Transmission of hepatitis C virus during computed tomography scanning with contrast.
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ABSTRACT:
SUBMITTER: Panella H
PROVIDER: S-EPMC2600211 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gold nanoparticles (gold-NPs) have lately been proposed as alternative contrast agents to iodine-based contrast agents (iodine-CA) for computed tomography (CT) angiography. The aims of this study were to confirm an appropriate environment in which to evaluate such novel contrast agents, to investigate the comparative contrast of iodine-CA versus gold-NP, and to determine optimal scanning parameters for gold-NP.Three different clinical scanners were used to acquire CT images. A range of concentrations (10 mM to 1.5 M) of gold-NP and iodine-CA were scanned with varying x-ray tube voltages and currents, reconstruction kernels, protocols, and scanner models. The different environments investigated were air, water, and water with a bone simulant (Ca3(PO4)2). Regression coefficients were derived from the attenuation values plotted against concentration and compared for statistical significance using t values.As expected, contrast was linearly related to concentrations up to 500 to 1000 mM, depending on the conditions used, whereupon a plateau of 3000 Hounsfield units was reached. Attenuation was significantly different depending on the environment used (air, water, or water and bone simulant). Contrast is dependent on the x-ray tube voltage used, with the contrast produced from iodine-CA sharply declining with increasing voltage, whereas the contrast of gold-NP varied less with tube voltage but was maximal at 120 kV in water with bone simulant. Current, reconstruction kernels, protocols, and scanner model had less effect on contrast.Water with a bone simulant is a preferable environment for evaluating novel cardiac CT contrast agents. Relative iodine-CA versus gold-NP contrast is dependent on the scanning conditions used. Optimal scanning conditions for gold-NP will likely use an x-ray tube voltage of 120 kV.
| S-EPMC3582405 | biostudies-literature
Project description:Assessment of the early stages of fracture healing via X-rays and computed tomography is limited by the low radio-opacity of cartilage. We validated a method of contrast-enhanced computed tomography (CECT) for non-destructive identification of cartilage within a healing fracture callus. Closed, stabilized fractures in femora of C57BL/6 mice were harvested on post-operative day 9.5 and imaged ex vivo with micro-computed tomography (µCT) before and after incubation in a cationic contrast agent that preferentially accumulates in cartilage due to the high concentration of sulfated glycosaminoglycans in the tissue. Co-registration of the pre- and post-incubation images, followed by image subtraction, enabled two- and three-dimensional delineation of mineralized tissue, soft callus, and cartilage. The areas of cartilage and callus identified with CECT were compared to those identified with the gold-standard method of histomorphometry. No difference was found between the areas of cartilage measured by the two methods (p = 0.999). Callus area measured by CECT was smaller than, but strongly predictive of (R(2) = 0.80, p < 0.001), the corresponding histomorphometric measurements. CECT also enabled qualitative identification of mineralized cartilage. These findings indicate that the CECT method provides accurate, quantitative, and non-destructive visualization of the shape and composition of the fracture callus, even during the early stages of repair when little mineralized tissue is present. The non-destructive nature of this method would allow subsequent analyses, such as mechanical testing, to be performed on the callus, thus enabling higher-throughput, comprehensive investigations of bone healing.
| S-EPMC3761062 | biostudies-literature
Project description:Aims: Multimodal computed tomography (mCT) (non-contrast CT, CT angiography, and CT perfusion) is not routinely used to assess posterior fossa strokes. We described the area under the curve (AUC) of brain NCCT, WB-CTP automated core-penumbra maps and comprehensive CTP analysis (automated core-penumbra maps and all perfusion maps) for posterior fossa strokes. Methods: We included consecutive patients with signs and symptoms of posterior fossa stroke who underwent acute mCT and follow up magnetic resonance diffusion weighted imaging (DWI). Multimodal CT images were reviewed blindly and independently by two stroke neurologists and area under the receiver operating characteristic curve (AUC) was used to compare imaging modalities. Results: From January 2014 to December 2019, 83 patients presented with symptoms suggestive of posterior fossa strokes and had complete imaging suitable for inclusion (49 posterior fossa strokes and 34 DWI negative patients). For posterior fossa strokes, comprehensive CTP analysis had an AUC of 0.68 vs. 0.62 for automated core-penumbra maps and 0.55 for NCCT. For cerebellar lesions >5 mL, the AUC was 0.87, 0.81, and 0.66, respectively. Conclusion: Comprehensive CTP analysis increases the detection of posterior fossa lesions compared to NCCT and should be implemented as part of the routine imaging assessment in posterior fossa strokes.
| S-EPMC7714905 | biostudies-literature
Project description:ObjectivesNon-contrast computed tomography (NCCT) markers are robust predictors of parenchymal hematoma expansion in intracerebral hemorrhage (ICH). We investigated whether NCCT features can also identify ICH patients at risk of intraventricular hemorrhage (IVH) growth.MethodsPatients with acute spontaneous ICH admitted at four tertiary centers in Germany and Italy were retrospectively included from January 2017 to June 2020. NCCT markers were rated by two investigators for heterogeneous density, hypodensity, black hole sign, swirl sign, blend sign, fluid level, island sign, satellite sign, and irregular shape. ICH and IVH volumes were semi-manually segmented. IVH growth was defined as IVH expansion > 1 mL (eIVH) or any delayed IVH (dIVH) on follow-up imaging. Predictors of eIVH and dIVH were explored with multivariable logistic regression. Hypothesized moderators and mediators were independently assessed in PROCESS macro models.ResultsA total of 731 patients were included, of whom 185 (25.31%) suffered from IVH growth, 130 (17.78%) had eIVH, and 55 (7.52%) had dIVH. Irregular shape was significantly associated with IVH growth (OR 1.68; 95%CI [1.16-2.44]; p = 0.006). In the subgroup analysis stratified by the IVH growth type, hypodensities were significantly associated with eIVH (OR 2.06; 95%CI [1.48-2.64]; p = 0.015), whereas irregular shape (OR 2.72; 95%CI [1.91-3.53]; p = 0.016) in dIVH. The association between NCCT markers and IVH growth was not mediated by parenchymal hematoma expansion.ConclusionsNCCT features identified ICH patients at a high risk of IVH growth. Our findings suggest the possibility to stratify the risk of IVH growth with baseline NCCT and might inform ongoing and future studies.Clinical relevance statementNon-contrast CT features identified ICH patients at a high risk of intraventricular hemorrhage growth with subtype-specific differences. Our findings may assist in the risk stratification of intraventricular hemorrhage growth with baseline CT and might inform ongoing and future clinical studies.Key points• NCCT features identified ICH patients at a high risk of IVH growth with subtype-specific differences. • The effect of NCCT features was not moderated by time and location or indirectly mediated by hematoma expansion. • Our findings may assist in the risk stratification of IVH growth with baseline NCCT and might inform ongoing and future studies.
| S-EPMC10598100 | biostudies-literature
Project description: Not available
| S-EPMC9185519 | biostudies-literature
Project description:Gross dissection has a long history as a tool for the study of human or animal soft- and hard-tissue anatomy. However, apart from being a time-consuming and invasive method, dissection is often unsuitable for very small specimens and often cannot capture spatial relationships of the individual soft-tissue structures. The handful of comprehensive studies on avian anatomy using traditional dissection techniques focus nearly exclusively on domestic birds, whereas raptorial birds, and in particular their cranial soft tissues, are essentially absent from the literature. Here, we digitally dissect, identify, and document the soft-tissue anatomy of the Common Buzzard (Buteo buteo) in detail, using the new approach of contrast-enhanced computed tomography using Lugol's iodine. The architecture of different muscle systems (adductor, depressor, ocular, hyoid, neck musculature), neurovascular, and other soft-tissue structures is three-dimensionally visualised and described in unprecedented detail. The three-dimensional model is further presented as an interactive PDF to facilitate the dissemination and accessibility of anatomical data. Due to the digital nature of the data derived from the computed tomography scanning and segmentation processes, these methods hold the potential for further computational analyses beyond descriptive and illustrative proposes.
| S-EPMC4098676 | biostudies-literature
Project description:Accurate gluteus medius (GMd) volume evaluation may aid in the analysis of muscular atrophy states and help gain an improved understanding of patient recovery via rehabilitation. However, the segmentation of muscle regions in GMd images for cubic muscle volume assessment is time-consuming and labor-intensive. This study automated GMd-region segmentation from the computed tomography (CT) images of patients diagnosed with hip osteoarthritis using deep learning and evaluated the segmentation accuracy. To this end, 5250 augmented pairs of training data were obtained from five participants, and a conditional generative adversarial network was used to identify the relationships between the image pairs. Using the preserved test datasets, the results of automatic segmentation with the trained deep learning model were compared to those of manual segmentation in terms of the dice similarity coefficient (DSC), volume similarity (VS), and shape similarity (MS). As observed, the average DSC values for automatic and manual segmentations were 0.748 and 0.812, respectively, with a significant difference (p < 0.0001); the average VS values were 0.247 and 0.203, respectively, with no significant difference (p = 0.069); and the average MS values were 1.394 and 1.156, respectively, with no significant difference (p = 0.308). The GMd volumes obtained by automatic and manual segmentation were 246.2 cm3 and 282.9 cm3, respectively. The noninferiority of the DSC obtained by automatic segmentation was verified against that obtained by manual segmentation. Accordingly, the proposed GAN-based automatic GMd-segmentation technique is confirmed to be noninferior to manual segmentation. Therefore, the findings of this research confirm that the proposed method not only reduces time and effort but also facilitates accurate assessment of the cubic muscle volume.
| S-EPMC8432798 | biostudies-literature
Project description:Introduction Accurate identification of infarcts in non-contrast computed tomography (NC-CT) scans of the brain is fundamental in the diagnosis and management of patients with stroke. Quantification of image contrast properties at the boundaries of ischemic infarct regions in NC-CT can contribute to a more precise manual or automatic delineation of these regions. Here we explore these properties quantitatively. Methods We retrospectively investigated 519 NC-CT studies of 425 patients with clinically confirmed ischemic strokes. The average and standard deviation (SD) of patients' age was 67.5?±?12.4 years and the average(median)±SD time from symptoms onset to NC-CT examination was 27.4(12)±35.7?h. For every scan with an ischemic lesion identified by experts, the image contrast of the lesion vs. normal surrounding parenchyma was calculated as a difference of mean Hounsfield Unit (HU) of 1-5 consecutive voxels (the contrast window width) belonging to the lesion and to the parenchyma. This contrast was calculated at each single voxel of ischemic lesion boundaries (previously delineated by the experts) in horizontal and vertical directions in each image. The distributions of obtained horizontal, vertical and both contrasts combined were calculated among all 519 NC-CTs. Results The highest applicative contrast window width was identified as 5 voxels. The ischemic infarcts were found to be characterized by 6.60?HU, 8.28?HU and 7.55?HU mean values for distributions of horizontal, vertical and combined contrasts. Approximately 40-50% of the infarct boundary voxels were found to refer to the image contrast below 5?HU. Conclusion Low image contrast of ischemic lesions prevents accurate delineation of the infarcts in NC-CT.
| S-EPMC5564335 | biostudies-literature
Project description:BackgroundTreatment of nasal tumors in dogs is associated with high morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion.ObjectivesTo assess perfusion parameters of nasal tumors (correlating with tumor type) before and during radiotherapy (RT) and find potential correlation with survival.AnimalsTwenty-four client-owned dogs with nasal tumors, including 16 epithelial tumors and 8 sarcomas.MethodsProspective cross-sectional study. All dogs had baseline DCECT to assess fractional vascular volume (BV), blood flow (BF), and transit time (TT). Thirteen dogs had repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated.ResultsMedian BV was 17.83 mL/100 g (range, 3.63-66.02), median BF was 122.63 mL/100 g/minute (range, 23.65-279.99), and median TT was 8.91 seconds (range, 4.57-14.23). Sarcomas had a significantly lower BF than adenocarcinomas (P = .002), carcinomas (P = .01), and other carcinomas (P = .001), and significantly lower BV than adenocarcinomas (P = .03) and other carcinomas (P = .004). Significant associations were found between epithelial tumors and sarcoma for change in tumor volume (P = .01), width (P = .004), and length (P = .02) in that epithelial tumors decreased in volume whereas sarcomas increased in volume. Perfusion parameters were not correlated with survival.Conclusions and clinical importanceNasal sarcomas have lower BV and BF than nasal carcinomas, and sarcomas have a lower size reduction than carcinomas early on during RT. Baseline results and changes in perfusion parameters may not be correlated with survival.
| S-EPMC10229329 | biostudies-literature
Project description:This study aimed to evaluate a deep learning model for generating synthetic contrast-enhanced CT (sCECT) from non-contrast chest CT (NCCT). A deep learning model was applied to generate sCECT from NCCT. We collected three separate data sets, the development set (n = 25) for model training and tuning, test set 1 (n = 25) for technical evaluation, and test set 2 (n = 12) for clinical utility evaluation. In test set 1, image similarity metrics were calculated. In test set 2, the lesion contrast-to-noise ratio of the mediastinal lymph nodes was measured, and an observer study was conducted to compare lesion conspicuity. Comparisons were performed using the paired t-test or Wilcoxon signed-rank test. In test set 1, sCECT showed a lower mean absolute error (41.72 vs 48.74; P < .001), higher peak signal-to-noise ratio (17.44 vs 15.97; P < .001), higher multiscale structural similarity index measurement (0.84 vs 0.81; P < .001), and lower learned perceptual image patch similarity metric (0.14 vs 0.15; P < .001) than NCCT. In test set 2, the contrast-to-noise ratio of the mediastinal lymph nodes was higher in the sCECT group than in the NCCT group (6.15 ± 5.18 vs 0.74 ± 0.69; P < .001). The observer study showed for all reviewers higher lesion conspicuity in NCCT with sCECT than in NCCT alone (P ≤ .001). Synthetic CECT generated from NCCT improves the depiction of mediastinal lymph nodes.
| S-EPMC8516920 | biostudies-literature