Seeing through "brain fog": neuroimaging assessment and imaging biomarkers for cancer-related cognitive impairments.

IF 3.5 2区 医学 Q2 ONCOLOGY Cancer Imaging Pub Date : 2024-11-18 DOI:10.1186/s40644-024-00797-2
Quanquan Gu, Liya Wang, Tricia Z King, Hongbo Chen, Longjiang Zhang, Jianming Ni, Hui Mao
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Abstract

Advances in cancer diagnosis and treatment have substantially improved patient outcomes and survival in recent years. However, up to 75% of cancer patients and survivors, including those with non-central nervous system (non-CNS) cancers, suffer from "brain fog" or impairments in cognitive functions such as attention, memory, learning, and decision-making. While we recognize the impact of cancer-related cognitive impairment (CRCI), we have not fully investigated and understood the causes, mechanisms and interplays of various involving factors. Consequently, there are unmet needs in clinical oncology in assessing the risk of CRCI and managing patients and survivors with this condition in order to make informed treatment decisions and ensure the quality of life for cancer survivors. The state-of-the-art neuroimaging technologies, particularly clinical imaging modalities like magnetic resonance imaging (MRI) and positron emission tomography (PET), have been widely used to study neuroscience questions, including CRCI. However, in-depth applications of these functional and molecular imaging methods in CRCI and their clinical implementation for CRCI management are largely limited. This scoping review provides the current understanding of contributing neurological factors to CRCI and applications of the state-of-the-art multi-modal neuroimaging methods in investigating the functional and structural alterations related to CRCI. Findings from these studies and potential imaging-biomarkers of CRCI that can be used to improve the assessment and characterization of CRCI as well as to predict the risk of CRCI are also highlighted. Emerging issues and perspectives on future development and applications of neuroimaging tools to better understand CRCI and incorporate neuroimaging-based approaches to treatment decisions and patient management are discussed.

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透过 "脑雾 "看世界:癌症相关认知障碍的神经影像评估和影像生物标志物。
近年来,癌症诊断和治疗的进步大大提高了患者的治疗效果和生存率。然而,多达 75% 的癌症患者和幸存者(包括非中枢神经系统癌症患者和幸存者)患有 "脑雾 "或认知功能障碍,如注意力、记忆力、学习能力和决策能力。虽然我们认识到癌症相关认知障碍(CRCI)的影响,但我们尚未充分调查和了解各种相关因素的成因、机制和相互作用。因此,临床肿瘤学在评估 CRCI 风险、管理患者和幸存者以做出明智的治疗决策和确保癌症幸存者的生活质量方面的需求尚未得到满足。最先进的神经成像技术,尤其是磁共振成像(MRI)和正电子发射断层扫描(PET)等临床成像模式,已被广泛用于研究包括 CRCI 在内的神经科学问题。然而,这些功能和分子成像方法在 CRCI 中的深入应用及其在 CRCI 管理中的临床应用却非常有限。本范围综述介绍了目前对导致 CRCI 的神经因素的理解,以及最先进的多模态神经成像方法在研究与 CRCI 相关的功能和结构改变方面的应用。这些研究结果和潜在的 CRCI 影像生物标志物可用于改善 CRCI 的评估和特征描述,并预测 CRCI 的风险。此外,还讨论了神经成像工具未来发展和应用的新问题和新前景,以便更好地了解 CRCI,并将基于神经成像的方法纳入治疗决策和患者管理。
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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
期刊最新文献
Correction: Optimization and validation of echo times of point-resolved spectroscopy for cystathionine detection in gliomas. Clinical significance of visual cardiac 18F-FDG uptake in advanced non-small cell lung cancer. Nuclear medicine imaging in non-seminomatous germ cell tumors: lessons learned from the past failures. Seeing through "brain fog": neuroimaging assessment and imaging biomarkers for cancer-related cognitive impairments. Prediction of lateral lymph node metastasis with short diameter less than 8 mm in papillary thyroid carcinoma based on radiomics.
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