Department of Pathology, King George's Medical University, Lucknow, India.
Department of Biostatistics and Health Informatics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India.
Diagn Cytopathol. 2022 Aug;50(8):375-385. doi: 10.1002/dc.24965. Epub 2022 Apr 16.
This study has been designed in an effort to identify the clinico-radiological and cytological features that could effectively help in differentiating cellular fibroadenoma (CFA) and phyllodes tumors (PT), which have several overlapping characteristics.
Histologically proven cases of CFA and PT were reviewed. Cytological features were assessed and categorized. Clinical and radiological details were also evaluated and he the two groups were compared statistically.
A total of 43 FA and 52 PT were specimens were reviewed. Mean age and tumor size for CFA and PT were 26.05 and 36.94 years, and 3.7 and 6.4 cm, respectively. Univariate analysis and regression models revealed that age >30 years, BIRADS grade of 4 or more, marked cellularity of stromal fragments, more than 30% spindle cells in background cell population and presence of traversing blood vessels in stromal fragments increased the odds of a tumor being phyllodes. The binary logistic regression model was able to predict PT accurately in 87.2% cases (p < .001).
PT and CFA could be differentiated if cytological findings are cautiously correlated clinically and radiologically. Age, BIRADS category along with assessment of stromal fragments and background population can effectively distinguish between CFA and PT.
本研究旨在识别有助于有效区分具有许多重叠特征的细胞性纤维腺瘤 (CFA) 和叶状肿瘤 (PT) 的临床放射学和细胞学特征。
回顾了经组织学证实的 CFA 和 PT 病例。评估和分类了细胞学特征。还评估了临床和放射学细节,并对两组进行了统计学比较。
共回顾了 43 例 FA 和 52 例 PT 标本。CFA 和 PT 的平均年龄和肿瘤大小分别为 26.05 岁和 36.94 岁,3.7 厘米和 6.4 厘米。单变量分析和回归模型显示,年龄 >30 岁、BIRADS 分级为 4 级或更高、间质碎片明显细胞增多、背景细胞群中超过 30%的梭形细胞和间质碎片中存在横切血管,这些都会增加肿瘤为叶状的几率。二元逻辑回归模型能够准确预测 87.2%的 PT 病例 (p < 0.001)。
如果细胞学发现与临床和放射学谨慎相关,则可以区分 PT 和 CFA。年龄、BIRADS 类别以及对间质碎片和背景人群的评估可以有效地区分 CFA 和 PT。