CT image quality over time: comparison of image quality for six different CT scanners over a six‐year period

Roa, A.M. Acosta; Andersen, Hilde Kjernlie; Martinsen, Anne Catrine Trægde

doi:10.1120/jacmp.v16i2.4972

Cited by 33 publications

(17 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Site-specific CT-to-density calibrations are often required due to variations between CT scanners, techniques and reconstruction algorithms. Different CT scanner models and manufacturers have been shown to produce different measurements [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] . For a given scanner, choice of tube voltage can have a significant impact on measured CT numbers [1] , [2] , [3] , [4] , [5] , [8] , [10] , [11] , [12] while other parameters such as tube current have been shown to have minimal impact [4] , [12] .…”

Section: Introductionmentioning

confidence: 99%

“…Beyond scanner parameters, variables including software [13] , reconstruction algorithm [3] , [14] and object location [15] have also been demonstrated to alter CT numbers. Once a CT scanner has been calibrated properly, stable CT number over time can be achieved [6] and variations due to phantom variation are typically much lower than those from using different scanners and tube voltages [16] .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations

Fang

Mazur

Mutic

et al. 2018

Physics and Imaging in Radiation Oncology

View full text Add to dashboard Cite

Background and Purpose: A key step in electron Monte Carlo dose calculation requires converting Computed Tomography (CT) numbers from a tomographic acquisition to a mass density. This study investigates the dosimetric consequences of perturbations applied to a calibration table between CT number and mass density. Materials and Methods: A literature search was performed to define lower and upper bounds for physically reasonable perturbations to a reference CT number to mass density calibration table. Electron beam dose was calculated for ten patients using these variations and the results were compared to clinical plans originally derived with a reference calibration table. Dose differences both globally and in the Planning Target Volume (PTV) were assessed using dose-and volume-based metrics and 3-dimensional gamma analysis for each patient. Results: Small but statistically significant differences were observed between perturbations and reference data for certain metrics including volume of the 50% prescription isodose. Upper and lower variations in CT number to mass density calibration yielded mean values of V50% that were 4.4% larger and 2.1% smaller than reference values respectively. Gamma analysis using 3%/3mm criteria indicated > 99% passing rate for the PTV for all patients. Global gamma analysis for some patients showed larger discrepancies possibly due to large electron path lengths through inhomogeneities. Conclusions: In most patients, physically reasonable perturbations in CT number to mass density curves will not induce clinically significant impact on calculated target dose distributions. Strong dependence of electron transport on voxel material may produce dose speckle throughout the volume. Care should be taken in evaluating critical structures at depths beyond the target volume in highly heterogeneous regions.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations

Fang

Mazur

Mutic

et al. 2018

Physics and Imaging in Radiation Oncology

View full text Add to dashboard Cite

show abstract

“…Therefore, for various contrast objects (teflon, delrin, LDPE, polystyrene, acrilic), we assessed CNR as the ratio between contrast (i.e. difference in CT numbers between the object and background) and noise [ 51 , 67 , 68 , 79 ]. Furthermore, we included the LCD analysis, which allows to assess the limiting detectable contrast threshold for a given object size [ 71 , 80 – 83 ].…”

Section: Discussionmentioning

confidence: 99%

A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre—A phantom study

et al. 2021

View full text Add to dashboard Cite

Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDIvol range: 54.7–57.5 mGy) employed by the staff of various Radiology/Neuroradiology departments of our institution for routine head examinations. CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. Noise values ranged from 3.5 HU to 5.7 HU across scanners/acquisition protocols. NPS curves differed in terms of peak position (range: 0.21–0.30 mm-1). A substantial variation of CNR values with scanner/acquisition protocol was observed for different contrast inserts. The coefficient of variation (standard deviation divided by mean value) of CNR values across scanners/acquisition protocols was 18.3%, 31.4%, 34.2%, 30.4% and 30% for teflon, delrin, LDPE, polystyrene and acrylic insert, respectively. An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f50%/f10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. A relevant difference in LCD performance of different scanners/acquisition protocols was found. The range of contrast threshold for a typical object size of 3 mm was 3.7–5.8 HU. Moreover, appreciable differences in terms of NUI values (range: 4.1%-8.3%) were found. The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. This highlights the importance of a physical in-depth characterization of image quality for each CT scanner as clinically used, in order to optimize CT imaging procedures.

show abstract

“…Increased image noise impeded clinical interpretation of post‐contrast CT scans from an updated CT scanner that was recently added to a fleet of existing scanners from the same vendor. The goals of this work were to quantify and standardize image quality on the new and an existing scanner using phantom images and determine why this issue was not discovered upon acceptance testing, which used conventional techniques employing water or water‐equivalent uniform sections of phantom to quantify image noise …”

Section: Discussionmentioning

confidence: 99%

“…These advancements create challenges in harmonizing image quality and appearance from a large fleet of clinical scanners. Several groups, however, have quantified and homogenized image appearance on similar scanner models using uniform sections of water or water‐equivalent materials . At our institution, feedback from radiologists indicated that differences in image appearance and noise on a new CT scanner we recently added to our fleet impeded reading of post‐contrast scans (Fig.…”

Section: Introductionmentioning

confidence: 99%

Quantification and homogenization of image noise between two CT scanner models

Einstein

Rong

Jensen

et al. 2019

J Applied Clin Med Phys

View full text Add to dashboard Cite

Feedback from radiologists indicated that differences in image appearance and noise impeded reading of post-contrast computed tomography (CT) scans from an updated CT scanner that was recently added to a fleet of existing scanners from the same vendor, despite using identically named reconstruction algorithms. The goals of this work were to quantify and possibly standardize image quality on the new and an existing scanner using phantom images. Three months of daily quality control images were analyzed to determine the mean CT number and noise magnitude in a water phantom. Next, subtraction images from the uniformity section of an American College of Radiology CT phantom were used to generate noise power spectra for both scanners. Then, a semi-anthropomorphic liver phantom was imaged with both scanners in triplicate using identical body protocols to quantify differences CT number and noise magnitude. Finally, the scanner dependence of CT number and noise magnitude on material attenuation was quantified using a multi-energy CT phantom with 15 material inserts. Significant differences between scanners were determined using a paired or Welch's t test as appropriate. In daily quality control images, the new scanner exhibited slightly higher CT number (0.697 vs. 0.412, P < 0.001, n = 85) and slightly lower noise magnitude (4.85 vs. 4.94, P < 0.001, n = 85). Measured NPS was not significantly different between the existing and new scanners. Interestingly, it was observed that the noise magnitude from the new scanner increased with increasing material attenuation in both the liver (P = 0.008) and multi-energy (P < 0.001) phantoms. Using an alternate reconstruction algorithm with the new scanner eliminated this deviation at high material attenuations. While standard noise evaluation in a water phantom was unable to discern differences between the scanners, more comprehensive testing with higher attenuation materials allowed for the characterization and homogenization of image quality. K E Y W O R D S computed tomography, image noise, image quality, noise power spectrum ---

show abstract

CT image quality over time: comparison of image quality for six different CT scanners over a six‐year period

Cited by 33 publications

References 12 publications

The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations

The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations

A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre—A phantom study

Quantification and homogenization of image noise between two CT scanner models

Contact Info

Product

Resources

About