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Burström G, Amini M, El-Hajj VG, Arfan A, Gharios M, Buwaider A, Losch MS, Manni F, Edström E, Elmi-Terander A. Optical Methods for Brain Tumor Detection: A Systematic Review. J Clin Med 2024; 13:2676. [PMID: 38731204 PMCID: PMC11084501 DOI: 10.3390/jcm13092676] [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: 04/11/2024] [Revised: 04/28/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.
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Affiliation(s)
- Gustav Burström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Misha Amini
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Victor Gabriel El-Hajj
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Arooj Arfan
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Maria Gharios
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Ali Buwaider
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Merle S. Losch
- Department of Biomechanical Engineering, Faculty of Mechanical Engineering, Delft University of Technology, 2627 Delft, The Netherlands
| | - Francesca Manni
- Department of Electrical Engineering, Eindhoven University of Technology (TU/e), 5612 Eindhoven, The Netherlands;
| | - Erik Edström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
| | - Adrian Elmi-Terander
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
- Department of Surgical Sciences, Uppsala University, 751 35 Uppsala, Sweden
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Liu Y, Ye F, Yang C, Jiang H. Use of in vivo Raman spectroscopy and cryoablation for diagnosis and treatment of bladder cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 308:123707. [PMID: 38043292 DOI: 10.1016/j.saa.2023.123707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/13/2023] [Accepted: 11/27/2023] [Indexed: 12/05/2023]
Abstract
Transurethral resection of bladder tumor (TURBT) is the first-line treatment option for non-muscle invasive bladder cancer (NMIBC), but residual tumor often remains after TURBT, thereby leading to cancer recurrence. Here, we introduce combined use of in vivo Raman spectroscopy and in vivo cryoablation as a new approach to detect and remove residual bladder tumor during TURBT. Bladder cancer (BCa) patients treated with TURBT at our urological department between Dec 2019 and Jan 2021 were collected. First, Raman signals were collected from 74 BCa patients to build reference spectra of normal bladder tissue and of bladder cancers of different pathological types. Then, another 53 BCa patients were randomly categorized into two groups, 26 patients accepted traditional TURBT, 27 patients accepted TURBT followed by Raman scanning and cryoablation if Raman detected existence of residual tumor. The recurrence rates of the two groups until Oct 2022 were compared. Raman was capable of discriminating normal bladder tissue and BCa with a sensitivity and specificity of 90.5% and 80.8 %; and discriminating invasive (T1, T2) and noninvasive (Ta) BCa with a sensitivity and specificity of 83.3 % and 87.3 %. During follow-up, 2 in 27 patients had cancer recurrence in Raman-Cryoablation group, while 8 in 26 patients had cancer recurrence in traditional TURBT group. Combined use of Raman and cryoablation significantly reduced cancer recurrence (p = 0.0394). Raman and cryoablation can serve as an adjuvant therapy to TURBT to improve therapeutic effects and reduce recurrence rate.
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Affiliation(s)
- Yufei Liu
- Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - Fangdie Ye
- Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Chen Yang
- Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Haowen Jiang
- Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China.
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Zamani E, Ksantini N, Sheehy G, Ember KJI, Baloukas B, Zabeida O, Trang T, Mahfoud M, Sapieha JE, Martinu L, Leblond F. Spectral effects and enhancement quantification in healthy human saliva with surface-enhanced Raman spectroscopy using silver nanopillar substrates. Lasers Surg Med 2024; 56:206-217. [PMID: 38073098 DOI: 10.1002/lsm.23746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/15/2023] [Accepted: 11/21/2023] [Indexed: 02/21/2024]
Abstract
OBJECTIVES Raman spectroscopy as a diagnostic tool for biofluid applications is limited by low inelastic scattering contributions compared to the fluorescence background from biomolecules. Surface-enhanced Raman spectroscopy (SERS) can increase Raman scattering signals, thereby offering the potential to reduce imaging times. We aimed to evaluate the enhancement related to the plasmonic effect and quantify the improvements in terms of spectral quality associated with SERS measurements in human saliva. METHODS Dried human saliva was characterized using spontaneous Raman spectroscopy and SERS. A fabrication protocol was implemented leading to the production of silver (Ag) nanopillar substrates by glancing angle deposition. Two different imaging systems were used to interrogate saliva from 161 healthy donors: a custom single-point macroscopic system and a Raman micro-spectroscopy instrument. Quantitative metrics were established to compare spontaneous RS and SERS measurements: the Raman spectroscopy quality factor (QF), the photonic count rate (PR), the signal-to-background ratio (SBR). RESULTS SERS measurements acquired with an excitation energy four times smaller than with spontaneous RS resulted in improved QF, PR values an order of magnitude larger and a SBR twice as large. The SERS enhancement reached 100×, depending on which Raman bands were considered. CONCLUSIONS Single-point measurement of dried saliva with silver nanopillars substrates led to reproducible SERS measurements, paving the way to real-time tools of diagnosis in human biofluids.
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Affiliation(s)
- Esmat Zamani
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Nassim Ksantini
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Guillaume Sheehy
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Katherine J I Ember
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Bill Baloukas
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
| | - Oleg Zabeida
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
| | - Tran Trang
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Myriam Mahfoud
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | | | - Ludvik Martinu
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
| | - Frédéric Leblond
- Department of Engineering Physics, Polytechnique Montreal, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Canada
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Kaynar G, Cakmakci D, Bund C, Todeschi J, Namer IJ, Cicek AE. PiDeeL: metabolic pathway-informed deep learning model for survival analysis and pathological classification of gliomas. Bioinformatics 2023; 39:btad684. [PMID: 37952175 PMCID: PMC10663986 DOI: 10.1093/bioinformatics/btad684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/19/2023] [Accepted: 11/10/2023] [Indexed: 11/14/2023] Open
Abstract
MOTIVATION Online assessment of tumor characteristics during surgery is important and has the potential to establish an intra-operative surgeon feedback mechanism. With the availability of such feedback, surgeons could decide to be more liberal or conservative regarding the resection of the tumor. While there are methods to perform metabolomics-based tumor pathology prediction, their model complexity predictive performance is limited by the small dataset sizes. Furthermore, the information conveyed by the feedback provided on the tumor tissue could be improved both in terms of content and accuracy. RESULTS In this study, we propose a metabolic pathway-informed deep learning model (PiDeeL) to perform survival analysis and pathology assessment based on metabolite concentrations. We show that incorporating pathway information into the model architecture substantially reduces parameter complexity and achieves better survival analysis and pathological classification performance. With these design decisions, we show that PiDeeL improves tumor pathology prediction performance of the state-of-the-art in terms of the Area Under the ROC Curve by 3.38% and the Area Under the Precision-Recall Curve by 4.06%. Similarly, with respect to the time-dependent concordance index (c-index), PiDeeL achieves better survival analysis performance (improvement of 4.3%) when compared to the state-of-the-art. Moreover, we show that importance analyses performed on input metabolite features as well as pathway-specific neurons of PiDeeL provide insights into tumor metabolism. We foresee that the use of this model in the surgery room will help surgeons adjust the surgery plan on the fly and will result in better prognosis estimates tailored to surgical procedures. AVAILABILITY AND IMPLEMENTATION The code is released at https://github.com/ciceklab/PiDeeL. The data used in this study are released at https://zenodo.org/record/7228791.
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Affiliation(s)
- Gun Kaynar
- Computer Engineering Department, Bilkent University, 06800 Ankara, Turkey
| | - Doruk Cakmakci
- School of Computer Science, McGill University, Montreal, QC, H3A 0E9, Canada
| | - Caroline Bund
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France
- ICube, University of Strasbourg, CNRS UMR, 7357, Strasbourg 67000, France
- Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | - Julien Todeschi
- Department of Neurosurgery, University Hospitals of Strasbourg, Strasbourg, 67091, France
| | - Izzie Jacques Namer
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France
- ICube, University of Strasbourg, CNRS UMR, 7357, Strasbourg 67000, France
- Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | - A Ercument Cicek
- Computer Engineering Department, Bilkent University, 06800 Ankara, Turkey
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, United States
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Bin-Alamer O, Abou-Al-Shaar H, Gersey ZC, Huq S, Kallos JA, McCarthy DJ, Head JR, Andrews E, Zhang X, Hadjipanayis CG. Intraoperative Imaging and Optical Visualization Techniques for Brain Tumor Resection: A Narrative Review. Cancers (Basel) 2023; 15:4890. [PMID: 37835584 PMCID: PMC10571802 DOI: 10.3390/cancers15194890] [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: 08/29/2023] [Revised: 09/26/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023] Open
Abstract
Advancements in intraoperative visualization and imaging techniques are increasingly central to the success and safety of brain tumor surgery, leading to transformative improvements in patient outcomes. This comprehensive review intricately describes the evolution of conventional and emerging technologies for intraoperative imaging, encompassing the surgical microscope, exoscope, Raman spectroscopy, confocal microscopy, fluorescence-guided surgery, intraoperative ultrasound, magnetic resonance imaging, and computed tomography. We detail how each of these imaging modalities contributes uniquely to the precision, safety, and efficacy of neurosurgical procedures. Despite their substantial benefits, these technologies share common challenges, including difficulties in image interpretation and steep learning curves. Looking forward, innovations in this field are poised to incorporate artificial intelligence, integrated multimodal imaging approaches, and augmented and virtual reality technologies. This rapidly evolving landscape represents fertile ground for future research and technological development, aiming to further elevate surgical precision, safety, and, most critically, patient outcomes in the management of brain tumors.
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Affiliation(s)
- Othman Bin-Alamer
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Hussam Abou-Al-Shaar
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Zachary C. Gersey
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Sakibul Huq
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Justiss A. Kallos
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - David J. McCarthy
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Jeffery R. Head
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Edward Andrews
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Xiaoran Zhang
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Constantinos G. Hadjipanayis
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
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Herta J, Cho A, Roetzer-Pejrimovsky T, Höftberger R, Marik W, Kronreif G, Peilnsteiner T, Rössler K, Wolfsberger S. Optimizing maximum resection of glioblastoma: Raman spectroscopy versus 5-aminolevulinic acid. J Neurosurg 2023; 139:334-343. [PMID: 36681953 DOI: 10.3171/2022.11.jns22693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 11/16/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE The objective of this study was to assess and compare the potential of 5-aminolevulinic acid (5-ALA) and Raman spectroscopy (RS) in detecting tumor-infiltrated brain in patients with glioblastoma (GBM). METHODS Between July 2020 and October 2021, the authors conducted a prospective clinical trial with 15 patients who underwent neurosurgical treatment of newly diagnosed and histologically verified GBM. A solid contrast-enhancing tumor core and peritumoral tissue were investigated intraoperatively for cancer cells by using 5-ALA and RS to achieve pathology-tailored maximum resection. In each case, a minimum of 10 biopsies were sampled from navigation-guided areas. Two neuropathologists examined the biopsies for the presence of neoplastic cells. The detection performance of 5-ALA and RS alone and in combination was assessed. Pre- and postoperative MRI, Karnofsky Performance Status (KPS), and National Institutes of Health Stroke Scale (NIHSS) scores were compared, and median progression-free survival (PFS) was evaluated. RESULTS A total of 185 biopsy samples were harvested from the contrast-enhancing tumor core (n = 19) and peritumoral tissue (n = 166). In the tumor core, 5-ALA and RS each showed a sensitivity of 100%. In the peritumoral tissue, 5-ALA was less sensitive than RS in detecting cancer (46% vs 69%) but showed higher specificity (81% vs 57%). When the two methods were combined, the accuracy of tumor detection was increased by about 10%. Pathology-tailored resection led to a 52% increase in resection volume comparing the volume of preoperative contrast enhancement with the postoperative resection cavity on MRI (p = 0.0123). Eloquent brain involvement prevented gross-total resection in 4 patients. Four weeks after surgery, mean KPS (p = 0.7637) and NIHSS scores (p = 0.3146) were not significantly different from preoperative values. Of the 13 patients who had received postoperative chemoradiotherapy, 4 did not show any progression after a median follow-up of 14 months. The remaining 9 patients had a median PFS of 8 months. CONCLUSIONS According to the study data, RS is capable of detecting tumor-infiltrated brain with higher sensitivity but lower specificity than the current standard of 5-ALA. With further technological and workflow advancements, RS in combination with protoporphyrin IX fluorescence may contribute to pathology-tailored glioma resection in the future.
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Affiliation(s)
- Johannes Herta
- 1Department of Neurosurgery, Medical University of Vienna
| | - Anna Cho
- 1Department of Neurosurgery, Medical University of Vienna
| | | | - Romana Höftberger
- 2Department of Neurology, Division of Neuropathology and Neurochemistry, Medical University of Vienna
| | - Wolfgang Marik
- 3Division of Neuroradiology and Musculoskeletal Radiology, Medical University of Vienna; and
| | - Gernot Kronreif
- 4Austrian Center for Medical Innovation and Technology (ACMIT), Wiener Neustadt, Austria
| | | | - Karl Rössler
- 1Department of Neurosurgery, Medical University of Vienna
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Asare-Werehene M, Hunter RA, Gerber E, Reunov A, Brine I, Chang CY, Chang CC, Shieh DB, Burger D, Anis H, Tsang BK. The Application of an Extracellular Vesicle-Based Biosensor in Early Diagnosis and Prediction of Chemoresponsiveness in Ovarian Cancer. Cancers (Basel) 2023; 15:cancers15092566. [PMID: 37174032 PMCID: PMC10177169 DOI: 10.3390/cancers15092566] [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: 02/27/2023] [Revised: 03/30/2023] [Accepted: 04/26/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Ovarian cancer (OVCA) is the most fatal gynecological cancer with late diagnosis and plasma gelsolin (pGSN)-mediated chemoresistance representing the main obstacles to treatment success. Since there is no reliable approach to diagnosing patients at an early stage as well as predicting chemoresponsiveness, there is an urgent need to develop a diagnostic platform for such purposes. Small extracellular vesicles (sEVs) are attractive biomarkers given their potential accuracy for targeting tumor sites. METHODS We have developed a novel biosensor which utilizes cysteine-functionalized gold nanoparticles that simultaneously bind to cisplatin (CDDP) and plasma/cell-derived EVs, affording us the advantage of predicting OVCA chemoresponsiveness, and early diagnosis using surface-enhanced Raman spectroscopy. RESULTS We found that pGSN regulates cortactin (CTTN) content resulting in the formation of nuclear- and cytoplasmic-dense granules facilitating the secretion of sEVs carrying CDDP; a strategy used by resistant cells to survive CDDP action. The clinical utility of the biosensor was tested and subsequently revealed that the sEV/CA125 ratio outperformed CA125 and sEV individually in predicting early stage, chemoresistance, residual disease, tumor recurrence, and patient survival. CONCLUSION These findings highlight pGSN as a potential therapeutic target and provide a potential diagnostic platform to detect OVCA earlier and predict chemoresistance; an intervention that will positively impact patient-survival outcomes.
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Affiliation(s)
- Meshach Asare-Werehene
- Departments of Obstetrics & Gynecology and Cellular & Molecular Medicine, Centre for Infection, Immunity and Inflammation, Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Chronic Disease Program, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
| | - Robert A Hunter
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Ottawa-Carleton Institute for Biomedical Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Emma Gerber
- Departments of Obstetrics & Gynecology and Cellular & Molecular Medicine, Centre for Infection, Immunity and Inflammation, Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Chronic Disease Program, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
| | - Arkadiy Reunov
- Department of Biology, St. Francis Xavier University, 2320 Notre Dame Avenue, Antigonish, NS B2G 2W5, Canada
| | - Isaiah Brine
- Ottawa-Carleton Institute for Biomedical Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Chia-Yu Chang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30068, Taiwan
- Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30068, Taiwan
- Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Chia-Ching Chang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30068, Taiwan
- Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30068, Taiwan
- Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
- Institute of Physics, Academia Sinica, Taipei 10529, Taiwan
| | - Dar-Bin Shieh
- Institute of Basic Medical Science, Institute of Oral Medicine and Department of Stomatology, National Cheng Kung University Hospital, National Cheng Kung University, Tainan 704, Taiwan
- Advanced Optoelectronic Technology Center and Center for Micro/Nano Science and Technology, National Cheng Kung University, Tainan 701, Taiwan
| | - Dylan Burger
- Chronic Disease Program, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
| | - Hanan Anis
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Benjamin K Tsang
- Departments of Obstetrics & Gynecology and Cellular & Molecular Medicine, Centre for Infection, Immunity and Inflammation, Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Chronic Disease Program, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada
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8
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David S, Tran T, Dallaire F, Sheehy G, Azzi F, Trudel D, Tremblay F, Omeroglu A, Leblond F, Meterissian S. In situ Raman spectroscopy and machine learning unveil biomolecular alterations in invasive breast cancer. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:036009. [PMID: 37009577 PMCID: PMC10062385 DOI: 10.1117/1.jbo.28.3.036009] [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: 11/04/2022] [Accepted: 02/27/2023] [Indexed: 06/19/2023]
Abstract
SIGNIFICANCE As many as 60% of patients with early stage breast cancer undergo breast-conserving surgery. Of those, 20% to 35% need a second surgery because of incomplete resection of the lesions. A technology allowing in situ detection of cancer could reduce re-excision procedure rates and improve patient survival. AIM Raman spectroscopy was used to measure the spectral fingerprint of normal breast and cancer tissue ex-vivo. The aim was to build a machine learning model and to identify the biomolecular bands that allow one to detect invasive breast cancer. APPROACH The system was used to interrogate specimens from 20 patients undergoing lumpectomy, mastectomy, or breast reduction surgery. This resulted in 238 ex-vivo measurements spatially registered with standard histology classifying tissue as cancer, normal, or fat. A technique based on support vector machines led to the development of predictive models, and their performance was quantified using a receiver-operating-characteristic analysis. RESULTS Raman spectroscopy combined with machine learning detected normal breast from ductal or lobular invasive cancer with a sensitivity of 93% and a specificity of 95%. This was achieved using a model based on only two spectral bands, including the peaks associated with C-C stretching of proteins around 940 cm - 1 and the symmetric ring breathing at 1004 cm - 1 associated with phenylalanine. CONCLUSIONS Detection of cancer on the margins of surgically resected breast specimen is feasible with Raman spectroscopy.
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Affiliation(s)
- Sandryne David
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Trang Tran
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Frédérick Dallaire
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Guillaume Sheehy
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Feryel Azzi
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Dominique Trudel
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
- Institut du cancer de Montréal, Montreal, Quebec, Canada
- Université de Montréal, Department of Pathology and Cellular Biology, Montreal, Quebec, Canada
| | - Francine Tremblay
- McGill University Health Center, Department of Surgery, Montreal, Quebec, Canada
| | - Atilla Omeroglu
- McGill University Health Center, Department of Pathology, Montreal, Quebec, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
- Institut du cancer de Montréal, Montreal, Quebec, Canada
| | - Sarkis Meterissian
- McGill University Health Center, Department of Surgery, Montreal, Quebec, Canada
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9
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Baria E, Giordano F, Guerrini R, Caporalini C, Buccoliero AM, Cicchi R, Pavone FS. Dysplasia and tumor discrimination in brain tissues by combined fluorescence, Raman, and diffuse reflectance spectroscopies. BIOMEDICAL OPTICS EXPRESS 2023; 14:1256-1275. [PMID: 36950232 PMCID: PMC10026567 DOI: 10.1364/boe.477035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/19/2022] [Accepted: 12/19/2022] [Indexed: 06/18/2023]
Abstract
Identification of neoplastic and dysplastic brain tissues is of paramount importance for improving the outcomes of neurosurgical procedures. This study explores the combined application of fluorescence, Raman and diffuse reflectance spectroscopies for the detection and classification of brain tumor and cortical dysplasia with a label-free modality. Multivariate analysis was performed to evaluate classification accuracies of these techniques-employed both in individual and multimodal configuration-obtaining high sensitivity and specificity. In particular, the proposed multimodal approach allowed discriminating tumor/dysplastic tissues against control tissue with 91%/86% sensitivity and 100%/100% specificity, respectively, whereas tumor from dysplastic tissues were discriminated with 89% sensitivity and 86% specificity. Hence, multimodal optical spectroscopy allows reliably differentiating these pathologies using a non-invasive, label-free approach that is faster than the gold standard technique and does not require any tissue processing, offering the potential for the clinical translation of the technology.
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Affiliation(s)
- Enrico Baria
- National Institute of Optics, National Research Council, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy
| | - Flavio Giordano
- Division of Neurosurgery, Department of Neuroscience I, "A. Meyer" Children's Hospital, Viale Gaetano Pieraccini 24, Florence 50141, Italy
| | - Renzo Guerrini
- Division of Neurosurgery, Department of Neuroscience I, "A. Meyer" Children's Hospital, Viale Gaetano Pieraccini 24, Florence 50141, Italy
| | - Chiara Caporalini
- Division of Pathology, Department of Critical Care Medicine and Surgery, University of Florence, Viale Giovanni Battista Morgagni 85, Florence 50134, Italy
| | - Anna Maria Buccoliero
- Division of Pathology, Department of Critical Care Medicine and Surgery, University of Florence, Viale Giovanni Battista Morgagni 85, Florence 50134, Italy
| | - Riccardo Cicchi
- National Institute of Optics, National Research Council, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy
| | - Francesco Saverio Pavone
- National Institute of Optics, National Research Council, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy
- European Laboratory for Non-Linear Spectroscopy, University of Florence, Via Nello Carrara 1, Sesto Fiorentino 50019, Italy
- Department of Physics and Astrophysics, University of Florence, Via Sansone 1, Sesto Fiorentino 50019, Italy
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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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Ranasinghe JC, Wang Z, Huang S. Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications. BIOSENSORS 2022; 13:27. [PMID: 36671862 PMCID: PMC9855372 DOI: 10.3390/bios13010027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.
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12
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Bhattacharya A, Benavides JA, Gerlein LF, Cloutier SG. Deep-learning framework for fully-automated recognition of TiO 2 polymorphs based on Raman spectroscopy. Sci Rep 2022; 12:21874. [PMID: 36536027 PMCID: PMC9763332 DOI: 10.1038/s41598-022-26343-3] [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: 09/29/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
Emerging machine learning techniques can be applied to Raman spectroscopy measurements for the identification of minerals. In this project, we describe a deep learning-based solution for automatic identification of complex polymorph structures from their Raman signatures. We propose a new framework using Convolutional Neural Networks and Long Short-Term Memory networks for compound identification. We train and evaluate our model using the publicly-available RRUFF spectral database. For model validation purposes, we synthesized and identified different TiO2 polymorphs to evaluate the performance and accuracy of the proposed framework. TiO2 is a ubiquitous material playing a crucial role in many industrial applications. Its unique properties are currently used advantageously in several research and industrial fields including energy storage, surface modifications, optical elements, electrical insulation to microelectronic devices such as logic gates and memristors. The results show that our model correctly identifies pure Anatase and Rutile with a high degree of confidence. Moreover, it can also identify defect-rich Anatase and modified Rutile based on their modified Raman Spectra. The model can also correctly identify the key component, Anatase, from the P25 Degussa TiO2. Based on the initial results, we firmly believe that implementing this model for automatically detecting complex polymorph structures will significantly increase the throughput, while dramatically reducing costs.
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Affiliation(s)
- Abhiroop Bhattacharya
- grid.459234.d0000 0001 2222 4302Department of Electrical Engineering, École de technologie supérieure, 1100 Notre-Dame West, Montreal, QC H3C 1K3 Canada
| | - Jaime A. Benavides
- grid.459234.d0000 0001 2222 4302Department of Electrical Engineering, École de technologie supérieure, 1100 Notre-Dame West, Montreal, QC H3C 1K3 Canada
| | - Luis Felipe Gerlein
- grid.459234.d0000 0001 2222 4302Department of Electrical Engineering, École de technologie supérieure, 1100 Notre-Dame West, Montreal, QC H3C 1K3 Canada
| | - Sylvain G. Cloutier
- grid.459234.d0000 0001 2222 4302Department of Electrical Engineering, École de technologie supérieure, 1100 Notre-Dame West, Montreal, QC H3C 1K3 Canada
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13
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Maryam S, Nogueira MS, Gautam R, Krishnamoorthy S, Venkata Sekar SK, Kho KW, Lu H, Ni Riordain R, Feeley L, Sheahan P, Burke R, Andersson-Engels S. Label-Free Optical Spectroscopy for Early Detection of Oral Cancer. Diagnostics (Basel) 2022; 12:diagnostics12122896. [PMID: 36552903 PMCID: PMC9776497 DOI: 10.3390/diagnostics12122896] [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: 10/24/2022] [Revised: 11/16/2022] [Accepted: 11/18/2022] [Indexed: 11/23/2022] Open
Abstract
Oral cancer is the 16th most common cancer worldwide. It commonly arises from painless white or red plaques within the oral cavity. Clinical outcome is highly related to the stage when diagnosed. However, early diagnosis is complex owing to the impracticality of biopsying every potentially premalignant intraoral lesion. Therefore, there is a need to develop a non-invasive cost-effective diagnostic technique to differentiate non-malignant and early-stage malignant lesions. Optical spectroscopy may provide an appropriate solution to facilitate early detection of these lesions. It has many advantages over traditional approaches including cost, speed, objectivity, sensitivity, painlessness, and ease-of use in clinical setting for real-time diagnosis. This review consists of a comprehensive overview of optical spectroscopy for oral cancer diagnosis, epidemiology, and recent improvements in this field for diagnostic purposes. It summarizes major developments in label-free optical spectroscopy, including Raman, fluorescence, and diffuse reflectance spectroscopy during recent years. Among the wide range of optical techniques available, we chose these three for this review because they have the ability to provide biochemical information and show great potential for real-time deep-tissue point-based in vivo analysis. This review also highlights the importance of saliva-based potential biomarkers for non-invasive early-stage diagnosis. It concludes with the discussion on the scope of development and future demands from a clinical point of view.
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Affiliation(s)
- Siddra Maryam
- Tyndall National Institute, University College Cork, T12 R229 Cork, Ireland
- Correspondence:
| | | | - Rekha Gautam
- Tyndall National Institute, University College Cork, T12 R229 Cork, Ireland
| | | | | | - Kiang Wei Kho
- Tyndall National Institute, University College Cork, T12 R229 Cork, Ireland
| | - Huihui Lu
- Tyndall National Institute, University College Cork, T12 R229 Cork, Ireland
| | - Richeal Ni Riordain
- ENTO Research Institute, University College Cork, T12 R229 Cork, Ireland
- Cork University Dental School and Hospital, Wilton, T12 E8YV Cork, Ireland
| | - Linda Feeley
- ENTO Research Institute, University College Cork, T12 R229 Cork, Ireland
- Cork University Hospital, T12 DC4A Cork, Ireland
| | - Patrick Sheahan
- ENTO Research Institute, University College Cork, T12 R229 Cork, Ireland
- South Infirmary Victoria University Hospital, T12 X23H Cork, Ireland
| | - Ray Burke
- Tyndall National Institute, University College Cork, T12 R229 Cork, Ireland
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14
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Haddad AF, Aghi MK, Butowski N. Novel intraoperative strategies for enhancing tumor control: Future directions. Neuro Oncol 2022; 24:S25-S32. [PMID: 36322096 PMCID: PMC9629473 DOI: 10.1093/neuonc/noac090] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023] Open
Abstract
Maximal safe surgical resection plays a key role in the care of patients with gliomas. A range of technologies have been developed to aid surgeons in distinguishing tumor from normal tissue, with the goal of increasing tumor resection and limiting postoperative neurological deficits. Technologies that are currently being investigated to aid in improving tumor control include intraoperative imaging modalities, fluorescent tumor makers, intraoperative cell and molecular profiling of tumors, improved microscopic imaging, intraoperative mapping, augmented and virtual reality, intraoperative drug and radiation delivery, and ablative technologies. In this review, we summarize the aforementioned advancements in neurosurgical oncology and implications for improving patient outcomes.
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Affiliation(s)
- Alexander F Haddad
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Manish K Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Nicholas Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
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15
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Khristoforova Y, Bratchenko I, Bratchenko L, Moryatov A, Kozlov S, Kaganov O, Zakharov V. Combination of Optical Biopsy with Patient Data for Improvement of Skin Tumor Identification. Diagnostics (Basel) 2022; 12:diagnostics12102503. [PMID: 36292192 PMCID: PMC9600416 DOI: 10.3390/diagnostics12102503] [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: 09/07/2022] [Revised: 10/11/2022] [Accepted: 10/12/2022] [Indexed: 11/29/2022] Open
Abstract
In this study, patient data were combined with Raman and autofluorescence spectral parameters for more accurate identification of skin tumors. The spectral and patient data of skin tumors were classified by projection on latent structures and discriminant analysis. The importance of patient risk factors was determined using statistical improvement of ROC AUCs when spectral parameters were combined with risk factors. Gender, age and tumor localization were found significant for classification of malignant versus benign neoplasms, resulting in improvement of ROC AUCs from 0.610 to 0.818 (p < 0.05). To distinguish melanoma versus pigmented skin tumors, the same factors significantly improved ROC AUCs from 0.709 to 0.810 (p < 0.05) when analyzed together according to the spectral data, but insignificantly (p > 0.05) when analyzed individually. For classification of melanoma versus seborrheic keratosis, no statistical improvement of ROC AUC was observed when the patient data were added to the spectral data. In all three classification models, additional risk factors such as occupational hazards, family history, sun exposure, size, and personal history did not statistically improve the ROC AUCs. In summary, combined analysis of spectral and patient data can be significant for certain diagnostic tasks: patient data demonstrated the distribution of skin tumor incidence in different demographic groups, whereas tumors within each group were distinguished using the spectral differences.
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Affiliation(s)
- Yulia Khristoforova
- Laser and Biotechnical Systems Department, Samara National Research University, 34 Moskovskoe Shosse, 443086 Samara, Russia
- Correspondence:
| | - Ivan Bratchenko
- Laser and Biotechnical Systems Department, Samara National Research University, 34 Moskovskoe Shosse, 443086 Samara, Russia
| | - Lyudmila Bratchenko
- Laser and Biotechnical Systems Department, Samara National Research University, 34 Moskovskoe Shosse, 443086 Samara, Russia
| | - Alexander Moryatov
- Department of Oncology, Samara State Medical University, 89 Chapaevskaya Str., 443099 Samara, Russia
| | - Sergey Kozlov
- Department of Oncology, Samara State Medical University, 89 Chapaevskaya Str., 443099 Samara, Russia
| | - Oleg Kaganov
- Department of Oncology, Samara State Medical University, 89 Chapaevskaya Str., 443099 Samara, Russia
| | - Valery Zakharov
- Laser and Biotechnical Systems Department, Samara National Research University, 34 Moskovskoe Shosse, 443086 Samara, Russia
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16
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Shukla S, Sah AN, Hatiboruah D, Ahirwar S, Nath P, Pradhan A. Design, fabrication and testing of 3D printed smartphone-based device for collection of intrinsic fluorescence from human cervix. Sci Rep 2022; 12:11192. [PMID: 35778460 PMCID: PMC9249735 DOI: 10.1038/s41598-022-15007-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 06/16/2022] [Indexed: 11/09/2022] Open
Abstract
Fluorescence spectroscopy has the potential to identify discriminatory signatures, crucial for early diagnosis of cervical cancer. We demonstrate here the design, fabrication and testing of a 3D printed smartphone based spectroscopic device. Polarized fluorescence and elastic scattering spectra are captured through the device using a 405 nm laser and a white LED source respectively. The device has been calibrated by comparison of spectra of standard fluorophores (Flavin adenine dinucleotide, fluorescein, rhodamine, and porphyrin) with the corresponding spectra collected from a commercial spectrometer. A few cervical tissue spectra have also been captured for proof of its applicability as a portable, standalone device for the collection of intrinsic fluorescence spectra from human cervix.
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Affiliation(s)
- Shivam Shukla
- Center for Lasers and Photonics, IIT Kanpur, Kanpur, 208016, India
| | - Amar Nath Sah
- Department of Biological sciences and Bioengineering, IIT Kanpur, Kanpur, 208016, India
| | | | - Shikha Ahirwar
- PhotoSpIMeDx Pvt. Ltd., SIIC, IIT Kanpur, Kanpur, 208016, India
| | - Pabitra Nath
- Department of Physics, Tezpur University, Tezpur, 784028, India
| | - Asima Pradhan
- Center for Lasers and Photonics, IIT Kanpur, Kanpur, 208016, India. .,Department of Physics, IIT Kanpur, Kanpur, 208016, India.
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17
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Cakmakci D, Kaynar G, Bund C, Piotto M, Proust F, Namer IJ, Cicek AE. Targeted metabolomics analyses for brain tumor margin assessment during surgery. BIOINFORMATICS (OXFORD, ENGLAND) 2022; 38:3238-3244. [PMID: 35512389 DOI: 10.1093/bioinformatics/btac309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/13/2022] [Accepted: 05/02/2022] [Indexed: 01/17/2023]
Abstract
MOTIVATION Identification and removal of micro-scale residual tumor tissue during brain tumor surgery are key for survival in glioma patients. For this goal, High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy-based assessment of tumor margins during surgery has been an effective method. However, the time required for metabolite quantification and the need for human experts such as a pathologist to be present during surgery are major bottlenecks of this technique. While machine learning techniques that analyze the NMR spectrum in an untargeted manner (i.e. using the full raw signal) have been shown to effectively automate this feedback mechanism, high dimensional and noisy structure of the NMR signal limits the attained performance. RESULTS In this study, we show that identifying informative regions in the HRMAS NMR spectrum and using them for tumor margin assessment improves the prediction power. We use the spectra normalized with the ERETIC (electronic reference to access in vivo concentrations) method which uses an external reference signal to calibrate the HRMAS NMR spectrum. We train models to predict quantities of metabolites from annotated regions of this spectrum. Using these predictions for tumor margin assessment provides performance improvements up to 4.6% the Area Under the ROC Curve (AUC-ROC) and 2.8% the Area Under the Precision-Recall Curve (AUC-PR). We validate the importance of various tumor biomarkers and identify a novel region between 7.97 ppm and 8.09 ppm as a new candidate for a glioma biomarker. AVAILABILITY AND IMPLEMENTATION The code is released at https://github.com/ciceklab/targeted_brain_tumor_margin_assessment. The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.5781769. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Doruk Cakmakci
- School of Computer Science, McGill University, Montreal, QC H3A 0E9, Canada
| | - Gun Kaynar
- School of Computer Science, McGill University, Montreal, QC H3A 0E9, Canada
| | - Caroline Bund
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France.,ICube, University of Strasbourg/CNRS UMR 7357, Strasbourg 67000, France.,Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | | | - Francois Proust
- Department of Neurosurgery, University Hospitals of Strasbourg, Strasbourg 67091, France
| | - Izzie Jacques Namer
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France.,ICube, University of Strasbourg/CNRS UMR 7357, Strasbourg 67000, France.,Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | - A Ercument Cicek
- Computer Engineering Department, Bilkent University, Ankara 06800, Turkey.,Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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18
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Wilson BC, Eu D. Optical Spectroscopy and Imaging in Surgical Management of Cancer Patients. TRANSLATIONAL BIOPHOTONICS 2022. [DOI: 10.1002/tbio.202100009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Brian C. Wilson
- Princess Margaret Cancer Centre/University Health Network 101 College Street Toronto Ontario Canada
- Department of Medical Biophysics, Faculty of Medicine University of Toronto Canada
| | - Donovan Eu
- Department of Otolaryngology‐Head and Neck Surgery‐Surgical Oncology, Princess Margaret Cancer Centre/University Health Network University of Toronto Canada
- Department of Otolaryngology‐Head and Neck Surgery National University Hospital System Singapore
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19
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Cameron JM, Rinaldi C, Rutherford SH, Sala A, G Theakstone A, Baker MJ. Clinical Spectroscopy: Lost in Translation? APPLIED SPECTROSCOPY 2022; 76:393-415. [PMID: 34041957 DOI: 10.1177/00037028211021846] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.
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Affiliation(s)
| | - Christopher Rinaldi
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Samantha H Rutherford
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Ashton G Theakstone
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
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20
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Ember K, Daoust F, Mahfoud M, Dallaire F, Ahmad EZ, Tran T, Plante A, Diop MK, Nguyen T, St-Georges-Robillard A, Ksantini N, Lanthier J, Filiatrault A, Sheehy G, Beaudoin G, Quach C, Trudel D, Leblond F. Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210270RR. [PMID: 35142113 PMCID: PMC8825664 DOI: 10.1117/1.jbo.27.2.025002] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 01/20/2022] [Indexed: 05/31/2023]
Abstract
SIGNIFICANCE The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus. AIM We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents. APPROACH We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique-Raman spectroscopy-to detect changes in the molecular profile of saliva associated with COVID-19 infection. RESULTS We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. CONCLUSION These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.
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Affiliation(s)
- Katherine Ember
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - François Daoust
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Myriam Mahfoud
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Frédérick Dallaire
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Esmat Zamani Ahmad
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
- Institut du cancer de Montréal, Montreal, Canada
| | - Trang Tran
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Arthur Plante
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Mame-Kany Diop
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
- Institut du cancer de Montréal, Montreal, Canada
| | - Tien Nguyen
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
- Institut du cancer de Montréal, Montreal, Canada
| | - Amélie St-Georges-Robillard
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Nassim Ksantini
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Julie Lanthier
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Antoine Filiatrault
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Guillaume Sheehy
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Gabriel Beaudoin
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
| | - Caroline Quach
- Research Center, CHU Sainte-Justine, Montreal, Canada
- University of Montreal, Faculty of Medicine, Montreal, Quebec, Canada
| | - Dominique Trudel
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
- Institut du cancer de Montréal, Montreal, Canada
- Université de Montréal, Department of Pathology and Cellular Biology, Montreal, Quebec, Canada
- Center Hospitalier de l’Université de Montréal, Department of Pathology, Montreal, Quebec, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Montreal, Canada
- Center de recherche du Center hospitalier de l’Université de Montréal, Montreal, Canada
- Institut du cancer de Montréal, Montreal, Canada
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21
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Allakhverdiev ES, Khabatova VV, Kossalbayev BD, Zadneprovskaya EV, Rodnenkov OV, Martynyuk TV, Maksimov GV, Alwasel S, Tomo T, Allakhverdiev SI. Raman Spectroscopy and Its Modifications Applied to Biological and Medical Research. Cells 2022; 11:cells11030386. [PMID: 35159196 PMCID: PMC8834270 DOI: 10.3390/cells11030386] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 01/17/2022] [Accepted: 01/22/2022] [Indexed: 02/06/2023] Open
Abstract
Nowadays, there is an interest in biomedical and nanobiotechnological studies, such as studies on carotenoids as antioxidants and studies on molecular markers for cardiovascular, endocrine, and oncological diseases. Moreover, interest in industrial production of microalgal biomass for biofuels and bioproducts has stimulated studies on microalgal physiology and mechanisms of synthesis and accumulation of valuable biomolecules in algal cells. Biomolecules such as neutral lipids and carotenoids are being actively explored by the biotechnology community. Raman spectroscopy (RS) has become an important tool for researchers to understand biological processes at the cellular level in medicine and biotechnology. This review provides a brief analysis of existing studies on the application of RS for investigation of biological, medical, analytical, photosynthetic, and algal research, particularly to understand how the technique can be used for lipids, carotenoids, and cellular research. First, the review article shows the main applications of the modified Raman spectroscopy in medicine and biotechnology. Research works in the field of medicine and biotechnology are analysed in terms of showing the common connections of some studies as caretenoids and lipids. Second, this article summarises some of the recent advances in Raman microspectroscopy applications in areas related to microalgal detection. Strategies based on Raman spectroscopy provide potential for biochemical-composition analysis and imaging of living microalgal cells, in situ and in vivo. Finally, current approaches used in the papers presented show the advantages, perspectives, and other essential specifics of the method applied to plants and other species/objects.
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Affiliation(s)
- Elvin S. Allakhverdiev
- Russian National Medical Research Center of Cardiology, 3rd Cherepkovskaya St., 15A, 121552 Moscow, Russia; (E.S.A.); (O.V.R.); (T.V.M.)
- Biology Faculty, Lomonosov Moscow State University, Leninskie Gory 1/12, 119991 Moscow, Russia;
| | - Venera V. Khabatova
- K.A. Timiryazev Institute of Plant Physiology, RAS, Botanicheskaya str., 35, 127276 Moscow, Russia; (V.V.K.); (E.V.Z.)
| | - Bekzhan D. Kossalbayev
- Geology and Oil-gas Business Institute Named after K. Turyssov, Satbayev University, Satpaeva, 22, Almaty 050043, Kazakhstan;
- Department of Biotechnology, Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Al-Farabi Avenue 71, Almaty 050038, Kazakhstan
| | - Elena V. Zadneprovskaya
- K.A. Timiryazev Institute of Plant Physiology, RAS, Botanicheskaya str., 35, 127276 Moscow, Russia; (V.V.K.); (E.V.Z.)
| | - Oleg V. Rodnenkov
- Russian National Medical Research Center of Cardiology, 3rd Cherepkovskaya St., 15A, 121552 Moscow, Russia; (E.S.A.); (O.V.R.); (T.V.M.)
| | - Tamila V. Martynyuk
- Russian National Medical Research Center of Cardiology, 3rd Cherepkovskaya St., 15A, 121552 Moscow, Russia; (E.S.A.); (O.V.R.); (T.V.M.)
| | - Georgy V. Maksimov
- Biology Faculty, Lomonosov Moscow State University, Leninskie Gory 1/12, 119991 Moscow, Russia;
- Department of Physical Materials Science, Technological University “MISiS”, Leninskiy Prospekt 4, Office 626, 119049 Moscow, Russia
| | - Saleh Alwasel
- Zoology Department, College of Science, King Saud University, Riyadh 12372, Saudi Arabia;
| | - Tatsuya Tomo
- Department of Biology, Faculty of Science, Tokyo University of Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-8601, Japan;
| | - Suleyman I. Allakhverdiev
- K.A. Timiryazev Institute of Plant Physiology, RAS, Botanicheskaya str., 35, 127276 Moscow, Russia; (V.V.K.); (E.V.Z.)
- Zoology Department, College of Science, King Saud University, Riyadh 12372, Saudi Arabia;
- Institute of Basic Biological Problems, RAS, Pushchino, 142290 Moscow, Russia
- Correspondence:
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22
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Cialla-May D, Krafft C, Rösch P, Deckert-Gaudig T, Frosch T, Jahn IJ, Pahlow S, Stiebing C, Meyer-Zedler T, Bocklitz T, Schie I, Deckert V, Popp J. Raman Spectroscopy and Imaging in Bioanalytics. Anal Chem 2021; 94:86-119. [PMID: 34920669 DOI: 10.1021/acs.analchem.1c03235] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Dana Cialla-May
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Christoph Krafft
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Tanja Deckert-Gaudig
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Torsten Frosch
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Izabella J Jahn
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Susanne Pahlow
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Clara Stiebing
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Tobias Meyer-Zedler
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Iwan Schie
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Ernst-Abbe-Hochschule Jena, University of Applied Sciences, Department of Biomedical Engineering and Biotechnology, Carl-Zeiss-Promenade 2, 07745 Jena, Germany
| | - Volker Deckert
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Jürgen Popp
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
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23
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Straehle J, Erny D, Neidert N, Heiland DH, El Rahal A, Sacalean V, Steybe D, Schmelzeisen R, Vlachos A, Mizaikoff B, Reinacher PC, Coenen VA, Prinz M, Beck J, Schnell O. Neuropathological interpretation of stimulated Raman histology images of brain and spine tumors: part B. Neurosurg Rev 2021; 45:1721-1729. [PMID: 34890000 PMCID: PMC8976804 DOI: 10.1007/s10143-021-01711-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/22/2021] [Accepted: 11/26/2021] [Indexed: 12/01/2022]
Abstract
Intraoperative histopathological examinations are routinely performed to provide neurosurgeons with information about the entity of tumor tissue. Here, we quantified the neuropathological interpretability of stimulated Raman histology (SRH) acquired using a Raman laser imaging system in a routine clinical setting without any specialized training or prior experience. Stimulated Raman scattering microscopy was performed on 117 samples of pathological tissue from 73 cases of brain and spine tumor surgeries. A board-certified neuropathologist — novice in the interpretation of SRH — assessed image quality by scoring subjective tumor infiltration and stated a diagnosis based on the SRH images. The diagnostic accuracy was determined by comparison to frozen hematoxylin–eosin (H&E)-stained sections and the ground truth defined as the definitive neuropathological diagnosis. The overall SRH imaging quality was rated high with the detection of tumor cells classified as inconclusive in only 4.2% of all images. The accuracy of neuropathological diagnosis based on SRH images was 87.7% and was non-inferior to the current standard of fast frozen H&E-stained sections (87.3 vs. 88.9%, p = 0.783). We found a substantial diagnostic correlation between SRH-based neuropathological diagnosis and H&E-stained frozen sections (κ = 0.8). The interpretability of intraoperative SRH imaging was demonstrated to be equivalent to the current standard method of H&E-stained frozen sections. Further research using this label-free innovative alternative vs. conventional staining is required to determine to which extent SRH-based intraoperative decision-making can be streamlined in order to facilitate the advancement of surgical neurooncology.
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Affiliation(s)
- Jakob Straehle
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Nicolas Neidert
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Freiburg, Germany
| | - Dieter Henrik Heiland
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Freiburg, Germany.,Comprehensive Cancer Center Freiburg (CCCF), Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), partner site Freiburg, Freiburg, Germany.,Medical Faculty of Freiburg University, Freiburg, Germany
| | - Amir El Rahal
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Vlad Sacalean
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Freiburg, Germany
| | - David Steybe
- Department of Oral and Maxillofacial Surgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Rainer Schmelzeisen
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Oral and Maxillofacial Surgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Andreas Vlachos
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Center Brain Links Brain Tools, University of Freiburg, Freiburg, Germany
| | - Boris Mizaikoff
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Ulm, Germany.,Hahn-Schickard Institute for Microanalysis Systems, Ulm, Germany
| | - Peter Christoph Reinacher
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Stereotactic and Functional Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Fraunhofer Institute for Laser Technology (ILT), Aachen, Germany
| | - Volker Arnd Coenen
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Stereotactic and Functional Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Marco Prinz
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Medical Faculty of Freiburg University, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Jürgen Beck
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Comprehensive Cancer Center Freiburg (CCCF), Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,Medical Faculty of Freiburg University, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany. .,Medical Faculty of Freiburg University, Freiburg, Germany.
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24
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Becker L, Janssen N, Layland SL, Mürdter TE, Nies AT, Schenke-Layland K, Marzi J. Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring. Cancers (Basel) 2021; 13:cancers13225682. [PMID: 34830837 PMCID: PMC8616063 DOI: 10.3390/cancers13225682] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/05/2021] [Accepted: 11/10/2021] [Indexed: 02/08/2023] Open
Abstract
Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.
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Affiliation(s)
- Lucas Becker
- Department for Medical Technologies and Regenerative Medicine, Institute of Biomedical Engineering, University of Tübingen, 72076 Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, 72076 Tübingen, Germany
| | - Nicole Janssen
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, University of Tübingen, 72076 Tübingen, Germany
| | - Shannon L Layland
- Department for Medical Technologies and Regenerative Medicine, Institute of Biomedical Engineering, University of Tübingen, 72076 Tübingen, Germany
| | - Thomas E Mürdter
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, University of Tübingen, 72076 Tübingen, Germany
| | - Anne T Nies
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, 72076 Tübingen, Germany
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, University of Tübingen, 72076 Tübingen, Germany
| | - Katja Schenke-Layland
- Department for Medical Technologies and Regenerative Medicine, Institute of Biomedical Engineering, University of Tübingen, 72076 Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, 72076 Tübingen, Germany
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany
- Cardiovascular Research Laboratories, Department of Medicine/Cardiology, David Geffen School of Medicine, UCLA, Los Angeles, CA 90073, USA
| | - Julia Marzi
- Department for Medical Technologies and Regenerative Medicine, Institute of Biomedical Engineering, University of Tübingen, 72076 Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, 72076 Tübingen, Germany
- NMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany
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25
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Tanwar S, Paidi SK, Prasad R, Pandey R, Barman I. Advancing Raman spectroscopy from research to clinic: Translational potential and challenges. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 260:119957. [PMID: 34082350 DOI: 10.1016/j.saa.2021.119957] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 05/08/2021] [Accepted: 05/10/2021] [Indexed: 05/18/2023]
Abstract
Raman spectroscopy has emerged as a non-invasive and versatile diagnostic technique due to its ability to provide molecule-specific information with ultrahigh sensitivity at near-physiological conditions. Despite exhibiting substantial potential, its translation from optical bench to clinical settings has been impacted by associated limitations. This perspective discusses recent clinical and biomedical applications of Raman spectroscopy and technological advancements that provide valuable insights and encouragement for resolving some of the most challenging hurdles.
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Affiliation(s)
- Swati Tanwar
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States
| | - Santosh Kumar Paidi
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States
| | - Ram Prasad
- Department of Botany, School of Life Sciences, Mahatma Gandhi Central University, Motihari, Bihar 845401, India
| | - Rishikesh Pandey
- CytoVeris Inc., Farmington, CT 06032, United States; Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, United States.
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, United States; The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, Baltimore, MD 21205, United States; Department of Oncology, Johns Hopkins University, Baltimore, MD 21287, United States.
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26
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Hollon T, Orringer DA. Label-free brain tumor imaging using Raman-based methods. J Neurooncol 2021; 151:393-402. [PMID: 33611706 DOI: 10.1007/s11060-019-03380-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 12/20/2019] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Label-free Raman-based imaging techniques create the possibility of bringing chemical and histologic data into the operation room. Relying on the intrinsic biochemical properties of tissues to generate image contrast and optical tissue sectioning, Raman-based imaging methods can be used to detect microscopic tumor infiltration and diagnose brain tumor subtypes. METHODS Here, we review the application of three Raman-based imaging methods to neurosurgical oncology: Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, and stimulated Raman histology (SRH). RESULTS Raman spectroscopy allows for chemical characterization of tissue and can differentiate normal and tumor-infiltrated tissue based on variations in macromolecule content, both ex vivo and in vivo. To improve signal-to-noise ratio compared to conventional Raman spectroscopy, a second pulsed excitation laser can be used to coherently drive the vibrational frequency of specific Raman active chemical bonds (i.e. symmetric stretching of -CH2 bonds). Coherent Raman imaging, including CARS and stimulated Raman scattering microscopy, has been shown to detect microscopic brain tumor infiltration in fresh brain tumor specimens with submicron image resolution. Advances in fiber-laser technology have allowed for the development of intraoperative SRH as well as artificial intelligence algorithms to facilitate interpretation of SRH images. With molecular diagnostics becoming an essential part of brain tumor classification, preliminary studies have demonstrated that Raman-based methods can be used to diagnose glioma molecular classes intraoperatively. CONCLUSIONS These results demonstrate how label-free Raman-based imaging methods can be used to improve the management of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.
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27
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Bratchenko IA, Bratchenko LA, Moryatov AA, Khristoforova YA, Artemyev DN, Myakinin OO, Orlov AE, Kozlov SV, Zakharov VP. In vivo diagnosis of skin cancer with a portable Raman spectroscopic device. Exp Dermatol 2021; 30:652-663. [PMID: 33566431 DOI: 10.1111/exd.14301] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 01/29/2021] [Accepted: 02/05/2021] [Indexed: 12/18/2022]
Abstract
In this study, we performed in vivo diagnosis of skin cancer based on implementation of a portable low-cost spectroscopy setup combining analysis of Raman and autofluorescence spectra in the near-infrared region (800-915 nm). We studied 617 cases of skin neoplasms (615 patients, 70 melanomas, 122 basal cell carcinomas, 12 squamous cell carcinomas and 413 benign tumors) in vivo with a portable setup. The studies considered the patients examined by GPs in local clinics and directed to a specialized Oncology Dispensary with suspected skin cancer. Each sample was histologically examined after excisional biopsy. The spectra were classified with a projection on latent structures and discriminant analysis. To check the classification models stability, a 10-fold cross-validation was performed. We obtained ROC AUCs of 0.75 (0.71-0.79; 95% CI), 0.69 (0.63-0.76; 95% CI) and 0.81 (0.74-0.87; 95% CI) for classification of a) malignant and benign tumors, b) melanomas and pigmented tumors and c) melanomas and seborrhoeic keratosis, respectively. The positive and negative predictive values ranged from 20% to 52% and from 73% to 99%, respectively. The biopsy ratio varied from 0.92:1 to 4.08:1 (at sensitivity levels from 90% to 99%). The accuracy of automatic analysis with the proposed system is higher than the accuracy of GPs and trainees, and is comparable or less to the accuracy of trained dermatologists. The proposed approach may be combined with other optical techniques of skin lesion analysis, such as dermoscopy- and spectroscopy-based computer-assisted diagnosis systems to increase accuracy of neoplasms classification.
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Affiliation(s)
- Ivan A Bratchenko
- Department of Laser and Biotechnical Systems, Samara University, Samara, Russia
| | | | - Alexander A Moryatov
- Department of Oncology, Samara State Medical University, Samara, Russia.,Department of Visual Localization Tumors, Samara Regional Clinical Oncology Dispensary, Samara, Russia
| | | | - Dmitry N Artemyev
- Department of Laser and Biotechnical Systems, Samara University, Samara, Russia
| | - Oleg O Myakinin
- Department of Laser and Biotechnical Systems, Samara University, Samara, Russia
| | - Andrey E Orlov
- Department of Visual Localization Tumors, Samara Regional Clinical Oncology Dispensary, Samara, Russia
| | - Sergey V Kozlov
- Department of Oncology, Samara State Medical University, Samara, Russia.,Department of Visual Localization Tumors, Samara Regional Clinical Oncology Dispensary, Samara, Russia
| | - Valery P Zakharov
- Department of Laser and Biotechnical Systems, Samara University, Samara, Russia
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28
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Schupper AJ, Yong RL, Hadjipanayis CG. The Neurosurgeon's Armamentarium for Gliomas: An Update on Intraoperative Technologies to Improve Extent of Resection. J Clin Med 2021; 10:jcm10020236. [PMID: 33440712 PMCID: PMC7826675 DOI: 10.3390/jcm10020236] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 01/06/2021] [Accepted: 01/08/2021] [Indexed: 12/18/2022] Open
Abstract
Maximal safe resection is the standard of care in the neurosurgical treatment of high-grade gliomas. To aid surgeons in the operating room, adjuvant techniques and technologies centered around improving intraoperative visualization of tumor tissue have been developed. In this review, we will discuss the most advanced technologies, specifically fluorescence-guided surgery, intraoperative imaging, neuromonitoring modalities, and microscopic imaging techniques. The goal of these technologies is to improve detection of tumor tissue beyond what conventional microsurgery has permitted. We describe the various advances, the current state of the literature that have tested the utility of the different adjuvants in clinical practice, and future directions for improving intraoperative technologies.
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29
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Orillac C, Stummer W, Orringer DA. Fluorescence Guidance and Intraoperative Adjuvants to Maximize Extent of Resection. Neurosurgery 2020; 89:727-736. [PMID: 33289518 DOI: 10.1093/neuros/nyaa475] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 08/23/2020] [Indexed: 12/27/2022] Open
Abstract
Safely maximizing extent of resection has become the central goal in glioma surgery. Especially in eloquent cortex, the goal of maximal resection is balanced with neurological risk. As new technologies emerge in the field of neurosurgery, the standards for maximal safe resection have been elevated. Fluorescence-guided surgery, intraoperative magnetic resonance imaging, and microscopic imaging methods are among the most well-validated tools available to enhance the level of accuracy and safety in glioma surgery. Each technology uses a different characteristic of glioma tissue to identify and differentiate tumor tissue from normal brain and is most effective in the context of anatomic, connectomic, and neurophysiologic context. While each tool is able to enhance resection, multiple modalities are often used in conjunction to achieve maximal safe resection. This paper reviews the mechanism and utility of the major adjuncts available for use in glioma surgery, especially in tumors within eloquent areas, and puts forth the foundation for a unified approach to how leverage currently available technology to ensure maximal safe resection.
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Affiliation(s)
- Cordelia Orillac
- Department of Neurosurgery, NYU Langone Health, New York, New York
| | - Walter Stummer
- Department of Neurosurgery, University Hospital Münster, Münster, Germany
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30
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Cakmakci D, Karakaslar EO, Ruhland E, Chenard MP, Proust F, Piotto M, Namer IJ, Cicek AE. Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy. PLoS Comput Biol 2020; 16:e1008184. [PMID: 33175838 PMCID: PMC7682900 DOI: 10.1371/journal.pcbi.1008184] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 11/23/2020] [Accepted: 07/22/2020] [Indexed: 11/19/2022] Open
Abstract
Complete resection of the tumor is important for survival in glioma patients. Even if the gross total resection was achieved, left-over micro-scale tissue in the excision cavity risks recurrence. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) technique can distinguish healthy and malign tissue efficiently using peak intensities of biomarker metabolites. The method is fast, sensitive and can work with small and unprocessed samples, which makes it a good fit for real-time analysis during surgery. However, only a targeted analysis for the existence of known tumor biomarkers can be made and this requires a technician with chemistry background, and a pathologist with knowledge on tumor metabolism to be present during surgery. Here, we show that we can accurately perform this analysis in real-time and can analyze the full spectrum in an untargeted fashion using machine learning. We work on a new and large HRMAS NMR dataset of glioma and control samples (n = 565), which are also labeled with a quantitative pathology analysis. Our results show that a random forest based approach can distinguish samples with tumor cells and controls accurately and effectively with a median AUC of 85.6% and AUPR of 93.4%. We also show that we can further distinguish benign and malignant samples with a median AUC of 87.1% and AUPR of 96.1%. We analyze the feature (peak) importance for classification to interpret the results of the classifier. We validate that known malignancy biomarkers such as creatine and 2-hydroxyglutarate play an important role in distinguishing tumor and normal cells and suggest new biomarker regions. The code is released at http://github.com/ciceklab/HRMAS_NC.
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Affiliation(s)
- Doruk Cakmakci
- Computer Engineering Department, Bilkent University, Ankara, Turkey
| | | | - Elisa Ruhland
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg, France
| | | | - Francois Proust
- Department of Neurosurgery, University Hospitals of Strasbourg, Strasbourg, France
| | | | - Izzie Jacques Namer
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg, France
- ICube, University of Strasbourg / CNRS UMR 7357, Strasbourg, France
- Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg, France
| | - A. Ercument Cicek
- Computer Engineering Department, Bilkent University, Ankara, Turkey
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania
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Laurence A, Bouthillier A, Robert M, Nguyen DK, Leblond F. Multispectral diffuse reflectance can discriminate blood vessels and bleeding during neurosurgery based on low-frequency hemodynamics. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200094R. [PMID: 33179457 PMCID: PMC7657412 DOI: 10.1117/1.jbo.25.11.116003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 10/21/2020] [Indexed: 06/11/2023]
Abstract
SIGNIFICANCE The practicality of optical methods detecting tissue optical contrast (absorption, elastic and inelastic scattering, fluorescence) for surgical guidance is limited by interferences from blood pooling and the resulting partial or complete inability to interrogate cortex and blood vessels. AIM A multispectral diffuse reflectance technique was developed for intraoperative brain imaging of hemodynamic activity to automatically discriminate blood vessels, cortex, and bleeding at the brain surface. APPROACH A manual segmentation of blood pooling, cortex, and vessels allowed the identification of a frequency range in hemoglobin concentration variations associated with high optical signal in blood vessels and cortex but not in bleeding. Reflectance spectra were then used to automatically segment areas with and without hemodynamic activity as well as to discriminate blood from cortical areas. RESULTS The frequency range associated with low-frequency hemodynamics and respiratory rate (0.03 to 0.3 Hz) exhibits the largest differences in signal amplitudes for bleeding, blood vessels, and cortex. A segmentation technique based on simulated reflectance spectra initially allowed discrimination of blood (bleeding and vessels) from cortical tissue. Then, a threshold applied to the low-frequency components from deoxyhemoglobin allowed the segmentation of bleeding from vessels. A study on the minimum acquisition time needed to discriminate all three components determined that ∼25 s was necessary to detect changes in the low-frequency range. Other frequency ranges such as heartbeat (1 to 1.7 Hz) can be used to reduce the acquisition time to few seconds but would necessitate optimizing instrumentation to ensure larger signal-to-noise ratios are achieved. CONCLUSIONS A method based on multispectral reflectance signals and low-frequency hemoglobin concentration changes can be used to distinguish bleeding, blood vessels, and cortex. This could be integrated into fiber optic probes to enhance signal specificity by providing users an indication of whether measurements are corrupted by blood pooling, an important confounding factor in biomedical optics applied to surgery.
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Affiliation(s)
- Audrey Laurence
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Québec, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
| | - Alain Bouthillier
- Centre Hospitalier de l’Université de Montréal, Division of Neurosurgery, Montréal, Québec, Canada
| | - Manon Robert
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
| | - Dang K. Nguyen
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Centre Hospitalier de l’Université de Montréal, Division of Neurology, Montréal, Québec, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Québec, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
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Picot F, Daoust F, Sheehy G, Dallaire F, Chaikho L, Bégin T, Kadoury S, Leblond F. Data consistency and classification model transferability across biomedical Raman spectroscopy systems. TRANSLATIONAL BIOPHOTONICS 2020. [DOI: 10.1002/tbio.202000019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Affiliation(s)
- Fabien Picot
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
- Centre de recherche du Centre Hospitalier de l'Université de Montréal Montreal Quebec Canada
| | - François Daoust
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
- Centre de recherche du Centre Hospitalier de l'Université de Montréal Montreal Quebec Canada
| | - Guillaume Sheehy
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
- Centre de recherche du Centre Hospitalier de l'Université de Montréal Montreal Quebec Canada
| | - Frédérick Dallaire
- Centre de recherche du Centre Hospitalier de l'Université de Montréal Montreal Quebec Canada
| | - Layal Chaikho
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
| | - Théophile Bégin
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
| | - Samuel Kadoury
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
- Centre de recherche du Centre Hospitalier de l'Université de Montréal Montreal Quebec Canada
| | - Frédéric Leblond
- Department of Engineering Physics Polytechnique Montréal, 2500 chemin de Polytechnique Montreal Quebec Canada
- Centre de recherche du Centre Hospitalier de l'Université de Montréal Montreal Quebec Canada
- Institut du Cancer de Montréal Montreal Quebec Canada
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Heng HPS, Shu C, Zheng W, Lin K, Huang Z. Advances in real‐time fiber‐optic Raman spectroscopy for early cancer diagnosis: Pushing the frontier into clinical endoscopic applications. TRANSLATIONAL BIOPHOTONICS 2020. [DOI: 10.1002/tbio.202000018] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
- Howard Peng Sin Heng
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering National University of Singapore Singapore Singapore
- NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore Singapore
| | - Chi Shu
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering National University of Singapore Singapore Singapore
| | - Wei Zheng
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering National University of Singapore Singapore Singapore
| | - Kan Lin
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering National University of Singapore Singapore Singapore
| | - Zhiwei Huang
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering National University of Singapore Singapore Singapore
- NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore Singapore
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Baria E, Pracucci E, Pillai V, Pavone FS, Ratto GM, Cicchi R. In vivo detection of murine glioblastoma through Raman and reflectance fiber-probe spectroscopies. NEUROPHOTONICS 2020; 7:045010. [PMID: 33274251 PMCID: PMC7707056 DOI: 10.1117/1.nph.7.4.045010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 10/14/2020] [Indexed: 05/29/2023]
Abstract
Significance: Glioblastoma (GBM) is the most common and aggressive malignant brain tumor in adults. With a worldwide incidence rate of 2 to 3 per 100,000 people, it accounts for more than 60% of all brain cancers; currently, its 5-year survival rate is < 5 % . GBM treatment relies mainly on surgical resection. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumor detection and guiding the removal of diseased tissues. Aim: Discriminating healthy brain from GBM tissues in an animal model through the combination of Raman and reflectance spectroscopies. Approach: EGFP-GL261 cells were injected into the brains of eight laboratory mice for inducing murine GBM in these animals. A multimodal optical fiber probe combining fluorescence, Raman, and reflectance spectroscopy was used to localize in vivo healthy and tumor brain areas and to collect their spectral information. Results: Tumor areas were localized through the detection of EGFP fluorescence emission. Then, Raman and reflectance spectra were collected from healthy and tumor tissues, and later analyzed through principal component analysis and linear discriminant analysis in order to develop a classification algorithm. Raman and reflectance spectra resulted in 92% and 93% classification accuracy, respectively. Combining together these techniques allowed improving the discrimination between healthy and tumor tissues up to 97%. Conclusions: These preliminary results demonstrate the potential of multimodal fiber-probe spectroscopy for in vivo label-free detection and delineation of brain tumors, and thus represent an additional, encouraging step toward clinical translation and deployment of fiber-probe spectroscopy.
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Affiliation(s)
- Enrico Baria
- University of Florence, Department of Physics, Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
| | - Enrico Pracucci
- Scuola Normale Superiore, National Enterprise for Nanoscience and Nanotechnology, Pisa, Italy
| | - Vinoshene Pillai
- Scuola Normale Superiore, National Enterprise for Nanoscience and Nanotechnology, Pisa, Italy
| | - Francesco S. Pavone
- University of Florence, Department of Physics, Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
- National Institute of Optics – National Research Council, Sesto Fiorentino, Italy
| | - Gian M. Ratto
- Scuola Normale Superiore, National Enterprise for Nanoscience and Nanotechnology, Pisa, Italy
| | - Riccardo Cicchi
- European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
- National Institute of Optics – National Research Council, Sesto Fiorentino, Italy
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Stepan KO, Li MM, Kang SY, Puram SV. Molecular margins in head and neck cancer: Current techniques and future directions. Oral Oncol 2020; 110:104893. [PMID: 32702629 DOI: 10.1016/j.oraloncology.2020.104893] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 07/01/2020] [Indexed: 12/14/2022]
Abstract
Complete tumor extirpation with clear surgical margins remains a central tenet of oncologic head and neck surgery. Rates of locoregional recurrence and survival are both significantly worse when clear margins are unable to be obtained. Current clinical practice relies on the use of frozen sections intra-operatively, followed by traditional histopathologic analysis post-operatively to assess the surgical margin. However, with improved understanding of tumor biology and advances in technology, new techniques have emerged to analyze margins at a molecular level. Such molecular margin analysis interrogates tissue for genetic, epigenetic, or proteomic changes that may belie tumor presence or aggressive features not captured by standard histopathologic techniques. Intra-operatively, this information may be used to guide resection, while post-operatively, it may help to stratify patients for adjuvant treatment. In this review, we summarize the current state of molecular margin analysis and describe directions for future research.
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Affiliation(s)
- Katelyn O Stepan
- Department of Otolaryngology - Head and Neck Surgery, Washington University School of Medicine, 4921 Parkview Pl, St. Louis, MO 63110, USA
| | - Michael M Li
- Department of Otolaryngology - Head and Neck Surgery, Ohio State University Wexner Medical Center, 410 W. 10(th) Ave, Columbus, OH, USA
| | - Stephen Y Kang
- Department of Otolaryngology - Head and Neck Surgery, Ohio State University Wexner Medical Center, 410 W. 10(th) Ave, Columbus, OH, USA
| | - Sidharth V Puram
- Department of Otolaryngology - Head and Neck Surgery, Washington University School of Medicine, 4921 Parkview Pl, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine, 4921 Parkview Pl, St. Louis, MO 63110, USA.
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Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening. Molecules 2020; 25:molecules25122852. [PMID: 32575717 PMCID: PMC7355922 DOI: 10.3390/molecules25122852] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/12/2020] [Accepted: 06/18/2020] [Indexed: 01/26/2023] Open
Abstract
A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a “second opinion” for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.
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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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DePaoli D, Lemoine É, Ember K, Parent M, Prud’homme M, Cantin L, Petrecca K, Leblond F, Côté DC. Rise of Raman spectroscopy in neurosurgery: a review. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-36. [PMID: 32358930 PMCID: PMC7195442 DOI: 10.1117/1.jbo.25.5.050901] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/10/2020] [Indexed: 05/21/2023]
Abstract
SIGNIFICANCE Although the clinical potential for Raman spectroscopy (RS) has been anticipated for decades, it has only recently been used in neurosurgery. Still, few devices have succeeded in making their way into the operating room. With recent technological advancements, however, vibrational sensing is poised to be a revolutionary tool for neurosurgeons. AIM We give a summary of neurosurgical workflows and key translational milestones of RS in clinical use and provide the optics and data science background required to implement such devices. APPROACH We performed an extensive review of the literature, with a specific emphasis on research that aims to build Raman systems suited for a neurosurgical setting. RESULTS The main translatable interest in Raman sensing rests in its capacity to yield label-free molecular information from tissue intraoperatively. Systems that have proven usable in the clinical setting are ergonomic, have a short integration time, and can acquire high-quality signal even in suboptimal conditions. Moreover, because of the complex microenvironment of brain tissue, data analysis is now recognized as a critical step in achieving high performance Raman-based sensing. CONCLUSIONS The next generation of Raman-based devices are making their way into operating rooms and their clinical translation requires close collaboration between physicians, engineers, and data scientists.
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Affiliation(s)
- Damon DePaoli
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
| | - Émile Lemoine
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Katherine Ember
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Martin Parent
- Université Laval, CERVO Brain Research Center, Québec, Canada
| | - Michel Prud’homme
- Hôpital de l’Enfant-Jésus, Department of Neurosurgery, Québec, Canada
| | - Léo Cantin
- Hôpital de l’Enfant-Jésus, Department of Neurosurgery, Québec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, Montreal, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
- Address all correspondence to Frédéric Leblond, E-mail: ; Daniel C. Côté, E-mail:
| | - Daniel C. Côté
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
- Address all correspondence to Frédéric Leblond, E-mail: ; Daniel C. Côté, E-mail:
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Hubbard TJE, Shore A, Stone N. Raman spectroscopy for rapid intra-operative margin analysis of surgically excised tumour specimens. Analyst 2020; 144:6479-6496. [PMID: 31616885 DOI: 10.1039/c9an01163c] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Raman spectroscopy, a form of vibrational spectroscopy, has the ability to provide sensitive and specific biochemical analysis of tissue. This review article provides an in-depth analysis of the suitability of different Raman spectroscopy techniques in providing intra-operative margin analysis in a range of solid tumour pathologies. Surgical excision remains the primary treatment of a number of solid organ cancers. Incomplete excision of a tumour and positive margins on histopathological analysis is associated with a worse prognosis, the need for adjuvant therapies with significant side effects and a resulting financial burden. The provision of intra-operative margin analysis of surgically excised tumour specimens would be beneficial for a number of pathologies, as there are no widely adopted and accurate methods of margin analysis, beyond histopathology. The limitations of Raman spectroscopic studies to date are discussed and future work necessary to enable translation to clinical use is identified. We conclude that, although there remain a number of challenges in translating current techniques into a clinically effective tool, studies so far demonstrate that Raman Spectroscopy has the attributes to successfully perform highly accurate intra-operative margin analysis in a clinically relevant environment.
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Lemoine É, Dallaire F, Yadav R, Agarwal R, Kadoury S, Trudel D, Guiot MC, Petrecca K, Leblond F. Feature engineering applied to intraoperative in vivo Raman spectroscopy sheds light on molecular processes in brain cancer: a retrospective study of 65 patients. Analyst 2020; 144:6517-6532. [PMID: 31647061 DOI: 10.1039/c9an01144g] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Raman spectroscopy is a promising tool for neurosurgical guidance and cancer research. Quantitative analysis of the Raman signal from living tissues is, however, limited. Their molecular composition is convoluted and influenced by clinical factors, and access to data is limited. To ensure acceptance of this technology by clinicians and cancer scientists, we need to adapt the analytical methods to more closely model the Raman-generating process. Our objective is to use feature engineering to develop a new representation for spectral data specifically tailored for brain diagnosis that improves interpretability of the Raman signal while retaining enough information to accurately predict tissue content. The method consists of band fitting of Raman bands which consistently appear in the brain Raman literature, and the generation of new features representing the pairwise interaction between bands and the interaction between bands and patient age. Our technique was applied to a dataset of 547 in situ Raman spectra from 65 patients undergoing glioma resection. It showed superior predictive capacities to a principal component analysis dimensionality reduction. After analysis through a Bayesian framework, we were able to identify the oncogenic processes that characterize glioma: increased nucleic acid content, overexpression of type IV collagen and shift in the primary metabolic engine. Our results demonstrate how this mathematical transformation of the Raman signal allows the first biological, statistically robust analysis of in vivo Raman spectra from brain tissue.
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Affiliation(s)
- Émile Lemoine
- Department of Engineering Physics, Polytechnique Montreal, Montreal, Quebec, Canada.
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Dallaire F, Picot F, Tremblay JP, Sheehy G, Lemoine É, Agarwal R, Kadoury S, Trudel D, Lesage F, Petrecca K, Leblond F. Quantitative spectral quality assessment technique validated using intraoperative in vivo Raman spectroscopy measurements. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-8. [PMID: 32319263 PMCID: PMC7171512 DOI: 10.1117/1.jbo.25.4.040501] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 04/08/2020] [Indexed: 05/14/2023]
Abstract
SIGNIFICANCE Ensuring spectral quality is prerequisite to Raman spectroscopy applied to surgery. This is because the inclusion of poor-quality spectra in the training phase of Raman-based pathology detection models can compromise prediction robustness and generalizability to new data. Currently, there exists no quantitative spectral quality assessment technique that can be used to either reject low-quality data points in existing Raman datasets based on spectral morphology or, perhaps more importantly, to optimize the in vivo data acquisition process to ensure minimal spectral quality standards are met. AIM To develop a quantitative method evaluating Raman signal quality based on the variance associated with stochastic noise in important tissue bands, including C─C stretch, CH2 / CH3 deformation, and the amide bands. APPROACH A single-point hand-held Raman spectroscopy probe system was used to acquire 315 spectra from 44 brain cancer patients. All measurements were classified as either high or low quality based on visual assessment (qualitative) and using a quantitative quality factor (QF) metric. Receiver-operator-characteristic (ROC) analyses were performed to evaluate the performance of the quantitative metric to assess spectral quality and improve cancer detection accuracy. RESULTS The method can separate high- and low-quality spectra with a sensitivity of 89% and a specificity of 90% which is shown to increase cancer detection sensitivity and specificity by up to 20% and 12%, respectively. CONCLUSIONS The QF threshold is effective in stratifying spectra in terms of spectral quality and the observed false negatives and false positives can be linked to limitations of qualitative spectral quality assessment.
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Affiliation(s)
- Frédérick Dallaire
- Polytechnique Montréal, Department of Computer Engineering and Software Engineering, Montréal, Québec, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
| | - Fabien Picot
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Québec, Canada
| | | | - Guillaume Sheehy
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Québec, Canada
| | - Émile Lemoine
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Polytechnique Montréal, Department of Electrical Engineering Montréal, Québec, Canada
| | | | - Samuel Kadoury
- Polytechnique Montréal, Department of Computer Engineering and Software Engineering, Montréal, Québec, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
| | - Dominique Trudel
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Université de Montréal, Department of Pathology and Cellular Biology, Montréal, Québec, Canada
- Centre Hospitalier de l’Université de Montréal, Department of Pathology, Québec, Canada
| | - Frédéric Lesage
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Centre de Recherche de l’Institut de Cardiologie de Montréal, Montréal, Québec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute and Hospital, Brain Tumour Research Center, Department of Neurology and Neurosurgery, Montréal, Québec, Canada
| | - Frédéric Leblond
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Québec, Canada
- Address all correspondence to Frédéric Leblond, E-mail:
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42
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Virtual spectral histopathology of colon cancer - biomedical applications of Raman spectroscopy and imaging. J Mol Liq 2020. [DOI: 10.1016/j.molliq.2020.112676] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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43
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Shams R, Picot F, Grajales D, Sheehy G, Dallaire F, Birlea M, Saad F, Trudel D, Menard C, Leblond F, Kadoury S. Pre-clinical evaluation of an image-guided in-situ Raman spectroscopy navigation system for targeted prostate cancer interventions. Int J Comput Assist Radiol Surg 2020; 15:867-876. [PMID: 32227280 DOI: 10.1007/s11548-020-02136-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Accepted: 03/18/2020] [Indexed: 01/13/2023]
Abstract
PURPOSE Transrectal ultrasound (TRUS) image guidance is the standard of care for diagnostic and therapeutic interventions in prostate cancer (PCa) patients, but can lead to high false-negative rates, compromising downstream effectiveness of therapeutic choices. A promising approach to improve in-situ detection of PCa lies in using the optical properties of the tissue to discern cancer from healthy tissue. In this work, we present the first in-situ image-guided navigation system for a spatially tracked Raman spectroscopy probe integrated in a PCa workflow, capturing the optical tissue fingerprint. The probe is guided with fused TRUS/MR imaging and tested with both tissue-simulating phantoms and ex-vivo prostates. The workflow was designed to be integrated the clinical workflow for trans-perineal prostate biopsies, as well as for high-dose rate (HDR) brachytherapy. METHODS The proposed system developed in 3D Slicer includes an electromagnetically tracked Raman spectroscopy probe, along with tracked TRUS imaging automatically registered to diagnostic MRI. The proposed system is tested on both custom gelatin tissue-simulating optical phantoms and biological tissue phantoms. A random-forest classifier was then trained on optical spectrums from ex-vivo prostates following prostatectomy using our optical probe. Preliminary in-human results are presented with the Raman spectroscopy instrument to detect malignant tissue in-situ with histopathology confirmation. RESULTS In 5 synthetic gelatin and biological tissue phantoms, we demonstrate the ability of the image-guided Raman system by detecting over 95% of lesions, based on biopsy samples. The included lesion volumes ranged from 0.1 to 0.61 cc. We showed the compatibility of our workflow with the current HDR brachytherapy setup. In ex-vivo prostates of PCa patients, the system showed a 81% detection accuracy in high grade lesions. CONCLUSION Pre-clinical experiments demonstrated promising results for in-situ confirmation of lesion locations in prostates using Raman spectroscopy, both in phantoms and human ex-vivo prostate tissue, which is required for integration in HDR brachytherapy procedures.
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Affiliation(s)
| | | | | | | | | | - Mirela Birlea
- Centre Hospitalier de l'Universite de Montreal Research Center, Montreal, Canada
| | - Fred Saad
- Centre Hospitalier de l'Universite de Montreal Research Center, Montreal, Canada
| | - Dominique Trudel
- Centre Hospitalier de l'Universite de Montreal Research Center, Montreal, Canada
| | - Cynthia Menard
- Centre Hospitalier de l'Universite de Montreal Research Center, Montreal, Canada
| | | | - Samuel Kadoury
- Polytechnique Montreal, Montreal, Canada.
- Centre Hospitalier de l'Universite de Montreal Research Center, Montreal, Canada.
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Agsalda-Garcia M, Shieh T, Souza R, Kamada N, Loi N, Oda R, Acosta-Maeda T, Choi SY, Lim E, Misra A, Shiramizu B. Raman-Enhanced Spectroscopy (RESpect) Probe for Childhood Non-Hodgkin Lymphoma. SCIMEDICINE JOURNAL 2020; 2:1-7. [PMID: 34085057 PMCID: PMC8172049 DOI: 10.28991/scimedj-2020-0201-1] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Raman-enhanced spectroscopy (RESpect) probe, which enhances Raman spectroscopy technology through a portable fiber-optic device, characterizes tissues and cells by identifying molecular chemical composition showing distinct differences/similarities for potential tumor markers or diagnosis. In a feasibility study with the ultimate objective to translate the technology to the clinic, a panel of pediatric non-Hodgkin lymphoma tissues and non-malignant specimens had RS analyses compared between standard Raman spectroscopy microscope instrument and RESpect probe. Cryopreserved tissues were mounted on front-coated aluminum mirror slides and analyzed by standard Raman spectroscopy and RESpect probe. Principal Component Analysis revealed similarities between non-Hodgkin lymphoma subtypes but not follicular hyperplasia. Standard Raman spectroscopy and RESpect probe fingerprint comparisons demonstrated comparable primary peaks. Raman spectroscopic fingerprints and peaks of pediatric non-Hodgkin lymphoma subtypes and follicular hyperplasia provided novel avenues to pursue diagnostic approaches and identify potential new therapeutic targets. The information could inform new insights into molecular cellular pathogenesis. Translating Raman spectroscopy technology by using the RESpect probe as a potential point-of-care screening instrument has the potential to change the paradigm of screening for cancer as an initial step to determine when a definitive tissue biopsy would be necessary.
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Affiliation(s)
- Melissa Agsalda-Garcia
- Department of Tropical Medicine, Medical Microbiology, and Pharmacology, University of Hawaii, Hawaii, United States
| | - Tiffany Shieh
- Department of Tropical Medicine, Medical Microbiology, and Pharmacology, University of Hawaii, Hawaii, United States
| | - Ryan Souza
- Department of Tropical Medicine, Medical Microbiology, and Pharmacology, University of Hawaii, Hawaii, United States
| | - Natalie Kamada
- Department of Tropical Medicine, Medical Microbiology, and Pharmacology, University of Hawaii, Hawaii, United States
| | - Nicholas Loi
- Department of Tropical Medicine, Medical Microbiology, and Pharmacology, University of Hawaii, Hawaii, United States
| | - Robert Oda
- Department Molecular Biosciences & Bioengineering, University of Hawaii, Hawaii, United States
| | - Tayro Acosta-Maeda
- Hawaii Institute of Geophysics and Planetology, University of Hawaii, Hawaii, United States
| | - So Yung Choi
- Biostatistics Core, Department of Complementary and Integrative Medicine, University of Hawaii, Hawaii, United States
| | - Eunjung Lim
- Biostatistics Core, Department of Complementary and Integrative Medicine, University of Hawaii, Hawaii, United States
| | - Anupam Misra
- Hawaii Institute of Geophysics and Planetology, University of Hawaii, Hawaii, United States
| | - Bruce Shiramizu
- Department of Tropical Medicine, Medical Microbiology, and Pharmacology, University of Hawaii, Hawaii, United States
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Tichauer KM, Wang C, Xu X, Samkoe KS. Task-based evaluation of fluorescent-guided cancer surgery as a means of identifying optimal imaging agent properties in the context of variability in tumor- and healthy-tissue physiology. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2020; 11222. [PMID: 33568879 DOI: 10.1117/12.2546700] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Fluorescent molecular-guided surgery (FGS) is at a tipping point in terms of clinical approval and adoption in a number cancer applications, with ongoing phase 0 and phase 1 clinical trials being carried out in a wide range of cancers using a wide range of agents. The pharmacokinetics of each of these agents and the physiology of these cancers can differ vastly on a patient-to-patient basis, bringing to question: how can one fairly compare different methodologies (defined as the combination of imaging agent, system, and protocol) and how can existing methodologies be further optimized? To this point, little methodology comparison has been carried out, and the majority of FGS optimization has concerned system development-on the level of maximizing signal-to-noise, dynamic detection range, and sensitivity-independently from traditional agent development-in terms of fluorophore brightness, toxicity, solubility, and binding affinity and specificity. Here we propose an inclusion of tumor and healthy tissue physiology (blood flow, vascular permeability, specific and nonspecific binding sites, extracellular matrix, interstitial pressure, etc…) variability into the optimization process and re-establish well-described task-based metrics for methodology optimization and comparing quality of one methodology to another. Two salient conclusions were identified: (1) contrast-to-background variability is a simple metric that correlates with difficult-to-carry-out task-based metrics for comparing methodologies, and (2) paired-agent imaging protocols offer unique advantages over single-imaging-agent studies for mitigating confounding tumor and background physiology variability.
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Affiliation(s)
| | - Cheng Wang
- Thayer School of Engineering, Dartmouth College, Hanover, NH
| | - Xiaochun Xu
- Department of Surgery, Dartmouth Geisel School of Medicine, Hanover, NH
| | - Kimberley S Samkoe
- Thayer School of Engineering, Dartmouth College, Hanover, NH.,Department of Surgery, Dartmouth Geisel School of Medicine, Hanover, NH
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Zhang Y, Moy AJ, Feng X, Nguyen HTM, Reichenberg JS, Markey MK, Tunnell JW. Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis. JOURNAL OF BIOPHOTONICS 2019; 12:e201900154. [PMID: 31325232 DOI: 10.1002/jbio.201900154] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 07/10/2019] [Accepted: 07/17/2019] [Indexed: 05/25/2023]
Abstract
Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low-cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.
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Affiliation(s)
- Yao Zhang
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
| | - Austin J Moy
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
| | - Xu Feng
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
| | - Hieu T M Nguyen
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
| | | | - Mia K Markey
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - James W Tunnell
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
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Wang C, Fan W, Zhang Z, Wen Y, Xiong L, Chen X. Advanced Nanotechnology Leading the Way to Multimodal Imaging-Guided Precision Surgical Therapy. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2019; 31:e1904329. [PMID: 31538379 DOI: 10.1002/adma.201904329] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Revised: 08/18/2019] [Indexed: 06/10/2023]
Abstract
Surgical resection is the primary and most effective treatment for most patients with solid tumors. However, patients suffer from postoperative recurrence and metastasis. In the past years, emerging nanotechnology has led the way to minimally invasive, precision and intelligent oncological surgery after the rapid development of minimally invasive surgical technology. Advanced nanotechnology in the construction of nanomaterials (NMs) for precision imaging-guided surgery (IGS) as well as surgery-assisted synergistic therapy is summarized, thereby unlocking the advantages of nanotechnology in multimodal IGS-assisted precision synergistic cancer therapy. First, mechanisms and principles of NMs to surgical targets are briefly introduced. Multimodal imaging based on molecular imaging technologies provides a practical method to achieve intraoperative visualization with high resolution and deep tissue penetration. Moreover, multifunctional NMs synergize surgery with adjuvant therapy (e.g., chemotherapy, immunotherapy, phototherapy) to eliminate residual lesions. Finally, key issues in the development of ideal theranostic NMs associated with surgical applications and challenges of clinical transformation are discussed to push forward further development of NMs for multimodal IGS-assisted precision synergistic cancer therapy.
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Affiliation(s)
- Cong Wang
- Department of General Surgery, Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China
| | - Wenpei Fan
- Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Zijian Zhang
- Department of General Surgery, Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China
| | - Yu Wen
- Department of General Surgery, Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China
| | - Li Xiong
- Department of General Surgery, Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China
| | - Xiaoyuan Chen
- Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
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Ghani KA, Sudik S, Omar AF, Mail MH, Seeni A. VIS-NIR spectral signature and quantitative analysis of HeLa and DU145 cell line. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 222:117241. [PMID: 31216502 DOI: 10.1016/j.saa.2019.117241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 06/01/2019] [Accepted: 06/05/2019] [Indexed: 06/09/2023]
Abstract
Cancer is increasing in incidence and the leading cause of death worldwide. Controlling and reducing cancer requires early detection and technique to accurately detect and quantify predictive biomarkers. Optical spectroscopy has shown promising non-destructive ability to display distinctive spectral characteristics between cancerous and normal tissues from different part of human organ. Nonetheless, not many information is available on spectroscopic properties of cancer cell lines. In this research, the visible-near infrared (VIS-NIR) absorbance spectroscopy measurement of cultured cervical cancer (HeLa) and prostate cancer cells (DU145) lines has been performed to develop spectral signature of cancer cells and to generate algorithm to quantify cancer cells. Spectroscopic measurement on mouse skin fibroblast (L929) was also taken for comparative purposes. In visible region, the raw cells' spectra do not produce any noticeable peak absorbance that provides information on color because the medium used for cells is colorless and transparent. NIR wavelength between 950 and 975 nm exhibit significant peak due to water absorbance by the medium. Development of spectral signature for the cells through the application of regression technique significantly enhances the diverse characteristics between L929, HeLa and DU145. The application of multiple linear regression allows high measurement accuracy of the cells with coefficient of determination above 0.94.
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Affiliation(s)
| | - Suhainah Sudik
- School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia
| | - Ahmad Fairuz Omar
- School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia.
| | - Mohd Hafiz Mail
- Malaysian Institute of Pharmaceuticals and Nutraceuticals, National Institute of Biotechnology Malaysia, Ministry of Energy, Science, Technology, Environment and Climate Change, 11700 Penang, Malaysia; Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, 13200, Pulau Pinang, Malaysia
| | - Azman Seeni
- Malaysian Institute of Pharmaceuticals and Nutraceuticals, National Institute of Biotechnology Malaysia, Ministry of Energy, Science, Technology, Environment and Climate Change, 11700 Penang, Malaysia; Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, 13200, Pulau Pinang, Malaysia
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Li MM, Puram SV, Silverman DA, Old MO, Rocco JW, Kang SY. Margin Analysis in Head and Neck Cancer: State of the Art and Future Directions. Ann Surg Oncol 2019; 26:4070-4080. [PMID: 31385128 PMCID: PMC7382965 DOI: 10.1245/s10434-019-07645-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Indexed: 01/28/2023]
Abstract
BACKGROUND The status of surgical margins is the most important prognosticator for patients undergoing surgical resection of head and neck squamous cell carcinoma (HNSCC). Despite this, analysis of surgical margins is fraught with inconsistencies, including the ways in which margins are sampled and interpreted. Fundamentally, even the definition what constitutes a "clear" (or negative) margin may vary between institutions, surgeons, and pathologists. METHODS The PubMed database was queried for articles relevant to the topic, and experts in the field were consulted regarding key articles for inclusion. Abstracts were reviewed and the full text was accessed for articles of particular interest. RESULTS Data regarding various approaches to traditional margin analysis have been published without consensus. Several next-generation technologies have emerged in recent years that hold promise. CONCLUSION An overview and appraisal of traditional margin analysis techniques are provided. Additionally, we explore novel technologies that may assist in more accurate margin assessment, guide the extent of surgical resections intraoperatively, and inform decisions regarding adjuvant treatment postoperatively.
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Affiliation(s)
- Michael M Li
- Division of Head and Neck Oncology, Department of Otolaryngology - Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA
| | - Sidharth V Puram
- Division of Head and Neck Oncology, Department of Otolaryngology - Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA
| | - Dustin A Silverman
- Division of Head and Neck Oncology, Department of Otolaryngology - Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA
| | - Matthew O Old
- Division of Head and Neck Oncology, Department of Otolaryngology - Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA
| | - James W Rocco
- Division of Head and Neck Oncology, Department of Otolaryngology - Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA
| | - Stephen Y Kang
- Division of Head and Neck Oncology, Department of Otolaryngology - Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, USA.
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Duan P, Li J, Yang W, Li X, Long M, Feng X, Zhang Y, Chen C, Morais CLM, Martin FL, Luo J, Liu D, Xiong C. Fourier transform infrared and Raman-based biochemical profiling of different grades of pure foetal-type hepatoblastoma. JOURNAL OF BIOPHOTONICS 2019; 12:e201800304. [PMID: 30993892 DOI: 10.1002/jbio.201800304] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 04/05/2019] [Accepted: 04/07/2019] [Indexed: 06/09/2023]
Abstract
The biomolecular events resulting from the progression of hepatoblastoma remain to be elucidated. Fourier-transform infrared (FTIR) and Raman spectroscopies are capable of noninvasively and accurately capturing the biochemical properties of biological tissue from its pathological status. Our aim was to probe critial biomolecular changes of liver accompanying the progression of pure foetal hepatoblastoma (PFH) by FTIR and Raman spectroscopies. Herein, biochemical alterations were both evident in the FTIR spectra (regions of 3100-2800 cm-1 and 1800-900 cm-1 ) and the Raman spectra (region of 1800-400 cm-1 ) among normal, borderline and malignant liver tissues. Compared with normal tissues, the ratios of protein-to-lipid, α-helix-to-β-sheet, RNA-to-DNA, CH3 methyl-to-CH2 methylene, glucose-to-phospholipids, and unsaturated-to-saturated lipids intensities were significantly higher in malignant tissues, while the ratios of RNA-to-Amide II, DNA-to-Amide II, glycogen-to-cholesterol and Amide I-to-Amide II intensities were remarkably lower. These biochemical alterations in the transition from normal to malignant have profound implications not only for cyto-pathological classification but also for molecular understanding of PFH progression. The successive changes of the spectral characteristics have been shown to be consistent with the development of PFH, indicating that FTIR and Raman spectroscopies are excellent tools to interrogate the biochemical features of different grades of PFH.
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Affiliation(s)
- Peng Duan
- Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Center for Reproductive Medicine, Xiangyang No. 1 People's Hospital, Hubei University of Medicine, Xiangyang, China
| | - Junyi Li
- State Key Laboratory of Tribology, Tsinghua University, Beijing, China
| | - Weiyingxue Yang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiandong Li
- Department of Clinical Laboratory, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Manman Long
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaobing Feng
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuge Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chunling Chen
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Camilo L M Morais
- Lancashire Teaching Hospitals NHS Trust, Preston, UK
- Biocel Ltd, Hull, UK
| | | | - Jianbin Luo
- State Key Laboratory of Tribology, Tsinghua University, Beijing, China
| | - Dameng Liu
- State Key Laboratory of Tribology, Tsinghua University, Beijing, China
| | - Chengliang Xiong
- Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Center for Reproductive Medicine, Wuhan Tongji Reproductive Medicine Hospital, Wuhan, China
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