Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (K.N., Y.J.S., K.H., Y.J.K., B.W.C.).
Department of Radiology, Seoul National University College of Medicine, Seoul National University, Korea (S.J.P.).
Circ Cardiovasc Imaging. 2019 Nov;12(11):e009496. doi: 10.1161/CIRCIMAGING.119.009496. Epub 2019 Nov 19.
We aimed to determine whether quantitative computed tomography radiomic features can aid in differentiating between the causes of prosthetic valve obstruction (PVO) in patients who had undergone prosthetic valve replacement.
This retrospective study included 39 periprosthetic masses in 34 patients who underwent cardiac computed tomography scan from January 2014 to August 2017 and were clinically suspected as PVO. The cause of PVO was assessed by redo-surgery and follow-up imaging as standard reference, and classified as pannus, thrombus, or vegetation. Visual analysis was performed to assess the possible cause of PVO on axial and valve-dedicated views. Computed tomography radiomic analysis of periprosthetic masses was performed and radiomic features were extracted. The advantage of radiomic score compared with visual analysis for differentiation of pannus from other abnormalities was assessed.
Of 39 masses, there were 20 cases of pannus, 11 of thrombus, and 8 of vegetation on final diagnosis. The radiomic score was significantly higher in the pannus group compared with nonpannus group (mean, -0.156±0.422 versus -0.883±0.474; <0.001). The area under the curve of radiomic score for diagnosis of pannus was 0.876 (95% CI, 0.731-0.960). Combination of radiomic score and visual analysis showed a better performance for the differentiation of pannus than visual analysis alone.
Compared with visual analysis, computed tomography radiomic features may have added value for differentiating pannus from thrombus or vegetation in patients with suspected PVO.
我们旨在确定定量计算机断层扫描（CT）放射组学特征是否有助于区分接受人工瓣膜置换术的患者发生人工瓣膜梗阻（PVO）的原因。
本回顾性研究纳入了 2014 年 1 月至 2017 年 8 月期间接受心脏 CT 扫描且临床上疑似 PVO 的 34 名患者的 39 个瓣周肿块。PVO 的病因通过再次手术和随访影像学评估作为标准参考，并分为假性血栓、血栓或赘生物。通过轴位和瓣膜专用视图进行视觉分析，以评估 PVO 可能的原因。对瓣周肿块进行 CT 放射组学分析并提取放射组学特征。评估放射组学评分与视觉分析相比，在区分假性血栓与其他异常方面的优势。
39 个肿块中，最终诊断为 20 例假性血栓、11 例血栓和 8 例赘生物。假性血栓组的放射组学评分明显高于非假性血栓组（均值，-0.156±0.422 与-0.883±0.474；<0.001）。放射组学评分诊断假性血栓的曲线下面积为 0.876（95%CI，0.731-0.960）。放射组学评分与视觉分析相结合在区分假性血栓与血栓或赘生物方面的表现优于单独的视觉分析。
与视觉分析相比，CT 放射组学特征可能有助于区分疑似 PVO 患者的假性血栓与血栓或赘生物。
