Hyperspectral imaging (HSI) enables visualisation of morphological and biochemical information, which could improve disease diagnostic accuracy. Unfortunately, the wide range of image distortions that arise during flexible endoscopy in the clinic have made integration of HSI challenging. To address this challenge, we demonstrate a hyperspectral endoscope (HySE) that simultaneously records intrinsically co-registered hyperspectral and standard-of-care white light images, which allows image distortions to be compensated computationally and an accurate hyperspectral data cube to be reconstructed as the endoscope moves in the lumen. Evaluation of HySE performance shows excellent spatial, spectral and temporal resolution and high colour fidelity. Application of HySE enables: quantification of blood oxygenation levels in tissue mimicking phantoms; differentiation of spectral profiles from normal and pathological ex vivo human tissues; and recording of hyperspectral data under freehand motion within an intact ex vivo pig oesophagus model. HySE therefore shows potential for enabling HSI in clinical endoscopy.

Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett's oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical imaging-technologies. Optical-imaging biomarkers (OIBs), which rely on the interactions of tissue and non-ionizing optical radiation (with typical wavelengths in the range of 400-1,000 nm), can be used for the non-invasive detection and characterization of disease states. OIBs enable the real-time analysis of tissue biochemistry and the use of compact point-of-care and low-cost imaging devices (when compared to radiological imaging), and can operate across ranges of resolutions and depths spanning over four orders of magnitude 1. Across the visible and near-infrared spectrum, light undergoes a range of complex interactions with tissue (Fig. 1). Conventional photographic methods that aim at replicating human vision 2 discard most of the information obtained from these interactions and only capture reflected light across three channels (red, green and blue). Over the past decade, a wide range of promising OIBs that extract in-depth information provided by the different light-tissue interactions have emerged. However, for any new imaging biomarker to be deployed in a clinical setting, detailed validation is required. Technical validation defines the precision and accuracy with which the biomarker can be measured, whereas biological validation establishes the association between the biomarker and the underlying physiological, anatomical or pathological process. Clinical validation can then establish whether the biomarker does indeed identify, measure or predict the clinical outcome of interest. To achieve clinical validation, the imaging device needs to conform to clinical performance and safety specifications, and be approved for use in patients. With standard radiological imaging-such as computed tomography (CT) or magnetic resonance imaging (MRI)-the imaging device required to measure a novel imaging biomarker is already clinically approved for use in humans and widely available across radiology departments 3. In contrast, for OIBs it is uncommon that a clinically approved imaging device (alongside its associated specialist data-acquisition and data-interpretation methods) is available for clinical validation. Therefore, biological validation may be restricted to testing ex vivo samples such as histopathological sections. Compared to the in vivo setting, these can be prone to bias, and generate a different range of optic...

Background and study aims  Endoscopic surveillance for Barrett’s esophagus (BE) is limited by long procedure times and sampling error. Near-infrared (NIR) fluorescence imaging minimizes tissue autofluorescence and optical scattering. We assessed the feasibility of a topically applied NIR dye-labeled lectin for the detection of early neoplasia in BE in an ex vivo setting. Methods  Consecutive patients undergoing endoscopic mucosal resection (EMR) for BE-related early neoplasia were recruited. Freshly collected EMR specimens were sprayed at the bedside with fluorescent lectin and then imaged. Punch biopsies were collected from each EMR under NIR light guidance. We compared the fluorescence intensity from dysplastic and nondysplastic areas within EMRs and from punch biopsies with different histological grades. Results  29 EMR specimens were included from 17 patients. A significantly lower fluorescence was found for dysplastic regions across whole EMR specimens ( P  < 0.001). We found a 41 % reduction in the fluorescence of dysplastic compared to nondysplastic punch biopsies ( P  < 0.001), with a sensitivity and specificity for dysplasia detection of 80 % and 82.9 %, respectively. Conclusion  Lectin-based NIR imaging can differentiate dysplastic from nondysplastic Barrett’s mucosa ex vivo.