Tagged cine magnetic resonance imaging with a finite element model can predict the severity of retrosternal adhesions prior to redo cardiac surgery.
OBJECTIVE
Reoperative median sternotomy entails a risk of damaging the heart or great vessels. If the severity of retrosternal adhesion is accurately assessed before sternal re-entry, resternotomy-related complications can be prevented. The purpose of this investigation was to evaluate whether the severity of retrosternal adhesions can be accurately predicted by tagged cine magnetic resonance imaging.


METHODS
Thirteen patients who were scheduled to undergo cardiac reoperation were investigated by electrocardiography-gated tagged cine magnetic resonance imaging before sternal re-entry. With the imaging data, the severity of retrosternal adhesion was scored visually on the basis of abnormality in regional myocardial motion and discordance in the tagged signals of the sternum and the myocardium. Also, with the aid of a finite element model, strain at the surface of the right ventricle was calculated on the basis of displacement of the tags on the heart over the cardiac cycle. For comparison, the adhesion severity was scored visually at the time of redo surgery by surgeons who were blinded to the preoperative assessment.


RESULTS
The preoperative adhesion severity score, as determined visually by tagged cine magnetic resonance imaging, was correlated with the intraoperative severity score (correlation coefficient: r = 0.76, P < .01). Mean strain at the surface of the heart, as calculated preoperatively by finite element model analysis, was inversely correlated with the intraoperative adhesion severity score (r = -0.78, P < .01).


CONCLUSIONS
Tagged cine magnetic resonance imaging with a finite element model can provide an accurate quantitative assessment of retrosternal adhesions before redo cardiac surgery.
Yoshioka
Ichiro
I
Department of Cardiovascular Surgery, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Saiki
Yoshikatsu
Y
Ichinose
Azusa
A
Takase
Kei
K
Takahashi
Shoki
S
Ohashi
Toshiro
T
Sato
Masaaki
M
Tabayashi
Koichi
K