Abstract
Conventional imaging modalities like CT, MRI, and x-ray have become indispensable for medical diagnosis, but continual innovation is required to overcome their limitations in terms of resolution, radiation exposure, and cost. As a leader in automated image analysis, speedier diagnosis, and personalized treatment through the analysis of large datasets and the discovery of hitherto invisible patterns, AI is simply amazing. Other than AI, new imaging modalities like dark-field radiography and photoacoustic imaging (PAI) provide distinct perspectives. Aside from that, visualization tools made possible by 3D printing and virtual reality (VR) are revolutionizing medical imaging. This chapter investigates few Advanced Imaging techniques like photoacoustic imaging, radiomics, photon counting – CT, and dark-field radiography. This review explores these developments' underlying theories, areas of current research interest, and possible uses, emphasizing how they could transform medical imaging in the direction of increased accuracy, earlier diagnosis, and better patient outcomes.
Top1. Introduction
Healthcare has undergone a revolution thanks to medical imaging, which has transformed disease diagnosis and treatment. Conventional methods such as computed tomography (CT) scans, magnetic resonance imaging (MRI), and X-rays have evolved into essential instruments for medical professionals. These techniques give us unique insights into the human body, making it possible to see within structures, spot anomalies, and track how well a treatment is working.
When Wilhelm Röntgen discovered X-rays in 1895, it was a revolutionary development in medical diagnosis. A rudimentary visualisation of bones and thick tissues can be obtained using these easily accessible and reasonably priced photos (X-ray, 2024). X-rays are limited in their ability to diagnose certain illnesses due to their lack of soft tissue distinction.
With the advent of CT scans in the 1970s, medical imaging underwent a revolutionary change as they offered detailed cross-sectional pictures of the body. Advanced computer techniques and X-rays are used in CT to recreate intricate images of blood arteries, soft tissues, and bones (CT scan - Mayo Clinic, 2022). Despite its versatility, CT scans expose users to ionising radiation, which raises questions regarding possible health dangers, especially when repeated exams are involved (Brenner & Hall, 2007).
Since their invention in the 1980s, magnetic resonance imaging (MRI) has produced detailed images of the brain, soft tissues, and organs by using radio waves and strong magnetic fields. Because they provide such a good soft tissue contrast, magnetic resonance imaging (MRI) is a powerful diagnostic tool for musculoskeletal injuries, tumours, and neurological problems (Magnetic Resonance Imaging, 2024). But MRIs are costly, can make some patients feel claustrophobic, and are not appropriate for people who have certain medical implants.
Despite their immense contribution, traditional imaging techniques have various limitations which includes:
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Ionizing radiation: Ionising radiation is used in CT and X-ray scans, and frequent exposure to it can harm healthy tissues. Patients who need regular scans and children should be especially concerned about this (Brenner & Hall, 2007).
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Limited contrast: Traditional methods can provide excellent anatomic information, but they might have trouble telling between specific tissues with similar densities. Because of this, it may be difficult to find minor anomalies, especially in soft tissues (Brenner & Hall, 2007).
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Cost and accessibility: Certain patients may not have access to advanced imaging modalities such as CT and MRI scans because they can be costly and unavailable in certain healthcare settings.
Now, these drawbacks emphasise the necessity of cutting-edge medical imaging technologies. There are now tremendous opportunities to overcome these obstacles and further revolutionise healthcare thanks to recent advancements:
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Artificial Intelligence (AI): Algorithms for machine learning are transforming picture analysis and enabling quicker and more precise diagnosis. AI can analyse enormous medical imaging databases, spotting minute patterns that are imperceptible to the human sight, and maybe enhancing risk assessment and illness diagnosis (Yu et al., 2018).
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Advanced Imaging Techniques: Emerging methods include dark-field radiography and photoacoustic imaging (PAI). PAI uses sound and light waves to visualise tissue function and blood flow, while dark-field radiography is more sensitive in identifying abnormalities in the lungs (Guo et al., 2024; Anil et al., 2024).
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3D Printing and Virtual Reality (VR): Surgical techniques and planning are being revolutionised by this technology. While virtual reality (VR) enables immersive visualisation of medical data, potentially enhancing surgical precision, 3D-printed models based on medical pictures give surgeons a tactile depiction of the anatomy (Abdullah & Reed, 2018; McKnight et al., 2020).
Key Terms in this Chapter
Photon Counting CT: Also abbreviated as PC-CT. It is a type of CT that uses a photon-counting detector (PCD) to register individual photon interactions to identify X-rays.
CT: CT stands for Computed Tomography. It is also called as CT scan. It is a medical imaging technique that creates images of the interior of the body by combining computer technology and X-rays.
Dark-Field Radiography: It's a kind of X-ray method similar to dark-field CT that creates X-ray images using ultra small angle X-ray scattering.
Advanced Imaging: In order to visualise the body's internal organs and structures, advanced imaging entails one or more specialised diagnostic tests.
MRI: MRI stands for Magnetic Resonance Imaging. The human body's internal structures that include the organs, bones, muscles, and blood arteries, can be seen in detail on an MRI.
Photoacoustic Imaging: It is also abbreviated as PAI. Using a pulsed laser to irradiate a substance, PAI is a simple medical imaging method that reconstructs the image of the tissue's distribution of light energy absorption.
Radiomics: Using data-characterisation algorithms, radiomics is a technique that extracts a lot of characteristics from medical images.
X-Ray: X-rays are a type of electromagnetic radiation. They can pass through different objects as well as our body which results in the generation of images of the inside of our body.