72 research outputs found

    3D ultrasound reconstruction of sonographic callus:a novel imaging modality for early evaluation of fracture healing

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    AIMS: The aim of this study was to establish a reliable method for producing 3D reconstruction of sonographic callus. METHODS: A cohort of ten closed tibial shaft fractures managed with intramedullary nailing underwent ultrasound scanning at two, six, and 12 weeks post-surgery. Ultrasound capture was performed using infrared tracking technology to map each image to a 3D lattice. Using echo intensity, semi-automated mapping was performed to produce an anatomical 3D representation of the fracture site. Two reviewers independently performed 3D reconstructions and kappa coefficient was used to determine agreement. A further validation study was undertaken with ten reviewers to estimate the clinical application of this imaging technique using the intraclass correlation coefficient (ICC). RESULTS: Nine of the ten patients achieved union at six months. At six weeks, seven patients had bridging callus of ≥ one cortex on the 3D reconstruction and when present all achieved union. Compared to six-week radiographs, no bridging callus was present in any patient. Of the three patients lacking sonographic bridging callus, one went onto a nonunion (77.8% sensitive and 100% specific to predict union). At 12 weeks, nine patients had bridging callus at ≥ one cortex on 3D reconstruction (100%-sensitive and 100%-specific to predict union). Presence of sonographic bridging callus on 3D reconstruction demonstrated excellent reviewer agreement on ICC at 0.87 (95% confidence interval 0.74 to 0.96). CONCLUSION: 3D fracture reconstruction can be created using multiple ultrasound images in order to evaluate the presence of bridging callus. This imaging modality has the potential to enhance the usability and accuracy of identification of early fracture healing. Cite this article: Bone Joint Res 2021;10(12):759–766

    Retinal Vascular Measures from Diabetes Retinal Screening Photographs and Risk of Incident Dementia in Type 2 Diabetes:A GoDARTS Study

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    OBJECTIVE: Patients with diabetes have an increased risk of dementia. Improved prediction of dementia is an important goal in developing future prevention strategies. Diabetic retinopathy screening (DRS) photographs may be a convenient source of imaging biomarkers of brain health. We therefore investigated the association of retinal vascular measures (RVMs) from DRS photographs in patients with type 2 diabetes with dementia risk. RESEARCH DESIGN AND METHODS: RVMs were obtained from 6,111 patients in the GoDARTS bioresource (635 incident cases) using VAMPIRE software. Their association, independent of Apo E4 genotype and clinical parameters, was determined for incident all cause dementia (ACD) and separately Alzheimer's disease (AD) and vascular dementia (VD). We used Cox’s proportional hazards with competing risk of death without dementia. The potential value of RVMs to increase the accuracy of risk prediction was evaluated. RESULTS: Increased retinal arteriolar fractal dimension associated with increased risk of ACD (csHR 1.17; 1.08–1.26) and AD (HR 1.33; 1.16–1.52), whereas increased venular fractal dimension (FDV) was associated with reduced risk of AD (csHR 0.85; 0.74–0.96). Conversely, FDV was associated with increased risk of VD (csHR 1.22; 1.07–1.40). Wider arteriolar calibre was associated with a reduced risk of ACD (csHR 0.9; 0.83–0.98) and wider venular calibre was associated with a reduced risk of AD (csHR 0.87; 0.78–0.97). Accounting for competing risk did not substantially alter these findings. RVMs significantly increased the accuracy of prediction. CONCLUSIONS: Conventional DRS photographs could enhance stratifying patients with diabetes at increased risk of dementia facilitating the development of future prevention strategies

    Retinal Vessel Phenotype In Patients With Primary Open-Angle Glaucoma

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    International audiencePURPOSE: To characterize the phenotype of retinal vessels using central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), tortuosity and fractal dimension (FD) in primary open-angle glaucoma (POAG) subjects. METHODS: This prospective case-control multicentre study included 61 POAG subjects and 61 controls matched for age, systemic hypertension and body mass index. Fundus images of the right eye were acquired using a non-mydriatic camera. Central retinal artery equivalent (CRAE), CRVE, arteriole-to-venule ratio, FD and tortuosity of the vascular network were measured using VAMPIRE software (Vessel Assessment and Measurement Platform for Images of the Retina). Primary open-angle glaucoma (POAG) patients underwent 24.2 sita-standard visual field and peri-papillary optical coherence tomography (OCT) examinations. Data were expressed as median and interquartile range (75-25th percentiles). RESULTS: The control group was comparable to the POAG group for sex ratio, refraction and intraocular pressure. The mean CRAE and the mean CRVE were significantly lower in the POAG group than in the control group [150.5 (137.9; 157.1) mum versus 161.3 (154.0; 168.4) mum and 204.8 (190.1; 218.1) mum versus 233.5 (222.3; 246.9) mum, respectively; p < 0.001] and for fractal parameters as well. No significant difference was found for tortuosity between the two groups. There was a significant correlation between CRAE and retinal nerve fibre layer (RNFL) thickness (r = 0.27; p = 0.03). VAMPIRE parameters were not correlated with visual field indices. CONCLUSION: Primary open-angle glaucoma (POAG) was associated with a narrowing of arterial and venous retinal vessels, a higher arteriole-to-venule ratio and lower values of FD. The relationship between CRAE and RNFL thickness needs further investigation

    An open-source deep learning algorithm for efficient and fully-automatic analysis of the choroid in optical coherence tomography

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    Purpose: To develop an open-source, fully-automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data. Methods: We used a dataset of 715 OCT B-scans (82 subjects, 115 eyes) from 3 clinical studies related to systemic disease. Ground truth segmentations were generated using a clinically validated, semi-automatic choroid segmentation method, Gaussian Process Edge Tracing (GPET). We finetuned a UNet with MobileNetV3 backbone pre-trained on ImageNet. Standard segmentation agreement metrics, as well as derived measures of choroidal thickness and area, were used to evaluate DeepGPET, alongside qualitative evaluation from a clinical ophthalmologist. Results: DeepGPET achieves excellent agreement with GPET on data from 3 clinical studies (AUC=0.9994, Dice=0.9664; Pearson correlation of 0.8908 for choroidal thickness and 0.9082 for choroidal area), while reducing the mean processing time per image on a standard laptop CPU from 34.49s (±\pm15.09) using GPET to 1.25s (±\pm0.10) using DeepGPET. Both methods performed similarly according to a clinical ophthalmologist, who qualitatively judged a subset of segmentations by GPET and DeepGPET, based on smoothness and accuracy of segmentations. Conclusions :DeepGPET, a fully-automatic, open-source algorithm for choroidal segmentation, will enable researchers to efficiently extract choroidal measurements, even for large datasets. As no manual interventions are required, DeepGPET is less subjective than semi-automatic methods and could be deployed in clinical practice without necessitating a trained operator. DeepGPET addresses the lack of open-source, fully-automatic and clinically relevant choroid segmentation algorithms, and its subsequent public release will facilitate future choroidal research both in ophthalmology and wider systemic health.Comment: 8 pages, 2 figures, 3 tables. Currently in submission to ARVO TVST (Association for Research in Vision and Ophthalmology, Translational Vision Science & Technology). GitHub link to codebase provided upon publicatio

    Measuring axial length of the eye from magnetic resonance brain imaging

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    BACKGROUND: Metrics derived from the human eye are increasingly used as biomarkers and endpoints in studies of cardiovascular, cerebrovascular and neurological disease. In this context, it is important to account for potential confounding that can arise from differences in ocular dimensions between individuals, for example, differences in globe size. METHODS: We measured axial length, a geometric parameter describing eye size from T(2)-weighted brain MRI scans using three different image analysis software packages (Mango, ITK and Carestream) and compared results to biometry measurements from a specialized ophthalmic instrument (IOLMaster 500) as the reference standard. RESULTS: Ninety-three healthy research participants of mean age 51.0 ± SD 5.4 years were analyzed. The level of agreement between the MRI-derived measurements and the reference standard was described by mean differences as follows, Mango − 0.8 mm; ITK − 0.5 mm; and Carestream − 0.1 mm (upper/lower 95% limits of agreement across the three tools ranged from 0.9 mm to − 2.6 mm). Inter-rater reproducibility was between − 0.03 mm and 0.45 mm (ICC 0.65 to 0.93). Intra-rater repeatability was between 0.0 mm and − 0.2 mm (ICC 0.90 to 0.95). CONCLUSIONS: We demonstrate that axial measurements of the eye derived from brain MRI are within 3.5% of the reference standard globe length of 24.1 mm. However, the limits of agreement could be considered clinically significant. Axial length of the eye obtained from MRI is not a replacement for the precision of biometry, but in the absence of biometry it could provide sufficient accuracy to act as a proxy. We recommend measuring eye axial length from MRI in studies that do not have biometry but use retinal imaging to study neurodegenerative changes so as to control for differing eye size across individuals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12886-022-02289-y

    Dietary patterns and chronic kidney disease: a cross-sectional association in the Irish Nun Eye Study

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    Associations between dietary patterns and chronic kidney disease are not well established, especially in European populations. We conducted a cross-sectional study of 1033 older Irish women (age range 56–100 years) with a restricted lifestyle. Dietary intake was assessed using a food frequency questionnaire. Renal function was determined by estimated glomerular filtration rate. Two dietary patterns were identified within the study population using factor analysis. A significant negative association was found between unhealthy dietary pattern adherence and renal function in both unadjusted and adjusted models controlling for potential confounding variables (p for trend &lt;0.001), with a mean difference in estimated glomerular filtration rate of −6 ml/min/1.73 m2 between those in the highest fifth of adherence to the unhealthy dietary pattern compared to the lowest, in the fully adjusted model. Chronic kidney disease risk was significantly greater for the highest fifth, compared to the lowest fifth of unhealthy dietary pattern adherence in adjusted models (adjusted odds ratio = 2.62, p &lt; 0.001). Adherence to the healthy dietary pattern was not associated with renal function or chronic kidney disease in adjusted models. In this cohort, an unhealthy dietary pattern was associated with lower renal function and greater prevalence of chronic kidney disease
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