Integration of 3D reconstruction in the SELection criteria for Excessive Crossing Times for Magnetically Supported Percutaneous Coronary Intervention. SELECT-MP.
OBJECTIVE
To develop a clinical prediction rule based on 3D reconstruction of coronary arteries that would prospectively identify lesions that are difficult to cross and could benefit from magnetic navigation.


RESULTS
The coronary anatomy of a cohort of 120 lesions that had undergone percutaneous coronary intervention (derivation set) was analysed using 3D reconstruction for vessel and lesion characteristics. The crossing time was the total clock time to reach a satisfactory distal position after leaving the guiding catheter. Multivariable logistic regression and linear shrinkage with bootstrapping were used to develop a clinical prediction rule that dichotomised cases into easy or difficult (prolonged crossing time). A value of 6 was the best cut-off value. This clinical prediction rule was applied to a second independent cohort of patients (validation set) where crossing time was measured. The bootstrapped c-statistic of the model was 0.82 indicating excellent discrimination.


CONCLUSIONS
3D reconstruction helped to develop a simple, accurate clinical prediction rule to identify difficult cases for conventional wires and in whom magnetic navigation may be preferable.
Patterson
Mark S
MS
Amsterdam Department of Interventional Cardiology, Onze Lieve Vrouwe Gasthuis, Amsterdam, The Netherlands. markspatterson@doctors.net.uk
Hoeks
Sanne E
SE
Rijkenberg
Saskia
S
Ramchartar
Steve
S
van Guens
Robert Jan
RJ
Tanimoto
Shuzou
S
van Domburg
Ron T
RT
Serruys
Patrick W
PW
D000368:Aged; D000465:Algorithms; D015906:Angioplasty, Balloon, Coronary / Q000009:adverse effects / Q000379:methods*; D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000628:therapy; D020000:Decision Support Systems, Clinical; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D016015:Logistic Models; D008280:Magnetics; D008297:Male; D008875:Middle Aged; D018579:Patient Selection; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D018570:Risk Assessment; D013997:Time Factors; D014584:User-Computer Interface