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Evaluation of Coronary Artery Image Quality with Knowledge-based Iterative Model Reconstruction

Rationale and Objectives

To evaluate knowledge-based iterative model reconstruction (IMR) to improve image quality and reduce radiation dose in coronary computed tomography angiography (cCTA).

Materials and Methods

We evaluated 45 consecutive cCTA studies, including 25 studies performed with an 80% systolic dose reduction using tube current modulation (TCM). Each study was reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (iDose 4 ), and IMR in a diastolic phase. Additional systolic phase reconstructions were obtained for TCM studies. Mean pixel attenuation value and standard deviation (SD) were measured in the left ventricle and left main coronary artery. Subjective scores were obtained by two independent reviewers on a 5-point scale for definitions of contours of small coronary arteries (<3 mm), coronary calcifications, noncalcified plaque, and overall diagnostic confidence for the presence/absence of stenosis.

Results

There was no significant difference in pixel intensity among FBP, iDose 4 , and IMR ( P > .8). For diastolic phase images, noise amplitude in the left main coronary artery was reduced by a factor of 1.3 from FBP to iDose 4 (SD = 99 vs. 74; P = .005) and by a factor of 2.6 from iDose 4 to IMR (SD = 74 vs. 28; P < .001). For systolic phase TCM images, noise amplitude in the left main coronary artery was reduced by a factor of 2.3 from FBP to iDose 4 (SD = 322 vs. 142; P < .001) and by a factor of 3.0 from iDose 4 to IMR (SD = 142 vs. 48; P < .001). All four subjective image quality scores were significantly better with IMR compared to iDose 4 and FBP ( P < .001). The reduction in image noise amplitude and improvement in image quality scores were greatest among obese patients.

Conclusions

IMR reduces intravascular noise on cCTA by 86%–88% compared to FBP, and improves image quality at radiation exposure levels 80% below our standard technique.

Since the introduction of the EMI computed tomography (CT) scanner in 1971, clinical CT image reconstruction has been based on filtered back projection (FBP) to reconstruct two-dimensional images from x-ray attenuation measurements in multiple one-dimensional planes. The original EMI scanner did provide an option for iterative reconstruction, but iterative reconstruction was not applied to clinical CT until recently because of computational requirements. Increased computational power now allows the application of iterative reconstruction techniques that were developed for lower resolution nuclear medicine images to high resolution CT. A history of CT reconstruction along with a synopsis of newer iterative reconstruction techniques are summarized in a recent review .

The first commercially available iterative reconstruction systems for CT used hybrid methods that combined FBP with iterative reconstruction to provide noise reduction. This noise reduction can be leveraged to improve image quality or to compensate for high noise with lower tube current acquisitions. Adaptive statistical iterative reconstruction (GE Healthcare, Waukesha, WI) and iDose 4 (Philips Healthcare, Cleveland, OH) are examples of this approach. These techniques decrease the noise in reconstructed images compared to FBP. Model-based iterative reconstruction by GE Healthcare and iterative model reconstruction (IMR) by Philips are the latest generation of commercially available iterative techniques that rely on statistical and system models and approach reconstruction as an optimization process. These newer techniques may simultaneously provide further reduction in image noise, potential dose savings, and improved image quality.

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Methods

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Statistical Analysis

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Results

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Figure 1, A 51-year-old male (weight, 125 kg; body mass index, 40.7) with two stents in the left anterior descending artery (LAD) presented with new chest pain. Diastolic phase imaging of the left anterior descending artery reconstructed with (a) FBP, (b) iDose 4 , and (c) IMR. Stents ( white arrows ), calcified plaque ( black arrow ), and noncalcified plaque ( white arrowheads ) are better defined on the IMR reconstruction. FBP, filtered back projection; IMR, iterative model reconstruction.

Figure 2, A 90-year-old female (weight, 79 kg; body mass index, 33) presented to the emergency room with chest pain. Systolic phase imaging of the left anterior descending artery reconstructed with (a) FBP, (b) iDose 4 , and (c) IMR. Calcified plaque ( black arrow ) and noncalcified plaque ( white arrowhead ) are better defined on the IMR reconstruction. FBP, filtered back projection; IMR, iterative model reconstruction.

Figure 3, A 35-year-old female (weight, 80 kg; body mass index, 35) with chest pain and abnormal stress test. Systolic phase imaging of the right coronary artery reconstructed with (a) FBP, (b) iDose 4 , and (c) IMR. Image quality is photon limited by the combination of a high body mass index and TCM. The right coronary artery ( white arrow ) and mild noncalcified plaque ( white arrowhead ) are better defined on the IMR reconstruction. FBP, filtered back projection; IMR, iterative model reconstruction; TCM, tube current modulation.

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Diastolic Phase Imaging

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Table 1

Image Noise within the Left Ventricle and Left Main Coronary Artery, Expressed as Standard Deviation within a Region of Interest for Diastolic Phase Reconstructions

FBP iDose 4 IMR Left ventricular noise1238217 Normal weight subgroup 96 71 14 Overweight subgroup 121 87 19 Obese subgroup 141 81 16 Left main coronary noise997428 Normal weight subgroup 86 66 36 Overweight subgroup 109 81 23 Obese subgroup 95 69 23

Numbers provided in bold font represent overall values for each group. Numbers in non-bold font are values for the individual subgroups.

Table 2

Subjective Image Quality Scores for Diastolic Phase Reconstructions on a 1–5 Scale Described in the Methods Section

FBP iDose 4 IMR Arterial contour2.13.24.8 Normal weight subgroup 2.8 3.8 5.0 Overweight subgroup 2.2 3.2 5.0 Obese subgroup 1.5 2.9 4.6 Coronary calcifications2.23.34.9 Normal weight subgroup 2.8 3.8 5.0 Overweight subgroup 2.2 3.4 5.0 Obese subgroup 1.5 2.6 4.6 Noncalcified plaque contour1.72.84.4 Normal weight subgroup 2.0 3.0 4.5 Overweight subgroup 2.2 3.2 4.6 Obese subgroup 1.1 2.4 4.3 Overall diagnostic confidence2.63.84.9 Normal weight subgroup 3.0 4.0 5.0 Overweight subgroup 2.6 3.8 5.0 Obese subgroup 2.0 3.6 4.8

Numbers provided in bold font represent overall values for each group. Numbers in non-bold font are values for the individual subgroups.

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Systolic Phase Imaging with TCM

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Table 3

Subjective Image Quality Scores for Systolic Phase Reconstructions on a 1–5 Scale Described in the Methods Section

FBP iDose 4 IMR Arterial contour 1.6 2.7 4.5 Coronary calcifications 1.6 2.8 4.6 Noncalcified plaque contour 1.6 2.6 4.0 Overall diagnostic confidence 1.7 3.0 4.5

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Inter-rater Agreement

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Discussion

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Conclusions

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