9,959 research outputs found

    Early prediction of pathological response to neoadjuvant chemotherapy of breast tumors: a comparative study using amide proton transfer-weighted, diffusion weighted and dynamic contrast enhanced MRI

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    ObjectiveTo examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer.MaterialsIn this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups.ResultsAPT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax).ConclusionAPTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment

    Desmoid-type fibromatosis:Towards a personalised approach

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    Development and assessment of learning-based vessel biomarkers from CTA in ischemic stroke

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    Transcatheter Aortic Valve Implantation (TAVI) Planning with Dual-Layer Spectral CT Using Virtual Monoenergetic Image (VMI) Reconstructions and 20 mL of Contrast Media

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    Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical implantation and its implementation is progressively increasing worldwide. We routinely perform pre-procedural aortic angiography CT to assess aortic dimensions and vascular anatomy. This study aims to evaluate the image quality of CTA for TAVI planning using dual-layer spectral CT, with virtual monoenergetic image reconstructions at 40 keV. Thirty-one patients underwent a CTA protocol with the injection of 20 mL of contrast media. Image quality was assessed by measuring the mean density in Hounsfield Units (HU), the signal-to-noise ratio, and the contrast-to-noise ratio in VMI reconstructions. Additionally, a blinded subjective analysis was conducted by two observers. The results showed significant enhancement at all sampled vascular levels with a gradual decrease in HU from proximal to distal regions. Favourable subjective ratings were given for all parameters, with greater variability in the evaluation of iliac axes. A significant negative correlation (p < 0.05) was observed between BMI and CA at all vascular levels, indicating reduced contrast enhancement with increasing BMI. Spectral CT, along with reducing iodine load, allows for obtaining high-quality images without a significant increase in noise. The reduction in iodine load can have positive implications in clinical practice, improving patient safety and resource efficiency

    The Structure and Function of the Retina in Multiple Sclerosis

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    Background: Multiple sclerosis (MS) is a complex heterogenous autoimmune inflammatory disease with a prolonged and variable time course. The visual system is frequently implicated, either as the presenting symptom, or, with advancement of the disease. This has been documented in the literature with changes in visual acuity (VA) that are accompanied by functional changes in the optic nerve, measured with the visual evoked potential (VEP) and possible retrograde degeneration involving the retinal ganglion cells in the retina, measured with the pattern reversal electroretinogram (PERG). However, inflammatory episodes may be clinical or subclinical in nature and may go unrecognised. Originating from the same embryological origins, the effect of inflammation in MS on the on the retina is less well known. The research hypothesis was that there is a measurable difference in the function of retinal cells in patients with newly diagnosed multiple sclerosis, suggestive of inflammatory retinopathy compared to healthy controls. The overall aim was to investigate any differences in the electrophysiological function of the visual pathway of patients newly diagnosed with MS compared to healthy controls. Methods: The visual system is explored with clinical (VA), electrophysiology (VEP and electroretinography (ERG – pattern and flash) and structural (OCT) measures, in patients presenting with symptoms suggestive of MS to a specialist service. This prospective case control study investigates the visual pathway at the earliest stage of the disease to look for differences in structure and function between patients and healthy volunteers that might serve as a biomarker in the future. Results: There were a number of variables that were significantly different between the two groups, logistic regression analysis found that VA (p 0.038) and VEP P100 peak-time (p 0.014) from the right eye as significant. Dividing the participants by prolongation of the VEP P100 peak-time as defined in clinical practice, found a number of ERG amplitude variables as well as VA that were consistently different between the groups regardless of symptoms. Conclusion: The study confirms optic nerve involvement in MS with VEP and VA abnormalities consistent with the literature in this cohort. Additionally, VA and some ERG amplitude variables were significantly reduced in participants with MS, when grouped according to VEP P100 peak-time, suggesting inner and outer retinal changes. Further work would be required to confirm these findings. No OCT structural changes were found in any of the analysis that included the macula thickness, ganglion cell layer or retinal nerve fibre layer. Keywords: multiple sclerosis (MS), visual evoked potential (VEP), pattern electroretinogram (PERG), electroretinogram (ERG), optical coherence tomography (OCT

    Desmoid-type fibromatosis:Towards a personalised approach

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    Development and assessment of learning-based vessel biomarkers from CTA in ischemic stroke

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    Modern computing: Vision and challenges

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    Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress
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