Blood Tumor Treatment Center, Beihua University Affiliated Hospital, Jilin, China.
Department of Radiology, Jilin Province Integrated Traditional Chinese and Western Medicine Hospital, Jilin, China.
Technol Health Care. 2024;32(3):1609-1618. doi: 10.3233/THC-230671.
Breast cancer has the second highest mortality rate of all cancers and occurs mainly in women.
To investigate the relationship between magnetic resonance imaging (MRI) radiomics features and histological grade of invasive ductal carcinoma (IDC) of the breast and to evaluate its diagnostic efficacy.
The two conventional MRI quantitative indicators, i.e. the apparent diffusion coefficient (ADC) and the initial enhancement rate, were collected from 112 patients with breast cancer. The breast cancer lesions were manually segmented in dynamic contrast-enhanced MRI (DCE-MRI) and ADC images, the differences in radiomics features between Grades I, II and III IDCs were compared and the diagnostic efficacy was evaluated.
The ADC values (0.77 ± 0.22 vs 0.91 ± 0.22 vs 0.92 ± 0.20, F= 4.204, p< 0.01), as well as the B_sum_variance (188.51 ± 67.803 vs 265.37 ± 77.86 vs 263.74 ± 82.58, F= 6.040, p< 0.01), L_energy (0.03 ± 0.02 vs 0.13 ± 0.11 vs 0.12 ± 0.14, F= 7.118, p< 0.01) and L_sum_average (0.78 ± 0.32 vs 16.34 ± 4.23 vs 015.45 ± 3.74, F= 21.860, p< 0.001) values of patients with Grade III IDC were significantly lower than those of patients with Grades I and II IDC. The B_uniform (0.15 ± 0.12 vs 0.11 ± 0.04 vs 0.12 ± 0.03, F= 3.797, p< 0.01) and L_SRE (0.85 ± 0.07 vs 0.78 ± 0.03 vs 0.79 ± 0.32, F= 3.024, p< 0.01) values of patients with Grade III IDC were significantly higher than those of patients with Grades I and II IDC. All differences were statistically significant (p< 0.05). The ADC radiomics signature model had a higher area-under-the-curve value in identifying different grades of IDC than the ADC value model and the DCE radiomics signature model (0.869 vs 0.711 vs 0.682). The accuracy (0.812 vs 0.647 vs 0.710), specificity (0.731 vs 0.435 vs 0.342), positive predictive value (0.815 vs 0.663 vs 0.669) and negative predictive value (0.753 vs 0.570 vs 0.718) of the ADC radiomics signature model were all significantly better than the ADC value model and the DCE radiomics signature model.
ADC values and breast MRI radiomics signatures are significant in identifying the histological grades of IDC, with the ADC radiomics signatures having greater value.
乳腺癌是所有癌症中死亡率第二高的癌症,主要发生在女性身上。
探讨磁共振成像(MRI)放射组学特征与乳腺浸润性导管癌(IDC)组织学分级的关系,并评估其诊断效能。
收集了 112 例乳腺癌患者的两种常规 MRI 定量指标,即表观扩散系数(ADC)和初始增强率。在动态对比增强 MRI(DCE-MRI)和 ADC 图像上手动对乳腺癌病变进行分割,比较 I、II 和 III 级 IDC 之间的放射组学特征差异,并评估其诊断效能。
ADC 值(0.77 ± 0.22 vs 0.91 ± 0.22 vs 0.92 ± 0.20,F= 4.204,p<0.01),以及 B_sum_variance(188.51 ± 67.803 vs 265.37 ± 77.86 vs 263.74 ± 82.58,F= 6.040,p<0.01)、L_energy(0.03 ± 0.02 vs 0.13 ± 0.11 vs 0.12 ± 0.14,F= 7.118,p<0.01)和 L_sum_average(0.78 ± 0.32 vs 16.34 ± 4.23 vs 015.45 ± 3.74,F= 21.860,p<0.001)值,III 级 IDC 患者显著低于 I 级和 II 级 IDC 患者。B_uniform(0.15 ± 0.12 vs 0.11 ± 0.04 vs 0.12 ± 0.03,F= 3.797,p<0.01)和 L_SRE(0.85 ± 0.07 vs 0.78 ± 0.03 vs 0.79 ± 0.32,F= 3.024,p<0.01)值,III 级 IDC 患者显著高于 I 级和 II 级 IDC 患者。所有差异均有统计学意义(p<0.05)。ADC 放射组学特征模型在识别不同等级 IDC 方面的曲线下面积值(AUC)高于 ADC 值模型和 DCE 放射组学特征模型(0.869 vs 0.711 vs 0.682)。ADC 放射组学特征模型的准确性(0.812 vs 0.647 vs 0.710)、特异性(0.731 vs 0.435 vs 0.342)、阳性预测值(0.815 vs 0.663 vs 0.669)和阴性预测值(0.753 vs 0.570 vs 0.718)均明显优于 ADC 值模型和 DCE 放射组学特征模型。
ADC 值和乳腺 MRI 放射组学特征在识别 IDC 的组织学分级方面具有显著意义,其中 ADC 放射组学特征具有更大的价值。