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Suero Molina E, Bruneau M, Reuter G, Shahein M, Cavallo LM, Daniel RT, Kasper EM, Froelich S, Jouanneau E, Manet R, Messerer M, Mazzatenta D, Meling TR, Roche PH, Schroeder HWS, Tatagiba M, Visocchi M, Prevedello DM, Stummer W, Cornelius JF. Fluorescence guidance in skull base surgery: Applications and limitations - A systematic review. BRAIN & SPINE 2024; 4:103328. [PMID: 39309550 PMCID: PMC11416557 DOI: 10.1016/j.bas.2024.103328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 08/18/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024]
Abstract
Introduction Intraoperative fluorescence guidance is a well-established surgical adjunct in high-grade glioma surgery. In contrast, the clinical use of such dyes and technology has been scarcely reported in skull base surgery. Research question We aimed to systematically review the clinical applications of different fluorophores in both open and endonasal skull base surgery. Material and methods We performed a systematic review and discussed the current literature on fluorescence guidance in skull base surgery. Results After a comprehensive literature search, 77 articles on skull base fluorescence guidance were evaluated. A qualitative analysis of the articles is presented, discussing clinical indications and current controversies. The use of intrathecal fluorescein was the most frequently reported in the literature. Beyond that, 5-ALA and ICG were two other fluorescent dyes most extensively discussed, with some experimental fluorophore applications in skull base surgery. Discussion and conclusion Intraoperative fluorescence imaging can serve as an adjunct technology in skull base surgery. The scope of initial indications of these fluorophores has expanded beyond malignant glioma resection alone. We discuss current use and controversies and present an extensive overview of additional indications for fluorescence imaging in skull base pathologies. Further quantitative studies will be needed in the future, focusing on tissue selectivity and time-dependency of the different fluorophores currently commercially available, as well as the development of new compounds to expand applications and facilitate skull base surgeries.
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Affiliation(s)
- Eric Suero Molina
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Michael Bruneau
- Department of Neurosurgery, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Gilles Reuter
- Department of Neurosurgery, University Hospital of Liège, Liège, Belgium
| | | | - Luigi M. Cavallo
- Department of Neurosciences and Reproductive and Dental Sciences, Division of Neurosurgery, Federico II University of Naples, Policlinico Federico II University Hospital, Italy
| | - Roy T. Daniel
- Department of Neurosurgery, Department of Neuroscience, Centre Hospitalier Universitaire Vaudois, University Hospital Lausanne, Switzerland
| | - Ekkehard M. Kasper
- Department of Neurosurgery, Boston University Medical School, MA and Steward Medical Group, Brighton, MA/USA McMaster University Faculty of Health Sciences, Hamilton, ON, Canada
| | - Sebastien Froelich
- Department of Neurosurgery, Lariboisière Hospital, Université Paris Diderot, Paris, France
| | - Emanuel Jouanneau
- Department of Neurosurgery, Hôpital Neurologique Pierre Wertheimer, Lyon, France
| | - Romain Manet
- Department of Neurosurgery, Hôpital Neurologique Pierre Wertheimer, Lyon, France
| | - Mahmoud Messerer
- Department of Neurosciences and Reproductive and Dental Sciences, Division of Neurosurgery, Federico II University of Naples, Policlinico Federico II University Hospital, Italy
| | - Diego Mazzatenta
- Department of Neurosurgery, Neurological Sciences Institut IRCCS, Bologna, Italy
| | - Torstein R. Meling
- Department of Neurosurgery, The National Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Pierre-Hugues Roche
- Department of Neurosurgery, Aix-Marseille Université, Assistance Publique-Hôpitaux de Marseille, Hôpital Nord, Marseille, France
| | | | - Marcos Tatagiba
- Department of Neurosurgery, University Hospital Tübingen, Tübingen, Germany
| | - Massimiliano Visocchi
- Department of Neurosurgery, Institute of Neurosurgery Catholic University of Rome, Italy
| | - Daniel M. Prevedello
- Deparmtent of Neurosurgery, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Walter Stummer
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
| | - Jan F. Cornelius
- Department of Neurosurgery, University Hospital of Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - EANS Skull Base Section
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
- Department of Neurosurgery, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Department of Neurosurgery, University Hospital of Liège, Liège, Belgium
- Department of Neurosurgery, Mansoura University, Egypt
- Department of Neurosciences and Reproductive and Dental Sciences, Division of Neurosurgery, Federico II University of Naples, Policlinico Federico II University Hospital, Italy
- Department of Neurosurgery, Department of Neuroscience, Centre Hospitalier Universitaire Vaudois, University Hospital Lausanne, Switzerland
- Department of Neurosurgery, Boston University Medical School, MA and Steward Medical Group, Brighton, MA/USA McMaster University Faculty of Health Sciences, Hamilton, ON, Canada
- Department of Neurosurgery, Lariboisière Hospital, Université Paris Diderot, Paris, France
- Department of Neurosurgery, Hôpital Neurologique Pierre Wertheimer, Lyon, France
- Department of Neurosurgery, Neurological Sciences Institut IRCCS, Bologna, Italy
- Department of Neurosurgery, The National Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Neurosurgery, Aix-Marseille Université, Assistance Publique-Hôpitaux de Marseille, Hôpital Nord, Marseille, France
- Department of Neurosurgery, University Medicine Greifswald, Germany
- Department of Neurosurgery, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, Institute of Neurosurgery Catholic University of Rome, Italy
- Deparmtent of Neurosurgery, The Ohio State University College of Medicine, Columbus, OH, USA
- Department of Neurosurgery, University Hospital of Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
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Black D, Liquet B, Di Ieva A, Stummer W, Suero Molina E. Spectral library and method for sparse unmixing of hyperspectral images in fluorescence guided resection of brain tumors. BIOMEDICAL OPTICS EXPRESS 2024; 15:4406-4424. [PMID: 39346979 PMCID: PMC11427211 DOI: 10.1364/boe.528535] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/06/2024] [Accepted: 06/06/2024] [Indexed: 10/01/2024]
Abstract
Through spectral unmixing, hyperspectral imaging (HSI) in fluorescence-guided brain tumor surgery has enabled the detection and classification of tumor regions invisible to the human eye. Prior unmixing work has focused on determining a minimal set of viable fluorophore spectra known to be present in the brain and effectively reconstructing human data without overfitting. With these endmembers, non-negative least squares regression (NNLS) was commonly used to compute the abundances. However, HSI images are heterogeneous, so one small set of endmember spectra may not fit all pixels well. Additionally, NNLS is the maximum likelihood estimator only if the measurement is normally distributed, and it does not enforce sparsity, which leads to overfitting and unphysical results. In this paper, we analyzed 555666 HSI fluorescence spectra from 891 ex vivo measurements of patients with various brain tumors to show that a Poisson distribution indeed models the measured data 82% better than a Gaussian in terms of the Kullback-Leibler divergence, and that the endmember abundance vectors are sparse. With this knowledge, we introduce (1) a library of 9 endmember spectra, including PpIX (620 nm and 634 nm photostates), NADH, FAD, flavins, lipofuscin, melanin, elastin, and collagen, (2) a sparse, non-negative Poisson regression algorithm to perform physics-informed unmixing with this library without overfitting, and (3) a highly realistic spectral measurement simulation with known endmember abundances. The new unmixing method was then tested on the human and simulated data and compared to four other candidate methods. It outperforms previous methods with 25% lower error in the computed abundances on the simulated data than NNLS, lower reconstruction error on human data, better sparsity, and 31 times faster runtime than state-of-the-art Poisson regression. This method and library of endmember spectra can enable more accurate spectral unmixing to aid the surgeon better during brain tumor resection.
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Affiliation(s)
- David Black
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Benoit Liquet
- School of Mathematical and Physical Sciences, Macquarie University, Sydney, Australia
- Laboratoire de Mathématiques et de ses Applications, E2S-UPPA, Université de Pau & Pays de L'Adour, France
- Computational NeuroSurgery (CNS) Lab, Macquarie University, Sydney, Australia
| | - Antonio Di Ieva
- Computational NeuroSurgery (CNS) Lab, Macquarie University, Sydney, Australia
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Walter Stummer
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
| | - Eric Suero Molina
- Computational NeuroSurgery (CNS) Lab, Macquarie University, Sydney, Australia
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
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Black D, Byrne D, Walke A, Liu S, Di Ieva A, Kaneko S, Stummer W, Salcudean T, Suero Molina E. Towards machine learning-based quantitative hyperspectral image guidance for brain tumor resection. COMMUNICATIONS MEDICINE 2024; 4:131. [PMID: 38965358 PMCID: PMC11224305 DOI: 10.1038/s43856-024-00562-3] [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: 07/19/2023] [Accepted: 06/25/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Complete resection of malignant gliomas is hampered by the difficulty in distinguishing tumor cells at the infiltration zone. Fluorescence guidance with 5-ALA assists in reaching this goal. Using hyperspectral imaging, previous work characterized five fluorophores' emission spectra in most human brain tumors. METHODS In this paper, the effectiveness of these five spectra was explored for different tumor and tissue classification tasks in 184 patients (891 hyperspectral measurements) harboring low- (n = 30) and high-grade gliomas (n = 115), non-glial primary brain tumors (n = 19), radiation necrosis (n = 2), miscellaneous (n = 10) and metastases (n = 8). Four machine-learning models were trained to classify tumor type, grade, glioma margins, and IDH mutation. RESULTS Using random forests and multilayer perceptrons, the classifiers achieve average test accuracies of 84-87%, 96.1%, 86%, and 91% respectively. All five fluorophore abundances vary between tumor margin types and tumor grades (p < 0.01). For tissue type, at least four of the five fluorophore abundances are significantly different (p < 0.01) between all classes. CONCLUSIONS These results demonstrate the fluorophores' differing abundances in different tissue classes and the value of the five fluorophores as potential optical biomarkers, opening new opportunities for intraoperative classification systems in fluorescence-guided neurosurgery.
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Affiliation(s)
- David Black
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Declan Byrne
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Anna Walke
- Department of Neurosurgery, University Hospital Münster, Münster, Germany
| | - Sidong Liu
- Computational NeuroSurgery (CNS) Lab, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
| | - Antonio Di Ieva
- Computational NeuroSurgery (CNS) Lab, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
| | - Sadahiro Kaneko
- Department of Neurosurgery, Hokkaido Medical Center, National Hospital Organization, Sapporo, Japan
| | - Walter Stummer
- Department of Neurosurgery, University Hospital Münster, Münster, Germany
| | - Tim Salcudean
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Eric Suero Molina
- Department of Neurosurgery, University Hospital Münster, Münster, Germany.
- Computational NeuroSurgery (CNS) Lab, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia.
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Gautheron A, Bernstock JD, Picart T, Guyotat J, Valdés PA, Montcel B. 5-ALA induced PpIX fluorescence spectroscopy in neurosurgery: a review. Front Neurosci 2024; 18:1310282. [PMID: 38348134 PMCID: PMC10859467 DOI: 10.3389/fnins.2024.1310282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/02/2024] [Indexed: 02/15/2024] Open
Abstract
The review begins with an overview of the fundamental principles/physics underlying light, fluorescence, and other light-matter interactions in biological tissues. It then focuses on 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence spectroscopy methods used in neurosurgery (e.g., intensity, time-resolved) and in so doing, describe their specific features (e.g., hardware requirements, main processing methods) as well as their strengths and limitations. Finally, we review current clinical applications and future directions of 5-ALA-induced protoporphyrin IX (PpIX) fluorescence spectroscopy in neurosurgery.
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Affiliation(s)
- A. Gautheron
- Université Jean Monnet Saint-Etienne, CNRS, Institut d Optique Graduate School, Laboratoire Hubert Curien UMR 5516, Saint-Étienne, France
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
| | - J. D. Bernstock
- Department of Neurosurgery, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - T. Picart
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, Lyon, France
- Université Lyon 1, INSERM 1052, CNRS 5286, Lyon, France
| | - J. Guyotat
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, Lyon, France
| | - P. A. Valdés
- Department of Neurosurgery, University of Texas Medical Branch, Galveston, TX, United States
- Department of Neurobiology, University of Texas Medical Branch, Galveston, TX, United States
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, United States
| | - B. Montcel
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
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Mohtasebi M, Huang C, Zhao M, Mazdeyasna S, Liu X, Haratbar SR, Fathi F, Sun J, Pittman T, Yu G. A Wearable Fluorescence Imaging Device for Intraoperative Identification of Human Brain Tumors. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2023; 12:225-232. [PMID: 38196823 PMCID: PMC10776094 DOI: 10.1109/jtehm.2023.3338564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/02/2023] [Accepted: 11/27/2023] [Indexed: 01/11/2024]
Abstract
Malignant glioma (MG) is the most common type of primary malignant brain tumors. Surgical resection of MG remains the cornerstone of therapy and the extent of resection correlates with patient survival. A limiting factor for resection, however, is the difficulty in differentiating the tumor from normal tissue during surgery. Fluorescence imaging is an emerging technique for real-time intraoperative visualization of MGs and their boundaries. However, most clinical grade neurosurgical operative microscopes with fluorescence imaging ability are hampered by low adoption rates due to high cost, limited portability, limited operation flexibility, and lack of skilled professionals with technical knowledge. To overcome the limitations, we innovatively integrated miniaturized light sources, flippable filters, and a recording camera to the surgical eye loupes to generate a wearable fluorescence eye loupe (FLoupe) device for intraoperative imaging of fluorescent MGs. Two FLoupe prototypes were constructed for imaging of Fluorescein and 5-aminolevulinic acid (5-ALA), respectively. The wearable FLoupe devices were tested on tumor-simulating phantoms and patients with MGs. Comparable results were observed against the standard neurosurgical operative microscope (PENTERO® 900) with fluorescence kits. The affordable and wearable FLoupe devices enable visualization of both color and fluorescence images with the same quality as the large and expensive stationary operative microscopes. The wearable FLoupe device allows for a greater range of movement, less obstruction, and faster/easier operation. Thus, it reduces surgery time and is more easily adapted to the surgical environment than unwieldy neurosurgical operative microscopes. Clinical and Translational Impact Statement-The affordable and wearable fluorescence imaging device developed in this study enables neurosurgeons to observe brain tumors with the same clarity and greater flexibility compared to bulky and costly operative microscopes.
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Affiliation(s)
- Mehrana Mohtasebi
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
| | - Chong Huang
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
| | - Mingjun Zhao
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
| | - Siavash Mazdeyasna
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
| | - Xuhui Liu
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
| | | | - Faraneh Fathi
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
| | | | - Thomas Pittman
- Department of NeurosurgeryUniversity of KentuckyLexingtonKY40506USA
| | - Guoqiang Yu
- Department of Biomedical EngineeringUniversity of KentuckyLexingtonKY40506USA
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Suero Molina E, Black D, Walke A, Azemi G, D’Alessandro F, König S, Stummer W. Unraveling the blue shift in porphyrin fluorescence in glioma: The 620 nm peak and its potential significance in tumor biology. Front Neurosci 2023; 17:1261679. [PMID: 38027504 PMCID: PMC10657867 DOI: 10.3389/fnins.2023.1261679] [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: 07/19/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
In glioma surgery, the low-density infiltration zone of tumors is difficult to detect by any means. While, for instance, 5-aminolevulinic acid (5-ALA)-induced fluorescence is a well-established surgical procedure for maximizing resection of malignant gliomas, a cell density in tumor tissue of 20-30% is needed to observe visual fluorescence. Hyperspectral imaging is a powerful technique for the optical characterization of brain tissue, which accommodates the complex spectral properties of gliomas. Thereby, knowledge about the signal source is essential to generate specific separation (unmixing) procedures for the different spectral characteristics of analytes and estimate compound abundances. It was stated that protoporphyrin IX (PpIX) fluorescence consists mainly of emission peaks at 634 nm (PpIX634) and 620 nm (PpIX620). However, other members of the substance group of porphyrins fluoresce similarly to PpIX due to their common tetrapyrrole core structure. While the PpIX634 signal has reliably been assigned to PpIX, it has not yet been analyzed if PpIX620 might result from a different porphyrin rather than being a second photo state of PpIX. We thus reviewed more than 200,000 spectra from various tumors measured in almost 600 biopsies of 130 patients. Insufficient consideration of autofluorescence led to artificial inflation of the PpIX620 peak in the past. Recently, five basis spectra (PpIX634, PpIX620, flavin, lipofuscin, and NADH) were described and incorporated into the analysis algorithm, which allowed more accurate unmixing of spectral abundances. We used the improved algorithm to investigate the PpIX620 signal more precisely and investigated coproporphyrin III (CpIII) fluorescence phantoms for spectral unmixing. Our findings show that the PpIX634 peak was the primary source of the 5-ALA-induced fluorescence. CpIII had a similar spectral characteristic to PpIX620. The supplementation of 5-ALA may trigger the increased production of porphyrins other than PpIX within the heme biosynthesis pathway, including that of CpIII. It is essential to correctly separate autofluorescence from the main PpIX634 peak to analyze the fluorescence signal. This article highlights the need for a comprehensive understanding of the spectral complexity in gliomas and suggests less significance of the 620 nm fluorescence peak for PpIX analysis and visualization.
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Affiliation(s)
- Eric Suero Molina
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
- Computational NeuroSurgery (CNS) Lab, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
| | - David Black
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Anna Walke
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
- Core Unit Proteomics, Interdisciplinary Centre for Clinical Research, University of Münster, Münster, Germany
| | - Ghasem Azemi
- Computational NeuroSurgery (CNS) Lab, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
| | - Fabio D’Alessandro
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
- Core Unit Proteomics, Interdisciplinary Centre for Clinical Research, University of Münster, Münster, Germany
| | - Simone König
- Core Unit Proteomics, Interdisciplinary Centre for Clinical Research, University of Münster, Münster, Germany
| | - Walter Stummer
- Department of Neurosurgery, University Hospital of Münster, Münster, Germany
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MacCormac O, Noonan P, Janatka M, Horgan CC, Bahl A, Qiu J, Elliot M, Trotouin T, Jacobs J, Patel S, Bergholt MS, Ashkan K, Ourselin S, Ebner M, Vercauteren T, Shapey J. Lightfield hyperspectral imaging in neuro-oncology surgery: an IDEAL 0 and 1 study. Front Neurosci 2023; 17:1239764. [PMID: 37790587 PMCID: PMC10544348 DOI: 10.3389/fnins.2023.1239764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/31/2023] [Indexed: 10/05/2023] Open
Abstract
Introduction Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous iterations of intra-operative HSI systems have shown limitations, either due to carrying a large footprint limiting ease of use within the confines of a neurosurgical theater environment, having a slow image acquisition time, or by compromising spatial/spectral resolution in favor of improvements to the surgical workflow. Lightfield hyperspectral imaging is a novel technique that has the potential to facilitate video rate image acquisition whilst maintaining a high spectral resolution. Our pre-clinical and first-in-human studies (IDEAL 0 and 1, respectively) demonstrate the necessary steps leading to the first in-vivo use of a real-time lightfield hyperspectral system in neuro-oncology surgery. Methods A lightfield hyperspectral camera (Cubert Ultris ×50) was integrated in a bespoke imaging system setup so that it could be safely adopted into the open neurosurgical workflow whilst maintaining sterility. Our system allowed the surgeon to capture in-vivo hyperspectral data (155 bands, 350-1,000 nm) at 1.5 Hz. Following successful implementation in a pre-clinical setup (IDEAL 0), our system was evaluated during brain tumor surgery in a single patient to remove a posterior fossa meningioma (IDEAL 1). Feedback from the theater team was analyzed and incorporated in a follow-up design aimed at implementing an IDEAL 2a study. Results Focusing on our IDEAL 1 study results, hyperspectral information was acquired from the cerebellum and associated meningioma with minimal disruption to the neurosurgical workflow. To the best of our knowledge, this is the first demonstration of HSI acquisition with 100+ spectral bands at a frame rate over 1Hz in surgery. Discussion This work demonstrated that a lightfield hyperspectral imaging system not only meets the design criteria and specifications outlined in an IDEAL-0 (pre-clinical) study, but also that it can translate into clinical practice as illustrated by a successful first in human study (IDEAL 1). This opens doors for further development and optimisation, given the increasing evidence that hyperspectral imaging can provide live, wide-field, and label-free intra-operative imaging and tissue differentiation.
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Affiliation(s)
- Oscar MacCormac
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
- Department of Neurosurgery, King's College Hospital, London, United Kingdom
| | - Philip Noonan
- Hypervision Surgical Limited, London, United Kingdom
| | - Mirek Janatka
- Hypervision Surgical Limited, London, United Kingdom
| | | | - Anisha Bahl
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
| | - Jianrong Qiu
- School of Craniofacial and Regenerative Biology, King's College London, London, United Kingdom
| | - Matthew Elliot
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
- Department of Neurosurgery, King's College Hospital, London, United Kingdom
| | - Théo Trotouin
- Hypervision Surgical Limited, London, United Kingdom
| | - Jaco Jacobs
- Hypervision Surgical Limited, London, United Kingdom
| | - Sabina Patel
- Department of Neurosurgery, King's College Hospital, London, United Kingdom
| | - Mads S. Bergholt
- School of Craniofacial and Regenerative Biology, King's College London, London, United Kingdom
| | - Keyoumars Ashkan
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
- Department of Neurosurgery, King's College Hospital, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
- Hypervision Surgical Limited, London, United Kingdom
| | - Michael Ebner
- Hypervision Surgical Limited, London, United Kingdom
| | - Tom Vercauteren
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
- Hypervision Surgical Limited, London, United Kingdom
| | - Jonathan Shapey
- School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom
- Department of Neurosurgery, King's College Hospital, London, United Kingdom
- Hypervision Surgical Limited, London, United Kingdom
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