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Erschienen in:
01.12.2012 | Original Article
A model for the prediction of a successful stress-first Tc-99m SPECT MPI
Erschienen in: Journal of Nuclear Cardiology | Ausgabe 6/2012
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Background
Stress-only Tc-99m MPI saves time, radiation exposure, and a normal study has a benign prognosis. However, a stress-first protocol is relatively labor intensive requiring pre-test screening for suitability and early post-stress image review to determine the need for rest imaging. The purpose of this study was to develop a simple clinical score used prior to a patient’s myocardial perfusion imaging (MPI) study to determine if they should undergo a stress-first protocol.
Methods
We reviewed all patients who underwent Tc-99m SPECT MPI over a 27-month period and divided them into derivation and validation cohorts. Patients were categorized as having a successful stress-first protocol based on a summed stress score ≤1, with or without attenuation correction. We generated a multivariable model from the derivation cohort to identify demographic and clinical correlates of successful stress-first imaging. Two validation cohorts using a CZT and a conventional SPECT camera were then used to test the performance of the model.
Results
The derivation cohort included 1,996 patients and the validation cohort consisted of 1,005 CZT SPECT patients and 2,430 conventional SPECT patients. The following variables were associated with unsuccessful (i.e., abnormal) stress-first imaging: age >65 years (1 point), diabetes (2 points), typical chest pain (2 points), congestive heart failure (3 points), abnormal ECG (4 points), male gender (4 points), and documented CAD (5 points). Emergency Department location (−2 points) was negatively associated with an unsuccessful protocol. An increasing score showed a strong association with an unsuccessful stress-first protocol in both the derivation and the validation cohorts (P < .0001) and dividing the cohorts into low (<5), intermediate (≥5 and <10), and high (≥10) risk scores accurately stratified patients based on their frequencies of unsuccessful stress-first imaging. ROC curve analysis showed excellent prediction in both the derivation and the validation cohorts with an area under the curve of 0.82 and 0.75-0.83, respectively.
Conclusions
This pre-test scoring tool accurately identifies patients who can successfully undergo a stress-first imaging protocol without the need for rest imaging and may allow for wider adoption of stress-first imaging protocols.