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1.
PLoS One ; 17(3): e0265691, 2022.
Article in English | MEDLINE | ID: covidwho-1770752

ABSTRACT

Automatic detection of some pulmonary abnormalities using chest X-rays may be impacted adversely due to obscuring by bony structures like the ribs and the clavicles. Automated bone suppression methods would increase soft tissue visibility and enhance automated disease detection. We evaluate this hypothesis using a custom ensemble of convolutional neural network models, which we call DeBoNet, that suppresses bones in frontal CXRs. First, we train and evaluate variants of U-Nets, Feature Pyramid Networks, and other proposed custom models using a private collection of CXR images and their bone-suppressed counterparts. The DeBoNet, constructed using the top-3 performing models, outperformed the individual models in terms of peak signal-to-noise ratio (PSNR) (36.7977±1.6207), multi-scale structural similarity index measure (MS-SSIM) (0.9848±0.0073), and other metrics. Next, the best-performing bone-suppression model is applied to CXR images that are pooled from several sources, showing no abnormality and other findings consistent with COVID-19. The impact of bone suppression is demonstrated by evaluating the gain in performance in detecting pulmonary abnormality consistent with COVID-19 disease. We observe that the model trained on bone-suppressed CXRs (MCC: 0.9645, 95% confidence interval (0.9510, 0.9780)) significantly outperformed (p < 0.05) the model trained on non-bone-suppressed images (MCC: 0.7961, 95% confidence interval (0.7667, 0.8255)) in detecting findings consistent with COVID-19 indicating benefits derived from automatic bone suppression on disease classification. The code is available at https://github.com/sivaramakrishnan-rajaraman/Bone-Suppresion-Ensemble.


Subject(s)
COVID-19/diagnostic imaging , Lung Diseases/diagnostic imaging , Neural Networks, Computer , Radiography, Thoracic/methods , Clavicle/diagnostic imaging , Humans , Ribs/diagnostic imaging , Signal-To-Noise Ratio
2.
Br J Radiol ; 95(1129): 20210835, 2022 Jan 01.
Article in English | MEDLINE | ID: covidwho-1575206

ABSTRACT

OBJECTIVE: To evaluate the efficacy of a barrier shield in reducing droplet transmission and its effect on image quality and radiation dose in an interventional suite. METHODS: A human cough droplet visualisation model in a supine position was developed to assess efficacy of barrier shield in reducing environmental contamination. Its effect on image quality (resolution and contrast) was evaluated via image quality test phantom. Changes in the radiation dose to patient post-shield utilisation was measured. RESULTS: Use of the shield prevented escape of visible fluorescent cough droplets from the containment area. No subjective change in line-pair resolution was observed. No significant difference in contrast-to-noise ratio was measured. Radiation dosage to patient was increased; this is predominantly attributed to the increased air gap and not the physical properties of the shield. CONCLUSION: Use of the barrier shield provided an effective added layer of personal protection in the interventional radiology theatre for aerosol generating procedures. ADVANCES IN KNOWLEDGE: This is the first time a human supine cough droplet visualisation has been developed. While multiple types of barrier shields have been described, this is the first systematic practical evaluation of a barrier shield designed for use in the interventional radiology theatre.


Subject(s)
Infectious Disease Transmission, Patient-to-Professional/prevention & control , Protective Devices , Radiology, Interventional/instrumentation , Adult , COVID-19/transmission , Cough , Equipment Design , Fluorescence , Humans , Male , Phantoms, Imaging , Radiation Dosage , Signal-To-Noise Ratio , Supine Position
3.
BMC Med Imaging ; 21(1): 192, 2021 12 13.
Article in English | MEDLINE | ID: covidwho-1571744

ABSTRACT

AIM: This study is to compare the lung image quality between shelter hospital CT (CT Ark) and ordinary CT scans (Brilliance 64) scans. METHODS: The patients who received scans with CT Ark or Brilliance 64 CT were enrolled. Their lung images were divided into two groups according to the scanner. The objective evaluation methods of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used. The subjective evaluation methods including the evaluation of the fine structure under the lung window and the evaluation of the general structure under the mediastinum window were compared. Kappa method was used to assess the reliability of the subjective evaluation. The subjective evaluation results were analyzed using the Wilcoxon rank sum test. SNR and CNR were tested using independent sample t tests. RESULTS: There was no statistical difference in somatotype of enrolled subjects. The Kappa value between the two observers was between 0.68 and 0.81, indicating good consistency. For subjective evaluation results, the rank sum test P value of fine structure evaluation and general structure evaluation by the two observers was ≥ 0.05. For objective evaluation results, SNR and CNR between the two CT scanners were significantly different (P<0.05). Notably, the absolute values ​​of SNR and CNR of the CT Ark were larger than Brilliance 64 CT scanner. CONCLUSION: CT Ark is fully capable of scanning the lungs of the COVID-19 patients during the epidemic in the shelter hospital.


Subject(s)
COVID-19/diagnostic imaging , Lung/diagnostic imaging , Mobile Health Units/standards , Tomography, X-Ray Computed/instrumentation , Tomography, X-Ray Computed/standards , Adult , Aged , COVID-19/epidemiology , China/epidemiology , Female , Humans , Male , Middle Aged , Observer Variation , Pandemics , SARS-CoV-2 , Signal-To-Noise Ratio
4.
Sensors (Basel) ; 21(21)2021 Oct 30.
Article in English | MEDLINE | ID: covidwho-1512566

ABSTRACT

The signal quality limits the applicability of phonocardiography at the patients' domicile. This work proposes the signal-to-noise ratio of the recorded signal as its main quality metrics. Moreover, we define the minimum acceptable values of the signal-to-noise ratio that warrantee an accuracy of the derived parameters acceptable in clinics. We considered 25 original heart sounds recordings, which we corrupted by adding noise to decrease their signal-to-noise ratio. We found that a signal-to-noise ratio equal to or higher than 14 dB warrants an uncertainty of the estimate of the valve closure latencies below 1 ms. This accuracy is higher than that required by most clinical applications. We validated the proposed method against a public database, obtaining results comparable to those obtained on our sample population. In conclusion, we defined (a) the signal-to-noise ratio of the phonocardiographic signal as the preferred metric to evaluate its quality and (b) the minimum values of the signal-to-noise ratio required to obtain an uncertainty of the latency of heart sound components compatible with clinical applications. We believe these results are crucial for the development of home monitoring systems aimed at preventing acute episodes of heart failure and that can be safely operated by naïve users.


Subject(s)
Heart Sounds , Signal Processing, Computer-Assisted , Algorithms , Humans , Phonocardiography , Signal-To-Noise Ratio
5.
Comput Math Methods Med ; 2021: 5208940, 2021.
Article in English | MEDLINE | ID: covidwho-1495711

ABSTRACT

The coronavirus disease 2019 (COVID-19) is a substantial threat to people's lives and health due to its high infectivity and rapid spread. Computed tomography (CT) scan is one of the important auxiliary methods for the clinical diagnosis of COVID-19. However, CT image lesion edge is normally affected by pixels with uneven grayscale and isolated noise, which makes weak edge detection of the COVID-19 lesion more complicated. In order to solve this problem, an edge detection method is proposed, which combines the histogram equalization and the improved Canny algorithm. Specifically, the histogram equalization is applied to enhance image contrast. In the improved Canny algorithm, the median filter, instead of the Gaussian filter, is used to remove the isolated noise points. The K-means algorithm is applied to separate the image background and edge. And the Canny algorithm is improved continuously by combining the mathematical morphology and the maximum between class variance method (OTSU). On selecting four types of lesion images from COVID-CT date set, MSE, MAE, SNR, and the running time are applied to evaluate the performance of the proposed method. The average values of these evaluation indicators are 1.7322, 7.9010, 57.1241, and 5.4887, respectively. Compared with other three methods, these values indicate that the proposed method achieves better result. The experimental results prove that the proposed algorithm can effectively detect the weak edge of the lesion, which is helpful for the diagnosis of COVID-19.


Subject(s)
COVID-19/diagnosis , Image Processing, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Algorithms , Female , Humans , Lung/diagnostic imaging , Male , Models, Theoretical , Normal Distribution , Reproducibility of Results , Signal-To-Noise Ratio
6.
Sensors (Basel) ; 21(19)2021 Sep 28.
Article in English | MEDLINE | ID: covidwho-1463796

ABSTRACT

The technique of active ionospheric sounding by ionosondes requires sophisticated methods for the recovery of experimental data on ionograms. In this work, we applied an advanced algorithm of deep learning for the identification and classification of signals from different ionospheric layers. We collected a dataset of 6131 manually labeled ionograms acquired from low-latitude ionosondes in Taiwan. In the ionograms, we distinguished 11 different classes of the signals according to their ionospheric layers. We developed an artificial neural network, FC-DenseNet24, based on the FC-DenseNet convolutional neural network. We also developed a double-filtering algorithm to reduce incorrectly classified signals. That made it possible to successfully recover the sporadic E layer and the F2 layer from highly noise-contaminated ionograms whose mean signal-to-noise ratio was low, SNR = 1.43. The Intersection over Union (IoU) of the recovery of these two signal classes was greater than 0.6, which was higher than the previous models reported. We also identified three factors that can lower the recovery accuracy: (1) smaller statistics of samples; (2) mixing and overlapping of different signals; (3) the compact shape of signals.


Subject(s)
Algorithms , Neural Networks, Computer , Signal-To-Noise Ratio , Taiwan
7.
Sci Rep ; 11(1): 18444, 2021 09 16.
Article in English | MEDLINE | ID: covidwho-1415956

ABSTRACT

Over the past year, the world's attention has focused on combating COVID-19 disease, but the other threat waiting at the door-antimicrobial resistance should not be forgotten. Although making the diagnosis rapidly and accurately is crucial in preventing antibiotic resistance development, bacterial identification techniques include some challenging processes. To address this challenge, we proposed a deep neural network (DNN) that can discriminate antibiotic-resistant bacteria using surface-enhanced Raman spectroscopy (SERS). Stacked autoencoder (SAE)-based DNN was used for the rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive S. aureus (MSSA) bacteria using a label-free SERS technique. The performance of the DNN was compared with traditional classifiers. Since the SERS technique provides high signal-to-noise ratio (SNR) data, some subtle differences were found between MRSA and MSSA in relative band intensities. SAE-based DNN can learn features from raw data and classify them with an accuracy of 97.66%. Moreover, the model discriminates bacteria with an area under curve (AUC) of 0.99. Compared to traditional classifiers, SAE-based DNN was found superior in accuracy and AUC values. The obtained results are also supported by statistical analysis. These results demonstrate that deep learning has great potential to characterize and detect antibiotic-resistant bacteria by using SERS spectral data.


Subject(s)
Methicillin Resistance , Staphylococcus aureus/classification , Staphylococcus aureus/growth & development , Deep Learning , Discriminant Analysis , Humans , Metal Nanoparticles/chemistry , Microbial Sensitivity Tests , Neural Networks, Computer , Signal-To-Noise Ratio , Silver/chemistry , Spectrum Analysis, Raman , Staphylococcus aureus/drug effects , Support Vector Machine
8.
Opt Express ; 29(16): 25745-25761, 2021 Aug 02.
Article in English | MEDLINE | ID: covidwho-1363582

ABSTRACT

In spite of tremendous advancements in modern diagnostics, there is a dire need for reliable, label-free detection of highly contagious pathogens like viruses. In view of the limitations of existing diagnostic techniques, the present theoretical study proposes a novel scheme of detecting virus-like particles employing whispering gallery and quasi-whispering gallery resonant modes of a composite optical system. Whereas whispering gallery mode (WGM) resonators are conventionally realized using micro-disk, -ring, -toroid or spherical structures, the present study utilizes a rotationally symmetric array of silicon nanowires which offers higher sensitivity compared to the conventional WGM resonator while detecting virus-like particles. Notwithstanding the relatively low quality factor of the system, the underlying multiple-scattering mediated photon entrapment, coupled with peripheral total-internal reflection, results in high fidelity of the system against low signal-to-noise ratio. Finite difference time domain based numerical analysis has been performed to correlate resonant modes of the array with spatial location of the virus. The correlation has been subsequently utilized for statistical analysis of simulated test cases. Assuming detection to be limited by resolution of the measurement system, results of the analysis suggest that for only about 5% of the simulate test cases the resonant wavelength shift lies within the minimum detection range of 0.001-0.01 nm. For a single virus of 160 nm diameter, more than 8 nm shift of the resonant mode and nearly 100% change of quality factor are attained with the proposed nanowire array based photonic structure.


Subject(s)
Models, Theoretical , Nanowires , Optical Devices , Silicon , Virion/isolation & purification , Optics and Photonics/methods , Signal-To-Noise Ratio , Virion/ultrastructure
9.
PLoS One ; 16(7): e0253874, 2021.
Article in English | MEDLINE | ID: covidwho-1291513

ABSTRACT

Daily-life conversation relies on speech perception in quiet and noise. Because of the COVID-19 pandemic, face masks have become mandatory in many situations. Acoustic attenuation of sound pressure by the mask tissue reduces speech perception ability, especially in noisy situations. Masks also can impede the process of speech comprehension by concealing the movements of the mouth, interfering with lip reading. In this prospective observational, cross-sectional study including 17 participants with normal hearing, we measured the influence of acoustic attenuation caused by medical face masks (mouth and nose protection) according to EN 14683 and of N95 masks according to EN 1149 (EN 14683) on the speech recognition threshold and listening effort in various types of background noise. Averaged over all noise signals, a surgical mask significantly reduced the speech perception threshold in noise was by 1.6 dB (95% confidence interval [CI], 1.0, 2.1) and an N95 mask reduced it significantly by 2.7 dB (95% CI, 2.2, 3.2). Use of a surgical mask did not significantly increase the 50% listening effort signal-to-noise ratio (increase of 0.58 dB; 95% CI, 0.4, 1.5), but use of an N95 mask did so significantly, by 2.2 dB (95% CI, 1.2, 3.1). In acoustic measures, mask tissue reduced amplitudes by up to 8 dB at frequencies above 1 kHz, whereas no reduction was observed below 1 kHz. We conclude that face masks reduce speech perception and increase listening effort in different noise signals. Together with additional interference because of impeded lip reading, the compound effect of face masks could have a relevant impact on daily life communication even in those with normal hearing.


Subject(s)
N95 Respirators , Speech Perception , Adult , Auditory Perception , COVID-19/prevention & control , Communication , Cross-Sectional Studies , Female , Hearing , Humans , Male , Noise , Signal-To-Noise Ratio , Young Adult
10.
PLoS One ; 16(6): e0252599, 2021.
Article in English | MEDLINE | ID: covidwho-1285199

ABSTRACT

Inflammation has an important role in the progression of various viral pneumonia, including COVID-19. Circulating biomarkers that can evaluate inflammation and immune status are potentially useful in diagnosing and prognosis of COVID-19 patients. Even more so when they are a part of the routine evaluation, chest CT could have even higher diagnostic accuracy than RT-PCT alone in a suggestive clinical context. This study aims to evaluate the correlation between inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocytes ratio (PLR), and eosinophils with the severity of CT lesions in patients with COVID-19. The second objective was to seek a statically significant cut-off value for NLR and PLR that could suggest COVID-19. Correlation of both NLR and PLR with already established inflammatory markers such as CRP, ESR, and those specific for COVID-19 (ferritin, D-dimers, and eosinophils) were also evaluated. One hundred forty-nine patients with confirmed COVID-19 disease and 149 age-matched control were evaluated through blood tests, and COVID-19 patients had thorax CT performed. Both NLR and PLR correlated positive chest CT scan severity. Both NLR and PLR correlated positive chest CT scan severity. When NLR value is below 5.04, CT score is lower than 3 with a probability of 94%, while when NLR is higher than 5.04, the probability of severe CT changes is only 50%. For eosinophils, a value of 0.35% corresponds to chest CT severity of 2 (Se = 0.88, Sp = 0.43, AUC = 0.661, 95% CI (0.544; 0.779), p = 0.021. NLR and PLR had significantly higher values in COVID-19 patients. In our study a NLR = 2.90 and PLR = 186 have a good specificity (0.89, p = 0.001, respectively 0.92, p<0.001). Higher levels in NLR, PLR should prompt the clinician to prescribe a thorax CT as it could reveal important lesions that could influence the patient's future management.


Subject(s)
Blood Platelets/cytology , COVID-19/diagnostic imaging , COVID-19/immunology , Eosinophils/cytology , Neutrophils/cytology , Signal-To-Noise Ratio , Tomography, X-Ray Computed , Adult , COVID-19/pathology , Female , Humans , Lymphocyte Count , Male , Middle Aged
11.
J Biol Dyn ; 15(1): 195-212, 2021 12.
Article in English | MEDLINE | ID: covidwho-1172612

ABSTRACT

Incidence vs. Cumulative Cases (ICC) curves are introduced and shown to provide a simple framework for parameter identification in the case of the most elementary epidemiological model, consisting of susceptible, infected, and removed compartments. This novel methodology is used to estimate the basic reproduction ratio of recent outbreaks, including those associated with the ongoing COVID-19 pandemic.


Subject(s)
COVID-19/epidemiology , Pandemics/statistics & numerical data , SARS-CoV-2 , Basic Reproduction Number/statistics & numerical data , COVID-19/transmission , China/epidemiology , Computer Simulation , Disease Susceptibility , Gastroenteritis/epidemiology , Humans , Incidence , Mathematical Concepts , Models, Biological , Models, Statistical , Nonlinear Dynamics , Poisson Distribution , Signal-To-Noise Ratio , Spain/epidemiology
12.
PET Clin ; 16(1): 89-97, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-938149

ABSTRACT

Total-body PET enables high-sensitivity imaging with dramatically improved signal-to-noise ratio. These enhanced performance characteristics allow for decreased PET scanning times acquiring data "total-body wide" and can be leveraged to decrease the amount of radiotracer required, thereby permitting more frequent imaging or longer imaging periods during radiotracer decay. Novel approaches to PET imaging of infectious diseases are emerging, including those that directly visualize pathogens in vivo and characterize concomitant immune responses and inflammation. Efforts to develop these imaging approaches are hampered by challenges of traditional imaging platforms, which may be overcome by novel total-body PET strategies.


Subject(s)
Communicable Diseases/diagnostic imaging , Positron-Emission Tomography/methods , Whole Body Imaging/methods , Humans , Signal-To-Noise Ratio , Time
13.
Minerva Cardiol Angiol ; 69(5): 606-618, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1128288

ABSTRACT

During the pandemic context, diagnostic algorithms had to be adapted considering the decimated medical personnel, local technical resources, and the likelihood of contamination. Given the higher probability of thrombotic complications related to COVID-19 and the availability of a dual-layer spectral computed tomography (CT) scanner, we have recently adopted the use of low-dose, non-gated, chest CT scans performed five minutes after contrast administration among patients admitted with acute ischemic stroke (AIS) undergoing cerebrovascular CT angiography. Dual-layer spectral CT comprises a single X-ray source and two-layer detector with different photon-absorption capabilities. In addition to conventional images, the two distinct energy datasets obtained enable multiparametric spectral analysis without need to change the original scanning protocol. The two spectral features that emerge as most useful for patients with AIS are virtual monoenergetic imaging and iodine-based results. Aside from the evaluation of lung parenchyma, this novel strategy enables ruling out cardioembolic sources and simultaneously providing evidence of pulmonary and myocardial injury in a single session and immediately after CT cerebrovascular angiography. Furthermore, it involves a non-invasive, seemingly accurate, unsophisticated, safer (very low radiation dose and no contrast administration), and cheaper tool for ruling out cardioembolic sources compared to transesophageal echocardiogram and cardiac CT. Accordingly, we sought to standardize the technical aspects and overview the usefulness of delayed-phase, low-dose chest spectral CT in patients admitted with AIS.


Subject(s)
Brain Ischemia , COVID-19 , Ischemic Stroke , Stroke , Brain Ischemia/diagnostic imaging , Humans , SARS-CoV-2 , Signal-To-Noise Ratio , Stroke/complications , Tomography, X-Ray Computed
14.
J Nucl Med Technol ; 49(1): 2-6, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1117149

ABSTRACT

The current pandemic has created a situation where nuclear medicine practitioners and medical physicists read or process nuclear medicine images remotely from their home office. This article presents recommendations on the components and specifications when setting up a remote viewing station for nuclear medicine imaging.


Subject(s)
COVID-19/epidemiology , Molecular Imaging/instrumentation , Nuclear Medicine/instrumentation , Practice Guidelines as Topic , Computer Security , Computers , Humans , Internet , Pandemics , Signal-To-Noise Ratio
15.
Sci Rep ; 11(1): 4290, 2021 02 22.
Article in English | MEDLINE | ID: covidwho-1096333

ABSTRACT

Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N = 80 samples from persons with RT-PCR confirmed SARS-CoV-2 infection), and a specificity of 97.2% (N = 106 control samples).


Subject(s)
COVID-19/diagnosis , COVID-19/immunology , Enzyme-Linked Immunosorbent Assay/methods , Epitopes, B-Lymphocyte/immunology , SARS-CoV-2/pathogenicity , Humans , Real-Time Polymerase Chain Reaction , SARS-CoV-2/immunology , Signal-To-Noise Ratio
16.
Biosens Bioelectron ; 178: 113049, 2021 Apr 15.
Article in English | MEDLINE | ID: covidwho-1056383

ABSTRACT

Prompt diagnosis, patient isolation, and contact tracing are key measures to contain the coronavirus disease 2019 (COVID-19). Molecular tests are the current gold standard for COVID-19 detection, but are carried out at central laboratories, delaying treatment and control decisions. Here we describe a portable assay system for rapid, onsite COVID-19 diagnosis. Termed CODA (CRISPR Optical Detection of Anisotropy), the method combined isothermal nucleic acid amplification, activation of CRISPR/Cas12a, and signal generation in a single assay, eliminating extra manual steps. Importantly, signal detection was based on the ratiometric measurement of fluorescent anisotropy, which allowed CODA to achieve a high signal-to-noise ratio. For point-of-care operation, we built a compact, standalone CODA device integrating optoelectronics, an embedded heater, and a microcontroller for data processing. The developed system completed SARS-CoV-2 RNA detection within 20 min of sample loading; the limit of detection reached 3 copy/µL. When applied to clinical samples (10 confirmed COVID-19 patients; 10 controls), the rapid CODA test accurately classified COVID-19 status, in concordance with gold-standard clinical diagnostics.


Subject(s)
Biosensing Techniques/methods , COVID-19 Nucleic Acid Testing/methods , COVID-19/diagnosis , Fluorescence Polarization/methods , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Biosensing Techniques/instrumentation , Biosensing Techniques/statistics & numerical data , COVID-19/virology , COVID-19 Nucleic Acid Testing/instrumentation , COVID-19 Nucleic Acid Testing/statistics & numerical data , CRISPR-Cas Systems , Equipment Design , Fluorescence Polarization/instrumentation , Fluorescence Polarization/statistics & numerical data , Humans , Molecular Diagnostic Techniques/instrumentation , Molecular Diagnostic Techniques/methods , Molecular Diagnostic Techniques/statistics & numerical data , Nucleic Acid Amplification Techniques/instrumentation , Nucleic Acid Amplification Techniques/methods , Nucleic Acid Amplification Techniques/statistics & numerical data , Pandemics , Point-of-Care Systems/statistics & numerical data , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio
17.
Anal Chem ; 93(5): 2950-2958, 2021 02 09.
Article in English | MEDLINE | ID: covidwho-1041144

ABSTRACT

There is an urgent need for ultrarapid testing regimens to detect the severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infections in real-time within seconds to stop its spread. Current testing approaches for this RNA virus focus primarily on diagnosis by RT-qPCR, which is time-consuming, costly, often inaccurate, and impractical for general population rollout due to the need for laboratory processing. The latency until the test result arrives with the patient has led to further virus spread. Furthermore, latest antigen rapid tests still require 15-30 min processing time and are challenging to handle. Despite increased polymerase chain reaction (PCR)-test and antigen-test efforts, the pandemic continues to evolve worldwide. Herein, we developed a superfast, reagent-free, and nondestructive approach of attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy with subsequent chemometric analysis toward the prescreening of virus-infected samples. Contrived saliva samples spiked with inactivated γ-irradiated COVID-19 virus particles at levels down to 1582 copies/mL generated infrared (IR) spectra with a good signal-to-noise ratio. Predominant virus spectral peaks are tentatively associated with nucleic acid bands, including RNA. At low copy numbers, the presence of a virus particle was found to be capable of modifying the IR spectral signature of saliva, again with discriminating wavenumbers primarily associated with RNA. Discrimination was also achievable following ATR-FTIR spectral analysis of swabs immersed in saliva variously spiked with virus. Next, we nested our test system in a clinical setting wherein participants were recruited to provide demographic details, symptoms, parallel RT-qPCR testing, and the acquisition of pharyngeal swabs for ATR-FTIR spectral analysis. Initial categorization of swab samples into negative versus positive COVID-19 infection was based on symptoms and PCR results (n = 111 negatives and 70 positives). Following training and validation (using n = 61 negatives and 20 positives) of a genetic algorithm-linear discriminant analysis (GA-LDA) algorithm, a blind sensitivity of 95% and specificity of 89% was achieved. This prompt approach generates results within 2 min and is applicable in areas with increased people traffic that require sudden test results such as airports, events, or gate controls.


Subject(s)
Algorithms , COVID-19/diagnosis , SARS-CoV-2/physiology , Spectroscopy, Fourier Transform Infrared/methods , Virion/chemistry , COVID-19/virology , Discriminant Analysis , Gamma Rays , Humans , Point-of-Care Testing , Principal Component Analysis , SARS-CoV-2/isolation & purification , Saliva/virology , Sensitivity and Specificity , Signal-To-Noise Ratio , Virion/radiation effects , Virus Inactivation
18.
IEEE Trans Ultrason Ferroelectr Freq Control ; 68(4): 1296-1304, 2021 04.
Article in English | MEDLINE | ID: covidwho-998673

ABSTRACT

During the COVID-19 pandemic, an ultraportable ultrasound smart probe has proven to be one of the few practical diagnostic and monitoring tools for doctors who are fully covered with personal protective equipment. The real-time, safety, ease of sanitization, and ultraportability features of an ultrasound smart probe make it extremely suitable for diagnosing COVID-19. In this article, we discuss the implementation of a smart probe designed according to the classic architecture of ultrasound scanners. The design balanced both performance and power consumption. This programmable platform for an ultrasound smart probe supports a 64-channel full digital beamformer. The platform's size is smaller than 10 cm ×5 cm. It achieves a 60-dBFS signal-to-noise ratio (SNR) and an average power consumption of ~4 W with 80% power efficiency. The platform is capable of achieving triplex B-mode, M-mode, color, pulsed-wave Doppler mode imaging in real time. The hardware design files are available for researchers and engineers for further study, improvement or rapid commercialization of ultrasound smart probes to fight COVID-19.


Subject(s)
Signal Processing, Computer-Assisted/instrumentation , Transducers , Ultrasonography/instrumentation , COVID-19/diagnostic imaging , Equipment Design , Humans , Image Interpretation, Computer-Assisted , Lung/diagnostic imaging , Pandemics , Phantoms, Imaging , SARS-CoV-2 , Signal-To-Noise Ratio , Ultrasonography/methods
19.
Ear Hear ; 42(1): 20-28, 2020 12 22.
Article in English | MEDLINE | ID: covidwho-998492

ABSTRACT

OBJECTIVES: The impact of social distancing on communication and psychosocial variables among individuals with hearing impairment during COVID-19 pandemic. It was our concern that patients who already found themselves socially isolated (Wie et al. 2010) as a result of their hearing loss would be perhaps more susceptible to changes in their communication habits resulting in further social isolation, anxiety, and depression. We wanted to better understand how forced social isolation (as part of COVID-19 mitigation) effected a group of individuals with hearing impairment from an auditory ecology and psychosocial perspective. We hypothesized that the listening environments would be different as a result of social isolation when comparing subject's responses regarding activities and participation before COVID-19 and during the COVID-19 pandemic. This change would lead to an increase in experienced and perceived social isolation, anxiety, and depression. DESIGN: A total of 48 adults with at least 12 months of cochlear implant (CI) experience reported their listening contexts and experiences pre-COVID and during-COVID using Ecological Momentary Assessment (EMA; methodology collecting a respondent's self-reports in their natural environments) through a smartphone-based app, and six paper and pencil questionnaires. The Smartphone app and paper-pencil questionnaires address topics related to their listening environment, social isolation, depression, anxiety, lifestyle and demand, loneliness, and satisfaction with amplification. Data from these two-time points were compared to better understand the effects of social distancing on the CI recipients' communication abilities. RESULTS: EMA demonstrated that during-COVID CI recipients were more likely to stay home or be outdoors. CI recipients reported that they were less likely to stay indoors outside of their home relative to the pre-COVID condition. Social distancing also had a significant effect on the overall signal-to-noise ratio of the environments indicating that the listening environments had better signal-to-noise ratios. CI recipients also reported better speech understanding, less listening effort, less activity limitation due to hearing loss, less social isolation due to hearing loss, and less anxiety due to hearing loss. Retrospective questionnaires indicated that social distancing had a significant effect on the social network size, participant's personal image of themselves, and overall loneliness. CONCLUSIONS: Overall, EMA provided us with a glimpse of the effect that forced social isolation has had on the listening environments and psychosocial perspectives of a select number of CI listeners. CI participants in this study reported that they were spending more time at home in a quieter environments during-COVID. Contrary to our hypothesis, CI recipients overall felt less socially isolated and reported less anxiety resulting from their hearing difficulties during-COVID in comparison to pre-COVID. This, perhaps, implies that having a more controlled environment with fewer speakers provided a more relaxing listening experience.


Subject(s)
COVID-19/prevention & control , Cochlear Implantation , Hearing Loss/psychology , Physical Distancing , Psychosocial Functioning , Signal-To-Noise Ratio , Speech Perception , Adult , Aged , Anxiety/psychology , Cochlear Implants , Deafness/physiopathology , Deafness/psychology , Deafness/rehabilitation , Depression/psychology , Ecological Momentary Assessment , Environment , Female , Hearing Aids , Hearing Loss/physiopathology , Hearing Loss/rehabilitation , Hearing Loss, Bilateral/physiopathology , Hearing Loss, Bilateral/psychology , Hearing Loss, Bilateral/rehabilitation , Hearing Loss, Unilateral/physiopathology , Hearing Loss, Unilateral/psychology , Hearing Loss, Unilateral/rehabilitation , Humans , Male , Middle Aged , Noise , SARS-CoV-2 , Social Isolation/psychology
20.
Sci Rep ; 10(1): 19196, 2020 11 05.
Article in English | MEDLINE | ID: covidwho-912912

ABSTRACT

Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT. For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University were retrospectively collected. Twenty-seven prospective consecutive patients in Renmin Hospital of Wuhan University were collected to evaluate the efficiency of radiologists against 2019-CoV pneumonia with that of the model. An external test was conducted in Qianjiang Central Hospital to estimate the system's robustness. The model achieved a per-patient accuracy of 95.24% and a per-image accuracy of 98.85% in internal retrospective dataset. For 27 internal prospective patients, the system achieved a comparable performance to that of expert radiologist. In external dataset, it achieved an accuracy of 96%. With the assistance of the model, the reading time of radiologists was greatly decreased by 65%. The deep learning model showed a comparable performance with expert radiologist, and greatly improved the efficiency of radiologists in clinical practice.


Subject(s)
Coronavirus Infections/complications , Deep Learning , Image Processing, Computer-Assisted/methods , Pneumonia, Viral/complications , Pneumonia/complications , Pneumonia/diagnostic imaging , Signal-To-Noise Ratio , Tomography, X-Ray Computed , Adult , COVID-19 , Female , Humans , Male , Middle Aged , Pandemics , Retrospective Studies
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