Rationale and Objectives
A new computed tomography (CT) detector with integrated electric components and shorter conducting pathways has recently been introduced to decrease system inherent electronic noise. The purpose of this study was to assess the potential benefit of such integrated circuit detector (ICD) in head CT by comparing objective and subjective image quality in low-dose examinations with a conventional detector design.
Materials and Methods
Using a conventional detector, reduced-dose noncontrast head CT (255 mAs; effective dose, 1.7 mSv) was performed in 25 consecutive patients. Following transition to ICD, 25 consecutive patients were scanned using identical imaging parameters. Images in both groups were reconstructed with iterative reconstruction (IR) and filtered back projection (FBP) and assessed in terms of quantitative and qualitative image quality.
Results
Acquisition of head CT using ICD increased signal-to-noise ratio of gray and white matter by 14% (10.0 ± 1.6 vs. 11.4 ± 2.5; P = .02) and 17% (8.2 ± 0.8 vs. 9.6 ± 1.5; P = .000). The associated improvement in contrast-to-noise ratio was 12% (2.0 ± 0.5 vs. 2.2 ± 0.6; P = .121). In addition, there was a 51% increase in objective image sharpness (582 ± 85 vs. 884.5 ± 191; change in HU/Pixel; P < .000). Compared to standard acquisitions, subjective grading of noise and overall image quality scores were significantly improved with ICD (2.1 ± 0.3 vs. 1.6 ± 0.3; P < .000; 2.0 ± 0.5 vs. 1.6 ± 0.3; P = .001). Moreover, streak artifacts in the posterior fossa were substantially reduced (2.3 ± 0.7 vs. 1.7 ± 0.5; P = .004).
Conclusions
At the same radiation level, acquisition of head CT with ICD achieves superior objective and subjective image quality and provides potential for significant dose reduction.
Although technical evolution of computed tomography (CT) has primarily been oriented by improvement of speed, volume coverage, and image quality, a continued rise in study numbers and heighted public awareness of radiation-associated cancer risks have eventually brought about a paradigm shift and initiated a recent quest for significant reduction of radiation dose .
Given the close correlation between signal-to-noise ratio (SNR) and dose, most attempts at dose reduction are essentially tradeoffs between image quality and patient exposure. Dose reduction with preserved image quality is a huge technical challenge and necessitates improvement of detector technology and reconstruction algorithms. In fact, more than a decade ago, transition from xenon gas to solid scintillator material detectors resulted in about 20% increase in dose efficiency . A more recent milestone in the realm of dose reduction is the reintroduction of alternative reconstruction algorithms, so-called iterative reconstruction (IR) variants. To a certain extent, the latter allow decoupling of spatial resolution and image noise and are currently challenging the old dose/image quality dogma in many clinical applications .
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Material and methods
Patient Groups
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CT Data Acquisition
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CT Data Reconstruction
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Quantitative Image Analysis
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SNR=mean HU of tissue in ROISD of HU in ROI SNR
=
mean HU of tissue in ROI
SD of HU in ROI
CNR=mean GM HU–mean WM HU[(SD GM HU)×2+(SD WM HU)×2]×12 CNR
=
mean GM HU
–
mean WM HU
[
(
SD GM HU
)
×
2
+
(
SD WM HU
)
×
2
]
×
1
2
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Qualitative Image Analysis
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Dose Measurements
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Statistical Analysis
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Results
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Quantitative Analysis
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Table 1
Comparison of Tissue SNR Between CDD and ICD
CDD ICD FBP IR FBP IR WM 6.6 ± 0.5 9.8 ± 1.0 7.9 ± 1.3; P < .000 11.3 ± 1.9; P = .002 GM 8.0 ± 1.1 11.9 ± 2.2 9.3 ± 1.8; P = .009 13.5 ± 3.2; P = .053 CSF 1.0 ± 0.2 1.4 ± 0.3 1.1 ± 0.3; P = .044 1.6 ± 0.5; P = .417
CDD, conventional distributed detector; CSF, cerebrospinal fluid; FBP, filtered back projection; GM, gray matter; ICD, integrated circuit detector; IR, iterative reconstruction; SNR, signal-to-noise ratio; WM, white matter.
Mean and standard deviation of SNR in acquisitions with CDD and ICD. Data are shown for reconstructions using FBP or IR. P values refer to the difference between ICD and standard detector, while comparing identical reconstruction algorithms.
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Qualitative Analysis
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Table 2
Comparison of Subjective Image Quality Between CDD and ICD
CDD ICD FBP IR FBP IR Noise 2.7 (3) 1.4 (1) 2.2 (2); P = .000 1.1 (1); P = .025 GM/WM 2.4 (2.5) 1.3 (1) 2.1 (2); P = .035 1.1 (1); P = .044 SA 2.4 (2) 2.2 (2) 1.8 (2); P = .008 1.6 (2); P = .003 DA 2.6 (3) 1.5 (1) 2.2 (2); P = .015 1.1 (1); P = .022
CDD, conventional distributed detector; CSF, cerebrospinal fluid; FBP, filtered back projection; GM, gray matter; ICD, integrated circuit detector; IR, iterative reconstruction; SNR, signal-to-noise ratio; WM, white matter.
Mean and median (brackets) image quality scores in acquisitions with CDD and ICD. Data are shown for reconstructions using FBP or IR. Image quality grading is provided for noise, GM–WM differentiation, streak artifacts involving the posterior fossa (SA) and overall diagnostic acceptability (DA). P values refer to the difference between ICD and standard detector, while comparing identical reconstruction algorithms.
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Discussion
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