The potential role of optical guidance for bone-related biomedical applications in orthopedics and neurosurgery

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dc.contributor.advisorAndersson-Engels, Stefan
dc.contributor.advisorBurke, Ray
dc.contributor.authorLi, Li Yaoen
dc.contributor.funderScience Foundation Ireland
dc.date.accessioned2025-02-14T16:50:53Z
dc.date.available2025-02-14T16:50:53Z
dc.date.issued2024en
dc.date.submitted2024
dc.description.abstractOptical sensing technology was explored as a means of intraoperative guidance for bone-related procedures in orthopedics and neurosurgery. Specifically, the feasibility of diffuse reflectance spectroscopy (DRS), a non-invasive and real-time optical technique that measures diffusely reflected light off samples of interest, was investigated in the thesis to differentiate biological tissue types and inform tissue boundaries as an intraoperative safety measure for revision total hip arthroplasty. Feature selection (FS) frameworks based on DRS measurements were developed utilizing machine learning techniques to determine wavelength features of optimal discriminative power for bone-related surgical procedures. Four FS frameworks, incorporating principal component analysis (PCA), linear discriminant analysis (LDA), backward interval partial least squares and an ensemble approach (biPLS), were designed with high adaptability to facilitate modifications and applications to other clinical scenarios. A feature subset of 10 wavelengths was generated from each FS framework yielding promising balanced accuracy scores for the one-vs-rest binary classification task. For cortical bone versus the rest class labels, PCA, LDA, biPLS and ensemble -based FS framework computed balanced accuracy scores of 94.8 ± 3.47%, 98.2 ± 2.02%, 95.8 ± 3.04% and 95.8 ± 3.16, respectively. For bone cement versus the rest, 100% balanced accuracy scores were generated from all FS frameworks. Subsequently, an in-house designed optical probe integrating DRS sensing was engineered and examined in ex vivo experiments. The most discriminative DRS wavelengths, selected by the FS frameworks including 1200 and 1450 nm, were incorporated as the illumination light sources. Furthermore, the performance of DRS to predict drilling depths in cranial bones was evaluated for craniotomy. Two models including partial least squares (PLS) regression and feedforward neural networks (FNN) were examined for prediction of skull thickness ranging from 1 to 5 mm away from the brain, yielding a root mean squared error regression loss of 0.08 and 0.06 mm from PLS, and 0.2 and 0.1 mm from FNN by using all versus selected features as model inputs, respectively. The predicted depths served as a safety protocol to indicate lookahead distances. On the other hand, the potential of ultrafast lasers in bone-related surgical applications was reviewed and explored from multiple perspectives. The advantages offered by ultrafast lasers over conventional laser systems (continuous wave or long-pulse lasers) included superior precision and minimized collateral thermal damage to surrounding tissues. However, clinical translation of ultrafast lasers to surgical applications had been constrained by limitations in pulse average power and material removal rate. In contrast, the use in implant surface texturing had advanced substantially, effectively enhancing bioactivation and osteointegration within bone matrices. At the end, ambient mass spectrometry, which employed a picosecond laser system for plume generation, was additionally assessed for tissue differentiation in a preliminary study. The classification model employed PCA for dimensionality reduction and LDA for multi-class classification. By using the reduced mass spectra dataset, bone cement was distinguished from biological tissue types with 100% in different classification metrics (precision, recall, F1 score). The highest misclassification rate occurred between trabecular and cortical bone with 18 instances where trabecular bone was classified as cortical bone. Overall, the research presented in the thesis has demonstrated promising results to advance basic science and consequently set the foundation for translational study of integrating optical sensing into surgical tools in bone-related procedures with valuable insights. This work was supported by Science Foundation Ireland (SFI), Grant No. SFI/15/RP/2828 and Grant No. SFI/22/RP-2TF/10293.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationLi, L. Y. 2024. The potential role of optical guidance for bone-related biomedical applications in orthopedics and neurosurgery. PhD Thesis, University College Cork.
dc.identifier.endpage145
dc.identifier.urihttps://hdl.handle.net/10468/17050
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Professorship Programme/15/RP/2828/IE/Novel applications and techniques for in vivo optical imaging and spectroscopy/
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Professorship Programme::Second-Term Funding/22/RP-2TF/10293/IE/Biophotonics@Tyndall phase 2 - Novel applications and techniques for in vivo optical imaging and spectroscopy/
dc.rights© 2024, Li Yao Li.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectFeature selectionen
dc.subjectOptical guidanceen
dc.subjectOrthopedicsen
dc.subjectDiffuse reflectance spectroscopyen
dc.subjectClassificationen
dc.subjectUltrafast lasersen
dc.titleThe potential role of optical guidance for bone-related biomedical applications in orthopedics and neurosurgeryen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD - Doctor of Philosophyen
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