Differentiation of Brain Metastases from Different Pathological Types of Lung Cancers by Using Radiomic Features of the Edema and Tumor Region

Motivation: Prediction of brain metastases from different pathological types of lung cancers. Goal(s): To develop a radiomic model based on the peritumoral edema and tumor region for tumor type prediction of brain metastases from different pathological types of lung cancers. Approach: Collect lung cancer patients, establish radiomics models, and test the model's differentiation of lesions. Results: The radiomic model could effectively differentiate two pathological types of brain metastasis from lung cancer. Impact: The radiomic model based on the edema and tumor region could effectively differentiate two pathological types of brain metastasis from lung cancer. It is expected to provide an imaging basis for clinicians to evaluate prognosis and formulate personalized treatment plans.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/3837
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Differentiation of Brain Metastases from Different Pathological Types of Lung Cancers by Using Radiomic Features of the Edema and Tumor Region

Hanting Zhu, Yu Zou, Rui Xiong, Chengyi Li et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Differentiation of Brain Metastases from Different Pathological Types of Lung Cancers by Using Radiomic Features of the Edema and Tumor Region

Hanting Zhu, Yu Zou, Rui Xiong, Chengyi Li, Xiaoping Tang, Pengxin Hu
article en

Abstract

Motivation: Prediction of brain metastases from different pathological types of lung cancers. Goal(s): To develop a radiomic model based on the peritumoral edema and tumor region for tumor type prediction of brain metastases from different pathological types of lung cancers. Approach: Collect lung cancer patients, establish radiomics models, and test the model's differentiation of lesions. Results: The radiomic model could effectively differentiate two pathological types of brain metastasis from lung cancer. Impact: The radiomic model based on the edema and tumor region could effectively differentiate two pathological types of brain metastasis from lung cancer. It is expected to provide an imaging basis for clinicians to evaluate prognosis and formulate personalized treatment plans.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
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Openalex Percentile: Top 64%
Radiomics and Machine Learning in Medical Imaging
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