Department of Radiology, Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, China.
Department of Breast Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, China.
Magn Reson Imaging. 2024 Jun;109:91-95. doi: 10.1016/j.mri.2024.03.008. Epub 2024 Mar 10.
This study intended to investigate the feasibility and effectiveness of using clinical magnetic resonance imaging (MRI) radiomics features to predict lymphovascular invasion (LVI) status in breast cancer (BC) patients.
A total of 182 BC patients were retrospectively collected and randomly divided into a training set (n = 127) and a validation set (n = 55) in a 7:3 ratio. Based on pathological examination results, the training set was further divided into LVI group (n = 60) and non-LVI group (n = 67), and the validation set was divided into LVI group (n = 24) and non-LVI group (n = 31). General data and MRI examination indicators were compared. Multivariate logistic regression was utilized to analyze MRI radiomics features and clinically relevant indicators that were significant in the baseline information of patients in training set, independent risk factors were identified, and a logistic regression model was built. The accuracy of logistic model was validated using ROC curves in training and validation sets.
Age, pathohistological classification, tumor length, tumor width, presence or absence of Magnetic Resonance Spectroscopy (MRS) cho peak, presence or absence of spicule sign, peritumoral enhancement, and peritumoral edema were statistically significant (P < 0.05) between the two groups. Multivariate logistic regression analysis presented that spicule and peritumoral edema were independent risk factors for LVI in BC patients (P < 0.05). The ROC curve illustrated that AUC of the logistic regression model in the training set was 0.807 (95%CI: 0.730-0.885) and that in the validation set was 0.837 (95%CI: 0.731-0.944).
Radiomics features of spicule sign and peritumoral edema were independent risk factors for LVI in BC patients. A logistic regression model based on these factors, along with age, could accurately predict LVI occurrence in BC patients, providing data support for diagnosis and modeling of LVI in BC patients.
本研究旨在探讨使用临床磁共振成像（MRI）放射组学特征预测乳腺癌（BC）患者淋巴血管侵犯（LVI）状态的可行性和有效性。
回顾性收集了 182 例 BC 患者，按照 7:3 的比例随机分为训练集（n=127）和验证集（n=55）。基于病理检查结果，训练集进一步分为 LVI 组（n=60）和非 LVI 组（n=67），验证集分为 LVI 组（n=24）和非 LVI 组（n=31）。比较一般资料和 MRI 检查指标。对训练集患者基线信息中具有统计学意义的 MRI 放射组学特征和临床相关指标进行多变量逻辑回归分析，确定独立危险因素，建立逻辑回归模型。采用 ROC 曲线在训练集和验证集验证逻辑模型的准确性。
年龄、病理组织学分类、肿瘤长度、肿瘤宽度、磁共振波谱（MRS）cho 峰存在或缺失、毛刺征存在或缺失、瘤周强化、瘤周水肿在两组间差异有统计学意义（P<0.05）。多变量逻辑回归分析显示，毛刺征和瘤周水肿是 BC 患者发生 LVI 的独立危险因素（P<0.05）。ROC 曲线表明，训练集逻辑回归模型的 AUC 为 0.807（95%CI：0.730-0.885），验证集的 AUC 为 0.837（95%CI：0.731-0.944）。
毛刺征和瘤周水肿的放射组学特征是 BC 患者发生 LVI 的独立危险因素。基于这些因素和年龄建立的逻辑回归模型可以准确预测 BC 患者 LVI 的发生，为 BC 患者 LVI 的诊断和建模提供数据支持。
