Miniature fluorescence sensor for quantitative detection of brain tumour
<|reference_start|>Miniature fluorescence sensor for quantitative detection of brain tumour: Fluorescence-guided surgery has emerged as a vital tool for tumour resection procedures. As well as intraoperative tumour visualisation, 5-ALA-induced PpIX provides an avenue for quantitative tumour identification based on ratiometric fluorescence measurement. To this end, fluorescence imaging and fibre-based probes have enabled more precise demarcation between the cancerous and healthy tissues. These sensing approaches, which rely on collecting the fluorescence light from the tumour resection site and its remote spectral sensing, introduce challenges associated with optical losses. In this work, we demonstrate the viability of tumour detection at the resection site using a miniature fluorescence measurement system. Unlike the current bulky systems, which necessitate remote measurement, we have adopted a millimetre-sized spectral sensor chip for quantitative fluorescence measurements. A reliable measurement at the resection site requires a stable optical window between the tissue and the optoelectronic system. This is achieved using an antifouling diamond window, which provides stable optical transparency. The system achieved a sensitivity of 92.3% and specificity of 98.3% in detecting a surrogate tumour at a resolution of 1 x 1 mm2. As well as addressing losses associated with collecting and coupling fluorescence light in the current remote sensing approaches, the small size of the system introduced in this work paves the way for its direct integration with the tumour resection tools with the aim of more accurate interoperative tumour identification.<|reference_end|>
@article{ndabakuranye2024miniature,
    title={Miniature fluorescence sensor for quantitative detection of brain tumour},
    author={Jean Pierre Ndabakuranye, James Belcourt, Deepak Sharma, Cathal D.
  O'Connell, Victor Mondal, Sanjay K. Srivastava, Alastair Stacey, Sam Long,
  Bobbi Fleiss, Arman Ahnood},
    journal={Lab on a Chip 24.4 (2024): 946-954},
    year={2024},
    doi={10.1039/D3LC00982C},
    archivePrefix={arXiv},
    eprint={2406.15520},
    primaryClass={eess.SY cs.SY physics.med-ph}
}