From the Institute for Diagnostic and Interventional Radiology (D.Z., K.L., R.R., N.G.H., C.K., L.P., A.C.B., M.S., S.L.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
From the Institute for Diagnostic and Interventional Radiology (D.Z., K.L., R.R., N.G.H., C.K., L.P., A.C.B., M.S., S.L.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
AJNR Am J Neuroradiol. 2022 Feb;43(2):188-194. doi: 10.3174/ajnr.A7380. Epub 2022 Jan 6.
MR imaging is the technique of choice for follow-up of patients with brain metastases, yet the radiologic assessment is often tedious and error-prone, especially in examinations with multiple metastases or subtle changes. This study aimed to determine whether using automated color-coding improves the radiologic assessment of brain metastases compared with conventional reading.
One hundred twenty-one pairs of follow-up examinations of patients with brain metastases were assessed. Two radiologists determined the presence of progression, regression, mixed changes, or stable disease between the follow-up examinations and indicated subjective diagnostic certainty regarding their decisions in a conventional reading and a second reading using automated color-coding after an interval of 8 weeks.
The rate of correctly classified diagnoses was higher (91.3%, 221/242, versus 74.0%, 179/242, < .01) when using automated color-coding, and the median Likert score for diagnostic certainty improved from 2 (interquartile range, 2-3) to 4 (interquartile range, 3-5) (< .05) compared with the conventional reading. Interrater agreement was excellent (κ = 0.80; 95% CI, 0.71-0.89) with automated color-coding compared with a moderate agreement (κ = 0.46; 95% CI, 0.34-0.58) with the conventional reading approach. When considering the time required for image preprocessing, the overall average time for reading an examination was longer in the automated color-coding approach (91.5 [SD, 23.1] seconds versus 79.4 [SD, 34.7 ] seconds, < .001).
Compared with the conventional reading, automated color-coding of lesion changes in follow-up examinations of patients with brain metastases significantly increased the rate of correct diagnoses and resulted in higher diagnostic certainty.
磁共振成像（MRI）是脑转移瘤患者随访的首选技术，但放射学评估通常繁琐且容易出错，尤其是在有多个转移灶或细微变化的检查中。本研究旨在确定与传统阅读相比，使用自动彩色编码是否能改善脑转移瘤的放射学评估。
共评估了 121 对脑转移瘤患者的随访检查。两名放射科医生在传统阅读和 8 周后使用自动彩色编码的第二次阅读中，确定随访检查之间进展、消退、混合变化或稳定疾病的存在，并对其决策的主观诊断确定性进行评估。
使用自动彩色编码时，正确分类诊断的比例更高（91.3%，221/242，而 74.0%，179/242，<0.01），诊断确定性的中位数 Likert 评分从 2（四分位距，2-3）提高到 4（四分位距，3-5）（<0.05）与传统阅读相比。与传统阅读相比，自动彩色编码的观察者间一致性极好（κ=0.80；95%置信区间，0.71-0.89），而传统阅读的一致性为中度（κ=0.46；95%置信区间，0.34-0.58）。考虑到图像预处理所需的时间，自动彩色编码方法阅读检查的总平均时间较长（91.5[SD，23.1]秒与 79.4[SD，34.7]秒，<0.001）。
与传统阅读相比，脑转移瘤患者随访检查中病变变化的自动彩色编码显著提高了正确诊断率，并提高了诊断确定性。
