基于人工智能的软件被证明可以提高性能。试验注册：注册名称：clinicaltrials.gov.试验注册号：NCT06298305。注册日期：2022-09。

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来源期刊

Radiologia Medica 医学-核医学

CiteScore

14.10

自引率

7.90%

发文量

133

审稿时长

4-8 weeks

期刊介绍： Felice Perussia founded La radiologia medica in 1914. It is a peer-reviewed journal and serves as the official journal of the Italian Society of Medical and Interventional Radiology (SIRM). The primary purpose of the journal is to disseminate information related to Radiology, especially advancements in diagnostic imaging and related disciplines. La radiologia medica welcomes original research on both fundamental and clinical aspects of modern radiology, with a particular focus on diagnostic and interventional imaging techniques. It also covers topics such as radiotherapy, nuclear medicine, radiobiology, health physics, and artificial intelligence in the context of clinical implications. The journal includes various types of contributions such as original articles, review articles, editorials, short reports, and letters to the editor. With an esteemed Editorial Board and a selection of insightful reports, the journal is an indispensable resource for radiologists and professionals in related fields. Ultimately, La radiologia medica aims to serve as a platform for international collaboration and knowledge sharing within the radiological community.