cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7513064
title: Volumetric T1 and T2 magnetic resonance brain toolkit for relaxometry mapping simulation

description: Abstract Introduction Relaxometry images are an important magnetic resonance imaging (MRI) technique in the clinical routine. Many diagnoses are based on the relaxometry maps to infer abnormal state in the tissue characteristic relaxation constant. In order to study the performance of these image processing approaches, a controlled simulated environment is necessary. However, a simulated relaxometry image tool is still lacking. This study proposes a computational anatomical brain phantom for MRI relaxometry images, which aims to offer an easy and flexible toolkit to test different image processing techniques, applied to MRI relaxometry maps in a controlled simulated environment. Methods A pipeline of image processing techniques such as brain extraction, image segmentation, normalization to a common space and signal relaxation decay simulation, were applied to a brain structural ICBM brain template, on both T1 and T2 weighted images, in order to simulate a volumetric brain relaxometry phantom. The FMRIB Software Library (FSL) toolkits were used here as the base image processing needed to all the relaxometry reconstruction. Results All the image processing procedures are performed using automatic algorithms. In addition, different artefact levels can be set from different sources such as Rician noise and radio-frequency inhomogeneity noises. Conclusion The main goal of this project is to help researchers in their future image processing analysis involving MRI relaxometry images, offering reliable and robust brain relaxometry simulation modelling. Furthermore, the entire pipeline is open-source, which provides a wide collaboration between researchers who may want to improve the software and its functionality.
DOI: 10.6084/m9.figshare.7513064.v1
title: Volumetric T1 and T2 magnetic resonance brain toolkit for relaxometry mapping simulation

description: Abstract Introduction Relaxometry images are an important magnetic resonance imaging (MRI) technique in the clinical routine. Many diagnoses are based on the relaxometry maps to infer abnormal state in the tissue characteristic relaxation constant. In order to study the performance of these image processing approaches, a controlled simulated environment is necessary. However, a simulated relaxometry image tool is still lacking. This study proposes a computational anatomical brain phantom for MRI relaxometry images, which aims to offer an easy and flexible toolkit to test different image processing techniques, applied to MRI relaxometry maps in a controlled simulated environment. Methods A pipeline of image processing techniques such as brain extraction, image segmentation, normalization to a common space and signal relaxation decay simulation, were applied to a brain structural ICBM brain template, on both T1 and T2 weighted images, in order to simulate a volumetric brain relaxometry phantom. The FMRIB Software Library (FSL) toolkits were used here as the base image processing needed to all the relaxometry reconstruction. Results All the image processing procedures are performed using automatic algorithms. In addition, different artefact levels can be set from different sources such as Rician noise and radio-frequency inhomogeneity noises. Conclusion The main goal of this project is to help researchers in their future image processing analysis involving MRI relaxometry images, offering reliable and robust brain relaxometry simulation modelling. Furthermore, the entire pipeline is open-source, which provides a wide collaboration between researchers who may want to improve the software and its functionality.
DOI: 10.6084/m9.figshare.7509080.v1
title: Heartbeat classification system based on neural networks and dimensionality reduction

description: Abstract Introduction This paper presents a complete approach for the automatic classification of heartbeats to assist experts in the diagnosis of typical arrhythmias, such as right bundle branch block, left bundle branch block, premature ventricular beats, premature atrial beats and paced beats. Methods A pre-processing step was performed on the electrocardiograms (ECG) for baseline removal. Next, a QRS complex detection algorithm was implemented to detect the heartbeats, which contain the primary information that is employed in the classification approach. Next, ECG segmentation was performed, by which a set of features based on the RR interval and the beat waveform morphology were extracted from the ECG signal. The size of the feature vector was reduced by principal component analysis. Finally, the reduced feature vector was employed as the input to an artificial neural network. Results Our approach was tested on the Massachusetts Institute of Technology arrhythmia database. The classification performance on a test set of 18 ECG records of 30 min each achieved an accuracy of 96.97%, a sensitivity of 95.05%, a specificity of 90.88%, a positive predictive value of 95.11%, and a negative predictive value of 92.7%. Conclusion The proposed approach achieved high accuracy for classifying ECG heartbeats and could be used to assist cardiologists in telecardiology services. The main contribution of our classification strategy is in the feature selection step, which reduced classification complexity without major changes in the performance.
DOI: 10.6084/m9.figshare.7509080
title: Heartbeat classification system based on neural networks and dimensionality reduction

description: Abstract Introduction This paper presents a complete approach for the automatic classification of heartbeats to assist experts in the diagnosis of typical arrhythmias, such as right bundle branch block, left bundle branch block, premature ventricular beats, premature atrial beats and paced beats. Methods A pre-processing step was performed on the electrocardiograms (ECG) for baseline removal. Next, a QRS complex detection algorithm was implemented to detect the heartbeats, which contain the primary information that is employed in the classification approach. Next, ECG segmentation was performed, by which a set of features based on the RR interval and the beat waveform morphology were extracted from the ECG signal. The size of the feature vector was reduced by principal component analysis. Finally, the reduced feature vector was employed as the input to an artificial neural network. Results Our approach was tested on the Massachusetts Institute of Technology arrhythmia database. The classification performance on a test set of 18 ECG records of 30 min each achieved an accuracy of 96.97%, a sensitivity of 95.05%, a specificity of 90.88%, a positive predictive value of 95.11%, and a negative predictive value of 92.7%. Conclusion The proposed approach achieved high accuracy for classifying ECG heartbeats and could be used to assist cardiologists in telecardiology services. The main contribution of our classification strategy is in the feature selection step, which reduced classification complexity without major changes in the performance.
DOI: 10.6084/m9.figshare.7510448
title: Influence of subcutaneous fat on mechanomyographic signals at three levels of voluntary effort

description: Abstract Introduction This study aims to assess the influence of different skinfold thicknesses (ST) and their relation to the attenuation of the mechanomyographic (MMG) signal at different force levels (maximal voluntary contraction – MVC, 40% of MVC and 70% of MVC) of the rectus femoris muscle. Methods Fifteen volunteers were divided in two groups: ST lower than 10mm (G&lt;10) (8 participants) and ST higher than 35mm (G&gt;35) (7 participants). Student t tests were employed to investigate differences between G&lt;10 and G&gt;35 regarding MMG analysis parameters (acceleration root mean square – aRMS, zero crossing – ZC, and median frequency – MDF), for the X, Y and Z axes, as well as for the modulus of these three axes. Results We found that thicker layers of body fat act as attenuator filters for the MMG signal [MDFMVC: X (p = 0.005), Z (p = 0.003); MDF70%MVC: X (p = 0.034); ZCMVC: Z (p = 0.037), modulus (p = 0.005); ZC70%MVC: Z (p = 0.047)]. We found significant correlation between ST values and aRMS in three levels, in the Yaxis (p = 0.591), for the group G&lt;10. For the modulus, the aRMS value showed correlation with ST values for group G&gt;35 in 40%MVC (R2 = 0.610), and 70%MVC (R2 = 0.592). The MDF parameter showed correlation with ST values only in the Yaxis in 70%MVC (R2 = 0.700) for G&gt;35. Conclusions We observed MMG signal attenuation in at least one of the parameters analyzed for each level of the rectus femoris muscle force, indicating that MMG signals are significantly attenuated with increasing thickness of the subcutaneous fat layer.
DOI: 10.6084/m9.figshare.7510448.v1
title: Influence of subcutaneous fat on mechanomyographic signals at three levels of voluntary effort

description: Abstract Introduction This study aims to assess the influence of different skinfold thicknesses (ST) and their relation to the attenuation of the mechanomyographic (MMG) signal at different force levels (maximal voluntary contraction – MVC, 40% of MVC and 70% of MVC) of the rectus femoris muscle. Methods Fifteen volunteers were divided in two groups: ST lower than 10mm (G&lt;10) (8 participants) and ST higher than 35mm (G&gt;35) (7 participants). Student t tests were employed to investigate differences between G&lt;10 and G&gt;35 regarding MMG analysis parameters (acceleration root mean square – aRMS, zero crossing – ZC, and median frequency – MDF), for the X, Y and Z axes, as well as for the modulus of these three axes. Results We found that thicker layers of body fat act as attenuator filters for the MMG signal [MDFMVC: X (p = 0.005), Z (p = 0.003); MDF70%MVC: X (p = 0.034); ZCMVC: Z (p = 0.037), modulus (p = 0.005); ZC70%MVC: Z (p = 0.047)]. We found significant correlation between ST values and aRMS in three levels, in the Yaxis (p = 0.591), for the group G&lt;10. For the modulus, the aRMS value showed correlation with ST values for group G&gt;35 in 40%MVC (R2 = 0.610), and 70%MVC (R2 = 0.592). The MDF parameter showed correlation with ST values only in the Yaxis in 70%MVC (R2 = 0.700) for G&gt;35. Conclusions We observed MMG signal attenuation in at least one of the parameters analyzed for each level of the rectus femoris muscle force, indicating that MMG signals are significantly attenuated with increasing thickness of the subcutaneous fat layer.
DOI: 10.6084/m9.figshare.7508441.v1
title: Reliability of biceps femoris and semitendinosus muscle architecture measurements obtained with ultrasonography

description: Introduction Currently, little attention is given to the muscle architecture reliability studies of the hamstring using a robust statistical. Our purpose was to determine the reliability of ultrasound measurements of muscle thickness, fascicle length and pennation angle of the biceps femoris and semitendinosus muscles, including heteroskedasticity and internal consistency analyses. Methods Two images of biceps femoris and semitendinosus at 50% of the thigh length were acquired from 21 volunteers, in two visits. The parameters were measured three times in each image, and for each muscle. The reliability was analyzed by the intraclass correlation coefficient (ICC) and Cronbach’s alpha (αCronbach). The relative standard error of the measurements (%SEM) were calculated and Bland-Altman plots were generated. Results All parameters presented excellent ICC for the three repeated measurements (ICC from 0.93 ‒ 0.99) and moderate to excellent reliability intraday (ICC from 0.70 ‒ 0.95) for both muscles. The present study indicates that ultrasound is a reliable tool to estimate the biceps femoris fascicle length (ICC = 0.97, αCronbach = 0.98, %SEM = 7.86) and semitendinosus (ICC = 0.90, αCronbach = 0.95, %SEM = 7.55), as well as the biceps femoris muscle thickness (ICC = 0.89, αCronbach = 0.94, %SEM = 10.23) and semitendinosus muscle thickness (ICC = 0.87, αCronbach = 0.93, %SEM = 1.35). At last, biceps femoris pennation angle (ICC = 0.93, αCronbach = 0.96 and %SEM = 4.36) and semitendinosus (ICC = 0.96, αCronbach = 0.98 and %SEM = 4.25) also had good repeatability. Conclusion Ultrasonography show good repeatability in estimating of muscle architecture parameters.
DOI: 10.6084/m9.figshare.7508441
title: Reliability of biceps femoris and semitendinosus muscle architecture measurements obtained with ultrasonography

description: Introduction Currently, little attention is given to the muscle architecture reliability studies of the hamstring using a robust statistical. Our purpose was to determine the reliability of ultrasound measurements of muscle thickness, fascicle length and pennation angle of the biceps femoris and semitendinosus muscles, including heteroskedasticity and internal consistency analyses. Methods Two images of biceps femoris and semitendinosus at 50% of the thigh length were acquired from 21 volunteers, in two visits. The parameters were measured three times in each image, and for each muscle. The reliability was analyzed by the intraclass correlation coefficient (ICC) and Cronbach’s alpha (αCronbach). The relative standard error of the measurements (%SEM) were calculated and Bland-Altman plots were generated. Results All parameters presented excellent ICC for the three repeated measurements (ICC from 0.93 ‒ 0.99) and moderate to excellent reliability intraday (ICC from 0.70 ‒ 0.95) for both muscles. The present study indicates that ultrasound is a reliable tool to estimate the biceps femoris fascicle length (ICC = 0.97, αCronbach = 0.98, %SEM = 7.86) and semitendinosus (ICC = 0.90, αCronbach = 0.95, %SEM = 7.55), as well as the biceps femoris muscle thickness (ICC = 0.89, αCronbach = 0.94, %SEM = 10.23) and semitendinosus muscle thickness (ICC = 0.87, αCronbach = 0.93, %SEM = 1.35). At last, biceps femoris pennation angle (ICC = 0.93, αCronbach = 0.96 and %SEM = 4.36) and semitendinosus (ICC = 0.96, αCronbach = 0.98 and %SEM = 4.25) also had good repeatability. Conclusion Ultrasonography show good repeatability in estimating of muscle architecture parameters.
DOI: 10.6084/m9.figshare.7513790
title: A magneto-motive ultrasound platform designed for pre-clinical and clinical applications

description: Abstract Introduction Magneto-motive ultrasound (MMUS) combines magnetism and ultrasound (US) to detect magnetic nanoparticles in soft tissues. One type of MMUS called shear-wave dispersion magneto-motive ultrasound (SDMMUS) analyzes magnetically induced shear waves (SW) to quantify the elasticity and viscosity of the medium. The lack of an established presets or protocols for pre-clinical and clinical studies currently limits the use of MMUS techniques in the clinical setting. Methods This paper proposes a platform to acquire, process, and analyze MMUS and SDMMUS data integrated with a clinical ultrasound equipment. For this purpose, we developed an easy-to-use graphical user interface, written in C++/Qt4, to create an MMUS pulse sequence and collect the ultrasonic data. We designed a graphic interface written in MATLAB to process, display, and analyze the MMUS images. To exemplify how useful the platform is, we conducted two experiments, namely (i) MMUS imaging to detect magnetic particles in the stomach of a rat, and (ii) SDMMUS to estimate the viscoelasticity of a tissue-mimicking phantom containing a spherical target of ferrite. Results The developed software proved to be an easy-to-use platform to automate the acquisition of MMUS/SDMMUS data and image processing. In an in vivo experiment, the MMUS technique detected an area of 6.32 ± 1.32 mm2 where magnetic particles were heterogeneously distributed in the stomach of the rat. The SDMMUS method gave elasticity and viscosity values of 5.05 ± 0.18 kPa and 2.01 ± 0.09 Pa.s, respectively, for a tissue-mimicking phantom. Conclusion Implementation of an MMUS platform with addressed presets and protocols provides a step toward the clinical implementation of MMUS imaging equipment. This platform may help to localize magnetic particles and quantify the elasticity and viscosity of soft tissues, paving a way for its use in pre-clinical and clinical studies.
DOI: 10.6084/m9.figshare.7513790.v1
title: A magneto-motive ultrasound platform designed for pre-clinical and clinical applications

description: Abstract Introduction Magneto-motive ultrasound (MMUS) combines magnetism and ultrasound (US) to detect magnetic nanoparticles in soft tissues. One type of MMUS called shear-wave dispersion magneto-motive ultrasound (SDMMUS) analyzes magnetically induced shear waves (SW) to quantify the elasticity and viscosity of the medium. The lack of an established presets or protocols for pre-clinical and clinical studies currently limits the use of MMUS techniques in the clinical setting. Methods This paper proposes a platform to acquire, process, and analyze MMUS and SDMMUS data integrated with a clinical ultrasound equipment. For this purpose, we developed an easy-to-use graphical user interface, written in C++/Qt4, to create an MMUS pulse sequence and collect the ultrasonic data. We designed a graphic interface written in MATLAB to process, display, and analyze the MMUS images. To exemplify how useful the platform is, we conducted two experiments, namely (i) MMUS imaging to detect magnetic particles in the stomach of a rat, and (ii) SDMMUS to estimate the viscoelasticity of a tissue-mimicking phantom containing a spherical target of ferrite. Results The developed software proved to be an easy-to-use platform to automate the acquisition of MMUS/SDMMUS data and image processing. In an in vivo experiment, the MMUS technique detected an area of 6.32 ± 1.32 mm2 where magnetic particles were heterogeneously distributed in the stomach of the rat. The SDMMUS method gave elasticity and viscosity values of 5.05 ± 0.18 kPa and 2.01 ± 0.09 Pa.s, respectively, for a tissue-mimicking phantom. Conclusion Implementation of an MMUS platform with addressed presets and protocols provides a step toward the clinical implementation of MMUS imaging equipment. This platform may help to localize magnetic particles and quantify the elasticity and viscosity of soft tissues, paving a way for its use in pre-clinical and clinical studies.
DOI: 10.6084/m9.figshare.7516658.v1
title: Comparative analysis of different doses of coherent light (laser) and non-coherent light (light-emitting diode) on cellular necrosis and apoptosis: a study in vitro

description: Introduction Threshold doses of electromagnetic radiation can initiate necrosis and apoptosis in cells. The purpose of this study was to evaluate cellular apoptosis and necrosis immediately (t0) and 24 hours (t24) after irradiation with different doses of coherent light (laser) or non-coherent light (LED). Methods CHO-K1 lineage cells were irradiated with laser (810nm) or LED (945±20nm), with 24mW, contact area of 1cm2 and doses of 10, 20, 30, 40 and 50J/cm2 for 300, 660, 960, 1230 and 1620s, respectively, at both wavelengths. Cells were evaluated by fluorescence microscopy, differentiating viable, apoptotic and necrotic cells immediately and 24 hours after irradiation. Results The number of necrotic cells at t0 was higher in the LED 40 and 50J/cm2 groups (86±14 and 84±16% respectively, p &lt;0.05), than in the 10 and 20J/cm2 laser (5±2 and 5±3%, p&lt;0.05) and LED (5±3 and 4±1%, p&lt;0.05) conditions. At t24, the LED 40J/cm2 (80±20%, p&lt;0.05) group also showed more necrosis than the control and lower dose groups (laser 10, 20, and 30J/cm2 percentage of 6±4, 10±3 and 7±3%, p&lt;0.05; LED 10 and 20J/cm2 percentage of 3±1 and 17±10%, p&lt;0.05). A decrease in apoptotic cells was observed in the laser group with doses of 10, 40, and 50J/cm2 (6±4, 3±1 and 1±1% respectively, not significant), as well as in the LED 40J/cm2 (2±2%, not significant) group versus control. The cells had a higher percentage of apoptosis cells in the control group and with laser doses of 10 and 30J/cm2 (percentage of 20±1 and 20±4%, not significant), while only the LED 40J/cm2 (10±10%, not significant) had a lower percentage compared the control group. Conclusion Laser or LED stimulation promoted an increase in cell necrosis in a high energy density condition as characterized in a dose-dependent inhibition therapy. Laser or LED infrared irradiation in low doses (up to 20J/cm2) reduced the percentage of apoptosis in CHO-K1 cells, while high doses (30J/cm2) elevated apoptosis.
DOI: 10.6084/m9.figshare.7516658
title: Comparative analysis of different doses of coherent light (laser) and non-coherent light (light-emitting diode) on cellular necrosis and apoptosis: a study in vitro

description: Introduction Threshold doses of electromagnetic radiation can initiate necrosis and apoptosis in cells. The purpose of this study was to evaluate cellular apoptosis and necrosis immediately (t0) and 24 hours (t24) after irradiation with different doses of coherent light (laser) or non-coherent light (LED). Methods CHO-K1 lineage cells were irradiated with laser (810nm) or LED (945±20nm), with 24mW, contact area of 1cm2 and doses of 10, 20, 30, 40 and 50J/cm2 for 300, 660, 960, 1230 and 1620s, respectively, at both wavelengths. Cells were evaluated by fluorescence microscopy, differentiating viable, apoptotic and necrotic cells immediately and 24 hours after irradiation. Results The number of necrotic cells at t0 was higher in the LED 40 and 50J/cm2 groups (86±14 and 84±16% respectively, p &lt;0.05), than in the 10 and 20J/cm2 laser (5±2 and 5±3%, p&lt;0.05) and LED (5±3 and 4±1%, p&lt;0.05) conditions. At t24, the LED 40J/cm2 (80±20%, p&lt;0.05) group also showed more necrosis than the control and lower dose groups (laser 10, 20, and 30J/cm2 percentage of 6±4, 10±3 and 7±3%, p&lt;0.05; LED 10 and 20J/cm2 percentage of 3±1 and 17±10%, p&lt;0.05). A decrease in apoptotic cells was observed in the laser group with doses of 10, 40, and 50J/cm2 (6±4, 3±1 and 1±1% respectively, not significant), as well as in the LED 40J/cm2 (2±2%, not significant) group versus control. The cells had a higher percentage of apoptosis cells in the control group and with laser doses of 10 and 30J/cm2 (percentage of 20±1 and 20±4%, not significant), while only the LED 40J/cm2 (10±10%, not significant) had a lower percentage compared the control group. Conclusion Laser or LED stimulation promoted an increase in cell necrosis in a high energy density condition as characterized in a dose-dependent inhibition therapy. Laser or LED infrared irradiation in low doses (up to 20J/cm2) reduced the percentage of apoptosis in CHO-K1 cells, while high doses (30J/cm2) elevated apoptosis.
DOI: 10.6084/m9.figshare.7518329.v1
title: Approaches to segment stent area from Intravascular Optical Coherence Tomography

description: Abstract Introduction Cardiovascular diseases (CVD) have been the focus of research in recent years due to its high mortality rate. It is estimated that 17.5 million people died of CVD in 2012, from which 7.4 million were due to coronary heart disease (CHD). In order to monitor CHD patients and avoid waste of specialists' time, this study proposes the development of a method that segments the area contained by stent struts from Frequency Domain Intravascular Optical Coherence Tomography (the latest technology to view vessels internally) of coronary arteries. Methods The novelty of this study is to find areas comprised by stent struts using two optimal strategies that are robust even with false positives and false negatives detection of stent struts. The first one uses an ellipse fitting algorithm and the other uses a cylinder fitting algorithm. Results Both strategies obtained similar accuracy results close to 98% of true positives, but the cylinder technique showed a run time of at least 50 times higher than the ellipse technique. Conclusion The methods were executed on 443 images with different characteristics showing robustness and usefulness in the medical area.