Model-based Iterative Reconstruction Compared to Adaptive Statistical Iterative Reconstruction and Filtered Back-projection in CT of the Kidneys and the Adjacent Retroperitoneum

Rationale and Objectives

To prospectively evaluate the perceived image quality of model-based iterative reconstruction (MBIR) compared to adaptive statistical iterative reconstruction (ASIR) and filtered back-projection (FBP) in computed tomography (CT) of the kidneys and retroperitoneum.

Materials and Methods

With investigational review board and Health Insurance Portability and Accountability Act compliance, 17 adults underwent 31 contrast-enhanced CT acquisitions at constant tube potential and current (range 30–300 mA). Each was reconstructed with MBIR, ASIR (50%), and FBP. Four reviewers scored each reconstruction’s perceived image quality overall and the perceived image quality of seven imaging features that were selected by the authors as being relevant to imaging in the region and pertinent to the evaluation of high-quality diagnostic CT.

Results

MBIR perceived image quality scored superior to ASIR and FBP both overall ( P < .001) and for observations of the retroperitoneal fascia (99.2%), corticomedullary differentiation (94.4%), renal hilar structures (96.8%), focal renal lesions (92.5%), and mitigation of streak artifact (100.0%; all, P < .001). MBIR achieved diagnostic overall perceived image quality with approximately half the radiation dose required by ASIR and FBP. The noise curve of MBIR was significantly lower and flatter ( P < .001).

Conclusions

Compared to ASIR and FBP, MBIR provides superior perceived image quality, both overall and for several specific imaging features, across a broad range of tube current levels, and requires approximately half the radiation dose to achieve diagnostic overall perceived image quality. Accordingly, MBIR should enable CT scanning with improved perceived image quality and/or reduced radiation exposure.

Iterative image reconstruction algorithms, such as the original algebraic reconstruction technique, (ART) were used in the early days of transmission computed tomography (CT) but were quickly superseded by much faster analytical methods such as filtered back-projection (FBP) . Significant disadvantages exist with FBP, however, including its assumption that data are exact when in reality they are not, and the operation of the FBP filter which typically amplifies noise in the projection data. Iterative techniques, in contrast, can include models of features such as noise that improve the image during each iteration. This produces much better image quality than FBP does, when the signal-to-noise ratio is low, although this occurs at the expense of substantially increased computation time .

Owing to substantial increases in computational power, iterative image reconstruction algorithms have recently re-emerged and are now available on commercial CT scanners manufactured by all major vendors . The recent literature appears to confirm the expected dose saving potential of modern implementations of iterative reconstruction algorithms ; however, the relationship between radiation dose, noise, and image quality over a broad dose range, rather than at just a pair of dose levels, is not well established.

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Materials and methods

Study Population

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Scanning Technique and Image Reconstruction

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Table 1

Scanning Parameters and Relative Doses in 17 Patients

Number of Patients Total Scans First CT Acquisition Second CT Acquisition Tube Current (mA) Individual CTDI vol (mGy) Fraction of Total CTDI vol (%) Tube Current (mA) Individual CTDI vol (mGy) Fraction of Total CTDI vol (%) 3 3 300 14 100 — — — 3 6 270 12.6 90 30 1.4 10 3 6 255 11.9 85 45 2.1 15 2 ∗ 4 ∗ 225 10.5 75 75 3.5 25 3 6 195 9.1 65 105 4.9 35 3 6 165 7.7 55 135 6.3 45

ASIR, adaptive statistical iterative reconstruction; CT, computed tomography; FBP, filtered back-projection; MBIR, model-based iterative reconstruction; CTDI vol , volume computed tomography dose index.

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Image Review

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Individual imaging features

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Overall perceived image quality

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Image noise

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Statistical Analysis

Individual imaging features

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Overall perceived image quality

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Image noise

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Investigational Approval

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Results

Individual Imaging Features

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Table 2

Observations of Individual Imaging Features in Which MBIR was Rated Superior to Both ASIR and FBP

Imaging Feature Percentage of Observations in Which MBIR was Rated Superior Percentage of Observations in Which MBIR was Rated Superior, Stratified by Tube Current (mA) and CTDI vol (mGy) Very Low Dose

30–105 mA

1.4–4.9 mGy Low Dose

135–225 mA

6.3–10.5 mGy Standard Dose 255–300 mA 11.9–14.0 mGy Retroperitoneal fascia 99.2% (123/124) 100.0% (44/44) 97.7% (43/44) 100.0% (36/36) Corticomedullary differentiation 94.4% (117/124) 97.7% (43/44) 93.2% (41/44) 91.7% (33/36) Hilar structures 96.8% (120/124) 100.0% (44/44) 95.5% (42/44) 94.4% (34/36) Lesions 92.5% (74/80) 100.0% (32/32) 91.7% (22/24) 83.3% (20/24)

P = .002 Mitigation of streak artifact 100.0% (124/124) 100.0% (44/44) 100.0% (44/44) 100.0% (36/36) Intrarenal collecting system 23.4% (29/124) 56.8% (25/44)

P = .451 6.8% (3/44) 2.8% (1/36) Calculi 6.3% (5/8)

P = .727 100.0% (4/4)

P = .125 25.0% (1/4)

P = .625 —

ASIR, adaptive statistical iterative reconstruction; FBP, filtered back-projection; MBIR, model-based iterative reconstruction; CTDI vol , volume computed tomography dose index.

Numerators indicate observations in which MBIR was rated superior to both ASIR and FBP; denominators indicate the total number of observations. Significance is assessed with the exact binomial test.

All P values <.001 unless otherwise indicated.

Table 3

Demographics in 17 Patients Stratified by Tube Current and CTDI vol

Stratification by Tube Current (mA) and CTDI vol (mGy) Very Low Dose

30–105 mA

1.4–4.9 mGy Low Dose

135–225 mA

6.3–10.5 mGy Standard Dose

255–300 mA

11.9–14.0 mGy Acquisitions 11 11 9 Male/female 6/5 7/4 5/4 Mean age (year) 47.7 48.6 45.8 Mean abdominal diameter (cm) ∗ 28.8 27.3 28.7

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Overall Perceived Image Quality

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Imagequality=b1×exp(−exp[−b2×{mA−b3}]) Image

quality

=

b

1

×

exp

(

−

exp

[

−

b

2

×

{

mA

−

b

3

}

]

)

where b1, b2, and b3 are parameters with estimated values and 95% CIs as displayed in Table 4 . Parameters b1 and b3 were significantly different for MBIR compared to those for ASIR and FBP (both with P < .001), whereas parameter b2 did not differ significantly ( P = .132 and .650, respectively).

Table 4

Mean Overall Image Quality Score for the Kidneys and Retroperitoneum as a Function of Tube Current (mA) in Nonlinear Least-squares Regression on the Form “Image quality = b1 × exp (−exp [−b2 × {dose − b3}])”

Algorithm b1 b2 b3 RMSE Value (95% CI) Value (95% CI) Value (95% CI) MBIR 3.18 (2.93–3.43) 0.012 (0.007–0.016) 37.82 (28.97–46.67) 0.53 ASIR 2.22 (1.93–2.52) 0.015 (0.008–0.021) 84.47 (84.47–106.48) 0.46 FBP 2.23 (1.87–2.60) 0.013 (0.007–0.018) 102.08 (71.70–132.46) 0.58 MBIR versus ASIR_P_ < .001P = .132P < .001 MBIR versus FBP_P_ < .001P = .650P < .001

ASIR, adaptive statistical iterative reconstruction; CI, confidence interval; FBP, filtered back-projection; MBIR, model-based iterative reconstruction; RMSE, root-mean-square error.

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Table 5

Pairwise Reader Agreement (Linearly Weighted Kappa and 95% CI) for Overall Image Quality Scores of the Kidneys and Adjacent Retroperitoneum ( N = 93)

Reader Reader 1 Reader 2 Reader 3 Reader 4 Reader 1 — Reader 2 0.78 (0.69–0.86) — Reader 3 0.38 (0.28–0.48) 0.37 (0.27–0.46) — Reader 4 0.65 (0.53–0.76) 0.57 (0.44–0.69) 0.63 (0.52–0.72) —

Confidence intervals (CIs) based on 1000 bootstrap replications.

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Table 6

Minimum Tube Current and CTDI vol Levels at Which all Readers Returned Specified Overall Image Quality Scores

Algorithm Overall Image Quality Score 1 = Minimally Diagnostic

Tube Current (CTDI vol ) 2 = Diagnostic

Tube Current (CTDI vol ) 3 = Superior

Tube Current (CTDI vol ) ASIR 135 mA (6.3 mGy) 270 mA (12.6 mGy) Not achieved FBP 135 mA (6.3 mGy) 270 mA (12.6 mGy) Not achieved MBIR 75 mA (3.5 mGy) 135 mA (6.3 mGy) 270 mA (112.6 mGy)

ASIR, adaptive statistical iterative reconstruction; FBP, filtered back-projection; MBIR, model-based iterative reconstruction; CTDI vol , volume computed tomography dose index.

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Image Noise

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Noise=b0×(mA)ˆb1 Noise

=

b

0

×

(

mA

)

ˆ

b

1

where b0 and b1 are parameters whose estimated values and 95% CIs are shown in Table 7 . Both parameters b0 and b1 differed significantly between MBIR and ASIR and between MBIR and FBP (b0: P = .011 and .006, respectively; b1: P < .001 in both cases). Image noise for ASIR and FBP rose with decreasing milliamperes at a rate proportional to nearly the traditionally expected rate of (mA) −0.5 as evidenced by their b1 values of −0.53 and −0.51, respectively. In contrast, noise for MBIR rose with decreasing milliamperes at a much slower rate, with b1 = −0.22.

Table 7

Noise as a Function of Tube Current (mA) in Nonlinear Least-squares Regression on the Form “Noise = b0 x (mA)bˆ1”

Algorithm b0 b1 RMSE Value (95% CI) Value (95% CI) MBIR 36.69 (12.96–60.43) −0.22 (−0.34 to −0.10) 3.05 ASIR 529.31 (127.56–931.27) −0.53 (−0.69 to −0.38) 10.98 FBP 609.30 (229.33–989.26) −0.51 (−0.65 to −0.38) 12.20 MBIR versus ASIR_P_ = .011P < .001 MBIR versus FBP_P_ = .002P < .001

ASIR, adaptive statistical iterative reconstruction; CI, confidence interval; FBP, filtered back-projection; MBIR, model-based iterative reconstruction; RMSE, root-mean-square error.

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Discussion

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Acknowledgments

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