Researchers in China are using radiomics to predict heart attacks

Researchers in China are using radiomics to predict heart attacks

A study in Radiology, a journal of the Radiological Society of North America, reveals that researchers are using radiomics to predict future heart attacks. Radiomics is an approach that helps extract quantitative information from CT images, enabling researchers to discover disease features not apparent from the images alone.

Researchers are using an approach called radiomics to predict future heart events such as heart attacks, according to a study published today (Feb. 14, 2023) in Radiology, a journal of the Radiological Society of North America (RSNA). Radiomics enables researchers to extract quantitative or measurable data from CT images that can reveal disease features not visible in the images alone.

Coronary artery disease is associated with fatty deposits of plaque that build up within the artery walls. Large, lipid-rich plaques are vulnerable to rupture. The rupture of these plaques causes most heart attacks. However, it is challenging to predict which plaques will rupture.

Researchers in China developed a radiomics model that uses information from coronary CT angiography images to assess plaque vulnerability. They developed the model in 299 patients. They then studied the approach in 708 patients with suspected coronary artery disease.

The model enabled the detection of vulnerable plaques associated with an increased risk of major adverse cardiac events such as heart attacks. A high radiomic signature was independently associated with these events over a median follow-up of three years.

Representative images from two patients demonstrate the use of a radiomic signature (RS) to distinguish vulnerable plaques defined with intravascular US. (AC) Images show a fragile plaque with a high RS. (A) Image of coronary CT angiography (CCTA) shows a partially calcified plaque (arrow) with an RS value of 0.56 in the proximal left anterior descending artery (LAD). (B) Corresponding axial CCTA image shows the plaque with an area of ​​low attenuation (circle, 25 HU). (C) Corresponding US intravascular scan confirms the plaque as an attenuated plaque

. (DF) Images show a non-vulnerable plaque with low RS. (D, E) CCTA images show a partially calcified plaque (arrow in D) with an RS value of 0.50 in the proximal left anterior descending artery. (F) Corresponding US intravascular scan confirms the plaque as a partially calcified plaque without echo attenuation and echolucent zone. High versus low RS lesion was defined with an optimal cut-off value of 0.53 (range, 0.46-0.58). Credit: Radiological Association of North America

“The results of this study are encouraging and exciting,” said co-lead author Long Jiang Zhang, MD, Ph.D., of the Department of Radiology at Jinling Hospital, Medical School of Nanjing University in Nanjing, China. “Radiomics provided a more accurate approach to detect vulnerable plaques compared to conventional anatomical parameters for coronary CT angiography.”

The radiomic signature could easily be added to clinical practice, said Dr. Zhang. In the clinic, it could assess potentially vulnerable plaques and help stratify high-risk patients.

“If the radiomics analysis is embedded in the routine CT angiography workstation, it can automatically identify vulnerable plaques for assessment by a physician,” said Dr. Zhang. “So radiomics can do the


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”>accuracy and precision of high-risk plaque detection in everyday clinical practice.”

The researchers plan to build a radiomics model from different scanner types and vendors. They are also planning a larger, multicenter study of 10,000 patients.

“With the support of large observational studies and randomized controlled trials, the radiomics approach may help guide clinical decision-making and improve patient care in the future,” said Dr. Zhang. “Een coronair CT-angiografie-radiomicsmodel om kwetsbare plaque te identifieren en cardiovasculaire gebeurtenissen te voorspellen” door Qian Chen, Tao Pan, Yi Ning Wang, U. Joseph Schoepf, Samuel L. Bidwell, Hongyan Qiao, Yun Feng, Cheng Xu, Hui Xu, Guanghui Xie, Xiaofei Gao, Xin-Wei Tao, Mengjie Lu, Peng Peng Xu, Jian Zhong, Yongyue Wei, Xindao Yin, Junjie Zhang en Long Jiang Zhang, 14 februari 2023,Radiology

DOI: 10.1148/radiol.221693

Samenwerken met Dr. Zhang waren Qian Chen, MD, Tao Pan, MBBS, Yi Ning Wang, MD, Ph.D., U. Joseph Schoepf, MD, Samuel L. Bidwell, BS, Hongyan Qiao, MD, Yun Feng, MD , Cheng Xu, MD, Hui Xu, M.Sc., Guanghui Xie, MBBS, Xiaofei Gao, MD, Xin-Wei Tao, M.Sc., Mengjie Lu, Ph.D., Peng Peng Xu, MD, Jian Zhong , MBBS, Yongyue Wei, Ph.D., Xindao Yin, MD, Ph.D., en Junjie Zhang, Ph.D.


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