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Lin S, Lv X, Lin X, Chen S, Li Y, Xu M, Qiu Y, Tang L. Modulation Effects of the CEP128 Gene on Radiotherapy-Related Brain Injury: A Longitudinal Structural Study Using Multi-Parametric Brain MR Images. J Magn Reson Imaging 2024; 59:648-658. [PMID: 37249021 DOI: 10.1002/jmri.28824] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/12/2023] [Accepted: 05/12/2023] [Indexed: 05/31/2023] Open
Abstract
BACKGROUND The promoter variant rs17111237 in the CEP128 closely relates to radiotherapy (RT)-related brain necrosis in nasopharyngeal carcinoma (NPC) patients. PURPOSE To explore RT-related dynamic alterations in brain morphology and their potential genetic mechanism, and to explore the modulatory effects of CEP128 genetic variants on RT-related brain morphological alterations in NPC patients. STUDY TYPE Prospective, longitudinal. POPULATION One hundred one patients with histopathologic ally-proven NPC (age 41.64 ± 9.63, 46 male), analyzed at baseline (pre-RT), 3-months post-RT and 6 months post-RT, and 19 sex-, age- and education-matched healthy controls. FIELD STRENGTH/SEQUENCE 3D gradient echo brain volume (3D-BRAVO) and diffusion-weighted single-shot spin-echo echo-planar sequences at 3.0 T. ASSESSMENT rs17111237 in CEP128 was detected by Sanger sequencing. Structural and diffusion images were processed with FreeSurfer and FSL. Morphometric similarity network (MSN) was constructed with nine cortical indices derived from structural and diffusion images. STATISTICAL TESTS One-way ANOVA, chi-square test. Pearson's correlation analysis was conducted to measure the relationship between CEP128 gene-expression level in human brain and MSN alterations. Repeated analysis of variance performed to assess group differences in MSN and the modulatory effects of the CEP128 gene within patients. Significance level: P < 0.05, false-discovery rate correction. RESULTS RT-related significant widespread MSN alterations were observed in the cortices of NPC patients. Notably, regional MSN alterations had a weak but significant negative correlation with the cortical pattern of CEP128 gene expression (r = -0.152). Furthermore, rs17111237 in the CEP128 had significant modulatory effects on the observed MSN alterations in NPC patients, with the modulatory effects being most obvious at 3 months post-RT. CONCLUSIONS MSN has potential to serve as a sensitive biomarker to detect RT-related brain injury. Inter-brain regional and inter-patient variability of RT-related brain injuries may be attributed to the cortical expression of the CEP128 gene and the modulatory effects of the promoter variant rs17111237 in CEP128. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Shiwei Lin
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Xiaofei Lv
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
| | - Xiaoshan Lin
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Shengli Chen
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Yanqing Li
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Manxi Xu
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Yingwei Qiu
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Linquan Tang
- Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
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Li Y, Gong F, Guo Y, Ng WT, Mejia MBA, Nei WL, Wang C, Jin Z. Predictive accuracy of machine learning for radiation-induced temporal lobe injury in nasopharyngeal carcinoma patients: a systematic review and meta-analysis. Transl Cancer Res 2023; 12:2361-2370. [PMID: 37859745 PMCID: PMC10583015 DOI: 10.21037/tcr-23-859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/18/2023] [Indexed: 10/21/2023]
Abstract
Background Radiotherapy is a common treatment for nasopharyngeal carcinoma (NPC) but can cause radiation-induced temporal lobe injury (RTLI), resulting in irreversible damage. Predicting RTLI at the early stage may help with that issue by personalized adjustment of radiation dose based on the predicted risk. Machine learning (ML) models have recently been used to predict RTLI but their predictive accuracy remains unclear because the reported concordance index (C-index) varied widely from around 0.31 to 0.97. Therefore, a meta-analysis was needed. Methods The PubMed, Web of Science, Embase, and Cochrane Library databases were searched from inception to November 2022. Studies that fully develop one or more ML risk models of RTLI after radiotherapy for NPC were included. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was used to assess the risk of bias in the included research. The primary outcome of this review was the C-index, specificity (Spe), and sensitivity (Sen). Results The meta-analysis included 14 studies with 15,573 NPC patients reporting a total of 72 prediction models. Overall, 94.44% of models were found to have a high risk of bias. Radiomics was included in 57 models, dosimetric predictors in 28, and clinical data in 27. The pooled C-index for ML models predicting RTLI was 0.77 [95% confidence interval (CI): 0.75-0.79] in the training set and 0.78 (95% CI: 0.75-0.81) in the validation set. The pooled Sen was 0.75 (95% CI: 0.69-0.80) in the training set and 0.70 (95% CI: 0.66-0.73) in the validation set and the pooled Spe was 0.78 (95% CI: 0.73-0.82) in the training set and 0.79 (95% CI: 0.75-0.82) in the validation set. Models with radiomics and clinical data achieved the most excellent discriminative performance, with a pooled C-index of 0.895. Conclusions ML models can accurately predict RTLI at an early stage, allowing for timely interventions to prevent further damage. The kind of ML methods and the selection of predictors may influence the predictive accuracy.
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Affiliation(s)
- Yiling Li
- Vertigo Clinic/Research Center of Aerospace Medicine, Air Force Medical Center, PLA, Beijing, China
| | - Fengyuan Gong
- Graduate School, Hebei North University, Zhangjiakou, China
| | - Yangyang Guo
- Vertigo Clinic/Research Center of Aerospace Medicine, Air Force Medical Center, PLA, Beijing, China
| | - Wai Tong Ng
- Clinical Oncology Center and Shenzhen Key Laboratory for Cancer Metastasis and Personalized Therapy, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
- Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | | | - Wen-Long Nei
- Division of Radiation Oncology, National Cancer Center Singapore, Singapore, Singapore
| | - Cuicui Wang
- Vertigo Clinic/Research Center of Aerospace Medicine, Air Force Medical Center, PLA, Beijing, China
| | - Zhanguo Jin
- Vertigo Clinic/Research Center of Aerospace Medicine, Air Force Medical Center, PLA, Beijing, China
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Voon NS, Manan HA, Yahya N. Role of resting-state functional MRI in detecting brain functional changes following radiotherapy for head and neck cancer: a systematic review and meta-analysis. Strahlenther Onkol 2023; 199:706-717. [PMID: 37280382 DOI: 10.1007/s00066-023-02089-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Accepted: 04/23/2023] [Indexed: 06/08/2023]
Abstract
PURPOSE Increasing evidence implicates changes in brain function following radiotherapy for head and neck cancer as precursors for brain dysfunction. These changes may thus be used as biomarkers for early detection. This review aimed to determine the role of resting-state functional magnetic resonance imaging (rs-fMRI) in detecting brain functional changes. METHODS A systematic search was performed in the PubMed, Scopus, and Web of Science (WoS) databases in June 2022. Patients with head and neck cancer treated with radiotherapy and periodic rs-fMRI assessments were included. A meta-analysis was performed to determine the potential of rs-fMRI for detecting brain changes. RESULTS Ten studies with a total of 513 subjects (head and neck cancer patients, n = 437; healthy controls, n = 76) were included. A significance of rs-fMRI for detecting brain changes in the temporal and frontal lobes, cingulate cortex, and cuneus was demonstrated in most studies. These changes were reported to be associated with dose (6/10 studies) and latency (4/10 studies). A strong effect size (r = 0.71, p < 0.001) between rs-fMRI and brain changes was also reported, suggesting rs-fMRI's capability for monitoring brain alterations. CONCLUSION Resting-state functional MRI is a promising tool for detecting brain functional changes following head and neck radiotherapy. These changes are correlated with latency and prescription dose.
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Affiliation(s)
- Noor Shatirah Voon
- Diagnostic Imaging and Radiotherapy, Centre of Diagnostic, Therapeutic and Investigative Sciences, Faculty of Health Sciences, National University of Malaysia, Jalan Raja Muda Aziz, 50300, Kuala Lumpur, Malaysia
- Department of Radiotherapy & Oncology, National Cancer Institute, Putrajaya, Malaysia
| | - Hanani Abdul Manan
- Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Cheras, 56000, Kuala Lumpur, Malaysia
| | - Noorazrul Yahya
- Diagnostic Imaging and Radiotherapy, Centre of Diagnostic, Therapeutic and Investigative Sciences, Faculty of Health Sciences, National University of Malaysia, Jalan Raja Muda Aziz, 50300, Kuala Lumpur, Malaysia.
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Perez WD, Perez-Torres CJ. Neurocognitive and radiological changes after cranial radiation therapy in humans and rodents: a systematic review. Int J Radiat Biol 2023; 99:119-137. [PMID: 35511499 DOI: 10.1080/09553002.2022.2074167] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Radiation-induced brain injury is a common long-term side effect for brain cancer survivors, leading to a reduced quality of life. Although there is growing research pertaining to this topic, the relationship between cognitive and radiologically detected lesions of radiation-induced brain injury in humans remains unclear. Furthermore, clinically translatable similarities between rodent models and human findings are also undefined. The objective of this review is to then identify the current evidence of radiation-induced brain injury in humans and to compare these findings to current rodent models of radiation-induced brain injury. METHODS This review includes an examination of the current literature on cognitive and radiological characteristics of radiation-induced brain injury in humans and rodents. A thorough search was conducted on PubMed, Web of Science, and Scopus to identify studies that performed cognitive assessments and magnetic resonance imaging techniques on either humans or rodents after cranial radiation therapy. A qualitative synthesis of the data is herein reported. RESULTS A total of 153 studies pertaining to cognitively or radiologically detected radiation injury of the brain are included in this systematic review; 106 studies provided data on humans while 47 studies provided data on rodents. Cognitive deficits in humans manifest across multiple domains after brain irradiation. Radiological evidence in humans highlight various neuroimaging-detectable changes post-irradiation. It is unclear, however, whether these findings reflect ground truth or research interests. Additionally, rodent models do not comprehensively reproduce characteristics of cognitive and radiological injury currently identified in humans. CONCLUSION This systematic review demonstrates that associations between and within cognitive and radiological radiation-induced brain injuries often rely on the type of assessment. Well-designed studies that evaluate the spectrum of potential injury are required for a precise understanding of not only the clinical significance of radiation-induced brain injury in humans, but also how to replicate injury development in pre-clinical models.
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Affiliation(s)
- Whitney D Perez
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - Carlos J Perez-Torres
- School of Health Sciences, Purdue University, West Lafayette, IN, USA.,Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN, USA.,Academy of Integrated Science, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.,School of Neuroscience, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
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Kang YF, Chen RT, Ding H, Li L, Gao JM, Liu LZ, Zhang YM. Structure–Function Decoupling: A Novel Perspective for Understanding the Radiation-Induced Brain Injury in Patients With Nasopharyngeal Carcinoma. Front Neurosci 2022; 16:915164. [PMID: 35860295 PMCID: PMC9289669 DOI: 10.3389/fnins.2022.915164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 06/09/2022] [Indexed: 11/29/2022] Open
Abstract
Radiation-induced functional and structural brain alterations are well documented in patients with nasopharyngeal carcinoma (NPC), followed by radiotherapy (RT); however, alterations in structure–function coupling remain largely unknown. Herein, we aimed to assess radiation-induced structure–function decoupling and its importance in predicting radiation encephalopathy (RE). We included 62 patients with NPC (22 patients in the pre-RT cohort, 18 patients in the post-RT-RE+ve cohort, and 22 patients in the post-RT-RE–ve cohort). A metric of regional homogeneity (ReHo)/voxel-based morphometry (VBM) was used to detect radiation-induced structure–function decoupling, which was then used as a feature to construct a predictive model for RE. Compared with the pre-RT group, patients in the post-RT group (which included post-RT-RE+ve and post-RT-RE–ve) showed higher ReHo/VBM coupling values in the substantia nigra (SN), the putamen, and the bilateral thalamus and lower values in the brain stem, the cerebellum, the bilateral medial temporal lobes (MTLs), the bilateral insula, the right precentral and postcentral gyri, the medial prefrontal cortex (MPFC), and the left inferior parietal lobule (IPL). In the post-RT group, negative correlations were observed between maximum dosage of RT (MDRT) to the ipsilateral temporal lobe and ReHo/VBM values in the ipsilateral middle temporal gyrus (MTG). Moreover, structure–function decoupling in the bilateral superior temporal gyrus (STG), the bilateral precentral and postcentral gyri, the paracentral lobules, the right precuneus and IPL, and the right MPFC exhibited excellent predictive performance (accuracy = 88.0%) in identifying patients likely to develop RE. These findings show that ReHo/VBM may be a novel effective imaging metric that reflects the neural mechanism underlying RE in patients with NPC.
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Affiliation(s)
- Ya-fei Kang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi’an, China
| | - Rui-ting Chen
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Hao Ding
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin, China
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Li Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jian-ming Gao
- State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Li-zhi Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - You-ming Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: You-ming Zhang,
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Lin X, Li Z, Chen S, Yang Y, He H, Lv X, Qiu Y. Divergent white matter changes in patients with nasopharyngeal carcinoma post-radiotherapy with different outcomes: a potential biomarker for prediction of radiation necrosis. Eur Radiol 2022; 32:7036-7047. [PMID: 35687134 DOI: 10.1007/s00330-022-08907-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 05/17/2022] [Accepted: 05/23/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To investigate the effects of standard radiotherapy on temporal white matter (WM) and its relationship with radiation necrosis (RN) in patients with nasopharyngeal carcinoma (NPC), and to determine the predictive value of WM volume alterations at the early stage for RN occurrence at the late-delay stage. METHODS Seventy-four treatment-naive NPC patients treated with standard radiotherapy were longitudinally followed up for 36 months. Structural MRIs were collected at multiple time points during the first year post-radiotherapy. Longitudinal structural images were processed using FreeSurfer. Linear mixed models were used to delineate divergent trajectories of temporal WM changes between patients who developed RN and who did not. Four machine learning methods were used to construct predictive models for RN with temporal WM volume alterations at early-stage. RESULTS The superior temporal gyrus (STG) had divergent atrophy trajectories in NPC patients with different outcomes (RN vs. NRN) post-radiotherapy. Patients with RN showed more rapid atrophy than those with NRN. A predictive model constructed with temporal WM volume alterations at early-stage post-radiotherapy had good performance for RN; the areas under the curve (AUC) were 0.879 and 0.806 at 1-3 months and 6 months post-radiotherapy, respectively. Moreover, the predictive model constructed with absolute temporal volume at 1-3 months post-radiotherapy also presented good performance; the AUC was 0.842, which was verified by another independent dataset (AUC = 0.773). CONCLUSIONS NPC patients with RN had more sharp atrophy in the STG than those with NRN. Temporal WM volume at early-stage post-radiotherapy may serve as an in vivo biomarker to identify and predict RN occurrence. KEY POINTS • The STG had divergent atrophy trajectories in NPC patients with different outcomes (RN vs. NRN) post-radiotherapy. • Although both groups exhibited time-dependent atrophy in the STG, the patients with RN showed a more rapid volume decrease than those with NRN. • Temporal WM volume alteration (or absolute volume) at the early stage could predict RN occurrence at the late-delay stage after radiotherapy.
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Affiliation(s)
- Xiaoshan Lin
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, 518052, China
| | - Zhipeng Li
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, 510060, China
| | - Shengli Chen
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, 518052, China
| | - Yadi Yang
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, 510060, China
| | - Haoqiang He
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, 510060, China
| | - Xiaofei Lv
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, 510060, China.
| | - Yingwei Qiu
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, 518052, China.
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