There is a contrast enhanced CT shortage and AI could solve it
Contrast CT, or contrast enhanced computed tomography (CECT), is a form of X-ray computed tomography using radiocontrast (substance that is injected into the body to allow the visualization of special structures such as blood vessels). Radiocontrast for CT is made generally from iodine-based compounds. This is important for highlighting features that are too difficult to distinguish from their surroundings normally. Using contrast material can also help to obtain functional information about tissues and different organ systems.
Images are frequently obtained in a double format (with and without radiocontrast). The scans are named pre-contrast or native-phase images before any radiocontrast has been administrated and postcontrast after contrast administration.
The power of contrast
The substance may be taken as liquid that is drinkable or administered intravenously (IV). The contrast is injected into the body by an intravenous cannula, a little plastic tube that is inserted into a vein in the arm by a nurse or radiographer who is experienced with the technique. This could cause minor discomfort, similarly to drawing blood from the arm. The amount of IV contrast required varies, based on the body size and the type of CT scan desired, but it is normally in the range of 30–120 ml.
The use of IV contrast increases the examination’s accuracy and aids in the exclusion of several life-threatening illnesses, including malignancy. IV contrast is mostly utilized to show distinctions in soft tissues that would otherwise appear to be indistinguishable.
CT with an IV contrast agent is recommended for vascular disease analysis to determine the vascular wall (e.g., aneurysm, dissection, or tumor invasion). One of the most common causes of acute cardiovascular illness is pulmonary embolism. Because of its accuracy, chest CT angiography is the best approach to evaluate for thromboembolism. It can also assess alternate diseases in cases with nonspecific chest pain.
The flow of goods and services
We now live in a time where resources have become a source of conflict between nations. Shortages of medical supplies, industrial, and consumer goods caused by the COVID-19 pandemic quickly became a major issue around the world. In most countries, there is a shortages of personal protective equipment such as medical masks and gloves, face shields, and sanitizing products, as well as hospital beds, ICU beds, oxygen treatment equipment, ventilators, and ECMO devices.
The chaotic incidents of the last several years have called into question the benefits of reducing inventory, while reigniting fears that certain sectors have gone too far and are now susceptible to problems. Many economies throughout the globe have been plagued by shortages of a wide range of goods as the epidemic has slowed industry operations and wreaked havoc on global transportation.
According to some analysts, the crisis is changing the way businesses function. It is pushing some of them to stash more goods and form additional supplier ties as a precautionary measure in the detriment of other businesses.
The hospital system is seeing supply problems that exceed those seen during the initial days of the Covid-19 outbreak, when masks and gowns, among other items, were practically impossible to come by. Deficiencies may have been more pressing back then, but today’s issues involve a much broader range of equipment. Material shortages, understaffed ports, transportation difficulties, and lockdowns in the industry are serious problems, even if the aim is to stop the spread of Covid-19.
Much of the attention on the supply-chain crisis is focused on automakers and electronics companies dealing with factory closures in manufacturing hubs such as those of the past months in Shenzhen and Shanghai but the effects of hard-to-find medical devices and supplies are more severe and impact doctors’s offices and operating rooms in every hospital.
The analysis suddenly became unclear
The shortage of iodinated contrast poses a challenge to radiologists and endangers the diagnosis of life-threatening illnesses. The shortage of Iohexol iodinated contrast media (ICM) traces its origins to the recent COVID-19-related shutdown of a factory in Shanghai. In an April 19 letter to consumers, GE Healthcare announced it would be limiting its orders and deliveries. The factory has since been reopened, but GE expects an 80% reduction in supplies through the end of June and the months forward.
Concern is running so high that the American Hospital Association asked GE in a letter to prioritize distribution to hospitals treating the most urgent patients.
If we look at the past several decades, geopolitical trade wars, shipping delays, plant closings, raw materials shortages, earthquakes and tsunamis have all exposed supply chain vulnerabilities and sent ripples throughout regional and global manufacturing.
Expanding globalization was the dominant economic model of the late twentieth century. It remains to be seen how and whether the current crisis has shifted these patterns. For now it has definitely exposed the reality that many production chains are designed for profit maximization and efficiency rather than stability.
While low-dose and no-dose imaging techniques and modalities exist, a compromise often must be made between patient exposure, clinical utility and cost. This type of computed tomography tends to produce lower image quality than normal dose computed tomography (CT) although it can help to reduce radiation hazards and helps substance shortages.
AI empowers organizations to effectively integrate their data
Artificial intelligence (AI) is revolutionizing nearly every aspect of modern life, including medical imaging.
Machine learning can quickly process large amount of medical imaging data and identify complex interactions and associations from high dimensional planning, to enable early and accurate disease diagnosis.
Automation has the potential to significantly reduce patient radiation dose in computed tomography (CT) by optimizing data acquisition operations, such as patient placement and parameter settings. With advanced reconstruction algorithms and image denoising methods this could enable the use of lower radiation dosage for the scans.
Various AI empowered solutions towards low-dose CT image reconstruction have been developed, such as Adaptive Statistical Iterative Reconstruction (ASIR) and Novel Model Based Iterative Reconstruction Algorithms (MBIR). Iterative reconstruction refers to an image reconstruction algorithm that begins with an image assumption, and compares it to the real time measured values while making constant adjustments until the two are in agreement.
Besides this, in processing data, AI can predict future demand, improve automation and increase transportation efficiency, giving supply chain managers deeper insight and control over every aspect of the chain.
In addition to decreasing the dose and obtaining images without the need for contrast, algorithms can improve the path that the inventory makes from the manufacturer to the hospital. It can predict demand across multiple product segments and geographies. Dynamically identifying trade-offs with hundreds or thousands of interlinked variables and innumerable technical constraints involve too much information for the human being to integrate in a short time.
By integrating AI solutions such as processing optimization and predictive maintenance we can ensure that plans get executed and countries and hospitals can adapt to variability effects such as demand shocks, production stoppages and transportation disruptions in a timely manner.
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You can also read about how Artificial Intelligence improves Healthcare here.