Improved quantitation and reproducibility in multi-PET/CT lung studies by combining CT information

Abstract

Background: Matched attenuation maps are vital for obtaining accurate and reproducible kinetic and static parameter estimates from PET data. With increased interest in PET/CT imaging of diffuse lung diseases for assessing disease progression and treatment effectiveness, understanding the extent of the effect of respiratory motion and establishing methods for correction are becoming more important. In a previous study, we have shown that using the wrong attenuation map leads to large errors due to density mismatches in the lung, especially in dynamic PET scans. Here, we extend this work to the case where the study is sub-divided into several scans, e.g. for patient comfort, each with its own CT (cine-CT and 'snap shot' CT). A method to combine multi-CT information into a combined-CT has then been developed, which averages the CT information from each study section to produce composite CT images with the lung density more representative of that in the PET data. This combined-CT was applied to nine patients with idiopathic pulmonary fibrosis, imaged with dynamic ¹⁸F-FDG PET/CT to determine the improvement in the precision of the parameter estimates.

Results: Using XCAT simulations, errors in the influx rate constant were found to be as high as 60% in multi-PET/CT studies. Analysis of patient data identified displacements between study sections in the time activity curves, which led to an average standard error in the estimates of the influx rate constant of 53% with conventional methods. This reduced to within 5% after use of combined-CTs for attenuation correction of the study sections.

Conclusions: Use of combined-CTs to reconstruct the sections of a multi-PET/CT study, as opposed to using the individually acquired CTs at each study stage, produces more precise parameter estimates and may improve discrimination between diseased and normal lung.

Keywords: Attenuation correction; Density; Dynamic PET; Lung; PET/CT; Quantitation; Respiration.

Fig. 1

Schematic of the method to combine the CT data. 1, 2 and 3 represent the CT images from the early, mid and late study sections; C is the resulting combined-CT image; and V is the concentration in the voxel of interest. The white boxes represent specific voxels that are filled in either one, two or all of the CT images after registration. The grey areas at the edges of CT 2 and 3 are the result of registration

Fig. 2

Variation in K _i due to respiration. The percentage difference between the true and measured K _i2 (dark grey bars) and K _iP (light grey bars) in each of the different TTAC configurations where I, E and M represent ungated PET data reconstructed with an end inspiration, an end expiration and a mid-breathing cycle ‘snap shot’ CT for AC respectively (i.e. IEM = the early study section PET data were reconstructed with an end inspiration CT for AC, the mid section with an end expiration CT for AC and the late section with a mid-breathing cycle CT for AC)

Fig. 3

Example patient TTAC and fits with conventional analysis measured patient TTAC (stars) and the associated compartment model and Patlak-Rutland (inset to column 2) fits (filled line). Both columns show the same data. However, the left column has the x-axis in log(time) to allow better visualisation of the peak, while in the second column, the x-axis is linear in time

Fig. 4

Regional variation in the K _i measurements with conventional analysis comparison of the fibrotic and normal appearing tissue influx rate constants using compartmental modelling (K_i2) and Patlak-Rutland analysis (K_iP) for all patients. Error bars represent standard errors

Fig. 5

Example patient original and combined-CT images. The registered original CT images from the early (top left), mid (top middle) and late (top right) study sections and the resulting combined-CT for the late section (bottom middle) for an example patient. Grey scale − 1350 < HU < 150

Fig. 6

Example patient TTAC and fits with using combined-CT reconstructions for analysis. An FDG example TTAC with associated compartment model and Patlak-Rutland (inset) fits. This is the same FDG patient as shown in Fig. 3 for comparison. Both columns show the same data using different time axes as before (Fig. 3)

Fig. 7

Regional variation in the K _i measurements using combined-CT reconstructions for analysis. Comparison of the fibrotic and normal appearing tissue influx rate constants determined after the PET data were reconstructed with the combined-CT, using compartmental modelling (K_i2) and Patlak-Rutland analysis (K_iP) for all patients. Error bars represent standard errors