| 1. |
- Banitalebi, H., et al.
(författare)
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A novel MRI index for paraspinal muscle fatty infiltration: reliability and relation to pain and disability in lumbar spinal stenosis: results from a multicentre study
- 2022
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Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Fatty infiltration of the paraspinal muscles may play a role in pain and disability in lumbar spinal stenosis. We assessed the reliability and association with clinical symptoms of a method for assessing fatty infiltration, a simplified muscle fat index (MFI). Methods: Preoperative axial T2-weighted magnetic resonance imaging (MRI) scans of 243 patients aged 66.6 +/- 8.5 years (mean +/- standard deviation), 119 females (49%), with symptomatic lumbar spinal stenosis were assessed. Fatty infiltration was assessed using both the MFI and the Goutallier classification system (GCS). The MFI was calculated as the signal intensity of the psoas muscle divided by that of the multifidus and erector spinae. Observer reliability was assessed in 102 consecutive patients for three independent investigators by intraclass correlation coefficient (ICC) and 95% limits of agreement (LoA) for continuous variables and Gwet's agreement coefficient (AC1) for categorical variables. Associations with patient-reported pain and disability were assessed using univariate and multivariate regression analyses. Results: Interobserver reliability was good for the MFI (ICC 0.79) and fair for the GCS (AC1 0.33). Intraobserver reliability was good or excellent for the MFI (ICC range 0.86-0.91) and moderate to almost perfect for the GCS (AC1 range 0.55-0.92). Mean interobserver differences of MFI measurements ranged from -0.09 to -0.04 (LoA -0.32 to 0.18). Adjusted for potential confounders, none of the disability or pain parameters was significantly associated with MFI or GCS. Conclusion: The proposed MFI demonstrated high observer reliability but was not associated with preoperative pain or disability.
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| 2. |
- Bibic, Adnan, et al.
(författare)
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Effects of red blood cells with reduced deformability on cerebral blood flow and vascular water transport: measurements in rats using time-resolved pulsed arterial spin labelling at 9.4 T
- 2021
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Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundOur aim was to introduce damaged red blood cells (RBCs) as a tool for haemodynamic provocation in rats, hypothesised to cause decreased cerebral blood flow (CBF) and prolonged water capillary transfer time (CTT), and to investigate whether expected changes in CBF could be observed and if haemodynamic alterations were reflected by the CTT metric.MethodsDamaged RBCs exhibiting a mildly reduced deformability were injected to cause aggregation of RBCs. Arterial spin labelling (ASL) magnetic resonance imaging experiments were performed at 9.4 T. Six datasets (baseline plus five datasets after injection) were acquired for each animal in a study group and a control group (13 and 10 female adult Wistar rats, respectively). For each dataset, ASL images at ten different inversion times were acquired. The CTT model was adapted to the use of a measured arterial input function, implying the use of a realistic labelling profile. Repeated measures ANOVA was used (alpha error = 0.05).ResultsAfter injection, significant differences between the study group and control group were observed for relative CBF in white matter (up to 20 percentage points) and putamen (up to 18–20 percentage points) and for relative CTT in putamen (up to 35–40 percentage points).ConclusionsHaemodynamic changes caused by injection of damaged RBCs were observed by ASL-based CBF and CTT measurements. Damaged RBCs can be used as a tool for test and validation of perfusion imaging modalities. CTT model fitting was challenging to stabilise at experimental signal-to-noise ratio levels, and the number of free parameters was minimised.
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| 3. |
- Borrelli, P., et al.
(författare)
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Artificial intelligence-aided CT segmentation for body composition analysis: a validation study
- 2021
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Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundBody composition is associated with survival outcome in oncological patients, but it is not routinely calculated. Manual segmentation of subcutaneous adipose tissue (SAT) and muscle is time-consuming and therefore limited to a single CT slice. Our goal was to develop an artificial-intelligence (AI)-based method for automated quantification of three-dimensional SAT and muscle volumes from CT images.MethodsEthical approvals from Gothenburg and Lund Universities were obtained. Convolutional neural networks were trained to segment SAT and muscle using manual segmentations on CT images from a training group of 50 patients. The method was applied to a separate test group of 74 cancer patients, who had two CT studies each with a median interval between the studies of 3days. Manual segmentations in a single CT slice were used for comparison. The accuracy was measured as overlap between the automated and manual segmentations.ResultsThe accuracy of the AI method was 0.96 for SAT and 0.94 for muscle. The average differences in volumes were significantly lower than the corresponding differences in areas in a single CT slice: 1.8% versus 5.0% (p <0.001) for SAT and 1.9% versus 3.9% (p < 0.001) for muscle. The 95% confidence intervals for predicted volumes in an individual subject from the corresponding single CT slice areas were in the order of 20%.Conclusions The AI-based tool for quantification of SAT and muscle volumes showed high accuracy and reproducibility and provided a body composition analysis that is more relevant than manual analysis of a single CT slice.
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| 4. |
- Buddenkotte, Thomas, et al.
(författare)
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Deep learning-based segmentation of multisite disease in ovarian cancer
- 2023
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Ingår i: EUROPEAN RADIOLOGY EXPERIMENTAL. - : Springer Nature. - 2509-9280. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established “no-new-Net” framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10–7, 3 × 10–4, 4 × 10–2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10–3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.Relevance statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.Key points:The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented.Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists.Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. Graphical Abstract: [Figure not available: see fulltext.]
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| 5. |
- Klasson, Niklas, et al.
(författare)
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Estimated intracranial volume from FreeSurfer is biased by total brain volume
- 2018
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Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Background Estimated intracranial volume (eTIV) from FreeSurfer is not segmentation-based but calculated from the alignment of the input magnetic resonance (MR) images to the MNI305 brain atlas, an approach that could lead to a bias by total brain volume. If eTIV is unbiased, variance beyond that explained by intracranial volume should be random. Our null hypothesis was that no correlation would remain between eTIV and total brain volume when controlling for intracranial volume. Methods eTIV and total brain volume for 62 participants were calculated on 1.5-T, T1-weighted MR images using FreeSurfer (version 6.0.0). Manual delineations of the intracranial volume were also made for the same images. To evaluate the null hypothesis, the partial correlation between eTIV and total brain volume was calculated when controlling for intracranial volume. Results The partial correlation between eTIV and total brain volume when controlling for intracranial volume was 0.355 (p=0.026). The null hypothesis was rejected. Conclusion eTIV from FreeSurfer is biased by total brain volume.
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| 6. |
- Klintström, Benjamin, et al.
(författare)
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Photon-counting detector CT and energy-integrating detector CT for trabecular bone microstructure analysis of cubic specimens from human radius
- 2022
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Ingår i: European radiology experimental. - : Springer Nature. - 2509-9280. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Background As bone microstructure is known to impact bone strength, the aim of this in vitro study was to evaluate if the emerging photon-counting detector computed tomography (PCD-CT) technique may be used for measurements of trabecular bone structures like thickness, separation, nodes, spacing and bone volume fraction. Methods Fourteen cubic sections of human radius were scanned with two multislice CT devices, one PCD-CT and one energy-integrating detector CT (EID-CT), using micro-CT as a reference standard. The protocols for PCD-CT and EID-CT were those recommended for inner- and middle-ear structures, although at higher mAs values: PCD-CT at 450 mAs and EID-CT at 600 (dose equivalent to PCD-CT) and 1000 mAs. Average measurements of the five bone parameters as well as dispersion measurements of thickness, separation and spacing were calculated using a three-dimensional automated region growing (ARG) algorithm. Spearman correlations with micro-CT were computed. Results Correlations with micro-CT, for PCD-CT and EID-CT, ranged from 0.64 to 0.98 for all parameters except for dispersion of thickness, which did not show a significant correlation (p = 0.078 to 0.892). PCD-CT had seven of the eight parameters with correlations rho > 0.7 and three rho > 0.9. The dose-equivalent EID-CT instead had four parameters with correlations rho > 0.7 and only one rho > 0.9. Conclusions In this in vitro study of radius specimens, strong correlations were found between trabecular bone structure parameters computed from PCD-CT data when compared to micro-CT. This suggests that PCD-CT might be useful for analysing bone microstructure in the peripheral human skeleton.
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| 7. |
- Leander, Peter, et al.
(författare)
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A novel food-based negative oral contrast agent compared with two conventional oral contrast agents in abdominal CT : a three-arm parallel blinded randomised controlled single-centre trial
- 2022
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Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: A negative oral contrast agent (OCA) has been long sought for, to better delineate the bowel and visualise surrounding structures. Lumentin® 44 (L44) is a new OCA formulated to fill the entire small bowel. The aim of this study was to compare L44 with positive and neutral conventional OCA in abdominal computed tomography (CT). Methods: Forty-five oncologic patients were randomised to receive either L44 or one of the two comparators (MoviPrep® or diluted Omnipaque®). Abdominal CT examinations with intravenous contrast agent were acquired according to standard protocols. The studies were read independently by two senior radiologists. Results: The mean intraluminal Hounsfield units (HU)-values of regions-of-interest (ROIs) for each subsegment of small bowel and treatment group were -404.0 HU for L44, 166.1 HU for Omnipaque®, and 16.7 HU for MoviPrep® (L44 versus Omnipaque, p < 0.001: L44 versus MoviPrep p < 0.001; Omnipaque versus MoviPrep, p = 0.003). Adverse events, only mild, using L44 were numerically fewer than for using conventional oral contrast agents. Visualisation of abdominal structures beyond the small bowel was similar to the comparators. Conclusions: L44 is a negative OCA with luminal radiodensity at approximately -400 HU creating a unique small bowel appearance on CT scans. The high bowel wall-to-lumen contrast may enable improved visualisation in a range of pathologic conditions. L44 showed a good safety profile and was well accepted by patients studied. Trial registration: EudraCT (2017-002368-42) and in ClinicalTrials.gov (NCT03326518).
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| 8. |
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| 9. |
- Shami, Annelie, et al.
(författare)
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Atherosclerotic plaque features relevant to rupture-risk detected by clinical photon-counting CT ex vivo : a proof-of-concept study
- 2024
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Ingår i: European Radiology Experimental. - 2509-9280. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: To identify subjects with rupture-prone atherosclerotic plaques before thrombotic events occur is an unmet clinical need. Thus, this proof-of-concept study aims to determine which rupture-prone plaque features can be detected using clinically available photon-counting computed tomography (PCCT). Methods: In this retrospective study, advanced atherosclerotic plaques (ex vivo, paraffin-embedded) from the Carotid Plaque Imaging Project were scanned by PCCT with reconstructed energy levels (45, 70, 120, 190 keV). Density in HU was measured in 97 regions of interest (ROIs) representing rupture-prone plaque features as demonstrated by histopathology (thrombus, lipid core, necrosis, fibrosis, intraplaque haemorrhage, calcium). The relationship between HU and energy was then assessed using a mixed-effects model for each plaque feature. Results: Plaques from five men (age 79 ± 8 [mean ± standard deviation]) were included in the study. Comparing differences in coefficients (b 1diff) of matched ROIs on plaque images obtained by PCCT and histology confirmed that calcium was distinguishable from all other analysed features. Of greater novelty, additional rupture-prone plaque features proved discernible from each other, particularly when comparing haemorrhage with fibrous cap (p = 0.017), lipids (p = 0.003) and necrosis (p = 0.004) and thrombus compared to fibrosis (p = 0.048), fibrous cap (p = 0.028), lipids (p = 0.015) and necrosis (p = 0.017). Conclusions: Clinically available PCCT detects not only calcification, but also other rupture-prone features of human carotid plaques ex vivo. Relevance statement: Improved atherosclerotic plaque characterisation by photon-counting CT provides the ability to distinguish not only calcium, but also rupture-prone plaque features such as haemorrhage and thrombus. This may potentially improve monitoring and risk stratification of atherosclerotic patients in order to prevent strokes. Key points: • CT of atherosclerotic plaques mainly detects calcium. • Many components, such as intra-plaque haemorrhage and lipids, determine increased plaque rupture risk. • Ex vivo carotid plaque photon-counting CT distinguishes haemorrhage and thrombus. • Improved plaque photon-counting CT evaluation may refine risk stratification accuracy to prevent strokes. Graphical Abstract: [Figure not available: see fulltext.].
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