Key result
The ratio of simultaneously acquired counts in adjacent energy windows on ventilation SPECT linearly predicted the final perfusion count rate (adjusted R2 = 0.756, p < 0.0001), enabling a predictive tool with 91% accuracy.
Why the study?
Same-day VP SPECT for pulmonary embolism diagnosis requires careful attention to achieving an optimal P/V ratio of ≥ 3:1, and whether primary-to-Compton scatter energy window count ratios on V SPECT could predict perfusion count rates was unknown.
Does a predictive tool based on dual energy window imaging on V SPECT accurately predict the final P/V ratio in adult patients undergoing same-day VP SPECT?
Observational (n=540)
No
Does a predictive tool based on dual energy window imaging on V SPECT accurately predict the final P/V ratio in adult patients undergoing same-day VP SPECT?
A predictive tool based on dual energy window imaging on V SPECT accurately predicts the final P/V ratio, allowing for optimization of [99mTc]Tc-MAA dose and timing in same-day VP SPECT studies.
Answers are grounded in this paper and cite their sources.
May facilitate [99mTc]Tc-MAA dosing in same-day VP SPECT; leaves open prospective validation before practice change.
Purpose Ventilation–perfusion single-photon emission computed tomography (VP SPECT) plays an important role in pulmonary embolism diagnosis. Rapid results may be obtained using same-day ventilation followed by perfusion imaging, but generally requires careful attention to achieving an optimal count rate ratio (P/Vratio) of ≥ 3:1. This study investigated whether the ratio of counts simultaneously acquired in adjacent primary and Compton scatter energy windows (Eratio) on V SPECT was predictive of final normalised perfusion count rate (PCRnorm) on P SPECT using [99mTc]Tc-macroaggregated albumin (MAA), thus allowing for optimisation ofP/Vratios. Methods Same-day VP SPECT studies acquired using standard protocols in adult patients during a 2-year period (training dataset) were assessed. Studies were included provided they were acquired with correct imaging parameters, and injection site imaging and laboratory records were available for quality control and normalised count rate corrections. Extraction of DICOM information, and linear regression were performed using customPythonandRscripts. A predictive tool was developed in Microsoft Excel. This tool was then validated using a second (validation) dataset of same-day studies acquired over a subsequent 7-month period. Accuracy of the prediction tool was assessed by calculating the mean absolute percentage error (MAPE). Results Of 643 studies performed, the scans of 342 participants (median age 30.4 years, 318 female) were included in the training dataset, the analysis of which yielded a significant regression equation (F(1,340) = 1057.3,p < 0.0001), with an adjustedR2of 0.756 and MSE of 0.001089. A prediction tool designed for routine clinical use was developed for predicting finalP/Vratio. Of an additional 285 studies, 198 were included in the second (validation) dataset (median age 29.7 years, 188 female). The Excel-based tool was shown to be 91% accurate (MAPE: 9%) in predictingP/Vratio. Conclusion The relationship between the ratio of simultaneously acquired counts in adjacent energy windows on V SPECT and perfusion count rate after administration of a known activity of [99mTc]Tc-MAA can be linearly approximated. A predictive tool based on this work may assist in optimising the dose and timing of [99mTc]Tc-MAA administration in same-day studies to the benefit of patients and workflows.
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Doruyter et al. (2021) conducted an observational in Suspected pulmonary embolism (n=540). Ratio of counts in adjacent energy windows on V SPECT (Eratio) was evaluated on Prediction of final normalised perfusion count rate (PCRnorm) using Eratio (Adjusted R2 0.756, p=<0.0001). The ratio of simultaneously acquired counts in adjacent energy windows on ventilation SPECT linearly predicted the final perfusion count rate (adjusted R2 = 0.756, p < 0.0001), enabling a predictive tool with 91% accuracy.
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