scholarly journals Identification of a distinct imaging phenotype may improve the management of palindromic rheumatism

2018 ◽  
Vol 78 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Kulveer Mankia ◽  
Maria-Antonietta D’Agostino ◽  
Richard J Wakefield ◽  
Jackie L Nam ◽  
Waqar Mahmood ◽  
...  
Keyword(s):  
At Risk ◽  
High Frequency ◽  
Power Doppler ◽  
Musculoskeletal Symptoms ◽  
High Resolution Imaging ◽  
Palindromic Rheumatism ◽  
Treatment Naïve ◽  
Resolution Imaging ◽  
Citrullinated Peptide ◽  
New Onset

ObjectivesTo use high-resolution imaging to characterise palindromic rheumatism (PR) and to compare the imaging pattern observed to that seen in new-onset rheumatoid arthritis (NORA).MethodsUltrasound (US) assessment of synovitis, tenosynovitis and non-synovial extracapsular inflammation (ECI) was performed during and between flares in a prospective treatment-naive PR cohort. MRI of the flaring region was performed where possible. For comparison, the same US assessment was also performed in anticyclic citrullinated peptide (CCP) positive individuals with musculoskeletal symptoms (CCP+ at risk) and patients with NORA.ResultsThirty-one of 79 patients with PR recruited were assessed during a flare. A high frequency of ECI was identified on US; 19/31 (61%) of patients had ECI including 12/19 (63%) in whom ECI was identified in the absence of synovitis. Only 7/31 (23%) patients with PR had synovitis (greyscale ≥1 and power Doppler ≥1) during flare. In the hands/wrists, ECI was more prevalent in PR compared with NORA and CCP+ at risk (65% vs 29 % vs 6%, p<0.05). Furthermore, ECI without synovitis was specific for PR (42% PR vs 4% NORA (p=0.003) and 6% CCP+ at risk (p=0.0012)). Eleven PR flares were captured by MRI, which was more sensitive than US for synovitis and ECI. 8/31 (26%) patients with PR developed RA and had a similar US phenotype to NORA at progression.ConclusionPR has a distinct US pattern characterised by reversible ECI, often without synovitis. In patients presenting with new joint swelling, US may refine management by distinguishing relapsing from persistent arthritis.

scholarly journals P240 Can ultrasound alone predict the need to treat ACPA positive individuals without synovitis?

Rheumatology ◽  
2020 ◽  
Vol 59 (Supplement_2) ◽  
Author(s):  
Laurence M Duquenne ◽  
Kulveer Mankia ◽  
Leticia Garcia Montoya ◽  
Andrea Di Matteo ◽  
Jacqueline Nam ◽  
...  
Keyword(s):  
At Risk ◽  
Predictive Value ◽  
Cox Regression ◽  
Clinical Symptoms ◽  
Power Doppler ◽  
Musculoskeletal Symptoms ◽  
Features Selection ◽  
Moderate Sensitivity ◽  
Us Scan ◽  
Selection Of

Abstract Background In anti-cyclic citrullinated peptide antibody-positive (ACPA+) individuals without clinical synovitis (at-risk), to define the critical ultrasound (US) features sufficiently predictive for inflammatory arthritis (IA) to enable logical initiation of therapy. Methods In a single centre prospective cohort, at risk ACPA+ individuals with a new musculoskeletal symptoms underwent an US scan of 38 joints and 18 tendons at first visit. The predictive value of US abnormalities (Power Doppler (PD), Grey Scale (GS), erosion or tenosynovitis (TSV)) for progression to IA was analysed and the best predictive joints determined by Multivariable Cox Regression, adjusted for confounders. The US results were combined with clinical symptoms/findings to produce predictive models. Results Consecutive at-risk ACPA+ individuals (n = 457, mean age 50.3 years old, 74.2% women) were followed up for median of 15.4 months (range 0.1-127.4), a complete dataset with follow-up of at least 6 months was available for 319 of them. 135 (29.5%) developed IA after a median of 11.3 months (range 0.1-111.7). The negative predictive value of a US scan without any abnormality was 82%. In multivariable Cox regression, both PD and TSV were predictive of progression, with respectively hazard ratios of 1.2 (9=0.026) and 1.13 (p = 0.025). All US abnormalities had a high specificity (spec) but only moderate sensitivity (sens), PD was the most specific with a spec/sens of 0.94/0.23, followed by TSV with a spec/sens of 0.91/0.26 but the best area under the curve (AUC) of 0.599 (P = 0.0015). The addition ACPA titre (high compared to low), but not GS, improved spec/sens up to 0.92/0.34 and AUC to 0.964 (p &lt; 0.001). A selection of US and clinical data of 14 joints also improved prediction, with an AUC of 0.670 (p &lt; 0.001) and a spec/sens of 0.65/0.62. A selection of the 34 most predictive features reached the same sens/spec as the ACR/EULAR 2010 classification criteria for RA, showing a spec/sens of 0.80/0.56. Conclusion In at-risk ACPA+ individuals, the presence of sub-clinical US abnormalities are highly specific for progression to IA. The only moderate sensitivity can be improved by using joints or features selection in combination with clinical examination. These results are the first step in providing guidance for which at-risk ACPA+ individuals to treat. Disclosures L.M. Duquenne None. K. Mankia None. L. Garcia Montoya None. A. Di Matteo None. J. Nam None. P. Emery None.

scholarly journals Ultrasound Biomicroscopy in Small Animal Research: Applications in Molecular and Preclinical Imaging

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
A. Greco ◽  
M. Mancini ◽  
S. Gargiulo ◽  
M. Gramanzini ◽  
P. P. Claudio ◽  
...  
Keyword(s):  
High Resolution ◽  
Power Doppler ◽  
Small Animal ◽  
Ultrasound Biomicroscopy ◽  
Animal Research ◽  
High Resolution Imaging ◽  
Cardiovascular Development ◽  
Preclinical Imaging ◽  
Resolution Imaging ◽  
Small Animal Research

Ultrasound biomicroscopy (UBM) is a noninvasive multimodality technique that allows high-resolution imaging in mice. It is affordable, widely available, and portable. When it is coupled to Doppler ultrasound with color and power Doppler, it can be used to quantify blood flow and to image microcirculation as well as the response of tumor blood supply to cancer therapy. Target contrast ultrasound combines ultrasound with novel molecular targeted contrast agent to assess biological processes at molecular level. UBM is useful to investigate the growth and differentiation of tumors as well as to detect early molecular expression of cancer-related biomarkersin vivoand to monitor the effects of cancer therapies. It can be also used to visualize the embryological development of mice in uterus or to examine their cardiovascular development. The availability of real-time imaging of mice anatomy allows performing aspiration procedures under ultrasound guidance as well as the microinjection of cells, viruses, or other agents into precise locations. This paper will describe some basic principles of high-resolution imaging equipment, and the most important applications in molecular and preclinical imaging in small animal research.

scholarly journals Automated Detection, Classification and Counting of Fish in Fish Passages With Deep Learning

2022 ◽  
Vol 8 ◽  
Author(s):  
Vishnu Kandimalla ◽  
Matt Richard ◽  
Frank Smith ◽  
Jean Quirion ◽  
Luis Torgo ◽  
...  
Keyword(s):  
At Risk ◽  
Deep Learning ◽  
High Resolution ◽  
Real Time ◽  
Fish Species ◽  
Fish Passage ◽  
High Resolution Imaging ◽  
Fish Ladder ◽  
Resolution Imaging ◽  
Imaging Sonar

The Ocean Aware project, led by Innovasea and funded through Canada's Ocean Supercluster, is developing a fish passage observation platform to monitor fish without the use of traditional tags. This will provide an alternative to standard tracking technology, such as acoustic telemetry fish tracking, which are often not appropriate for tracking at-risk fish species protected by legislation. Rather, the observation platform uses a combination of sensors including acoustic devices, visual and active sonar, and optical cameras. This will enable more in-depth scientific research and better support regulatory monitoring of at-risk fish species in fish passages or marine energy sites. Analysis of this data will require a robust and accurate method to automatically detect fish, count fish, and classify them by species in real-time using both sonar and optical cameras. To meet this need, we developed and tested an automated real-time deep learning framework combining state of the art convolutional neural networks and Kalman filters. First, we showed that an adaptation of the widely used YOLO machine learning model can accurately detect and classify eight species of fish from a public high resolution DIDSON imaging sonar dataset captured from the Ocqueoc River in Michigan, USA. Although there has been extensive research in the literature identifying particular fish such as eel vs. non-eel and seal vs. fish, to our knowledge this is the first successful application of deep learning for classifying multiple fish species with high resolution imaging sonar. Second, we integrated the Norfair object tracking framework to track and count fish using a public video dataset captured by optical cameras from the Wells Dam fish ladder on the Columbia River in Washington State, USA. Our results demonstrate that deep learning models can indeed be used to detect, classify species, and track fish using both high resolution imaging sonar and underwater video from a fish ladder. This work is a first step toward developing a fully implemented system which can accurately detect, classify and generate insights about fish in a wide variety of fish passage environments and conditions with data collected from multiple types of sensors.

scholarly journals High-resolution imaging with high-frequency 1-D linear CMUT arrays

2006 ◽  
Author(s):  
D.T. Yeh ◽  
O. Oralkan ◽  
I.O. Wygant ◽  
A.S. Ergun ◽  
J.H. Wong ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
High Resolution Imaging ◽  
Resolution Imaging
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