Cancer can be accurately diagnosed using urine test with artificial intelligence



[ad_1]

PICTURE

PICTURE: The set of detection signals collected for each patient was then analyzed using ML to screen the patient for PCa. Seventy-six urine samples were measured three times, resulting in 912 … see more

Credit: Korea Institute of Science and Technology (KIST)

Prostate cancer is one of the most common cancers in men. Patients are determined to have prostate cancer primarily based on * PSA, a cancer factor in the blood. However, since the diagnostic accuracy is as low as 30%, a considerable number of patients undergo further invasive biopsy and therefore suffer from the resulting side effects, such as bleeding and pain.

* Prostate Specific Antigen (PSA): A prostate specific antigen (a cancer factor) used as an index for screening for prostate cancer.

The Korea Institute of Science and Technology (KIST) announced that the collaborative research team led by Dr Kwan Hyi Lee of the Biomaterials Research Center and Professor In Gab Jeong of Asan Medical Center has developed a technique to diagnose prostate cancer from urine in just twenty minutes. with almost 100% accuracy. The research team developed this technique by introducing a method of intelligent analysis of AI in an ultrasensitive biosensor based on an electrical signal.

As a non-invasive method, a diagnostic test using urine is convenient for patients and does not require invasive biopsy, thereby diagnosing cancer without side effects. However, since the concentration of cancer factors ** is low in urine, a urine-based biosensor has been used to classify risk groups rather than for precise diagnosis so far.

** Cancer Factor: A cancer-related biological index that can objectively measure and assess the drug’s responsiveness to a normal biological process, disease course, and method of treatment.

Dr Lee’s team at KIST worked on developing a technique to diagnose the disease from urine using the ultrasensitive biosensor based on the electrical signal. An approach using a single cancer factor associated with a cancer diagnosis was limited to increase the diagnostic accuracy to over 90%. However, to overcome this limitation, the team simultaneously used different types of cancer factors instead of using just one to improve diagnostic accuracy in innovative ways.

The team has developed an ultra-sensitive solid-state sensor system capable of simultaneously measuring traces of four selected cancer factors in urine to diagnose prostate cancer. They trained the AI ​​using the correlation between the four cancer factors, which were obtained from the developed sensor. The trained AI algorithm was then used to identify people with prostate cancer by analyzing complex patterns of the detected signals. Diagnosis of prostate cancer using AI analysis successfully detected 76 urine samples with almost 100% accuracy.

“For patients requiring surgery and / or treatment, cancer will be diagnosed with high accuracy using urine to minimize unnecessary biopsies and treatments, which can dramatically reduce medical costs and fatigue for medical staff. Said Prof Jeong from Asan Medical Center. “This research has developed a smart biosensor that can quickly diagnose prostate cancer with nearly 100 percent accuracy only through a urine test, and it can be used further in the accurate diagnosis of other cancers. using a urine test, “said KIST’s Dr Lee. .

###

This research was supported by the Korean National Research Foundation Mid-Career Research Fellowship Program, government departments (Ministry of Science and ICT, Ministry of Trade and Industry, Ministry of Health and Welfare and the Ministry of Food and Pharmaceutical Safety), and Korea Medical Device Development Fund, funded by the Ministry of Science and ICT (MSIT). The research results were published in the latest issue of ACS Nano, a leading international academic journal in the field of nanotechnologies.

Warning: AAAS and EurekAlert! are not responsible for the accuracy of any press releases posted on EurekAlert! by the contributing institutions or for the use of any information via the EurekAlert system.

[ad_2]

Source link