Optimal reconstructed section thickness for the detection of liver lesions with multidetector CT

Soo, Geoffrey; Lau, Ken; Yik, T.; Kutschera, P.

doi:10.1016/j.crad.2009.10.009

“…For example, Soo et al8 found that a slice thickness of 5 mm allowed a better detection, by radiologists, of lesions <5 mm in diameter than 2.5, 7.5, and 10 mm slices. Z ‐axial PVE dramatically decreased the detection rate from 95% for 5 mm slices to 65% and 42% for the thicker 7.5‐ and 10‐mm slices, respectively, while an increase in image noise on the thinner 2.5‐mm slices decreased detection to 90%.…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, tradeoffs between axial resolution and noise can be envisaged to optimize CT protocols for an envisaged clinical application 7. Previous studies have tested various protocols to find the slice thickness,8, 9, 10 slice spacing,11, 12 or interpolation algorithm13 that would give the best compromise between z ‐axial resolution and noise. Although the physical relationships between axial resolution and noise in CT are long known, the stochastic influence of z ‐axial PVE on the contrast of small objects has never been taken into account.…”

Section: Introductionmentioning

confidence: 99%

Optimal slice thickness for object detection with longitudinal partial volume effects in computed tomography

Monnin¹,

Sfameni²,

Gianoli³

et al. 2016

J Applied Clin Med Phys

View full text Add to dashboard Cite

Longitudinal partial volume effects (z‐axial PVE), which occur when an object partly occupies a slice, degrade image resolution and contrast in computed tomography (CT). Z‐axial PVE is unavoidable for subslice objects and reduces their contrast according to their fraction contained within the slice. This effect can be countered using a smaller slice thickness, but at the cost of an increased image noise or radiation dose. The aim of this study is to offer a tool for optimizing the reconstruction parameters (slice thickness and slice spacing) in CT protocols in the case of partial volume effects. This optimization is based on the tradeoff between axial resolution and noise. For that purpose, we developed a simplified analytical model investigating the average statistical effect of z‐axial PVE on contrast and contrast‐to‐noise ratio (CNR). A Catphan 500 phantom was scanned with various pitches and CTDI and reconstructed with different slice thicknesses to assess the visibility of subslice targets that simulate low contrast anatomical features present in CT exams. The detectability score of human observers was used to rank the perceptual image quality against the CNR. Contrast and CNR reduction due to z‐axial PVE measured on experimental data were first compared to numerical calculations and then to the analytical model. Compared to numerical calculations, the simplified algebraic model slightly overestimated the contrast but the differences remained below 5%. It could determine the optimal reconstruction parameters that maximize the objects visibility for a given dose in the case of z‐axial PVE. An optimal slice thickness equal to three‐fourth of the object width was correctly proposed by the model for nonoverlapping slices. The tradeoff between detectability and dose is maximized for a slice spacing of half the slice thickness associated with a slice width equal to the characteristic object width.

show abstract

“…The results showed that 5-mm slice thickness proved to be more effective in the detection of small liver metastases. Soo et al reported significantly improved sensitivity in 2.5-mm and 5-mm compared with 7.5-mm and 10-mm slices for the detection of liver lesions (92% in 2.5 mm, 98% in 5 mm, 78% in 7.5-mm, and 54% in 10-mm) [16]. They noticed an impaired diagnostic accuracy in 2.5-mm compared to 5-mm computed slices due to lower signal noise to ratio.…”

Section: Discussionmentioning

confidence: 99%

Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality

Tamura

¹

,

Nakayama

²

,

Ota

³

et al. 2019

View full text Add to dashboard Cite

The purpose of this study was to investigate whether the novel image-based noise reduction software (NRS) improves image quality, and to assess the feasibility of using this software in combination with hybrid iterative reconstruction (IR) in image quality on thin-slice abdominal CT. In this retrospective study, 54 patients who underwent dynamic liver CT between April and July 2017 and had a body mass index higher than 25 kg/m2 were included. Three image sets of each patient were reconstructed as follows: hybrid IR images with 1-mm slice thickness (group A), hybrid IR images with 5-mm slice thickness (group B), and hybrid IR images with 1-mm slice thickness denoised using NRS (group C). The mean image noise and contrast-to-noise ratio relative to the muscle of the aorta and liver were assessed. Subjective image quality was evaluated by two radiologists for sharpness, noise, contrast, and overall quality using 5-point scales. The mean image noise was significantly lower in group C than in group A (p < 0.01), but no significant difference was observed between groups B and C. The contrast-to-noise ratio was significantly higher in group C than in group A (p < 0.01 and p = 0.01, respectively). Subjective image quality was also significantly higher in group C than in group A (p < 0.01), in terms of noise and overall quality, but not in terms of sharpness and contrast (p = 0.65 and 0.07, respectively). The contrast of images in group C was greater than that in group A, but this difference was not significant. Compared with hybrid IR alone, the novel NRS combined with a hybrid IR could result in significant noise reduction without sacrificing image quality on CT. This combined approach will likely be particularly useful for thin-slice abdominal CT examinations of overweight patients.

show abstract

“…Nevertheless, the analytical model may be easily applied for a complicated clinical task such as liver lesion detection. For example, Soo et al found that a slice thickness of 5 mm allowed a better detection, by radiologists, of lesions <5 mm in diameter than 2.5, 7.5, and 10 mm slices. Z ‐axial PVE dramatically decreased the detection rate from 95% for 5 mm slices to 65% and 42% for the thicker 7.5‐ and 10‐mm slices, respectively, while an increase in image noise on the thinner 2.5‐mm slices decreased detection to 90%.…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, tradeoffs between axial resolution and noise can be envisaged to optimize CT protocols for an envisaged clinical application . Previous studies have tested various protocols to find the slice thickness, slice spacing, or interpolation algorithm that would give the best compromise between z ‐axial resolution and noise. Although the physical relationships between axial resolution and noise in CT are long known, the stochastic influence of z ‐axial PVE on the contrast of small objects has never been taken into account.…”

Section: Introductionmentioning

confidence: 99%

Optimal slice thickness for object detection with longitudinal partial volume effects in computed tomography [JACMP, 18(1) 251-259, 2017]

Monnin

¹

,

Sfameni

²

,

Gianoli

³

et al. 2018

J Appl Clin Med Phys

View full text Add to dashboard Cite

Longitudinal partial volume effects (z‐axial PVE), which occur when an object partly occupies a slice, degrade image resolution and contrast in computed tomography (CT). Z‐axial PVE is unavoidable for subslice objects and reduces their contrast according to their fraction contained within the slice. This effect can be countered using a smaller slice thickness, but at the cost of an increased image noise or radiation dose. The aim of this study is to offer a tool for optimizing the reconstruction parameters (slice thickness and slice spacing) in CT protocols in the case of partial volume effects. This optimization is based on the tradeoff between axial resolution and noise. For that purpose, we developed a simplified analytical model investigating the average statistical effect of z‐axial PVE on contrast and contrast‐to‐noise ratio (CNR). A Catphan 500 phantom was scanned with various pitches and CTDI and reconstructed with different slice thicknesses to assess the visibility of subslice targets that simulate low contrast anatomical features present in CT exams. The detectability score of human observers was used to rank the perceptual image quality against the CNR. Contrast and CNR reduction due to z‐axial PVE measured on experimental data were first compared to numerical calculations and then to the analytical model. Compared to numerical calculations, the simplified algebraic model slightly overestimated the contrast but the differences remained below 5%. It could determine the optimal reconstruction parameters that maximize the objects visibility for a given dose in the case of z‐axial PVE. An optimal slice thickness equal to three‐fourth of the object width was correctly proposed by the model for nonoverlapping slices. The tradeoff between detectability and dose is maximized for a slice spacing of half the slice thickness associated with a slice width equal to the characteristic object width.

show abstract

Optimal reconstructed section thickness for the detection of liver lesions with multidetector CT

Cited by 9 publications

References 8 publications

Optimal slice thickness for object detection with longitudinal partial volume effects in computed tomography

Optimal slice thickness for object detection with longitudinal partial volume effects in computed tomography

Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality

Optimal slice thickness for object detection with longitudinal partial volume effects in computed tomography [JACMP, 18(1) 251-259, 2017]

Contact Info

Product

Resources

About