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Abstract #4808

Discrimination between Benign and Malignant Lung Lesions Using a Tri-Compartmental Restriction Spectrum Imaging Model

Xue Liu1,2, Nan Meng2, Han Jiang3, Yihang Zhou3, Jianmin Yuan4, Zhe Wang4, Yang Yang5, and Meiyun Wang1,2,6
1Department of Medical Imaging, Zhengzhou University People’s Hospital, Zhengzhou, China, 2Department of Medical Imaging, Henan Provincial People’s Hospital, Zhengzhou, China, 3Department of Medical Imaging, Xinxiang Medical University & Henan Provincial People's Hospital, Zhengzhou, China, 4Central Research Institute, United Imaging Healthcare Group, Shanghai, China, 5Beijing United Imaging Research Institute of Intelligent Imaging, United Imaging Healthcare Group, Beijing, China, 6Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China

Synopsis

Keywords: Diffusion Modeling, Cancer, RSI; PET/MRI; Lung Lesion

Motivation: An accurate non-invasive detection method is required to identify benign and malignant lung lesions.

Goal(s): To assess the predictive value of the tri-compartmental RSI model in distinguishing between benign and malignant lung lesions.

Approach: In a prospective study, 137 suspected lung tumor patients who underwent PET/MRI scans were included.

Results: Elevated RSI-C1, SUVmax, and lower ADC, RSI-C3 were observed in the malignant group compared with benign group (all P < 0.001). The AUCs, ranked from highest to lowest, were 0.819 (SUVmax) > 0.811 (RSI-C3) > 0.770 (RSI-C1) > 0.745 (ADC). The combined model of RSI-C1, RSI-C3, and SUVmax showed an AUC of 0.900.

Impact: Our study provides preliminary evidence of the potential of RSI-MRI technology to enhance non-invasive imaging of lung lesions. PET/MRI combined with metabolic parameter is helpful to optimize the clinical diagnosis of lung lesions.

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Abstract

Keywords