scholarly journals CT Chest Severity Score for COVID 19 Pneumonia: A Quantitative Imaging Tool for Severity Assessment of Disease

2021 ◽  
Vol 31 (4) ◽  
pp. 388-392
Keyword(s):  
Severity Score ◽  
Quantitative Imaging ◽  
Severity Assessment ◽  
Imaging Tool

scholarly journals Quantitative imaging of intracellular nanoparticle exposure enables prediction of nanotherapeutic efficacy

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Qingqing Yin ◽  
Anni Pan ◽  
Binlong Chen ◽  
Zenghui Wang ◽  
Mingmei Tang ◽  
...  
Keyword(s):  
Quantitative Imaging ◽  
Tumour Mass ◽  
Nanoparticle Exposure ◽  
Imaging Tool ◽  
Intracellular Compartments ◽  
Signal Output ◽  
Extracellular Microenvironment ◽  
Intracellular Targets ◽  
Ph Variations ◽  
Therapeutic Responses

AbstractNanoparticle internalisation is crucial for the precise delivery of drug/genes to its intracellular targets. Conventional quantification strategies can provide the overall profiling of nanoparticle biodistribution, but fail to unambiguously differentiate the intracellularly bioavailable particles from those in tumour intravascular and extracellular microenvironment. Herein, we develop a binary ratiometric nanoreporter (BiRN) that can specifically convert subtle pH variations involved in the endocytic events into digitised signal output, enabling the accurately quantifying of cellular internalisation without introducing extracellular contributions. Using BiRN technology, we find only 10.7–28.2% of accumulated nanoparticles are internalised into intracellular compartments with high heterogeneity within and between different tumour types. We demonstrate the therapeutic responses of nanomedicines are successfully predicted based on intracellular nanoparticle exposure rather than the overall accumulation in tumour mass. This nonlinear optical nanotechnology offers a valuable imaging tool to evaluate the tumour targeting of new nanomedicines and stratify patients for personalised cancer therapy.

Quantitative Imaging Of the Green Fluorescent Proteins

1998 ◽  
Vol 4 (S2) ◽  
pp. 1004-1005
Author(s):  
David W. Piston ◽  
George H. Patterson ◽  
Susan M. Knobel
Keyword(s):  
Fluorescent Proteins ◽  
Protein Localization ◽  
Quantitative Imaging ◽  
Cloning And Expression ◽  
Green Fluorescent Proteins ◽  
Specific Gene ◽  
Full Potential ◽  
Imaging Tool ◽  
Naturally Occurring ◽  
Green Fluorescent

The cloning and expression of GFP in heterologous systems introduced a fantastic tool for studying specific gene expression and protein localization inside living cells. However, one aspect of GFP that has not been exploited to its full potential is its use as a quantitative imaging tool. To determine its quantitative usefulness, we have addressed five points that are important in GFP imaging: detectable signal over background, photostability, pH stability of the molecule, temperature dependence of chromophore formation, and estimation and normalization of GFP levels.To determine the quantitative limits of GFP in cells, several GFP versions (wtGFP, αGFP (F99S/M153T/V163A), S65T, EGFP (F64L/S65T), and a blue-shifted variant, EBFP (F64L/S65T/Y66H/Y145F)) were compared by imaging of GFP expressing cells or by spectroscopic measurements of purified proteins. When imaged, the GFP signals are contaminated by the naturally occurring background autofluorescence, but improved detection can be achieved for each green GFP by combination of confocal microscopy using 488 nm excitation, a rapid cut-on dichroic mirror, and a narrow bandpass emission filter (Figure l).

Comparison of the Poisoning Severity Score and National Poison Data System schemes for the severity assessment of animal poisonings: a pilot study

2017 ◽  
Vol 55 (7) ◽  
pp. 629-635
Author(s):  
Sarah E. McFarland ◽  
Alvin C. Bronstein ◽  
Shireen Banerji ◽  
Jane LeBlond ◽  
Reinhard H. Mischke ◽  
...  
Keyword(s):  
Pilot Study ◽  
Severity Score ◽  
Data System ◽  
Severity Assessment ◽  
National Poison ◽  
Poisoning Severity Score ◽  
National Poison Data System

scholarly journals Imaging and Electrophysiology for Degenerative Cervical Myelopathy [AO Spine RECODE DCM Research Priority Number 9]

2021 ◽  
pp. 219256822110574
Author(s):  
Allan R. Martin ◽  
Lindsay Tetreault ◽  
Benjamin M. Davies ◽  
Armin Curt ◽  
Patrick Freund ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Cervical Myelopathy ◽  
Tissue Injury ◽  
Quantitative Imaging ◽  
Cord Compression ◽  
Narrative Review ◽  
Imaging Tool ◽  
Spinal Cord Dysfunction ◽  
Degenerative Cervical Myelopathy ◽  
And Function

Study Design Narrative review. Objective The current review aimed to describe the role of existing techniques and emerging methods of imaging and electrophysiology for the management of degenerative cervical myelopathy (DCM), a common and often progressive condition that causes spinal cord dysfunction and significant morbidity globally. Methods A narrative review was conducted to summarize the existing literature and highlight future directions. Results Anatomical magnetic resonance imaging (MRI) is well established in the literature as the key imaging tool to identify spinal cord compression, disc herniation/bulging, and inbuckling of the ligamentum flavum, thus facilitating surgical planning, while radiographs and computed tomography (CT) provide complimentary information. Electrophysiology techniques are primarily used to rule out competing diagnoses. However, signal change and measures of cord compression on conventional MRI have limited utility to characterize the degree of tissue injury, which may be helpful for diagnosis, prognostication, and repeated assessments to identify deterioration. Early translational studies of quantitative imaging and electrophysiology techniques show potential of these methods to more accurately reflect changes in spinal cord microstructure and function. Conclusion Currently, clinical management of DCM relies heavily on anatomical MRI, with additional contributions from radiographs, CT, and electrophysiology. Novel quantitative assessments of microstructure, perfusion, and function have the potential to transform clinical practice, but require robust validation, automation, and standardization prior to uptake.

scholarly journals Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19

2020 ◽  
Vol 2 (2) ◽  
pp. e200047 ◽  
Author(s):  
Ran Yang ◽  
Xiang Li ◽  
Huan Liu ◽  
Yanling Zhen ◽  
Xianxiang Zhang ◽  
...  
Keyword(s):  
Severity Score ◽  
Chest Ct ◽  
Imaging Tool

scholarly journals Interobserver variability of injury severity assessment in polytrauma patients: does the anatomical region play a role?

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Eftychios Bolierakis ◽  
Sylvia Schick ◽  
Kai Sprengel ◽  
Kai Oliver Jensen ◽  
Frank Hildebrand ◽  
...  
Keyword(s):  
Injury Severity Score ◽  
Severity Score ◽  
Injury Severity ◽  
Interobserver Variability ◽  
Severity Assessment ◽  
Severely Injured ◽  
X Rays ◽  
Severely Injured Patients ◽  
Anatomical Region ◽  
Injured Patients

Abstract Background The Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS) are widely used to assess trauma patients. In this study, the interobserver variability of the injury severity assessment for severely injured patients was analyzed based on different injured anatomical regions, and the various demographic backgrounds of the observers. Methods A standardized questionnaire was presented to surgical experts and participants of clinical polytrauma courses. It contained medical information and initial X-rays/CT-scans of 10 cases of severely injured patients. Participants estimated the severity of each injury based on the AIS. Interobserver variability for the AIS, ISS, and New Injury Severity Score (NISS) was calculated by employing the statistical method of Krippendorff's α coefficient. Results Overall, 54 participants were included. The major contributing medical specialties were orthopedic trauma surgery (N = 36, 67%) and general surgery (N = 13, 24%). The measured interobserver variability in the assessment of the overall injury severity was high (α ISS: 0.33 / α NISS: 0.23). Moreover, there were differences in the interobserver variability of the maximum AIS (MAIS) depending on the anatomical region: αhead and neck: 0.06, αthorax: 0.45, αabdomen: 0.27 and αextremities: 0.55. Conclusions Interobserver agreement concerning injury severity assessment appears to be low among clinicians. We also noted marked differences in variability according to injury anatomy. The study shows that the assessment of injury severity is also highly variable between experts in the field. This implies the need for appropriate education to improve the accuracy of trauma evaluation in the respective trauma registries.

Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction

2019 ◽  
Vol 12 (7) ◽  
pp. 714-719 ◽  
Author(s):  
Mohammad Mahdi Shiraz Bhurwani ◽  
Muhammad Waqas ◽  
Alexander R Podgorsak ◽  
Kyle A Williams ◽  
Jason M Davies ◽  
...  
Keyword(s):  
Neural Networks ◽  
Network Performance ◽  
Deep Neural Networks ◽  
Characteristic Curve ◽  
Quantitative Imaging ◽  
Parametric Imaging ◽  
Post Intervention ◽  
Imaging Tool ◽  
Flow Parameters ◽  
Occlusion Prediction

BackgroundAngiographic parametric imaging (API), based on digital subtraction angiography (DSA), is a quantitative imaging tool that may be used to extract contrast flow parameters related to hemodynamic conditions in abnormal pathologies such as intracranial aneurysms (IAs).ObjectiveTo investigate the feasibility of using deep neural networks (DNNs) and API to predict IA occlusion using pre- and post-intervention DSAs.MethodsWe analyzed DSA images of IAs pre- and post-treatment to extract API parameters in the IA dome and the corresponding main artery (un-normalized data). We implemented a two-step correction to account for injection variability (normalized data) and projection foreshortening (relative data). A DNN was trained to predict a binary IA occlusion outcome: occluded/unoccluded. Network performance was assessed with area under the receiver operating characteristic curve (AUROC) and classification accuracy. To evaluate the effect of the proposed corrections, prediction accuracy analysis was performed after each normalization step.ResultsThe study included 190 IAs. The mean and median duration between treatment and follow-up was 9.8 and 8.0 months, respectively. For the un-normalized, normalized, and relative subgroups, the DNN average prediction accuracies for IA occlusion were 62.5% (95% CI 60.5% to 64.4%), 70.8% (95% CI 68.2% to 73.4%), and 77.9% (95% CI 76.2% to 79.6%). The average AUROCs for the same subgroups were 0.48 (0.44–0.52), 0.67 (0.61–0.73), and 0.77 (0.74–0.80).ConclusionsThe study demonstrated the feasibility of using API and DNNs to predict IA occlusion using only pre- and post-intervention angiographic information.

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