signal dropout
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2021 ◽  
Vol 11 ◽  
Author(s):  
Thomas Noh ◽  
Parikshit Juvekar ◽  
Raymond Huang ◽  
Gunnar Lee ◽  
Christian T. Ogasawara ◽  
...  

PurposeThe safety and effectiveness of laser interstitial thermal therapy (LITT) relies critically on the ability to continuously monitor the ablation based on real-time temperature mapping using magnetic resonance thermometry (MRT). This technique uses gradient recalled echo (GRE) sequences that are especially sensitive to susceptibility effects from air and blood. LITT for brain tumors is often preceded by a biopsy and is anecdotally associated with artifact during ablation. Thus, we reviewed our experience and describe the qualitative signal dropout that can interfere with ablation.MethodsWe retrospectively reviewed all LITT cases performed in our intraoperative MRI suite for tumors between 2017 and 2020. We identified a total of 17 LITT cases. Cases were reviewed for age, sex, pathology, presence of artifact, operative technique, and presence of blood/air on post-operative scans.ResultsWe identified six cases that were preceded by biopsy, all six had artifact present during ablation, and all six were noted to have air/blood on their post-operative MRI or CT scans. In two of those cases, the artifactual signal dropout qualitatively interfered with thermal damage thresholds at the borders of the tumor. There was no artifact in the 11 non-biopsy cases and no obvious blood or air was noted on the post-ablation scans.ConclusionAdditional consideration should be given to pre-LITT biopsies. The presence of air/blood caused an artifactual signal dropout effect in cases with biopsy that was severe enough to interfere with ablation in a significant number of those cases. Additional studies are needed to identify modifying strategies.



Neonatology ◽  
2021 ◽  
pp. 1-6
Author(s):  
Christoph E. Schwarz ◽  
John M. O’Toole ◽  
Vicki Livingstone ◽  
Andreea M. Pavel ◽  
Eugene M. Dempsey

<b><i>Objective:</i></b> The use of noninvasive monitoring of neonatal hemodynamics is increasing in neonatal care. Methods include noninvasive cardiac output estimated by electrical cardiometry (EC) and peripheral perfusion as perfusion index (PI) using pulse oximetry. Our aim was to evaluate the feasibility to continuously monitor preterm infants with EC and PI during the first 2 postnatal days and the effects of averaging EC data in signal quality (SigQ) analysis. <b><i>Design:</i></b> Prospective observational study. <b><i>Setting:</i></b> Tertiary neonatal academic hospital. <b><i>Patients:</i></b> Preterm infants &#x3c;32 weeks gestation from birth until 48 h. <b><i>Main Outcome Measures:</i></b> Continuous EC and PI measurements. Feasibility was quantified as the time with high SigQ, classified using SigQ index in EC and exception codes in PI. Our predefined threshold for good feasibility was minimum of 24 h with high SigQ for both. <b><i>Results:</i></b> Twenty-two preterm infants (median [IQR] gestational age 28 + 6 (26 + 0, 30 + 4) weeks + days, birth weight 960 [773, 1,500] g) were included. We recorded a minimum of 24 h with high SigQ in 14 infants for EC (unaveraged data) and 22 infants for PI measurements. The median (range) % of recording time with high SigQ was 74% (50%, 88%) for EC and 94% (82%, 96%) for PI. Using 1 minute averaging for EC data resulted in an increase of infants with minimum 24 h of high SigQ to 21 infants. <b><i>Conclusions:</i></b> EC and PI monitoring are feasible in preterm infants within the first 48 h, but SigQ remains problematic for EC. Signal dropout is masked in averaged EC values.



2021 ◽  
Vol 8 ◽  
Author(s):  
Debbie Zhao ◽  
Gina M. Quill ◽  
Kathleen Gilbert ◽  
Vicky Y. Wang ◽  
Helene C. Houle ◽  
...  

Aims: Left ventricular (LV) volumes estimated using three-dimensional echocardiography (3D-echo) have been reported to be smaller than those measured using cardiac magnetic resonance (CMR) imaging, but the underlying causes are not well-understood. We investigated differences in regional LV anatomy derived from these modalities and related subsequent findings to image characteristics.Methods and Results: Seventy participants (18 patients and 52 healthy participants) were imaged with 3D-echo and CMR (&lt;1 h apart). Three-dimensional left ventricular models were constructed at end-diastole (ED) and end-systole (ES) from both modalities using previously validated software, enabling the fusion of CMR with 3D-echo by rigid registration. Regional differences were evaluated as mean surface distances for each of the 17 American Heart Association segments, and by comparing contours superimposed on images from each modality. In comparison to CMR-derived models, 3D-echo models underestimated LV end-diastolic volume (EDV) by −16 ± 22, −1 ± 25, and −18 ± 24 ml across three independent analysis methods. Average surface distance errors were largest in the basal-anterolateral segment (11–15 mm) and smallest in the mid-inferoseptal segment (6 mm). Larger errors were associated with signal dropout in anterior regions and the appearance of trabeculae at the lateral wall.Conclusions: Fusion of CMR and 3D-echo provides insight into the causes of volume underestimation by 3D-echo. Systematic signal dropout and differences in appearances of trabeculae lead to discrepancies in the delineation of LV geometry at anterior and lateral regions. A better understanding of error sources across modalities may improve correlation of clinical indices between 3D-echo and CMR.



2021 ◽  
Vol 12 ◽  
Author(s):  
Alexander D. Cohen ◽  
Amritpal S. Jagra ◽  
Nicholas J. Visser ◽  
Baolian Yang ◽  
Brice Fernandez ◽  
...  

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is commonly used to measure cerebrovascular reactivity (CVR), which can convey insightful information about neurovascular health. Breath-holding (BH) has been shown to be a practical vasodilatory stimulus for measuring CVR in clinical settings. The conventional BOLD fMRI approach has some limitations, however, such as susceptibility-induced signal dropout at air tissue interfaces and low BOLD sensitivity especially in areas of low T2*. These drawbacks can potentially be mitigated with multi-echo sequences, which acquire several images at different echo times in one shot. When combined with multiband techniques, high temporal resolution images can be acquired. This study compared an advanced multiband multi-echo (MBME) echo planar imaging (EPI) sequence with an existing multiband single-echo (MB) sequence to evaluate the repeatability and sensitivity of BH activation and CVR mapping. Images were acquired from 28 healthy volunteers, of which 18 returned for repeat imaging. Both MBME and MB data were pre-processed using both standard and advanced denoising techniques. The MBME data was further processed by combining echoes using a T2*-weighted approach and denoising using multi-echo independent component analysis. BH activation was calculated using a general linear model and the respiration response function. CVR was computed as the percent change related to the activation. To account for differences in CVR related to TE, relative CVR (rCVR) was computed and normalized to the mean gray matter CVR. Test–retest metrics were assessed with the Dice coefficient, rCVR difference, within subject coefficient of variation, and the intraclass correlation coefficient. Our findings demonstrate that rCVR for MBME scans were significantly higher than for MB scans across most of the gray matter. In areas of high susceptibility-induced signal dropout, however, MBME rCVR was significantly less than MB rCVR due to artifactually high rCVR for MB scans in these regions. MBME rCVR showed improved test–retest metrics compared with MB. Overall, the MBME sequence displayed superior BOLD sensitivity, improved specificity in areas of signal dropout on MBME scans, enhanced reliability, and reduced variability across subjects compared with MB acquisitions. Our results suggest that the MBME EPI sequence is a promising tool for imaging CVR.



Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 998
Author(s):  
Marvin Schewe ◽  
Christian Rembe

The intensity of the reflected measuring beam is greatly reduced for laser-Doppler vibrometer (LDV) measurements on rough surfaces since a considerable part of the light is scattered and cannot reach the photodetector (laser speckle effect). The low intensity of the reflected laser beam leads to a so-called signal dropout, which manifests as noise peaks in the demodulated velocity signal. In such cases, no light reaches the detector at a specific time and, therefore, no signal can be detected. Consequently, the overall quality of the signal decreases significantly. In the literature, first attempts and a practical implementation to reduce this effect by signal diversity can be found. In this article, a practical implementation with four measuring heads of a Multipoint Vibrometer (MPV) and an evaluation and optimization of an algorithm from the literature is presented. The limitations of the algorithm, which combines velocity signals, are shown by evaluating our measurements. We present a modified algorithm, which generates a combined detector signal from the raw signals of the individual channels, reducing the mean noise level in our measurement by more than 10 dB. By comparing the results of our new algorithm with the algorithms of the state-of-the-art, we can show an improvement of the noise reduction with our approach.



2018 ◽  
Author(s):  
Jo Cutler ◽  
Joaquim Radua ◽  
Daniel Campbell-Meiklejohn

Meta-analyses of fMRI studies are vital to establish consistent findings across the literature. However, fMRI data are susceptible to signal dropout (i.e. incomplete brain coverage), which varies across studies and brain regions. In other words, for some brain regions, only a variable subset of the studies included in an fMRI meta-analysis have data present. These missing data can mean activations in fMRI meta-analysis are underestimated (type II errors). Here we present SPM (MATLAB) code to run a novel method of adjusting random-effects models for meta-analytic averaging of a group of studies and mixed-effects models for comparison between two groups of studies. In two separate datasets, meta-analytic effect sizes and z-scores were larger in the adjusted, compared to the unadjusted analysis. Relevantly, these changes were in regions such as the ventromedial prefrontal cortex where coverage was lowest. Limitations of the method, including issues of how to threshold the adjusted maps are discussed. Code and demonstration data for the adjusted method are available at https://doi.org/10.25377/sussex.c.4223411.



2018 ◽  
Vol 5 (02) ◽  
pp. 1
Author(s):  
Wenyao Xia ◽  
John Moore ◽  
Elvis C. S. Chen ◽  
Yuanwei Xu ◽  
Olivia Ginty ◽  
...  


2015 ◽  
Vol 100 (5) ◽  
pp. F436-F438 ◽  
Author(s):  
Kathleen Lim ◽  
Kevin I Wheeler ◽  
Hamish D Jackson ◽  
Omid Sadeghi Fathabadi ◽  
Timothy J Gale ◽  
...  




Author(s):  
Christine U. Lee ◽  
James F. Glockner

58-year-old woman with a mixed epithelial stromal tumor of the left kidney, status post open partial nephrectomy. MRI was requested to assess for metastatic disease. The radiologist chose to use Multihance Axial fat-suppressed T2-weighted FSE image (Figure 1.12.1) demonstrates a right hepatic lobe mass with mildly increased signal intensity relative to liver and central high signal intensity. There is no signal dropout from IP to OP T1-weighted 2D SPGR images (...



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