Xu Ye, Sun Jianghong, Guo Fei, Nanding Abiyasi, Li Qiyang, Jiang Dan
Department of Radiology, Harbin Medical University Cancer Hospital, Harbin, China.
Department of Pathology, Harbin Medical University Cancer Hospital, Harbin, China.
Front Genet. 2022 Feb 4;13:822858. doi: 10.3389/fgene.2022.822858. eCollection 2022.
To determine the independent risk factors associated with malignant nonspiculate and noncalcified masses (NSNCMs) and evaluate the predictive values of extratumoral structural abnormalities on digital mammography. A total of 435 patients were included between January and May 2018. Tumor signs included shape, density, and margin, which were evaluated. Extratumoral signs were classified into extratumoral structural abnormalities (parenchymal and trabecular) and halo; subclassification included contraction, distortion, pushing and atrophy sign of parenchyma, parallel, vertical, and reticular trabecula sign, and narrow and wide halo. Univariate and multivariate analysis was performed. The positive predictive value (PPV) of the independent predictor was calculated, and diagnostic performance was evaluated using the receiver operating characteristic curve. Of all cases, 243 (55.8%) were benign and 192 (44.2%) were malignant. Extratumoral contraction sign of parenchyma was the strongest independent predictor of malignancy (odds ratio [OR] 36.2, < 0.001; PPV = 96.6%), followed by parenchymal distortion sign (OR 10.2, < 0.001; PPV = 92%), parallel trabecula sign (OR 7.2, < 0.001; PPV = 85.6%), and indistinct margin of tumor (OR 4.3, < 0.001; PPV =70.9%), and also parenchymal atrophy sign, wide halo, vertical trabecula, age ≥ 47.5 years, irregular shape, and size ≥ 22.5 mm of tumor (OR range, 1.3-4.0; PPV range, 56.6-83.6%). The diagnostic performance of most of the extratumoral signs was between that of indistinct margin and irregular shape of tumor. The subclassification of extratumoral structural abnormalities has important predictive value for mammographic malignant NSNCM, which should be given more attention.
确定与恶性非毛刺状和非钙化肿块（NSNCMs）相关的独立危险因素，并评估数字化乳腺摄影中肿瘤外结构异常的预测价值。2018年1月至5月共纳入435例患者。评估肿瘤的征象，包括形态、密度和边缘。肿瘤外征象分为肿瘤外结构异常（实质和小梁）和晕圈；亚分类包括实质的收缩、扭曲、推挤和萎缩征，平行、垂直和网状小梁征，以及窄晕圈和宽晕圈。进行单因素和多因素分析。计算独立预测因素的阳性预测值（PPV），并使用受试者工作特征曲线评估诊断性能。所有病例中，243例（55.8%）为良性，192例（44.2%）为恶性。实质的肿瘤外收缩征是恶性肿瘤最强的独立预测因素（比值比[OR]36.2，<0.001；PPV=96.6%），其次是实质扭曲征（OR 10.2，<0.001；PPV=92%）、平行小梁征（OR 7.2，<0.001；PPV=85.6%）和肿瘤边缘不清（OR 4.3，<0.001；PPV=70.9%），还有实质萎缩征、宽晕圈、垂直小梁、年龄≥47.5岁、形态不规则和肿瘤大小≥22.5 mm（OR范围为1.3 - 4.0；PPV范围为56.6 - 83.6%）。大多数肿瘤外征象的诊断性能介于肿瘤边缘不清和形态不规则之间。肿瘤外结构异常的亚分类对乳腺钼靶恶性NSNCM具有重要的预测价值，应予以更多关注。
