Department of Radiology, West China Hospital, Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China.
BMC Cardiovasc Disord. 2022 May 21;22(1):235. doi: 10.1186/s12872-022-02671-0.
To elucidate the value of texture analysis (TA) in detecting and differentiating myocardial tissue alterations on T2-weighted CMR (cardiovascular magnetic resonance imaging) in patients with cardiac amyloidosis (CA) and hypertrophic cardiomyopathy (HCM).
In this retrospective study, 100 CA (58.5 ± 10.7 years; 41 (41%) females) and 217 HCM (50.7 ± 14.8 years, 101 (46.5%) females) patients who underwent CMR scans were included. Regions of interest for TA were delineated by two radiologists independently on T2-weighted imaging (T2WI). Stepwise dimension reduction and texture feature selection based on reproducibility, machine learning algorithms, and correlation analyses were performed to select features. Both the CA and HCM groups were randomly divided into a training dataset and a testing dataset (7:3). After the TA model was established in the training set, the diagnostic performance of the model was validated in the testing set and further validated in a subgroup of patients with similar hypertrophy.
The 7 independent texture features provided, in combination, a diagnostic accuracy of 86.0% (AUC = 0.915; 95% CI 0.879-0.951) in the training dataset and 79.2% (AUC = 0.842; 95% CI 0.759-0.924) in the testing dataset. The differential diagnostic accuracy in the similar hypertrophy subgroup was 82.2% (AUC = 0.864, 95% CI 0.805-0.922). The significance of the difference between the AUCs of the TA model and late gadolinium enhancement (LGE) was verified by Delong's test (p = 0.898). All seven texture features showed significant differences between CA and HCM (all p < 0.001).
Our study demonstrated that texture analysis based on T2-weighted images could feasibly differentiate CA from HCM, even in patients with similar hypertrophy. The selected final texture features could achieve a comparable diagnostic capacity to the quantification of LGE. Trial registration Since this study is a retrospective observational study and no intervention had been involved, trial registration is waived.
在患有心脏淀粉样变性(CA)和肥厚型心肌病(HCM)的患者中,利用 T2 加权心脏磁共振成像(CMR)检测和区分心肌组织改变,阐明纹理分析(TA)的价值。
在这项回顾性研究中,纳入了 100 例 CA(58.5±10.7 岁;41[41%]名女性)和 217 例 HCM(50.7±14.8 岁,101[46.5%]名女性)患者,这些患者均接受了 CMR 扫描。由两名放射科医生在 T2 加权成像(T2WI)上独立勾画 TA 的感兴趣区。基于可重复性、机器学习算法和相关性分析,进行逐步降维和纹理特征选择,以选择特征。将 CA 和 HCM 两组患者随机分为训练数据集和测试数据集(7:3)。在训练集中建立 TA 模型后,在测试集中验证模型的诊断性能,并在具有相似肥大的患者亚组中进一步验证。
这 7 个独立的纹理特征结合起来,在训练数据集的诊断准确率为 86.0%(AUC=0.915;95%CI 0.879-0.951),在测试数据集的诊断准确率为 79.2%(AUC=0.842;95%CI 0.759-0.924)。在相似肥大亚组中,鉴别诊断的准确率为 82.2%(AUC=0.864,95%CI 0.805-0.922)。通过 Delong 检验验证了 TA 模型和钆延迟增强(LGE)之间 AUC 差异的显著性(p=0.898)。所有 7 个纹理特征在 CA 和 HCM 之间均有显著差异(均 p<0.001)。
本研究表明,基于 T2 加权图像的纹理分析可以有效地将 CA 与 HCM 区分开来,即使在具有相似肥大的患者中也是如此。所选的最终纹理特征可以达到与 LGE 定量相当的诊断能力。
由于本研究是一项回顾性观察性研究,且未涉及任何干预措施,因此无需进行试验注册。