Medical Imaging The Light that Listens to Health and Disease

Images can tell fascinating stories. Vasilis Ntziachristos aims to channel this fascination into devices that use light with tangible benefits for mankind. Holding positions as Head of the Bioengineering Center and Director of the Institute of Biological and Medical Imaging at Helmholtz Munich, as well as Professor and Director of the Chair of Biological Imaging at the Technical University of Munich, he stands as a pioneering figure in the imaging field. Additionally, he holds a track record as a serial entrepreneur, having successfully launched numerous spin-offs specializing in fluorescence and optoacoustic imaging for biomedical applications. Among his achievements is the development of Raster Scan Optoacoustic Mesoscopy (RSOM), a ground-breaking technology enabling highly detailed visualization of biological structures and functions within and beneath the skin. These images, aside from their aesthetic appeal, hold profound significance in unravelling the intricacies of disease development.

Although still in its early stages, RSOM technology has demonstrated considerable potential in utilizing the skin as a gateway to observe disease progression, not only within dermatology but also in the realms of diabetes and cardiovascular disorders. Traditional microscopy techniques cannot penetrate deep into human skin to provide such insights. Similarly, radiological approaches like ultrasonography, X-ray imaging, or MRI (magnetic resonance imaging) fall short in visualizing biological functions with the level of detail and contrast afforded by RSOM. By harnessing light and sound, RSOM not only proves to be cost-effective but also holds the promise of miniaturization, allowing for placement not only within hospital settings but also within households. This advancement aims to broaden the accessibility and affordability of medical care by decentralizing it from hospitals and specialized facilities to individuals' homes.

“The underlying concept of RSOM is quite simple: The skin produces ultrasound in response to exposure to low-energy light pulses,” explains Ntziachristos. This phenomenon is why the term ‘optoacoustics’ is employed, where ‘optical’ pertains to light illumination and ‘acoustic’ refers to the production and detection of sound. When light pulses reach a specific area of the body, they induce a slight warming, typically much less than one degree Celsius, causing a temporary expansion and subsequent contraction. This fluctuation generates sound waves, primarily within the ultrasound frequency range, imperceptible to the human ear. These waves propagate from within the skin to its surface, where they are captured by ultrasound transducers. Subsequent processing of these sound waves enables the creation of highly detailed, three-dimensional representations of the area imaged. This breakthrough technology, further empowered by advanced computational methods including Artificial Intelligence (AI), aims to impart new abilities in prevention and precision medicine.

Throughout the history of medicine, physicians have relied on surface features of the skin to gain insights into various diseases. Alterations in skin color or appearance often signify underlying conditions, whether localized to the skin or indicative of systemic issues. However, the human eye's capabilities are limited to superficial observation, lacking the ability to penetrate beneath the skin's surface and accurately assess what lies beneath. Similarly, conventional optical tools such as cameras and microscopes are confined to shallow depths of penetration.

RSOM, however, revolutionizes this paradigm by facilitating highly detailed visualization deep within the layers of the skin. This innovative technology provides accurate depictions of various pathophysiological parameters, including intricate details of microvascular structure and function, as well as measurements of oxygenation and lipid content. These insights, obtained through RSOM, surpass the limitations of visual skin inspection, offering a more precise understanding of disease development and progression.

Apart from morphological changes, one pivotal advantage of optoacoustic imaging over conventional radiological methods lies in its capability to conduct measurements across different colors. Color perception has long been fundamental to our comprehension of the world, aiding in the differentiation of natural structures, such as identifying ripe red fruits amidst green foliage or assessing the quality of food and water based on appearance. Optoacoustic measurements encompass an extensive spectrum of colors, far beyond the range visible to the human eye. As various molecules exhibit distinct color absorption properties, employing illumination across different colors enables the technique to discover information about specific molecules.

While the selection of color significantly influences the achieved penetration depth, ongoing research by the Ntziachristos team focuses on real-time visualization of metabolic processes, leveraging direct contrast from essential molecules like proteins and sugars. A novel microscopy method, termed MiROM (mid-infrared optoacoustic microscopy), has recently emerged, undergoing testing on cells and tissues to visualize molecular presence without necessitating contrast agents, albeit at shallower depths compared to RSOM. Beyond its use for biomedical research, emerging evidence suggests that this technique holds promise in enhancing early disease diagnostics.

Advancing the clinical applicability of optoacoustic imaging is of upmost importance. As the result of a collaboration of Vasilis Ntziachristos with Dominik Jüstel at the Computational Health Department their teams have achieved a significant milestone with their deep-learning framework, DeepMB. Focused on multispectral optoacoustic tomography (MSOT), they've devised a method to generate high-quality images at extraordinary speeds, surpassing previous algorithms by about a thousandfold. This remarkable benefit is credited to an inventive training approach that synthesizes optoacoustic signals from real-world images, enabling DeepMB to overcome the challenge of generalization and accurately reconstruct scans from any patient, regardless of the targeted body part or underlying condition. This breakthrough holds the potential to transform MSOT imaging, fostering improved clinical studies and patient care.

Notable advancements have been achieved by Vasilis Ntziachristos and his team in the realm of diabetes management, exemplified by their work in non-invasive glucose monitoring using optoacoustic technology. By harnessing specific light pulses to stimulate glucose and capture resulting ultrasound signals within the skin, they've pioneered a needle-free method for measuring blood glucose levels. This breakthrough holds transformative potential for the future of diabetes care, offering a more comfortable and convenient alternative to traditional methods. Transitioning from successful laboratory testing, the next crucial phase involves conducting clinical studies to validate its efficacy.

Furthermore, the Ntziachristos team applied RSOM integrated with artificial intelligence (AI) to investigate diabetes-related skin changes. The researchers captured high-resolution images of skin microstructures in both diabetic and non-diabetic individuals. AI algorithms were then employed to analyze these images, detecting subtle alterations indicative of diabetes, such as changes in blood vessel density and skin thickness. In this way, the stage and progression of diabetes can be monitored from taking quick, non-invasive images of the skin. This fusion of advanced imaging technology and machine learning holds substantial potential for transforming diabetes diagnosis and monitoring, potentially leading to earlier interventions and better patient outcomes, thereby addressing the increasing global burden of diabetes.

Latest update: June 2024.