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Thenuwara G, Curtin J, Tian F. Advances in Diagnostic Tools and Therapeutic Approaches for Gliomas: A Comprehensive Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:9842. [PMID: 38139688 PMCID: PMC10747598 DOI: 10.3390/s23249842] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023]
Abstract
Gliomas, a prevalent category of primary malignant brain tumors, pose formidable clinical challenges due to their invasive nature and limited treatment options. The current therapeutic landscape for gliomas is constrained by a "one-size-fits-all" paradigm, significantly restricting treatment efficacy. Despite the implementation of multimodal therapeutic strategies, survival rates remain disheartening. The conventional treatment approach, involving surgical resection, radiation, and chemotherapy, grapples with substantial limitations, particularly in addressing the invasive nature of gliomas. Conventional diagnostic tools, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), play pivotal roles in outlining tumor characteristics. However, they face limitations, such as poor biological specificity and challenges in distinguishing active tumor regions. The ongoing development of diagnostic tools and therapeutic approaches represents a multifaceted and promising frontier in the battle against this challenging brain tumor. The aim of this comprehensive review is to address recent advances in diagnostic tools and therapeutic approaches for gliomas. These innovations aim to minimize invasiveness while enabling the precise, multimodal targeting of localized gliomas. Researchers are actively developing new diagnostic tools, such as colorimetric techniques, electrochemical biosensors, optical coherence tomography, reflectometric interference spectroscopy, surface-enhanced Raman spectroscopy, and optical biosensors. These tools aim to regulate tumor progression and develop precise treatment methods for gliomas. Recent technological advancements, coupled with bioelectronic sensors, open avenues for new therapeutic modalities, minimizing invasiveness and enabling multimodal targeting with unprecedented precision. The next generation of multimodal therapeutic strategies holds potential for precision medicine, aiding the early detection and effective management of solid brain tumors. These innovations offer promise in adopting precision medicine methodologies, enabling early disease detection, and improving solid brain tumor management. This review comprehensively recognizes the critical role of pioneering therapeutic interventions, holding significant potential to revolutionize brain tumor therapeutics.
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Affiliation(s)
- Gayathree Thenuwara
- School of Food Science and Environmental Health, Technological University Dublin, Grangegorman Lower, D07 H6K8 Dublin, Ireland;
- Institute of Biochemistry, Molecular Biology, and Biotechnology, University of Colombo, Colombo 00300, Sri Lanka
| | - James Curtin
- Faculty of Engineering and Built Environment, Technological University Dublin, Bolton Street, D01 K822 Dublin, Ireland;
| | - Furong Tian
- School of Food Science and Environmental Health, Technological University Dublin, Grangegorman Lower, D07 H6K8 Dublin, Ireland;
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Li K, Wu Q, Feng S, Zhao H, Jin W, Qiu H, Gu Y, Chen D. In situ detection of human glioma based on tissue optical properties using diffuse reflectance spectroscopy. JOURNAL OF BIOPHOTONICS 2023; 16:e202300195. [PMID: 37589177 DOI: 10.1002/jbio.202300195] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 07/18/2023] [Accepted: 08/15/2023] [Indexed: 08/18/2023]
Abstract
Safely maximizing brain cancer removal without injuring adjacent healthy tissue is crucial for optimal treatment outcomes. However, it is challenging to distinguish cancer from noncancer intraoperatively. This study aimed to explore the feasibility of diffuse reflectance spectroscopy (DRS) as a label-free and real-time detection technology for discrimination between brain cancer and noncancer tissues. Fifty-five fresh cancer and noncancer specimens from 19 brain surgeries were measured with DRS, and the results were compared with co-registered clinical standard histopathology. Tissue optical properties were quantitatively obtained from the diffuse reflectance spectra and compared among different types of brain tissues. A machine learning-based classifier was trained to differentiate cancerous versus noncancerous tissues. Our method could achieve a sensitivity of 93% and specificity of 95% for discriminating high-grade glioma from normal white matter. Our results showed that DRS has the potential to be used for label-free, real-time in vivo cancer detection during brain surgery.
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Affiliation(s)
- Kerui Li
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Qijia Wu
- Department of Neurosurgery, First Medical Center of PLA General Hospital, Beijing, China
| | - Shiyu Feng
- Department of Neurosurgery, First Medical Center of PLA General Hospital, Beijing, China
| | - Hongyou Zhao
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Wei Jin
- Department of Pathology, Chinese PLA General Hospital, Beijing, China
| | - Haixia Qiu
- Department of Laser Medicine, First Medical Center of PLA General Hospital, Beijing, China
| | - Ying Gu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
- Department of Laser Medicine, First Medical Center of PLA General Hospital, Beijing, China
- Precision Laser Medical Diagnosis and Treatment Innovation Unit, Chinese Academy of Medical Sciences, Beijing, China
| | - Defu Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
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Dao E, Gohla G, Williams P, Lovrics P, Badr F, Fang Q, Farrell T, Farquharson M. Breast tissue analysis using a clinically compatible combined time-resolved fluorescence and diffuse reflectance (TRF-DR) system. Lasers Surg Med 2023; 55:769-783. [PMID: 37526280 DOI: 10.1002/lsm.23710] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 06/29/2023] [Accepted: 07/11/2023] [Indexed: 08/02/2023]
Abstract
OBJECTIVE This work aims to develop a clinically compatible system that can perform breast tissue analysis in a more time efficient process than conventional histopathological assessment. The potential for such a system to be used in vivo in the operating room or surgical suite to improve patient outcome is investigated. METHOD In this work, 80 matched pairs of invasive ductal carcinoma and adjacent normal breast tissue were measured in a combined time-resolved fluorescence and diffuse reflectance (DA) system. Following measurement, the fluorescence intensity of collagen and flavin adenine dinucleotide (FAD); the fluorescence lifetime of collagen, nicotinamide adenine dinucleotide (NADH), and FAD; the DA; absorption coefficient; and reduced scattering coefficient were extracted. Samples then underwent histological processing and H&E staining to classify composition as tumor, fibroglandular, and/or adipose tissue. RESULTS Statistically significant differences in the collagen and FAD fluorescence intensity, collagen and FAD fluorescence lifetime, DA, and scattering coefficient were found between each tissue group. The NADH fluorescence lifetime and absorption coefficient were statistically different between the tumor and fibroglandular groups, and the tumor and adipose groups. While many breast tissue analysis studies label fibroglandular and adipose together as "normal" breast tissue, this work indicates that some differences between tumor and fibroglandular tissue are not the same as differences between tumor and adipose tissue. Observations of the reduced scatter coefficient may also indicate further classification to include fibro-adipose may be necessary. Future work would benefit from the additional tissue classification. CONCLUSION With observable differences in optical parameters between the three tissue types, this system shows promise as a breast analysis tool in a clinical setting. With further work involving samples of mixed composition, this combined system could potentially be used intraoperatively for rapid margin assessment.
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Affiliation(s)
- Erica Dao
- Department of Physics & Astronomy, McMaster University, Hamilton, Canada
| | - Gabriela Gohla
- St. Joseph's Healthcare, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - Phillip Williams
- St. Joseph's Healthcare, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - Peter Lovrics
- St. Joseph's Healthcare, Hamilton, Canada
- Department of Surgery, McMaster University, Hamilton, Canada
| | - Fares Badr
- Department of Engineering Physics, McMaster University, Hamilton, Canada
| | - Qiyin Fang
- Department of Engineering Physics, McMaster University, Hamilton, Canada
| | - Thomas Farrell
- School of Interdisciplinary Science, Hamilton, Canada
- Juravinski Hospital and Cancer Center, Hamilton, Canada
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Wang S, Saeidi T, Lilge L, Betz V. Integrating clinical access limitations into iPDT treatment planning with PDT-SPACE. BIOMEDICAL OPTICS EXPRESS 2023; 14:714-738. [PMID: 36874501 PMCID: PMC9979674 DOI: 10.1364/boe.478217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/03/2023] [Accepted: 01/03/2023] [Indexed: 06/18/2023]
Abstract
PDT-SPACE is an open-source software tool that automates interstitial photodynamic therapy treatment planning by providing patient-specific placement of light sources to destroy a tumor while minimizing healthy tissue damage. This work extends PDT-SPACE in two ways. The first enhancement allows specification of clinical access constraints on light source insertion to avoid penetrating critical structures and to minimize surgical complexity. Constraining fiber access to a single burr hole of adequate size increases healthy tissue damage by 10%. The second enhancement generates an initial placement of light sources as a starting point for refinement, rather than requiring entry of a starting solution by the clinician. This feature improves productivity and also leads to solutions with 4.5% less healthy tissue damage. The two features are used in concert to perform simulations of various surgery options of virtual glioblastoma multiforme brain tumors.
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Affiliation(s)
- Shuran Wang
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Rd, Toronto, ON M5S3G8, Canada
| | - Tina Saeidi
- Department of Medical Biophysics, University of Toronto, Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G1L7, Canada
| | - Lothar Lilge
- Department of Medical Biophysics, University of Toronto, Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON M5G1L7, Canada
| | - Vaughn Betz
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Rd, Toronto, ON M5S3G8, Canada
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Skyrman S, Burström G, Lai M, Manni F, Hendriks B, Frostell A, Edström E, Persson O, Elmi-Terander A. Diffuse reflectance spectroscopy sensor to differentiate between glial tumor and healthy brain tissue: a proof-of-concept study. BIOMEDICAL OPTICS EXPRESS 2022; 13:6470-6483. [PMID: 36589562 PMCID: PMC9774850 DOI: 10.1364/boe.474344] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/03/2022] [Accepted: 11/06/2022] [Indexed: 06/17/2023]
Abstract
Glial tumors grow diffusely in the brain. Survival is correlated to the extent of tumor removal, but tumor borders are often invisible. Resection beyond the borders as defined by conventional methods may further improve prognosis. In this proof-of-concept study, we evaluate diffuse reflectance spectroscopy (DRS) for discrimination between glial tumors and normal brain ex vivo. DRS spectra and histology were acquired from 22 tumor samples and nine brain tissue samples retrieved from 30 patients. The content of biological chromophores and scattering features were estimated by fitting a model derived from diffusion theory to the DRS spectra. DRS parameters differed significantly between tumor and normal brain tissue. Classification using random forest yielded a sensitivity and specificity for the detection of low-grade gliomas of 82.0% and 82.7%, respectively, and the area under curve (AUC) was 0.91. Applied in a hand-held probe or biopsy needle, DRS has the potential to provide intra-operative tissue analysis.
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Affiliation(s)
- Simon Skyrman
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Gustav Burström
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Marco Lai
- Philips Research, 5656 AE, Eindhoven, The Netherlands
- Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
| | - Francesca Manni
- Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
| | - Benno Hendriks
- Philips Research, 5656 AE, Eindhoven, The Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, 2628 CD, Delft, The Netherlands
| | - Arvid Frostell
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Erik Edström
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
| | - Oscar Persson
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Adrian Elmi-Terander
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
- Stockholm Spine Center, 194 45 Upplands-Väsby, Sweden
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Yassine AA, Lilge L, Betz V. Machine learning for real-time optical property recovery in interstitial photodynamic therapy: a stimulation-based study. BIOMEDICAL OPTICS EXPRESS 2021; 12:5401-5422. [PMID: 34692191 PMCID: PMC8515975 DOI: 10.1364/boe.431310] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/21/2021] [Accepted: 07/21/2021] [Indexed: 05/24/2023]
Abstract
With the continued development of non-toxic photosensitizer drugs, interstitial photodynamic therapy (iPDT) is showing more favorable outcomes in recent clinical trials. IPDT planning is crucial to further increase the treatment efficacy. However, it remains a major challenge to generate a high-quality, patient-specific plan due to uncertainty in tissue optical properties (OPs), µ a and µ s . These parameters govern how light propagates inside tissues, and any deviation from the planning-assumed values during treatment could significantly affect the treatment outcome. In this work, we increase the robustness of iPDT against OP variations by using machine learning models to recover the patient-specific OPs from light dosimetry measurements and then re-optimizing the diffusers' optical powers to adapt to these OPs in real time. Simulations on virtual brain tumor models show that reoptimizing the power allocation with the recovered OPs significantly reduces uncertainty in the predicted light dosimetry for all tissues involved.
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Affiliation(s)
- Abdul-Amir Yassine
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Rd, Toronto, ON M5S3G8, Canada
| | - Lothar Lilge
- Princess Margaret Cancer Center, University Health Network, 101 College Street, Toronto, ON M5G1L7, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G1L7, Canada
| | - Vaughn Betz
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Rd, Toronto, ON M5S3G8, Canada
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Yassine AA, Lilge L, Betz V. Optimizing Interstitial Photodynamic Therapy Planning With Reinforcement Learning-Based Diffuser Placement. IEEE Trans Biomed Eng 2021; 68:1668-1679. [PMID: 33471748 DOI: 10.1109/tbme.2021.3053197] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Interstitial photodynamic therapy (iPDT) has shown promising results recently as a minimally invasive stand-alone or intra-operative cancer treatment. The development of non-toxic photosensitizing drugs with improved target selectivity has increased its efficacy. However, personalized treatment planning that determines the number of photon emitters, their positions and their input powers while taking into account tissue anatomy and treatment response is still lacking to further improve outcomes. OBJECTIVE To develop new algorithms that generate high-quality plans by optimizing over the light source positions, along with their powers, to minimize the damage to organs-at-risk while eradicating the tumor. The optimization algorithms should also accurately model the physics of light propagation through the use of Monte-Carlo simulators. METHODS We use simulated-annealing as a baseline algorithm to place the sources. We propose different source perturbations that are likely to provide better outcomes and study their impact. To minimize the number of moves attempted (and effectively runtime) without degrading result quality, we use a reinforcement learning-based method to decide which perturbation strategy to perform in each iteration. We simulate our algorithm on virtual brain tumors modeling real glioblastoma multiforme cases, assuming a 5-ALA PpIX induced photosensitizer that is activated at [Formula: see text] wavelength. RESULTS The algorithm generates plans that achieve an average of 46% less damage to organs-as-risk compared to the manual placement used in current clinical studies. SIGNIFICANCE Having a general and high-quality planning system makes iPDT more effective and applicable to a wider variety of oncological indications. This paves the way for more clinical trials.
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Baria E, Pracucci E, Pillai V, Pavone FS, Ratto GM, Cicchi R. In vivo detection of murine glioblastoma through Raman and reflectance fiber-probe spectroscopies. NEUROPHOTONICS 2020; 7:045010. [PMID: 33274251 PMCID: PMC7707056 DOI: 10.1117/1.nph.7.4.045010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 10/14/2020] [Indexed: 05/29/2023]
Abstract
Significance: Glioblastoma (GBM) is the most common and aggressive malignant brain tumor in adults. With a worldwide incidence rate of 2 to 3 per 100,000 people, it accounts for more than 60% of all brain cancers; currently, its 5-year survival rate is < 5 % . GBM treatment relies mainly on surgical resection. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumor detection and guiding the removal of diseased tissues. Aim: Discriminating healthy brain from GBM tissues in an animal model through the combination of Raman and reflectance spectroscopies. Approach: EGFP-GL261 cells were injected into the brains of eight laboratory mice for inducing murine GBM in these animals. A multimodal optical fiber probe combining fluorescence, Raman, and reflectance spectroscopy was used to localize in vivo healthy and tumor brain areas and to collect their spectral information. Results: Tumor areas were localized through the detection of EGFP fluorescence emission. Then, Raman and reflectance spectra were collected from healthy and tumor tissues, and later analyzed through principal component analysis and linear discriminant analysis in order to develop a classification algorithm. Raman and reflectance spectra resulted in 92% and 93% classification accuracy, respectively. Combining together these techniques allowed improving the discrimination between healthy and tumor tissues up to 97%. Conclusions: These preliminary results demonstrate the potential of multimodal fiber-probe spectroscopy for in vivo label-free detection and delineation of brain tumors, and thus represent an additional, encouraging step toward clinical translation and deployment of fiber-probe spectroscopy.
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Affiliation(s)
- Enrico Baria
- University of Florence, Department of Physics, Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
| | - Enrico Pracucci
- Scuola Normale Superiore, National Enterprise for Nanoscience and Nanotechnology, Pisa, Italy
| | - Vinoshene Pillai
- Scuola Normale Superiore, National Enterprise for Nanoscience and Nanotechnology, Pisa, Italy
| | - Francesco S. Pavone
- University of Florence, Department of Physics, Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
- National Institute of Optics – National Research Council, Sesto Fiorentino, Italy
| | - Gian M. Ratto
- Scuola Normale Superiore, National Enterprise for Nanoscience and Nanotechnology, Pisa, Italy
| | - Riccardo Cicchi
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
- National Institute of Optics – National Research Council, Sesto Fiorentino, Italy
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Optical percutaneous needle biopsy of the liver: a pilot animal and clinical study. Sci Rep 2020; 10:14200. [PMID: 32848190 PMCID: PMC7449966 DOI: 10.1038/s41598-020-71089-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 08/10/2020] [Indexed: 12/15/2022] Open
Abstract
This paper presents the results of the experiments which were performed using the optical biopsy system specially developed for in vivo tissue classification during the percutaneous needle biopsy (PNB) of the liver. The proposed system includes an optical probe of small diameter acceptable for use in the PNB of the liver. The results of the feasibility studies and actual tests on laboratory mice with inoculated hepatocellular carcinoma and in clinical conditions on patients with liver tumors are presented and discussed. Monte Carlo simulations were carried out to assess the diagnostic volume and to trace the sensing depth. Fluorescence and diffuse reflectance spectroscopy measurements were used to monitor metabolic and morphological changes in tissues. The tissue oxygen saturation was evaluated using a recently developed approach to neural network fitting of diffuse reflectance spectra. The Support Vector Machine Classification was applied to identify intact liver and tumor tissues. Analysis of the obtained results shows the high sensitivity and specificity of the proposed multimodal method. This approach allows to obtain information before the tissue sample is taken, which makes it possible to significantly reduce the number of false-negative biopsies.
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Nie Z, Yeh SCA, LePalud M, Badr F, Tse F, Armstrong D, Liu LWC, Deen MJ, Fang Q. Optical Biopsy of the Upper GI Tract Using Fluorescence Lifetime and Spectra. Front Physiol 2020; 11:339. [PMID: 32477151 PMCID: PMC7237753 DOI: 10.3389/fphys.2020.00339] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 03/24/2020] [Indexed: 12/11/2022] Open
Abstract
Screening and surveillance for gastrointestinal (GI) cancers by endoscope guided biopsy is invasive, time consuming, and has the potential for sampling error. Tissue endogenous fluorescence spectra contain biochemical and physiological information, which may enable real-time, objective diagnosis. We first briefly reviewed optical biopsy modalities for GI cancer diagnosis with a focus on fluorescence-based techniques. In an ex vivo pilot clinical study, we measured fluorescence spectra and lifetime on fresh biopsy specimens obtained during routine upper GI screening procedures. Our results demonstrated the feasibility of rapid acquisition of time-resolved fluorescence (TRF) spectra from fresh GI mucosal specimens. We also identified spectroscopic signatures that can differentiate between normal mucosal samples obtained from the esophagus, stomach, and duodenum.
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Affiliation(s)
- Zhaojun Nie
- School of Biomedical Engineering, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
| | - Shu-Chi Allison Yeh
- Advanced Microscopy Program, Center for Systems Biology and Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Michelle LePalud
- School of Biomedical Engineering, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
| | - Fares Badr
- School of Biomedical Engineering, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
| | - Frances Tse
- Division of Gastroenterology and Farncombe Family Digestive Health Research Institute, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - David Armstrong
- Division of Gastroenterology and Farncombe Family Digestive Health Research Institute, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Louis W. C. Liu
- Division of Gastrointestinal Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - M. Jamal Deen
- School of Biomedical Engineering, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
- Department of Electrical and Computer Engineering, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
| | - Qiyin Fang
- School of Biomedical Engineering, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
- Department of Engineering Physics, Faculty of Engineering, McMaster University, Hamilton, ON, Canada
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Young-Schultz T, Brown S, Lilge L, Betz V. FullMonteCUDA: a fast, flexible, and accurate GPU-accelerated Monte Carlo simulator for light propagation in turbid media. BIOMEDICAL OPTICS EXPRESS 2019; 10:4711-4726. [PMID: 31565520 PMCID: PMC6757465 DOI: 10.1364/boe.10.004711] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 08/12/2019] [Accepted: 08/14/2019] [Indexed: 05/07/2023]
Abstract
Optimizing light delivery for photodynamic therapy, quantifying tissue optical properties or reconstructing 3D distributions of sources in bioluminescence imaging and absorbers in diffuse optical imaging all involve solving an inverse problem. This can require thousands of forward light propagation simulations to determine the parameters to optimize treatment, image tissue or quantify tissue optical properties, which is time-consuming and computationally expensive. Addressing this problem requires a light propagation simulator that produces results quickly given modelling parameters. In previous work, we developed FullMonteSW: currently the fastest, tetrahedral-mesh, Monte Carlo light propagation simulator written in software. Additional software optimizations showed diminishing performance improvements, so we investigated hardware acceleration methods. This work focuses on FullMonteCUDA: a GPU-accelerated version of FullMonteSW which targets NVIDIA GPUs. FullMonteCUDA has been validated across several benchmark models and, through various GPU-specific optimizations, achieves a 288-936x speedup over the single-threaded, non-vectorized version of FullMonteSW and a 4-13x speedup over the highly optimized, hand-vectorized and multi-threaded version. The increase in performance allows inverse problems to be solved more efficiently and effectively.
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Affiliation(s)
- Tanner Young-Schultz
- University of Toronto, Department of Electrical & Computer Engineering, Toronto, ON, Canada
| | - Stephen Brown
- University of Toronto, Department of Electrical & Computer Engineering, Toronto, ON, Canada
| | - Lothar Lilge
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- University of Toronto, Department of Medical Biophysics, Toronto, ON, Canada
| | - Vaughn Betz
- University of Toronto, Department of Electrical & Computer Engineering, Toronto, ON, Canada
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12
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Munegowda MA, Fisher C, Molehuis D, Foltz W, Roufaiel M, Bassan J, Nitz M, Mandel A, Lilge L. Efficacy of ruthenium coordination complex-based Rutherrin in a preclinical rat glioblastoma model. Neurooncol Adv 2019; 1:vdz006. [PMID: 32642649 PMCID: PMC7212850 DOI: 10.1093/noajnl/vdz006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Background Glioblastoma is an aggressive brain cancer in adults with a grave prognosis, aggressive radio and chemotherapy provide only a 15 months median survival. Methods We evaluated the tolerability and efficacy of the Ruthenium-based photosensitizer TLD-1433 with apo-Transferrin (Rutherrin) in the rat glioma 2 (RG-2) model. The specific tumor uptake ratio and photodynamic therapy (PDT) threshold of the rat glioblastoma and normal brain were determined, survival and CD8+T-cell infiltration post-therapy were analyzed. Results were compared with those obtained for 5-aminolevulinic acid (ALA)-induced Protoporphyrin IX (PpIX)-mediated photodynamic therapy in the same animal model. As both photosensitizers have different photophysical properties, the number of absorbed photons required to achieve an equal cell kill was determined for in vitro and in vivo studies. Results A significantly lower absorbed energy was sufficient to achieve LD50 with Rutherrin versus PpIX-mediated PDT. Rutherrin provides a higher specific uptake ratio (SUR) >20 in tumors versus normal brain, whereas the SUR for ALA-induced PpIX was 10.6. To evaluate the short-term tissue response in vivo, enhanced T2-weighted magnetic resonance imaging (MRI) provided the spatial extent of edema, post PpIX-PDT at twice the cross-section versus Rutherrin-PDT suggesting reduced nonspecific damage, typically associated with a secondary wave of neuronal damage. Following a single therapy, a significant survival increase was observed in rats bearing glioma for PDT mediated by Rutherrin versus PpIX for the selected treatment conditions. Rutherrin-PDT also demonstrated an increased CD8+T-cell infiltration in the tumors. Conclusion Rutherrin-PDT was well tolerated providing a safe and effective treatment of RG-2 glioma.
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Affiliation(s)
| | - Carl Fisher
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Daniel Molehuis
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Warren Foltz
- Techna Institute, University Health Network, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Mark Roufaiel
- Theralase Technologies Inc., Toronto, Ontario, Canada
| | - Jay Bassan
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
| | - Mark Nitz
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
| | - Arkady Mandel
- Theralase Technologies Inc., Toronto, Ontario, Canada
| | - Lothar Lilge
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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13
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Yassine AA, Lilge L, Betz V. Optimizing interstitial photodynamic therapy with custom cylindrical diffusers. JOURNAL OF BIOPHOTONICS 2019; 12:e201800153. [PMID: 30178604 DOI: 10.1002/jbio.201800153] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 09/02/2018] [Indexed: 05/07/2023]
Abstract
Interstitial photodynamic therapy (iPDT) has shown promise recently as a minimally invasive cancer treatment, partially due to the development of non-toxic photosensitizers in the absence of activation light. However, a major challenge in iPDT is the pre-treatment planning process that specifies the number of diffusers needed, along with their positions and allocated powers, to confine the light distribution to the target volume as much as possible. In this work, a new power allocation algorithm for cylindrical light diffusers including those that can produce customized longitudinal (tailored) emission profiles is introduced. The proposed formulation is convex to guarantee the minimum over-dose possible on the surrounding organs-at-risk. The impact of varying the diffuser lengths and penetration angles on the quality of the plan is evaluated. The results of this study are demonstrated for different photosensitizers activated at different wavelengths and simulated on virtual tumors modeling virtual glioblastoma multiforme cases. Results show that manufacturable cylindrical diffusers with tailored emission profiles can significantly outperform those with conventional flat profiles with an average damage reduction on white matter of 15% to 55% and on gray matter of 23% to 58%.
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Affiliation(s)
- Abdul-Amir Yassine
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
| | - Lothar Lilge
- Princess Margaret Cancer Centre, Toronto Medical Discovery Tower, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Vaughn Betz
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
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Yassine AA, Kingsford W, Xu Y, Cassidy J, Lilge L, Betz V. Automatic interstitial photodynamic therapy planning via convex optimization. BIOMEDICAL OPTICS EXPRESS 2018; 9:898-920. [PMID: 29552420 PMCID: PMC5854086 DOI: 10.1364/boe.9.000898] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Revised: 01/15/2018] [Accepted: 01/16/2018] [Indexed: 05/23/2023]
Abstract
Finding a high-quality treatment plan is an essential, yet difficult, stage of Photodynamic therapy (PDT) as it will determine the therapeutic efficacy in eradicating malignant tumors. A high-quality plan is patient-specific, and provides clinicians with the number of fiber-based spherical diffusers, their powers, and their interstitial locations to deliver the required light dose to destroy the tumor while minimizing the damage to surrounding healthy tissues. In this work, we propose a general convex light source power allocation algorithm that, given light source locations, guarantees optimality of the resulting solution in minimizing the over/under-dosage of volumes of interest. Furthermore, we provide an efficient framework for source selection with concomitant power reallocation to achieve treatment plans with a clinically feasible number of sources and comparable quality. We demonstrate our algorithms on virtual test cases that model glioblastoma multiforme tumors, and evaluate the performance of four different photosensitizers with different activation wavelengths and specific tissue uptake ratios. Results show an average reduction of the damage to organs-at-risk (OAR) by 29% to 31% with comparable runtime to existing power allocation techniques.
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Affiliation(s)
- Abdul-Amir Yassine
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S3G8, Canada
| | - William Kingsford
- Division of Engineering Science, University of Toronto, 27 King's College Circle, Toronto, ON M5S1A1, Canada
| | - Yiwen Xu
- Department of Mathematics, University of British Columbia, 1980 Mathematics Road, Vancouver, BC V6T1Z2, Canada
| | - Jeffrey Cassidy
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S3G8, Canada
| | - Lothar Lilge
- Princess Margaret Cancer Centre, Toronto Medical Discovery Tower, 101 College Street, Toronto, ON M5G1L7, Canada
| | - Vaughn Betz
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S3G8, Canada
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