Advanced Imaging and Artificial Intelligence Can Help Classify Child Brain Cancers

4 mn read

When it comes to life-threatening diseases, brain tumor is one of them. From children to adults, anyone can develop the illness at any point in life. The illness does not go away quickly and takes a lot of time in healing and treatment to fully recover from it. Different types of tumors exist in the brain, some of which are treatable, while others are not. 

Brain tumors are known as the most common type of solid tumors found in children that are life-threatening to a great level. Brain tumors are of different types; therefore, analyzing their type is the most important step. Since brain biopsy is difficult, new imaging methods are required for doctors to make a solid diagnosis. 

The diffusion-weighted imaging technique has appeared to an advanced imaging technique that uses machine learning to produce images of the brain. The method is found to help analyze the type of brain tumor. The findings are put forward by the University of Warwick and UK-based multi-center study along with WMG.

Diffusion-Weighted Imaging

Diffusion-Weighted Imaging is a wonderful technique that helps in the proper diagnosis and characterization of tumors. Once the original type of the tumor is known, doctors should come up with a treatment plan. The treatment plan can be more specific if the exact problem is diagnosed in time. Diffused Weighted Imaging is the best way to characterize the tumor and assist doctors in reducing the lifetime risk of patients.

Pediatric brain tumors can be easily assessed with this technique, which can lead to better treatment options for patients. A lot of patients don’t get the chance of getting an appropriate treatment due to the lack of accurate diagnosis. 

One of the cancers, which is highly responsible for deaths in children, is a brain tumor known as the posterior fossa. This particular area of the brain is a house for three more types of brain tumors, hence, there was a need for better diagnosis. The Diffusion-Weighted Imaging produces good results to characterize the brain tumor in time, so the patient can receive the best treatment.

Why is Diffusion-Weighted Imaging a Good Way for Brain Tumor Diagnosis?

As of now, a qualitative assessment is an appropriate way used by radiologists to assess a tumor. Overlapping radiological characteristics is however not an adequate way to tell the type of the tumor. Hence, diffusion-weighted imaging along with machine learning shows promising results for tumor differentiation as reported by the researchers at WMG, University of Warwick. The study was published in the Journal of Scientific Reports which shows the credibility of the research.

According to the study, the classification is non-invasive diffusion-weighted imaging that produces accurate results of the brain tumors without biopsy. The method involves the use of specific advanced MRI sequences along with software that produces the images from the data. The method involves using diffusion of water molecules for contrast purposes with the MRI images. The doctors are able to calculate the Apparent Diffusion Coefficient (ADC), which gives enormous details about the tumor type. Once the information is collected, an appropriate treatment plan can be prepared for the patient.

The research involved about 117 patients in the UK and their scans were collected from 12 different hospitals. About 12 different scanners were involved in getting the scans of the patient. The scans were analyzed by experienced scientists in pediatric neuroimaging and radiologists. Some of the interesting regions in the brain scans were marked and studied by experts. 

When the Apparent Diffusion Coefficient was obtained, it was further fed to the AI algorithms to identify the type of tumor. The results of the analysis were remarkable as the treatment was successful in identifying the most common types of posterior fossa brain tumors. The whole procedure was non-invasive and did not hurt any of the patients. 

According to the experts involved in the study, the use of advanced magnetic resonance and AI leads to the proper identification of brain tumors in children. It’s one of the best ways to find tumors in children and treat them when there is enough time to do it. Since it’s a new revelation; therefore, not a lot of New Jersey imaging center are opting for this technique.

Brain tumors are life-threatening and it’s great pressure on the parents as well. Everyone looks for a definite answer and it’s extremely heartbreaking to not have them. However, with the use of artificial intelligence, it’s becoming easier to distinguish between the tumors and get a diagnostic accuracy. Some scanning mechanisms pose limitations, but this invasive technique can be an answer to solving the existing problem. 

Diffusion-Weighted Imaging might be the future of brain tumor diagnosis in children. The classification of the tumor remains a problem for radiologists and doctors, which is why more and more technological intervention is required to solve the issue.

Final Words 

Brain tumors require instant treatment, but it’s often hard for doctors to prescribe a treatment plan to the patient without knowing the type of the tumor. Children with brain tumors are on the high-risk of wrong cancer characterization; therefore, it’s necessary to find a proper solution for it. 

The Diffusion-Weighted Imaging has shown great results for brain tumor identification in children. With proper analysis, doctors are able to make a call and start the treatment as soon as possible. The study has summarized how AI can prove to be beneficial in the long run for the medical field. Although it’s one study, it has opened a way for more research in this direction.


A brain tumor is a life-threatening disease and prolonging its treatment can risk the life of the patient. It’s important to come up with the answers for the patient’s family, so they are under less pressure as well. The use of AI for cancer characterization proves to be a great way to help children with brain tumors.

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