Impact of [18F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role

Seminars in Nuclear Medicine, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Lung cancer remains one of the most prevalent cancers globally and leading cause cancer-related deaths, accounting for nearly one-fifth all fatalities. Fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) plays a vital role in assessing lung managing disease progression. While traditional PET/CT imaging relies on qualitative analysis basic quantitative parameters, radiomics offers more advanced approach to analyzing tumor phenotypes. Recently, has gained attention its potential enhance prognostic diagnostic capabilities [18F]FDG various cancers. This review explores expanding PET/CT-based radiomics, particularly when integrated with artificial intelligence (AI), cancer, especially non-small cell (NSCLC). We how AI improve diagnostics, staging, subtype identification, molecular marker detection, which influence treatment decisions. Additionally, we address challenges clinical integration, such as protocol standardization, feature reproducibility, need extensive prospective studies. Ultimately, hold great promise enabling personalized effective treatments, potentially transforming management.

Язык: Английский

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[18F]FDG-PET/CT Radiomics and Artificial Intelligence in Lung Cancer: Technical Aspects and Potential Clinical Applications

Seminars in Nuclear Medicine, Год журнала: 2022, Номер 52(6), С. 759 - 780

Опубликована: Июнь 15, 2022

Lung cancer is the second most common and leading cause of cancer-related death worldwide. Molecular imaging using [18F]fluorodeoxyglucose Positron Emission Tomography and/or Computed ([18F]FDG-PET/CT) plays an essential role in diagnosis, evaluation response to treatment, prediction outcomes. The images are evaluated qualitative conventional quantitative indices. However, there far more information embedded images, which can be extracted by sophisticated algorithms. Recently, concept uncovering analyzing invisible data from medical called radiomics, gaining attention. Currently, [18F]FDG-PET/CT radiomics growingly lung discover if it enhances diagnostic performance or implication management cancer. In this review, we provide a short overview technical aspects, as they discussed different articles special issue. We mainly focus on [18F]FDG-PET/CT‐based artificial intelligence non-small cell cancer, impacting early detection, staging, tumor subtypes, biomarkers, patient's

Язык: Английский

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Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal carcinoma

European Radiology, Год журнала: 2022, Номер 32(6), С. 4079 - 4089

Опубликована: Янв. 20, 2022

Язык: Английский

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Advances of PET/CT in Target Delineation of Lung Cancer Before Radiation Therapy

Seminars in Nuclear Medicine, Год журнала: 2025, Номер 55(2), С. 190 - 201

Опубликована: Март 1, 2025

Язык: Английский

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Clinical application of AI-based PET images in oncological patients

Seminars in Cancer Biology, Год журнала: 2023, Номер 91, С. 124 - 142

Опубликована: Март 10, 2023

Язык: Английский

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Differentiation of benign versus malignant indistinguishable vertebral compression fractures by different machine learning with MRI-based radiomic features

European Radiology, Год журнала: 2023, Номер 33(7), С. 5069 - 5076

Опубликована: Апрель 26, 2023

Язык: Английский

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A CT-based deep learning radiomics nomogram outperforms the existing prognostic models for outcome prediction in clear cell renal cell carcinoma: a multicenter study

European Radiology, Год журнала: 2023, Номер 33(12), С. 8858 - 8868

Опубликована: Июнь 30, 2023

Язык: Английский

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Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI

Magnetic Resonance Imaging, Год журнала: 2020, Номер 77, С. 36 - 43

Опубликована: Ноя. 18, 2020

Язык: Английский

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Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma

European Journal of Nuclear Medicine and Molecular Imaging, Год журнала: 2022, Номер 49(8), С. 2972 - 2982

Опубликована: Апрель 26, 2022

Язык: Английский

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The value of 18F-FDG PET/CT-based radiomics in predicting perineural invasion and outcome in non-metastatic colorectal cancer

Abdominal Radiology, Год журнала: 2022, Номер 47(4), С. 1244 - 1254

Опубликована: Фев. 26, 2022

Язык: Английский

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