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- Ehsan Saffari, Seyed, et al.
(författare)
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Regression models for analyzing radiological visual grading studies - an empirical comparison
- 2015
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Ingår i: BMC Medical Imaging. - : BioMed Central. - 1471-2342. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Background: For optimizing and evaluating image quality in medical imaging, one can use visual grading experiments, where observers rate some aspect of image quality on an ordinal scale. To analyze the grading data, several regression methods are available, and this study aimed at empirically comparing such techniques, in particular when including random effects in the models, which is appropriate for observers and patients. Methods: Data were taken from a previous study where 6 observers graded or ranked in 40 patients the image quality of four imaging protocols, differing in radiation dose and image reconstruction method. The models tested included linear regression, the proportional odds model for ordinal logistic regression, the partial proportional odds model, the stereotype logistic regression model and rank-order logistic regression (for ranking data). In the first two models, random effects as well as fixed effects could be included; in the remaining three, only fixed effects. Results: In general, the goodness of fit (AIC and McFadden's Pseudo R-2) showed small differences between the models with fixed effects only. For the mixed-effects models, higher AIC and lower Pseudo R-2 was obtained, which may be related to the different number of parameters in these models. The estimated potential for dose reduction by new image reconstruction methods varied only slightly between models. Conclusions: The authors suggest that the most suitable approach may be to use ordinal logistic regression, which can handle ordinal data and random effects appropriately.
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| 2. |
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| 3. |
- Löve, Askell, et al.
(författare)
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Comprehensive CT Evaluation in Acute Ischemic Stroke: Impact on Diagnosis and Treatment Decisions.
- 2011
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Ingår i: Stroke Research and Treatment. - : Hindawi Limited. - 2042-0056. ; 2011:Mar 15
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Tidskriftsartikel (refereegranskat)abstract
- Background. With modern CT imaging a comprehensive overview of cerebral macro- and microcirculation can be obtained within minutes in acute ischemic stroke. This opens for patient stratification and individualized treatment. Methods. Four patients with acute ischemic stroke of different aetiologies and/or treatments were chosen for illustration of the comprehensive CT protocol and its value in subsequent treatment decisions. The patients were clinically evaluated according to the NIHSS-scale, examined with the comprehensive CT protocol including both CT angiography and CT perfusion, and followed up by MRI. Results. The comprehensive CT examination protocol increased the examination time but did not delay treatment initiation. In some cases CT angiography revealed the cause of stroke while CT perfusion located and graded the perfusion defect with reasonable accuracy, confirmed by follow-up MR-diffusion. In the presented cases findings of the comprehensive CT examination influenced the treatment strategy. Conclusions. The comprehensive CT examination is a fast and safe method allowing accurate diagnosis and making way for individualized treatment in acute ischemic stroke.
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| 5. |
- Löve, Askell, et al.
(författare)
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Hybrid Iterative Reconstruction Algorithm Improves Image Quality in Craniocervical CT Angiography.
- 2013
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Ingår i: American Journal of Roentgenology: diagnostic imaging and related sciences. - 1546-3141. ; 201:6, s. 861-866
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE. The purpose of this study was to evaluate the potential of a hybrid iterative reconstruction algorithm for improving image quality in craniocervical CT angiography (CTA) and to assess observer performance. SUBJECTS AND METHODS. Thirty patients (mean age, 58 years; range 16-80 years) underwent standard craniocervical CTA (volume CT dose index, 6.8 mGy, 2.8 mSv). Images were reconstructed using both filtered back projection (FBP) and a hybrid iterative reconstruction algorithm. Five neuroradiologists assessed general image quality and delineation of the vessel lumen in seven arterial segments using a 4-grade scale. Interobserver and intraobserver variability were determined. Mean attenuation and noise were measured and signal-to-noise and contrast-to-noise ratios calculated. Descriptive statistics are presented and data analyzed using linear mixed-effects models. RESULTS. In pooled data, image quality in iterative reconstruction was graded superior to FBP regarding all five quality criteria (p < 0.0001), with the greatest improvement observed in the vertebral arteries. Iterative reconstruction resulted in elimination of arterial segments graded poor. Interobserver percentage agreement was significantly better (p = 0.024) for iterative reconstruction (69%) than for FBP (66%) but worse than intraobserver percentage agreement (mean, 79%). Noise levels, signal-to-noise ratio, and contrast-to-noise ratio were significantly (p < 0.001) improved in iterative reconstruction at all measured levels. CONCLUSION. The iterative reconstruction algorithm significantly improves image quality in craniocervical CT, especially at the thoracic inlet. Despite careful study design, considerable interobserver and intraobserver variability was noted.
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| 6. |
- Löve, Askell, et al.
(författare)
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Hybrid iterative reconstruction algorithm in brain CT: a radiation dose reduction and image quality assessment study.
- 2013
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Ingår i: Acta radiologica (Stockholm, Sweden : 1987). - : SAGE Publications. - 1600-0455 .- 0284-1851.
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Tidskriftsartikel (refereegranskat)abstract
- Iterative reconstruction (IR) algorithms improve image quality and allow for radiation dose reduction in CT. Dose reduction is particularly challenging in brain CT where good low-contrast resolution is essential. Ideally, evaluation of image quality combines objective measurements and subjective assessment of clinically relevant quality criteria. Subjective assessment is associated with various pitfalls and biases.
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| 7. |
- Löve, Askell
(författare)
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Optimization of image quality and radiation dose in neuroradiological computed tomography
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: The goal of clinical computed tomography (CT) is to produce images of diagnostic quality using the lowest possible radiation exposure. Degradation of image quality, with increased image noise and reduced spatial resolution, is a major limitation for radiation dose reduction in CT. This can be counteracted with new post-processing image filters and iterative reconstruction (IR) algorithms that improve image quality and allow for reduced radiation doses. Implementation of new methods in clinical routine requires prior validation in phantoms and clinical feasibility studies including comprehensive evaluation of diagnostic image quality. Aims: The main objectives of this thesis were to assess new methods for improvement of image quality in CT, explore the associated potential for radiation dose reduction, and to outline a comprehensive approach for evaluation of image quality. Methods: Extensive phantom testing was performed and a total of 100 human subjects were included in the clinical studies. Image quality and diagnostic acceptability were assessed in brain CT acquired with 30% reduced radiation dose in combination with post-processing filter (Paper I) and IR (Paper II). The potential of IR for image quality improvement, without concomitant radiation dose reduction, was assessed in craniocervical CT angiography (CTA) (Paper III). The performance of six IR algorithms was evaluated in a brain CT phantom model (Paper IV), using different combinations of radiation dose levels and iterative image optimization levels. Throughout the studies, various approaches for subjective and objective evaluation of image quality were used and assessed. Results: Post-processing image filtering (Paper I) and IR (Paper II) compensated partly or entirely for the loss of image quality caused by 30% reduced radiation dose in brain CT. In both studies, considerable inter-observer variation was seen. In Paper II a discrepancy was seen between results of objective and subjective evaluation of image quality and also between grading and ranking, indicating observer bias. Statistical IR improved image quality in craniocervical CTA (Paper III) with fairly good inter-observer agreement. Despite having different strengths and weaknesses, the six iterative reconstruction algorithms evaluated in Paper IV all improved image quality. Best over-all improvement was seen for one of the model-based IR algorithms, especially at lower radiation doses. Conclusion: All evaluated methods improved image quality and showed potential for radiation dose reduction while maintaining diagnostic quality. Careful study design and comprehensive evaluation of image quality including objective and subjective evaluation steps may reduce observer bias and improve reliability of study results.
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| 9. |
- Siemund, Roger, et al.
(författare)
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Radiation dose reduction in CT of the brain: can advanced noise filtering compensate for loss of image quality?
- 2012
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Ingår i: Acta radiologica (Stockholm, Sweden : 1987). - : SAGE Publications. - 1600-0455 .- 0284-1851. ; 53:4, s. 468-472
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Tidskriftsartikel (refereegranskat)abstract
- Background: Computed tomography (CT) of the brain is performed with high local doses due to high demands on low contrast resolution. Advanced algorithms for noise reduction might be able to preserve critical image information when reducing radiation dose.PurposeTo evaluate the effect of advanced noise filtering on image quality in brain CT acquired with reduced radiation dose. Material and Methods: Thirty patients referred for non-enhanced CT of the brain were examined with two helical protocols: normal dose (ND, CTDI(vol) 57 mGy) and low dose (LD, CTDI(vol) 40 mGy) implying a 30% radiation dose reduction. Images from the LD examinations were also postprocessed with a noise reduction software with non-linear filters (SharpView CT), creating filtered low dose images (FLD) for each patient. The three image stacks for each patient were presented side by side in randomized order. Five radiologists, blinded for dose level and filtering, ranked these three axial image stacks (ND, LD, FLD) as best to poorest (1 to 3) regarding three image quality criteria. Measurements of mean Hounsfield units (HU) and standard deviation (SD) of the HU were calculated for large region of interest in the centrum semiovale as a measure for noise. Results: Ranking results in pooled data showed that the advanced noise filtering significantly improved the image quality in FLD as compared to LD images for all tested criteria. No significant differences in image quality were found between ND examinations and FLD. However, there was a notable inter-reader spread of the ranking. SD values were 15% higher for LD as compared to ND and FLD.ConclusionThe advanced noise filtering clearly improves image quality of CT examinations of the brain. This effect can be used to significantly lower radiation dose.
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