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Zlobina NV, Budylin GS, Tseregorodtseva PS, Andreeva VA, Sorokin NI, Kamalov DM, Strigunov AA, Armaganov AG, Kamalov AA, Shirshin EA. In vivo assessment of bladder cancer with diffuse reflectance and fluorescence spectroscopy: A comparative study. Lasers Surg Med 2024. [PMID: 38650443 DOI: 10.1002/lsm.23788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 03/20/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024]
Abstract
OBJECTIVES The aim of this work is to assess the performance of multimodal spectroscopic approach combined with single core optical fiber for detection of bladder cancer during surgery in vivo. METHODS Multimodal approach combines diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy in the visible (405 nm excitation) and near-infrared (NIR) (690 nm excitation) ranges, and high-wavenumber Raman spectroscopy. All four spectroscopic methods were combined in a single setup. For 21 patients with suspected bladder cancer or during control cystoscopy optical spectra of bladder cancer, healthy bladder wall tissue and/or scars were measured. Classification of cancerous and healthy bladder tissue was performed using machine learning methods. RESULTS Statistically significant differences in relative total haemoglobin content, oxygenation, scattering, and visible fluorescence intensity were found between tumor and normal tissues. The combination of DRS and visible fluorescence spectroscopy allowed detecting cancerous tissue with sensitivity and specificity of 78% and 91%, respectively. The addition of features extracted from NIR fluorescence and Raman spectra did not improve the quality of classification. CONCLUSIONS This study demonstrates that multimodal spectroscopic approach allows increasing sensitivity and specificity of bladder cancer detection in vivo. The developed approach does not require special probes and can be used with single-core optical fibers applied for laser surgery.
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Affiliation(s)
- Nadezhda V Zlobina
- Department of Quantum Electronics, Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia
- Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia
- Department of Fundamental Pathology, National Medical Research Center for Endocrinology, Moscow, Russia
| | - Gleb S Budylin
- Biomedical Science and Technology Park, Laboratory of Clinical Biophotonics, First Moscow State Medical University, Moscow, Russia
| | - Polina S Tseregorodtseva
- Department of Quantum Electronics, Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia
- Department of Fundamental Pathology, National Medical Research Center for Endocrinology, Moscow, Russia
| | | | - Nikolay I Sorokin
- Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia
| | - David M Kamalov
- Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia
| | - Andrey A Strigunov
- Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia
| | - Artashes G Armaganov
- Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia
| | - Armais A Kamalov
- Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia
| | - Evgeny A Shirshin
- Department of Quantum Electronics, Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia
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2
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Veluponnar D, de Boer LL, Dashtbozorg B, Jong LJS, Geldof F, Guimaraes MDS, Sterenborg HJCM, Vrancken-Peeters MJTFD, van Duijnhoven F, Ruers T. Margin assessment during breast conserving surgery using diffuse reflectance spectroscopy. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:045006. [PMID: 38665316 PMCID: PMC11045169 DOI: 10.1117/1.jbo.29.4.045006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 04/03/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024]
Abstract
Significance During breast-conserving surgeries, it is essential to evaluate the resection margins (edges of breast specimen) to determine whether the tumor has been removed completely. In current surgical practice, there are no methods available to aid in accurate real-time margin evaluation. Aim In this study, we investigated the diagnostic accuracy of diffuse reflectance spectroscopy (DRS) combined with tissue classification models in discriminating tumorous tissue from healthy tissue up to 2 mm in depth on the actual resection margin of in vivo breast tissue. Approach We collected an extensive dataset of DRS measurements on ex vivo breast tissue and in vivo breast tissue, which we used to develop different classification models for tissue classification. Next, these models were used in vivo to evaluate the performance of DRS for tissue discrimination during breast conserving surgery. We investigated which training strategy yielded optimum results for the classification model with the highest performance. Results We achieved a Matthews correlation coefficient of 0.76, a sensitivity of 96.7% (95% CI 95.6% to 98.2%), a specificity of 90.6% (95% CI 86.3% to 97.9%) and an area under the curve of 0.98 by training the optimum model on a combination of ex vivo and in vivo DRS data. Conclusions DRS allows real-time margin assessment with a high sensitivity and specificity during breast-conserving surgeries.
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Affiliation(s)
- Dinusha Veluponnar
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
| | - Lisanne L. de Boer
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
| | - Behdad Dashtbozorg
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
| | - Lynn-Jade S. Jong
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
| | - Freija Geldof
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
| | - Marcos Da Silva Guimaraes
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Pathology, Amsterdam, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | | | - Frederieke van Duijnhoven
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
| | - Theo Ruers
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
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3
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Feenstra L, van der Stel SD, Da Silva Guimaraes M, Dashtbozorg B, Ruers TJM. Point Projection Mapping System for Tracking, Registering, Labeling, and Validating Optical Tissue Measurements. J Imaging 2024; 10:37. [PMID: 38392085 PMCID: PMC10890146 DOI: 10.3390/jimaging10020037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/23/2024] [Accepted: 01/27/2024] [Indexed: 02/24/2024] Open
Abstract
The validation of newly developed optical tissue-sensing techniques for tumor detection during cancer surgery requires an accurate correlation with the histological results. Additionally, such an accurate correlation facilitates precise data labeling for developing high-performance machine learning tissue-classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with the histopathology results is proposed and validated on a case study. The proposed framework provides a more-robust and accurate method for the tracking and validation of optical tissue-sensing techniques, which saves time and resources compared to the available conventional techniques.
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Affiliation(s)
- Lianne Feenstra
- Image-Guided Surgery, Department of Surgical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Stefan D van der Stel
- Image-Guided Surgery, Department of Surgical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Marcos Da Silva Guimaraes
- Department of Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Behdad Dashtbozorg
- Image-Guided Surgery, Department of Surgical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Theo J M Ruers
- Image-Guided Surgery, Department of Surgical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
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4
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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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5
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Rodriguez Troncoso J, Marium Mim U, Ivers JD, Paidi SK, Harper MG, Nguyen KG, Ravindranathan S, Rebello L, Lee DE, Zaharoff DA, Barman I, Rajaram N. Evaluating differences in optical properties of indolent and aggressive murine breast tumors using quantitative diffuse reflectance spectroscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:6114-6126. [PMID: 38420330 PMCID: PMC10898562 DOI: 10.1364/boe.505153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/06/2023] [Accepted: 10/26/2023] [Indexed: 03/02/2024]
Abstract
We used diffuse reflectance spectroscopy to quantify tissue absorption and scattering-based parameters in similarly sized tumors derived from a panel of four isogenic murine breast cancer cell lines (4T1, 4T07, 168FARN, 67NR) that are each capable of accomplishing different steps of the invasion-metastasis cascade. We found lower tissue scattering, increased hemoglobin concentration, and lower vascular oxygenation in indolent 67NR tumors incapable of metastasis compared with aggressive 4T1 tumors capable of metastasis. Supervised learning statistical approaches were able to accurately differentiate between tumor groups and classify tumors according to their ability to accomplish each step of the invasion-metastasis cascade. We investigated whether the inhibition of metastasis-promoting genes in the highly metastatic 4T1 tumors resulted in measurable optical changes that made these tumors similar to the indolent 67NR tumors. These results demonstrate the potential of diffuse reflectance spectroscopy to noninvasively evaluate tumor biology and discriminate between indolent and aggressive tumors.
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Affiliation(s)
| | - Umme Marium Mim
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Jesse D. Ivers
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Santosh K. Paidi
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mason G. Harper
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Khue G. Nguyen
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Sruthi Ravindranathan
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
| | - Lisa Rebello
- Cell and Molecular Biology Program, University of Arkansas, Fayetteville, AR 72701, USA
| | - David E. Lee
- Cell and Molecular Biology Program, University of Arkansas, Fayetteville, AR 72701, USA
- Department of Exercise Science, University of Arkansas, Fayetteville, AR 72703, USA
| | - David A. Zaharoff
- Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Raleigh, NC 27695, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Narasimhan Rajaram
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
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6
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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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7
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Cheng K, Wang J, Liu J, Zhang X, Shen Y, Su H. Public health implications of computer-aided diagnosis and treatment technologies in breast cancer care. AIMS Public Health 2023; 10:867-895. [PMID: 38187901 PMCID: PMC10764974 DOI: 10.3934/publichealth.2023057] [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: 08/26/2023] [Accepted: 10/10/2023] [Indexed: 01/09/2024] Open
Abstract
Breast cancer remains a significant public health issue, being a leading cause of cancer-related mortality among women globally. Timely diagnosis and efficient treatment are crucial for enhancing patient outcomes, reducing healthcare burdens and advancing community health. This systematic review, following the PRISMA guidelines, aims to comprehensively synthesize the recent advancements in computer-aided diagnosis and treatment for breast cancer. The study covers the latest developments in image analysis and processing, machine learning and deep learning algorithms, multimodal fusion techniques and radiation therapy planning and simulation. The results of the review suggest that machine learning, augmented and virtual reality and data mining are the three major research hotspots in breast cancer management. Moreover, this paper discusses the challenges and opportunities for future research in this field. The conclusion highlights the importance of computer-aided techniques in the management of breast cancer and summarizes the key findings of the review.
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Affiliation(s)
- Kai Cheng
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, 264100, China
| | - Jiangtao Wang
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, 264100, China
| | - Jian Liu
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, 264100, China
| | - Xiangsheng Zhang
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, 264100, China
| | - Yuanyuan Shen
- Yantai Affiliated Hospital of Binzhou Medical University, Yantai, 264100, China
| | - Hang Su
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
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8
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Veluponnar D, Dashtbozorg B, Jong LJS, Geldof F, Da Silva Guimaraes M, Vrancken Peeters MJTFD, van Duijnhoven F, Sterenborg HJCM, Ruers TJM, de Boer LL. Diffuse reflectance spectroscopy for accurate margin assessment in breast-conserving surgeries: importance of an optimal number of fibers. BIOMEDICAL OPTICS EXPRESS 2023; 14:4017-4036. [PMID: 37799696 PMCID: PMC10549728 DOI: 10.1364/boe.493179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 10/07/2023]
Abstract
During breast-conserving surgeries, it remains challenging to accomplish adequate surgical margins. We investigated different numbers of fibers for fiber-optic diffuse reflectance spectroscopy to differentiate tumorous breast tissue from healthy tissue ex vivo up to 2 mm from the margin. Using a machine-learning classification model, the optimal performance was obtained using at least three emitting fibers (Matthew's correlation coefficient (MCC) of 0.73), which was significantly higher compared to the performance of using a single-emitting fiber (MCC of 0.48). The percentage of correctly classified tumor locations varied from 75% to 100% depending on the tumor percentage, the tumor-margin distance and the number of fibers.
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Affiliation(s)
- Dinusha Veluponnar
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Behdad Dashtbozorg
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Lynn-Jade S. Jong
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Freija Geldof
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Marcos Da Silva Guimaraes
- Department of Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | | | - Frederieke van Duijnhoven
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands
| | - Theo J. M. Ruers
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Lisanne L. de Boer
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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9
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Overview of Optical Biosensors for Early Cancer Detection: Fundamentals, Applications and Future Perspectives. BIOLOGY 2023; 12:biology12020232. [PMID: 36829508 PMCID: PMC9953566 DOI: 10.3390/biology12020232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/09/2022] [Accepted: 11/11/2022] [Indexed: 02/05/2023]
Abstract
Conventional cancer detection and treatment methodologies are based on surgical, chemical and radiational processes, which are expensive, time consuming and painful. Therefore, great interest has been directed toward developing sensitive, inexpensive and rapid techniques for early cancer detection. Optical biosensors have advantages in terms of high sensitivity and being label free with a compact size. In this review paper, the state of the art of optical biosensors for early cancer detection is presented in detail. The basic idea, sensitivity analysis, advantages and limitations of the optical biosensors are discussed. This includes optical biosensors based on plasmonic waveguides, photonic crystal fibers, slot waveguides and metamaterials. Further, the traditional optical methods, such as the colorimetric technique, optical coherence tomography, surface-enhanced Raman spectroscopy and reflectometric interference spectroscopy, are addressed.
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10
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Optical spectroscopy and chemometrics in intraoperative tumor margin assessment. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.116955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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11
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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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12
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Witteveen M, Sterenborg HJCM, van Leeuwen TG, Aalders MCG, Ruers TJM, Post AL. Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:106003. [PMID: 36207772 PMCID: PMC9541333 DOI: 10.1117/1.jbo.27.10.106003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/23/2022] [Indexed: 06/16/2023]
Abstract
SIGNIFICANCE Hyperspectral reflectance imaging can be used in medicine to identify tissue types, such as tumor tissue. Tissue classification algorithms are developed based on, e.g., machine learning or principle component analysis. For the development of these algorithms, data are generally preprocessed to remove variability in data not related to the tissue itself since this will improve the performance of the classification algorithm. In hyperspectral imaging, the measured spectra are also influenced by reflections from the surface (glare) and height variations within and between tissue samples. AIM To compare the ability of different preprocessing algorithms to decrease variations in spectra induced by glare and height differences while maintaining contrast based on differences in optical properties between tissue types. APPROACH We compare eight preprocessing algorithms commonly used in medical hyperspectral imaging: standard normal variate, multiplicative scatter correction, min-max normalization, mean centering, area under the curve normalization, single wavelength normalization, first derivative, and second derivative. We investigate conservation of contrast stemming from differences in: blood volume fraction, presence of different absorbers, scatter amplitude, and scatter slope-while correcting for glare and height variations. We use a similarity metric, the overlap coefficient, to quantify contrast between spectra. We also investigate the algorithms for clinical datasets from the colon and breast. CONCLUSIONS Preprocessing reduces the overlap due to glare and distance variations. In general, the algorithms standard normal variate, min-max, area under the curve, and single wavelength normalization are the most suitable to preprocess data used to develop a classification algorithm for tissue classification. The type of contrast between tissue types determines which of these four algorithms is most suitable.
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Affiliation(s)
- Mark Witteveen
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- University of Twente, Science and Technology, Nanobiophysics, Enschede, The Netherlands
| | - Henricus J. C. M. Sterenborg
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Ton G. van Leeuwen
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Maurice C. G. Aalders
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
- University of Amsterdam, Co van Ledden Hulsebosch Center, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- University of Twente, Science and Technology, Nanobiophysics, Enschede, The Netherlands
| | - Anouk L. Post
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
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13
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Sun Y, Dumont AP, Arefin MS, Patil CA. Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:095002. [PMID: 36088529 PMCID: PMC9463544 DOI: 10.1117/1.jbo.27.9.095002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 08/22/2022] [Indexed: 06/15/2023]
Abstract
SIGNIFICANCE Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements. AIM The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications. APPROACH A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses. RESULTS EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus. CONCLUSIONS Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.
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Affiliation(s)
- Yu Sun
- Temple University, Department of Bioengineering, Philadelphia, Pennsylvania, United States
| | - Alexander P. Dumont
- Temple University, Department of Bioengineering, Philadelphia, Pennsylvania, United States
| | | | - Chetan A. Patil
- Temple University, Department of Bioengineering, Philadelphia, Pennsylvania, United States
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14
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Amiri SA, Berckel PV, Lai M, Dankelman J, Hendriks BHW. Tissue-mimicking phantom materials with tunable optical properties suitable for assessment of diffuse reflectance spectroscopy during electrosurgery. BIOMEDICAL OPTICS EXPRESS 2022; 13:2616-2643. [PMID: 35774339 PMCID: PMC9203083 DOI: 10.1364/boe.449637] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 06/15/2023]
Abstract
Emerging intraoperative tumor margin assessment techniques require the development of more complex and reliable organ phantoms to assess the performance of the technique before its translation into the clinic. In this work, electrically conductive tissue-mimicking materials (TMMs) based on fat, water and agar/gelatin were produced with tunable optical properties. The composition of the phantoms allowed for the assessment of tumor margins using diffuse reflectance spectroscopy, as the fat/water ratio served as a discriminating factor between the healthy and malignant tissue. Moreover, the possibility of using polyvinyl alcohol (PVA) or transglutaminase in combination with fat, water and gelatin for developing TMMs was studied. The diffuse spectral response of the developed phantom materials had a good match with the spectral response of porcine muscle and adipose tissue, as well as in vitro human breast tissue. Using the developed recipe, anatomically relevant heterogeneous breast phantoms representing the optical properties of different layers of the human breast were fabricated using 3D-printed molds. These TMMs can be used for further development of phantoms applicable for simulating the realistic breast conserving surgery workflow in order to evaluate the intraoperative optical-based tumor margin assessment techniques during electrosurgery.
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Affiliation(s)
- Sara Azizian Amiri
- Department of Biomechanical Engineering, Faculty of Mechanical, Maritime, and Materials Engineering, Delft University of Technology, The Netherlands
| | - Pieter Van Berckel
- Department of Biomechanical Engineering, Faculty of Mechanical, Maritime, and Materials Engineering, Delft University of Technology, The Netherlands
| | - Marco Lai
- Philips Research, IGT & US Devices and Systems Department, Eindhoven, The Netherlands
- Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
| | - Jenny Dankelman
- Department of Biomechanical Engineering, Faculty of Mechanical, Maritime, and Materials Engineering, Delft University of Technology, The Netherlands
| | - Benno H. W. Hendriks
- Department of Biomechanical Engineering, Faculty of Mechanical, Maritime, and Materials Engineering, Delft University of Technology, The Netherlands
- Philips Research, IGT & US Devices and Systems Department, Eindhoven, The Netherlands
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15
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Sangha GS, Hu B, Li G, Fox SE, Sholl AB, Brown JQ, Goergen CJ. Assessment of photoacoustic tomography contrast for breast tissue imaging using 3D correlative virtual histology. Sci Rep 2022; 12:2532. [PMID: 35169198 PMCID: PMC8847353 DOI: 10.1038/s41598-022-06501-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 01/25/2022] [Indexed: 11/12/2022] Open
Abstract
Current breast tumor margin detection methods are destructive, time-consuming, and result in significant reoperative rates. Dual-modality photoacoustic tomography (PAT) and ultrasound has the potential to enhance breast margin characterization by providing clinically relevant compositional information with high sensitivity and tissue penetration. However, quantitative methods that rigorously compare volumetric PAT and ultrasound images with gold-standard histology are lacking, thus limiting clinical validation and translation. Here, we present a quantitative multimodality workflow that uses inverted Selective Plane Illumination Microscopy (iSPIM) to facilitate image co-registration between volumetric PAT-ultrasound datasets with histology in human invasive ductal carcinoma breast tissue samples. Our ultrasound-PAT system consisted of a tunable Nd:YAG laser coupled with a 40 MHz central frequency ultrasound transducer. A linear stepper motor was used to acquire volumetric PAT and ultrasound breast biopsy datasets using 1100 nm light to identify hemoglobin-rich regions and 1210 nm light to identify lipid-rich regions. Our iSPIM system used 488 nm and 647 nm laser excitation combined with Eosin and DRAQ5, a cell-permeant nucleic acid binding dye, to produce high-resolution volumetric datasets comparable to histology. Image thresholding was applied to PAT and iSPIM images to extract, quantify, and topologically visualize breast biopsy lipid, stroma, hemoglobin, and nuclei distribution. Our lipid-weighted PAT and iSPIM images suggest that low lipid regions strongly correlate with malignant breast tissue. Hemoglobin-weighted PAT images, however, correlated poorly with cancerous regions determined by histology and interpreted by a board-certified pathologist. Nuclei-weighted iSPIM images revealed similar cellular content in cancerous and non-cancerous tissues, suggesting malignant cell migration from the breast ducts to the surrounding tissues. We demonstrate the utility of our nondestructive, volumetric, region-based quantitative method for comprehensive validation of 3D tomographic imaging methods suitable for bedside tumor margin detection.
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Affiliation(s)
- Gurneet S Sangha
- Fischell Department of Bioengineering, University of Maryland, 8278 Paint Branch Dr, College Park, MD, 20742, USA.,Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Dr., West Lafayette, IN, 47907, USA
| | - Bihe Hu
- Department of Biomedical Engineering, Tulane University, 547 Lindy Boggs Center, New Orleans, LA, 70118, USA
| | - Guang Li
- Department of Biomedical Engineering, Tulane University, 547 Lindy Boggs Center, New Orleans, LA, 70118, USA
| | - Sharon E Fox
- Department of Pathology, LSU Health Sciences Center, New Orleans, 433 Bolivar St, New Orleans, LA, 70112, USA.,Pathology and Laboratory Medicine Service, Southeast Louisiana Veterans Healthcare System, 2400 Canal Street, New Orleans, LA, 70112, USA
| | - Andrew B Sholl
- Delta Pathology Group, Touro Infirmary, 1401 Foucher St, New Orleans, LA, 70115, USA
| | - J Quincy Brown
- Department of Biomedical Engineering, Tulane University, 547 Lindy Boggs Center, New Orleans, LA, 70118, USA
| | - Craig J Goergen
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Dr., West Lafayette, IN, 47907, USA. .,Purdue University Center for Cancer Research, Purdue University, 201 S. University St., West Lafayette, IN, 47907, USA.
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16
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Geldof F, Dashtbozorg B, Hendriks BHW, Sterenborg HJCM, Ruers TJM. Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy. Sci Rep 2022; 12:1698. [PMID: 35105926 PMCID: PMC8807816 DOI: 10.1038/s41598-022-05751-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 01/12/2022] [Indexed: 11/26/2022] Open
Abstract
During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.
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Affiliation(s)
- Freija Geldof
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands.
| | - Behdad Dashtbozorg
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
| | - Benno H W Hendriks
- Department of IGT and US Devices & Systems, Philips Research Laboratories, 5656 AE, Eindhoven, The Netherlands
- Department of BioMechanical Engineering, 3mE, Delft University of Technology, 2628 CD, Delft, The Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, 1105 AZ, Amsterdam, The Netherlands
| | - Theo J M Ruers
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
- Faculty of Science and Technology, University of Twente, 7522 NB, Enschede, The Netherlands
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17
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Schouw HM, Huisman LA, Janssen YF, Slart RHJA, Borra RJH, Willemsen ATM, Brouwers AH, van Dijl JM, Dierckx RA, van Dam GM, Szymanski W, Boersma HH, Kruijff S. Targeted optical fluorescence imaging: a meta-narrative review and future perspectives. Eur J Nucl Med Mol Imaging 2021; 48:4272-4292. [PMID: 34633509 PMCID: PMC8566445 DOI: 10.1007/s00259-021-05504-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/23/2021] [Indexed: 12/27/2022]
Abstract
Purpose The aim of this review is to give an overview of the current status of targeted optical fluorescence imaging in the field of oncology, cardiovascular, infectious and inflammatory diseases to further promote clinical translation. Methods A meta-narrative approach was taken to systematically describe the relevant literature. Consecutively, each field was assigned a developmental stage regarding the clinical implementation of optical fluorescence imaging. Results Optical fluorescence imaging is leaning towards clinical implementation in gastrointestinal and head and neck cancers, closely followed by pulmonary, neuro, breast and gynaecological oncology. In cardiovascular and infectious disease, optical imaging is in a less advanced/proof of concept stage. Conclusion Targeted optical fluorescence imaging is rapidly evolving and expanding into the clinic, especially in the field of oncology. However, the imaging modality still has to overcome some major challenges before it can be part of the standard of care in the clinic, such as the provision of pivotal trial data. Intensive multidisciplinary (pre-)clinical joined forces are essential to overcome the delivery of such compelling phase III registration trial data and subsequent regulatory approval and reimbursement hurdles to advance clinical implementation of targeted optical fluorescence imaging as part of standard practice. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05504-y.
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Affiliation(s)
- H M Schouw
- Department of Surgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - L A Huisman
- Department of Surgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Y F Janssen
- Department of Surgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - R H J A Slart
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.,Department of Biomedical Photonic Imaging, Faculty of Science and Technology, University of Twente, Enschede, The Netherlands
| | - R J H Borra
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.,Department of Radiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - A T M Willemsen
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - A H Brouwers
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - J M van Dijl
- Department of Medical Microbiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - R A Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.,Department of Diagnostic Sciences, Ghent University Faculty of Medicine and Health Sciences, Gent, Belgium
| | - G M van Dam
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.,AxelaRx/TRACER Europe BV, Groningen, The Netherlands
| | - W Szymanski
- Department of Radiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - H H Boersma
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.,Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Centre of Groningen, Groningen, The Netherlands
| | - S Kruijff
- Department of Surgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands. .,Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.
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18
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Alfonso-Garcia A, Bec J, Weyers B, Marsden M, Zhou X, Li C, Marcu L. Mesoscopic fluorescence lifetime imaging: Fundamental principles, clinical applications and future directions. JOURNAL OF BIOPHOTONICS 2021; 14:e202000472. [PMID: 33710785 PMCID: PMC8579869 DOI: 10.1002/jbio.202000472] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 05/16/2023]
Abstract
Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm.
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Affiliation(s)
- Alba Alfonso-Garcia
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Julien Bec
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Brent Weyers
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Mark Marsden
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Xiangnan Zhou
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Cai Li
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Laura Marcu
- Department of Biomedical Engineering, University of California, Davis, Davis, California
- Department Neurological Surgery, University of California, Davis, California
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19
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de Boer LL, Kho E, Van de Vijver KK, Vranken Peeters MJTFD, van Duijnhoven F, Hendriks BHW, Sterenborg HJCM, Ruers TJM. Optical tissue measurements of invasive carcinoma and ductal carcinoma in situ for surgical guidance. Breast Cancer Res 2021; 23:59. [PMID: 34022928 PMCID: PMC8141169 DOI: 10.1186/s13058-021-01436-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 05/05/2021] [Indexed: 11/10/2022] Open
Abstract
Background Although the incidence of positive resection margins in breast-conserving surgery has decreased, both incomplete resection and unnecessary large resections still occur. This is especially the case in the surgical treatment of ductal carcinoma in situ (DCIS). Diffuse reflectance spectroscopy (DRS), an optical technology based on light tissue interactions, can potentially characterize tissue during surgery thereby guiding the surgeon intraoperatively. DRS has shown to be able to discriminate pure healthy breast tissue from pure invasive carcinoma (IC) but limited research has been done on (1) the actual optical characteristics of DCIS and (2) the ability of DRS to characterize measurements that are a mixture of tissue types. Methods In this study, DRS spectra were acquired from 107 breast specimens from 107 patients with proven IC and/or DCIS (1488 measurement locations). With a generalized estimating equation model, the differences between the DRS spectra of locations with DCIS and IC and only healthy tissue were compared to see if there were significant differences between these spectra. Subsequently, different classification models were developed to be able to predict if the DRS spectrum of a measurement location represented a measurement location with “healthy” or “malignant” tissue. In the development and testing of the models, different definitions for “healthy” and “malignant” were used. This allowed varying the level of homogeneity in the train and test data. Results It was found that the optical characteristics of IC and DCIS were similar. Regarding the classification of tissue with a mixture of tissue types, it was found that using mixed measurement locations in the development of the classification models did not tremendously improve the accuracy of the classification of other measurement locations with a mixture of tissue types. The evaluated classification models were able to classify measurement locations with > 5% malignant cells with a Matthews correlation coefficient of 0.41 or 0.40. Some models showed better sensitivity whereas others had better specificity. Conclusion The results suggest that DRS has the potential to detect malignant tissue, including DCIS, in healthy breast tissue and could thus be helpful for surgical guidance. Supplementary Information The online version contains supplementary material available at 10.1186/s13058-021-01436-5.
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Affiliation(s)
- Lisanne L de Boer
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands.
| | - Esther Kho
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands
| | - Koen K Van de Vijver
- Department of Pathology, Ghent University Hospital, and Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
| | | | - Frederieke van Duijnhoven
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands
| | - Benno H W Hendriks
- Philips Research, In-body Systems Group, Eindhoven, Netherlands.,Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands.,Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Theo J M Ruers
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands.,Faculty of Science and Technology, University of Twente, Enschede, the Netherlands
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20
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Matthies L, Gebrekidan MT, Tegtmeyer JF, Oetter N, Rohde M, Vollkommer T, Smeets R, Wilczak W, Stelzle F, Gosau M, Braeuer AS, Knipfer C. Optical diagnosis of oral cavity lesions by label-free Raman spectroscopy. BIOMEDICAL OPTICS EXPRESS 2021; 12:836-851. [PMID: 33680545 PMCID: PMC7901324 DOI: 10.1364/boe.409456] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 11/21/2020] [Accepted: 12/08/2020] [Indexed: 06/12/2023]
Abstract
Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers and frequently preceded by non-malignant lesions. Using Shifted-Excitation Raman Difference Spectroscopy (SERDS), principal component and linear discriminant analysis in native tissue specimens, 9500 raw Raman spectra of OSCC, 4300 of non-malignant lesions and 4200 of physiological mucosa were evaluated. Non-malignant lesions were distinguished from physiological mucosa with a classification accuracy of 95.3% (95.4% sensitivity, 95.2% specificity, area under the curve (AUC) 0.99). Discriminating OSCC from non-malignant lesions showed an accuracy of 88.4% (93.7% sensitivity, 76.7% specificity, AUC 0.93). OSCC was identified against physiological mucosa with an accuracy of 89.8% (93.7% sensitivity, 81.0% specificity, AUC 0.90). These findings underline the potential of SERDS for the diagnosis of oral cavity lesions.
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Affiliation(s)
- Levi Matthies
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
- These authors contributed equally
| | - Medhanie T. Gebrekidan
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Straße 6, D-91054 Erlangen, Germany
- Technische Universität Bergakademie Freiberg (TUBAF), Institute of Thermal-, Environmental- and Resources‘ Process Engineering (ITUN), Leipziger Straße 28, D-09599 Freiberg, Germany
- These authors contributed equally
| | - Jasper F. Tegtmeyer
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Nicolai Oetter
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Straße 6, D-91054 Erlangen, Germany
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Oral and Maxillofacial Surgery, Glückstraße 11, D-91054 Erlangen, Germany
| | - Maximilian Rohde
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Oral and Maxillofacial Surgery, Glückstraße 11, D-91054 Erlangen, Germany
| | - Tobias Vollkommer
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Ralf Smeets
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Waldemar Wilczak
- University Medical Center Hamburg-Eppendorf (UKE), Institute of Pathology, Martinistraße 52, D-20246 Hamburg, Germany
| | - Florian Stelzle
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Straße 6, D-91054 Erlangen, Germany
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Oral and Maxillofacial Surgery, Glückstraße 11, D-91054 Erlangen, Germany
| | - Martin Gosau
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Andreas S. Braeuer
- Technische Universität Bergakademie Freiberg (TUBAF), Institute of Thermal-, Environmental- and Resources‘ Process Engineering (ITUN), Leipziger Straße 28, D-09599 Freiberg, Germany
| | - Christian Knipfer
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
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21
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Balasundaram G, Krafft C, Zhang R, Dev K, Bi R, Moothanchery M, Popp J, Olivo M. Biophotonic technologies for assessment of breast tumor surgical margins-A review. JOURNAL OF BIOPHOTONICS 2021; 14:e202000280. [PMID: 32951321 DOI: 10.1002/jbio.202000280] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 09/15/2020] [Accepted: 09/18/2020] [Indexed: 06/11/2023]
Abstract
Breast conserving surgery (BCS) offering similar surgical outcomes as mastectomy while retaining breast cosmesis is becoming increasingly popular for the management of early stage breast cancers. However, its association with reoperation rates of 20% to 40% following incomplete tumor removal warrants the need for a fast and accurate intraoperative surgical margin assessment tool that offers cellular, structural and molecular information of the whole specimen surface to a clinically relevant depth. Biophotonic technologies are evolving to qualify as such an intraoperative tool for clinical assessment of breast cancer surgical margins at the microscopic and macroscopic scale. Herein, we review the current research in the application of biophotonic technologies such as photoacoustic imaging, Raman spectroscopy, multimodal multiphoton imaging, diffuse optical imaging and fluorescence imaging using medically approved dyes for breast cancer detection and/or tumor subtype differentiation toward intraoperative assessment of surgical margins in BCS specimens, and possible challenges in their route to clinical translation.
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Affiliation(s)
- Ghayathri Balasundaram
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | | | - Ruochong Zhang
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Kapil Dev
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Renzhe Bi
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Mohesh Moothanchery
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, University Jena, Jena, Germany
| | - Malini Olivo
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
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22
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Kaur P, Choudhury D. Functionality of receptor targeted zinc-insulin quantum clusters in skin tissue augmentation and bioimaging. J Drug Target 2020; 29:541-550. [PMID: 33307859 DOI: 10.1080/1061186x.2020.1864740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Quantum clusters with target specificity are suitable for tissue-specific imaging. In the present work, amorphous zinc insulin quantum clusters (IZnQCs) had been synthesised to promote and monitor wound recovery. Easy synthesis, biocompatibility, stability, enhanced quantum yield, and solubility made the cluster suitable for preclinical/clinical exploration. Zn2+ is known for its binding to insulin hexamer. Here we report the reformation of the structure in a quantum cluster form in the presence of Zn2+. The formation of IZnQCs was confirmed by the change in zeta potential from -25.6 mV to -17.9 mV and also the formation of protein metal interaction was confirmed in FTIR bands at 450, 480, and 613 cm-1 for Zn-O, Zn-N, and Zn-S, respectively. HRTEM-EDS and SAED data analysis showed an amorphous nature of the cluster. The binding of IZnQCs to the cells has been confirmed using confocal microscopy. IZnQCs showed a synergistic effect in wound recovery than insulin or Zn2+ alone. Further due to high fluorescence this recovery process can be monitored under an appropriate setup. Wound healing promotional activity, target specificity, and fluorescence properties make the IZnQCs ideal to use for bioimaging along with promoting and monitoring of wound recovery agent.
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Affiliation(s)
- Pawandeep Kaur
- School of Chemistry and Biochemistry, Thapar Institute of Engineering and Technology, Patiala, Punjab, India
| | - Diptiman Choudhury
- School of Chemistry and Biochemistry, Thapar Institute of Engineering and Technology, Patiala, Punjab, India.,Thapar Institute of Engineering and Technology - Virginia Tech Centre for Excellence in Material Sciences, Thapar Institute of Engineering and Technology, Patiala, Punjab, India
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23
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Balasundaram G, Goh Y, Moothanchery M, Attia A, Lim HQ, Burton NC, Qiu Y, Putti TC, Chan CW, Hartmann M, Quek ST, Olivo M. Optoacoustic characterization of breast conserving surgery specimens - A pilot study. PHOTOACOUSTICS 2020; 19:100164. [PMID: 32420026 PMCID: PMC7215246 DOI: 10.1016/j.pacs.2020.100164] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Revised: 01/22/2020] [Accepted: 01/28/2020] [Indexed: 05/04/2023]
Abstract
In this pilot study, we tested an ultrasound-guided optoacoustic tomography (US-OT) two-dimensional (2D) array scanner to understand the optoacoustic patterns of excised breastconserving surgery (BCS) specimens. We imaged 14 BCS specimens containing malignant tumors at eight wavelengths spanning 700-1100 nm. Spectral unmixing across multiple wavelengths allowed for visualizing major intrinsic chromophores in the breast tissue including hemoglobin and lipid up to a depth of 7 mm. We identified less/no lipid signals within the tumor and intense deoxy-hemoglobin (Hb) signals on the rim of the tumor as unique characteristics of malignant tumors in comparison to no tumor region. We also observed continuous broad lipid signals as features of negative margins and compromised lipid signals interrupted by vasculature as features of positive margins. These differentiating patterns can form the basis of US-OT to be explored as an alternate, fast and efficient intraoperative method for evaluation of tumor resection margins.
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Affiliation(s)
| | - Yonggeng Goh
- Department of Diagnostic Imaging, National University Hospital, Singapore
| | - Mohesh Moothanchery
- Laboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Singapore
| | - Amalina Attia
- Laboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Singapore
| | - Hann Qian Lim
- Laboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Singapore
| | | | - Yi Qiu
- iThera Medical GmbH, Germany
| | | | - Ching Wan Chan
- Department of Breast Surgery, National University Hospital, Singapore
| | - Mikael Hartmann
- Department of Breast Surgery, National University Hospital, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, Singapore
| | - Malini Olivo
- Laboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Singapore
- Corresponding author at: Singapore Bioimaging Consortium (SBIC). A⁎STAR Research Entities, 11 Biopolis Way, #02-02 Helios, 138667, Singapore.
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24
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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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25
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Babu S, Vengalathunadakal K S, Nair SK. Design and development of portable handheld multimodal spectroscopic probe system for skin tissue analysis. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2020; 91:073104. [PMID: 32752815 DOI: 10.1063/1.5144483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 06/14/2020] [Indexed: 06/11/2023]
Abstract
The potential of optical spectroscopic techniques such as diffused reflectance and fluorescence as non-invasive, in vivo diagnostic tools is being explored and validated recently. In this paper, we present the design and development of a handheld, portable, multimodal fiber optic based probe scheme to sequentially measure diffuse reflectance and fluorescence. The proposed prototype is designed to sequentially acquire diffused reflectance in the broad wavelength range of 400 nm-1600 nm and fluorescence using custom-chosen spectrophotometers, monochromatic and broadband light sources, fibers to accommodate a wide wavelength range, custom-built probe distal end, and a real-time spectral stitching and display unit. The prototype is characterized using in-house fabricated phantom tissue samples with tunable optical properties such as scattering and absorption. The depth profile study is carried out using phantom tissue layers of known optical parameters followed by the sequential measurement of diffused reflectance and fluorescence from the tissue mimicking sample.
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Affiliation(s)
- Shinto Babu
- Optics and Spectroscopy Lab, Department of Physics, Union Christian College, Aluva 683102, Kerala, India
| | - Shinoj Vengalathunadakal K
- Optics and Spectroscopy Lab, Department of Physics, Union Christian College, Aluva 683102, Kerala, India
| | - Saritha K Nair
- Department of Physics, Mar Athanasius College (Autonomous), Kothamangalam 686666, Kerala, India
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26
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Zhang Y, Moy AJ, Feng X, Nguyen HTM, Sebastian KR, Reichenberg JS, Markey MK, Tunnell JW. Diffuse reflectance spectroscopy as a potential method for nonmelanoma skin cancer margin assessment. TRANSLATIONAL BIOPHOTONICS 2020. [DOI: 10.1002/tbio.202000001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Yao Zhang
- Department of Biomedical Engineering The University of Texas at Austin Austin Texas USA
| | - Austin J. Moy
- Department of Biomedical Engineering The University of Texas at Austin Austin Texas USA
| | - Xu Feng
- Department of Biomedical Engineering The University of Texas at Austin Austin Texas USA
| | - Hieu T. M. Nguyen
- Department of Biomedical Engineering The University of Texas at Austin Austin Texas USA
| | | | | | - Mia K. Markey
- Department of Biomedical Engineering The University of Texas at Austin Austin Texas USA
- Department of Imaging Physics The University of Texas MD Anderson Cancer Center Houston Texas USA
| | - James W. Tunnell
- Department of Biomedical Engineering The University of Texas at Austin Austin Texas USA
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27
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De Maria GL, Lee R, Alkhalil M, Borlotti A, Kotronias R, Langrish J, Lucking A, Dawkins S, Choudhury RP, Kharbanda R, Banning AP, Vallance C, Channon KM. Reflectance spectral analysis for novel characterization and clinical assessment of aspirated coronary thrombi in patients with ST elevation myocardial infarction. Physiol Meas 2020; 41:045001. [PMID: 32197256 DOI: 10.1088/1361-6579/ab81de] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
OBJECTIVE The visual appearance of coronary thrombi may be clinically informative in ST elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (pPCI). However, subjective assessment is poorly reproducible and cannot provide an objective basis for treatment decisions or patient stratification. We have assessed the feasibility of a novel reflectance spectroscopy technique to systematically characterize coronary artery thrombi retrieved by aspiration during pPCI in patients with STEMI, and the clinical utility for predicting distal microvascular obstruction. APPROACH Patients with STEMI treated with pPCI and thrombus aspiration (n = 288) were recruited from the Oxford Acute Myocardial Infarction (OxAMI) Study. Of these, 158 patients underwent cardiac magnetic resonance imaging within 48 h for assessment of microvascular obstruction (MVO). Coronary thrombi were imaged by reflectance spectroscopy across wavelengths 500-800 nm. MAIN RESULTS Spectral data were analysed using function fitting and multivariate models. The coefficient 'c red' determined from the fitting procedure correlated with the visually-assessed colour of thrombi ('red' or 'white') and with MVO. When applied to a reduced data set, consisting of spectra from 20 patients with the largest MVO and from 20 propensity-score-matched patients with no MVO, three multivariate analysis methods were able to discriminate spectra of thrombi from patients without MVO and with the largest MVO. SIGNIFICANCE Reflectance spectral analysis of coronary thrombus provides new insights into the pathology of STEMI, with potential clinical implications for emergency patient care. Further studies are warranted for validation as a point-of-care stratification tool in predicting the degree of microvascular injury and clinical outcomes in STEMI.
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Affiliation(s)
- Giovanni Luigi De Maria
- Oxford Heart Centre, NIHR Biomedical Research Centre, Oxford University Hospitals, John Radcliffe Hospital, Oxford, United Kingdom
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28
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Amiri SA, Van Gent CM, Dankelman J, Hendriks BHW. Intraoperative tumor margin assessment using diffuse reflectance spectroscopy: the effect of electrosurgery on tissue discrimination using ex vivo animal tissue models. BIOMEDICAL OPTICS EXPRESS 2020; 11:2402-2415. [PMID: 32499933 PMCID: PMC7249845 DOI: 10.1364/boe.385621] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 03/11/2020] [Accepted: 04/01/2020] [Indexed: 06/11/2023]
Abstract
Using an intraoperative margin assessment technique during breast-conserving surgery (BCS) helps surgeons to decrease the risk of positive margin occurrence. Diffuse reflectance spectroscopy (DRS) has the potential to discriminate healthy breast tissue from cancerous tissue. We investigated the performance of an electrosurgical knife integrated with a DRS on porcine muscle and adipose tissue. Characterization of the formed debris on the optical fibers after electrosurgery revealed that the contamination is mostly burned tissue. Even with contaminated optical fibers, both tissues could still be discriminated with DRS based on fat/water ratio. Therefore, an electrosurgical knife integrated with DRS may be a promising technology to provide the surgeon with real-time guidance during BCS.
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Affiliation(s)
- Sara Azizian Amiri
- Delft University of Technology, Biomechanical Engineering Department, Delft, The Netherlands
| | - Carlijn M. Van Gent
- Delft University of Technology, Biomechanical Engineering Department, Delft, The Netherlands
| | - Jenny Dankelman
- Delft University of Technology, Biomechanical Engineering Department, Delft, The Netherlands
| | - Benno H. W. Hendriks
- Delft University of Technology, Biomechanical Engineering Department, Delft, The Netherlands
- Philips Research, In-Body Systems Department, Eindhoven, The Netherlands
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29
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Mondal SB, O'Brien CM, Bishop K, Fields RC, Margenthaler JA, Achilefu S. Repurposing Molecular Imaging and Sensing for Cancer Image-Guided Surgery. J Nucl Med 2020; 61:1113-1122. [PMID: 32303598 DOI: 10.2967/jnumed.118.220426] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 03/05/2020] [Indexed: 12/25/2022] Open
Abstract
Gone are the days when medical imaging was used primarily to visualize anatomic structures. The emergence of molecular imaging (MI), championed by radiolabeled 18F-FDG PET, has expanded the information content derived from imaging to include pathophysiologic and molecular processes. Cancer imaging, in particular, has leveraged advances in MI agents and technology to improve the accuracy of tumor detection, interrogate tumor heterogeneity, monitor treatment response, focus surgical resection, and enable image-guided biopsy. Surgeons are actively latching on to the incredible opportunities provided by medical imaging for preoperative planning, intraoperative guidance, and postoperative monitoring. From label-free techniques to enabling cancer-selective imaging agents, image-guided surgery provides surgical oncologists and interventional radiologists both macroscopic and microscopic views of cancer in the operating room. This review highlights the current state of MI and sensing approaches available for surgical guidance. Salient features of nuclear, optical, and multimodal approaches will be discussed, including their strengths, limitations, and clinical applications. To address the increasing complexity and diversity of methods available today, this review provides a framework to identify a contrast mechanism, suitable modality, and device. Emerging low-cost, portable, and user-friendly imaging systems make the case for adopting some of these technologies as the global standard of care in surgical practice.
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Affiliation(s)
- Suman B Mondal
- Department of Radiology, Washington University, St. Louis, Missouri
| | | | - Kevin Bishop
- Department of Radiology, Washington University, St. Louis, Missouri
| | - Ryan C Fields
- Department of Surgery and Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri
| | - Julie A Margenthaler
- Department of Surgery and Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri
| | - Samuel Achilefu
- Department of Radiology, Washington University, St. Louis, Missouri .,Department of Biomedical Engineering, Washington University, St. Louis, Missouri; and.,Department of Biochemistry and Molecular Biophysics, Washington University, St. Louis, Missouri
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30
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Unger J, Hebisch C, Phipps JE, Lagarto JL, Kim H, Darrow MA, Bold RJ, Marcu L. Real-time diagnosis and visualization of tumor margins in excised breast specimens using fluorescence lifetime imaging and machine learning. BIOMEDICAL OPTICS EXPRESS 2020; 11:1216-1230. [PMID: 32206404 PMCID: PMC7075618 DOI: 10.1364/boe.381358] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 01/14/2020] [Accepted: 01/14/2020] [Indexed: 05/03/2023]
Abstract
Tumor-free surgical margins are critical in breast-conserving surgery. In up to 38% of the cases, however, patients undergo a second surgery since malignant cells are found at the margins of the excised resection specimen. Thus, advanced imaging tools are needed to ensure clear margins at the time of surgery. The objective of this study was to evaluate a random forest classifier that makes use of parameters derived from point-scanning label-free fluorescence lifetime imaging (FLIm) measurements of breast specimens as a means to diagnose tumor at the resection margins and to enable an intuitive visualization of a probabilistic classifier on tissue specimen. FLIm data from fresh lumpectomy and mastectomy specimens from 18 patients were used in this study. The supervised training was based on a previously developed registration technique between autofluorescence imaging data and cross-sectional histology slides. A pathologist's histology annotations provide the ground truth to distinguish between adipose, fibrous, and tumor tissue. Current results demonstrate the ability of this approach to classify the tumor with 89% sensitivity and 93% specificity and to rapidly (∼ 20 frames per second) overlay the probabilistic classifier overlaid on excised breast specimens using an intuitive color scheme. Furthermore, we show an iterative imaging refinement that allows surgeons to switch between rapid scans with a customized, low spatial resolution to quickly cover the specimen and slower scans with enhanced resolution (400 μm per point measurement) in suspicious regions where more details are required. In summary, this technique provides high diagnostic prediction accuracy, rapid acquisition, adaptive resolution, nondestructive probing, and facile interpretation of images, thus holding potential for clinical breast imaging based on label-free FLIm.
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Affiliation(s)
- Jakob Unger
- Department of Biomedical Engineering, University of California Davis, California, CA 95616, USA
- Corresponding authors
| | - Christoph Hebisch
- Department of Biomedical Engineering, University of California Davis, California, CA 95616, USA
| | - Jennifer E. Phipps
- Department of Biomedical Engineering, University of California Davis, California, CA 95616, USA
| | - João L. Lagarto
- Department of Biomedical Engineering, University of California Davis, California, CA 95616, USA
| | - Hanna Kim
- Department of Otolaryngology, University of California Davis, California, CA 95817, USA
| | - Morgan A. Darrow
- Department of Pathology and Laboratory Medicine, University of California Davis, California, CA 95817, USA
| | - Richard J. Bold
- Department of Surgery, University of California Davis, California, CA 95817, USA
| | - Laura Marcu
- Department of Biomedical Engineering, University of California Davis, California, CA 95616, USA
- Corresponding authors
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31
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Baltussen EJM, Sterenborg HJCM, Ruers TJM, Dashtbozorg B. Optimizing algorithm development for tissue classification in colorectal cancer based on diffuse reflectance spectra. BIOMEDICAL OPTICS EXPRESS 2019; 10:6096-6113. [PMID: 31853388 PMCID: PMC6913395 DOI: 10.1364/boe.10.006096] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 10/11/2019] [Accepted: 10/31/2019] [Indexed: 06/01/2023]
Abstract
Diffuse reflectance spectroscopy can be used in colorectal cancer surgery for tissue classification. The main challenge in the classification task is to separate healthy colorectal wall from tumor tissue. In this study, four normalization techniques, four feature extraction methods and five classifiers are applied to nine datasets, to obtain the optimal method to separate spectra measured on healthy colorectal wall from spectra measured on tumor tissue. All results are compared to the use of the entire non-normalized spectra. It is found that the most optimal classification approach is to apply a feature extraction method on non-normalized spectra combined with support vector machine or neural network classifier.
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Affiliation(s)
- Elisabeth J. M. Baltussen
- Department of Surgery, Antoni van Leeuwenhoek Hospital – The Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Department of Surgery, Antoni van Leeuwenhoek Hospital – The Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- Department of Surgery, Antoni van Leeuwenhoek Hospital – The Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
- Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Behdad Dashtbozorg
- Department of Surgery, Antoni van Leeuwenhoek Hospital – The Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
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32
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de Boer LL, Kho E, Jóźwiak K, Van de Vijver KK, Vrancken Peeters MJTFD, van Duijnhoven F, Hendriks BHW, Sterenborg HJCM, Ruers TJM. Influence of neoadjuvant chemotherapy on diffuse reflectance spectra of tissue in breast surgery specimens. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:115004. [PMCID: PMC7003145 DOI: 10.1117/1.jbo.24.11.115004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 11/04/2019] [Indexed: 05/28/2023]
Abstract
Diffuse reflectance spectroscopy (DRS) can discriminate different tissue types based on optical characteristics. Since this technology has the ability to detect tumor tissue, several groups have proposed to use DRS for margin assessment during breast-conserving surgery for breast cancer. Nowadays, an increasing number of patients with breast cancer are being treated by neoadjuvant chemotherapy. Limited research has been published on the influence of neoadjuvant chemotherapy on the optical characteristics of the tissue. Hence, it is unclear whether margin assessment based on DRS is feasible in this specific group of patients. We investigate whether there is an effect of neoadjuvant chemotherapy on optical measurements of breast tissue. To this end, DRS measurements were performed on 92 ex-vivo breast specimens from 92 patients, treated with neoadjuvant chemotherapy and without neoadjuvant chemotherapy. Generalized estimating equation (GEE) models were generated, comparing the measurements of patients with and without neoadjuvant chemotherapy in datasets of different tissue types using a significance level of 5%. As input for the GEE models, either the intensity at a specific wavelength or a fit parameter, derived from the spectrum, was used. In the evaluation of the intensity, no influence of neoadjuvant chemotherapy was found, since none of the wavelengths were significantly different between the measurements with and the measurements without neoadjuvant chemotherapy in any of the datasets. These results were confirmed by the analysis of the fit parameters, which showed a significant difference for the amount of collagen in only one dataset. All other fit parameters were not significant for any of the datasets. These findings may indicate that assessment of the resection margin with DRS is also feasible in the growing population of breast cancer patients who receive neoadjuvant chemotherapy. However, it is possible that we did not detect neoadjuvant chemotherapy effect in the some of the datasets due to the small number of measurements in those datasets.
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Affiliation(s)
- Lisanne L. de Boer
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Esther Kho
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Katarzyna Jóźwiak
- The Netherlands Cancer Institute, Department of Epidemiology and Biostatistics, The Netherlands
- Institute of Biostatistics and Registry Research, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany
| | - Koen K. Van de Vijver
- The Netherlands Cancer Institute, Department of Pathology, Amsterdam, The Netherlands
- Ghent University Hospital, Department of Pathology, Gent, Belgium
| | | | | | - Benno H. W. Hendriks
- Philips Research, Eindhoven, The Netherlands
- Delft University of Technology, Biomechanical Engineering Department, Delft, The Netherlands
| | - Henricus J. C. M. Sterenborg
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
- Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
- University of Twente, TNW, Technical Medical Centre, Enschede, The Netherlands
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33
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Burström G, Swamy A, Spliethoff JW, Reich C, Babic D, Hendriks BHW, Skulason H, Persson O, Elmi Terander A, Edström E. Diffuse reflectance spectroscopy accurately identifies the pre-cortical zone to avoid impending pedicle screw breach in spinal fixation surgery. BIOMEDICAL OPTICS EXPRESS 2019; 10:5905-5920. [PMID: 31799054 PMCID: PMC6865097 DOI: 10.1364/boe.10.005905] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 10/09/2019] [Accepted: 10/09/2019] [Indexed: 05/03/2023]
Abstract
Pedicle screw placement accuracy during spinal fixation surgery varies greatly and severe misplacement has been reported in 1-6.5% of screws. Diffuse reflectance (DR) spectroscopy has previously been shown to reliably discriminate between tissues in the human body. We postulate that it could be used to discriminate between cancellous and cortical bone. Therefore, the purpose of this study is to validate DR spectroscopy as a warning system to detect impending pedicle screw breach in a cadaveric surgical setting using typical clinical breach scenarios. DR spectroscopy was incorporated at the tip of an integrated pedicle screw and screw driver used for tissue probing during pedicle screw insertions on six cadavers. Measurements were collected in the wavelength range of 400-1600 nm and each insertion was planned to result in a breach. Measurements were labelled as cancellous, cortical or representing a pre-cortical zone (PCZ) in between, based on information from cone beam computed tomographies at corresponding positions. In addition, DR spectroscopy data was recorded after breach. Four typical pedicle breach types were performed, and a total of 45 pedicle breaches were recorded. For each breach direction, the technology was able to detect the transition of the screw tip from the cancellous bone to the PCZ (P < 0.001), to cortical bone (P < 0.001), and to a subsequent breach (P < 0.001). Using support vector machine (SVM) classification, breach could reliably be detected with a sensitivity of 98.3 % [94.3-100 %] and a specificity of 97.7 % [91.0-100 %]. We conclude that DR spectroscopy reliably identifies the area of transition from cancellous to cortical bone in typical breach scenarios and can warn the surgeon of impending pedicle breach, thereby resulting in safer spinal fixation surgeries.
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Affiliation(s)
- Gustav Burström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden
| | - Akash Swamy
- Delft University of Technology, Department of Biomechanical Engineering, Delft, The Netherlands
- Department of In-body Systems, Philips Research, Royal Philips NV, Eindhoven, The Netherlands
| | - Jarich W. Spliethoff
- Department of In-body Systems, Philips Research, Royal Philips NV, Eindhoven, The Netherlands
| | - Christian Reich
- Department of In-body Systems, Philips Research, Royal Philips NV, Eindhoven, The Netherlands
| | - Drazenko Babic
- Department of In-body Systems, Philips Research, Royal Philips NV, Eindhoven, The Netherlands
| | - Benno H. W. Hendriks
- Delft University of Technology, Department of Biomechanical Engineering, Delft, The Netherlands
- Department of In-body Systems, Philips Research, Royal Philips NV, Eindhoven, The Netherlands
| | - Halldor Skulason
- Department of Neurosurgery, Landspitali University Hospital, Reykjavik, Iceland
| | - Oscar Persson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden
| | - Adrian Elmi Terander
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden
| | - Erik Edström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden
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