The Centre has a long history of developing new techniques for medical imaging (particularly in magnetic resonance imaging), transforming them from a primarily diagnostic modality into an interventional and therapeutic platform. This is facilitated by the Centre's strong engineering background in practical imaging and image analysis platform development, as well as advances in minimal access and robotic assisted surgery. Hamlyn has a strong tradition in pursuing basic sciences and theoretical research, with a clear focus on clinical translation.

In response to the current paradigm shift and clinical demand in bringing cellular and molecular imaging modalities to an in vivo – in situ setting during surgical intervention, our recent research has also been focussed on novel biophotonics platforms that can be used for real-time tissue characterisation, functional assessment, and intraoperative guidance during minimally invasive surgery. This includes, for example, SMART confocal laser endomicroscopy, time-resolved fluorescence spectroscopy and flexible FLIM catheters.


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  • Journal article
    Giannarou S, Hacihaliloglu I, 2020,

    IJCARS - IPCAI 2020 special issue: 11th conference on information processing for computer-assisted interventions - part 1

    , International Journal of Computer Assisted Radiology and Surgery, Vol: 15, Pages: 737-738, ISSN: 1861-6410
  • Journal article
    Kim JA, Wales D, Thompson A, Yang G-Zet al., 2020,

    Fiber-optic SERS probes fabricated using two-photon polymerization for rapid detection of bacteria

    , Advanced Optical Materials, Vol: 8, Pages: 1-12, ISSN: 2195-1071

    This study presents a novel fiber-optic surface-enhanced Raman spectroscopy (SERS) probe (SERS-on-a-tip) fabricated using a simple, two-step protocol based on off-the-shelf components and materials, with a high degree of controllability and repeatability. Two-photon polymerization and subsequent metallization was adopted to fabricate a range of SERS arrays on both planar substrates and end-facets of optical fibers. For the SERS-on-a-tip probes, a limit of detection of 10-7 M (Rhodamine 6G) and analytical enhancement factors of up to 1300 were obtained by optimizing the design, geometry and alignment of the SERS arrays on the tip of the optical fiber. Furthermore, strong repeatability and consistency were achieved for the fabricated SERS arrays, demonstrating that the technique may be suitable for large-scale fabrication procedures in the future. Finally, rapid SERS detection of live Escherichia coli cells was demonstrated using integration times in the milliseconds to seconds range. This result indicates strong potential for in vivo diagnostic use, particularly for detection of infections. Moreover, to the best of our knowledge, this represents the first report of detection of live, unlabeled bacteria using a fiber-optic SERS probe.

  • Journal article
    Li Z, Shahbazi M, Patel N, O' Sullivan E, Zhang H, Vyas K, Chalasani P, Deguet A, Gehlbach PL, Iordachita I, Yang G-Z, Taylor RHet al., 2020,

    Hybrid Robot-assisted Frameworks for Endomicroscopy Scanning in Retinal Surgeries.

    , IEEE Trans Med Robot Bionics, Vol: 2, Pages: 176-187

    High-resolution real-time intraocular imaging of retina at the cellular level is very challenging due to the vulnerable and confined space within the eyeball as well as the limited availability of appropriate modalities. A probe-based confocal laser endomicroscopy (pCLE) system, can be a potential imaging modality for improved diagnosis. The ability to visualize the retina at the cellular level could provide information that may predict surgical outcomes. The adoption of intraocular pCLE scanning is currently limited due to the narrow field of view and the micron-scale range of focus. In the absence of motion compensation, physiological tremors of the surgeons' hand and patient movements also contribute to the deterioration of the image quality. Therefore, an image-based hybrid control strategy is proposed to mitigate the above challenges. The proposed hybrid control strategy enables a shared control of the pCLE probe between surgeons and robots to scan the retina precisely, with the absence of hand tremors and with the advantages of an image-based auto-focus algorithm that optimizes the quality of pCLE images. The hybrid control strategy is deployed on two frameworks - cooperative and teleoperated. Better image quality, smoother motion, and reduced workload are all achieved in a statistically significant manner with the hybrid control frameworks.

  • Journal article
    Cartucho J, Shapira D, Ashrafian H, Giannarou Set al., 2020,

    Multimodal mixed reality visualisation for intraoperative surgical guidance

    , International Journal of Computer Assisted Radiology and Surgery, Vol: 15, Pages: 819-826, ISSN: 1861-6410

    PurposeIn the last decade, there has been a great effort to bring mixed reality (MR) into the operating room to assist surgeons intraoperatively. However, progress towards this goal is still at an early stage. The aim of this paper is to propose a MR visualisation platform which projects multiple imaging modalities to assist intraoperative surgical guidance.MethodologyIn this work, a MR visualisation platform has been developed for the Microsoft HoloLens. The platform contains three visualisation components, namely a 3D organ model, volumetric data, and tissue morphology captured with intraoperative imaging modalities. Furthermore, a set of novel interactive functionalities have been designed including scrolling through volumetric data and adjustment of the virtual objects’ transparency. A pilot user study has been conducted to evaluate the usability of the proposed platform in the operating room. The participants were allowed to interact with the visualisation components and test the different functionalities. Each surgeon answered a questionnaire on the usability of the platform and provided their feedback and suggestions.ResultsThe analysis of the surgeons’ scores showed that the 3D model is the most popular MR visualisation component and neurosurgery is the most relevant speciality for this platform. The majority of the surgeons found the proposed visualisation platform intuitive and would use it in their operating rooms for intraoperative surgical guidance. Our platform has several promising potential clinical applications, including vascular neurosurgery.ConclusionThe presented pilot study verified the potential of the proposed visualisation platform and its usability in the operating room. Our future work will focus on enhancing the platform by incorporating the surgeons’ suggestions and conducting extensive evaluation on a large group of surgeons.

  • Journal article
    Clancy NT, Jones G, Maier-Hein L, Elson DS, Stoyanov Det al., 2020,

    Surgical spectral imaging.

    , Medical Image Analysis, Vol: 63, Pages: 1-18, ISSN: 1361-8415

    Recent technological developments have resulted in the availability of miniaturised spectral imaging sensors capable of operating in the multi- (MSI) and hyperspectral imaging (HSI) regimes. Simultaneous advances in image-processing techniques and artificial intelligence (AI), especially in machine learning and deep learning, have made these data-rich modalities highly attractive as a means of extracting biological information non-destructively. Surgery in particular is poised to benefit from this, as spectrally-resolved tissue optical properties can offer enhanced contrast as well as diagnostic and guidance information during interventions. This is particularly relevant for procedures where inherent contrast is low under standard white light visualisation. This review summarises recent work in surgical spectral imaging (SSI) techniques, taken from Pubmed, Google Scholar and arXiv searches spanning the period 2013-2019. New hardware, optimised for use in both open and minimally-invasive surgery (MIS), is described, and recent commercial activity is summarised. Computational approaches to extract spectral information from conventional colour images are reviewed, as tip-mounted cameras become more commonplace in MIS. Model-based and machine learning methods of data analysis are discussed in addition to simulation, phantom and clinical validation experiments. A wide variety of surgical pilot studies are reported but it is apparent that further work is needed to quantify the clinical value of MSI/HSI. The current trend toward data-driven analysis emphasises the importance of widely-available, standardised spectral imaging datasets, which will aid understanding of variability across organs and patients, and drive clinical translation.

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