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Abdollahi H, Yousefirizi F, Shiri I, Brosch-Lenz J, Mollaheydar E, Fele-Paranj A, Shi K, Zaidi H, Alberts I, Soltani M, Uribe C, Saboury B, Rahmim A. Theranostic digital twins: Concept, framework and roadmap towards personalized radiopharmaceutical therapies. Theranostics 2024; 14:3404-3422. [PMID: 38948052 PMCID: PMC11209714 DOI: 10.7150/thno.93973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Accepted: 04/22/2024] [Indexed: 07/02/2024] Open
Abstract
Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with several RPTs already well established in the treatment of several different types of cancers. However, the current approaches to RPTs often follow a somewhat inflexible "one size fits all" paradigm, where patients are administered the same amount of radioactivity per cycle regardless of their individual characteristics and features. This approach fails to consider inter-patient variations in radiopharmacokinetics, radiation biology, and immunological factors, which can significantly impact treatment outcomes. To address this limitation, we propose the development of theranostic digital twins (TDTs) to personalize RPTs based on actual patient data. Our proposed roadmap outlines the steps needed to create and refine TDTs that can optimize radiation dose to tumors while minimizing toxicity to organs at risk. The TDT models incorporate physiologically-based radiopharmacokinetic (PBRPK) models, which are additionally linked to a radiobiological optimizer and an immunological modulator, taking into account factors that influence RPT response. By using TDT models, we envisage the ability to perform virtual clinical trials, selecting therapies towards improved treatment outcomes while minimizing risks associated with secondary effects. This framework could empower practitioners to ultimately develop tailored RPT solutions for subgroups and individual patients, thus improving the precision, accuracy, and efficacy of treatments while minimizing risks to patients. By incorporating TDT models into RPTs, we can pave the way for a new era of precision medicine in cancer treatment.
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Affiliation(s)
- Hamid Abdollahi
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | | | - Isaac Shiri
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
- Department of Cardiology, University Hospital Bern, Switzerland
| | - Julia Brosch-Lenz
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Elahe Mollaheydar
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Biomedical Engineering, University of British Columbia, Vancouver, Canada
| | - Ali Fele-Paranj
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Biomedical Engineering, University of British Columbia, Vancouver, Canada
- Department of Mathematics, University of British Columbia, Vancouver, Canada
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Informatics, Technical University of Munich, Munich, Germany
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark
- University Research and Innovation Center, Óbuda University, Budapest, Hungary
| | - Ian Alberts
- Department of Molecular Imaging and Therapy, BC Cancer, Vancouver, Canada
| | - Madjid Soltani
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
- Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada
| | - Carlos Uribe
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Molecular Imaging and Therapy, BC Cancer, Vancouver, Canada
| | - Babak Saboury
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, USA
| | - Arman Rahmim
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Biomedical Engineering, University of British Columbia, Vancouver, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
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Piranfar A, Moradi Kashkooli F, Zhan W, Bhandari A, Saboury B, Rahmim A, Soltani M. Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model. NPJ Syst Biol Appl 2024; 10:39. [PMID: 38609421 PMCID: PMC11015041 DOI: 10.1038/s41540-024-00362-4] [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: 09/01/2023] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open
Abstract
Lutetium-177 prostate-specific membrane antigen (177Lu-PSMA)-targeted radiopharmaceutical therapy is a clinically approved treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Even though common practice reluctantly follows "one size fits all" approach, medical community believes there is significant room for deeper understanding and personalization of radiopharmaceutical therapies. To pursue this aim, we present a 3-dimensional spatiotemporal radiopharmaceutical delivery model based on clinical imaging data to simulate pharmacokinetic of 177Lu-PSMA within the prostate tumors. The model includes interstitial flow, radiopharmaceutical transport in tissues, receptor cycles, association/dissociation with ligands, synthesis of PSMA receptors, receptor recycling, internalization of radiopharmaceuticals, and degradation of receptors and drugs. The model was studied for a range of values for injection amount (100-1000 nmol), receptor density (10-500 nmol•l-1), and recycling rate of receptors (10-4 to 10-1 min-1). Furthermore, injection type, different convection-diffusion-reaction mechanisms, characteristic time scales, and length scales are discussed. The study found that increasing receptor density, ligand amount, and labeled ligands improved radiopharmaceutical uptake in the tumor. A high receptor recycling rate (0.1 min-1) increased radiopharmaceutical concentration by promoting repeated binding to tumor cell receptors. Continuous infusion results in higher radiopharmaceutical concentrations within tumors compared to bolus administration. These insights are crucial for advancing targeted therapy for prostate cancer by understanding the mechanism of radiopharmaceutical distribution in tumors. Furthermore, measures of characteristic length and advection time scale were computed. The presented spatiotemporal tumor transport model can analyze different physiological parameters affecting 177Lu-PSMA delivery.
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Affiliation(s)
- Anahita Piranfar
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | | | - Wenbo Zhan
- School of Engineering, King's College, University of Aberdeen, Aberdeen, AB24 3UE, UK
| | - Ajay Bhandari
- Biofluids Research Lab, Department of Mechanical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, India
| | - Babak Saboury
- Department of Computational Nuclear Oncology, Institute of Nuclear Medicine, Bethesda, MD, USA
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
| | - Arman Rahmim
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
- Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, Canada
| | - M Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada.
- Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada.
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Tehrani MHH, Moradi Kashkooli F, Soltani M. Effect of tumor heterogeneity on enhancing drug delivery to vascularized tumors using thermo-sensitive liposomes triggered by hyperthermia: A multi-scale and multi-physics computational model. Comput Biol Med 2024; 170:108050. [PMID: 38308872 DOI: 10.1016/j.compbiomed.2024.108050] [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: 08/31/2023] [Revised: 01/16/2024] [Accepted: 01/26/2024] [Indexed: 02/05/2024]
Abstract
In this study, a novel multi-scale and multi-physics image-based computational model is introduced to assess the delivery of doxorubicin (Dox) loaded temperature-sensitive liposomes (TSLs) in the presence of hyperthermia. Unlike previous methodologies, this approach incorporates capillary network geometry extracted from images, resulting in a more realistic physiological tumor model. This model holds significant promise in advancing personalized medicine by integrating patient-specific tumor properties. The finite element method is employed to solve the equations governing intravascular and interstitial fluid flows, as well as the transport of therapeutic agents within the tissue. Realistic biological conditions and intricate processes like intravascular pressure, drug binding to cells, and cellular uptake are also considered to enhance the model's accuracy. The results underscore the significant impact of vascular architecture on treatment outcomes. Variation in vascular network pattern yielded changes of up to 38 % in the fraction of killed cells (FKCs) parameter under identical conditions. Pressure control of the parent vessels can also improve FKCs by approximately 17 %. Tailoring the treatment plan based on tumor-specific parameters emerged as a critical factor influencing treatment efficacy. For instance, changing the time interval between the administration of Dox-loaded TSLs and hyperthermia can result in a 48 % improvement in treatment outcomes. Additionally, devising a customized heating schedule led to a 20 % increase in treatment efficacy. Our proposed model highlights the significant effect of tumor characteristics and vascular network structure on the final treatment outcomes of the presented combination treatment.
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Affiliation(s)
- Masoud H H Tehrani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.
| | | | - M Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran; Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada; Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada.
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Dayong N. A global solution to a hyperbolic problem for blood flow modelling. Biosystems 2024; 237:105160. [PMID: 38382825 DOI: 10.1016/j.biosystems.2024.105160] [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: 12/08/2023] [Revised: 02/19/2024] [Accepted: 02/19/2024] [Indexed: 02/23/2024]
Abstract
The paper aims to examine the hyperbolic system of equations governing one-dimensional haemodynamics and its relevance in analysing blood flow under mechanical influences, with particular emphasis on the impact of altering the angle of the leg axis. Methods and approaches for solving hyperbolic equations have been developed in light of their properties and characteristics. The primary objective of this study was to investigate the interplay between vein pressure, pulse wave velocity, and vascular distension. The study revealed an inverse relationship between vein pressure and pulse wave velocity. A decrease in pulse wave velocity occurs when vein pressure rises, and vice versa. Both real measurements and modelling results confirmed this dependence. The pressure in the veins is between 10.8 and 13.6 kPa, and the speed of the pulse wave is between 0.061 and 0.27 kPa. The agreement between real and model data was high. The modelled venous pressure and pulse wave velocity values are close to the actual values. However, it is essential to acknowledge the limitations of this paper. These limitations include the utilisation of one-dimensional haemodynamic models, which fail to consider the three-dimensional structure of the circulatory system. Additionally, the analysis is restricted to examining changes solely in the leg axis angle. The research helps to clarify the relationship between mechanical actions and haemodynamic parameters. The findings may help research and develop new methods for identifying and treating conditions associated with the cardiovascular system.
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Affiliation(s)
- Nie Dayong
- Department of Science & Technology, Yellow River Conservancy Technical Institute, Kaifeng, Henan Province, China.
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Piranfar A, Soltani M, Kashkooli FM, Uribe CF, Rahmim A. Spatiotemporal modeling of radiopharmaceutical transport in solid tumors: Application to 177Lu-PSMA therapy of prostate cancer. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 245:108004. [PMID: 38215660 DOI: 10.1016/j.cmpb.2023.108004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/14/2023] [Accepted: 12/31/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND AND OBJECTIVE 177Lu-labeled prostate-specific membrane antigen (PSMA) radiopharmaceutical therapy (RPT) represents a pivotal advancement in addressing prostate cancer. However, existing therapies, while promising, remain incompletely understood and optimized. Computational models offer potential insights into RPTs, aiding in clinical drug delivery enhancement. In this study, we investigate the impact of various physiological parameters on the delivery of 177Lu-PSMA-617 RPT using the convection-diffusion-reaction (CDR) model. METHODS Our investigation encompasses tumor geometry and surrounding tissue, characterized by well-defined boundaries and initial conditions. Utilizing the finite element method, we solve governing equations across a range of parameters: dissociation constant KD (1, 0.1, 0.01 [nM]), internalization rate (0.01-0.0001 [min-1]), diverse tumor shapes, and variable necrotic zone sizes. This model can provide an accurate analysis of radiopharmaceutical delivery from the injection site to the tumor cell, including drug transport in the vascular, interstitial, and intracellular spaces, and considering important parameters (e.g., drug extravasation from microvessels or to lymphatic vessels, the extracellular matrix, receptors, and intracellular space). RESULTS Our findings reveal significant enhancements in tumor-absorbed doses as KD decreases. This outcome can be attributed to the higher affinity of radiopharmaceuticals for PSMA receptors as KD diminishes, facilitating a more efficient binding and retention of the therapeutic agent within the tumor microenvironment. Additionally, tumor-absorbed doses for KD ∼ 1 [nM] show an upward trend with higher internalization rates. This observation can be rationalized by considering that a greater internalization rate would result in a higher proportion of radiopharmaceuticals being taken up by tumor cells after binding to receptors on the cell surface. Notably, tumor shape and necrotic zone size exhibit limited influence on tumor absorbed dose. CONCLUSIONS The present study employs the CDR model to explore the role of physiological parameters in shaping 177Lu-PSMA-617 RPT delivery. These findings provide insights for improving prostate cancer therapy by understanding radiopharmaceutical transport dynamics. This computational approach contributes to advancing our understanding of radiopharmaceutical delivery mechanisms and has implications for enhancing treatment efficacy.
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Affiliation(s)
- Anahita Piranfar
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | - M Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran; Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada; Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
| | - Farshad M Kashkooli
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | - Carlos F Uribe
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada; Functional Imaging, BC Cancer, Vancouver, BC, Canada; Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Arman Rahmim
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada; Functional Imaging, BC Cancer, Vancouver, BC, Canada; Department of Radiology, University of British Columbia, Vancouver, BC, Canada
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Piranfar A, Souri M, Rahmim A, Soltani M. Localized radiotherapy of solid tumors using radiopharmaceutical loaded implantable system: insights from a mathematical model. Front Oncol 2024; 14:1320371. [PMID: 38559559 PMCID: PMC10979490 DOI: 10.3389/fonc.2024.1320371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/06/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Computational models yield valuable insights into biological interactions not fully elucidated by experimental approaches. This study investigates an innovative spatiotemporal model for simulating the controlled release and dispersion of radiopharmaceutical therapy (RPT) using 177Lu-PSMA, a prostate-specific membrane antigen (PSMA) targeted radiopharmaceutical, within solid tumors via a dual-release implantable delivery system. Local delivery of anticancer agents presents a strategic approach to mitigate adverse effects while optimizing therapeutic outcomes. Methods This study evaluates various factors impacting RPT efficacy, including hypoxia region extension, binding affinity, and initial drug dosage, employing a novel 3-dimensional computational model. Analysis gauges the influence of these factors on radiopharmaceutical agent concentration within the tumor microenvironment. Furthermore, spatial and temporal radiopharmaceutical distribution within both the tumor and surrounding tissue is explored. Results Analysis indicates a significantly higher total concentration area under the curve within the tumor region compared to surrounding normal tissue. Moreover, drug distribution exhibits notably superior efficacy compared to the radiation source. Additionally, low microvascular density in extended hypoxia regions enhances drug availability, facilitating improved binding to PSMA receptors and enhancing therapeutic effectiveness. Reductions in the dissociation constant (KD) lead to heightened binding affinity and increased internalized drug concentration. Evaluation of initial radioactivities (7.1×107, 7.1×108, and 7.1×109 [Bq]) indicates that an activity of 7.1×108 [Bq] offers a favorable balance between tumor cell elimination and minimal impact on normal tissues. Discussion These findings underscore the potential of localized radiopharmaceutical delivery strategies and emphasize the crucial role of released drugs relative to the radiation source (implant) in effective tumor treatment. Decreasing the proximity of the drug to the microvascular network and enhancing its distribution within the tumor promote a more effective therapeutic outcome. The study furnishes valuable insights for future experimental investigations and clinical trials, aiming to refine medication protocols and minimize reliance on in vivo testing.
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Affiliation(s)
- Anahita Piranfar
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | - Mohammad Souri
- Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
| | - Madjid Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
- Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada
- Centre for Sustainable Business, International Business University, Toronto, ON, Canada
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Moradi Kashkooli F, Hornsby TK, Kolios MC, Tavakkoli JJ. Ultrasound-mediated nano-sized drug delivery systems for cancer treatment: Multi-scale and multi-physics computational modeling. WILEY INTERDISCIPLINARY REVIEWS. NANOMEDICINE AND NANOBIOTECHNOLOGY 2024; 16:e1913. [PMID: 37475577 DOI: 10.1002/wnan.1913] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 05/18/2023] [Accepted: 05/30/2023] [Indexed: 07/22/2023]
Abstract
Computational modeling enables researchers to study and understand various complex biological phenomena in anticancer drug delivery systems (DDSs), especially nano-sized DDSs (NSDDSs). The combination of NSDDSs and therapeutic ultrasound (TUS), that is, focused ultrasound and low-intensity pulsed ultrasound, has made significant progress in recent years, opening many opportunities for cancer treatment. Multiple parameters require tuning and optimization to develop effective DDSs, such as NSDDSs, in which mathematical modeling can prove advantageous. In silico computational modeling of ultrasound-responsive DDS typically involves a complex framework of acoustic interactions, heat transfer, drug release from nanoparticles, fluid flow, mass transport, and pharmacodynamic governing equations. Owing to the rapid development of computational tools, modeling the different phenomena in multi-scale complex problems involved in drug delivery to tumors has become possible. In the present study, we present an in-depth review of recent advances in the mathematical modeling of TUS-mediated DDSs for cancer treatment. A detailed discussion is also provided on applying these computational models to improve the clinical translation for applications in cancer treatment. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.
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Affiliation(s)
| | - Tyler K Hornsby
- Department of Physics, Toronto Metropolitan University, Toronto, Ontario, Canada
| | - Michael C Kolios
- Department of Physics, Toronto Metropolitan University, Toronto, Ontario, Canada
- Institute for Biomedical Engineering, Science and Technology (iBEST), Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Jahangir Jahan Tavakkoli
- Department of Physics, Toronto Metropolitan University, Toronto, Ontario, Canada
- Institute for Biomedical Engineering, Science and Technology (iBEST), Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada
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8
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Souri M, Kiani Shahvandi M, Chiani M, Moradi Kashkooli F, Farhangi A, Mehrabi MR, Rahmim A, Savage VM, Soltani M. Stimuli-sensitive nano-drug delivery with programmable size changes to enhance accumulation of therapeutic agents in tumors. Drug Deliv 2023; 30:2186312. [PMID: 36895188 PMCID: PMC10013474 DOI: 10.1080/10717544.2023.2186312] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023] Open
Abstract
Nano-based drug delivery systems hold significant promise for cancer therapies. Presently, the poor accumulation of drug-carrying nanoparticles in tumors has limited their success. In this study, based on a combination of the paradigms of intravascular and extravascular drug release, an efficient nanosized drug delivery system with programmable size changes is introduced. Drug-loaded smaller nanoparticles (secondary nanoparticles), which are loaded inside larger nanoparticles (primary nanoparticles), are released within the microvascular network due to temperature field resulting from focused ultrasound. This leads to the scale of the drug delivery system decreasing by 7.5 to 150 times. Subsequently, smaller nanoparticles enter the tissue at high transvascular rates and achieve higher accumulation, leading to higher penetration depths. In response to the acidic pH of tumor microenvironment (according to the distribution of oxygen), they begin to release the drug doxorubicin at very slow rates (i.e., sustained release). To predict the performance and distribution of therapeutic agents, a semi-realistic microvascular network is first generated based on a sprouting angiogenesis model and the transport of therapeutic agents is then investigated based on a developed multi-compartment model. The results show that reducing the size of the primary and secondary nanoparticles can lead to higher cell death rate. In addition, tumor growth can be inhibited for a longer time by enhancing the bioavailability of the drug in the extracellular space. The proposed drug delivery system can be very promising in clinical applications. Furthermore, the proposed mathematical model is applicable to broader applications to predict the performance of drug delivery systems.
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Affiliation(s)
- Mohammad Souri
- Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran
| | | | - Mohsen Chiani
- Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran
| | | | - Ali Farhangi
- Department of NanoBiotechnology, Pasteur Institute of Iran, Tehran, Iran
| | | | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, British Columbia, Canada
| | - Van M Savage
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, USA.,Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Santa Fe Institute, Santa Fe, New Mexico, USA
| | - M Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.,Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada.,Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, Canada.,Advanced Bioengineering Initiative Center, Multidisciplinary International Complex, K. N. Toosi University of Technology, Tehran, Iran
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Kopylova V, Boronovskiy S, Nartsissov Y. Approaches to vascular network, blood flow, and metabolite distribution modeling in brain tissue. Biophys Rev 2023; 15:1335-1350. [PMID: 37974995 PMCID: PMC10643724 DOI: 10.1007/s12551-023-01106-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 07/24/2023] [Indexed: 11/19/2023] Open
Abstract
The cardiovascular system plays a key role in the transport of nutrients, ensuring a continuous supply of all cells of the body with the metabolites necessary for life. The blood supply to the brain is carried out by the large arteries located on its surface, which branch into smaller arterioles that penetrate the cerebral cortex and feed the capillary bed, thereby forming an extensive branching network. The formation of blood vessels is carried out via vasculogenesis and angiogenesis, which play an important role in both embryo and adult life. The review presents approaches to modeling various aspects of both the formation of vascular networks and the construction of the formed arterial tree. In addition, a brief description of models that allows one to study the blood flow in various parts of the circulatory system and the spatiotemporal metabolite distribution in brain tissues is given. Experimental study of these issues is not always possible due to both the complexity of the cardiovascular system and the mechanisms through which the perfusion of all body cells is carried out. In this regard, mathematical models are a good tool for studying hemodynamics and can be used in clinical practice to diagnose vascular diseases and assess the need for treatment.
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Affiliation(s)
- Veronika Kopylova
- Institute of Cytochemistry and Molecular Pharmacology, Moscow, 115404 Russia
| | | | - Yaroslav Nartsissov
- Institute of Cytochemistry and Molecular Pharmacology, Moscow, 115404 Russia
- Biomedical Research Group, BiDiPharma GmbH, Siek, 22962 Germany
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10
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Hossain MMN, Hu NW, Abdelhamid M, Singh S, Murfee WL, Balogh P. Angiogenic Microvascular Wall Shear Stress Patterns Revealed Through Three-dimensional Red Blood Cell Resolved Modeling. FUNCTION 2023; 4:zqad046. [PMID: 37753184 PMCID: PMC10519277 DOI: 10.1093/function/zqad046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/28/2023] Open
Abstract
The wall shear stress (WSS) exerted by blood flowing through microvascular capillaries is an established driver of new blood vessel growth, or angiogenesis. Such adaptations are central to many physiological processes in both health and disease, yet three-dimensional (3D) WSS characteristics in real angiogenic microvascular networks are largely unknown. This marks a major knowledge gap because angiogenesis, naturally, is a 3D process. To advance current understanding, we model 3D red blood cells (RBCs) flowing through rat angiogenic microvascular networks using state-of-the-art simulation. The high-resolution fluid dynamics reveal 3D WSS patterns occurring at sub-endothelial cell (EC) scales that derive from distinct angiogenic morphologies, including microvascular loops and vessel tortuosity. We identify the existence of WSS hot and cold spots caused by angiogenic surface shapes and RBCs, and notably enhancement of low WSS regions by RBCs. Spatiotemporal characteristics further reveal how fluctuations follow timescales of RBC "footprints." Altogether, this work provides a new conceptual framework for understanding how shear stress might regulate EC dynamics in vivo.
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Affiliation(s)
- Mir Md Nasim Hossain
- Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07114, USA
| | - Nien-Wen Hu
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Maram Abdelhamid
- Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07114, USA
| | - Simerpreet Singh
- Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07114, USA
| | - Walter L Murfee
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Peter Balogh
- Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07114, USA
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11
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Zhang G, Liu B, Yang Y, Xie S, Chen L, Luo H, Zhong J, Wei Y, Guo F, Gan J, Zhu F, Xu L, Li Q, Shen Y, Zhang H, Liu Y, Li R, Deng H, Yang H. Mitochondrial UQCC3 controls embryonic and tumor angiogenesis by regulating VEGF expression. iScience 2023; 26:107370. [PMID: 37539028 PMCID: PMC10393800 DOI: 10.1016/j.isci.2023.107370] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 06/05/2023] [Accepted: 07/10/2023] [Indexed: 08/05/2023] Open
Abstract
Mitochondria play important roles in angiogenesis. However, the mechanisms remain elusive. In this study, we found that mitochondrial ubiquinol-cytochrome c reductase complex assembly factor 3 (UQCC3) is a key regulator of angiogenesis. TALEN-mediated knockout of Uqcc3 in mice caused embryonic lethality at 9.5-10.5 days postcoitum, and vessel density was dramatically reduced. Similarly, knockout of uqcc3 in zebrafish induced lethality post-fertilization and impaired vascular development. Knockout of UQCC3 resulted in slower tumor growth and angiogenesis. Mechanistically, UQCC3 was upregulated under hypoxia, promoted reactive oxygen species (ROS) generation, enhanced HIF-1α stability and increased VEGF expression. Finally, higher expression of UQCC3 was associated with poor prognosis in multiple types tumors, implying a role for UQCC3 in tumor progression. In conclusion, our findings highlight the important contribution of UQCC3 to angiogenesis under both physiological and pathological conditions, indicating the potential of UQCC3 as a therapeutic target for cancer.
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Affiliation(s)
- Guimin Zhang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Binrui Liu
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yun Yang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Shuo Xie
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Lingcheng Chen
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Hui Luo
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Jian Zhong
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yinhao Wei
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Fengzhu Guo
- Department of Medical Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Jia Gan
- Department of Pathology, Xinqiao Hospital, Third Military Medical University, Chongqing 400037, P.R.China
| | - Fan Zhu
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Lin Xu
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Qiqi Li
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yuge Shen
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Huajin Zhang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yan Liu
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Rong Li
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Hongxin Deng
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Hanshuo Yang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
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12
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Sauer TJ, Bejan A, Segars P, Samei E. Development and CT image-domain validation of a computational lung lesion model for use in virtual imaging trials. Med Phys 2023; 50:4366-4378. [PMID: 36637206 PMCID: PMC10338637 DOI: 10.1002/mp.16222] [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: 03/18/2022] [Revised: 11/03/2022] [Accepted: 12/14/2022] [Indexed: 01/14/2023] Open
Abstract
PURPOSE Computational abnormalities (e.g., lesion models) for use in medical imaging simulation studies are frequently generated using data collected from clinical images. Although this approach allows for highly-customizable lesion detectability studies on clinical computed tomography (CT) data, the ground-truth lesion models produced with this method do not provide a sufficiently realistic lesion morphology for use with current anthropomorphic simulation studies. This work is intended to demonstrate that the new anatomically-informed lesion model presented here is not inferior to the previous lesion model under CT imaging, and can therefore provide a more biologically-informed model for use with simulated CT imaging studies. METHODS The lesion model was simulated initially from a seed cell with 10 μm diameter placed in an anatomical location within segmented lung CT and was allowed to reproduce locally within the available solid angle in discrete time-intervals (corresponding to synchronous cell cycles) up to a size of ∼200 μm in diameter. Daughter cells of generation G were allowed also to reproduce on the next available time-step given sufficient space. At lesion sizes beyond 200 μm in diameter, the health of subregions of cells were tracked with a Markov chain technique, indicating which regions were likely to continue growing, which were likely stable, and which were likely to develop necrosis given their proximity to anatomical features and other lesion cells. For lesion sizes beyond 500 μm, the lesion was represented with three nested, triangulated surfaces (corresponding to proliferating, dormant, and necrotic regions), indicating how discrete volumes of the lesion were behaving at a particular time. Lesions were then assigned smoothly-varying material properties based on their cellular level health in each region, resulting in a multi-material lesion model. The lesions produced with this model were then voxelized and placed into lung CT images for comparison with both prior work and clinical data. This model was subject to an observer study in which cardiothoracic imaging radiologists assessed the realism of both clinical and synthetic lesions in CT images. RESULTS The useable outputs of this work were voxel- or surface-based, validated, computational lesions, at a scale clearly visible on clinical CT (3-4 cm). Analysis of the observer study results indicated that the computationally-generated lesions were indistinguishable from clinical lesions (AUC = 0.49, 95% CI = [0.36, 0.61]) and non-inferior to an earlier image-based lesion model-indicating the advantage of the model for use in both hybrid CT images and in simulated CT imaging of the lungs. CONCLUSIONS Results indicated the non-inferiority of this model as compared to previous methods, indicating the utility of the model for use in both hybrid CT images and in simulated CT imaging.
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Affiliation(s)
- Thomas J. Sauer
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Adrian Bejan
- Department of Mechanical Engineering, Duke University, Durham, North Carolina, USA
| | - Paul Segars
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Ehsan Samei
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
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13
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Xu J, Yang M, Shao AZ, Pan HW, Fan YX, Chen KP. Identification and Validation of Common Reference Genes for Normalization of Esophageal Squamous Cell Carcinoma Gene Expression Profiles. BIOMED RESEARCH INTERNATIONAL 2022; 2022:9125242. [PMID: 36467891 PMCID: PMC9711964 DOI: 10.1155/2022/9125242] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 09/04/2024]
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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Affiliation(s)
- Jia Xu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Ming Yang
- Department of General Surgery, Fifth People's Hospital of Huaian City, Huaian, China
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China
| | - Ai-zhong Shao
- Department of Cardiothorac Surgery, Affiliated People's Hospital of Jiangsu University, Zhenjiang, China
| | - Hui-wen Pan
- Department of Cardiothoracic Surgery, Affiliated People's Hospital of Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Yi-xuan Fan
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Ke-ping Chen
- School of Life Sciences, Jiangsu University, Zhenjiang, China
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14
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Du W, Cui G, Wang K, Li S. Clinical significance of 18F-FDG PET/CT imaging in 32 cases of gastrointestinal stromal tumors. Eur J Med Res 2022; 27:182. [PMID: 36114563 PMCID: PMC9479238 DOI: 10.1186/s40001-022-00806-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/06/2022] [Indexed: 11/23/2022] Open
Abstract
Objectives To explore the clinical significance of 18F-FDG metabolic imaging in the diagnosis and biological risk assessment of gastrointestinal stromal tumors (GIST). Methods This study is a clinical retrospective study. The research subjects were patients with GIST who were admitted to our hospital from January 2014 to December 2019 and underwent 18F-FDG metabolic imaging, and the relationship between biological risk and FDG metabolism was analyzed retrospectively. Results A total of 32 patients with GIST were included in this study, of which 17 patients had very low and low-risk lesions, and the FDG metabolism level did not increase; five patients had moderate-risk gastric lesions, and the FDG metabolism level was abnormally increased; 10 patients had high-risk lesions, and except for one patient with multiple lesions, the FDG metabolism level of these patients was increased. Conclusions The level of glucose metabolism is abnormally increased in tumor cells with vigorous mitosis and has higher biological risk. The 18F-FDG metabolism level can determine the biological risk of GIST and whether high-risk lesions involve other tissues and organs, as it more comprehensively reflects the distribution of lesions, the activity of tumor cells and the stage of the disease.
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15
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Kiani Shahvandi M, Soltani M, Moradi Kashkooli F, Saboury B, Rahmim A. Spatiotemporal multi-scale modeling of radiopharmaceutical distributions in vascularized solid tumors. Sci Rep 2022; 12:14582. [PMID: 36028541 PMCID: PMC9418261 DOI: 10.1038/s41598-022-18723-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 08/18/2022] [Indexed: 11/09/2022] Open
Abstract
We present comprehensive mathematical modeling of radiopharmaceutical spatiotemporal distributions within vascularized solid tumors. The novelty of the presented model is at mathematical level. From the mathematical viewpoint, we provide a general modeling framework for the process of radiopharmaceutical distribution in the tumor microenvironment to enable an analysis of the effect of various tumor-related parameters on the distribution of different radiopharmaceuticals. We argue that partial differential equations (PDEs), beyond conventional methods, including ODE-based kinetic compartment modeling, can be used to evaluate radiopharmaceutical distribution in both time and space. In addition, we consider the spatially-variable dynamic structure of tumor microvascular networks to simulate blood flow distribution. To examine the robustness of the model, the effects of microvessel density (MVD) and tumor size, as two important factors in tumor prognosis, on the radiopharmaceutical distribution within the tumor are investigated over time (in the present work, we focus on the radiopharmaceutical [18F]FDG, yet the framework is broadly applicable to radiopharmaceuticals). Results demonstrate that the maximum total uptake of [18F]FDG at all time frames occurs in the tumor area due to the high capillary permeability and lack of a functional lymphatic system. As the MVD of networks increases, the mean total uptake in the tumor is also enhanced, where the rate of diffusion from vessel to tissue has the highest contribution and the rate of convection transport has the lowest contribution. The results of this study can be used to better investigate various phenomena and bridge a gap among cancer biology, mathematical oncology, medical physics, and radiology.
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Affiliation(s)
| | - M Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran. .,Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada. .,Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada. .,Advanced Bioengineering Initiative Center, Multidisciplinary International Complex, K. N. Toosi University of Technology, Tehran, Iran.
| | | | - Babak Saboury
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA.,Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
| | - Arman Rahmim
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.,Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, Canada
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16
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Hasan MR, Alsaiari AA, Fakhurji BZ, Molla MHR, Asseri AH, Sumon MAA, Park MN, Ahammad F, Kim B. Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process. Molecules 2022; 27:4169. [PMID: 35807415 PMCID: PMC9268380 DOI: 10.3390/molecules27134169] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 01/18/2023] Open
Abstract
The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure-activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.
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Affiliation(s)
- Md Rifat Hasan
- Department of Mathematics, Faculty of Science, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
- Department of Applied Mathematics, Faculty of Science, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
| | - Ahad Amer Alsaiari
- College of Applied Medical Science, Clinical Laboratories Science Department, Taif University, Taif 21944, Saudi Arabia;
| | - Burhan Zain Fakhurji
- iGene Medical Training and Molecular Research Center, Jeddah 21589, Saudi Arabia;
| | | | - Amer H. Asseri
- Biochemistry Department, Faculty of Science, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
- Centre for Artificial Intelligence in Precision Medicines, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia
| | - Md Afsar Ahmed Sumon
- Department of Marine Biology, Faculty of Marine Sciences, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
| | - Moon Nyeo Park
- College of Korean Medicine, Kyung Hee University, Hoigidong, Dongdaemungu, Seoul 02453, Korea;
| | - Foysal Ahammad
- Department of Biological Sciences, Faculty of Science, King Abdul-Aziz University, Jeddah 21589, Saudi Arabia;
| | - Bonglee Kim
- College of Korean Medicine, Kyung Hee University, Hoigidong, Dongdaemungu, Seoul 02453, Korea;
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Abazari MA, Soltani M, Moradi Kashkooli F, Raahemifar K. Synthetic 18F-FDG PET Image Generation Using a Combination of Biomathematical Modeling and Machine Learning. Cancers (Basel) 2022; 14:2786. [PMID: 35681767 PMCID: PMC9179454 DOI: 10.3390/cancers14112786] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 05/21/2022] [Accepted: 06/01/2022] [Indexed: 12/10/2022] Open
Abstract
No previous works have attempted to combine generative adversarial network (GAN) architectures and the biomathematical modeling of positron emission tomography (PET) radiotracer uptake in tumors to generate extra training samples. Here, we developed a novel computational model to produce synthetic 18F-fluorodeoxyglucose (18F-FDG) PET images of solid tumors in different stages of progression and angiogenesis. First, a comprehensive biomathematical model is employed for creating tumor-induced angiogenesis, intravascular and extravascular fluid flow, as well as modeling of the transport phenomena and reaction processes of 18F-FDG in a tumor microenvironment. Then, a deep convolutional GAN (DCGAN) model is employed for producing synthetic PET images using 170 input images of 18F-FDG uptake in each of 10 different tumor microvascular networks. The interstitial fluid parameters and spatiotemporal distribution of 18F-FDG uptake in tumor and healthy tissues have been compared against previously published numerical and experimental studies, indicating the accuracy of the model. The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the generated PET sample and the experimental one are 0.72 and 28.53, respectively. Our results demonstrate that a combination of biomathematical modeling and GAN-based augmentation models provides a robust framework for the non-invasive and accurate generation of synthetic PET images of solid tumors in different stages.
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Affiliation(s)
- Mohammad Amin Abazari
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran; (M.A.A.); (F.M.K.)
| | - Madjid Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran; (M.A.A.); (F.M.K.)
- Faculty of Science, School of Optometry and Vision Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada;
- Advanced Bioengineering Initiative Center, Multidisciplinary International Complex, K. N. Toosi Univesity of Technology, Tehran 14176-14411, Iran
- Center for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON N2L 3G1, Canada
- Department of Electrical and Computer Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Farshad Moradi Kashkooli
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran; (M.A.A.); (F.M.K.)
| | - Kaamran Raahemifar
- Faculty of Science, School of Optometry and Vision Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada;
- Data Science and Artificial Intelligence Program, College of Information Sciences and Technology (IST), Penn State University, State College, PA 16801, USA
- Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
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