Jamal N, Ng K-H, Looi L-M, McLean D, Zulfiqar A, Tan S-P, Liew W-F, Shantini A, Ranganathan S
Medical Technology Division, Malaysian Institute for Nuclear Technology Research (MINT) 43000 Kajang, Malaysia.
Phys Med Biol. 2006 Nov 21;51(22):5843-57. doi: 10.1088/0031-9155/51/22/008. Epub 2006 Oct 25.
We describe a semi-automated technique for the quantitative assessment of breast density from digitized mammograms in comparison with patterns suggested by Tabar. It was developed using the MATLAB-based graphical user interface applications. It is based on an interactive thresholding method, after a short automated method that shows the fibroglandular tissue area, breast area and breast density each time new thresholds are placed on the image. The breast density is taken as a percentage of the fibroglandular tissue to the breast tissue areas. It was tested in four different ways, namely by examining: (i) correlation of the quantitative assessment results with subjective classification, (ii) classification performance using the quantitative assessment technique, (iii) interobserver agreement and (iv) intraobserver agreement. The results of the quantitative assessment correlated well (r2 = 0.92) with the subjective Tabar patterns classified by the radiologist (correctly classified 83% of digitized mammograms). The average kappa coefficient for the agreement between the readers was 0.63. This indicated moderate agreement between the three observers in classifying breast density using the quantitative assessment technique. The kappa coefficient of 0.75 for intraobserver agreement reflected good agreement between two sets of readings. The technique may be useful as a supplement to the radiologist's assessment in classifying mammograms into Tabar's pattern associated with breast cancer risk.
我们描述了一种用于从数字化乳腺钼靶片中定量评估乳腺密度的半自动技术，并将其与塔巴尔（Tabar）提出的模式进行比较。该技术是使用基于MATLAB的图形用户界面应用程序开发的。它基于一种交互式阈值方法，在此之前有一个简短的自动方法，每次在图像上设置新阈值时，该方法会显示纤维腺体组织面积、乳房面积和乳腺密度。乳腺密度以纤维腺体组织占乳房组织面积的百分比来表示。该技术通过四种不同方式进行了测试，即通过检查：（i）定量评估结果与主观分类的相关性，（ii）使用定量评估技术的分类性能，（iii）观察者间一致性和（iv）观察者内一致性。定量评估结果与放射科医生主观分类的塔巴尔模式相关性良好（r2 = 0.92）（正确分类了83%的数字化乳腺钼靶片）。读者之间一致性的平均kappa系数为0.63。这表明在使用定量评估技术对乳腺密度进行分类时，三位观察者之间存在中度一致性。观察者内一致性的kappa系数为0.75，反映了两组读数之间的良好一致性。该技术在将乳腺钼靶片分类为与乳腺癌风险相关的塔巴尔模式时，可作为放射科医生评估的补充手段。
