MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer

Zhu, Xuehua; Shao, Lizhi; Liu, Zhenyu; Liu, Zenan; He, Jide; Liu, Jiangang; Hao, Ping; Lu, Jiwen

doi:10.1631/jzus.b2200619

J. Zhejiang Univ. Sci. B

2023

DOI: 10.1631/jzus.b2200619

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MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer

Xuehua Zhu

Lizhi Shao

Zhenyu Liu

et al.

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Cited by 7 publications

References 98 publications

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Artificial intelligence and radiomics applied to prostate cancer bone metastasis imaging: A review

Pawan,

Rich,

et al. 2024

iRADIOLOGY

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The skeletal system is the most common site of metastatic prostate cancer and these lesions are associated with poor outcomes. Diagnosing these osseous metastatic lesions relies on radiologic imaging, making early detection, diagnosis, and monitoring crucial for clinical management. However, the literature lacks a detailed analysis of various approaches and future directions. To address this gap, we present a scoping review of quantitative methods from diverse domains, including radiomics, machine learning, and deep learning, applied to imaging analysis of prostate cancer with clinical insights. Our findings highlight the need for developing clinically significant methods to aid in the battle against prostate bone metastasis.

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Artificial intelligence and radiomics applied to prostate cancer bone metastasis imaging: A review

Pawan,

Rich,

et al. 2024

iRADIOLOGY

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show abstract

Insights into radiomics: impact of feature selection and classification

Perniciano,

Loddo,

Di Ruberto

et al. 2024

Multimed Tools Appl

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Prediction of high-risk prostate cancer based on the habitat features of biparametric magnetic resonance and the omics features of contrast-enhanced ultrasound

Huang,

Liao

et al. 2024

Heliyon

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MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer

Cited by 7 publications

References 98 publications

Artificial intelligence and radiomics applied to prostate cancer bone metastasis imaging: A review

Artificial intelligence and radiomics applied to prostate cancer bone metastasis imaging: A review

Insights into radiomics: impact of feature selection and classification

Prediction of high-risk prostate cancer based on the habitat features of biparametric magnetic resonance and the omics features of contrast-enhanced ultrasound

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