Use of Hyperspectral/Multispectral Imaging in Gastroenterology. Shedding Some⁻Different⁻Light into the Dark

Abstract

Hyperspectral/Multispectral imaging (HSI/MSI) technologies are able to sample from tens to hundreds of spectral channels within the electromagnetic spectrum, exceeding the capabilities of human vision. These spectral techniques are based on the principle that every material has a different response (reflection and absorption) to different wavelengths. Thereby, this technology facilitates the discrimination between different materials. HSI has demonstrated good discrimination capabilities for materials in fields, for instance, remote sensing, pollution monitoring, field surveillance, food quality, agriculture, astronomy, geological mapping, and currently, also in medicine. HSI technology allows tissue observation beyond the limitations of the human eye. Moreover, many researchers are using HSI as a new diagnosis tool to analyze optical properties of tissue. Recently, HSI has shown good performance in identifying human diseases in a non-invasive manner. In this paper, we show the potential use of these technologies in the medical domain, with emphasis in the current advances in gastroenterology. The main aim of this review is to provide an overview of contemporary concepts regarding HSI technology together with state-of-art systems and applications in gastroenterology. Finally, we discuss the current limitations and upcoming trends of HSI in gastroenterology.

Keywords: biomedical optical imaging; clinical diagnosis; gastroenterology; hyperspectral imaging; medical diagnostic imaging; multispectral imaging.

Figure 1

Example of an HS cube from in-vivo human brain surface and spectrum from the pixel in red (left). Several images at different wavelengths obtained from the HS datacube (right).

Figure 2

Spectral signatures of different brain tumor tissues in the VNIR (Visible and Near Infrared) range [10]. The abscissa axis represents the different wavelengths, and the ordinate axis represents the normalized reflectance. The continuous red line corresponds to Glioblastoma (GBM); the dashed blue line corresponds to Oligodendroglioma grade III; the dashed black, green and cyan lines correspond to a metastatic lung, renal and breast tumors, respectively.

Figure 3

HS acquisition system used in medical applications. (A,B) HSI acquisition systems based on push-broom cameras for in-vivo human brain tumor detection [40] and in-vivo pig abdominal surgery [20]; (C) Liquid crystal tunable filter camera attached to an endoscope for cancerous tissue detection [43]; (D) Microscope coupled to an HSI push-broom camera for pathological slides registration [36].

Figure 4

Taxonomy of the current gastrointestinal HSI applications.

Figure 5

Use of HSI for organs identification in pig’s abdominal surgery performed in [61]. (A) RGB image from pig’s abdominal cavity and organs; (B) Segmentation map obtained after HS image processing and analysis, where the different organs are identified using different colors.

Figure 6

Mean spectra per tissue type acquired during colorectal surgery in [62]. Average tissue spectra for ureter (green), mesenteric adipose tissue (dark blue), artery (red), colon (light blue), muscle (black), and vein (purple).

Figure 7

HSI application in Bowel anastomosis. (A) Small bowel oxygenation estimation shown in [68]; (B) Suture map and recommendations about the location of the suture provided in [69].

Figure 8

Spectral differences between normal and cancerous tissue for two specimen pairs: S4 and S5 presented in [83]. Preliminary data demonstrate the differences in spectral signature between cancerous and normal tissue. Transmission and absorbance spectral data indicate that adenocarcinoma displays increased optical absorbance, as compared to surrounding normal tissue, with additional spectral differences that could be exploited to increase sensitivity and specificity for tumor detection. Spectral scan types are as follows: (A) Fluorescence excitation scan from 390 to 450 nm; (B) Fluorescence excitation scan from 390 to 480 nm; (C) Fluorescence excitation scan from 390 to 550 nm; (D) Transmission scan from 390 to 700 nm; (E) Absorbance scan from 390 to 700 nm.

Figure 9

Samples of HS normal and abnormal colonic tissue images and the results obtained after applying the pre-processing sonification presented in [87]. (A) Sample specimen showing normal colonic tissue in gray-scale image; (B) Final three-dimension image that gives the probabilities that the point in the specimen belongs to normal colon tissue; (C) Sample specimen showing abnormal colonic tissue in gray-scale image; (D) Final three-dimension image that gives the probabilities that the point in the specimen belongs to abnormal colon tissue.