A blinded study using laser induced endogenous fluorescence spectroscopy to differentiate ex vivo spine tumor, healthy muscle, and healthy bone.

dc.contributor.author

Sperber, Jacob

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Zachem, Tanner J

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Prakash, Ravi

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Owolo, Edwin

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Yamamoto, Kent

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Nguyen, Annee D

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Hockenberry, Harrison

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Ross, Weston A

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Herndon, James E

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Codd, Patrick J

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Goodwin, C Rory

dc.date.accessioned

2024-02-01T16:15:09Z

dc.date.available

2024-02-01T16:15:09Z

dc.date.issued

2024-01

dc.description.abstract

Ten patients undergoing surgical resection for spinal tumors were selected. Samples of tumor, muscle, and bone were resected, de-identified by the treating surgeon, and then scanned with the TumorID technology ex vivo. This study investigates whether TumorID technology is able to differentiate three different human clinical fresh tissue specimens: spine tumor, normal muscle, and normal bone. The TumorID technology utilizes a 405 nm excitation laser to target endogenous fluorophores, thereby allowing for the detection of tissue based on emission spectra. Metabolic profiles of tumor and healthy tissue vary, namely NADH (bound and free emission peak, respectively: 487 nm, 501 nm) and FAD (emission peak: 544) are endogenous fluorophores with distinct concentrations in tumor and healthy tissue. Emission spectra analyzed consisted of 74 scans of spine tumor, 150 scans of healthy normal bone, and 111 scans of healthy normal muscle. An excitation wavelength of 405 nm was used to obtain emission spectra from tissue as previously described. Emission spectra consisted of approximately 1400 wavelength intensity pairs between 450 and 750 nm. Kruskal-Wallis tests were conducted comparing AUC distributions for each treatment group, α = 0.05. Spectral signatures varied amongst the three different tissue types. All pairwise comparisons among tissues for Free NADH were statistically significant (Tumor vs. Muscle: p = 0.0006, Tumor vs. Bone: p < 0.0001, Bone vs. Muscle: p = 0.0357). The overall comparison of tissues for FAD (506.5-581.5 nm) was also statistically significant (p < 0.0001), with two pairwise comparisons being statistically significant (Tumor vs. Muscle: p < 0.0001, Tumor vs. Bone: p = 0.0045, Bone vs. Muscle: p = 0.249). These statistically significant differences were maintained when stratifying tumor into metastatic carcinoma (N = 57) and meningioma (N = 17). TumorID differentiates tumor tissue from normal bone and normal muscle providing further clinical evidence of its efficacy as a tissue identification tool. Future studies should evaluate TumorID's ability to serve as an adjunctive tool for intraoperative assessment of surgical margins and surgical decision-making.

dc.identifier

10.1038/s41598-023-50995-4

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2045-2322

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2045-2322

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https://hdl.handle.net/10161/30030

dc.language

eng

dc.publisher

Springer Science and Business Media LLC

dc.relation.ispartof

Scientific reports

dc.relation.isversionof

10.1038/s41598-023-50995-4

dc.rights.uri

https://creativecommons.org/licenses/by-nc/4.0

dc.subject

Humans

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NAD

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Spectrometry, Fluorescence

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Muscles

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Fluorescent Dyes

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Ionophores

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Lasers

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Meningeal Neoplasms

dc.title

A blinded study using laser induced endogenous fluorescence spectroscopy to differentiate ex vivo spine tumor, healthy muscle, and healthy bone.

dc.type

Journal article

duke.contributor.orcid

Zachem, Tanner J|0000-0002-3129-1133

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Prakash, Ravi|0000-0002-4020-1590

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Yamamoto, Kent|0000-0002-9296-8056

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Nguyen, Annee D|0000-0002-5550-9053

duke.contributor.orcid

Goodwin, C Rory|0000-0002-6540-2751

pubs.begin-page

1921

pubs.issue

1

pubs.organisational-group

Duke

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Pratt School of Engineering

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School of Medicine

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Student

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Basic Science Departments

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Clinical Science Departments

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Institutes and Centers

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Biostatistics & Bioinformatics

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Thomas Lord Department of Mechanical Engineering and Materials Science

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Orthopaedic Surgery

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Radiation Oncology

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Duke Cancer Institute

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Institutes and Provost's Academic Units

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Initiatives

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Neurosurgery

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Duke Innovation & Entrepreneurship

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Head and Neck Surgery & Communication Sciences

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Biostatistics & Bioinformatics, Division of Biostatistics

pubs.publication-status

Published

pubs.volume

14

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