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Ashikuzzaman M, Peng B, Jiang J, Rivaz H. Alternating direction method of multipliers for displacement estimation in ultrasound strain elastography. Med Phys 2024; 51:3521-3540. [PMID: 38159299 DOI: 10.1002/mp.16921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/11/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Ultrasound strain imaging, which delineates mechanical properties to detect tissue abnormalities, involves estimating the time delay between two radio-frequency (RF) frames collected before and after tissue deformation. The existing regularized optimization-based time-delay estimation (TDE) techniques suffer from at least one of the following drawbacks: (1) The regularizer is not aligned with the tissue deformation physics due to taking only the first-order displacement derivative into account; (2) TheL 2 $L2$ -norm of the displacement derivatives, which oversmooths the estimated time-delay, is utilized as the regularizer; (3) The modulus function defined mathematically should be approximated by a smooth function to facilitate the optimization ofL 1 $L1$ -norm. PURPOSE Our purpose is to develop a novel TDE technique that resolves the aforementioned shortcomings of the existing algorithms. METHODS Herein, we propose employing the alternating direction method of multipliers (ADMM) for optimizing a novel cost function consisting ofL 2 $L2$ -norm data fidelity term andL 1 $L1$ -norm first- and second-order spatial continuity terms. ADMM empowers the proposed algorithm to use different techniques for optimizing different parts of the cost function and obtain high-contrast strain images with smooth backgrounds and sharp boundaries. We name our technique ADMM for totaL variaTion RegUlarIzation in ultrasound STrain imaging (ALTRUIST). ALTRUIST's efficacy is quantified using absolute error (AE), Structural SIMilarity (SSIM), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and strain ratio (SR) with respect to GLUE, OVERWIND, andL 1 $L1$ -SOUL, three recently published energy-based techniques, and UMEN-Net, a state-of-the-art deep learning-based algorithm. Analysis of variance (ANOVA)-led multiple comparison tests and paired t $t$ -tests at5 % $5\%$ overall significance level were conducted to assess the statistical significance of our findings. The Bonferroni correction was taken into account in all statistical tests. Two simulated layer phantoms, three simulated resolution phantoms, one hard-inclusion simulated phantom, one multi-inclusion simulated phantom, one experimental breast phantom, and three in vivo liver cancer datasets have been used for validation experiments. We have published the ALTRUIST code at http://code.sonography.ai. RESULTS ALTRUIST substantially outperforms the four state-of-the-art benchmarks in all validation experiments, both qualitatively and quantitatively. ALTRUIST yields up to573 % ∗ ${573\%}^{*}$ ,41 % ∗ ${41\%}^{*}$ , and51 % ∗ ${51\%}^{*}$ SNR improvements and443 % ∗ ${443\%}^{*}$ ,53 % ∗ ${53\%}^{*}$ , and15 % ∗ ${15\%}^{*}$ CNR improvements overL 1 $L1$ -SOUL, its closest competitor, for simulated, phantom, and in vivo liver cancer datasets, respectively, where the asterisk (*) indicates statistical significance. In addition, ANOVA-led multiple comparison tests and paired t $t$ -tests indicate that ALTRUIST generally achieves statistically significant improvements over GLUE, UMEN-Net, OVERWIND, andL 1 $L1$ -SOUL in terms of AE, SSIM map, SNR, and CNR. CONCLUSIONS A novel ultrasonic displacement tracking algorithm named ALTRUIST has been developed. The principal novelty of ALTRUIST is incorporating ADMM for optimizing anL 1 $L1$ -norm regularization-based cost function. ALTRUIST exhibits promising performance in simulation, phantom, and in vivo experiments.
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Affiliation(s)
- Md Ashikuzzaman
- Department of Electrical and Computer Engineering, Concordia University, Montreal, Québec, Canada
| | - Bo Peng
- School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, China
| | - Jingfeng Jiang
- Department of Biomedical Engineering, Michigan Technological University, Houghton, Michigan, USA
| | - Hassan Rivaz
- Department of Electrical and Computer Engineering, Concordia University, Montreal, Québec, Canada
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Cihan A, Holko K, Wei L, Vos HJ, Debbaut C, Caenen A, Segers P. Effect of interstitial fluid pressure on shear wave elastography: an experimental and computational study. Phys Med Biol 2024; 69:075001. [PMID: 38412537 DOI: 10.1088/1361-6560/ad2d80] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/27/2024] [Indexed: 02/29/2024]
Abstract
Objective. An elevated interstitial fluid pressure (IFP) can lead to strain-induced stiffening of poroelastic biological tissues. As shear wave elastography (SWE) measures functional tissue stiffness based on the propagation speed of acoustically induced shear waves, the shear wave velocity (SWV) can be used as an indirect measurement of the IFP. The underlying biomechanical principle for this stiffening behavior with pressurization is however not well understood, and we therefore studied how IFP affects SWV through SWE experiments and numerical modeling.Approach. For model set-up and verification, SWE experiments were performed while dynamically modulating IFP in a chicken breast. To identify the confounding factors of the SWV-IFP relationship, we manipulated the material model (linear poroelastic versus porohyperelastic), deformation assumptions (geometric linearity versus nonlinearity), and boundary conditions (constrained versus unconstrained) in a finite element model mimicking the SWE experiments.Main results. The experiments demonstrated a statistically significant positive correlation between the SWV and IFP. The model was able to reproduce a similar SWV-IFP relationship by considering an unconstrained porohyperelastic tissue. Material nonlinearity was identified as the primary factor contributing to this relationship, whereas geometric nonlinearity played a smaller role. The experiments also highlighted the importance of the dynamic nature of the pressurization procedure, as indicated by a different observed SWV-IFP for pressure buildup and relaxation, but its clinical relevance needs to be further investigated.Significance. The developed model provides an adaptable framework for SWE of poroelastic tissues and paves the way towards non-invasive measurements of IFP.
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Affiliation(s)
- Ariana Cihan
- Institute of Biomedical Engineering and Technology, Ghent University, Ghent, Belgium
| | - Kristyna Holko
- Institute of Biomedical Engineering and Technology, Ghent University, Ghent, Belgium
- Department of Structural Engineering, Norwegian University of Science and Technology, Trondheim, Norway
| | - Luxi Wei
- Cardiovascular Institute, Thorax Center, Department of Cardiology, Erasmus MC, Rotterdam, The Netherlands
| | - Hendrik J Vos
- Cardiovascular Institute, Thorax Center, Department of Cardiology, Erasmus MC, Rotterdam, The Netherlands
| | - Charlotte Debbaut
- Institute of Biomedical Engineering and Technology, Ghent University, Ghent, Belgium
| | - Annette Caenen
- Institute of Biomedical Engineering and Technology, Ghent University, Ghent, Belgium
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Patrick Segers
- Institute of Biomedical Engineering and Technology, Ghent University, Ghent, Belgium
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Salavati H, Pullens P, Debbaut C, Ceelen W. Hydraulic conductivity of human cancer tissue: A hybrid study. Bioeng Transl Med 2024; 9:e10617. [PMID: 38435818 PMCID: PMC10905546 DOI: 10.1002/btm2.10617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 09/22/2023] [Accepted: 10/15/2023] [Indexed: 03/05/2024] Open
Abstract
Background Elevated tumor tissue interstitial fluid pressure (IFP) is an adverse biomechanical biomarker that predicts poor therapy response and an aggressive phenotype. Advances in functional imaging have opened the prospect of measuring IFP non-invasively. Image-based estimation of the IFP requires knowledge of the tissue hydraulic conductivity (K), a measure for the ease of bulk flow through the interstitium. However, data on the magnitude of K in human cancer tissue are not available. Methods We measured the hydraulic conductivity of tumor tissue using modified Ussing chambers in surgical resection specimens. The effect of the tumor microenvironment (TME) on K was investigated by quantifying the collagen content, cell density, and fibroblast density of the tested samples using quantitative immune histochemistry. Also, we developed a computational fluid dynamics (CFD) model to evaluate the role of K on interstitial fluid flow and drug transport in solid tumors. Results The results show that the hydraulic conductivity of human tumor tissues is very limited, ranging from approximately 10-15 to 10-14 m2/Pa∙s. Moreover, K values varied significantly between tumor types and between different samples from the same tumor. A significant inverse correlation was found between collagen fiber density and hydraulic conductivity values. However, no correlation was detected between K and cancer cell or fibroblast densities. The computational model demonstrated the impact of K on the interstitial fluid flow and the drug concentration profile: higher K values led to a lower IFP and deeper drug penetration. Conclusions Human tumor tissue is characterized by a very limited hydraulic conductivity, representing a barrier to effective drug transport. The results of this study can inform the development of realistic computational models, facilitate non-invasive IFP estimation, and contribute to stromal targeting anticancer therapies.
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Affiliation(s)
- Hooman Salavati
- Department of Human Structure and RepairGhent UniversityGhentBelgium
- IBiTech–BioMMedA, Ghent UniversityGhentBelgium
- Cancer Research Institute Ghent (CRIG)GhentBelgium
| | - Pim Pullens
- Department of RadiologyUniversity Hospital GhentGhentBelgium
- Ghent Institute of Functional and Metabolic Imaging (GIFMI)Ghent UniversityGhentBelgium
- IBiTech–Medisip, Ghent UniversityGhentBelgium
| | - Charlotte Debbaut
- IBiTech–BioMMedA, Ghent UniversityGhentBelgium
- Cancer Research Institute Ghent (CRIG)GhentBelgium
| | - Wim Ceelen
- Department of Human Structure and RepairGhent UniversityGhentBelgium
- Cancer Research Institute Ghent (CRIG)GhentBelgium
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4
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Laurie MA, Zhou SR, Islam MT, Shkolyar E, Xing L, Liao JC. Bladder Cancer and Artificial Intelligence: Emerging Applications. Urol Clin North Am 2024; 51:63-75. [PMID: 37945103 PMCID: PMC10697017 DOI: 10.1016/j.ucl.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Bladder cancer is a common and heterogeneous disease that poses a significant burden to the patient and health care system. Major unmet needs include effective early detection strategy, imprecision of risk stratification, and treatment-associated morbidities. The existing clinical paradigm is imprecise, which results in missed tumors, suboptimal therapy, and disease progression. Artificial intelligence holds immense potential to address many unmet needs in bladder cancer, including early detection, risk stratification, treatment planning, quality assessment, and outcome prediction. Despite recent advances, extensive work remains to affirm the efficacy of artificial intelligence as a decision-making tool for bladder cancer management.
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Affiliation(s)
- Mark A Laurie
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA; Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive Room G204, Stanford, CA 94305-5847, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA; Institute for Computational and Mathematical Engineering, Stanford University School of Engineering, Stanford, CA 94305, USA
| | - Steve R Zhou
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA
| | - Md Tauhidul Islam
- Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive Room G204, Stanford, CA 94305-5847, USA
| | - Eugene Shkolyar
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA
| | - Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive Room G204, Stanford, CA 94305-5847, USA
| | - Joseph C Liao
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA.
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Akinpelu A, Akinsipe T, Avila LA, Arnold RD, Mistriotis P. The impact of tumor microenvironment: unraveling the role of physical cues in breast cancer progression. Cancer Metastasis Rev 2024:10.1007/s10555-024-10166-x. [PMID: 38238542 DOI: 10.1007/s10555-024-10166-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/02/2024] [Indexed: 01/30/2024]
Abstract
Metastasis accounts for the vast majority of breast cancer-related fatalities. Although the contribution of genetic and epigenetic modifications to breast cancer progression has been widely acknowledged, emerging evidence underscores the pivotal role of physical stimuli in driving breast cancer metastasis. In this review, we summarize the changes in the mechanics of the breast cancer microenvironment and describe the various forces that impact migrating and circulating tumor cells throughout the metastatic process. We also discuss the mechanosensing and mechanotransducing molecules responsible for promoting the malignant phenotype in breast cancer cells. Gaining a comprehensive understanding of the mechanobiology of breast cancer carries substantial potential to propel progress in prognosis, diagnosis, and patient treatment.
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Affiliation(s)
- Ayuba Akinpelu
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, 36849, USA
| | - Tosin Akinsipe
- Department of Biological Sciences, College of Science and Mathematics, Auburn University, Auburn, AL, 36849, USA
| | - L Adriana Avila
- Department of Biological Sciences, College of Science and Mathematics, Auburn University, Auburn, AL, 36849, USA
| | - Robert D Arnold
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, Auburn, AL, 36849, USA
| | - Panagiotis Mistriotis
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, 36849, USA.
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Zhang S, Grifno G, Passaro R, Regan K, Zheng S, Hadzipasic M, Banerji R, O'Connor L, Chu V, Kim SY, Yang J, Shi L, Karrobi K, Roblyer D, Grinstaff MW, Nia HT. Intravital measurements of solid stresses in tumours reveal length-scale and microenvironmentally dependent force transmission. Nat Biomed Eng 2023; 7:1473-1492. [PMID: 37640900 PMCID: PMC10836235 DOI: 10.1038/s41551-023-01080-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/19/2023] [Indexed: 08/31/2023]
Abstract
In cancer, solid stresses impede the delivery of therapeutics to tumours and the trafficking and tumour infiltration of immune cells. Understanding such consequences and the origin of solid stresses requires their probing in vivo at the cellular scale. Here we report a method for performing volumetric and longitudinal measurements of solid stresses in vivo, and findings from its applicability to tumours. We used multimodal intravital microscopy of fluorescently labelled polyacrylamide beads injected in breast tumours in mice as well as mathematical modelling to compare solid stresses at the single-cell and tissue scales, in primary and metastatic tumours, in vitro and in mice, and in live mice and post-mortem tissue. We found that solid-stress transmission is scale dependent, with tumour cells experiencing lower stresses than their embedding tissue, and that tumour cells in lung metastases experience substantially higher solid stresses than those in the primary tumours. The dependence of solid stresses on length scale and the microenvironment may inform the development of therapeutics that sensitize cancer cells to such mechanical forces.
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Affiliation(s)
- Sue Zhang
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Gabrielle Grifno
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Rachel Passaro
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Kathryn Regan
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Siyi Zheng
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Muhamed Hadzipasic
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Rohin Banerji
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Logan O'Connor
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Vinson Chu
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Sung Yeon Kim
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Jiarui Yang
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Linzheng Shi
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Kavon Karrobi
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Darren Roblyer
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Mark W Grinstaff
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Department of Chemistry, Boston University, Boston, MA, USA
| | - Hadi T Nia
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
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Tang S, Weiner B, Taraballi F, Haase C, Stetco E, Mehta SM, Shajudeen P, Hogan M, De Rosa E, Horner PJ, Grande-Allen KJ, Shi Z, Karmonik C, Tasciotti E, Righetti R. Assessment of spinal cord injury using ultrasound elastography in a rabbit model in vivo. Sci Rep 2023; 13:15323. [PMID: 37714920 PMCID: PMC10504274 DOI: 10.1038/s41598-023-41172-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 08/23/2023] [Indexed: 09/17/2023] Open
Abstract
The effect of the mechanical micro-environment on spinal cord injury (SCI) and treatment effectiveness remains unclear. Currently, there are limited imaging methods that can directly assess the localized mechanical behavior of spinal cords in vivo. In this study, we apply new ultrasound elastography (USE) techniques to assess SCI in vivo at the site of the injury and at the time of one week post injury, in a rabbit animal model. Eleven rabbits underwent laminectomy procedures. Among them, spinal cords of five rabbits were injured during the procedure. The other six rabbits were used as control. Two neurological statuses were achieved: non-paralysis and paralysis. Ultrasound data were collected one week post-surgery and processed to compute strain ratios. Histologic analysis, mechanical testing, magnetic resonance imaging (MRI), computerized tomography and MRI diffusion tensor imaging (DTI) were performed to validate USE results. Strain ratios computed via USE were found to be significantly different in paralyzed versus non-paralyzed rabbits. The myelomalacia histologic score and spinal cord Young's modulus evaluated in selected animals were in good qualitative agreement with USE assessment. It is feasible to use USE to assess changes in the spinal cord of the presented animal model. In the future, with more experimental data available, USE may provide new quantitative tools for improving SCI diagnosis and prognosis.
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Affiliation(s)
- Songyuan Tang
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Bradley Weiner
- Orthopedics and Sports Medicine, Houston Methodist Hospital, Houston, TX, USA
| | - Francesca Taraballi
- Orthopedics and Sports Medicine, Houston Methodist Hospital, Houston, TX, USA
- Department of Orthopedics and Sports Medicine, Center for Musculoskeletal Regeneration, Houston Methodist Hospital, Houston, TX, USA
| | - Candice Haase
- Orthopedics and Sports Medicine, Houston Methodist Hospital, Houston, TX, USA
- Department of Orthopedics and Sports Medicine, Center for Musculoskeletal Regeneration, Houston Methodist Hospital, Houston, TX, USA
| | - Eliana Stetco
- Orthopedics and Sports Medicine, Houston Methodist Hospital, Houston, TX, USA
- Department of Orthopedics and Sports Medicine, Center for Musculoskeletal Regeneration, Houston Methodist Hospital, Houston, TX, USA
| | | | - Peer Shajudeen
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Matthew Hogan
- Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist Research Institute, Houston, TX, USA
| | - Enrica De Rosa
- Orthopedics and Sports Medicine, Houston Methodist Hospital, Houston, TX, USA
- Department of Orthopedics and Sports Medicine, Center for Musculoskeletal Regeneration, Houston Methodist Hospital, Houston, TX, USA
| | - Philip J Horner
- Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist Research Institute, Houston, TX, USA
| | | | - Zhaoyue Shi
- Translational Imaging Center, Houston Methodist Research Institute, Houston, TX, USA
| | - Christof Karmonik
- Translational Imaging Center, Houston Methodist Research Institute, Houston, TX, USA
| | - Ennio Tasciotti
- Department of Human Sciences and Promotion of Quality of Life, San Raffaele Roma Open University and IRCCS San Raffaele Pisana, 00166, Rome, Italy
| | - Raffaella Righetti
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
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Majumder S, Islam MT, Righetti R. Non-invasive imaging of interstitial fluid transport parameters in solid tumors in vivo. Sci Rep 2023; 13:7132. [PMID: 37130836 PMCID: PMC10154396 DOI: 10.1038/s41598-023-33651-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 04/17/2023] [Indexed: 05/04/2023] Open
Abstract
In this paper, new and non-invasive imaging methods to assess interstitial fluid transport parameters in tumors in vivo are developed, analyzed and experimentally validated. These parameters include extracellular volume fraction (EVF), interstitial fluid volume fraction (IFVF) and interstitial hydraulic conductivity (IHC), and they are known to have a critical role in cancer progression and drug delivery effectiveness. EVF is defined as the volume of extracellular matrix per unit volume of the tumor, while IFVF refers to the volume of interstitial fluid per unit bulk volume of the tumor. There are currently no established imaging methods to assess interstitial fluid transport parameters in cancers in vivo. We develop and test new theoretical models and imaging techniques to assess fluid transport parameters in cancers using non-invasive ultrasound methods. EVF is estimated via the composite/mixture theory with the tumor being modeled as a biphasic (cellular phase and extracellular phase) composite material. IFVF is estimated by modeling the tumor as a biphasic poroelastic material with fully saturated solid phase. Finally, IHC is estimated from IFVF using the well-known Kozeny-Carman method inspired by soil mechanics theory. The proposed methods are tested using both controlled experiments and in vivo experiments on cancers. The controlled experiments were performed on tissue mimic polyacrylamide samples and validated using scanning electron microscopy (SEM). In vivo applicability of the proposed methods was demonstrated using a breast cancer model implanted in mice. Based on the controlled experimental validation, the proposed methods can estimate interstitial fluid transport parameters with an error below 10% with respect to benchmark SEM data. In vivo results demonstrate that EVF, IFVF and IHC increase in untreated tumors whereas these parameters are observed to decrease over time in treated tumors. The proposed non-invasive imaging methods may provide new and cost-effective diagnostic and prognostic tools to assess clinically relevant fluid transport parameters in cancers in vivo.
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Affiliation(s)
- Sharmin Majumder
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Md Tauhidul Islam
- Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA
| | - Raffaella Righetti
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA.
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9
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Identification and Validation of Common Reference Genes for Normalization of Esophageal Squamous Cell Carcinoma Gene Expression Profiles. BIOMED RESEARCH INTERNATIONAL 2022; 2022:9125242. [DOI: 10.1155/2022/9125242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/27/2022]
Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the subtypes of esophageal cancer with Chinese characteristics, and its five-year survival rate is less than 20%. Early diagnosis is beneficial to improving the survival rate of ESCC significantly. Quantitative Real-Time Polymerase Chain Reaction is a high-throughput technique that can quantify tumor-related genes for early diagnosis. Its accuracy largely depends on the stability of the reference gene. There is no systematic scientific basis to demonstrate which reference gene expression is stable in ESCC and no consensus on the selection of internal reference. Therefore, this research used four software programs (The comparative delta-Ct method, GeNorm, NormFinder, and BestKeeper) to evaluate the expression stability of eight candidate reference genes commonly used in other tumor tissues and generated a comprehensive analysis by RefFinder. Randomly selected transcriptome sequencing analysis confirmed the SPP1 gene is closely related to ESCC. It was found that the expression trend of SPP1 obtained by RPS18 and PPIA as internal reference genes were the same as that of sequencing. The results show that RPS18 and PPIA are stable reference genes, and PPIA + RPS18 are a suitable reference gene combination. This is a reference gene report that combines transcriptome sequencing analysis and only focuses on ESCC, which makes the quantification more precise, systematic, and standardized, and promotes gene regulation research and the early diagnosis of ESCC in the future.
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10
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Salavati H, Debbaut C, Pullens P, Ceelen W. Interstitial fluid pressure as an emerging biomarker in solid tumors. Biochim Biophys Acta Rev Cancer 2022; 1877:188792. [PMID: 36084861 DOI: 10.1016/j.bbcan.2022.188792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/12/2022] [Accepted: 08/30/2022] [Indexed: 11/28/2022]
Abstract
The physical microenvironment of cancer is characterized by elevated stiffness and tissue pressure, the main component of which is the interstitial fluid pressure (IFP). Elevated IFP is an established negative predictive and prognostic parameter, directly affecting malignant behavior and therapy response. As such, measurement of the IFP would allow to develop strategies aimed at engineering the physical microenvironment of cancer. Traditionally, IFP measurement required the use of invasive methods. Recent progress in dynamic and functional imaging methods such as dynamic contrast enhanced (DCE) magnetic resonance imaging and elastography, combined with numerical models and simulation, allows to comprehensively assess the biomechanical landscape of cancer, and may help to overcome physical barriers to drug delivery and immune cell infiltration. Here, we provide a comprehensive overview of the origin of elevated IFP, and its role in the malignant phenotype. Also, we review the methods used to measure IFP using invasive and imaging based methods, and highlight remaining obstacles and potential areas of progress in order to implement IFP measurement in clinical practice.
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Affiliation(s)
- Hooman Salavati
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium; IBitech- Biommeda, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Charlotte Debbaut
- IBitech- Biommeda, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Pim Pullens
- Department of Radiology, Ghent University Hospital, Ghent, Belgium; Ghent Institute of Functional and Metabolic Imaging (GIFMI), Ghent University, Ghent, Belgium; IBitech- Medisip, Ghent University, Ghent, Belgium
| | - Wim Ceelen
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium.
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11
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A spatiotemporal multi-scale computational model for FDG PET imaging at different stages of tumor growth and angiogenesis. Sci Rep 2022; 12:10062. [PMID: 35710559 PMCID: PMC9203789 DOI: 10.1038/s41598-022-13345-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 05/09/2022] [Indexed: 01/07/2023] Open
Abstract
A deeper understanding of the tumor microenvironment (TME) and its role in metabolic activity at different stages of vascularized tumors can provide useful insights into cancer progression and better support clinical assessments. In this study, a robust and comprehensive multi-scale computational model for spatiotemporal transport of F-18 fluorodeoxyglucose (FDG) is developed to incorporate important aspects of the TME, spanning subcellular-, cellular-, and tissue-level scales. Our mathematical model includes biophysiological details, such as radiopharmaceutical transport within interstitial space via convection and diffusion mechanisms, radiopharmaceutical exchange between intracellular and extracellular matrices by glucose transporters, cellular uptake of radiopharmaceutical, as well as its intracellular phosphorylation by the enzyme. Further, to examine the effects of tumor size by varying microvascular densities (MVDs) on FDG dynamics, four different capillary networks are generated by angiogenesis modeling. Results demonstrate that as tumor grows, its MVD increases, and hence, the spatiotemporal distribution of total FDG uptake by tumor tissue changes towards a more homogenous distribution. In addition, spatiotemporal distributions in tumor with lower MVD have relatively smaller magnitudes, due to the lower diffusion rate of FDG as well as lower local intravenous FDG release. Since mean standardized uptake value (SUVmean) differs at various stages of microvascular networks with different tumor sizes, it may be meaningful to normalize the measured values by tumor size and the MVD prior to routine clinical reporting. Overall, the present framework has the potential for more accurate investigation of biological phenomena within TME towards personalized medicine.
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