Image reconstruction and image quality evaluation for a dual source CT scanner

Abstract

The authors present and evaluate concepts for image reconstruction in dual source CT (DSCT). They describe both standard spiral (helical) DSCT image reconstruction and electrocardiogram (ECG)-synchronized image reconstruction. For a compact mechanical design of the DSCT, one detector (A) can cover the full scan field of view, while the other detector (B) has to be restricted to a smaller, central field of view. The authors develop an algorithm for scan data completion, extrapolating truncated data of detector (B) by using data of detector (A). They propose a unified framework for convolution and simultaneous 3D backprojection of both (A) and (B) data, with similar treatment of standard spiral, ECG-gated spiral, and sequential (axial) scan data. In ECG-synchronized image reconstruction, a flexible scan data range per measurement system can be used to trade off temporal resolution for reduced image noise. Both data extrapolation and image reconstruction are evaluated by means of computer simulated data of anthropomorphic phantoms, by phantom measurements and patient studies. The authors show that a consistent filter direction along the spiral tangent on both detectors is essential to reduce cone-beam artifacts, requiring truncation of the extrapolated (B) data after convolution in standard spiral scans. Reconstructions of an anthropomorphic thorax phantom demonstrate good image quality and dose accumulation as theoretically expected for simultaneous 3D backprojection of the filtered (A) data and the truncated filtered (B) data into the same 3D image volume. In ECG-gated spiral modes, spiral slice sensitivity profiles (SSPs) show only minor dependence on the patient's heart rate if the spiral pitch is properly adapted. Measurements with a thin gold plate phantom result in effective slice widths (full width at half maximum of the SSP) of 0.63-0.69 mm for the nominal 0.6 mm slice and 0.82-0.87 mm for the nominal 0.75 mm slice. The visually determined through-plane (z axis) spatial resolution in a bar pattern phantom is 0.33-0.36 mm for the nominal 0.6 mm slice and 0.45 mm for the nominal 0.75 mm slice, again almost independent of the patient's heart rate. The authors verify the theoretically expected temporal resolution of 83 ms at 330 ms gantry rotation time by blur free images of a moving coronary artery phantom with 90 ms rest phase and demonstrate image noise reduction as predicted for increased reconstruction data ranges per measurement system. Finally, they show that the smoothness of the transition between image stacks acquired in different cardiac cycles can be efficiently controlled with the proposed approach for ECG-synchronized image reconstruction.

FIG. 1.

Technical realization of a DSCT system (SOMATOM Definition, Siemens Healthcare, Forchheim, Germany). One detector (A) covers the entire scan field of view with a diameter of $50\mathrm{cm}$, while the other detector (B) is restricted to a smaller, central field of view.

FIG. 2.

System geometry of a DSCT system. The $z$ axis points into the paper plane and from the patient table into the gantry.

FIG. 3.

Data completion of truncated (B) data in parallel geometry. The $z$-axis corresponds to the patient axis. A slice $q$ on detector (B) is indicated. (A) data measured at the same view angle are used to extrapolate the (B) projections in the $b$ direction. If no (A) data from the current half turn of the spiral $(\Lambda =0)$ are available, as in this case, (A) data from the adjacent half turn $\Lambda =1$ are used.

FIG. 4.

Schematic illustration of data segments in parallel geometry used for ECG-synchronized DSCT image reconstruction. Due to the mechanical assembly, the minimum data interval per measurement system is ${\theta }_{\mathrm{rec}}=\pi ∕2$ in parallel geometry (indicated by dashed lines). The data interval for each measurement system can be increased (indicated by solid lines) to trade-off temporal resolution for dose accumulation in order to reduce the image noise for obese patients.

FIG. 5.

Angular weighting functions ${\tilde{w}}^{A∕B}\left(\theta \right)$ for both measurement systems (A) and (B) to ensure correct normalization and smooth data transition for ECG-synchronized DSCT image reconstruction. Left: Minimum data interval ${\theta }_{\mathrm{rec}}+{\theta }_{\mathrm{trans}}=\pi ∕2+\pi ∕6$ per measurement system to optimize temporal resolution. Right: Larger data interval ${\theta }_{\mathrm{rec}}+{\theta }_{\mathrm{trans}}=3\pi ∕4+\pi ∕6$ per measurement system to accumulate dose and trade-off temporal resolution for reduced image noise.

FIG. 6.

Computer-controlled robot arm moving a tube filled with contrast agent (“coronary artery”) in a water tank. The motion amplitudes and velocities of the robot arm can be adjusted to provide a realistic motion pattern of the tube.

FIG. 7.

Spiral reconstructions of the anthropomorphic thorax phantom at pitch $p=0.8$ (left) and $p=1.4$ (right), $\mathrm{FOV}=400\mathrm{mm}$. (a) Reconstruction using (A) data only. (b) Simultaneous 3D backprojection of (A) and (B) data without extrapolation of the truncated (B) data. Note the severe truncation artifacts at the boundary of the small SFOV. (c) Simultaneous 3D backprojection of (A) and (B) data with extrapolation of the truncated (B) data, but without truncation of the extrapolated (B) data after convolution. Cone-beam artifacts (arrows) are a result of the inconsistent filter direction of the (B) data. (d) Simultaneous 3D backprojection of (A) and (B) data with extrapolation of the truncated (B) data and truncation of the extrapolated (B) data after convolution. Cone-beam artifacts are significantly reduced. The ROIs 1, 2, and 3 were used to measure image noise.

FIG. 8.

Spiral reconstructions of the anthropomorphic thorax phantom at pitch $p=0.8$ (left) and $p=1.4$ (right), detail. For (a), (b), (c), and (d) see Fig. 7.

FIG. 9.

Relative image noise reduction in a $40\mathrm{cm}$ water phantom obtained by simultaneously backprojecting both the (A) data and the truncated (B) data. Ratio of the standard deviation of the image noise ${\sigma }_{A+B}\left(r\right)$ using (A) and (B) data with truncation of the extrapolated (B) data after convolution, and ${\sigma }_A\left(r\right)$ using (A) data only as a function of the distance $r$ from the isocenter. The solid line represents the theoretically expected value $1∕\sqrt{2}$ for $0<r⩽b_B^{\max }$.

FIG. 10.

ECG-gated spiral (helical) reconstructions of the stationary anthropomorphic thorax phantom at pitch $p=0.3$, assuming an artificial ECG at $70\mathrm{bpm}$, for ${\theta }_{\mathrm{rec}}=\pi ∕2$, $3\pi ∕4$, and $\pi$. Cone-beam artifacts decrease with increasing ${\theta }_{\mathrm{rec}}$, but temporal resolution is then compromised.

FIG. 11.

Measured SSPs (at the isocenter) of the nominal $0.6\mathrm{mm}$ slice as a function of the heart rate of an artificial ECG at 60, 70, 80, 90, and 100 bpm with the correspondingly adapted pitch values $p=0.27$, 0.32, 0.37, 0.43, and 0.46, respectively, using dual source acquisition and ECG-gated spiral (helical) image reconstruction. The indicated slice widths are the FWHMs of the SSPs.

FIG. 12.

Measured SSPs (at the isocenter) of the nominal $0.75\mathrm{mm}$ slice as a function of the heart rate of an artificial ECG at 60, 70, 80, 90, and $100\mathrm{bpm}$ with the correspondingly adapted pitch values $p=0.27$, 0.32, 0.37, 0.43, and 0.46, respectively, using dual source acquisition and ECG-gated spiral (helical) image reconstruction. The indicated slice widths are the FWHMs of the SSPs.

FIG. 13.

Fourier transforms of the measured SSPs of the nominal $0.6\mathrm{mm}$ slice (see Fig. 11) at various heart rates. The SSPs were obtained by using dual source acquisition and ECG-gated spiral (helical) image reconstruction. The Fourier transforms are the MTFs in the $z$ direction.

FIG. 14.

Fourier transforms of the measured SSPs of the nominal $0.75\mathrm{mm}$ slice (see Fig. 12) at various heart rates. The SSPs were obtained by using dual source acquisition and ECG-gated spiral (helical) image reconstruction. The Fourier transforms are the MTFs in the $z$ direction.

FIG. 15.

MPRs of the $z$-resolution phantom at $0.6\mathrm{mm}$ nominal reconstruction slice width, as a function of the heart rate of an artificial ECG at 60, 70, 80, 90, and $100\mathrm{bpm}$ with the correspondingly adapted pitch values $p=0.27$, 0.32, 0.37, 0.43, and 0.46, respectively. Independent of the heart rate, the bar patterns with $14–15\mathrm{lp}∕\mathrm{cm}$ are visible, which corresponds to $0.33–0.36\mathrm{mm}$ object size. This result is in good agreement with the evaluation of the $z$-MTFs, see Fig. 13.

FIG. 16.

MPRs of the $z$-resolution phantom at $0.75\mathrm{mm}$ nominal reconstruction slice width. Independent of the heart rate, the bar patterns with $13\mathrm{lp}∕\mathrm{cm}$ are visible, corresponding to about $11\mathrm{lp}∕\mathrm{cm}$ true resolution due to the 30° angle of the bar-patterns. Hence, objects of about $0.45\mathrm{mm}$ in size can be differentiated. This result is in good agreement with the evaluation of the $z$-MTFs, see Fig. 14.

FIG. 17.

Axial images and MPRs of the moving coronary artery phantom for various choices of the reconstruction data interval ${\theta }_{\mathrm{rec}}$ per measurement system. With increasing ${\theta }_{\mathrm{rec}}$, image noise is reduced, but at the expense of temporal resolution. ROI 1 was used for image noise measurements.

FIG. 18.

MPR of a DSCT coronary angiographic patient examination for various values of the smoothing parameter $Q$, which controls the smoothness of the transition between image stacks acquired in different cardiac cycles, see the arrows. As $Q$ approaches 0, the transition is more pronounced (image courtesy of Dr. J. Hausleiter, German Heart Center, Munich).