|
1
|
Alharshan F, Aloufi A, Rowe F, Meyer G. Tracking microstructural adaptations in primary visual areas: A diffusion kurtosis imaging study on visuomotor learning. Neuroimage 2025; 310:121138. [PMID: 40081515 DOI: 10.1016/j.neuroimage.2025.121138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Revised: 02/17/2025] [Accepted: 03/10/2025] [Indexed: 03/16/2025] Open
Abstract
This study investigates the potential of Diffusion Kurtosis Imaging (DKI) to detect microstructural changes induced by visuomotor training and its added value over Diffusion Tensor Imaging (DTI). Fourteen healthy participants completed a six-week home-based eye movement training intervention. Pre-and post-training DKI scans were analysed. Descriptive analysis, including the Coefficient of Variation (CV) and Bland-Altman (BA) metrics, was used to assess training effects. Results revealed significant reductions in kurtosis (MK, RK, AK) and diffusivity (MD) in task-relevant areas, particularly the cuneus, with overlapping findings between DKI and DTI-derived measures. In contrast, the pericalcarine area showed reductions only in MK and AK, suggesting that kurtosis metrics were more sensitive in this region. Increases in KA and FA post-training were not significant. BA analysis confirmed systematic training-related changes in the visual target area, while the transverse temporal gyrus, used as a control, remained stable, providing evidence for the specificity of these effects. These findings highlight DKI's ability to capture training-induced microstructural changes, complementing DTI. Among the metrics, AK emerged as a stable, sensitive marker, while MK and RK provided additional insights with greater variability. This study underscores the role of the cuneus in visuomotor adaptation and the potential of DKI to measure microstructural change cognitive training and neurorehabilitation.
Collapse
Affiliation(s)
- Fahad Alharshan
- Department of Radiological Sciences, College of Applied Medical Scieneces, King Saud bin Abdulaziz University for Health Sciences, Alahsa, Saudi Arabia; Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Abdulrahman Aloufi
- Department of Radiologic Technology, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia
| | - Fiona Rowe
- Institute of Population Health, University of Liverpool, Liverpool, United Kingdom
| | - Georg Meyer
- Digital Innovation Facility, University of Liverpool, Liverpool, United Kingdom; Hanse Wissenschaftskolleg, Delmenhorst, Germany.
| |
Collapse
|
|
2
|
Yue KC, Zhu YY, Sun JW, Wu XT, Liu WJ, Shi HF. Imaging characteristics of brain microstructure and cerebral perfusion in Crohn's disease patients with anxiety: A prospective comparative study. World J Gastroenterol 2025; 31:99014. [PMID: 39877713 PMCID: PMC11718645 DOI: 10.3748/wjg.v31.i4.99014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Revised: 11/13/2024] [Accepted: 12/09/2024] [Indexed: 12/30/2024] Open
Abstract
BACKGROUND Anxiety is a common comorbidity in patients with Crohn's disease (CD). Data on the imaging characteristics of brain microstructure and cerebral perfusion in CD with anxiety are limited. AIM To compare the imaging characteristics of brain microstructure and cerebral perfusion among CD patients with or without anxiety and healthy individuals. METHODS This prospective comparative study enrolled consecutive patients with active CD and healthy individuals who visited the study hospital between January 2022 and January 2023. Anxiety was measured using the Hospital Anxiety and Depression Scale-Anxiety. The imaging characteristics of brain microstructure and cerebral perfusion were measured by diffusion kurtosis imaging and intravoxel incoherent motion. RESULTS A total of 57 participants were enrolled. Among the patients with active CD, 16 had anxiety. Compared with healthy individuals, patients with active CD demonstrated significantly lower radial kurtosis values in the right cerebellar region 6, lower axial kurtosis (AK) values in the right insula, left superior temporal gyrus, and right thalamus, and higher slow and fast apparent diffusion coefficients (ADCslow and ADCfast) in the bilateral frontal lobe, bilateral temporal lobe, and bilateral insular lobe (all P < 0.05). Compared with patients with CD without anxiety, patients with CD and anxiety exhibited significantly higher ADCslow values in the left insular lobe and lower AK values in the right insula and right anterior cuneus (all P < 0.05). CONCLUSION There are variations in brain microstructure and perfusion among CD patients with/without anxiety and healthy individuals, suggesting potential use in assessing anxiety-related changes in active CD.
Collapse
Affiliation(s)
- Ke-Cen Yue
- Dalian Medical University, Dalian 116044, Liaoning Province, China
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Medical Center, Changzhou 213000, Jiangsu Province, China
| | - Ying-Yin Zhu
- Department of Radiology, Suzhou 100 Hospital, Suzhou 215000, Jiangsu Province, China
| | - Jing-Wen Sun
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Medical Center, Changzhou 213000, Jiangsu Province, China
| | - Xin-Tong Wu
- Dalian Medical University, Dalian 116044, Liaoning Province, China
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Medical Center, Changzhou 213000, Jiangsu Province, China
| | - Wen-Jia Liu
- Department of Gastroenterology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Medical Center, Changzhou 213000, Jiangsu Province, China
| | - Hai-Feng Shi
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Medical Center, Changzhou 213000, Jiangsu Province, China
| |
Collapse
|
|
3
|
Zheng X, Shen F, Chen W, Ren W, Tang S. Integrated pretreatment diffusion kurtosis imaging and serum squamous cell carcinoma antigen levels: a biomarker strategy for early assessment of radiotherapy outcomes in cervical cancer. Abdom Radiol (NY) 2024; 49:1502-1511. [PMID: 38536425 DOI: 10.1007/s00261-024-04270-3] [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: 12/03/2023] [Revised: 02/22/2024] [Accepted: 02/25/2024] [Indexed: 05/22/2024]
Abstract
OBJECTIVE This study aims to explore the utility of pretreatment DKI parameters and serum SCC-Ag in evaluating the early therapeutic response of cervical cancer to radiotherapy. MATERIALS AND METHODS A total of 33 patients diagnosed with cervical cancer, including 31 cases of cervical squamous cell carcinoma and two cases of adenosquamous carcinoma, participated in the study. All patients underwent conventional MRI and DKI scans on a 3T magnetic resonance scanner before radiotherapy and after ten sessions of radiotherapy. The therapeutic response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Patients were categorized into a response group (RG), comprising Complete Remission (CR) and Partial Remission (PR), and a non-response group (NRG), comprising Stable Disease (SD) and Progressive Disease (PD). LASSO was employed to select pretreatment DKI parameters, and ROC curves were generated for the selected parameters and serum SCC-Ag. RESULTS Significant differences were observed in pretreatment MD, Da, Dr, MK, Ka, Kr, and SCC-Ag between the RG and NRG groups (P < 0.01). However, no significant differences were noted for FA and FAK (P = 0.441&0.928). The two selected parameters (MD and MK) demonstrated area under the curve (AUC), sensitivity, and specificity of 0.810, 0.769, 0.850 and 0.827, 0.846, 0.750, respectively. The combination of MD and MK exhibited an improved AUC of 0.901, sensitivity of 0.692, and specificity of 1.000, with a higher Youden index compared to the individual parameters. Conversely, the AUC, sensitivity, and specificity of the combination of MD, MK, and SCC-Ag were 0.852, 0.615, and 1.000, with a Youden index of 0.615. CONCLUSION Pretreatment MD, MK, and SCC-Ag demonstrate potential clinical utility, with the combined application of MD and MK showing enhanced efficacy in assessing the early therapeutic response of cervical cancer to radiotherapy. The addition of SCC-Ag did not contribute further to the assessment efficacy.
Collapse
Affiliation(s)
- Xiang Zheng
- Department of Radiologic Diagnosis, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 420 Fuma Road, Fuzhou, 350014, Fujian, China.
| | - Fangmin Shen
- Department of Radiologic Diagnosis, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 420 Fuma Road, Fuzhou, 350014, Fujian, China
| | - Wenjuan Chen
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Wang Ren
- Department of Radiologic Diagnosis, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No. 420 Fuma Road, Fuzhou, 350014, Fujian, China
| | - Shaoliang Tang
- School of Medical Imaging, Fujian Medical University, Fuzhou, 350122, China
| |
Collapse
|
|
4
|
Sun H, Yan R, Hua L, Xia Y, Huang Y, Wang X, Yao Z, Lu Q. Based on white matter microstructure to early identify bipolar disorder from patients with depressive episode. J Affect Disord 2024; 350:428-434. [PMID: 38244786 DOI: 10.1016/j.jad.2024.01.147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 01/10/2024] [Accepted: 01/14/2024] [Indexed: 01/22/2024]
Abstract
OBJECTIVE Because of similar clinical manifestations, bipolar disorder (BD) patients are often misdiagnosed as major depressive disorder (MDD). This study aimed to compare the difference between depressed patients later converting to BD and unipolar depression (UD) according to diffusion tensor imaging (DTI). METHOD Patients with MDD (562 participants) in depressive episode states and healthy controls (HCs) (145 participants) were recruited over 10 years. Demographic and magnetic resonance imaging (MRI) data were collected at the time of recruitment. All patients with MDD were followed up for 5 years and classified into the transfer to BD (tBD) group (83 participants) and UD group (160 participants) according to the follow-up results. DTI and functional magnetic resonance imaging at baseline were compared. RESULTS Common abnormalities were found in both tBD and UD groups, including left superior cerebellar peduncle (SCP.L), right anterior limb of the internal capsule (ALIC.R), right superior fronto-occipital fasciculus (SFOF.R), and right inferior fronto-occipital fasciculus (IFOF.R). The tBD showed more extensive abnormalities than the UD in the body of corpus callosum, fornix, left superior corona radiata, left posterior corona radiata, left superior longitudinal fasciculus, and left superior fronto-occipital fasciculus. CONCLUSION The study demonstrated the common and distinct abnormalities of tBD and UD when compared to HC. The tBD group showed more extensive disruptions of white matter integrity, which could be a potential biomarker for the early identification of BD.
Collapse
Affiliation(s)
- Hao Sun
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China
| | - Rui Yan
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China
| | - Lingling Hua
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China
| | - Yi Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China
| | - Yinghong Huang
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China
| | - Xiaoqin Wang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China
| | - Zhijian Yao
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing 210029, China; School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China.
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China.
| |
Collapse
|
|
5
|
Zheng J, Jiao Z, Dai J, Liu T, Shi H. Abnormal cerebral micro-structures in end-stage renal disease patients related to mild cognitive impairment. Eur J Radiol 2022; 157:110597. [DOI: 10.1016/j.ejrad.2022.110597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 10/20/2022] [Accepted: 11/06/2022] [Indexed: 11/13/2022]
|
|
6
|
De Luca A, Kuijf H, Exalto L, Thiebaut de Schotten M, Biessels GJ. Multimodal tract-based MRI metrics outperform whole brain markers in determining cognitive impact of small vessel disease-related brain injury. Brain Struct Funct 2022; 227:2553-2567. [PMID: 35994115 PMCID: PMC9418106 DOI: 10.1007/s00429-022-02546-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 07/27/2022] [Indexed: 01/04/2023]
Abstract
In cerebral small vessel disease (cSVD), whole brain MRI markers of cSVD-related brain injury explain limited variance to support individualized prediction. Here, we investigate whether considering abnormalities in brain tracts by integrating multimodal metrics from diffusion MRI (dMRI) and structural MRI (sMRI), can better capture cognitive performance in cSVD patients than established approaches based on whole brain markers. We selected 102 patients (73.7 ± 10.2 years old, 59 males) with MRI-visible SVD lesions and both sMRI and dMRI. Conventional linear models using demographics and established whole brain markers were used as benchmark of predicting individual cognitive scores. Multi-modal metrics of 73 major brain tracts were derived from dMRI and sMRI, and used together with established markers as input of a feed-forward artificial neural network (ANN) to predict individual cognitive scores. A feature selection strategy was implemented to reduce the risk of overfitting. Prediction was performed with leave-one-out cross-validation and evaluated with the R2 of the correlation between measured and predicted cognitive scores. Linear models predicted memory and processing speed with R2 = 0.26 and R2 = 0.38, respectively. With ANN, feature selection resulted in 13 tract-specific metrics and 5 whole brain markers for predicting processing speed, and 28 tract-specific metrics and 4 whole brain markers for predicting memory. Leave-one-out ANN prediction with the selected features achieved R2 = 0.49 and R2 = 0.40 for processing speed and memory, respectively. Our results show proof-of-concept that combining tract-specific multimodal MRI metrics can improve the prediction of cognitive performance in cSVD by leveraging tract-specific multi-modal metrics.
Collapse
Affiliation(s)
- Alberto De Luca
- VCI Group, Neurology Department, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, The Netherlands.
- Image Sciences Institute, Division Imaging and Oncology, UMC Utrecht, Utrecht, The Netherlands.
| | - Hugo Kuijf
- Image Sciences Institute, Division Imaging and Oncology, UMC Utrecht, Utrecht, The Netherlands
| | - Lieza Exalto
- VCI Group, Neurology Department, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, The Netherlands
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Lab, Sorbonne University, Paris, France
- Institut des Maladies Neurodégénératives, Neurofunctional Imaging Group, University of Bordeaux, Bordeaux, France
| | - Geert-Jan Biessels
- VCI Group, Neurology Department, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, The Netherlands
| |
Collapse
|
|
7
|
Huisman SI, van der Boog ATJ, Cialdella F, Verhoeff JJC, David S. Quantifying the post-radiation accelerated brain aging rate in glioma patients with deep learning. Radiother Oncol 2022; 175:18-25. [PMID: 35963398 DOI: 10.1016/j.radonc.2022.08.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 07/12/2022] [Accepted: 08/01/2022] [Indexed: 10/15/2022]
Abstract
BACKGROUND AND PURPOSE Changes of healthy appearing brain tissue after radiotherapy (RT) have been previously observed. Patients undergoing RT may have a higher risk of cognitive decline, leading to a reduced quality of life. The experienced tissue atrophy is similar to the effects of normal aging in healthy individuals. We propose a new way to quantify tissue changes after cranial RT as accelerated brain aging using the BrainAGE framework. MATERIALS AND METHODS BrainAGE was applied to longitudinal MRI scans of 32 glioma patients. Utilizing a pre-trained deep learning model, brain age is estimated for all patients' pre-radiotherapy planning and follow-up MRI scans to acquire a quantification of the changes occurring in the brain over time. Saliency maps were extracted from the model to spatially identify which areas of the brain the deep learning model weighs highest for predicting age. The predicted ages from the deep learning model were used in a linear mixed effects model to quantify aging of patients after RT. RESULTS The linear mixed effects model resulted in an accelerated aging rate of 2.78 years/year, a significant increase over a normal aging rate of 1 (p < 0.05, confidence interval = 2.54-3.02). Furthermore, the saliency maps showed numerous anatomically well-defined areas, e.g.: Heschl's gyrus among others, determined by the model as important for brain age prediction. CONCLUSION We found that patients undergoing RT are affected by significant post-radiation accelerated aging, with several anatomically well-defined areas contributing to this aging. The estimated brain age could provide a method for quantifying quality of life post-radiotherapy.
Collapse
Affiliation(s)
- Selena I Huisman
- Department of Radiation Oncology, UMC Utrecht, 3584 CX Utrecht, The Netherlands.
| | | | - Fia Cialdella
- Department of Radiation Oncology, UMC Utrecht, 3584 CX Utrecht, The Netherlands; Department of Medical Oncology, UMC Utrecht, 3584 CX Utrecht, The Netherlands.
| | - Joost J C Verhoeff
- Department of Radiation Oncology, UMC Utrecht, 3584 CX Utrecht, The Netherlands.
| | - Szabolcs David
- Department of Radiation Oncology, UMC Utrecht, 3584 CX Utrecht, The Netherlands.
| |
Collapse
|
|
8
|
Zheng J, Wu X, Dai J, Pan C, Shi H, Liu T, Jiao Z. Aberrant brain gray matter and functional networks topology in end stage renal disease patients undergoing maintenance hemodialysis with cognitive impairment. Front Neurosci 2022; 16:967760. [PMID: 36033631 PMCID: PMC9399762 DOI: 10.3389/fnins.2022.967760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 07/18/2022] [Indexed: 11/22/2022] Open
Abstract
Purpose To characterize the topological properties of gray matter (GM) and functional networks in end-stage renal disease (ESRD) patients undergoing maintenance hemodialysis to provide insights into the underlying mechanisms of cognitive impairment. Materials and methods In total, 45 patients and 37 healthy controls were prospectively enrolled in this study. All subjects completed resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) examinations and a Montreal cognitive assessment scale (MoCA) test. Differences in the properties of GM and functional networks were analyzed, and the relationship between brain properties and MoCA scores was assessed. Cognitive function was predicted based on functional networks by applying the least squares support vector regression machine (LSSVRM) and the whale optimization algorithm (WOA). Results We observed disrupted topological organizations of both functional and GM networks in ESRD patients, as indicated by significantly decreased global measures. Specifically, ESRD patients had impaired nodal efficiency and degree centrality, predominantly within the default mode network, limbic system, frontal lobe, temporal lobe, and occipital lobe. Interestingly, the involved regions were distributed laterally. Furthermore, the MoCA scores significantly correlated with decreased standardized clustering coefficient (γ), standardized characteristic path length (λ), and nodal efficiency of the right insula and the right superior temporal gyrus. Finally, optimized LSSVRM could predict the cognitive scores of ESRD patients with great accuracy. Conclusion Disruption of brain networks may account for the progression of cognitive dysfunction in ESRD patients. Implementation of prediction models based on neuroimaging metrics may provide more objective information to promote early diagnosis and intervention.
Collapse
Affiliation(s)
- Jiahui Zheng
- Department of Radiology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Xiangxiang Wu
- Department of Radiology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Jiankun Dai
- GE Healthcare, MR Research China, Beijing, China
| | - Changjie Pan
- Department of Radiology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Haifeng Shi
- Department of Radiology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- *Correspondence: Haifeng Shi,
| | - Tongqiang Liu
- Department of Nephrology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- Tongqiang Liu,
| | - Zhuqing Jiao
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, China
- Zhuqing Jiao,
| |
Collapse
|
|
9
|
Guo LM, Zhao M, Cai Y, Li N, Xu XQ, Zhang X, Zhang JL, Xie QL, Li SS, Chen XQ, Cui SD, Lu C. Microstructural changes of white matter assessed with diffusional kurtosis imaging in extremely preterm infants with severe intraventricular hemorrhage. Front Pediatr 2022; 10:1054443. [PMID: 36605755 PMCID: PMC9808076 DOI: 10.3389/fped.2022.1054443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/01/2022] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE Intraventricular hemorrhage (IVH) is a serious neurological complication in premature infants. This study aimed to investigate the white matter impairments and neurodevelopmental outcomes of severe IVH in extremely preterm infants with gestation age less than 28 weeks. METHODS We retrospectively evaluated the extremely preterm infants between 2017 and 2020. Neurodevelopmental outcomes were evaluated with the Bayley Scales of Infant and Toddler Development-III at 2 years of corrected age. Diffusional kurtosis imaging (DKI) was employed to evaluate the microstructural changes in white matter tracts. Mean kurtosis (MK) and fractional anisotropy (FA) values of DKI were measured in the brain regions including posterior limbs of the internal capsule (PLIC) and the corpus callosum at term equivalent age. RESULTS Of 32 extremely preterm infants with severe IVH during the follow-up period, 18 cases were identified as neurodevelopmental impairments. The delay rates of motor and language were 58.4% and 52.7%. The cases with neurodevelopmental impairments had lower MK and FA values in both bilateral PLIC and the corpus callosum. The analysis of multivariable regression models predicting motor and language outcomes at 2 years of corrected age, showed that the decreases of MK values in both PLIC and the corpus callosum at the term equivalent age contributed to a significantly increased risk of neurodevelopmental impairments (all p < 0.05). During follow-up period, obvious loss of nerve fiber bundles was observed with DKI tractography. CONCLUSION Motor and language abilities at age 2 years were associated with MK values of DKI at the term equivalent age in both PLIC and the corpus callosum of extremely preterm infants with severe IVH. The evaluation of white matter microstructural changes with MK values might provide feasible indicators of neurodevelopmental outcomes of extremely preterm infants with severe intraventricular hemorrhage.
Collapse
Affiliation(s)
- Li-Min Guo
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Meng Zhao
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yue Cai
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Na Li
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao-Quan Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xuan Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiu-Lou Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qi-Lian Xie
- Department of Critical Care Medicine, Anhui Children's Hospital, Hefei, China
| | - Si-Si Li
- Clinical Laboratory, Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao-Qing Chen
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shu-Dong Cui
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Lu
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| |
Collapse
|