Molecular Imaging Program, NCI, NIH, 10 Center Drive, Room B3B85, Bethesda, MD, 20892, USA.
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA.
Eur Radiol. 2018 Oct;28(10):4407-4417. doi: 10.1007/s00330-018-5374-6. Epub 2018 Apr 12.
To evaluate if computer-aided diagnosis (CAD) prior to prostate multi-parametric MRI (mpMRI) can improve sensitivity and agreement between radiologists.
Nine radiologists (three each high, intermediate, low experience) from eight institutions participated. A total of 163 patients with 3-T mpMRI from 4/2012 to 6/2015 were included: 110 cancer patients with prostatectomy after mpMRI, 53 patients with no lesions on mpMRI and negative TRUS-guided biopsy. Readers were blinded to all outcomes and detected lesions per PI-RADSv2 on mpMRI. After 5 weeks, readers re-evaluated patients using CAD to detect lesions. Prostatectomy specimens registered to MRI were ground truth with index lesions defined on pathology. Sensitivity, specificity and agreement were calculated per patient, lesion level and zone-peripheral (PZ) and transition (TZ).
Index lesion sensitivity was 78.2% for mpMRI alone and 86.3% for CAD-assisted mpMRI (p = 0.013). Sensitivity was comparable for TZ lesions (78.7% vs 78.1%; p = 0.929); CAD improved PZ lesion sensitivity (84% vs 94%; p = 0.003). Improved sensitivity came from lesions scored PI-RADS < 3 as index lesion sensitivity was comparable at PI-RADS ≥ 3 (77.6% vs 78.1%; p = 0.859). Per patient specificity was 57.1% for CAD and 70.4% for mpMRI (p = 0.003). CAD improved agreement between all readers (56.9% vs 71.8%; p < 0.001).
CAD-assisted mpMRI improved sensitivity and agreement, but decreased specificity, between radiologists of varying experience.
• Computer-aided diagnosis (CAD) assists clinicians in detecting prostate cancer on MRI. • CAD assistance improves agreement between radiologists in detecting prostate cancer lesions. • However, this CAD system induces more false positives, particularly for less-experienced clinicians and in the transition zone. • CAD assists radiologists in detecting cancer missed on MRI, suggesting a path for improved diagnostic confidence.
评估前列腺多参数 MRI（mpMRI）前的计算机辅助诊断（CAD）是否可以提高放射科医生之间的敏感性和一致性。
来自 8 家机构的 9 名放射科医生（各有 3 名高、中、低经验）参与了研究。共纳入了 163 名 3-T mpMRI 患者，这些患者来自于 2012 年 4 月至 2015 年 6 月：110 名接受 mpMRI 后前列腺切除术的癌症患者，53 名 mpMRI 未见病变且经 TRUS 引导的活检为阴性的患者。在 MRI 上按 PI-RADSv2 检测到病变。在 5 周后，读者使用 CAD 重新评估患者以检测病变。前列腺切除术标本与 MRI 配准，将指数病变定义为病理上的病变。根据患者、病变水平和外周区（PZ）和移行区（TZ）计算敏感性、特异性和一致性。
mpMRI 单独检测指数病变的敏感性为 78.2%，CAD 辅助 mpMRI 的敏感性为 86.3%（p = 0.013）。TZ 病变的敏感性相似（78.7% vs 78.1%；p = 0.929）；CAD 提高了 PZ 病变的敏感性（84% vs 94%；p = 0.003）。敏感性的提高来自于评分 PI-RADS < 3 的病变，因为 PI-RADS ≥ 3 的指数病变的敏感性相似（77.6% vs 78.1%；p = 0.859）。每位患者的 CAD 特异性为 57.1%，mpMRI 特异性为 70.4%（p = 0.003）。CAD 提高了所有读者之间的一致性（56.9% vs 71.8%；p < 0.001）。
CAD 辅助 mpMRI 提高了不同经验放射科医生之间的敏感性和一致性，但降低了特异性。
计算机辅助诊断（CAD）帮助临床医生在 MRI 上检测前列腺癌。
CAD 辅助提高了放射科医生检测前列腺癌病变的一致性。
然而，这种 CAD 系统会产生更多的假阳性，特别是对于经验较少的临床医生和移行区。
CAD 辅助放射科医生检测 MRI 遗漏的癌症，提示提高诊断信心的途径。
