Publications

@article{Dooley2022-rt,

title = {Model-based optimization of laser excitation and detection 

 improves spectral contrast in noninvasive diffuse Raman 

 spectroscopy},

author = {Max Dooley and Thomas Paterson and Louise Dexter and Pavel Matousek and Hamid Dehghani and Ioan Notingher},

year  = {2022},

date = {2022-07-01},

journal = {Appl. Spectrosc.},

volume = {76},

number = {7},

pages = {801\textendash811},

publisher = {SAGE Publications},

abstract = {Spatially offset Raman spectroscopy (SORS) is a powerful 

 technique for subsurface molecular analysis of optically turbid 

 samples. Numerical modeling of light propagation has been used 

 to investigate opportunities for improving spectral contrast and 

 signal to noise ratio when imaging regions of interest located 

 0-4.5 mm below the surface in polymer bulk material. Two- and 

 three-dimensional modeling results demonstrate that when 

 analyzing a certain region of interest (ROI) of finite lateral 

 dimensions below the sample surface, offsetting both the laser 

 source and detector in opposite directions from the central 

 point of the ROI can increase the spectral contrast as compared 

 to conventional SORS approach where the detector or the laser 

 source is maintained at the central point (centered SORS). The 

 outlined modeling results have been validated experimentally 

 using a bulk polymer sample with a trans-stilbene ROI (cylinder) 

 below the sample surface. The results show that modeling of the 

 spatial configurations of laser excitation and detection points 

 can be used to optimize the instrument configuration to achieve 

 significant improvements (up to 2.25-fold) in performance over 

 the conventional centered SORS. Such optimal solutions can then 

 be implemented, for example, using robust fiber optic probes, 

 moveable optics, or flexible spatial light modulator instruments 

 for specific applications.},

keywords = {computational modeling, diffuse Raman, Raman spectroscopy, SORS, spatially offset Raman spectroscopy},

pubstate = {published},

tppubtype = {article}

}

@article{Dooley2020-vf,

title = {Investigating the feasibility of spatially offset Raman 

 spectroscopy for in-vivo monitoring of bone healing in rat 

 calvarial defect models},

author = {Max Dooley and Jane McLaren and Felicity R A J Rose and Ioan Notingher},

year  = {2020},

date = {2020-10-01},

journal = {J. Biophotonics},

volume = {13},

number = {10},

pages = {e202000190},

publisher = {Wiley},

abstract = {A wide range of biomaterials and tissue-engineered scaffolds are 

 being investigated to support and stimulate bone healing in 

 animal models. Using phantoms and rat cadavers, we investigated 

 the feasibility of using spatially offset Raman spectroscopy 

 (SORS) to monitor changes in collagen concentration at levels 

 similar to those expected to occur in vivo during bone 

 regeneration (0-0.84 g/cm3 ). A partial least squares (PLS) 

 regression model was developed to quantify collagen 

 concentration in plugs consisting of mixtures or collagen and 

 hydroxyapatite (predictive power of $±$0.16 g/cm3 ). The PLS 

 model was then applied on SORS spectra acquired from rat 

 cadavers after implanting the collagen: hydroxyapatite plugs in 

 drilled skull defects. The PLS model successfully predicting the 

 profile of collagen concentration, but with an increased 

 predictive error of $±$0.30 g/cm3 . These results demonstrate 

 the potential of SORS to quantify collagen concentrations, in 

 the range relevant to those occurring during new bone formation.},

keywords = {bone, connective tissue, regenerative medicine, SORS},

pubstate = {published},

tppubtype = {article}

}