Sørensen Thomas Sangild, Beerbaum Philipp, Mosegaard Jesper, Rasmusson Allan, Schaeffter Tobias, Austin Conal, Razavi Reza, Greil Gerald Franz
Department of Computer Science, University of Aarhus, Aabogade 34, 8200, Aarhus N, Denmark.
Pediatr Radiol. 2008 Dec;38(12):1314-22. doi: 10.1007/s00247-008-1032-5. Epub 2008 Oct 25.
Patient-specific preoperative planning in complex congenital heart disease may be greatly facilitated by virtual cardiotomy. Surgeons can perform an unlimited number of surgical incisions on a virtual 3-D reconstruction to evaluate the feasibility of different surgical strategies.
To quantitatively evaluate the quality of the underlying imaging data and the accuracy of the corresponding segmentation, and to qualitatively evaluate the feasibility of virtual cardiotomy.
A whole-heart MRI sequence was applied in 42 children with congenital heart disease (age 3 +/- 3 years, weight 13 +/- 9 kg, heart rate 96 +/- 21 bpm). Image quality was graded 1-4 (diagnostic image quality > or =2) by two independent blinded observers. In patients with diagnostic image quality the segmentation quality was also graded 1-4 (4 no discrepancies, 1 misleading error).
The average image quality score was 2.7 - sufficient for virtual reconstruction in 35 of 38 patients (92%) older than 1 month. Segmentation time was 59 +/- 10 min (average quality score 3.5). Virtual cardiotomy was performed in 19 patients.
Accurate virtual reconstructions of patient-specific cardiac anatomy can be produced in less than 1 h from 3-D MRI. The presented work thus introduces a new, clinically feasible noninvasive technique for improved preoperative planning in complex cases of congenital heart disease.
虚拟心脏切开术可极大地促进复杂先天性心脏病患者的术前个性化规划。外科医生可以在虚拟三维重建上进行无限数量的手术切口，以评估不同手术策略的可行性。
定量评估基础成像数据的质量和相应分割的准确性，并定性评估虚拟心脏切开术的可行性。
对42例先天性心脏病患儿（年龄3±3岁，体重13±9 kg，心率96±21次/分钟）应用全心MRI序列。由两名独立的盲法观察者将图像质量评为1-4级（诊断图像质量≥2级）。对于诊断图像质量的患者，分割质量也评为1-4级（4级无差异，1级有误导性错误）。
平均图像质量评分为2.7——对于38例年龄大于1个月的患者中的35例（92%），足以进行虚拟重建。分割时间为59±10分钟（平均质量评分3.5）。对19例患者进行了虚拟心脏切开术。
从三维MRI可在不到1小时内生成患者特异性心脏解剖结构的准确虚拟重建。因此，本研究介绍了一种新的、临床可行的非侵入性技术，用于改善复杂先天性心脏病病例的术前规划。
