Dual energy window imaging for optimisation of P/V ratios in VP SPECT

Abstract

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/V ratio) of ≥ 3:1. This study investigated whether the ratio of counts simultaneously acquired in adjacent primary and Compton scatter energy windows (E_ratio) on V SPECT was predictive of final normalised perfusion count rate (PCR_norm) on P SPECT using [^99mTc]Tc-macroaggregated albumin (MAA), thus allowing for optimisation of P/V ratios.

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 custom Python and R scripts. 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 adjusted R² of 0.756 and MSE of 0.001089. A prediction tool designed for routine clinical use was developed for predicting final P/V ratio. 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 predicting P/V ratio.

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.

Keywords: Count rate ratio; Lung SPECT; Perfusion; Pulmonary embolism; Ventilation.

Fig. 1

Final linear regression of perfusion count rate normalised to 1 MBq of administered [^99mTc]Tc-MAA, and a camera-collimator sensitivity of 1 cps/MBq (PCR_norm) as a function of the dual energy window count ratio of the ventilation study (E_ratio). Regression line (blue solid line), 95% confidence band (dark grey), and 95% prediction bands (red dashed lines). Image generated in RStudio

Fig. 2

Final linear regression as shown in Fig. 1, with training dataset values in grey and superimposed validation dataset values in blue. Image generated in RStudio

Fig. 3

Scatter plot of P/V ratio values predicted with the Excel-based tool versus actual values (validation dataset). The straight line indicates points for which P/V ratio predicted = P/V ratio actual. Image generated in RStudio

Fig. 4

Results of applying the prediction tool to ventilation studies in the validation dataset using a dose-sparing strategy (targeting a [^99mTc]Tc-MAA dose of 120 MBq, and a P/V ratio of 3). In the stimulation, values predicted by the tool were compared to equivalent values calculated directly from actual perfusion data