Spectroscopic detection of traumatic brain injury severity and biochemistry from the retina

Abstract

Traumatic brain injury (TBI) is a major burden on healthcare services worldwide, where scientific and clinical innovation is needed to provide better understanding of biochemical damage to improve both pre-hospital assessment and intensive care monitoring. Here, we present an unconventional concept of using Raman spectroscopy to measure the biochemical response to the retina in an ex-vivo murine model of TBI. Through comparison to spectra from the brain and retina following injury, we elicit subtle spectral changes through the use of multivariate analysis, linked to a decrease in cardiolipin and indicating metabolic disruption. The ability to classify injury severity via spectra of the retina is demonstrated for severe TBI (82.0 %), moderate TBI (75.1 %) and sham groups (69.4 %). By showing that optical spectroscopy can be used to explore the eye as the window to the brain, we lay the groundwork for further exploitation of Raman spectroscopy for indirect, non-invasive assessment of brain chemistry.

Development and Characterization of a Probe Device toward Intracranial Spectroscopy of Traumatic Brain Injury

“…(b) Representative spectra from TBI (red) compared to the healthy controls (black) in murine brain tissue (785 nm, 20 mW, 3–5 s) with specific bands highlighted at 1266, 1447, and 1660 cm –1 and (c) changes to relative lipid composition as a result of severe (sTBI), moderate (mTBI) vs control. 39 The boxplots show the non-negative least squares regression coefficient fitted to the average spectrum collected from each sample ( p < 0.05). (d).…”

“…These weights are associated with each group at 1003, 1266, 1337, 1447, and 1660 cm –1 representing, skeletal C–H of phenylalanine, C–C bending of mixed proteins/lipids, C–N stretching, N–H bending of the amide III, C–H 2 bending, and C=C stretching of the proteins and lipids, in correspondence with the Figures S4–S6 and the literature. 33 , 39 , 42 , 56 − 59 …”

“…Unlike the previous study, attribution to the underlying biochemistry was made with reference to Raman spectra of brain specific lipids to make qualitative attribution to a relative increase in cholesterol with injury. Recently, Raman spectroscopy combined with advanced machine learning was applied to investigate whether the retina can reflect the brain microenvironment after TBI, 39 in a clinically relevant murine model, showing that spectra from the eye can distinguish moderate TBI and severe TBI from a sham group, and show this to be as a result of similar chemical changes to those seen at the point of injury on the brain with the detected changes identified being largely due to metabolic distress and the release of cardiolipin, consistent with the use of mass spectrometry as a diagnostic modality for TBI. 35 While mass spectrometry can provide superior molecular discrimination, Raman spectroscopy has the advantage of being both a portable and nondestructive technique with many ongoing efforts in the field for translation into in vivo measurements and diagnostics.…”

“…Recently, we developed a machine learning technique based on the self-optimizing Kohonen index network (SKiNET) for simultaneously providing rich information and classification from complex biological matrices, even with noisy or poor-quality spectra with very subtle differences that would result from a low laser power and short acquisition times required in intraoperative or diagnostic applications of Raman spectroscopy. 39 …”

Identifying diabetes from conjunctival images using a novel hierarchical multi-task network

“…Because of its high learning ability and computing ability, deep learning can even extract hidden information that doctors cannot perceive from the data. For ophthalmic image analysis, deep learning can detect several systemic diseases through eye images, such as anemia 1 , cardiovascular disease 2 , hepatobiliary disease 3 , traumatic brain injury 4 etc. This is because the visual blood vessels and nerves in the eyes are closely related to the health of the whole body.…”