Pub Date : 2024-09-27DOI: 10.1109/TBME.2024.3470534
Sharon Haimov;Alissa Tabakhov;Riva Tauman;Joachim A. Behar
Background: Sleep staging is critical for diagnosing sleep disorders. Traditional methods in clinical settings involve time-intensive scoring procedures. Recent advancements in data-driven algorithms using photoplethysmogram (PPG) time series have shown promise in automating sleep staging in adults. However, for children, algorithm development is hindered by the limited availability of datasets, with the Childhood Adenotonsillectomy Trial (CHAT) being the only substantial source, comprising recordings from children aged 5-10. This limitation constrains the evaluation of algorithmic generalization performance. Methods: We employed a deep learning model for sleep staging from PPG, initially trained using a large dataset of adult sleep recordings, and fine-tuned it on 80% of the CHAT dataset (CHAT-train) for the task of three-class sleep staging (wake, REM, non-REM). The resulting algorithm performance was compared to the same model architecture but trained from scratch on CHAT-train (benchmark). The algorithms are evaluated on the local test set, denoted CHAT-test, as well as on a newly introduced independent dataset. Results: Our deep learning algorithm achieved a Cohen's Kappa of 0.88 on CHAT-test (versus 0.65), and demonstrated generalization capabilities with a Kappa of 0.72 on the external Ichilov dataset for children above 5 years old (versus 0.64) and 0.64 for those below 5 (versus 0.53). Significance: This research establishes a new state-of-the-art performance for the task of sleep staging in children using raw PPG. The findings underscore the value of transfer learning from the adults to children domain. However, the reduced performance in children under 5 suggests the need for further research and additional datasets covering a broader pediatric age range to fully address generalization limitations.
{"title":"Deep Learning for Pediatric Sleep Staging From Photoplethysmography: A Transfer Learning Approach From Adults to Children","authors":"Sharon Haimov;Alissa Tabakhov;Riva Tauman;Joachim A. Behar","doi":"10.1109/TBME.2024.3470534","DOIUrl":"10.1109/TBME.2024.3470534","url":null,"abstract":"<italic>Background:</i> Sleep staging is critical for diagnosing sleep disorders. Traditional methods in clinical settings involve time-intensive scoring procedures. Recent advancements in data-driven algorithms using photoplethysmogram (PPG) time series have shown promise in automating sleep staging in adults. However, for children, algorithm development is hindered by the limited availability of datasets, with the Childhood Adenotonsillectomy Trial (CHAT) being the only substantial source, comprising recordings from children aged 5-10. This limitation constrains the evaluation of algorithmic generalization performance. <italic>Methods:</i> We employed a deep learning model for sleep staging from PPG, initially trained using a large dataset of adult sleep recordings, and fine-tuned it on 80% of the CHAT dataset (CHAT-train) for the task of three-class sleep staging (wake, REM, non-REM). The resulting algorithm performance was compared to the same model architecture but trained from scratch on CHAT-train (benchmark). The algorithms are evaluated on the local test set, denoted CHAT-test, as well as on a newly introduced independent dataset. <italic>Results:</i> Our deep learning algorithm achieved a Cohen's Kappa of 0.88 on CHAT-test (versus 0.65), and demonstrated generalization capabilities with a Kappa of 0.72 on the external Ichilov dataset for children above 5 years old (versus 0.64) and 0.64 for those below 5 (versus 0.53). <italic>Significance:</i> This research establishes a new state-of-the-art performance for the task of sleep staging in children using raw PPG. The findings underscore the value of transfer learning from the adults to children domain. However, the reduced performance in children under 5 suggests the need for further research and additional datasets covering a broader pediatric age range to fully address generalization limitations.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"760-767"},"PeriodicalIF":4.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: Endovascular revascularization of peripheral arterial occlusions has a high technical failure rate of 15–20%, mainly due to difficulties in crossing the occlusion with a guidewire. This study evaluates the use of a Picosecond mid-Infrared Laser (PIRL) to facilitate occlusion crossing. Methods: Popliteal artery lesion samples were obtained from a donated limb of a patient with critical limb ischemia (CLI). A customized system advanced the PIRL fiber at controlled speeds toward the occlusion. The fiber was tested with its source OFF and ON at either 500 mW or 1000 mW power, 2.96 µm wavelength, and 1 kHz repetition rate. Lesions were scanned using µ-CT before and after the test, and post-ablated tissues were analyzed histologically. The feasibility of using PIRL with the CathCam, an optical image-guided steerable catheter, was also assessed under X-ray fluoroscopy in an OR suite. Results: Tests showed a significant crossing success improvement with the laser ON vs. OFF (95.6% vs. 73.9%, p <<>Conclusion: PIRL plaque ablation is minimally invasive, and 0.1 mm/s was identified as the optimal fiber advancement speed. Significance: PIRL, guided with CathCam, demonstrates high potential for endovascular revascularization procedures.
{"title":"CathCam-Guided Picosecond Infrared Laser Ablation in Peripheral Artery Disease Revascularization","authors":"Mohammadmahdi Tahmasebi;Rob Reyes Perez;Andrew Marques;Yohannes Soenjaya;Mohammad Khoobani;Mohammadmahdi Keshavarz;Ahmed Kayssi;Andrew Dueck;Darren Kraemer;Christine Demore;R.J. Dwayne Miller;Graham Wright;M. Ali Tavallaei","doi":"10.1109/TBME.2024.3468889","DOIUrl":"10.1109/TBME.2024.3468889","url":null,"abstract":"<italic>Objective:</i> Endovascular revascularization of peripheral arterial occlusions has a high technical failure rate of 15–20%, mainly due to difficulties in crossing the occlusion with a guidewire. This study evaluates the use of a Picosecond mid-Infrared Laser (PIRL) to facilitate occlusion crossing. <italic>Methods</i>: Popliteal artery lesion samples were obtained from a donated limb of a patient with critical limb ischemia (CLI). A customized system advanced the PIRL fiber at controlled speeds toward the occlusion. The fiber was tested with its source OFF and ON at either 500 mW or 1000 mW power, 2.96 µm wavelength, and 1 kHz repetition rate. Lesions were scanned using µ-CT before and after the test, and post-ablated tissues were analyzed histologically. The feasibility of using PIRL with the CathCam, an optical image-guided steerable catheter, was also assessed under X-ray fluoroscopy in an OR suite. <italic>Results</i>: Tests showed a significant crossing success improvement with the laser ON vs. OFF (95.6% vs. 73.9%, p <<>Conclusion</i>: PIRL plaque ablation is minimally invasive, and 0.1 mm/s was identified as the optimal fiber advancement speed. <italic>Significance</i>: PIRL, guided with CathCam, demonstrates high potential for endovascular revascularization procedures.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"725-733"},"PeriodicalIF":4.4,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1109/TBME.2024.3468159
Kenneth N. Aycock;Sabrina N. Campelo;Zaid S. Salameh;Joshua M. K. Davis;David A. Iannitti;Iain H. McKillop;Rafael V. Davalos
Irreversible electroporation (IRE) is a minimally thermal tissue ablation modality used to treat solid tumors adjacent to critical structures. Widespread clinical adoption of IRE has been limited due to complicated anesthetic management requirements and technical demands associated with placing multiple needle electrodes in anatomically challenging environments. High-frequency irreversible electroporation (H-FIRE) delivered using a novel single-insertion bipolar probe system could potentially overcome these limitations, but ablation volumes have remained small using this approach. While H-FIRE is minimally thermal in mode of action, high voltages or multiple pulse trains can lead to unwanted Joule heating. In this work, we improve the H-FIRE waveform design to increase the safe operating voltage using a single-insertion bipolar probe before electrical arcing occurs. By uniformly increasing interphase ($d_{1}$) and interpulse ($d_{2}$) delays, we achieved higher maximum operating voltages for all pulse lengths. Additionally, increasing pulse length led to higher operating voltages up to a certain delay length ($sim$25 μs), after which shorter pulses enabled higher voltages. We then delivered novel H-FIRE waveforms via an actively cooled single-insertion bipolar probe in swine liver in vivo to determine the upper limits to ablation volume possible using a single-needle H-FIRE device. Ablations up to 4.62 $pm$ 0.12 cm x 1.83 $pm$ 0.05 cm were generated in 5 minutes without a requirement for cardiac synchronization during treatment. Ablations were minimally thermal, easily visualized with ultrasound, and stimulated an immune response 24 hours post H-FIRE delivery. These data suggest H-FIRE can rapidly produce clinically relevant, minimally thermal ablations with a more user-friendly electrode design.
{"title":"Toward Large Ablations With Single-Needle High-Frequency Irreversible Electroporation In Vivo","authors":"Kenneth N. Aycock;Sabrina N. Campelo;Zaid S. Salameh;Joshua M. K. Davis;David A. Iannitti;Iain H. McKillop;Rafael V. Davalos","doi":"10.1109/TBME.2024.3468159","DOIUrl":"10.1109/TBME.2024.3468159","url":null,"abstract":"Irreversible electroporation (IRE) is a minimally thermal tissue ablation modality used to treat solid tumors adjacent to critical structures. Widespread clinical adoption of IRE has been limited due to complicated anesthetic management requirements and technical demands associated with placing multiple needle electrodes in anatomically challenging environments. High-frequency irreversible electroporation (H-FIRE) delivered using a novel single-insertion bipolar probe system could potentially overcome these limitations, but ablation volumes have remained small using this approach. While H-FIRE is minimally thermal in mode of action, high voltages or multiple pulse trains can lead to unwanted Joule heating. In this work, we improve the H-FIRE waveform design to increase the safe operating voltage using a single-insertion bipolar probe before electrical arcing occurs. By uniformly increasing interphase (<inline-formula><tex-math>$d_{1}$</tex-math></inline-formula>) and interpulse (<inline-formula><tex-math>$d_{2}$</tex-math></inline-formula>) delays, we achieved higher maximum operating voltages for all pulse lengths. Additionally, increasing pulse length led to higher operating voltages up to a certain delay length (<inline-formula><tex-math>$sim$</tex-math></inline-formula>25 μs), after which shorter pulses enabled higher voltages. We then delivered novel H-FIRE waveforms via an actively cooled single-insertion bipolar probe in swine liver in vivo to determine the upper limits to ablation volume possible using a single-needle H-FIRE device. Ablations up to 4.62 <inline-formula><tex-math>$pm$</tex-math></inline-formula> 0.12 cm x 1.83 <inline-formula><tex-math>$pm$</tex-math></inline-formula> 0.05 cm were generated in 5 minutes without a requirement for cardiac synchronization during treatment. Ablations were minimally thermal, easily visualized with ultrasound, and stimulated an immune response 24 hours post H-FIRE delivery. These data suggest H-FIRE can rapidly produce clinically relevant, minimally thermal ablations with a more user-friendly electrode design.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"705-715"},"PeriodicalIF":4.4,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: Multi-modal MR/CT image segmentation is an important task in disease diagnosis and treatment, but it is usually difficult to acquire aligned multi-modal images of a patient in clinical practice due to the high cost and specific allergic reactions to contrast agents. To address these issues, a task complementation framework is proposed to enable unpaired multi-modal image complementation learning in the training stage and single-modal image segmentation in the inference stage. Method: To fuse unpaired dual-modal images in the training stage and allow single-modal image segmentation in the inference stage, a synthesis-segmentation task complementation network is constructed to mutually facilitate cross-modal image synthesis and segmentation since the same content feature can be used to perform the image segmentation task and image synthesis task. To maintain the consistency of the target organ with varied shapes, a curvature consistency loss is proposed to align the segmentation predictions of the original image and the cross-modal synthesized image. To segment the small lesions or substructures, a regression-segmentation task complementation network is constructed to utilize the auxiliary feature of the target organ. Results: Comprehensive experiments have been performed with an in-house dataset and a publicly available dataset. The experimental results have demonstrated the superiority of our framework over state-of-the-art methods. Conclusion: The proposed method can fuse dual-modal CT/MR images in the training stage and only needs single-modal CT/MR images in the inference stage. Significance: The proposed method can be used in routine clinical occasions when only single-modal CT/MR image is available for a patient.
{"title":"Unpaired Dual-Modal Image Complementation Learning for Single-Modal Medical Image Segmentation","authors":"Dehui Xiang;Tao Peng;Yun Bian;Lang Chen;Jianbin Zeng;Fei Shi;Weifang Zhu;Xinjian Chen","doi":"10.1109/TBME.2024.3467216","DOIUrl":"10.1109/TBME.2024.3467216","url":null,"abstract":"<italic>Objective:</i> Multi-modal MR/CT image segmentation is an important task in disease diagnosis and treatment, but it is usually difficult to acquire aligned multi-modal images of a patient in clinical practice due to the high cost and specific allergic reactions to contrast agents. To address these issues, a task complementation framework is proposed to enable unpaired multi-modal image complementation learning in the training stage and single-modal image segmentation in the inference stage. <italic>Method:</i> To fuse unpaired dual-modal images in the training stage and allow single-modal image segmentation in the inference stage, a synthesis-segmentation task complementation network is constructed to mutually facilitate cross-modal image synthesis and segmentation since the same content feature can be used to perform the image segmentation task and image synthesis task. To maintain the consistency of the target organ with varied shapes, a curvature consistency loss is proposed to align the segmentation predictions of the original image and the cross-modal synthesized image. To segment the small lesions or substructures, a regression-segmentation task complementation network is constructed to utilize the auxiliary feature of the target organ. <italic>Results:</i> Comprehensive experiments have been performed with an in-house dataset and a publicly available dataset. The experimental results have demonstrated the superiority of our framework over state-of-the-art methods. <italic>Conclusion:</i> The proposed method can fuse dual-modal CT/MR images in the training stage and only needs single-modal CT/MR images in the inference stage. <italic>Significance:</i> The proposed method can be used in routine clinical occasions when only single-modal CT/MR image is available for a patient.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"664-674"},"PeriodicalIF":4.4,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1109/TBME.2024.3468351
Haiyun Huang;Jie Chen;Jun Xiao;Di Chen;Jun Zhang;Jiahui Pan;Yuanqing Li
Objective: Attention regulation is an essential ability in daily life that affects learning and work efficiency and is closely related to mental health. The effectiveness of brain-computer interface (BCI) systems in attention regulation has been proven, but most of these systems rely on bulky and expensive equipment and are still in the experimental stage. This study proposes a wearable BCI system for real-time attention regulation and cognitive monitoring. Methods: The BCI system integrates a wearable single-channel electroencephalogram (EEG) headband with wireless data streaming for real-time analysis. Twenty healthy subjects participated in the long-term attention regulation experiment and were evenly divided into an experimental group and a control group based on the presence of real-time neurofeedback. The neurofeedback is represented by output value of attention, which calculated from single-channel EEG data. Before and after the regulation sessions, baseline assessments were conducted for each subject, incorporating multi-channel EEG data analysis and cognitive behavioral evaluations, to verify the effectiveness of system for attention regulation. Results: The online experimental results indicate that the average attention level in the experimental group increased from 0.625 to 0.812, while no significant improvement was observed in the control group. Further comparative analysis revealed the reasons for the enhancement of attention regulation ability in terms of both brain network patterns and cognitive performance. Significance: The proposed wearable BCI system is effective at improving attention regulation ability and could be a promising tool for assisting people with attention disorders.
{"title":"Real-Time Attention Regulation and Cognitive Monitoring Using a Wearable EEG-Based BCI","authors":"Haiyun Huang;Jie Chen;Jun Xiao;Di Chen;Jun Zhang;Jiahui Pan;Yuanqing Li","doi":"10.1109/TBME.2024.3468351","DOIUrl":"10.1109/TBME.2024.3468351","url":null,"abstract":"<italic>Objective:</i> Attention regulation is an essential ability in daily life that affects learning and work efficiency and is closely related to mental health. The effectiveness of brain-computer interface (BCI) systems in attention regulation has been proven, but most of these systems rely on bulky and expensive equipment and are still in the experimental stage. This study proposes a wearable BCI system for real-time attention regulation and cognitive monitoring. <italic>Methods:</i> The BCI system integrates a wearable single-channel electroencephalogram (EEG) headband with wireless data streaming for real-time analysis. Twenty healthy subjects participated in the long-term attention regulation experiment and were evenly divided into an experimental group and a control group based on the presence of real-time neurofeedback. The neurofeedback is represented by output value of attention, which calculated from single-channel EEG data. Before and after the regulation sessions, baseline assessments were conducted for each subject, incorporating multi-channel EEG data analysis and cognitive behavioral evaluations, to verify the effectiveness of system for attention regulation. <italic>Results:</i> The online experimental results indicate that the average attention level in the experimental group increased from 0.625 to 0.812, while no significant improvement was observed in the control group. Further comparative analysis revealed the reasons for the enhancement of attention regulation ability in terms of both brain network patterns and cognitive performance. <italic>Significance:</i> The proposed wearable BCI system is effective at improving attention regulation ability and could be a promising tool for assisting people with attention disorders.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"716-724"},"PeriodicalIF":4.4,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1109/TBME.2024.3467221
Subhrajit Das;Janaka Senarathna;Yunke Ren;Vu Dinh;Mingyao Ying;Ralph Etienne-Cummings;Arvind P. Pathak
Recent advances in low-power wireless-capable system-on-chips (SoCs) have accelerated diverse Internet of Things (IoT) applications, encompassing wearables, asset monitoring, and more. Concurrently, the field of neuroimaging has experienced escalating demand for lightweight, untethered, low-power systems capable of imaging in small animals. This article explores the feasibility of using a low-power asset monitoring system as the basis of a new architecture for fluorescence and hemodynamic contrast-based wireless functional imaging. The core system architecture hinges on the fusion of a Bluetooth Low Energy (BLE) 5.2 SoC and a low-power 560 × 560, 8-bit monochrome CMOS image sensor module. Successful integration of a multicontrast optical front-end consisting of a fluorescence channel (FL) and an intrinsic optical signal (IOS) channel resulted in the creation of a wireless microscope called ‘BLEscope’. Next, we developed a wireless (i.e., BLE) protocol to remotely operate the BLEscope via a laptop and acquire in vivo images at 1 frame per second (fps). We then conducted a comprehensive characterization of the BLEscope to assess its optical capabilities and power consumption. We report a new benchmark for continuous wireless imaging of ∼1.5 hours with a 100 mAh battery. Via the FL channel of the BLEscope, we successfully tracked the kinetics of an intravenously injected fluorescent tracer and acquired images of fluorescent brain tumor cells in vivo. Via the IOS channel, we characterized the differential response of normal and tumor-associated blood vessels to a carbogen gas inhalation challenge. When miniaturized, the BLEscope will result in a new class of low-power, implantable or wireless microscopes that could transform preclinical and clinical neuroimaging applications.
{"title":"BLEscope: A Bluetooth Low Energy (BLE) Microscope for Wireless Multicontrast Functional Imaging","authors":"Subhrajit Das;Janaka Senarathna;Yunke Ren;Vu Dinh;Mingyao Ying;Ralph Etienne-Cummings;Arvind P. Pathak","doi":"10.1109/TBME.2024.3467221","DOIUrl":"10.1109/TBME.2024.3467221","url":null,"abstract":"Recent advances in low-power wireless-capable system-on-chips (SoCs) have accelerated diverse Internet of Things (IoT) applications, encompassing wearables, asset monitoring, and more. Concurrently, the field of neuroimaging has experienced escalating demand for lightweight, untethered, low-power systems capable of imaging in small animals. This article explores the feasibility of using a low-power asset monitoring system as the basis of a new architecture for fluorescence and hemodynamic contrast-based wireless functional imaging. The core system architecture hinges on the fusion of a Bluetooth Low Energy (BLE) 5.2 SoC and a low-power 560 × 560, 8-bit monochrome CMOS image sensor module. Successful integration of a multicontrast optical front-end consisting of a fluorescence channel (FL) and an intrinsic optical signal (IOS) channel resulted in the creation of a wireless microscope called ‘BLEscope’. Next, we developed a wireless (i.e., BLE) protocol to remotely operate the BLEscope via a laptop and acquire in vivo images at 1 frame per second (fps). We then conducted a comprehensive characterization of the BLEscope to assess its optical capabilities and power consumption. We report a new benchmark for continuous wireless imaging of ∼1.5 hours with a 100 mAh battery. Via the FL channel of the BLEscope, we successfully tracked the kinetics of an intravenously injected fluorescent tracer and acquired images of fluorescent brain tumor cells in vivo. Via the IOS channel, we characterized the differential response of normal and tumor-associated blood vessels to a carbogen gas inhalation challenge. When miniaturized, the BLEscope will result in a new class of low-power, implantable or wireless microscopes that could transform preclinical and clinical neuroimaging applications.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"675-688"},"PeriodicalIF":4.4,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1109/TBME.2024.3466929
Huaiming Wang;Wenlong Feng;Xue Ren;Quan Tao;Liangliang Rong;Yiping P. Du;Hui Dong
Objective: In recent years, ultra-low field (ULF) magnetic resonance imaging (MRI) has gained widespread attention due to its advantages, such as low cost, light weight, and portability. However, the low signal-to-noise ratio (SNR) leads to a long scan time. Herein, we study the acceleration performance of parallel imaging (PI) and compressed sensing (CS) in different k-space sampling strategies at 0.12 mT. Methods: This study employs phantoms to assess the efficiency of acceleration methods at ULF MRI, in which signals are detected by ultra-sensitive superconducting quantum interference devices (SQUIDs). We compare the performance of fast Fourier transform (FFT), generalized auto-calibrating partially parallel acquisitions (GRAPPA), and eigenvector-based SPIRiT (ESPIRiT) in Cartesian sampling, while also evaluating non-uniform FFT (NUFFT), GRAPPA operator gridding, and ESPIRiT in non-Cartesian sampling. We design a resolution phantom to investigate the effectiveness of these methods in maintaining image resolution. Results: In Cartesian sampling, GRAPPA and ESPIRiT jointly regularized by total variation and ℓ1-norm (TVJℓ1-ESPIRiT) methods reconstructed good-quality phantom images with an acceleration factor of R = 2. In contrast, TVJℓ1-ESPIRiT exhibited improved image quality and much less signal loss even for R = 4. In radial sampling, TVJℓ1-ESPIRiT reduced the acquisition time to 1.69 minutes at R = 4, with a respective improvement of 12.26 dB in peak SNR compared to NUFFT. The resolution phantom imaging showed that the reconstructions by PI and CS maintained the original resolution of 2 mm. Conclusion and significance: This study improves the practicality of ULF MRI at microtesla fields by implementing imaging acceleration with PI and CS in different k-space sampling.
{"title":"Acquisition Acceleration of Ultra-Low Field MRI With Parallel Imaging and Compressed Sensing in Microtesla Fields","authors":"Huaiming Wang;Wenlong Feng;Xue Ren;Quan Tao;Liangliang Rong;Yiping P. Du;Hui Dong","doi":"10.1109/TBME.2024.3466929","DOIUrl":"10.1109/TBME.2024.3466929","url":null,"abstract":"<italic>Objective:</i> In recent years, ultra<italic>-</i>low field (ULF) magnetic resonance imaging (MRI) has gained widespread attention due to its advantages, such as low cost, light weight, and portability. However, the low signal-to-noise ratio (SNR) leads to a long scan time. Herein, we study the acceleration performance of parallel imaging (PI) and compressed sensing (CS) in different <italic>k</i>-space sampling strategies at 0.12 mT. <italic>Methods:</i> This study employs phantoms to assess the efficiency of acceleration methods at ULF MRI, in which signals are detected by ultra-sensitive superconducting quantum interference devices (SQUIDs). We compare the performance of fast Fourier transform (FFT), generalized auto-calibrating partially parallel acquisitions (GRAPPA), and eigenvector-based SPIRiT (ESPIRiT) in Cartesian sampling, while also evaluating non-uniform FFT (NUFFT), GRAPPA operator gridding, and ESPIRiT in non-Cartesian sampling. We design a resolution phantom to investigate the effectiveness of these methods in maintaining image resolution. <italic>Results:</i> In Cartesian sampling, GRAPPA and ESPIRiT jointly regularized by total variation and <italic>ℓ</i><sup>1</sup>-norm (TVJ<italic>ℓ</i><sup>1</sup>-ESPIRiT) methods reconstructed good-quality phantom images with an acceleration factor of <italic>R =</i> 2. In contrast, TVJ<italic>ℓ</i><sup>1</sup>-ESPIRiT exhibited improved image quality and much less signal loss even for <italic>R =</i> 4. In radial sampling, TVJ<italic>ℓ</i><sup>1</sup>-ESPIRiT reduced the acquisition time to 1.69 minutes at <italic>R =</i> 4, with a respective improvement of 12.26 dB in peak SNR compared to NUFFT. The resolution phantom imaging showed that the reconstructions by PI and CS maintained the original resolution of 2 mm. <italic>Conclusion and significance:</i> This study improves the practicality of ULF MRI at microtesla fields by implementing imaging acceleration with PI and CS in different <italic>k</i>-space sampling.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"655-663"},"PeriodicalIF":4.4,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1109/TBME.2024.3466831
Quentin Goossens;Miguel Locsin;Lori A. Ponder;Michael Chan;Goktug C. Ozmen;Sampath Prahalad;Omer T. Inan
Objective: This study explores the potential of active vibrational sensing as a digital biomarker to identify and characterize inflammatory symptomatology in the Achilles tendon and its entheses in juvenile idiopathic arthritis (JIA), particularly enthesitis related arthritis (ERA), a subcategory of JIA. Methods: Active vibrational data were non-invasively recorded using a miniature coin vibration motor and accelerometer. Twenty active vibration recordings from children diagnosed with JIA were used in the analysis. Machine learning algorithms were leveraged to classify the vibrational signatures according to the corresponding subject groups. Subjects were classified into symptomatic ERA (sxERA), asymptomatic ERA (asxERA), and asymptomatic JIA (non-ERA) (asxNERA) groups based on clinical evaluations and ILAR criteria. Results: Distinct vibrational signatures were observed during tiptoe standing, providing differentiation between subject groups. Feature-based and waveform-based approaches effectively classified the sxERA group against asxNERA and asxERA groups using leave-one-subject-out (LOSO-CV) and 3-fold cross-validation. For the 3-fold cross-validation, the mean accuracies for distinguishing sxERA from asxNERA were 81% (feature-based) and 81% (waveform-based), while the accuracies for discriminating sxERA against asxERA were 73% (feature-based) and 74% (waveform-based). Conclusion: Active vibrational sensing demonstrates promise as a tool for identifying Achilles tendon inflammation in JIA, potentially aiding in early diagnosis and disease monitoring. Significance: Developing active vibrational sensing as a diagnostic modality could address challenges in diagnosing ERA and facilitate timely intervention and personalized care for JIA, potentially enhancing long-term patient outcomes.
{"title":"Active Vibrational Achilles Tendon Sensing for Identifying and Characterizing Inflammatory Symptomatology in Enthesitis Related Arthritis","authors":"Quentin Goossens;Miguel Locsin;Lori A. Ponder;Michael Chan;Goktug C. Ozmen;Sampath Prahalad;Omer T. Inan","doi":"10.1109/TBME.2024.3466831","DOIUrl":"10.1109/TBME.2024.3466831","url":null,"abstract":"<italic>Objective</i>: This study explores the potential of active vibrational sensing as a digital biomarker to identify and characterize inflammatory symptomatology in the Achilles tendon and its entheses in juvenile idiopathic arthritis (JIA), particularly enthesitis related arthritis (ERA), a subcategory of JIA. Methods: Active vibrational data were non-invasively recorded using a miniature coin vibration motor and accelerometer. Twenty active vibration recordings from children diagnosed with JIA were used in the analysis. Machine learning algorithms were leveraged to classify the vibrational signatures according to the corresponding subject groups. Subjects were classified into symptomatic ERA (sxERA), asymptomatic ERA (asxERA), and asymptomatic JIA (non-ERA) (asxNERA) groups based on clinical evaluations and ILAR criteria. Results: Distinct vibrational signatures were observed during tiptoe standing, providing differentiation between subject groups. Feature-based and waveform-based approaches effectively classified the sxERA group against asxNERA and asxERA groups using leave-one-subject-out (LOSO-CV) and 3-fold cross-validation. For the 3-fold cross-validation, the mean accuracies for distinguishing sxERA from asxNERA were 81% (feature-based) and 81% (waveform-based), while the accuracies for discriminating sxERA against asxERA were 73% (feature-based) and 74% (waveform-based). Conclusion: Active vibrational sensing demonstrates promise as a tool for identifying Achilles tendon inflammation in JIA, potentially aiding in early diagnosis and disease monitoring. <italic>Significance</i>: Developing active vibrational sensing as a diagnostic modality could address challenges in diagnosing ERA and facilitate timely intervention and personalized care for JIA, potentially enhancing long-term patient outcomes.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"645-654"},"PeriodicalIF":4.4,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142345821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1109/TBME.2024.3465663
Ramin Farzam;Mohammad Hasan Azad;Hamid Abrishami Moghaddam;Mohamad Forouzanfar
Objective: Our study aims to advance noninvasive blood pressure (BP) monitoring through the introduction of innovative beat-to-beat oscillometric BP estimation methods. We aim to overcome current device limitations by delivering continuous and accurate BP estimates, utilizing physiologically based mathematical models. Methods: We developed novel beat-to-beat oscillometric BP estimation methods based on physiologically grounded mathematical models of intra-arterial BP and the arterial system effect. Our approach includes a recursive Bayesian method for parameter estimation and a new system identification technique to refine initial parameter estimates. We tested our methods through simulations and real-world experiments involving 10 individuals. Results: Mean errors for systolic and diastolic BP were as low as −1.26 mmHg and 2.03 mmHg, respectively, with standard deviations of errors at 5.95 mmHg and 4.16 mmHg. Furthermore, our methods enabled the estimation of additional cardiovascular parameters such as heart rate, respiration rate, and mean arterial pressure. Conclusion: Our novel beat-to-beat oscillometric BP estimation methods offer a significant advancement in noninvasive BP monitoring technology, addressing the limitations of current devices by providing continuous beat-to-beat BP estimates. Significance: Our approach represents a promising direction for improving the reliability and comprehensiveness of cardiovascular parameter estimation in noninvasive BP monitoring devices, facilitating more effective patient care and monitoring.
{"title":"Beat-to-Beat Oscillometric Blood Pressure Estimation: A Bayesian Approach With System Identification","authors":"Ramin Farzam;Mohammad Hasan Azad;Hamid Abrishami Moghaddam;Mohamad Forouzanfar","doi":"10.1109/TBME.2024.3465663","DOIUrl":"10.1109/TBME.2024.3465663","url":null,"abstract":"<italic>Objective:</i> Our study aims to advance noninvasive blood pressure (BP) monitoring through the introduction of innovative beat-to-beat oscillometric BP estimation methods. We aim to overcome current device limitations by delivering continuous and accurate BP estimates, utilizing physiologically based mathematical models. <italic>Methods:</i> We developed novel beat-to-beat oscillometric BP estimation methods based on physiologically grounded mathematical models of intra-arterial BP and the arterial system effect. Our approach includes a recursive Bayesian method for parameter estimation and a new system identification technique to refine initial parameter estimates. We tested our methods through simulations and real-world experiments involving 10 individuals. <italic>Results:</i> Mean errors for systolic and diastolic BP were as low as −1.26 mmHg and 2.03 mmHg, respectively, with standard deviations of errors at 5.95 mmHg and 4.16 mmHg. Furthermore, our methods enabled the estimation of additional cardiovascular parameters such as heart rate, respiration rate, and mean arterial pressure. <italic>Conclusion:</i> Our novel beat-to-beat oscillometric BP estimation methods offer a significant advancement in noninvasive BP monitoring technology, addressing the limitations of current devices by providing continuous beat-to-beat BP estimates. <italic>Significance:</i> Our approach represents a promising direction for improving the reliability and comprehensiveness of cardiovascular parameter estimation in noninvasive BP monitoring devices, facilitating more effective patient care and monitoring.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"619-629"},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1109/TBME.2024.3466550
Yi Lin;Dallan McMahon;Ryan M. Jones;Kullervo Hynynen
Focused ultrasound (FUS) combined with circulating microbubbles (MBs) can be employed for non-invasive, localized agent delivery across the blood-brain barrier (BBB). Previous work has demonstrated the feasibility of clinical-scale transmit-receive phased arrays for performing transcranial therapies under MB imaging feedback. Objective: This study aimed to design, construct, and evaluate a dual-mode phased array for MB-mediated FUS brain therapy in small animals. Methods: A 256-element sparse hemispherical array (100 mm diameter) was fabricated by installing 128 PZT cylinder transmitters (f0 = 1.16 MHz) and 128 broadband PVDF receivers within a 3D-printed scaffold. Results: The transmit array's focal size at the geometric focus was 0.8 mm × 0.8 mm × 1.7 mm, with a 31 mm/27 mm (lateral/axial) steering range. The receive array's point spread function was 0.6 mm × 0.6 mm × 1.5 mm (1.16 MHz source) at the geometric focus, and sources were localized up to 30 mm/16 mm (lateral/axial) from geometric focus. The array was able to spatially map MB cloud activity in 3D throughout a vessel-mimicking phantom at sub-, ultra-, and second-harmonic frequencies. Preliminary in-vivo work demonstrated its ability to induce localized BBB permeability changes under 3D sub-harmonic MB imaging feedback in a mouse model. Conclusion: Small form factor transmit-receive phased arrays enable acoustic imaging-controlled FUS and MB-mediated brain therapies with high targeting precision required for rodent studies. Significance: Dual-mode phased arrays dedicated for small animal use will facilitate high-throughput studies of FUS-mediated BBB permeability enhancement to explore novel therapeutic strategies for future clinical application.
{"title":"A Transmit-Receive Phased Array for Microbubble-Mediated Focused Ultrasound Brain Therapy in Small Animals","authors":"Yi Lin;Dallan McMahon;Ryan M. Jones;Kullervo Hynynen","doi":"10.1109/TBME.2024.3466550","DOIUrl":"10.1109/TBME.2024.3466550","url":null,"abstract":"Focused ultrasound (FUS) combined with circulating microbubbles (MBs) can be employed for non-invasive, localized agent delivery across the blood-brain barrier (BBB). Previous work has demonstrated the feasibility of clinical-scale transmit-receive phased arrays for performing transcranial therapies under MB imaging feedback. <italic>Objective:</i> This study aimed to design, construct, and evaluate a dual-mode phased array for MB-mediated FUS brain therapy in small animals. <italic>Methods:</i> A 256-element sparse hemispherical array (100 mm diameter) was fabricated by installing 128 PZT cylinder transmitters (f<sub>0</sub> = 1.16 MHz) and 128 broadband PVDF receivers within a 3D-printed scaffold. <italic>Results:</i> The transmit array's focal size at the geometric focus was 0.8 mm × 0.8 mm × 1.7 mm, with a 31 mm/27 mm (lateral/axial) steering range. The receive array's point spread function was 0.6 mm × 0.6 mm × 1.5 mm (1.16 MHz source) at the geometric focus, and sources were localized up to 30 mm/16 mm (lateral/axial) from geometric focus. The array was able to spatially map MB cloud activity in 3D throughout a vessel-mimicking phantom at sub-, ultra-, and second-harmonic frequencies. Preliminary <italic>in-vivo</i> work demonstrated its ability to induce localized BBB permeability changes under 3D sub-harmonic MB imaging feedback in a mouse model. <italic>Conclusion:</i> Small form factor transmit-receive phased arrays enable acoustic imaging-controlled FUS and MB-mediated brain therapies with high targeting precision required for rodent studies. <italic>Significance:</i> Dual-mode phased arrays dedicated for small animal use will facilitate high-throughput studies of FUS-mediated BBB permeability enhancement to explore novel therapeutic strategies for future clinical application.","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"72 2","pages":"630-644"},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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