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Current Protocols in Cytometry Mar 2020In light microscopy, illuminating light is passed through the sample as uniformly as possible over the field of view. For thicker samples, where the objective lens does...
In light microscopy, illuminating light is passed through the sample as uniformly as possible over the field of view. For thicker samples, where the objective lens does not have sufficient depth of focus, light from sample planes above and below the focal plane will also be detected. The out-of-focus light will add blur to the image, reducing the resolution. In fluorescence microscopy, any dye molecules in the field of view will be stimulated, including those in out-of-focus planes. Confocal microscopy provides a means of rejecting the out-of-focus light from the detector such that it does not contribute blur to the images being collected. This technique allows for high-resolution imaging in thick tissues. In a confocal microscope, the illumination and detection optics are focused on the same diffraction-limited spot in the sample, which is the only spot imaged by the detector during a confocal scan. To generate a complete image, the spot must be moved over the sample and data collected point by point. A significant advantage of the confocal microscope is the optical sectioning provided, which allows for 3D reconstruction of a sample from high-resolution stacks of images. Several types of confocal microscopes have been developed for this purpose, and each has different advantages and disadvantages. This article provides a concise introduction to confocal microscopy. © 2019 by John Wiley & Sons, Inc.
Topics: Animals; Drosophila; HeLa Cells; Humans; Larva; Microscopy, Confocal; Microtubules; Sample Size; Time Factors
PubMed: 31876974
DOI: 10.1002/cpcy.68 -
Journal of the American College of... Dec 2018This JACC Scientific Expert Panel provides consensus recommendations for an update of the cardiovascular magnetic resonance (CMR) diagnostic criteria for myocardial... (Review)
Review
This JACC Scientific Expert Panel provides consensus recommendations for an update of the cardiovascular magnetic resonance (CMR) diagnostic criteria for myocardial inflammation in patients with suspected acute or active myocardial inflammation (Lake Louise Criteria) that include options to use parametric mapping techniques. While each parameter may indicate myocardial inflammation, the authors propose that CMR provides strong evidence for myocardial inflammation, with increasing specificity, if the CMR scan demonstrates the combination of myocardial edema with other CMR markers of inflammatory myocardial injury. This is based on at least one T2-based criterion (global or regional increase of myocardial T2 relaxation time or an increased signal intensity in T2-weighted CMR images), with at least one T1-based criterion (increased myocardial T1, extracellular volume, or late gadolinium enhancement). While having both a positive T2-based marker and a T1-based marker will increase specificity for diagnosing acute myocardial inflammation, having only one (i.e., T2-based OR T1-based) marker may still support a diagnosis of acute myocardial inflammation in an appropriate clinical scenario, albeit with less specificity. The update is expected to improve the diagnostic accuracy of CMR further in detecting myocardial inflammation.
Topics: Cardiac Imaging Techniques; Humans; Magnetic Resonance Imaging; Myocarditis; Patient Selection
PubMed: 30545455
DOI: 10.1016/j.jacc.2018.09.072 -
Indian Journal of Dental Research :... 2017The effectiveness of ProTaper Universal and ProTaper Retreatment rotary instruments was compared to the Hedström files in the removal of filling material from root...
INTRODUCTION
The effectiveness of ProTaper Universal and ProTaper Retreatment rotary instruments was compared to the Hedström files in the removal of filling material from root canals.
MATERIALS AND METHODS
Thirty-six extracted human mandibular premolars with a single straight root canal were shaped and filled with gutta-percha and AH Plus. The specimens were stored for 6 months at 37°C and at 100% relative humidity, and then randomly divided into three groups: PTU - removal of filling material performed with ProTaper Universal instruments; PTR - removal of filling material performed with ProTaper Retreatment instruments; HF - removal of filling material performed with Gates-Glidden burs, Hedström files and solvent. After the filling material removal and diaphanization, the specimens were longitudinally sectioned and images of the canal surfaces were scanned. The remaining areas of filling material were measured (Image Tool 3.0), and data was analyzed statistically (Kruskal-Wallis and Dunn tests). The time required for filling removal in each group was also recorded (one-way ANOVA and Tukey's HSD test).
RESULTS
All groups presented remnants of filling material; PTU had the smallest amount and HF group presented the highest mean value (P< 0.05) in all the thirds. The cervical third had the smallest amount of material when compared with the other thirds (P< 0.05). HF group required a longer mean time, presenting significant difference (P< 0.05).
CONCLUSION
Considering the time required and the amount of the filling removal, ProTaper Retreatment were not superior to ProTaper Universal, but both rotary instruments were more effective and less time-consuming than Hedström manual files.
Topics: Bicuspid; Humans; In Vitro Techniques; Random Allocation; Retreatment; Root Canal Filling Materials; Root Canal Preparation; Treatment Outcome
PubMed: 28836531
DOI: 10.4103/ijdr.IJDR_89_16 -
Zeitschrift Fur Medizinische Physik Aug 2023Ultrasound Localization Microscopy (ULM) is an emerging technique that provides impressive super-resolved images of microvasculature, i.e., images with much better... (Review)
Review
Ultrasound Localization Microscopy (ULM) is an emerging technique that provides impressive super-resolved images of microvasculature, i.e., images with much better resolution than the conventional diffraction-limited ultrasound techniques and is already taking its first steps from preclinical to clinical applications. In comparison to the established perfusion or flow measurement methods, namely contrast-enhanced ultrasound (CEUS) and Doppler techniques, ULM allows imaging and flow measurements even down to the capillary level. As ULM can be realized as a post-processing method, conventional ultrasound systems can be used for. ULM relies on the localization of single microbubbles (MB) of commercial, clinically approved contrast agents. In general, these very small and strong scatterers with typical radii of 1-3 µm are imaged much larger in ultrasound images than they actually are due to the point spread function of the imaging system. However, by applying appropriate methods, these MBs can be localized with sub-pixel precision. Then, by tracking MBs over successive frames of image sequences, not only the morphology of vascular trees but also functional information such as flow velocities or directions can be obtained and visualized. In addition, quantitative parameters can be derived to describe pathological and physiological changes in the microvasculature. In this review, the general concept of ULM and conditions for its applicability to microvessel imaging are explained. Based on this, various aspects of the different processing steps for a concrete implementation are discussed. The trade-off between complete reconstruction of the microvasculature and the necessary measurement time as well as the implementation in 3D are reviewed in more detail, as they are the focus of current research. Through an overview of potential or already realized preclinical and clinical applications - pathologic angiogenesis or degeneration of vessels, physiological angiogenesis, or the general understanding of organ or tissue function - the great potential of ULM is demonstrated.
Topics: Microscopy; Ultrasonography; Contrast Media; Microvessels; Microbubbles
PubMed: 37328329
DOI: 10.1016/j.zemedi.2023.02.004 -
Canadian Association of Radiologists... Nov 2019The required training sample size for a particular machine learning (ML) model applied to medical imaging data is often unknown. The purpose of this study was to provide...
PURPOSE
The required training sample size for a particular machine learning (ML) model applied to medical imaging data is often unknown. The purpose of this study was to provide a descriptive review of current sample-size determination methodologies in ML applied to medical imaging and to propose recommendations for future work in the field.
METHODS
We conducted a systematic literature search of articles using Medline and Embase with keywords including "machine learning," "image," and "sample size." The search included articles published between 1946 and 2018. Data regarding the ML task, sample size, and train-test pipeline were collected.
RESULTS
A total of 167 articles were identified, of which 22 were included for qualitative analysis. There were only 4 studies that discussed sample-size determination methodologies, and 18 that tested the effect of sample size on model performance as part of an exploratory analysis. The observed methods could be categorized as pre hoc model-based approaches, which relied on features of the algorithm, or post hoc curve-fitting approaches requiring empirical testing to model and extrapolate algorithm performance as a function of sample size. Between studies, we observed great variability in performance testing procedures used for curve-fitting, model assessment methods, and reporting of confidence in sample sizes.
CONCLUSIONS
Our study highlights the scarcity of research in training set size determination methodologies applied to ML in medical imaging, emphasizes the need to standardize current reporting practices, and guides future work in development and streamlining of pre hoc and post hoc sample size approaches.
Topics: Biomedical Research; Diagnostic Imaging; Humans; Machine Learning; Sample Size
PubMed: 31522841
DOI: 10.1016/j.carj.2019.06.002 -
NeuroImage Feb 2019This article aims to provide the reader with an overview of recent developments in Arterial Spin Labeling (ASL) MRI techniques. A great deal of progress has been made in... (Review)
Review
This article aims to provide the reader with an overview of recent developments in Arterial Spin Labeling (ASL) MRI techniques. A great deal of progress has been made in recent years in terms of the SNR and acquisition speed. New strategies have been introduced to improve labeling efficiency, reduce artefacts, and estimate other relevant physiological parameters besides perfusion. As a result, ASL techniques has become a reliable workhorse for researchers as well as clinicians. After a brief overview of the technique's fundamentals, this article will review new trends and variants in ASL including vascular territory mapping and velocity selective ASL, as well as arterial blood volume imaging techniques. This article will also review recent processing techniques to reduce partial volume effects and physiological noise. Next the article will examine how ASL techniques can be leveraged to calculate additional physiological parameters beyond perfusion and finally, it will review a few recent applications of ASL in the literature.
Topics: Arteries; Blood Flow Velocity; Brain; Brain Mapping; Cerebral Blood Volume; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Neurological; Signal-To-Noise Ratio; Spin Labels
PubMed: 29305164
DOI: 10.1016/j.neuroimage.2017.12.095 -
Mathematical Biosciences and... Aug 2023Social media contains useful information about people and society that could help advance research in many different areas of health (e.g. by applying opinion mining,...
Social media contains useful information about people and society that could help advance research in many different areas of health (e.g. by applying opinion mining, emotion/sentiment analysis and statistical analysis) such as mental health, health surveillance, socio-economic inequality and gender vulnerability. User demographics provide rich information that could help study the subject further. However, user demographics such as gender are considered private and are not freely available. In this study, we propose a model based on transformers to predict the user's gender from their images and tweets. The image-based classification model is trained in two different methods: using the profile image of the user and using various image contents posted by the user on Twitter. For the first method a Twitter gender recognition dataset, publicly available on Kaggle and for the second method the PAN-18 dataset is used. Several transformer models, i.e. vision transformers (ViT), LeViT and Swin Transformer are fine-tuned for both of the image datasets and then compared. Next, different transformer models, namely, bidirectional encoders representations from transformers (BERT), RoBERTa and ELECTRA are fine-tuned to recognize the user's gender by their tweets. This is highly beneficial, because not all users provide an image that indicates their gender. The gender of such users could be detected from their tweets. The significance of the image and text classification models were evaluated using the Mann-Whitney U test. Finally, the combination model improved the accuracy of image and text classification models by 11.73 and 5.26% for the Kaggle dataset and by 8.55 and 9.8% for the PAN-18 dataset, respectively. This shows that the image and text classification models are capable of complementing each other by providing additional information to one another. Our overall multimodal method has an accuracy of 88.11% for the Kaggle and 89.24% for the PAN-18 dataset and outperforms state-of-the-art models. Our work benefits research that critically require user demographic information such as gender to further analyze and study social media content for health-related issues.
Topics: Humans; Social Media; Electric Power Supplies; Research Design
PubMed: 37919997
DOI: 10.3934/mbe.2023711 -
Open Heart Oct 2020A modified Delphi approach was used to develop consensus opinion among British Society for Cardiac Imaging/British Society of Cardiac CT (BSCI/BSCCT) members in order to...
AIM
A modified Delphi approach was used to develop consensus opinion among British Society for Cardiac Imaging/British Society of Cardiac CT (BSCI/BSCCT) members in order to prioritise research questions in cardiovascular imaging.
METHODS
All members of the BSCI/BSCCT were invited to submit research questions that they considered to be of the highest clinical and/or academic priority in the field of cardiovascular imaging (phase 1). Subsequently a steering committee removed duplicate questions and combined questions of a similar theme by consensus agreement where appropriate. BSCI/BSCCT members were invited to rank the resulting research questions in two further iterative rounds (phases 2 and 3) to determine a final list of high-priority research questions.
RESULTS
A total of 111 research questions were submitted in phase 1 by 30 BSCI/BSCCT members. While there was a broad range of topics, from determining the optimal features/markers of the vulnerable plaque to investigating how cardiac imaging can best be used to maximise clinical outcomes and economic costs, multimodality imaging-related (n=44, 40%) questions dominated the categories and coronary artery imaging (n=40, 36%) was the most common topic. Over two iterative rounds of prioritisation of these research questions, the original 111 were reduced to 75 questions in round 2, and 25 in round 3. From these 25 a final was distilled by consensus grouping.
CONCLUSION
This study has identified and ranked the top research priorities in cardiovascular imaging, as identified by the BSCI/BSCCT membership. This is a first step towards identifying the cardiovascular imaging research priorities within the UK and may assist researchers and funding bodies alike in setting priorities.
Topics: Biomedical Research; Cardiac Imaging Techniques; Cardiovascular Diseases; Consensus; Delphi Technique; Humans; Predictive Value of Tests; Prognosis; Research Design
PubMed: 33046593
DOI: 10.1136/openhrt-2020-001389 -
NeuroImage Feb 2019Magnetic resonance elastography (MRE) is an imaging technique for noninvasively and quantitatively assessing tissue stiffness, akin to palpation. MRE is further able... (Review)
Review
Magnetic resonance elastography (MRE) is an imaging technique for noninvasively and quantitatively assessing tissue stiffness, akin to palpation. MRE is further able assess the mechanical properties of tissues that cannot be reached by hand including the brain. The technique is a three-step process beginning with the introduction of shear waves into the tissue of interest by applying an external vibration. Next, the resulting motion is imaged using a phase-contrast MR pulse sequence with motion encoding gradients that are synchronized to the vibration. Finally, the measured displacement images are mathematically inverted to compute a map of the estimated stiffness. In the brain, the technique has demonstrated strong test-retest repeatability with typical errors of 1% for measuring global stiffness, 2% for measuring stiffness in the lobes of the brain, and 3-7% for measuring stiffness in subcortical gray matter. In healthy volunteers, multiple studies have confirmed that stiffness decreases with age, while more recent studies have demonstrated a strong relationship between viscoelasticity and behavioral performance. Furthermore, several studies have demonstrated the sensitivity of brain stiffness to neurodegeneration, as stiffness has been shown to decrease in multiple sclerosis and in several forms of dementia. Moreover, the spatial pattern of stiffness changes varies among these different classes of dementia. Finally, MRE is a promising tool for the preoperative assessment of intracranial tumors, as it can measure both tumor consistency and adherence to surrounding tissues. These factors are important predictors of surgical difficulty. In brief, MRE demonstrates potential value in a number of neurological diseases. However, significant opportunity remains to further refine the technique and better understand the underlying physiology.
Topics: Animals; Brain; Brain Neoplasms; Dementia; Demyelinating Diseases; Elasticity Imaging Techniques; Humans; Image Processing, Computer-Assisted
PubMed: 28993232
DOI: 10.1016/j.neuroimage.2017.10.008 -
JACC. Cardiovascular Imaging Mar 2017Cardiovascular imaging is an integral component of many clinical trials beyond those for which the primary goal is to evaluate or validate imaging technologies. The... (Review)
Review
Cardiovascular imaging is an integral component of many clinical trials beyond those for which the primary goal is to evaluate or validate imaging technologies. The scope of such trials is broad, ranging from those in which a medical, surgical, or interventional cardiovascular device or drug is being evaluated to those in which there is concern about cardiovascular adverse events complicating treatment for noncardiac conditions. This paper discusses study design as it pertains to the incorporation of imaging elements, the important role played by imaging core laboratories, the rationale for and approaches to involvement of imagers in clinical trials, and guidance by the U.S. Food and Drug Administration on imaging endpoints in clinical trials.
Topics: Cardiac Imaging Techniques; Cardiovascular Diseases; Clinical Trials as Topic; Endpoint Determination; Humans; Observer Variation; Predictive Value of Tests; Reproducibility of Results; Research Design; United States; United States Food and Drug Administration
PubMed: 28279377
DOI: 10.1016/j.jcmg.2016.12.003