Department of Bioscience and Laboratory Medicine, Hirosaki University Graduate School of Health Sciences, Hirosaki, Japan,
Department of Bioscience and Laboratory Medicine, Hirosaki University Graduate School of Health Sciences, Hirosaki, Japan.
Acta Cytol. 2021;65(1):4-12. doi: 10.1159/000509668. Epub 2020 Aug 25.
Because of the increased precision of ultrasound breast cancer screening, early cancer cases with no clear mass or extraction of microcysts on imaging have recently increased, and improvement of the accuracy of breast fine-needle aspiration biopsy (FNAB) cytology is needed. The objective of this study was to investigate the usefulness of cluster gray image-fractal analysis evaluating the darkness of clusters, cluster unevenness, and complexity of hyperchromicity (cluster density) of deep-stained cell clusters, known as hyperchromatic crowded cell groups (HCG), on FNAB as a cytology assistance system for breast FNAB.
One hundred clusters collected from 10 patients with fibroadenoma (FA), 90 clusters from 9 patients with ductal carcinoma in situ (DCIS), and 122 clusters from 11 patients with invasive breast carcinoma of no special type (IBC-NST) were used. (1) Cluster size classification: clusters were classified into small, middle, and large clusters (small cluster: smaller than 40 × 102 μm2; large cluster: 100 × 102 μm2 or larger; middle cluster: intermediate), and their frequency was calculated. (2) Cluster gray image-fractal analysis: (a) the darkness of clusters (luminance), (b) cluster unevenness (complexity), and (c) complexity of cluster density (roundness-corrected fractal value) were assessed. For statistical analysis, the multiple comparison Steel-Dwass test was used, with a significance level of p < 0.05.
(1) Cluster size classification: in FA, small, middle, and large clusters appeared at a similar frequency, and the frequency (30%) of large clusters was significantly higher than that in other diseases. In IBC-NST, many small clusters (61%) appeared and their frequency was significantly higher than that in other diseases, whereas the frequency of large clusters was significantly lower. (2) Cluster gray image-fractal analysis: in IBC-NST, the luminance of small clusters was low (dark), the cluster unevenness was high, and the complexity of cluster density was high, whereas the luminance of large clusters was high (bright), the cluster unevenness was high, and complexity of cluster density was high compared with those in FA.
Cluster gray image-fractal analysis evaluating the darkness of clusters, cluster unevenness, and complexity of cluster density in breast FNAB HCG is a useful cytology assistance system for breast FNA.
由于超声乳腺癌筛查的精度提高，最近在影像学上出现了无明显肿块或微囊提取的早期癌症病例，因此需要提高乳腺细针抽吸活检（FNAB）细胞学的准确性。本研究的目的是探讨簇状灰度图像-分形分析评估簇状暗度、簇不均匀性和深染细胞簇（称为嗜色拥挤细胞群[HCG]）的复杂性（簇密度）在 FNAB 中的作为乳腺 FNAB 的细胞学辅助系统的有用性。
从 10 例纤维腺瘤（FA）患者中收集了 100 个簇，从 9 例导管原位癌（DCIS）患者中收集了 90 个簇，从 11 例非特殊类型浸润性乳腺癌（IBC-NST）患者中收集了 122 个簇。（1）簇大小分类：将簇分为小、中、大簇（小簇：小于 40×102μm2；大簇：100×102μm2 或更大；中簇：中间），并计算其频率。（2）簇状灰度图像分形分析：（a）评估簇状暗度（亮度），（b）簇不均匀性（复杂性）和（c）簇密度复杂性（校正圆度的分形值）。进行统计分析时，使用多重比较 Steel-Dwass 检验，显著性水平为 p<0.05。
（1）簇大小分类：在 FA 中，小、中、大簇的出现频率相似，大簇的频率（30%）明显高于其他疾病。在 IBC-NST 中，出现了许多小簇（61%），其频率明显高于其他疾病，而大簇的频率明显降低。（2）簇状灰度图像分形分析：在 IBC-NST 中，小簇的亮度低（暗），簇不均匀度高，簇密度复杂性高，而大簇的亮度高（亮），簇不均匀度高，簇密度复杂性高与 FA 相比。
评估乳腺 FNAB HCG 中簇状暗度、簇不均匀性和簇密度复杂性的簇状灰度图像分形分析是一种有用的乳腺 FNA 细胞学辅助系统。
