Is training essential for interpreting cardiac computed tomography?
BACKGROUND
Cardiac computed tomography (CT) has gained increasing acceptance for diagnosing obstructive coronary artery disease (CAD). Several guidelines have been published on required education for proficiency in the interpretation of these examinations.


OBJECTIVE
To describe the learning-curve effect of the interpretation of 100 consecutive cardiac CT examinations aimed at diagnosing CAD. The diagnostic accuracy of radiologists and radiographers was also compared.


METHODS
Two radiologists and two radiographers, all with no prior experience in evaluation of cardiac CT, independently underwent a dedicated training program of 100 examinations randomized into 10 blocks (sessions), with 10 cases in each. They independently evaluated the coronary arteries regarding significant obstructive CAD. After every session, individual feedback on diagnostic accuracy and comparison with the corresponding invasive coronary angiography (currently regarded as the gold standard to detect coronary lesions) was given. The time required for interpretation was recorded.


RESULTS
The mean review time decreased (P<0.0001) successively during the 10 sessions for all the observers together. The first session had a mean review time of 32 min, and the last session 16 min. No significant improvement in sensitivity, specificity, or negative predictive value (NPV) was observed. For positive predictive value (PPV), there was an improvement for the radiologists (P<0.05), but not for the radiographers. The radiographers had a higher total specificity compared to the radiologists (P<0.01).


CONCLUSIONS
The review time for novices in cardiac CT was approximately halved during the first 100 cases, with maintained accuracy. There was a learning-curve effect in PPV for the radiologists. The diagnostic accuracy of dedicated radiographers indicates that they might be considered to be included as part of the evaluation team.
Ripsweden
J
J
Division of Radiology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden. jonaz.ripsweden@ki.se
Mir-Akbari
H
H
Brolin
E Bacsovics
EB
Brismar
T
T
Nilsson
T
T
Rasmussen
E
E
Rück
A
A
Svensson
A
A
Werner
C
C
Winter
R
R
Cederlund
K
K
D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D016009:Chi-Square Distribution; D002983:Clinical Competence / Q000706:statistics & numerical data*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007318:Inservice Training; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed