NEAR-INFRARED IMAGING SENSOR WITH IMPROVED HANDLING AND DIRECT LOCALIZATION IN SIMULTANEOUS MAGNETIC RESONANCE IMAGING MEASUREMENTS

2011 ◽  
Vol 04 (02) ◽  
pp. 191-198
Author(s):  
SONJA SPICHTIG ◽  
MARCO PICCIRELLI ◽  
ROBERT S. VORBURGER ◽  
MARTIN WOLF
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Optical Sensor ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Fmri Data ◽  
Resonance Imaging ◽  
Near Infrared Imaging ◽  
Cerebral Activation ◽  
Direct Localization

We present a novel optical sensor to acquire simultaneously functional near-infrared imaging (fNIRI) and functional magnetic resonance imaging (fMRI) data with an improved handling and direct localization in the MRI compared to available sensors. Quantitative phantom and interference measurements showed that both methods can be combined without reciprocal adverse effects. The direct localization of the optical sensor on MR images acquired with a T1-weighted echo sequence simplifies the co-registration of NIRI and MRI data. In addition, the optical sensor is simple to attach, which is crucial for measurements on vulnerable subjects. The fNIRI and T2*-weighted fMRI data of a cerebral activation were simultaneously acquired proving the practicability of the setup.

scholarly journals Informative Biomarkers for Autism Spectrum Disorder Diagnosis in Functional Magnetic Resonance Imaging Data on the Default Mode Network

2021 ◽  
Vol 11 (13) ◽  
pp. 6216
Author(s):  
Aikaterini S. Karampasi ◽  
Antonis D. Savva ◽  
Vasileios Ch. Korfiatis ◽  
Ioannis Kakkos ◽  
George K. Matsopoulos
Keyword(s):  
Magnetic Resonance Imaging ◽  
Autism Spectrum Disorder ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Fmri Data ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Dynamic Connectivity

Effective detection of autism spectrum disorder (ASD) is a complicated procedure, due to the hundreds of parameters suggested to be implicated in its etiology. As such, machine learning methods have been consistently applied to facilitate diagnosis, although the scarcity of potent autism-related biomarkers is a bottleneck. More importantly, the variability of the imported attributes among different sites (e.g., acquisition parameters) and different individuals (e.g., demographics, movement, etc.) pose additional challenges, eluding adequate generalization and universal modeling. The present study focuses on a data-driven approach for the identification of efficacious biomarkers for the classification between typically developed (TD) and ASD individuals utilizing functional magnetic resonance imaging (fMRI) data on the default mode network (DMN) and non-physiological parameters. From the fMRI data, static and dynamic connectivity were calculated and fed to a feature selection and classification framework along with the demographic, acquisition and motion information to obtain the most prominent features in regard to autism discrimination. The acquired results provided high classification accuracy of 76.63%, while revealing static and dynamic connectivity as the most prominent indicators. Subsequent analysis illustrated the bilateral parahippocampal gyrus, right precuneus, midline frontal, and paracingulate as the most significant brain regions, in addition to an overall connectivity increment.

Near-infrared Fluorescence Optical Imaging in Early Rheumatoid Arthritis: A Comparison to Magnetic Resonance Imaging and Ultrasonography

2015 ◽  
Vol 42 (7) ◽  
pp. 1112-1118 ◽  
Author(s):  
Michaela Krohn ◽  
Sarah Ohrndorf ◽  
Stephanie G. Werner ◽  
Bernd Schicke ◽  
Gerd-Rüdiger Burmester ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Optical Imaging ◽  
Early Rheumatoid Arthritis ◽  
Near Infrared ◽  
Resonance Imaging ◽  
Near Infrared Fluorescence ◽  
Fluorescence Optical Imaging ◽  
Early Ra

Objective.Near-infrared fluorescence optical imaging (FOI) is a novel imaging technology in the detection and evaluation of different arthritides. FOI was validated in comparison to magnetic resonance imaging (MRI), greyscale ultrasonography (GSUS), and power Doppler ultrasonography (PDUS) in patients with early rheumatoid arthritis (RA).Methods.Hands of 31 patients with early RA were examined by FOI, MRI, and US. In each modality, synovitis of the wrist, metacarpophalangeal joints (MCP) 2–5, and proximal interphalangeal joints (PIP) 2–5 were scored on a 4-point scale (0–3). Sensitivity and specificity of FOI were analyzed in comparison to MRI and US as reference methods, differentiating between 3 phases of FOI enhancement (P1–3). Intraclass correlation coefficients (ICC) were calculated to evaluate the agreement of FOI with MRI and US.Results.A total of 279 joints (31 wrists, 124 MCP and 124 PIP joints) were evaluated. With MRI as the reference method, overall sensitivity/specificity of FOI was 0.81/0.00, 0.49/0.84, and 0.86/0.38 for wrist, MCP, and PIP joints, respectively. Under application of PDUS as reference, sensitivity was even higher, while specificity turned out to be low, except for MCP joints (0.88/0.15, 0.81/0.76, and 1.00/0.27, respectively). P2 appears to be the most sensitive FOI phase, while P1 showed the highest specificity. The best agreement of FOI was shown for PDUS, especially with regard to MCP and PIP joints (ICC of 0.57 and 0.53, respectively), while correlation with MRI was slightly lower.Conclusion.FOI remains an interesting diagnostic tool for patients with early RA, although this study revealed limitations concerning the detection of synovitis. Further research is needed to evaluate its full diagnostic potential in rheumatic diseases.

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