Image and Research Progress of Intracranial Germ Cell Tumor

影像学在颅内生殖细胞肿瘤诊断中发挥着重要作用,一些特征性的表现有利于将其与其他肿瘤性病变区分。此外,在颅内生殖细胞肿瘤中,不同组织学亚型的生物学特性也存在差异,明确诊断对于临床治疗决策十分重要。随着影像组学及机器学习的发展,通过图像实现组织学亚型区分也具有了可能性。因此,本文旨在分析生殖细胞肿瘤的影像学特征,并对其影像组学研究进展进行综述。Medical Imaging plays an important role in the diagnosis of intracranial germ cell tumors (ICGCTs), and some characteristic manifestations are conducive to distinguishing it from other tumorous lesions. In addition, in ICGCTs, the biological characteristics of different histological subtypes are also different, and a clear diagnosis is very important for clinical treatment decision. With the development of radiomics and machine learning (ML), it is possible to distinguish histological subtypes through ML. Therefore, this paper aims to analyze the imaging features of germ cell tumors and review the advances in their radiomics.

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Publication Details

Journal
Advances in Clinical Medicine
Published
2025-01-01
DOI
https://doi.org/10.12677/acm.2025.1551435
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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Image and Research Progress of Intracranial Germ Cell Tumor

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Advances in Clinical Medicine
Radiomics and Machine Learning in Medical Imaging
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Image and Research Progress of Intracranial Germ Cell Tumor

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Abstract

影像学在颅内生殖细胞肿瘤诊断中发挥着重要作用,一些特征性的表现有利于将其与其他肿瘤性病变区分。此外,在颅内生殖细胞肿瘤中,不同组织学亚型的生物学特性也存在差异,明确诊断对于临床治疗决策十分重要。随着影像组学及机器学习的发展,通过图像实现组织学亚型区分也具有了可能性。因此,本文旨在分析生殖细胞肿瘤的影像学特征,并对其影像组学研究进展进行综述。Medical Imaging plays an important role in the diagnosis of intracranial germ cell tumors (ICGCTs), and some characteristic manifestations are conducive to distinguishing it from other tumorous lesions. In addition, in ICGCTs, the biological characteristics of different histological subtypes are also different, and a clear diagnosis is very important for clinical treatment decision. With the development of radiomics and machine learning (ML), it is possible to distinguish histological subtypes through ML. Therefore, this paper aims to analyze the imaging features of germ cell tumors and review the advances in their radiomics.

Advances in Clinical MedicineVol. 15(05)
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Radiomics and Machine Learning in Medical Imaging
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