Assessment of Microvascular Function Using Near-Infrared Spectroscopic 2D Imaging of Whole Hand Combined with Vascular Occlusion Test

Spatial-Temporal Oxygenation Mapping Using a Near-Infrared Optical Scanner: Towards Peripheral Vascular Imaging

Near-infrared spectroscopy (NIRS)-based peripheral perfusion, or microcirculation, can be used to assess the severity of peripheral vascular dysfunction. A low-cost, portable non-contact near-infrared optical scanner (NIROS) was developed for spatio-temporal mapping of tissue oxygenation and perfusion in tissues. In vivo validation studies were carried out on control subjects (n = 3) to assess the ability of NIROS to measure real-time oxygenation changes in response to an occlusion paradigm on the dorsum of the hand. NIROS captured real-time tissue oxygenation changes with 95% correlation when compared to a commercial device. A feasibility peripheral imaging study was performed in a mouse model (n = 5) of chronic kidney disease (CKD) induced vascular calcification to assess differences in microcirculatory peripheral tissue oxygenation. The tissue oxygenation (in terms of oxy-, deoxy-, and total hemoglobin changes) due to the occlusion paradigm was distinctly different prior to (week-6) and after the onset of vascular calcification (week-12) in the murine tails. Future work will involve extensive studies to correlate these microcirculatory tissue oxygenation changes in the peripheral tail to the vascular calcification in the heart.

The Core of Medical Imaging: State of the Art and Perspectives on the Detectors

In this review, the roles of detectors in various medical imaging techniques were described. Ultrasound, optical (near-infrared spectroscopy and optical coherence tomography) and thermal imaging, magnetic resonance imaging, computed tomography, single-photon emission tomography, positron emission tomography were the imaging modalities considered. For each methodology, the state of the art of detectors mainly used in the systems was described, emphasizing new technologies applied.

Surgical spectral imaging

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.