Department of Radiology, the Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong Province, People's Republic of China, China.
Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong Province, People's Republic of China, China.
Br J Radiol. 2022 Apr 1;95(1132):20210466. doi: 10.1259/bjr.20210466. Epub 2022 Jan 7.
To evaluate whether contrast-enhanced cone-beam breast CT (CE-CBBCT) features can risk-stratify prognostic stage in breast cancer.
Overall, 168 biopsy-proven breast cancer patients were analysed: 115 patients in the training set underwent scanning using v. 1.5 CE-CBBCT between August 2019 and December 2019, whereas 53 patients in the test set underwent scanning using v. 1.0 CE-CBBCT between May 2012 and August 2014. All patients were restaged according to the American Joint Committee on Cancer eighth edition prognostic staging system. Following the combination of CE-CBBCT imaging parameters and clinicopathological factors, predictors that were correlated with stratification of prognostic stage via logistic regression were analysed. Predictive performance was assessed according to the area under the receiver operating characteristic curve (AUC). Goodness-of-fit of the models was assessed using the Hosmer-Lemeshow test.
As regards differentiation between prognostic stage (PS) I and II/III, increased tumour-to-breast volume ratio (TBR), rim enhancement pattern, and the presence of penetrating vessels were significant predictors for PS II/III disease ( < 0.05). The AUCs in the training and test sets were 0.967 [95% confidence interval (CI) 0.938-0.996; < 0.001] and 0.896 (95% CI, 0.809-0.983; = 0.001), respectively. Two features were selected in the training set of PS II III, including tumour volume [odds ratio (OR)=1.817, = 0.019] and calcification (OR = 4.600, = 0.040), achieving an AUC of 0.790 (95% CI, 0.636-0.944, = 0.001). However, there was no significant difference in the test set of PS II III (0.05).
CE-CBBCT imaging biomarkers may provide a large amount of anatomical and radiobiological information for the pre-operative distinction of prognostic stage.
CE-CBBCT features have distinctive promise for stratification of prognostic stage in breast cancer.
评估对比增强锥形束乳腺 CT(CE-CBBCT)特征能否对乳腺癌的预后分期进行风险分层。
共分析了 168 例经活检证实的乳腺癌患者:115 例患者在训练集中于 2019 年 8 月至 12 月接受 v.1.5CE-CBBCT 扫描,而 53 例患者在测试集中于 2012 年 5 月至 2014 年 8 月接受 v.1.0CE-CBBCT 扫描。所有患者均根据美国癌症联合委员会第八版预后分期系统重新分期。在结合 CE-CBBCT 成像参数和临床病理因素后,通过逻辑回归分析与预后分期分层相关的预测因素。根据受试者工作特征曲线(ROC)下面积(AUC)评估预测性能。通过 Hosmer-Lemeshow 检验评估模型的拟合优度。
在区分预后分期(PS)I 期和 II/III 期方面,肿瘤与乳房体积比(TBR)增加、边缘强化模式和穿透血管的存在是 PS II/III 疾病的显著预测因子(<0.05)。训练集和测试集的 AUC 分别为 0.967[95%置信区间(CI)0.938-0.996;<0.001]和 0.896(95%CI,0.809-0.983;=0.001)。在 PS II/III 的训练集中选择了两个特征,包括肿瘤体积[比值比(OR)=1.817,=0.019]和钙化(OR=4.600,=0.040),AUC 为 0.790(95%CI,0.636-0.944,=0.001)。然而,在 PS II/III 的测试集中差异无统计学意义(0.05)。
CE-CBBCT 成像生物标志物可为术前区分预后分期提供大量解剖学和放射生物学信息。
CE-CBBCT 特征有望对乳腺癌的预后分期进行分层。