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| 1 | Emerging Advances to Transform Histopathology Using Virtual Staining显示文摘In an age where digitization is widespread in clinical and preclinical workflows,pathology is still predominantly practiced by microscopic evaluation of stained tissue specimens affixed on glass slides.Over the last decade,new high throughput digital scanning microscopes have ushered in the era of digital pathology that,along with recent advances in machine vision,have opened up new possibilities for Computer-Aided-Diagnoses.Despite these advances,the high infrastructural costs related to digital pathology and the perception that the digitization process is an additional and nondirectly reimbursable step have challenged its widespread adoption.Here,we discuss how emerging virtual staining technologies and machine learning can help to disrupt the standard histopathology workflow and create new avenues for the diagnostic paradigm that will benefit patients and healthcare systems alike via digital pathology. | Yair Rivenson Kevin de Haan W.Dean Wallace Aydogan Ozcan | 2020 | Biomedical Engineering Frontiers2020，1，1： | 4 |
| 2 | Ultrasound-Mediated Drug Delivery:Sonoporation Mechanisms,Biophysics,and Critical Factors显示文摘Sonoporation,or the use of ultrasound in the presence of cavitation nuclei to induce plasma membrane perforation,is well considered as an emerging physical approach to facilitate the delivery of drugs and genes to living cells.Nevertheless,this emerging drug delivery paradigm has not yet reached widespread clinical use,because the efficiency of sonoporation is often deemed to be mediocre due to the lack of detailed understanding of the pertinent scientific mechanisms.Here,we summarize the current observational evidence available on the notion of sonoporation,and we discuss the prevailing understanding of the physical and biological processes related to sonoporation.To facilitate systematic understanding,we also present how the extent of sonoporation is dependent on a multitude of factors related to acoustic excitation parameters(ultrasound frequency,pressure,cavitation dose,exposure time),microbubble parameters(size,concentration,bubble-to-cell distance,shell composition),and cellular properties(cell type,cell cycle,biochemical contents).By adopting a science-backed approach to the realization of sonoporation,ultrasound-mediated drug delivery can be more controllably achieved to viably enhance drug uptake into living cells with high sonoporation efficiency.This drug delivery approach,when coupled with concurrent advances in ultrasound imaging,has potential to become an effective therapeutic paradigm. | Juan Tu Alfred C.H.Yu | 2022 | Biomedical Engineering Frontiers2022，3，1： | 2 |
| 3 | Recent Advancements in Ultrasound Transducer:From Material Strategies to Biomedical Applications显示文摘Ultrasound is extensively studied for biomedical engineering applications.As the core part of the ultrasonic system,the ultrasound transducer plays a significant role.For the purpose of meeting the requirement of precision medicine,the main challenge for the development of ultrasound transducer is to further enhance its performance.In this article,an overview of recent developments in ultrasound transducer technologies that use a variety of material strategies and device designs based on both the piezoelectric and photoacoustic mechanisms is provided.Practical applications are also presented,including ultrasound imaging,ultrasound therapy,particle/cell manipulation,drug delivery,and nerve stimulation.Finally,perspectives and opportunities are also highlighted. | Jiapu Li Yuqing Ma Tao Zhang KKirk Shung Benpeng Zhu | 2022 | Biomedical Engineering Frontiers2022，3，1： | 2 |
| 4 | Terahertz Imaging and Spectroscopy in Cancer Diagnostics:A Technical Review显示文摘Terahertz(THz)waves are electromagnetic waves with frequency in the range from 0.1 to 10 THz.THz waves have great potential in the biomedical field,especially in cancer diagnosis,because they exhibit low ionization energy and can be used to discern most biomolecules based on their spectral fingerprints.In this paper,we review the recent progress in two applications of THz waves in cancer diagnosis:imaging and spectroscopy.THz imaging is expected to help researchers and doctors attain a direct intuitive understanding of a cancerous area.THz spectroscopy is an efficient tool for component analysis of tissue samples to identify cancer biomarkers.Additionally,the advantages and disadvantages of the developed technologies for cancer diagnosis are discussed.Furthermore,auxiliary techniques that have been used to enhance the spectral signal-to-noise ratio(SNR)are also reviewed. | Yan Peng Chenjun Shi Xu Wu Yiming Zhu Songlin Zhuang | 2020 | Biomedical Engineering Frontiers2020，1，1： | 2 |
| 5 | Functional Photoacoustic and Ultrasonic Assessment of Osteoporosis:A Clinical Feasibility Study显示文摘Objective and Impact Statement.To study the feasibility of combined functional photoacoustic(PA)and quantitative ultrasound(US)for diagnosis of osteoporosis in vivo based on the detection of chemical and microarchitecture(BMA)information in calcaneus bone.Introduction.Clinically available X-ray or US technologies for the diagnosis of osteoporosis do not report important parameters such as chemical information and BMA.With unique advantages,including good sensitivity to molecular and metabolic properties,PA bone assessment techniques hold a great potential for clinical translation.Methods.By performing multiwavelength PA measurements,the chemical information in the human calcaneus bone,including mineral,lipid,oxygenated-hemoglobin,and deoxygenated-hemoglobin,were assessed.In parallel,by performing PA spectrum analysis,the BMA as an important bone physical property was quantified.An unpaired t-test and a two-way ANOVA test were conducted to compare the outcomes from the two subject groups.Results.Multiwavelength PA measurement is capable of assessing the relative contents of several chemical components in the trabecular bone in vivo,including both minerals and organic materials such as oxygenated-hemoglobin,deoxygenated-hemoglobin,and lipid,which are relevant to metabolic activities and bone health.In addition,PA measurements of BMA show good correlations(R^(2)up to 0.65)with DEXA.Both the chemical and microarchitectural measurements from PA techniques can differentiate the two subject groups.Conclusion.The results from this initial clinical study suggest that PA techniques,by providing additional chemical and microarchitecture information relevant to bone health,may lead to accurate and early diagnosis,as well as sensitive monitoring of the treatment of osteoporosis. | Ting Feng Yunhao Zhu Richard Morris Kenneth M.Kozloff Xueding Wang | 2020 | Biomedical Engineering Frontiers2020，1，1： | 2 |
| 6 | Recent Advancements in Optical Harmonic Generation Microscopy: Applications and Perspectives显示文摘Second harmonic generation(SHG)and third harmonic generation(THG)microscopies have emerged as powerful imaging modalities to examine structural properties of a wide range of biological tissues.Although SHG and THG arise from very different contrast mechanisms,the two are complimentary and can often be collected simultaneously using a modified multiphoton microscope.In this review,we discuss the needed instrumentation for these modalities as well as the underlying theoretical principles of SHG and THG in tissue and describe how these can be leveraged to extract unique structural information.We provide an overview of recent advances showing how SHG microscopy has been used to evaluate collagen alterations in the extracellular matrix and how this has been used to advance our knowledge of cancers,fibroses,and the cornea,as well as in tissue engineering applications.Specific examples using polarization-resolved approaches and machine learning algorithms are highlighted.Similarly,we review how THG has enabled developmental biology and skin cancer studies due to its sensitivity to changes in refractive index,which are ubiquitous in all cell and tissue assemblies.Lastly,we offer perspectives and outlooks on future directions of SHG and THG microscopies and present unresolved questions,especially in terms of overall miniaturization and the development of microendoscopy instrumentation. | Darian S.James Paul J.Campagnola | 2021 | Biomedical Engineering Frontiers2021，2，1： | 1 |
| 7 | A Review of Imaging Methods to Assess Ultrasound-Mediated Ablation显示文摘Ultrasound ablation techniques are minimally invasive alternatives to surgical resection and have rapidly increased in use.The response of tissue to HIFU ablation differs based on the relative contributions of thermal and mechanical effects,which can be varied to achieve optimal ablation parameters for a given tissue type and location.In tumor ablation,similar to surgical resection,it is desirable to include a safety margin of ablated tissue around the entirety of the tumor.A factor in optimizing ablative techniques is minimizing the recurrence rate,which can be due to incomplete ablation of the target tissue.Further,combining focal ablation with immunotherapy is likely to be key for effective treatment of metastatic cancer,and therefore characterizing the impact of ablation on the tumor microenvironment will be important.Thus,visualization and quantification of the extent of ablation is an integral component of ablative procedures.The aim of this review article is to describe the radiological findings after ultrasound ablation across multiple imaging modalities.This review presents readers with a general overview of the current and emerging imaging methods to assess the efficacy of ultrasound ablative treatments. | Brett Z.Fite James Wang Pejman Ghanouni Katherine W.Ferrara | 2022 | Biomedical Engineering Frontiers2022，3，1： | 1 |
| 8 | A Low-Cost High-Performance Data Augmentation for Deep Learning-Based Skin Lesion Classification显示文摘Objective and Impact Statement.There is a need to develop high-performance and low-cost data augmentation strategies for intelligent skin cancer screening devices that can be deployed in rural or underdeveloped communities.The proposed strategy can not only improve the classification performance of skin lesions but also highlight the potential regions of interest for clinicians’attention.This strategy can also be implemented in a broad range of clinical disciplines for early screening and automatic diagnosis of many other diseases in low resource settings.Methods.We propose a high-performance data augmentation strategy of search space 101,which can be combined with any model through a plug-and-play mode and search for the best argumentation method for a medical database with low resource cost.Results.With EfficientNets as a baseline,the best BACC of HAM10000 is 0.853,outperforming the other published models of“single-model and no-external-database”for ISIC 2018 Lesion Diagnosis Challenge(Task 3).The best average AUC performance on ISIC 2017 achieves 0.909(±0.015),exceeding most of the ensembling models and those using external datasets.Performance on Derm7pt archives the best BACC of 0.735(±0.018)ahead of all other related studies.Moreover,the model-based heatmaps generated by Grad-CAM++verify the accurate selection of lesion features in model judgment,further proving the scientific rationality of model-based diagnosis.Conclusion.The proposed data augmentation strategy greatly reduces the computational cost for clinically intelligent diagnosis of skin lesions.It may also facilitate further research in low-cost,portable,and AI-based mobile devices for skin cancer screening and therapeutic guidance. | Shuwei Shen Mengjuan Xu Fan Zhang Pengfei Shao Honghong Liu Liang Xu Chi Zhang Peng Liu Peng Yao Ronald X.Xu | 2022 | Biomedical Engineering Frontiers2022，3，1： | 1 |
| 9 | Effects of Histotripsy on Local Tumor Progression in an in vivo Orthotopic Rodent Liver Tumor Model显示文摘Objective and Impact Statement.This is the first longitudinal study investigating the effects of histotripsy on local tumor progression in an in vivo orthotopic,immunocompetent rat hepatocellular carcinoma(HCC)model.Introduction.Histotripsy is the first noninvasive,nonionizing,nonthermal,mechanical ablation technique using ultrasound to generate acoustic cavitation to liquefy the target tissue into acellular debris with millimeter accuracy.Previously,histotripsy has demonstrated in vivo ablation of noncancerous liver tissue.Methods.N1-S1 HCC tumors were generated in the livers of immunocompetent rats(n=6,control;n=15,treatment).Real-time ultrasound-guided histotripsy was applied to ablate either 100%tumor volume+up to 2 mm margin(n=9,complete treatment)or 50-75%tumor volume(n=6,partial treatment)by delivering 1-2 cycle histotripsy pulses at 100 Hz PRF(pulse repetition frequency)with p−≥30 MPa using a custom 1 MHz transducer.Rats were monitored weekly using MRI(magnetic resonance imaging)for 3 months or until tumors reached~25 mm.Results.MRI revealed effective post-histotripsy reduction of tumor burden with near-complete resorption of the ablated tumor in 14/15(93.3%)treated rats.Histopathology showed<5 mm shrunken,non-tumoral,fibrous tissue at the treatment site at 3 months.Rats with increased tumor burden(3/6 control and 1 partial treatment)were euthanized early by 2-4 weeks.In 3 other controls,histology revealed fibrous tissue at original tumor site at 3 months.There was no evidence of histotripsy-induced off-target tissue injury.Conclusion.Complete and partial histotripsy ablation resulted in effective tumor removal for 14/15 rats,with no evidence of local tumor progression or recurrence. | Tejaswi Worlikar Mishal Mendiratta-Lala Eli Vlaisavljevich Ryan Hubbard Jiaqi Shi Timothy L.Hall Clifford S.Cho Fred T.Lee Joan Greve Zhen Xu | 2020 | Biomedical Engineering Frontiers2020，1，1： | 1 |
| 10 | Multimodal Metabolic Imaging Reveals Pigment Reduction and Lipid Accumulation in Metastatic Melanoma显示文摘Objective and Impact Statement.Molecular signatures are needed for early diagnosis and improved treatment of metastatic melanoma.By high-resolution multimodal chemical imaging of human melanoma samples,we identify a metabolic reprogramming from pigmentation to lipid droplet(LD)accumulation in metastatic melanoma.Introduction.Metabolic plasticity promotes cancer survival and metastasis,which promises to serve as a prognostic marker and/or therapeutic target.However,identifying metabolic alterations has been challenged by difficulties in mapping localized metabolites with high spatial resolution.Methods.We developed a multimodal stimulated Raman scattering and pump-probe imaging platform.By time-domain measurement and phasor analysis,our platform allows simultaneous mapping of lipids and pigments at a subcellular level.Furthermore,we identify the sources of these metabolic signatures by tracking deuterium metabolites at a subcellular level.By validation with mass spectrometry,a specific fatty acid desaturase pathway was identified.Results.We identified metabolic reprogramming from a pigment-containing phenotype in low-grade melanoma to an LD-rich phenotype in metastatic melanoma.The LDs contain high levels of cholesteryl ester and unsaturated fatty acids.Elevated fatty acid uptake,but not de novo lipogenesis,contributes to the LD-rich phenotype.Monounsaturated sapienate,mediated by FADS2,is identified as an essential fatty acid that promotes cancer migration.Blocking such metabolic signatures effectively suppresses the migration capacity both in vitro and in vivo.Conclusion.By multimodal spectroscopic imaging and lipidomic analysis,the current study reveals lipid accumulation,mediated by fatty acid uptake,as a metabolic signature that can be harnessed for early diagnosis and improved treatment of metastatic melanoma. | Hyeon Jeong Lee Zhicong Chen Marianne Collard Fukai Chen Jiaji G.Chen Muzhou Wu Rhoda M.Alani Ji-Xin Cheng | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 11 | Label-Free White Blood Cell Classification Using Refractive Index Tomography and Deep Learning显示文摘Objective and Impact Statement.We propose a rapid and accurate blood cell identification method exploiting deep learning and label-free refractive index(RI)tomography.Our computational approach that fully utilizes tomographic information of bone marrow(BM)white blood cell(WBC)enables us to not only classify the blood cells with deep learning but also quantitatively study their morphological and biochemical properties for hematology research.Introduction.Conventional methods for examining blood cells,such as blood smear analysis by medical professionals and fluorescence-activated cell sorting,require significant time,costs,and domain knowledge that could affect test results.While label-free imaging techniques that use a specimen’s intrinsic contrast(e.g.,multiphoton and Raman microscopy)have been used to characterize blood cells,their imaging procedures and instrumentations are relatively time-consuming and complex.Methods.The RI tomograms of the BM WBCs are acquired via Mach-Zehnder interferometer-based tomographic microscope and classified by a 3D convolutional neural network.We test our deep learning classifier for the four types of bone marrow WBC collected from healthy donors(n=10):monocyte,myelocyte,B lymphocyte,and T lymphocyte.The quantitative parameters of WBC are directly obtained from the tomograms.Results.Our results show>99%accuracy for the binary classification of myeloids and lymphoids and>96%accuracy for the four-type classification of B and T lymphocytes,monocyte,and myelocytes.The feature learning capability of our approach is visualized via an unsupervised dimension reduction technique.Conclusion.We envision that the proposed cell classification framework can be easily integrated into existing blood cell investigation workflows,providing cost-effective and rapid diagnosis for hematologic malignancy. | DongHun Ryu Jinho Kim Daejin Lim Hyun-Seok Min In Young Yoo Duck Cho YongKeun Park | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 12 | Recent Advances in Photoacoustic Tomography显示文摘Photoacoustic tomography(PAT)that integrates the molecular contrast of optical imaging with the high spatial resolution of ultrasound imaging in deep tissue has widespread applications in basic biological science,preclinical research,and clinical trials.Recently,tremendous progress has been made in PAT regarding technical innovations,preclinical applications,and clinical translations.Here,we selectively review the recent progresses and advances in PAT,including the development of advanced PAT systems for small-animal and human imaging,newly engineered optical probes for molecular imaging,broad-spectrum PAT for label-free imaging of biological tissues,high-throughput snapshot photoacoustic topography,and integration of machine learning for image reconstruction and processing.We envision that PAT will have further technical developments and more impactful applications in biomedicine. | Lei Li Lihong V.Wang | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 13 | Optical Detection of Distal Lung Enzyme Activity in Human Inflammatory Lung Disease显示文摘Objective and Impact Statement.There is a need to develop platforms delineating inflammatory biology of the distal human lung.We describe a platform technology approach to detect in situ enzyme activity and observe drug inhibition in the distal human lung using a combination of matrix metalloproteinase(MMP)optical reporters,fibered confocal fluorescence microscopy(FCFM),and a bespoke delivery device.Introduction.The development of new therapeutic agents is hindered by the lack of in vivo in situ experimental methodologies that can rapidly evaluate the biological activity or drug-target engagement in patients.Methods.We optimised a novel highly quenched optical molecular reporter of enzyme activity(FIB One)and developed a translational pathway for in-human assessment.Results.We demonstrate the specificity for matrix metalloproteases(MMPs)2,9,and 13 and probe dequenching within physiological levels of MMPs and feasibility of imaging within whole lung models in preclinical settings.Subsequently,in a first-in-human exploratory experimental medicine study of patients with fibroproliferative lung disease,we demonstrate,through FCFM,the MMP activity in the alveolar space measured through FIB One fluorescence increase(with pharmacological inhibition).Conclusion.This translational in situ approach enables a new methodology to demonstrate active drug target effects of the distal lung and consequently may inform therapeutic drug development pathways. | Alicia Megia-Fernandez Adam Marshall Ahsan R.Akram Bethany Mills Sunay V.Chankeshwara Emma Scholefield Amy Miele Bruce C.McGorum Chesney Michaels Nathan Knighton Tom Vercauteren Francois Lacombe Veronique Dentan Annya M.Bruce Joanne Mair Robert Hitchcock Nik Hirani Chris Haslett Mark Bradley Kevin Dhaliwal | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 14 | Real-Time High-Resolution MRI Endoscopy at up to 10 Frames per Second显示文摘Objective.Atherosclerosis is a leading cause of mortality and morbidity.Optical endoscopy,ultrasound,and X-ray offer minimally invasive imaging assessments but have limited sensitivity for characterizing disease and therapeutic response.Magnetic resonance imaging(MRI)endoscopy is a newer idea employing tiny catheter-mounted detectors connected to the MRI scanner.It can see through vessel walls and provide soft-tissue sensitivity,but its slow imaging speed limits practical applications.Our goal is highresolution MRI endoscopy with real-time imaging speeds comparable to existing modalities.Methods.Intravascular(3 mm)transmit-receive MRI endoscopes were fabricated for highly undersampled radial-projection MRI in a clinical 3-tesla MRI scanner.Iterative nonlinear reconstruction was accelerated using graphics processor units connected via a single ethernet cable to achieve true real-time endoscopy visualization at the scanner.MRI endoscopy was performed at 6-10 frames/sec and 200-300μm resolution in human arterial specimens and porcine vessels ex vivo and in vivo and compared with fully sampled 0.3 frames/sec and three-dimensional reference scans using mutual information(MI)and structural similarity(3-SSIM)indices.Results.High-speed MRI endoscopy at 6-10 frames/sec was consistent with fully sampled MRI endoscopy and histology,with feasibility demonstrated in vivo in a large animal model.A 20-30-fold speed-up vs.0.3 frames/sec reference scans came at a cost of~7%in MI and~45%in 3-SSIM,with reduced motion sensitivity.Conclusion.High-resolution MRI endoscopy can now be performed at frame rates comparable to those of X-ray and optical endoscopy and could provide an alternative to existing modalities,with MRI’s advantages of soft-tissue sensitivity and lack of ionizing radiation. | Xiaoyang Liu Parag Karmarkar Dirk Voit Jens Frahm Clifford R.Weiss Dara L.Kraitchman Paul A.Bottomley | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 15 | Bioresorbable Multilayer Photonic Cavities as Temporary Implants for Tether-Free Measurements of Regional Tissue Temperatures显示文摘Objective and Impact Statement.Real-time monitoring of the temperatures of regional tissue microenvironments can serve as the diagnostic basis for treating various health conditions and diseases.Introduction.Traditional thermal sensors allow measurements at surfaces or at near-surface regions of the skin or of certain body cavities.Evaluations at depth require implanted devices connected to external readout electronics via physical interfaces that lead to risks for infection and movement constraints for the patient.Also,surgical extraction procedures after a period of need can introduce additional risks and costs.Methods.Here,we report a wireless,bioresorbable class of temperature sensor that exploits multilayer photonic cavities,for continuous optical measurements of regional,deep-tissue microenvironments over a timeframe of interest followed by complete clearance via natural body processes.Results.The designs decouple the influence of detection angle from temperature on the reflection spectra,to enable high accuracy in sensing,as supported by in vitro experiments and optical simulations.Studies with devices implanted into subcutaneous tissues of both awake,freely moving and asleep animal models illustrate the applicability of this technology for in vivo measurements.Conclusion.The results demonstrate the use of bioresorbable materials in advanced photonic structures with unique capabilities in tracking of thermal signatures of tissue microenvironments,with potential relevance to human healthcare. | Wubin Bai Masahiro Irie Zhonghe Liu Haiwen Luan Daniel Franklin Khizar Nandoliya Hexia Guo Hao Zang Yang Weng Di Lu Di Wu Yixin Wu Joseph Song Mengdi Han Enming Song Yiyuan Yang Xuexian Chen Hangbo Zhao Wei Lu Giuditta Monti Iwona Stepien Irawati Kandela Chad R.Haney Changsheng Wu Sang Min Won Hanjun Ryu Alina Rwei Haixu Shen Jihye Kim Hong-Joon Yoon Wei Ouyang Yihan Liu Emily Suen Huang-yu Chen Jerry Okina Jushen Liang Yonggang Huang Guillermo A.Ameer Weidong Zhou John A.Rogers | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 16 | Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning显示文摘Objective and Impact Statement.Segmentation of blood vessels from two-photon microscopy(2PM)angiograms of brains has important applications in hemodynamic analysis and disease diagnosis.Here,we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups.The technique is computationally efficient,thus ideal for large-scale neurovascular analysis.Introduction.Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature.Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms.In this work,we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms.Methods.We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output.Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702μm.Results.To demonstrate the superior generalizability of our framework,we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning.Overall,our method demonstrates 10×faster computation in terms of voxels-segmented-per-second and 3×larger depth compared to the state-of-the-art.Conclusion.Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature,which consists of deep learning-based vascular segmentation followed by graphing.It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before. | Waleed Tahir Sreekanth Kura Jiabei Zhu Xiaojun Cheng Rafat Damseh Fetsum Tadesse Alex Seibel Blaire S.Lee Frédéric Lesage Sava Sakadžic David A.Boas Lei Tian | 2021 | Biomedical Engineering Frontiers2021，2，1： | 0 |
| 17 | Automated Segmentation and Connectivity Analysis for Normal Pressure Hydrocephalus显示文摘Objective and Impact Statement.We propose an automated method of predicting Normal Pressure Hydrocephalus(NPH)from CT scans.A deep convolutional network segments regions of interest from the scans.These regions are then combined with MRI information to predict NPH.To our knowledge,this is the first method which automatically predicts NPH from CT scans and incorporates diffusion tractography information for prediction.Introduction.Due to their low cost and high versatility,CT scans are often used in NPH diagnosis.No well-defined and effective protocol currently exists for analysis of CT scans for NPH.Evans’index,an approximation of the ventricle to brain volume using one 2D image slice,has been proposed but is not robust.The proposed approach is an effective way to quantify regions of interest and offers a computational method for predicting NPH.Methods.We propose a novel method to predict NPH by combining regions of interest segmented from CT scans with connectome data to compute features which capture the impact of enlarged ventricles by excluding fiber tracts passing through these regions.The segmentation and network features are used to train a model for NPH prediction.Results.Our method outperforms the current state-of-the-art by 9 precision points and 29 recall points.Our segmentation model outperforms the current state-of-the-art in segmenting the ventricle,gray-white matter,and subarachnoid space in CT scans.Conclusion.Our experimental results demonstrate that fast and accurate volumetric segmentation of CT brain scans can help improve the NPH diagnosis process,and network properties can increase NPH prediction accuracy. | Angela Zhang Amil Khan Saisidharth Majeti Judy Pham Christopher Nguyen Peter Tran Vikram Iyer Ashutosh Shelat Jefferson Chen B.S.Manjunath | 2022 | Biomedical Engineering Frontiers2022，3，1： | 0 |
| 18 | A Review of Deep Learning Applications in Lung Ultrasound Imaging of COVID-19 Patients显示文摘The massive and continuous spread of COVID-19 has motivated researchers around the world to intensely explore,understand,and develop new techniques for diagnosis and treatment.Although lung ultrasound imaging is a less established approach when compared to other medical imaging modalities such as X-ray and CT,multiple studies have demonstrated its promise to diagnose COVID-19 patients.At the same time,many deep learning models have been built to improve the diagnostic efficiency of medical imaging.The integration of these initially parallel efforts has led multiple researchers to report deep learning applications in medical imaging of COVID-19 patients,most of which demonstrate the outstanding potential of deep learning to aid in the diagnosis of COVID-19.This invited review is focused on deep learning applications in lung ultrasound imaging of COVID-19 and provides a comprehensive overview of ultrasound systems utilized for data acquisition,associated datasets,deep learning models,and comparative performance. | Lingyi Zhao Muyinatu A.Lediju Bell | 2022 | Biomedical Engineering Frontiers2022，3，1： | 0 |
| 19 | Recent Advances in the Science of Burst Wave Lithotripsy and Ultrasonic Propulsion显示文摘Nephrolithiasis is a common,painful condition that requires surgery in many patients whose stones do not pass spontaneously.Recent technologic advances have enabled the use of ultrasonic propulsion to reposition stones within the urinary tract,either to relieve symptoms or facilitate treatment.Burst wave lithotripsy(BWL)has emerged as a noninvasive technique to fragment stones in awake patients without significant pain or renal injury.We review the preclinical and human studies that have explored the use of these two technologies.We envision that BWL will fill an unmet need for the noninvasive treatment of patients with nephrolithiasis. | Dima Raskolnikov Michael R.Bailey Jonathan D.Harper | 2022 | Biomedical Engineering Frontiers2022，3，1： | 0 |
| 20 | ecent Advances in the Science of Burst Wave Lithotripsy and Ultrasonic Propulsion显示文摘Objective.Retinal degeneration involving progressive deterioration and loss of function of photoreceptors is a major cause of permanent vision loss worldwide.Strategies to treat these incurable conditions incorporate retinal prostheses via electrically stimulating surviving retinal neurons with implanted devices in the eye,optogenetic therapy,and sonogenetic therapy.Existing challenges of these strategies include invasive manner,complex implantation surgeries,and risky gene therapy.Methods and Results.Here,we show that direct ultrasound stimulation on the retina can evoke neuron activities from the visual centers including the superior colliculus and the primary visual cortex(V1),in either normal-sighted or retinal degenerated blind rats in vivo.The neuron activities induced by the customized spherically focused 3.1 MHz ultrasound transducer have shown both good spatial resolution of 250μm and temporal resolution of 5 Hz in the rat visual centers.An additional customized 4.4 MHz helical transducer was further implemented to generate a static stimulation pattern of letter forms.Conclusion.Our findings demonstrate that ultrasound stimulation of the retina in vivo is a safe and effective approach with high spatiotemporal resolution,indicating a promising future of ultrasound stimulation as a novel and noninvasive visual prosthesis for translational applications in blind patients. | Xuejun Qian Gengxi Lu Biju B.Thomas Runze Li Xiaoyang Chen K.Kirk Shung Mark Humayun Qifa Zhou | 2022 | Biomedical Engineering Frontiers2022，3，1： | 0 |
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