Correlation Between Pharmacokinetic Analysis of DCE-MRI and Breast Image Reporting and Data System (BIRADS) Classification

Xia Wu, Yulong Qi, Fei Feng, Guanxun Cheng, N. Zhang
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Abstract

To determine if pharmacokinetic information derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) could improve the diagnostic value of breast disease. A total of thirty-six female patients (range, 30-70 years, mean 48.1±12.6 years) confirmed BIRADS 3~6 underwent DCE-MRI were retrospectively recruited to this study. Modified two-compartment Tofts model and Brix mode were used to obtain relevant tracer kinetic parameters. Mann-Whitney U-test was used to compare the parameters between the BIRADS 3 and 4, BIRADS 4 and 5, BIRADS 5 and 6, respectively. A P value of less than 0.05 was considered to indicate a significant difference. In evaluating significance between BIRADS 3 and BIRADS 4, the statistical analysis showed that Brix-kep (P=0.014), ABrix (P<0.001), TTP (P=0.022) were independent factors associated with the discrepancy. All kinetic parameters we calculated were independent factors associated with the discrepancy between BIRADS 4 and BIRADS 5. ABrix (AUC=0.915) do have a good discriminative power between BIRADS 3 and 4. Tofts-kep (AUC= 0.952), ABrix (AUC= 0.990) do have a good discriminative power between BIRADS 4 and 5.The numeric values of Brix-kep, Brix-kel, ABrix, Tofts-ktrans, Tofts-kep and Slope were higher in high grades (BIRADS 5 and BIRADS 6) than in low grades (BIRADS 3 and BIRADS 4) tumors. ABrix have a good discriminative power between BIRADS 3 and 4. Tofts-kep, ABrix do have a good discriminative power between BIRADS 4 and 5. No significant difference between BIRADS 5 and 6.
DCE-MRI药代动力学分析与乳腺图像报告和数据系统(BIRADS)分类的相关性
目的探讨动态增强磁共振成像(DCE-MRI)的药代动力学信息是否能提高乳腺疾病的诊断价值。回顾性招募36例经DCE-MRI证实BIRADS 3~6的女性患者(年龄30 ~ 70岁,平均48.1±12.6岁)。采用改进的双室Tofts模型和Brix模型获得了相关的示踪剂动力学参数。采用Mann-Whitney u检验分别比较BIRADS 3与4、BIRADS 4与5、BIRADS 5与6的参数。P值小于0.05为差异有统计学意义。在评价BIRADS 3与BIRADS 4之间的显著性时,统计学分析显示Brix-kep (P=0.014)、ABrix (P<0.001)、TTP (P=0.022)是导致差异的独立因素。我们计算的所有动力学参数都是与BIRADS 4和BIRADS 5差异相关的独立因素。ABrix (AUC=0.915)在BIRADS 3和BIRADS 4之间有很好的判别能力。tofts - keep (AUC= 0.952)和ABrix (AUC= 0.990)在BIRADS 4和BIRADS 5之间具有较好的判别能力。brix - keep、Brix-kel、ABrix、Tofts-ktrans、tofts - keep和Slope的数值在高分级(BIRADS 5和BIRADS 6)肿瘤中高于低分级(BIRADS 3和BIRADS 4)肿瘤。ABrix对BIRADS 3和BIRADS 4具有较好的判别能力。尽管如此,ABrix在BIRADS 4和BIRADS 5之间确实有很好的区分能力。BIRADS 5和6之间无显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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