筛查发现的乳腺癌病例的分类和既往筛查乳房x光检查的回顾

Z. Gandomkar, S. Lewis, Somphone Siviengphanom, M. Suleiman, D. Wong, W. Reed, E. Ekpo, P. Brennan
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引用次数: 1

摘要

本研究旨在对基于独立双读仲裁的全视场数字乳房x光片上筛查出的乳腺癌的既往乳房x光片进行回顾。在常规乳腺癌筛查中诊断为乳腺癌的607名妇女的既往乳房x线照片分为“未检出”、“既往可见”和“既往未检出”。“遗漏”和“既往可见”病例的既往乳房x光片分别显示可诉和不可诉的可见癌症征象。“先前的Invis”病例在先前的乳房x光检查中没有明显的癌症迹象。“未检”、“在先可见”和“在先未见”的病例比例分别为25.5%、21.7%和52.7%。高密度病例所占比例在三类间差异无统计学意义(p值<0.05)。在侵入性(488例)和原位性(119例)病例中,病例分为“未诊”、“既往可见”和“既往未见”类别并无差异。在有创类别中,黄体酮(p值=0.015)和雌激素(p值=0.007)阳性以及ki-67中位评分(p值=0.006)在不同类别间差异显著,其中“在先Invis”患者的激素受体阴性比例最高。在侵袭性病例中,与“未发现”和“未发现”类别相比,3级(即更具侵袭性)癌症的百分比明显高于“未发现”类别(p值均<0.05)。原位病例的受体状态和乳腺癌分级在三类之间无显著差异。先验图像分类可以预测乳腺癌的侵袭性。如其他地方所示,更好地询问先前图像的技术可能会产生重要的患者结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification and reviewing of prior screening mammograms from screen-detected breast cancer cases
This study aimed at conducting a review of the prior mammograms of screen-detected breast cancers, found on full-field digital mammograms based on independent double reading with arbitration. The prior mammograms of 607 women diagnosed with breast cancer during routine breast cancer screening were categorized into “Missed”, “Prior Vis”, and “Prior Invis” . The prior mammograms of “Missed” and “Prior Vis” cases showed actionable and non-actionable visible cancer signs, respectively. The “Prior Invis” cases had no overt cancer signs on the prior mammograms. The percentage of cases classified as “Missed”, “Prior Vis”, and “Prior Invis” categories were 25.5%, 21.7%, 52.7%, respectively. The proportion of high-density cases showed no significant differences among the three categories (p-values<0.05). The breakdown of cases into “Missed”, “Prior Vis”, and “Prior Invis” categories did not differ between invasive (488) and in-situ (119) cases. In the invasive category, the progesterone (p-value=0.015) and estrogen (p-value=0.007) positivity and the median ki-67 score (p-value=0.006) differed significantly among the categories with the “Prior Invis” cases exhibiting the highest percentage of hormone receptors negativity. In the invasive cases, the percentage of cancers graded as 3 (i.e., more aggressive) were significantly more in the “Prior Invis” category compared to both “Missed” and “Prior Vis” categories (both p-values<0.05). The status of receptors and breast cancer grade for the in-situ cases did not differ significantly among the three categories. Prior images categorization can predict the aggressiveness of breast cancer. Techniques to better interrogate prior images as shown elsewhere may yield important patient outcomes.
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