State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Neuro Oncol. 2022 Sep 1;24(9):1559-1570. doi: 10.1093/neuonc/noac025.
Accurate detection is essential for brain metastasis (BM) management, but manual identification is laborious. This study developed, validated, and evaluated a BM detection (BMD) system.
Five hundred seventy-three consecutive patients (10 448 lesions) with newly diagnosed BMs and 377 patients without BMs were retrospectively enrolled to develop a multi-scale cascaded convolutional network using 3D-enhanced T1-weighted MR images. BMD was validated using a prospective validation set comprising an internal set (46 patients with 349 lesions; 44 patients without BMs) and three external sets (102 patients with 717 lesions; 108 patients without BMs). The lesion-based detection sensitivity and the number of false positives (FPs) per patient were analyzed. The detection sensitivity and reading time of three trainees and three experienced radiologists from three hospitals were evaluated using the validation set.
The detection sensitivity and FPs were 95.8% and 0.39 in the test set, 96.0% and 0.27 in the internal validation set, and ranged from 88.9% to 95.5% and 0.29 to 0.66 in the external sets. The BMD system achieved higher detection sensitivity (93.2% [95% CI, 91.6-94.7%]) than all radiologists without BMD (ranging from 68.5% [95% CI, 65.7-71.3%] to 80.4% [95% CI, 78.0-82.8%], all P < .001). Radiologist detection sensitivity improved with BMD, reaching 92.7% to 95.0%. The mean reading time was reduced by 47% for trainees and 32% for experienced radiologists assisted by BMD relative to that without BMD.
BMD enables accurate BM detection. Reading with BMD improves radiologists' detection sensitivity and reduces their reading times.
准确检测对于脑转移瘤（BM）的管理至关重要，但手动识别非常繁琐。本研究开发、验证并评估了一种 BM 检测（BMD）系统。
回顾性纳入 573 例初诊 BM 患者（10448 个病灶）和 377 例无脑转移瘤患者，使用 3D 增强 T1 加权磁共振图像开发多尺度级联卷积网络。前瞻性验证集由内部集（46 例患者 349 个病灶；44 例无脑转移瘤患者）和 3 个外部集（102 例患者 717 个病灶；108 例无脑转移瘤患者）组成，用于验证 BMD。分析病灶的检测灵敏度和每个患者的假阳性（FP）数。使用验证集评估 3 家医院的 3 名受训者和 3 名有经验的放射科医生的检测灵敏度和阅读时间。
测试集的检测灵敏度和 FP 分别为 95.8%和 0.39，内部验证集为 96.0%和 0.27，外部集的范围分别为 88.9%至 95.5%和 0.29 至 0.66。BMD 系统的检测灵敏度（93.2%[95%CI，91.6%-94.7%]）高于无脑转移瘤的所有放射科医生（范围为 68.5%[95%CI，65.7%-71.3%]至 80.4%[95%CI，78.0%-82.8%]，均 P<0.001）。在 BMD 的辅助下，放射科医生的检测灵敏度提高，达到 92.7%至 95.0%。与无脑转移瘤相比，受训者的平均阅读时间减少了 47%，有经验的放射科医生的阅读时间减少了 32%。
BMD 可实现 BM 的准确检测。阅读时使用 BMD 可提高放射科医生的检测灵敏度并减少阅读时间。
