Li Yuan, Wei Xiu-Liang, Pang Kun-Kun, Ni Ping-Juan, Wu Mei, Xiao Juan, Zhang Lu-Lu, Zhang Fei-Xue
Department of Ultrasound, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Center of Evidence-Based Medicine, Institute of Medical Sciences, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Front Oncol. 2023 Oct 23;13:1276524. doi: 10.3389/fonc.2023.1276524. eCollection 2023.
To analyze the clinical and ultrasonic characteristics of breast sclerosing adenosis (SA) and invasive ductal carcinoma (IDC), and construct a predictive nomogram for SA.
A total of 865 patients were recruited at the Second Hospital of Shandong University from January 2016 to November 2022. All patients underwent routine breast ultrasound examinations before surgery, and the diagnosis was confirmed by histopathological examination following the operation. Ultrasonic features were recorded using the Breast Imaging Data and Reporting System (BI-RADS). Of the 865 patients, 203 (252 nodules) were diagnosed as SA and 662 (731 nodules) as IDC. They were randomly divided into a training set and a validation set at a ratio of 6:4. Lastly, the difference in clinical characteristics and ultrasonic features were comparatively analyzed.
There was a statistically significant difference in multiple clinical and ultrasonic features between SA and IDC (<0.05). As age and lesion size increased, the probability of SA significantly decreased, with a cut-off value of 36 years old and 10 mm, respectively. In the logistic regression analysis of the training set, age, nodule size, menopausal status, clinical symptoms, palpability of lesions, margins, internal echo, color Doppler flow imaging (CDFI) grading, and resistance index (RI) were statistically significant (<0.05). These indicators were included in the static and dynamic nomogram model, which showed high predictive performance, calibration and clinical value in both the training and validation sets.
SA should be suspected in asymptomatic young women, especially those younger than 36 years of age, who present with small-size lesions (especially less than 10 mm) with distinct margins, homogeneous internal echo, and lack of blood supply. The nomogram model can provide a more convenient tool for clinicians.
分析乳腺硬化性腺病（SA）和浸润性导管癌（IDC）的临床及超声特征，并构建SA的预测列线图。
2016年1月至2022年11月，山东大学齐鲁医院共纳入865例患者。所有患者术前均接受常规乳腺超声检查，术后经组织病理学检查确诊。采用乳腺影像报告和数据系统（BI-RADS）记录超声特征。865例患者中，203例（252个结节）诊断为SA，662例（731个结节）诊断为IDC。按照6:4的比例随机分为训练集和验证集。最后，对临床特征和超声特征的差异进行比较分析。
SA和IDC在多个临床和超声特征上存在统计学显著差异（<0.05）。随着年龄和病变大小增加，SA的概率显著降低，截断值分别为36岁和10 mm。在训练集的逻辑回归分析中，年龄、结节大小、绝经状态、临床症状、病变可触及性、边界、内部回声、彩色多普勒血流成像（CDFI）分级和阻力指数（RI）具有统计学意义（<0.05）。这些指标被纳入静态和动态列线图模型，在训练集和验证集中均显示出较高的预测性能、校准度和临床价值。
对于无症状的年轻女性，尤其是年龄小于36岁、病变较小（尤其是小于10 mm）、边界清晰、内部回声均匀且无血供的患者，应怀疑为SA。列线图模型可为临床医生提供更便捷的工具。
