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Ultra-low-dose CT of the Lung

Posted May 31, 2014 Updated Apr 10, 2023
By Masahiro Yanagawa MD PhD , Tomoko Gyobu MD , Ann N. Leung MD , Misa Kawai MD , Yutaka Kawata MD , Hiromitsu Sumikawa MD PhD , Osamu Honda MD PhD , Noriyuki Tomiyama MD PhD
12 min read

Rationale and Objectives

To compare quality of ultra-low-dose thin-section computed tomography (CT) images of the lung reconstructed using model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASIR) to filtered back projection (FBP) and to determine the minimum tube current–time product on MBIR images by comparing to standard-dose FBP images.

Materials and Methods

Ten cadaveric lungs were scanned using 120 kVp and four different tube current–time products (8, 16, 32, and 80 mAs). Thin-section images were reconstructed using MBIR, three ASIR blends (30%, 60%, and 90%), and FBP. Using the 8-mAs data, side-to-side comparison of the four iterative reconstruction image sets to FBP was performed by two independent observers who evaluated normal and abnormal findings, subjective image noise, streak artifact, and overall image quality. Image noise was also measured quantitatively. Subsequently, 8-, 16-, and 32-mAs MBIR images were compared to standard-dose FBP images. Comparisons of image sets were analyzed using the Wilcoxon signed rank test with Bonferroni correction.

Results

At 8 mAs, MBIR images were significantly better ( P < .005) than other reconstruction techniques except in evaluation of interlobular septal thickening. Each set of low-dose MBIR images had significantly lower ( P < .001) subjective and objective noise and streak artifacts than standard-dose FBP images. Conspicuity and visibility of normal and abnormal findings were not significantly different between 16-mAs MBIR and 80-mAs FBP images except in identification of intralobular reticular opacities.

Conclusions

MBIR imaging shows higher overall quality with lower noise and streak artifacts than ASIR or FBP imaging, resulting in nearly 80% dose reduction without any degradations of overall image quality.

The increase of the radiation dose delivered in computed tomography (CT) has recently been a problem. Because there is a trade-off between image quality and radiation dose on CT, however, it is not always appropriate to decrease radiation dose on CT. Iterative reconstruction algorithms for CT have been developed by multiple equipment manufacturers to reduce image noise associated with radiation dose reduction . Adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) are types of iterative reconstruction algorithms available on clinical settings. The ASIR technique models photon and electronic noise statistics; by partially correcting for fluctuations in projection measurements due to limited photon statistics, ASIR enables a time-efficient reduction in pixel variance that is statistically unlikely to be representative of anatomic features resulting in a reduction of image noise with no decrement in spatial resolution . In clinical practice, ASIR is typically used in combination with the standard filtered back projection (FBP) reconstruction to create blended images. As compared to ASIR, MBIR is a more mathematically complex and time-consuming technique as it models not only system statistics but also system optics . Phantom experiments show that MBIR has potential to improve spatial resolution and allow further reductions in image noise . To date, few studies have evaluated CT image quality of the lung using MBIR . Thus, unlike FBP and ASIR, MBIR technique might have the potential not to degrade image quality even under the extreme dose reduction. McCollough et al. reported that the advances in data acquisition, image reconstruction, and optimization processes that were identified by consensus as being necessary to achieve submillisievert-dose CT examinations. It is expected that MBIR might be one of techniques to enable a submillisievert-dose CT. The present study was performed using cadaveric lung models that can provide multiple acquisitions to determine the minimum tube current–time product at which image quality of a low-dose MBIR study is comparable to that of a standard-dose FBP study. The aim of this present study was two-fold: to compare quality of ultra-low-dose thin-section CT images of the lung reconstructed using MBIR and ASIR to FBP and to determine the minimum tube current–time product at which image quality of an MBIR study is comparable to that of a standard-dose FBP.

Materials and methods

Cadaveric Lungs and Imaging

We obtained approval from our internal Ethics Review Board. Informed consent was obtained for the use of patient biomaterial and for retrospective review of patient records and images. Ten cadaveric lungs were inflated and fixed by the method of Heitzman . These lungs were distended through the main bronchus with fixative fluid that contained polyethylene glycol 400, 95% ethyl alcohol, 40% formalin, and water in the proportions of 10:5:2:3. The specimens were immersed in fixative for 2 days and the lungs were then air dried. The pathologic diagnoses of these 10 lungs were usual interstitial pneumonia ( n = 1), diffuse alveolar damage ( n = 1), diffuse panbronchiolitis ( n = 1), pneumonia ( n = 2), emphysema ( n = 1), diffuse alveolar hemorrhage ( n = 1), metastatic disease ( n = 2), and lymphangitic carcinomatosis ( n = 1).

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Subjective Image Analysis

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Objective Image Analysis

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Statistical Analysis

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Results

Radiation Doses

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Table 1

Radiation Dose Descriptions

Low Dose Standard Dose 8 mAs 16 mAs 32 mAs 80 mAs CTDIvol (mGy) 0.65 1.30 2.59 6.49 DLP (mGy-cm) 22.15 44.30 88.60 221.50 ED (mSv) 0.31 0.62 1.24 3.10

CTDIvol, computed tomography dose index volume; DLP, dose–length product; ED, effective dose.

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Subjective Evaluation of CT Findings

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Table 2

Comparison among FBP, ASIR, and MBIR on Ultra-low-dose (8 mAs) CT

Normal Findings Abnormal Findings Other Findings Overall Image Quality Central Vessels and Airways Peripheral Vessels and Airways Interlobar Fissures Nodules GGO ISP Image Noise Streak Artifact Reconstruction technique MBIR 4.83 ± 0.07 4.68 ± 0.09 4.75 ± 0.11 4.96 ± 0.04 4.84 ± 0.07 4.19 ± 0.16 5.00 ± 0.00 5.00 ± 0.00 4.97 ± 0.03 ASIR 90 4.06 ± 0.11 4.04 ± 0.07 4.00 ± 0.13 4.00 ± 0.05 4.16 ± 0.07 3.88 ± 0.09 4.21 ± 0.07 4.03 ± 0.12 4.55 ± 0.09 ASIR 60 3.52 ± 0.09 3.32 ± 0.09 3.19 ± 0.10 3.39 ± 0.09 3.84 ± 0.07 3.31 ± 0.12 3.73 ± 0.08 3.45 ± 0.09 3.55 ± 0.09 ASIR 30 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.04 ± 0.04 3.04 ± 0.04 3.00 ± 0.00 3.03 ± 0.03 3.00 ± 0.00 3.00 ± 0.00 FBP 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 Pairwise comparison ( P *) MBIR versus ASIR 90 <.001 <.001 .005 <.001 <.001 .962 <.001 <.001 <.001 ASIR 60 <.001 <.001 <.001 <.001 <.001 .002 <.001 <.001 <.001 ASIR 30 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 FBP <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 ASIR 90 versus ASIR 60 <.001 <.001 <.001 <.001 .084 .005 <.001 <.001 <.001 ASIR 30 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 FBP <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 ASIR 60 versus ASIR 30 <.001 .026 .825 .006 <.001 .197 <.001 <.001 <.001 FBP <.001 .026 .825 .003 <.001 .197 <.001 <.001 <.001 ASIR 30 versus FBP 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

ASIR, adaptive statistical iterative reconstruction; GGO, ground-glass opacity; ISP, interlobular septal thickening; FBP, filtered back projection; MBIR, model-based iterative reconstruction.

Data are presented as mean ± standard deviation. Data of the subjective image analysis were statistically analyzed using the Wilcoxon signed rank tests with a Bonferroni correction applied for multiple comparisons. P \* is a Bonferroni-corrected P value. P \* value <.05 was considered to be significant.

Figure 1, Ultra-low-dose (8 mAs) thin-section computed tomographic images of a cadaveric lung with diffuse panbronchiolitis show serial improvement in image noise and streak artifacts in following ascending order: FBP (a) , ASIR 30 (b) , ASIR 90 (c) , and MBIR (d) . With almost no perceptible noise or streak artifact on MBIR image, conspicuity and visibility of the fissure ( long arrow ), small nodules ( short arrows ), and bronchial walls ( arrowheads ) are improved as compared to FBP or ASIR blends. Note the blotchy pixilated appearance of the MBIR images. ASIR, adaptive statistical iterative reconstruction; FBP, filtered back projection; MBIR, model-based iterative reconstruction.

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Table 3

Comparison between 8-mAs, 16-mAs, and 32-mAs MBIR Versus 80-mAs FBP

Normal Findings Abnormal Findings Other Findings Overall Image Quality Central Vessels and Airways Peripheral Vessels and Airways Interlobar Fissures Nodules GGO ISP Image Noise Streak Artifact Reconstruction technique 32-mAs MBIR 3.33 ± 0.09 3.50 ± 0.11 3.53 ± 0.17 3.46 ± 0.09 3.77 ± 0.11 3.44 ± 0.13 4.97 ± 0.03 4.97 ± 0.03 3.67 ± 0.12 16-mAs-MBIR 3.07 ± 0.07 3.14 ± 0.14 3.27 ± 0.12 3.18 ± 0.10 3.27 ± 0.13 2.75 ± 0.17 4.93 ± 0.05 4.93 ± 0.05 2.93 ± 0.08 8-mAs MBIR 3.07 ± 0.07 2.73 ± 0.18 2.93 ± 0.07 2.82 ± 0.12 2.86 ± 0.12 2.19 ± 0.10 4.87 ± 0.06 4.93 ± 0.05 2.63 ± 0.10 80-mAs FBP 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 3.00 ± 0.00 Pairwise comparison ( P *) 32-mAs MBIR versus 16-mAs MBIR .179 .047 .243 .108 .005 .002 1.000 1.000 <.001 8-mAs MBIR .179 <.001 .015 .001 <.001 <.001 1.000 1.000 <.001 80-mAs FBP .004 .001 .037 <.001 <.001 .023 <.001 <.001 <.001 16-mAs MBIR versus 8-mAs MBIR 1.000 .023 .115 .013 .023 .017 .965 1.000 .028 80-mAs FBP 1.000 1.000 .243 .576 .333 .983 <.001 <.001 1.000 8-mAs MBIR versus 80-mAs FBP 1.000 .821 1.000 .805 1.000 <.001 <.001 <.001 .007

ASIR, adaptive statistical iterative reconstruction; GGO, ground-glass opacity; ISP, interlobular septal thickening; FBP, filtered back projection; MBIR, model-based iterative reconstruction.

Data are presented as mean ± standard deviation. Data of the subjective image analysis were statistically analyzed using the Wilcoxon signed rank tests with a Bonferroni correction applied for multiple comparisons. P \* is a Bonferroni-corrected P value. P \* value <0.05 was considered to be significant.

Figure 2, Thin-section computed tomographic images of a cadaveric lung with diffuse alveolar hemorrhage show diminished visibility of intralobular reticular opacities ( arrowheads ) on (a) 8-mAs and (b) 16-mAs MBIR images as compared to (c) 8-mAs and (d) 80-mAs FBP despite their higher noise levels. FBP, filtered back projection; MBIR, model-based iterative reconstruction.

Figure 3, Thin-section computed tomographic images of a cadaveric lung with metastases acquired and reconstructed using 8-mAs MBIR (a) , 16-mAs MBIR (b) , 32-mAs MBIR (c) , and 80-mAs FBP (d) show similar low level of noise and streak artifacts on the three MBIR images, irrespective of dose. Conspicuity and visibility of peripheral vessels ( long arrow ), interlobar fissure ( arrowheads ), and margins of small and large nodules ( short arrows ) are worse on 8-mAs (a) , similar on 16-mAs (b) , and better on 32-mAs MBIR (c) images as compared to standard-dose FBP (d) . FBP, filtered back projection; MBIR, model-based iterative reconstruction.

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Quantitative Image Noise Measurements

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Figure 4, Quantitative noise measurements (mean ± standard deviation): 8-mAs FBP (24.7 ± 2.21), 8-mAs ASIR 30 (21.6 ± 2.01), 8-mAs ASIR 60 (18.5 ± 1.81), 8-mAs ASIR 90 (15.5 ± 1.64), and 8-mAs MBIR (2.71 ± 1.10). Significant differences in quantitative noise measurements were found among all groups ( P < .001). ASIR, adaptive statistical iterative reconstruction; FBP, filtered back projection; MBIR, model-based iterative reconstruction.

Figure 5, Quantitative noise measurements (mean ± standard deviation): 80-mAs FBP (11.99 ± 2.01), 8-mAs MBIR (2.73 ± 1.11), 16-mAs MBIR (2.42 ± 1.10), and 32-mAs MBIR (2.12 ± 1.10). Significant differences in quantitative noise measurements were found among all groups ( P < .001). FBP, filtered back projection; MBIR = model-based iterative reconstruction.

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Discussion

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Academic Radiology, Volume 21, Issue 6
Journals General Radiology
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