How Contemporary Technologies are Reshaping Medical Imaging
healthcaretechoutlook

How Contemporary Technologies are Reshaping Medical Imaging

Healthcare Tech Outlook | Thursday, July 21, 2022

The technology development in artificial intelligence (AI) leads to advancements in CT and MR imaging for the welfare of picture quality and diagnostic efficiency.

FORMAT, CA: The use of most recent technological developments has been in radiology, which uses imaging modalities and techniques to picture the human body for diagnostic and therapeutic purposes. A recent evolution using artificial intelligence-based software has added to the advancements in CT and MR imaging technologies, broadening the possibilities for picture quality and diagnostic effectiveness.

1. Breaching the technical limits of CT imaging

The first photon-counting CT (PCCT) scanner in the world received clinical certification from the European and FDA in 2021. By drastically enhancing resolution while lowering radiation exposure, this technology exceeds the existing technical limitations of traditional CT. Although this technique has been in development for more than 15 years, a recent review emphasises its potential to significantly enhance clinical CTs.

From the number of counts in each energy bin, energy-selective pictures are produced. These photos are used to create material-selective images using a data-processing technique called material decomposition.

The trade-off between ionising radiation dose and image quality is just one of the restrictions on the capabilities of current CT equipment. Reduced dose worsens the already limited ability of CT to accurately distinguish between healthy and pathologic tissues by increasing artefacts like image noise and distortions. The problems of tissue distinction and ambiguous x-ray attenuation values are addressed by contrast agents and dual-energy CT scanners, however existing energy-integrating detectors (EIDs) can only assess the total deposited energy of x-rays, limiting spatial resolution. Photon-counting detectors (PCDs), on the other hand, can directly convert a single photon into an electrical signal, greatly enhancing spatial resolution and minimising image artefacts. The use of K-edge imaging (step-change attenuation of x-ray energy for high atomic number elements) also considerably enhances the accuracy of contrast agent concentration and may permit simultaneous quantification of numerous contrast agents. In the upcoming years, these technological advancements will lead to better clinical outcomes.

 2. Growing impact of artificial intelligence

The area of (neuro)radiology is constantly being impacted by artificial intelligence (AI) at an exponential rate. Radiologists can now diagnose patients more quickly and accurately where drastic changes in clinical decision support and workflow optimization are made possible as this technology matures and is more widely used.

AI, and more specifically deep learning (DL), can be used flexibly for a variety of imaging modalities, including MRI, functional MRI, CT, PET, and US, as well as neurological diseases, including Alzheimer's disease, vascular injuries, fetal brain development, and cerebral neoplasms.

MRI applications were the main focus of AI utility, using DL algorithms for image classification (e.g., of major intracranial tumour types 9), segmentation (e.g., of anatomical structures of the inner ear 10), generation (e.g., of MPRAGE images from mGRE images 11), detection (e.g., of neuroanatomical changes in people with autism spectrum disorder 12), reconstruction (e.g., of high-resolution MRI from under-samp (i.e. of brain age14). This wide range of uses illustrates the extraordinary variability of AI applications in (neuro)radiology and other imaging modalities.

3. Bed-side imaging for improved diagnosis

For the diagnosis and progression tracking of seriously ill viral patients, the COVID-19 pandemic continues to call for effective and precise imaging methods. For a large portion of the pandemic, CT was hailed as the front-line imaging modality of choice, but point-of-care ultrasonography (PoCUS) has recently grown in popularity, ushering in the development of smaller, more affordable ultrasound machines that are capable of accurate and timely diagnosis and monitoring. Before COVID-19, PoCUS had already attracted a substantial amount of interest, but a recent review outlines the technology's key developments, improvements in clinical applications, and greater utility in primary imaging specialities.

A new era of innovative, cost-effective technologies is being done in current research, whether it be through the clinical application of innovations like photon-counting CT machines or the exciting advancements of tools like PoCUS. Both of these advancements are complemented by the incredible potential of artificial intelligence.

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