scholarly journals Paediatric lung imaging: the times they are a-changin'

2018 ◽  
Vol 27 (147) ◽  
pp. 170097 ◽  
Author(s):  
Harm A.W.M Tiddens ◽  
Wieying Kuo ◽  
Marcel van Straten ◽  
Pierluigi Ciet
Keyword(s):  
Image Analysis ◽  
Paediatric Population ◽  
Chest Imaging ◽  
Technology Acquisition ◽  
Lung Structure ◽  
Analysis Strategies ◽  
Integrate State ◽  
Magnetic Resonance Imaging Mri ◽  
The Times ◽  
Novel Applications

Until recently, functional tests were the most important tools for the diagnosis and monitoring of lung diseases in the paediatric population. Chest imaging has gained considerable importance for paediatric pulmonology as a diagnostic and monitoring tool to evaluate lung structure over the past decade. Since January 2016, a large number of papers have been published on innovations in chest computed tomography (CT) and/or magnetic resonance imaging (MRI) technology, acquisition techniques, image analysis strategies and their application in different disease areas. Together, these papers underline the importance and potential of chest imaging and image analysis for today's paediatric pulmonology practice. The focus of this review is chest CT and MRI, as these are, and will be, the modalities that will be increasingly used by most practices. Special attention is given to standardisation of image acquisition, image analysis and novel applications in chest MRI. The publications discussed underline the need for the paediatric pulmonology community to implement and integrate state-of-the-art imaging and image analysis modalities into their structure–function laboratory for the benefit of their patients.

26. Nothing but the truth, so help me God: The history of magnetic resonance imaging

2007 ◽  
Vol 30 (4) ◽  
pp. 41
Author(s):  
A. Dechant
Keyword(s):  
Magnetic Resonance Imaging ◽  
New York ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Nobel Prize ◽  
Resonance Imaging ◽  
Solid State Physics ◽  
Magnetic Resonance Imaging Mri ◽  
The Times ◽  
Nuclear Magnetic

On the morning of October 10, 2003, the residents of New York awoke to find that an entire page of their beloved paper, The Times, had been usurped for the sole purpose of flagrant self-promotion and protestation. On his own behalf, Dr. Raymand Damadian had purchased a one page spread bemoaning his exclusion in the Nobel Prize for Medicine that year which had previously been awarded to Paul Laterbur and Peter Mansfield for their contributions to the development of Magnetic Resonance Imaging (MRI). Over the course of the next few months, the public was to witness a series of such articles proclaiming that a shameful wrong had been committed, and that the truth would eventually prove Dr. Damadian’s accusations. That truth lay in the early theoretical and technical foundations that led to the discovery of MRI. Described just after the Second World War, nuclear magnetic resonance (NMR) was hailed as a breakthrough in physical chemistry for which Felix Bloch and Edward Purcell were awarded the Nobel Prize in Physics in 1952. Two decades later, in 1971, Dr. Damadian discovered that differences between the NMR signals of cancerous and normal tissue might provide a rapid means of cancer detection. However, Laterbur and Mansfield were the first to actually demonstrate images of live tissue using the application of magnetic gradients – the key to modern MRI. Though speculation exists that Dr. Damadian may have been excluded from the prize due to his religious beliefs or political rivalry, only time will reveal the whole truth when the Nobel files are opened 50 years hence. Bradley W. The Nobel Prize: Three Investigators Allowed but Two Were Chosen. Journal of Magnetic Resonance Imaging 2004; 19:520. Laterbur P. Image formation by induced local interactions: examples of employing nuclear magnetic resonance. Nature 1973; 242:190-191. Mansfield P, Grannell P. “NMR diffraction in solids?” Journal of Physics C: Solid State Physics 1973; 63:L433-L426.

scholarly journals Quality Control in Fiore Sardo PDO Cheese: Detection of Heat Treatment Application and Production Chain by MRI Relaxometry and Image Analysis

Dairy ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 270-287
Author(s):  
Roberto Anedda ◽  
Riccardo Melis ◽  
Elena Curti
Keyword(s):  
Image Analysis ◽  
Raw Milk ◽  
Characteristic Relaxation Time ◽  
Resonance Imaging ◽  
Production Chain ◽  
Visual Appearance ◽  
Heat Treated ◽  
Heat Application ◽  
Magnetic Resonance Imaging Mri ◽  
Treatment Application

Fiore Sardo (FS), a traditional Italian cheese, is present in the market as a heterogeneous variety of products. The use of heat-treated (HT) milk is forbidden by the official production protocol, but no official analytical method able to detect heat application is yet available. Here, a combined magnetic resonance imaging (MRI) relaxometry and image analysis approach to recognize FS made from raw milk is presented. Artisanal FS cheeses were produced from raw milk (RC) by five shepherds in accordance with the official protocol. They were compared to HT-milk counterparts (HTC). Additionally, industrially manufactured commercial FS cheeses (I) were also purchased and compared to RC and HTC. Relaxometry data of FS indicated the presence of two water populations; the ratio of characteristic relaxation time constant T2 and area fraction (Score, Ṩ) of the fastest relaxing population was used to compare RC, HTC and I samples. RC from HTC were successfully discriminated, the latter exhibiting lower Ṩ (enhanced protein hydration). I cheeses exhibited the lowest Ṩ values, sometimes comparable to HTC. Since visual appearance of RC and HTC is appreciably different, an image analysis deep learning approach using MRI and photographic pictures was adopted to discriminate the two productions, with promising percentages (>93%).

scholarly journals Ultrasonic image analysis and image-guided interventions

2011 ◽  
Vol 1 (4) ◽  
pp. 673-685 ◽  
Author(s):  
J. Alison Noble ◽  
Nassir Navab ◽  
H. Becher
Keyword(s):  
Image Analysis ◽  
Imaging Modality ◽  
Medical Image Analysis ◽  
Three Dimensional ◽  
Clinical Information ◽  
Image Guided ◽  
Software Algorithms ◽  
Positron Emission ◽  
Imaging Research ◽  
Magnetic Resonance Imaging Mri

The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

scholarly journals Influence of image analysis strategy, cooling rate, and sample volume on apparent protein cloud-point temperature determination

2020 ◽  
Author(s):  
Marieke E. Klijn ◽  
Jürgen Hubbuch
Keyword(s):  
Image Analysis ◽  
Cooling Rate ◽  
Cloud Point ◽  
Detection Method ◽  
Sample Volume ◽  
Point Temperature ◽  
Analysis Strategies ◽  
Experimental Parameters ◽  
Analysis Strategy ◽  
Cloud Point Temperature

AbstractThe protein cloud-point temperature (TCloud) is a known representative of protein–protein interaction strength and provides valuable information during the development and characterization of protein-based products, such as biopharmaceutics. A high-throughput low volume TCloud detection method was introduced in preceding work, where it was concluded that the extracted value is an apparent TCloud (TCloud,app). As an understanding of the apparent nature is imperative to facilitate inter-study data comparability, the current work was performed to systematically evaluate the influence of 3 image analysis strategies and 2 experimental parameters (sample volume and cooling rate) on TCloud,app detection of lysozyme. Different image analysis strategies showed that TCloud,app is detectable by means of total pixel intensity difference and the total number of white pixels, but the latter is also able to extract the ice nucleation temperature. Experimental parameter variation showed a TCloud,app depression for increasing cooling rates (0.1–0.5 °C/min), and larger sample volumes (5–24 μL). Exploratory thermographic data indicated this resulted from a temperature discrepancy between the measured temperature by the cryogenic device and the actual sample temperature. Literature validation confirmed that the discrepancy does not affect the relative inter-study comparability of the samples, regardless of the image analysis strategy or experimental parameters. Additionally, high measurement precision was demonstrated, as TCloud,app changes were detectable down to a sample volume of only 5 μL and for 0.1 °C/min cooling rate increments. This work explains the apparent nature of the TCloud detection method, showcases its detection precision, and broadens the applicability of the experimental setup.

scholarly journals MRI-based measurements of aerosol deposition in the lung of healthy and elastase-treated rats

2014 ◽  
Vol 116 (12) ◽  
pp. 1561-1568 ◽  
Author(s):  
Jessica M. Oakes ◽  
Ellen C. Breen ◽  
Miriam Scadeng ◽  
Ghislain S. Tchantchou ◽  
Chantal Darquenne
Keyword(s):  
Particle Deposition ◽  
Aerosol Deposition ◽  
Relative Dispersion ◽  
Iron Oxide Particles ◽  
Signal Decay ◽  
Chronic Lung Diseases ◽  
Lung Structure ◽  
Oxide Particles ◽  
Magnetic Resonance Imaging Mri ◽  
Mass Median

Aerosolized drugs are increasingly being used to treat chronic lung diseases or to deliver therapeutics systemically through the lung. The influence of disease, such as emphysema, on particle deposition is not fully understood. With the use of magnetic resonance imaging (MRI), the deposition pattern of iron oxide particles with a mass median aerodynamic diameter of 1.2 μm was assessed in the lungs of healthy and elastase-treated rats. Tracheostomized rats were ventilated with particles, at a tidal volume of 2.2 ml, and a breathing frequency of 80 breaths/min. Maximum airway pressure was significantly lower in the elastase-treated (Paw = 7.71 ± 1.68 cmH2O) than in the healthy rats (Paw = 10.43 ± 1.02 cmH2O; P < 0.01). This is consistent with an increase in compliance characteristic of an emphysema-like lung structure. Following exposure, lungs were perfusion fixed and imaged in a 3T MR scanner. Particle concentration in the different lobes was determined based on a relationship with the MR signal decay rate, R2*. Whole lung particle deposition was significantly higher in the elastase-treated rats (CE,part = 3.03 ± 0.61 μm/ml) compared with the healthy rats (CH,part = 1.84 ± 0.35 μm/ml; P < 0.01). However, when particle deposition in each lobe was normalized by total deposition in the lung, there was no difference between the experimental groups. However, the relative dispersion [RD = standard deviation/mean] of R2* was significantly higher in the elastase-treated rats (RDE = 0.32 ± 0.02) compared with the healthy rats (RDH = 0.25 ± 0.02; P < 0.01). These data show that particle deposition is higher and more heterogeneously distributed in emphysematous lungs compared with healthy lungs.

Pooled historical MRI data as a basis for research in multiple sclerosis - a statistical evaluation

2007 ◽  
Vol 13 (4) ◽  
pp. 509-516 ◽  
Author(s):  
S. Schach ◽  
M. Scholz ◽  
J.S. Wolinsky ◽  
L. Kappos
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Image Analysis ◽  
Statistical Analysis ◽  
Statistical Evaluation ◽  
Treated Group ◽  
Resonance Imaging ◽  
Pooled Data ◽  
Magnetic Resonance Imaging Mri ◽  
Degree Of Heterogeneity

Pooled data from placebo groups of different trials can serve as historical control for ongoing or future therapeutic studies and as a reference for power calculations. In order to assess their usefulness for this purpose, we investigated the degree of heterogeneity of placebo arm data from 14 controlled studies included in the database of the Sylvia Lawry Centre for Multiple Sclerosis Research. Since different criteria for the inclusion/exclusion of patients were used in these studies, an attempt was made to adjust the distribution of magnetic resonance imaging (MRI) measures for the differences in the study populations. The analyses showed that, even after adjustment, significant differences remained. This heterogeneity does not reduce the usefulness of the database for statistical analysis of inter-relationships between variables, provided that it is explicitly taken into account as a stratification factor. However, care must be taken when trying to compare the results of a newly treated group with the patients of this pool. Heterogeneity in some MRI variables was greatly reduced when only studies from the same image analysis centre were compared. Multiple Sclerosis 2007; 13: 509-516. http://msj.sagepub.com

scholarly journals MRI image analysis methods and applications: an algorithmic perspective using brain tumors as an exemplar

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Vachan Vadmal ◽  
Grant Junno ◽  
Chaitra Badve ◽  
William Huang ◽  
Kristin A Waite ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computer Vision ◽  
Image Analysis ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Computational Techniques ◽  
Complex Nature ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Image

Abstract The use of magnetic resonance imaging (MRI) in healthcare and the emergence of radiology as a practice are both relatively new compared with the classical specialties in medicine. Having its naissance in the 1970s and later adoption in the 1980s, the use of MRI has grown exponentially, consequently engendering exciting new areas of research. One such development is the use of computational techniques to analyze MRI images much like the way a radiologist would. With the advent of affordable, powerful computing hardware and parallel developments in computer vision, MRI image analysis has also witnessed unprecedented growth. Due to the interdisciplinary and complex nature of this subfield, it is important to survey the current landscape and examine the current approaches for analysis and trend trends moving forward.

Glucocorticoid induced impairment of lung structure assessed by digital image analysis

2001 ◽  
Vol 161 (1) ◽  
pp. 26-30 ◽  
Author(s):  
Stefan A. Tschanz ◽  
Beat Haenni ◽  
Peter H. Burri
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Lung Structure

scholarly journals Recent Advances in Fluorescence Imaging of Pulmonary Fibrosis in Animal Models

2021 ◽  
Vol 8 ◽  
Author(s):  
Zongwei Liu ◽  
Xiaofang Tang ◽  
Zongling Zhu ◽  
Xunxun Ma ◽  
Wenjuan Zhou ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Fluorescence Imaging ◽  
Design Strategies ◽  
High Resolution Computed Tomography ◽  
Hyperpolarized Gases ◽  
Recent Advances ◽  
Lung Structure ◽  
Imaging Research ◽  
Magnetic Resonance Imaging Mri ◽  
Effective Diagnosis

Pulmonary fibrosis (PF) is a lung disease that may cause impaired gas exchange and respiratory failure while being difficult to treat. Rapid, sensitive, and accurate detection of lung tissue and cell changes is essential for the effective diagnosis and treatment of PF. Currently, the commonly-used high-resolution computed tomography (HRCT) imaging has been challenging to distinguish early PF from other pathological processes in the lung structure. Magnetic resonance imaging (MRI) using hyperpolarized gases is hampered by the higher cost to become a routine diagnostic tool. As a result, the development of new PF imaging technologies may be a promising solution. Here, we summarize and discuss recent advances in fluorescence imaging as a talented optical technique for the diagnosis and evaluation of PF, including collagen imaging, oxidative stress, inflammation, and PF-related biomarkers. The design strategies of the probes for fluorescence imaging (including multimodal imaging) of PF are briefly described, which can provide new ideas for the future PF-related imaging research. It is hoped that this review will promote the translation of fluorescence imaging into a clinically usable assay in PF.

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