<i>Objective and Impact Statement</i>. 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. <i>Introduction</i>. 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. <i>Methods</i>. 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 <svg xmlns="http://www.w3.org/2000/svg" id="M1" style="vertical-align:-2.73183pt" height="11.467pt" version="1.1" viewBox="-0.0498162 -8.73517 102.552 11.467" width="102.552pt">


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</svg>. <i>Results</i>. 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. <i>Conclusion</i>. 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

Fr&#x00E9;d&#x00E9;ric Lesage

Sava Sakad&#x017E;ic

David A. Boas

Lei Tian

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Understanding how brain activity encodes information and controls behavior is a long-standing question in neuroscience. This complex problem requires converging efforts from neuroscience and engineering, including technological solutions to perform high-precision and large-scale recordings of neuronal activity <i>in vivo</i> as well as unbiased methods to reliably measure and quantify behavior. Thanks to advances in genetics, molecular biology, engineering, and neuroscience, in recent decades, a variety of optical imaging and electrophysiological approaches for recording neuronal activity in awake animals have been developed and widely applied in the field. Moreover, sophisticated computer vision and machine learning algorithms have been developed to analyze animal behavior. In this review, we provide an overview of the current state of technology for neuronal recordings with a focus on optical and electrophysiological methods in rodents. In addition, we discuss areas that future technological development will need to cover in order to further our understanding of the neural activity underlying behavior.

Richard H. Roth

Jun B. Ding

From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior

<i>Objective and Impact Statement</i>. This is the first longitudinal study investigating the effects of histotripsy on local tumor progression in an <i>in vivo</i> orthotopic, immunocompetent rat hepatocellular carcinoma (HCC) model. <i>Introduction</i>. 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 <i>in vivo</i> ablation of noncancerous liver tissue. <i>Methods</i>. N1-S1 HCC tumors were generated in the livers of immunocompetent rats (<svg xmlns="http://www.w3.org/2000/svg" id="M1" style="vertical-align:-0.1688595pt" height="8.90403pt" version="1.1" viewBox="-0.0498162 -8.73517 28.7695 8.90403" width="28.7695pt">


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</svg>, complete treatment) or 50-75% tumor volume (<svg xmlns="http://www.w3.org/2000/svg" id="M5" style="vertical-align:-0.1688595pt" height="8.90403pt" version="1.1" viewBox="-0.0498162 -8.73517 28.7695 8.90403" width="28.7695pt">


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</svg>, partial treatment) by delivering 1-2 cycle histotripsy pulses at 100 Hz PRF (pulse repetition frequency) with <svg xmlns="http://www.w3.org/2000/svg" id="M6" style="vertical-align:-2.73183pt" height="11.467pt" version="1.1" viewBox="-0.0498162 -8.73517 44.0096 11.467" width="44.0096pt">


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</svg> 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. <i>Results</i>. 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 &lt;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. <i>Conclusion</i>. 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

Effects of Histotripsy on Local Tumor Progression in an <i>in vivo</i> Orthotopic Rodent Liver Tumor Model

<i>Objective and Impact Statement</i>. To study the feasibility of combined functional photoacoustic (PA) and quantitative ultrasound (US) for diagnosis of osteoporosis <i>in vivo</i> based on the detection of chemical and microarchitecture (BMA) information in calcaneus bone. <i>Introduction</i>. 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. <i>Methods</i>. 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 <svg xmlns="http://www.w3.org/2000/svg" id="M1" style="vertical-align:-0.1876597pt" height="7.43768pt" version="1.1" viewBox="-0.0498162 -7.25002 5.2507 7.43768" width="5.2507pt">


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</svg>-test and a two-way ANOVA test were conducted to compare the outcomes from the two subject groups. <i>Results</i>. Multiwavelength PA measurement is capable of assessing the relative contents of several chemical components in the trabecular bone <i>in vivo</i>, 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 (<svg xmlns="http://www.w3.org/2000/svg" id="M2" style="vertical-align:-0.04979992pt" height="10.5659pt" version="1.1" viewBox="-0.0498162 -10.5161 13.4942 10.5659" width="13.4942pt">


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</svg> up to 0.65) with DEXA. Both the chemical and microarchitectural measurements from PA techniques can differentiate the two subject groups. <i>Conclusion</i>. 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

Functional Photoacoustic and Ultrasonic Assessment of Osteoporosis: A Clinical Feasibility Study

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

Terahertz Imaging and Spectroscopy in Cancer Diagnostics: A Technical Review

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

Emerging Advances to Transform Histopathology Using Virtual Staining

<i>Objective</i>. The goal is to increase the precision of radiation delivery during radiotherapy by tracking the movements of the tumor and other surrounding normal tissues due to respiratory and other body motions. <i>Introduction</i>. This work presents the recent advancement of X-ray-induced radiation acoustic imaging (xRAI) technology and the evaluation of its feasibility for real-time monitoring of geometric and morphological misalignments of the X-ray field with respect to the target tissue by combining xRAI with established ultrasound (US) imaging, thereby improving radiotherapy tumor eradication and limiting treatment side effects. <i>Methods</i>. An integrated xRAI and B-mode US dual-modality system was established based on a clinic-ready research US platform. The performance of this dual-modality imaging system was evaluated via experiments on phantoms and ex <i>vivo</i> and <i>in vivo</i> rabbit liver models. <i>Results</i>. This system can alternatively switch between the xRAI and the US modes, with spatial resolutions of 1.1&#x2009;mm and 0.37&#x2009;mm, respectively. 300 times signal averaging was required for xRAI to reach a satisfactory signal-to-noise ratio, and a frame rate of 1.1&#x2009;Hz was achieved with a clinical linear accelerator. The US imaging frame rate was 22&#x2009;Hz, which is sufficient for real-time monitoring of the displacement of the target due to internal body motion. <i>Conclusion</i>. Our developed xRAI, in combination with US imaging, allows for mapping of the dose deposition in biological samples <i>in vivo</i>, in real-time, during radiotherapy. <i>Impact Statement</i>. The US-based image-guided radiotherapy system presented in this work holds great potential for personalized cancer treatment and better outcomes.

Wei Zhang

Ibrahim Oraiqat

Hao Lei

Paul L. Carson

Issam EI Naqa

Dual-Modality X-Ray-Induced Radiation Acoustic and Ultrasound Imaging for Real-Time Monitoring of Radiotherapy

Xingde Li

Guoqi Zhang

Yuguo Tang

BME Frontiers: A Platform for Engineering the Future of Biomedicine

About this journal

<p>The open access journal <em>BME Frontiers</em>, published in association with SIBET CAS, is a platform for the multidisciplinary community of biomedical engineering, publishing wide-ranging research in the field.</p>


Journal profile

Meet the editorial board

<p><em>BME Frontiers'</em> editorial board is led by Xingde Li&nbsp;(Johns Hopkins University), Yuguo Tang&nbsp;(Suzhou Institute of Biomedical Engineering and Technology), and&nbsp;Guoqi Zhang&nbsp;(Delft University of Technology) and is comprised of leading experts in the field of biomedical engineering.</p>


Editorial board

More special issue details

<p><em>BME Frontiers</em> is now considering submissions for its first&nbsp;<br />
special issue:</p>

<p>&nbsp;</p>

<p><a href="https://spj.sciencemag.org/bme-frontiers-special-issues/advanced-optical-imaging/"><strong>Advanced Optical Imaging for Biomedicine</strong></a></p>

<p>&nbsp;</p>

<p>&nbsp;</p>
