Abstract
Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation. However, whilst the methodology is simple and does not require extensive sample preparation, the throughput of such an approach is limited. Here we describe the development of instrumentation for the analysis of serum that is able to differentiate cancer and control patients at a sensitivity and specificity of 93.2% and 92.8%. Furthermore, preliminary data from the first prospective clinical validation study of its kind are presented, demonstrating how this innovative technology can triage patients and allow rapid access to imaging.
Highlights
IntroductionQUALITY TEST (13) Nine spectra per patient generated PATIENT DATASET Labelled sticker Si IRE
SPECTRUMQUALITY TEST (13) Nine spectra per patient generated PATIENT DATASET Labelled sticker Si IREPlastic IRE holderStacked absorbance Diamond2500 WavenumberRetrospective patient cohort
We develop disposable Si IRE sample slides that allow the rapid preparation and analysis of multiple samples, enabling high-throughput attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy optimised for clinical research (Fig. 2)
Summary
QUALITY TEST (13) Nine spectra per patient generated PATIENT DATASET Labelled sticker Si IRE. A 724 retrospective patient cohort was investigated to assess the diagnostic performance of Si IRE based ATR-FTIR spectroscopy. This cohort contains a range of primary and secondary brain cancers as well as control (noncancer) patients (Table 1). Glioblastoma multiforme (GBM) is the largest primary cancer group in this study, reflecting the higher incidence of this tumour class. Where possible patients have been age and sex matched between both disease groups, whilst taking into account the natural disease prevalence (Table 2)[32].
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