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QUANTRA 软件评估与目测分类法评估乳腺 X 光密度的初步比较。

A first evaluation of breast radiological density assessment by QUANTRA software as compared to visual classification.

机构信息

UO Senologia Clinica e Screening Mammografico, Dipartimento di Radiodiagnostica, APSS, Trento, Italy.

出版信息

Breast. 2012 Aug;21(4):503-6. doi: 10.1016/j.breast.2012.01.005. Epub 2012 Jan 27.

Abstract

Breast radiological density is a determinant of breast cancer risk and of mammography sensitivity and may be used to personalize screening approach. We first analyzed the reproducibility of visual density assessment by eleven experienced radiologists classifying a set of 418 digital mammograms: reproducibility was satisfactory on a four (BI-RADS D1-2-3-4: weighted kappa = 0.694-0.844) and on a two grade (D1-2 vs D3-4: kappa = 0.620-0.851), but subjects classified as with dense breast would range between 25.1 and 50.5% depending on the classifying reader. Breast density was then assessed by computer using the QUANTRA software which provided systematically lower density percentage values as compared to visual classification. In order to predict visual classification results in discriminating dense and non-dense breast subjects on a two grade scale (D3-4 vs, D1-2) the best fitting cut off value observed for QUANTRA was ≤22.0%, which correctly predicted 88.6% of D1-2, 89.8% of D3-4, and 89.0% of total cases. Computer assessed breast density is absolutely reproducible, and thus to be preferred to visual classification. Thus far few studies have addressed the issue of adjusting computer assessed density to reproduce visual classification, and more similar comparative studies are needed.

摘要

乳腺放射密度是乳腺癌风险和乳房 X 线摄影敏感性的决定因素,可用于个性化筛查方法。我们首先分析了 11 位有经验的放射科医生对一组 418 张数字乳房 X 光片进行的视觉密度评估的可重复性:在四级(BI-RADS D1-2-3-4:加权 κ = 0.694-0.844)和两级(D1-2 与 D3-4:κ = 0.620-0.851)上的可重复性是令人满意的,但根据分类读者的不同,被分类为致密乳房的患者比例将在 25.1%至 50.5%之间变化。然后使用 QUANTRA 软件通过计算机评估乳腺密度,与视觉分类相比,该软件提供的密度百分比值系统地更低。为了预测 QUANTRA 在二级(D3-4 与 D1-2)上区分致密和非致密乳腺受试者的视觉分类结果,观察到的最佳拟合截止值为≤22.0%,正确预测了 88.6%的 D1-2、89.8%的 D3-4 和 89.0%的总病例。计算机评估的乳腺密度是绝对可重复的,因此优于视觉分类。到目前为止,很少有研究解决调整计算机评估密度以重现视觉分类的问题,需要更多类似的比较研究。

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