Discipline of Medical Imaging Sciences, Faculty of Medicine and Health, University of Sydney, D18 Susan Wakil Health Building, Western Avenue, Camperdown, NSW, 2006, Australia.
J Cancer Educ. 2024 Apr;39(2):186-193. doi: 10.1007/s13187-023-02393-7. Epub 2023 Dec 15.
Medical imaging with mammography plays a very important role in screening and diagnosis of breast cancer, Australia's most common female cancer. The visualisation of cancers on mammograms often forms a diagnosis and guidance for radiologists and breast surgeons, and education platforms that provide real cases in a simulated testing environment have been shown to improve observer performance for radiologists. This study reports on the performance of surgical and radiology trainees in locating breast cancers. An enriched test set of 20 mammography cases (6 cancer and 14 cancer free) was created, and 18 surgical trainees and 32 radiology trainees reviewed the cases via the Breast Screen Reader Assessment Strategy (BREAST) platform and marked any lesions identifiable. Further analysis of performance with high- and low-density cases was undertaken, and standard metrics including sensitivity and specificity. Radiology trainees performed significantly better than surgical trainees in terms of specificity (0.72 vs. 0.35; P < 0.01). No significant differences were observed between the surgical and radiology trainees in sensitivity or lesion sensitivity. Mixed results were obtained with participants regarding breast density, with higher density cases generally having lower performance. The higher specificity of the radiology trainees compared to the surgical trainees likely represents less exposure to negative mammography cases. The use of high-fidelity simulated self-test environments like BREAST is able to benchmark, understand and build strategies for improving cancer education in a safe environment, including identifying challenging scenarios like breast density for enhanced training.
乳腺 X 线摄影在乳腺癌的筛查和诊断中起着非常重要的作用,乳腺癌是澳大利亚最常见的女性癌症。乳腺 X 线照片上癌症的可视化通常构成放射科医生和乳腺外科医生的诊断和指导,并且已经表明,提供模拟测试环境中的真实病例的教育平台可以提高放射科医生的观察能力。本研究报告了外科和放射科受训者在定位乳腺癌方面的表现。创建了一个包含 20 个乳腺 X 线摄影病例(6 个癌症病例和 14 个无癌症病例)的丰富测试集,然后 18 名外科受训者和 32 名放射科受训者通过 Breast Screen Reader Assessment Strategy(BREAST)平台审查了这些病例,并标记了可识别的任何病变。对高密度和低密度病例的性能进行了进一步分析,并采用了包括敏感性和特异性在内的标准指标。在特异性方面,放射科受训者的表现明显优于外科受训者(0.72 比 0.35;P < 0.01)。在敏感性或病变敏感性方面,外科和放射科受训者之间没有观察到显着差异。关于乳房密度,参与者的结果喜忧参半,较高密度的病例通常表现较差。与外科受训者相比,放射科受训者的特异性较高,这可能代表着他们接触到的阴性乳腺 X 线摄影病例较少。在安全的环境中,使用高保真模拟自我测试环境(如 BREAST)可以进行基准测试、了解和制定策略,以改善癌症教育,包括识别像乳房密度这样的具有挑战性的情况,以进行强化培训。