Fractal Analysis Method for the Complexity of Cell Cluster Staining on Breast FNAB
Fractal Analysis Method for the Complexity of Cell Cluster Staining on Breast FNAB
复制标题
DOI：
10.1159/000509668
复制
发表时间：
2021-01-01
期刊：
影响因子：
1.8
通讯作者：
Watanabe，Jun
中科院分区：
文献类型：
--
作者：
Yoshioka，Haruhiko;Herai，Anna;Watanabe，Jun
目的随着超声乳腺癌筛查精度的提高，影像学上无明确肿块或提取微囊肿的早期癌症病例有所增加，需要提高乳腺细针抽吸活检（FNAB）细胞学检查的准确性。本研究的目的是探讨簇灰度图像分形分析的有用性，评估深染色细胞簇（称为深染色拥挤细胞群（HCG））的簇暗度、簇不均匀性和增色性（簇密度）的复杂性，作为乳腺 FNAB 的细胞学辅助系统。研究设计从 10 名纤维腺瘤（FA）患者中收集了 100 个簇，从 9 名导管原位癌患者中收集了 90 个簇。 (DCIS)和11例非特殊类型浸润性乳腺癌(IBC-NST)患者的122个簇。(1)簇大小分类：簇分为小簇、中簇和大簇(小簇：小于40×10 2 μm 2；大簇：100×10 2 μm 2 或更大；中簇：中等)，并计算它们的频率。(2)簇灰度图像-分形分析：评估了（a）簇的暗度（亮度）、（b）簇的不均匀性（复杂性）和（c）簇密度的复杂性（圆度校正分形值）。统计分析采用多重比较Steel-Dwass检验，显着性水平p<0.05。结果(1)簇大小分类：FA中小、中、大簇出现频率相似，大簇出现频率(30%)显着高于其他疾病。 IBC-NST中出现较多小簇(61%)，其频率明显高于其他疾病，而大簇出现频率明显较低。(2)簇灰度图像分形分析：与IBC-NST相比，小簇亮度低(暗)，簇不均匀度高，簇密度复杂度高，而大簇亮度高(亮)，簇不均匀度高，簇密度复杂度高。 FA.结论簇灰度图像分形分析评估乳腺 FNAB HCG 中簇的暗度、簇不均匀性和簇密度的复杂性，是乳腺 FNA 的有用细胞学辅助系统。
ObjectiveBecause 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.Study DesignOne 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× 10 2 μm 2; large cluster: 100× 10 2 μm 2 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.Results(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.ConclusionCluster 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.