Lung perfusion imaging in small animals using 4D micro-CT at heartbeat temporal resolution

Abstract

Purpose: Quantitative in vivo imaging of lung perfusion in rodents can provide critical information for preclinical studies. However, the combined challenges of high temporal and spatial resolution have made routine quantitative perfusion imaging difficult in small animals. The purpose of this work is to demonstrate 4D micro-CT for perfusion imaging in rodents at heartbeat temporal resolution and isotropic spatial resolution.

Methods: We have recently developed a dual tube/detector micro-CT scanner that is well suited to capture first pass kinetics of a bolus of contrast agent used to compute perfusion information. Our approach is based on the paradigm that similar time density curves can be reproduced in a number of consecutive, small volume injections of iodinated contrast agent at a series of different angles. This reproducibility is ensured by the high-level integration of the imaging components of our system with a microinjector, a mechanical ventilator, and monitoring applications. Sampling is controlled through a biological pulse sequence implemented in LABVIEW. Image reconstruction is based on a simultaneous algebraic reconstruction technique implemented on a graphic processor unit. The capabilities of 4D micro-CT imaging are demonstrated in studies on lung perfusion in rats.

Results: We report 4D micro-CT imaging in the rat lung with a heartbeat temporal resolution (approximately 150 ms) and isotropic 3D reconstruction with a voxel size of 88 microm based on sampling using 16 injections of 50 microL each. The total volume of contrast agent injected during the experiments (0.8 mL) was less than 10% of the total blood volume in a rat. This volume was not injected in a single bolus, but in multiple injections separated by at least 2 min interval to allow for clearance and adaptation. We assessed the reproducibility of the time density curves with multiple injections and found that these are very similar. The average time density curves for the first eight and last eight injections are slightly different, i.e., for the last eight injections, both the maximum of the average time density curves and its area under the curve are decreased by 3.8% and 7.2%, respectively, relative to the average time density curves based on the first eight injections. The radiation dose associated with our 4D micro-CT imaging is 0.16 Gy and is therefore in the range of a typical micro-CT dose.

Conclusions: 4D micro-CT-based perfusion imaging demonstrated here has immediate application in a wide range of preclinical studies such as tumor perfusion, angiogenesis, and renal function. Although our imaging system is in many ways unique, we believe that our approach based on the multiple injection paradigm can be used with the newly developed flat-panel slip-ring-based micro-CT to increase their temporal resolution in dynamic perfusion studies.

Figure 1

The sampling involves multiple injections, Inj1 to InjN, which create TDCs. Two orthogonal projection images represented here as two orthogonal lines in the Fourier space are acquired at each of the sampling time points tp₁ to tp_M and are synchronized with R peak of the ECG signal. Following each injection and sampling the first pass perfusion, the specimen is rotated by Δα. Each imaging chain acquires projection data for approximately 90°+fan angle and the two imaging chains collect together projections over 180°+fan angle for each time point. Note that the Fourier distribution of projections is not the same for each time point. A 3D reconstruction is performed for each time point by combining projection images from multiple injections. The temporal resolution is maintained to heartbeat.

Figure 2

A DSA sequence of projections for first 20 consecutive heartbeats following one injection of 75 μL Isovue 370 in a Ficher 344 rat. A ROI (arrow) was selected in the aorta. The TDCs for ROI in aorta corresponding to 16 consecutive injections are shown in (B). The values corresponding to the MTTs for each injection are shown in (C).

Figure 3

The SART reconstruction after 20 iterations using (A) 16, (B) 32, and (C) 64 projections. The equivalent FBP reconstruction is shown in (E)–(G), while the true phantom image is shown in (D). The line profiles show that the SART reconstruction recovered the lung enhancement values well, but was not able to recover the blood vessel. Overall the SART reconstruction with few projections is smoother than the equivalent FBP reconstruction via the Feldkamp algorithm.

Figure 4

(A) The RMSE computed for SART reconstructions with simulated noisy DSA projections for the Moby Phantom with a weighting factor of 1. Note that all SART reconstruction give a better RMSE than FBP (A). (B) The percentage error change in RMS is less than 3% (around ten iterations) and less than 1% (around 20 iterations).

Figure 5

The SART-based tomographic reconstruction at iteration 10 of a time point 9 (i.e., after the ninth heartbeat after the bolus injection), data reveal the 3D nature of the perfusion data. The 16 axial slices indicated on a maximum intensity projection image (A) are distanced by 1 mm and are displayed from bottom to top in (B).

Figure 6

(A) An example of 16 successive micro-CT perfusion images in an axial slice cutting through the lung at heartbeat temporal resolution (140 ms). The images were reconstructed at 88 μm voxel size. The SVD-based perfusion maps for PBF, PBV, and MTT are shown in (B). The units for MTT are in seconds, PBV is given in mL and PBF in mL/s.

Figure 7

A comparison between two reconstruction of the same slice with SART using (A) 32 and (B) 16 projections. (C) A plot of a line profile through the two images shows that although noisier, the SART reconstruction using 16 projections is very similar to SART with 16 projections. In (D), TDCs were plotted for mean values in ROIs placed in the lung parenchyma, and the left and right ventricles for reconstructions using SART with 32 and 16 projections. The two sets of curves almost coincide.