Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Swedish eScience Research Centre (SeRC), Karolinska Institutet, Stockholm, Sweden.
Sci Rep. 2023 Aug 30;13(1):14194. doi: 10.1038/s41598-023-41356-2.
Understanding the detectability of breast cancer using mammography is important when considering nation-wide screening programmes. Although the role of imaging settings on image quality has been studied extensively, their role in detectability of cancer at a population level is less well studied. We wish to quantify the association between mammographic screening sensitivity and various imaging parameters. Using a novel approach applied to a population-based breast cancer screening cohort, we specifically focus on sensitivity as defined in the classical diagnostic testing literature, as opposed to the screen-detected cancer rate, which is often used as a measure of sensitivity for monitoring and evaluating breast cancer screening. We use a natural history approach to model the presence and size of latent tumors at risk of detection at mammography screening, and the screening sensitivity is modeled as a logistic function of tumor size. With this approach we study the influence of compressed breast thickness, x-ray exposure, and compression pressure, in addition to (percent) breast density, on the screening test sensitivity. When adjusting for all screening parameters in addition to latent tumor size, we find that percent breast density and compressed breast thickness are statistically significant factors for the detectability of breast cancer. A change in breast density from 6.6 to 33.5% (the inter-quartile range) reduced the odds of detection by 61% (95% CI 48-71). Similarly, a change in compressed breast thickness from 46 to 66 mm reduced the odds by 42% (95% CI 21-57). The true sensitivity of mammography, defined as the probability that an examination leads to a positive result if a tumour is present in the breast, is associated with compressed breast thickness after accounting for mammographic density and tumour size. This can be used to guide studies of setups aimed at improving lesion detection. Compressed breast thickness-in addition to breast density-should be considered when assigning complementary screening modalities and personalized screening intervals.
了解乳房 X 光摄影术检测乳腺癌的能力在考虑全国性筛查计划时非常重要。尽管已经广泛研究了成像参数对图像质量的影响，但它们在人群水平上对癌症检测能力的影响研究较少。我们希望量化乳房 X 光筛查敏感性与各种成像参数之间的关联。我们使用一种应用于基于人群的乳腺癌筛查队列的新方法，特别关注经典诊断测试文献中定义的敏感性，而不是作为监测和评估乳腺癌筛查敏感性的指标的筛查检出癌症率。我们使用一种自然史方法来模拟在乳房 X 光筛查中可检测到的潜在肿瘤的存在和大小，并且将筛查敏感性建模为肿瘤大小的逻辑函数。通过这种方法，我们研究了压缩乳房厚度、X 射线曝光量和压缩压力以及（百分比）乳房密度对筛查试验敏感性的影响。当除了潜在肿瘤大小外还调整所有筛查参数时，我们发现乳房密度和压缩乳房厚度是乳腺癌可检测性的统计显著因素。乳房密度从 6.6%变为 33.5%（四分位距）会使检测到的肿瘤的可能性降低 61%（95%CI 48-71）。同样，压缩乳房厚度从 46 毫米变为 66 毫米会使检测到的肿瘤的可能性降低 42%（95%CI 21-57）。在考虑到乳腺密度和肿瘤大小后，乳房 X 光摄影术的真实敏感性（定义为如果乳房中有肿瘤存在，则检查会导致阳性结果的概率）与压缩乳房厚度相关。这可用于指导旨在提高病变检测能力的设置研究。在分配补充筛查方式和个性化筛查间隔时，除了乳腺密度外，还应考虑压缩乳房厚度。
