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Kochunov P, Hong LE, Summerfelt A, Gao S, Brown PL, Terzi M, Acheson A, Woldorff MG, Fieremans E, Abdollahzadeh A, Sathyasaikumar KV, Clark SM, Schwarcz R, Shepard PD, Elmer GI. White matter and latency of visual evoked potentials during maturation: A miniature pig model of adolescent development. J Neurosci Methods 2024; 411:110252. [PMID: 39159872 DOI: 10.1016/j.jneumeth.2024.110252] [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: 01/10/2024] [Revised: 07/17/2024] [Accepted: 08/16/2024] [Indexed: 08/21/2024]
Abstract
BACKGROUND Continuous myelination of cerebral white matter (WM) during adolescence overlaps with the formation of higher cognitive skills and the onset of many neuropsychiatric disorders. We developed a miniature-pig model of adolescent brain development for neuroimaging and neurophysiological assessment during this critical period. Minipigs have gyroencephalic brains with a large cerebral WM compartment and a well-defined adolescence period. METHODS Eight Sinclair™ minipigs (Sus scrofa domestica) were evaluated four times during weeks 14-28 (40, 28 and 28 days apart) of adolescence using monocular visual stimulation (1 Hz)-evoked potentials and diffusion MRI (dMRI) of WM. The latency for the pre-positive 30 ms (PP30), positive 30 ms (P30) and negative 50 ms (N50) components of the flash visual evoked potentials (fVEPs) and their interhemispheric latency (IL) were recorded in the frontal, central and occipital areas during ten 60-second stimulations for each eye. The dMRI imaging protocol consisted of fifteen b-shells (b = 0-3500 s/mm2) with 32 directions/shell, providing measurements that included fractional anisotropy (FA), radial kurtosis, kurtosis anisotropy (KA), axonal water fraction (AWF), and the permeability-diffusivity index (PDI). RESULTS Significant reductions (p < 0.05) in the latency and IL of fVEP measurements paralleled significant rises in FA, KA, AWF and PDI over the same period. The longitudinal latency changes in fVEPs were primarily associated with whole-brain changes in diffusion parameters, while fVEP IL changes were related to maturation of the corpus callosum. CONCLUSIONS Good agreement between reduction in the latency of fVEPs and maturation of cerebral WM was interpreted as evidence for ongoing myelination and confirmation of the minipig as a viable research platform. Adolescent development in minipigs can be studied using human neuroimaging and neurophysiological protocols and followed up with more invasive assays to investigate key neurodevelopmental hypotheses in psychiatry.
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Affiliation(s)
- Peter Kochunov
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA; Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - L Elliot Hong
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ann Summerfelt
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Si Gao
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA; Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - P Leon Brown
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Matthew Terzi
- Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ashley Acheson
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Marty G Woldorff
- Center for Cognitive Neuroscience, Duke University, Durham, NC. USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Ali Abdollahzadeh
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Korrapati V Sathyasaikumar
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Sarah M Clark
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Robert Schwarcz
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paul D Shepard
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Greg I Elmer
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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O'Connor EE, Salerno-Goncalves R, Rednam N, O'Brien R, Rock P, Levine AR, Zeffiro TA. Macro- and Microstructural White Matter Differences in Neurologic Postacute Sequelae of SARS-CoV-2 Infection. AJNR Am J Neuroradiol 2024:ajnr.A8481. [PMID: 39389778 DOI: 10.3174/ajnr.a8481] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Accepted: 07/11/2024] [Indexed: 10/12/2024]
Abstract
BACKGROUND AND PURPOSE Neuropsychiatric complications of SARS-CoV-2 infection, also known as neurologic postacute sequelae of SARS-CoV-2 infection (NeuroPASC), affect 10%-60% of infected individuals. There is growing evidence that NeuroPASC is a multi system immune dysregulation disease affecting the brain. The behavioral manifestations of NeuroPASC, such as impaired processing speed, executive function, memory retrieval, and sustained attention, suggest widespread WM involvement. Although previous work has documented WM damage following acute SARS-CoV-2 infection, its involvement in NeuroPASC is less clear. We hypothesized that macrostructural and microstructural WM differences in NeuroPASC participants would accompany cognitive and immune system differences. MATERIALS AND METHODS In a cross-sectional study, we screened a total of 159 potential participants and enrolled 72 participants, with 41 asymptomatic controls (NoCOVID) and 31 NeuroPASC participants matched for age, sex, and education. Exclusion criteria included neurologic disorders unrelated to SARS-CoV-2 infection. Assessments included clinical symptom questionnaires, psychometric tests, brain MRI measures, and peripheral cytokine levels. Statistical modeling included separate multivariable regression analyses of GM/WM/CSF volume, WM microstructure, cognitive, and cytokine concentration between-group differences. RESULTS NeuroPASC participants had larger cerebral WM volume than NoCOVID controls (β = 0.229; 95% CI: 0.017-0.441; t = 2.16; P = .035). The most pronounced effects were in the prefrontal and anterior temporal WM. NeuroPASC participants also exhibited higher WM mean kurtosis, consistent with ongoing neuroinflammation. NeuroPASC participants had more self-reported symptoms, including headache, and lower performance on measures of attention, concentration, verbal learning, and processing speed. A multivariate profile analysis of the cytokine panel showed different group cytokine profiles (Wald-type-statistic = 44.6, P = .046), with interferon (IFN)-λ1 and IFN-λ2/3 levels higher in the NeuroPASC group. CONCLUSIONS NeuroPASC participants reported symptoms of lower concentration, higher fatigue, and impaired cognition compatible with WM syndrome. Psychometric testing confirmed these findings. NeuroPASC participants exhibited larger cerebral WM volume and higher WM mean kurtosis than NoCOVID controls. These findings suggest that immune dysregulation could influence WM properties to produce WM volume increases and consequent cognitive effects and headaches. Further work will be needed to establish mechanistic links among these variables.
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Affiliation(s)
- Erin E O'Connor
- From the Department of Diagnostic Radiology & Nuclear Medicine (E.E.O., N.R., T.A.Z.), University of Maryland School of Medicine, Baltimore, Maryland
| | | | - Nikita Rednam
- From the Department of Diagnostic Radiology & Nuclear Medicine (E.E.O., N.R., T.A.Z.), University of Maryland School of Medicine, Baltimore, Maryland
| | | | - Peter Rock
- Department of Anesthesiology (P.R.), University of Maryland School of Medicine, Baltimore, Maryland
| | - Andrea R Levine
- Department of Medicine (A.R.L.), Division of Pulmonary and Critical Care Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Thomas A Zeffiro
- From the Department of Diagnostic Radiology & Nuclear Medicine (E.E.O., N.R., T.A.Z.), University of Maryland School of Medicine, Baltimore, Maryland
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Farquhar ME, Yang Q, Vegh V. Robust, fast and accurate mapping of diffusional mean kurtosis. eLife 2024; 12:RP90465. [PMID: 39374133 PMCID: PMC11458175 DOI: 10.7554/elife.90465] [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] [Indexed: 10/09/2024] Open
Abstract
Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.
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Affiliation(s)
- Megan E Farquhar
- School of Mathematical Sciences, Faculty of Science, Queensland University of TechnologyBrisbaneAustralia
| | - Qianqian Yang
- School of Mathematical Sciences, Faculty of Science, Queensland University of TechnologyBrisbaneAustralia
- Centre for Data Science, Queensland University of TechnologyBrisbaneAustralia
- Centre for Biomedical Technologies, Queensland University of TechnologyBrisbaneAustralia
| | - Viktor Vegh
- Centre for Advanced Imaging, The University of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging TechnologyBrisbaneAustralia
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Genç B, Aslan K, Özçağlayan A, İncesu L. Microstructural Abnormalities in the Contralateral Normal-appearing White Matter of Glioblastoma Patients Evaluated with Advanced Diffusion Imaging. Magn Reson Med Sci 2024; 23:479-486. [PMID: 37532585 PMCID: PMC11447469 DOI: 10.2463/mrms.mp.2023-0054] [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: 05/25/2023] [Accepted: 06/30/2023] [Indexed: 08/04/2023] Open
Abstract
PURPOSE Glioblastoma patients develop recurrence in the opposite hemisphere far from the primary tumor site even after complete resection. This is one of the main reasons for short disease survival. Our aim in this study is to detect microstructural changes in the contralateral hemisphere of glioblastoma patients using different diffusion models with the fully automated tract-based spatial statistics (TBSS) method. METHODS Fourteen right-sided and eleven left-sided glioblastoma patients without any treatment and eighteen age- and gender-matched controls were included in the study. Multi-shell diffusion weighted images were created with a 3T MRI device. After various preprocessing steps, images of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK), intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic water fraction (ISO) were obtained. TBSS was used to compare diffusion tensor imaging, diffusion kurtosis imaging, and neurite orientation dispersion and density imaging parameters of right- and left-sided glioblastoma patients with the control group for the contralateral hemisphere. RESULTS Both right-sided and left-sided glioblastoma patients have shown an increase in MD and ODI in the contralateral hemisphere. While right-sided glioblastoma patients showed an increase in RD, AD, and ISO in a more limited area in the contralateral hemisphere, left-sided glioblastoma patients showed an increase in MK and AK. FA, ICVF, and RK did not show any difference in both groups. CONCLUSION There are microstructural changes in the contralateral hemisphere in glioblastoma patients, and these changes differ between right-sided and left-sided glioblastoma patients.
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Affiliation(s)
- Barış Genç
- Department of Radiology, Samsun Education and Research Hospital, İlkadım, Samsun, Turkey
| | - Kerim Aslan
- Department of Radiology, Ondokuz Mayis University, Faculty of Medicine, İlkadım, Samsun, Turkey
| | - Ali Özçağlayan
- Department of Radiology, Ondokuz Mayis University, Faculty of Medicine, İlkadım, Samsun, Turkey
| | - Lütfi İncesu
- Department of Radiology, Ondokuz Mayis University, Faculty of Medicine, İlkadım, Samsun, Turkey
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Fouto AR, Henriques RN, Golub M, Freitas AC, Ruiz-Tagle A, Esteves I, Gil-Gouveia R, Silva NA, Vilela P, Figueiredo P, Nunes RG. Impact of truncating diffusion MRI scans on diffusional kurtosis imaging. MAGMA (NEW YORK, N.Y.) 2024; 37:859-872. [PMID: 38393541 PMCID: PMC11452422 DOI: 10.1007/s10334-024-01153-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/09/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024]
Abstract
OBJECTIVE Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects but requires longer acquisition times. To ensure the robustness of DKI parameters, data acquisition ordering should be optimized allowing for scan interruptions or shortening. Three methodologies were used to examine how reduced diffusion MRI scans impact DKI histogram-metrics: 1) the electrostatic repulsion model (OptEEM); 2) spherical codes (OptSC); 3) random (RandomTRUNC). MATERIALS AND METHODS Pre-acquired diffusion multi-shell data from 14 female healthy volunteers (29±5 years) were used to generate reordered data. For each strategy, subsets containing different amounts of the full dataset were generated. The subsampling effects were assessed on histogram-based DKI metrics from tract-based spatial statistics (TBSS) skeletonized maps. To evaluate each subsampling method on simulated data at different SNRs and the influence of subsampling on in vivo data, we used a 3-way and 2-way repeated measures ANOVA, respectively. RESULTS Simulations showed that subsampling had different effects depending on DKI parameter, with fractional anisotropy the most stable (up to 5% error) and radial kurtosis the least stable (up to 26% error). RandomTRUNC performed the worst while the others showed comparable results. Furthermore, the impact of subsampling varied across distinct histogram characteristics, the peak value the least affected (OptEEM: up to 5% error; OptSC: up to 7% error) and peak height (OptEEM: up to 8% error; OptSC: up to 11% error) the most affected. CONCLUSION The impact of truncation depends on specific histogram-based DKI metrics. The use of a strategy for optimizing the acquisition order is advisable to improve DKI robustness to exam interruptions.
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Affiliation(s)
- Ana R Fouto
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
| | | | - Marc Golub
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Andreia C Freitas
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Amparo Ruiz-Tagle
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Inês Esteves
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Raquel Gil-Gouveia
- Neurology Department, Hospital da Luz, Lisbon, Portugal
- Center for Interdisciplinary Research in Health, Universidade Católica Portuguesa, Lisbon, Portugal
| | - Nuno A Silva
- Learning Health, Hospital da Luz, Lisbon, Portugal
| | - Pedro Vilela
- Imaging Department, Hospital da Luz, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Rita G Nunes
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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Zhou M, Chen M, Chen M, Yan X, Yang G, Huang H. Predictive value of mono-exponential and multiple mathematical models in locally advanced rectal cancer response to neoadjuvant chemoradiotherapy. Abdom Radiol (NY) 2024:10.1007/s00261-024-04588-y. [PMID: 39276193 DOI: 10.1007/s00261-024-04588-y] [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: 08/10/2024] [Revised: 09/05/2024] [Accepted: 09/09/2024] [Indexed: 09/16/2024]
Abstract
PURPOSE This prospective study aimed to assess the predictive value of mono-exponential and multiple mathematical diffusion-weighted imaging (DWI) models in determining the response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). METHODS The study included 103 LARC patients scheduled for preoperative chemoradiotherapy between December 2021 and June 2023 Magnetic resonance imaging (MRI) scans were performed using a 3.0-T MR scanner, encompassing sagittal, axial, and oblique coronal T2-weighted images without fat saturation, along with DWI perpendicular to the rectum's long axis. Various DWI parameters, including apparent diffusion coefficient (ADC), stretched exponential model (SEM), continuous-time random-walk model (CTRW), and fractional-order calculus model (FROC), were measured. The pathologic complete response (pCR) rate and tumor downstaging (T-downstage) rate were determined. RESULTS After nCRT, SEM-α, SEM-DDC, CTRW-α, CTRW-β, CTRW-D, FROC-β, and ADC values were significantly higher in the pCR group compared to the non-pCR group (all P < 0.05). SEM-DDC, CTRW-α, CTRW-D, FROC-β, FROC-µ, and ADC values were significantly higher in the T-downstage group (ypT0-1) than in the non-T-downstage group (ypT2-4) (P < 0.05). The combination of CTRW (α + β + D) exhibited the best diagnostic performance for assessing pCR after nCRT (AUC = 0.840, P < 0.001). Pre-nCRT CTRW (α + β) demonstrated a predictive AUC of 0.652 (95%CI: 0.552-0.743), 90.3% sensitivity, and 43.1% specificity for pCR. Regarding T-downstage assessment after nCRT, the combination of CTRW (α + D) yielded the best diagnostic performance (AUC = 0.877, P = 0.048). CONCLUSION In LARC patients, imaging markers derived from CTRW show promise in predicting tumor response before nCRT and assessing pCR after nCRT.
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Affiliation(s)
- Mi Zhou
- sichuan provincial orthopedics hospital, Chengdu, China
| | - Mengyuan Chen
- Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Xu Yan
- Siemens Healthineers (China), Pudong, China
| | - Guang Yang
- East China Normal University, Shanghai, China
| | - Hongyun Huang
- Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
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Li J, Zhang H, Bei T, Wang Y, Ma F, Wang S, Li H, Qu J. Advanced diffusion-weighted MRI models for preoperative prediction of lymph node metastasis in resectable gastric cancer. Abdom Radiol (NY) 2024:10.1007/s00261-024-04559-3. [PMID: 39254709 DOI: 10.1007/s00261-024-04559-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 08/20/2024] [Accepted: 08/29/2024] [Indexed: 09/11/2024]
Abstract
OBJECTIVE To investigate the potential of six advanced diffusion-weighted imaging (DWI) models for preoperative prediction of lymph node metastasis (LNM) in resectable gastric cancer (GC). METHODS Between Nov 2022 and Nov 2023, standard MRI scans were prospectively performed in consecutive patients with endoscopic pathology-confirmed gastric adenocarcinoma who were referred for direct radical gastrectomy. Six DWI models, including fractional order calculus (FROC), continuous-time random walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), the mono-exponential model (MEM) and the stretched exponential model (SEM) were computed. Surgical pathologic diagnosis of LNM was the reference standard, and patients were classified into LNM-positive or LNM-negative groups accordingly. The morphological features and quantitative parameters of the DWI models in different LNM categories were analyzed and compared. Multivariable logistic regression was used to screen significant predictors. Receiver-operating characteristic curves and the area under the curve (AUC) were plotted to evaluate the performances, the Delong test was performed to compare the AUCs. RESULTS In the LNM-positive group, tumor thickness and kurtosis (DKI_K) were significantly higher, while anomalous diffusion coefficient (CTRW_D), diffusivity (DKI_D), diffusion coefficient (FROC_D), pseudodiffusion coefficient (IVIM_D*), perfusion fraction (IVIM_f), and ADC were lower compared to the LNM-negative group. Clinical tumor staging (cT) and CTRW_D were independent predictors. Their combination demonstrated a superior AUC of 0.930, significantly higher than that of individual parameters. CONCLUSIONS Tumor thickness, DKI_K, CTRW_D, DKI_D, FROC_D, IVIM_D*, IVIM_f and ADC were associated with LNM status. The combination of independent predictors of cT and CTRW_D further enhanced the performance.
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Affiliation(s)
- Jing Li
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
| | - Hongkai Zhang
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Tianxia Bei
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Yi Wang
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Fei Ma
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Shaoyu Wang
- MR Research Collaboration, Siemens Healthineers, Shanghai, China
| | - Haocheng Li
- Sanquan College of Xinxiang Medical University, Xinxiang, China
| | - Jinrong Qu
- The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
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Shamir I, Assaf Y. Tutorial: a guide to diffusion MRI and structural connectomics. Nat Protoc 2024:10.1038/s41596-024-01052-5. [PMID: 39232202 DOI: 10.1038/s41596-024-01052-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/09/2024] [Indexed: 09/06/2024]
Abstract
Diffusion magnetic resonance imaging (dMRI) is a versatile imaging technique that has gained popularity thanks to its sensitive ability to measure displacement of water molecules within a living tissue on a micrometer scale. Although dMRI has been around since the early 1990s, its applications are constantly evolving, primarily regarding the inference of structural connectomics from nerve fiber trajectories. However, these applications require expertise in image processing and statistics, and it can be difficult for a newcomer to choose an appropriate pipeline to fit their research needs, not least because dMRI is such a flexible methodology that dozens of acquisition and analysis pipelines have been developed over the years. This introductory guide is designed for graduate students and researchers in the neuroscience community who are interested in integrating this new methodology regardless of their background in neuroimaging and computational tools. The guide provides a brief overview of the basic dMRI methodologies but focuses on its applications in neuroplasticity and connectomics. The guide starts with dMRI experimental designs and a complete step-by-step pipeline for structural connectomics. The following section covers the basics of dMRI, including parameters and clinical applications (apparent diffusion coefficient, mean diffusivity, fractional anisotropy and microscopic fractional anisotropy), as well as different approaches and models. The final section focuses on structural connectomics, covering subjects from fiber tracking (techniques, evaluation and limitations) to structural networks (constructing, analyzing and visualizing a network).
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Affiliation(s)
- Ittai Shamir
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaniv Assaf
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
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Zhou M, Bao D, Huang H, Chen M, Jiang W. Utilization of diffusion-weighted derived mathematical models to predict prognostic factors of resectable rectal cancer. Abdom Radiol (NY) 2024; 49:3282-3293. [PMID: 38744701 DOI: 10.1007/s00261-024-04239-2] [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: 12/21/2023] [Revised: 02/05/2024] [Accepted: 02/05/2024] [Indexed: 05/16/2024]
Abstract
PURPOSE This study explored models of monoexponential diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), stretched exponential (SEM), fractional-order calculus (FROC), and continuous-time random-walk (CTRW) as diagnostic tools for assessing pathological prognostic factors in patients with resectable rectal cancer (RRC). METHODS RRC patients who underwent radical surgery were included. The apparent diffusion coefficient (ADC), the mean kurtosis (MK) and mean diffusion (MD) from the DKI model, the distributed diffusion coefficient (DDC) and α from the SEM model, D, β and u from the FROC model, and D, α and β from the CTRW model were assessed. RESULTS There were a total of 181 patients. The area under the receiver operating characteristic (ROC) curve (AUC) of CTRW-α for predicting histology type was significantly higher than that of FROC-u (0.780 vs. 0.671, p = 0.043). The AUC of CTRW-α for predicting pT stage was significantly higher than that of FROC-u and ADC (0.786 vs.0.683, p = 0.043; 0.786 vs. 0.682, p = 0.030), the difference in predictive efficacy of FROC-u between ADC and MK was not statistically significant [0.683 vs. 0.682, p = 0.981; 0.683 vs. 0.703, p = 0.720]; the difference between the predictive efficacy of MK and ADC was not statistically significant (p = 0.696). The AUC of CTRW (α + β) (0.781) was significantly higher than that of FROC-u (0.781 vs. 0.625, p = 0.003) in predicting pN stage but not significantly different from that of MK (p = 0.108). CONCLUSION The CTRW and DKI models may serve as imaging biomarkers to predict pathological prognostic factors in RRC patients before surgery.
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Affiliation(s)
- Mi Zhou
- Department of Radiology, Sichuan Provincial Orthopedic Hospital, Chengdu, China.
| | - Deying Bao
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Hongyun Huang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Meining Chen
- Department of MR Scientific Marketing, Siemens Healthineers, Shanghai, 200135, China
| | - Wenli Jiang
- Department of Radiology, Second Affiliated Hospital of Chongqing University of Medical Sciences, Chongqing, 400010, China
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Das CJ, Malagi AV, Sharma R, Mehndiratta A, Kumar V, Khan MA, Seth A, Kaushal S, Nayak B, Kumar R, Gupta AK. Intravoxel incoherent motion and diffusion kurtosis imaging and their machine-learning-based texture analysis for detection and assessment of prostate cancer severity at 3 T. NMR IN BIOMEDICINE 2024; 37:e5144. [PMID: 38556777 DOI: 10.1002/nbm.5144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 02/01/2024] [Accepted: 02/20/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVES To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa). MATERIALS AND METHODS Eighty-eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM-DKI data were acquired using 13 b values (0-2000 s/mm2) and analyzed using the IVIM-DKI model with the total variation (TV) method. PCa patients were categorized into two groups: clinically insignificant prostate cancer (CISPCa) (Gleason grade ≤ 6) and clinically significant prostate cancer (CSPCa) (Gleason grade ≥ 7). One-way analysis-of-variance, t test, and receiver operating characteristic analysis was performed to measure the discriminative ability to detect PCa using IVIM-DKI parameters. A chi-square test was used to select important texture features of apparent diffusion coefficient (ADC) and IVIM-DKI parameters. These selected texture features were used in an artificial neural network for PCa detection. RESULTS ADC and diffusion coefficient (D) were significantly lower (p < 0.001), and kurtosis (k) was significantly higher (p < 0.001), in PCa as compared with benign prostatic hyperplasia (BPH) and normal peripheral zone (PZ). ADC, D, and k showed high areas under the curves (AUCs) of 0.92, 0.89, and 0.88, respectively, in PCa detection. ADC and D were significantly lower (p < 0.05) as compared with CISPCa versus CSPCa. D for detecting CSPCa was high, with an AUC of 0.63. A negative correlation of ADC and D with GS (ADC, ρ = -0.33; D, ρ = -0.35, p < 0.05) and a positive correlation of k with GS (ρ = 0.22, p < 0.05) were observed. Combined IVIM-DKI texture showed high AUC of 0.83 for classification of PCa, BPH, and normal PZ. CONCLUSION D, f, and k computed using the IVIM-DKI model with the TV method were able to differentiate PCa from BPH and normal PZ. Texture features of combined IVIM-DKI parameters showed high accuracy and AUC in PCa detection.
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Affiliation(s)
- Chandan J Das
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Archana Vadiraj Malagi
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Raju Sharma
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Amit Mehndiratta
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Virendra Kumar
- Department of Nuclear Magnetic Resonance, All India Institute of Medical Sciences, New Delhi, India
| | - Maroof A Khan
- Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
| | - Amlesh Seth
- Department of Urology, All India Institute of Medical Sciences, New Delhi, India
| | - Seema Kaushal
- Department of Pathology, All India Institute of Medical Sciences, New Delhi, India
| | - Baibaswata Nayak
- Department of Gastroenterology (Molecular Biology Division), All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Arun Kumar Gupta
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
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11
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Khosdelazad S, van der Horn HJ, Jorna LS, Groen RJM, van der Hoorn A, Rakers SE, Buunk AM, Spikman JM. White matter abnormalities in aneurysmal and angiographically negative subarachnoid hemorrhage: A diffusion kurtosis imaging study. Neuroimage Clin 2024; 43:103662. [PMID: 39232414 DOI: 10.1016/j.nicl.2024.103662] [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: 01/17/2024] [Revised: 08/13/2024] [Accepted: 08/25/2024] [Indexed: 09/06/2024]
Abstract
OBJECTIVE Aneurysmal subarachnoid hemorrhage (aSAH) and angiographically negative subarachnoid hemorrhage (anSAH) cause an abrupt rise in intracranial pressure, resulting in shearing forces, causing damage to the white matter tracts. This study aims to investigate whole-brain white matter abnormalities with diffusion kurtosis imaging (DKI) after both aSAH and anSAH and explores whether these abnormalities are associated with impaired cognitive functioning. METHODS Five months post-ictus, 34 patients with aSAH, 24 patients with anSAH and 17 healthy controls (HC) underwent DKI MRI scanning and neuropsychological assessment (measuring verbal memory, psychomotor speed, executive control, and social cognition). Differences in DKI measures (fractional anisotropy, mean diffusivity, axial diffusivity [AD], radial diffusivity, and mean kurtosis) were examined using tract-based spatial statistics. Significant voxel masks were then correlated with neuropsychological scores. RESULTS All DKI measures differed significantly between patients with aSAH and HC, but no significant differences were found between patients with anSAH and HC. Although the two SAH groups did not differ significantly on all DKI parameters, effect sizes indicated that the anSAH group might be more similar to HC. Cognitive impairments were found for both SAH groups relative to HC. No significant associations were found between these impairments and white matter abnormalities in the aSAH group, but lower psychomotor speed scores were associated with higher AD values (r = -0.41, p = 0.04) in patients with anSAH. CONCLUSIONS Patients with aSAH showed significant white matter diffusion abnormalities, while the anSAH group, despite cognitive deficits, did not. However, there were no significant differences between the SAH groups, and no correlations between DKI metrics and cognitive measures, except for one test on psychomotor speed in the anSAH group. Overall, this study suggests that while anSAH may not be as severe as aSAH, it is still not a benign condition. Further research with larger anSAH cohorts is necessary to gain a more precise understanding of white matter injuries, particularly regarding their prevalence.
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Affiliation(s)
- Sara Khosdelazad
- Department of Neurology, unit Neuropsychology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
| | - Harm J van der Horn
- Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - Lieke S Jorna
- Department of Neurology, unit Neuropsychology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - Rob J M Groen
- Department of Neurosurgery, University Medical Centre Groningen, University of Groningen, the Netherlands; Department of Neurosurgery, Faculty of Medicine Universitas Airlangga, Dr. Soetomo General Academic Hospital, Surabaya, Indonesia
| | - Anouk van der Hoorn
- Department of Radiology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - Sandra E Rakers
- Department of Neurology, unit Neuropsychology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - Anne M Buunk
- Department of Neurology, unit Neuropsychology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands; Department of Neurosurgery, University Medical Centre Groningen, University of Groningen, the Netherlands
| | - Jacoba M Spikman
- Department of Neurology, unit Neuropsychology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
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12
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Salazar CA, Welsh JM, Lench D, Harmsen IE, Jensen JH, Grewal P, Yazdani M, Al Kasab S, Spiotta A, Bonilha L, George MS, Kautz SA, Rowland NC. Concurrent tDCS-fMRI after stroke reveals link between attention network organization and motor improvement. Sci Rep 2024; 14:19334. [PMID: 39164440 PMCID: PMC11336178 DOI: 10.1038/s41598-024-70083-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 08/12/2024] [Indexed: 08/22/2024] Open
Abstract
Restoring motor function after stroke necessitates involvement of numerous cognitive systems. However, the impact of damage to motor and cognitive network organization on recovery is not well understood. To discover correlates of successful recovery, we explored imaging characteristics in chronic stroke subjects by combining noninvasive brain stimulation and fMRI. Twenty stroke survivors (6 months or more after stroke) were randomly assigned to a single session of transcranial direct current stimulation (tDCS) or sham during image acquisition. Twenty healthy subjects were included as controls. tDCS was limited to 10 min at 2 mA to serve as a mode of network modulation rather than therapeutic delivery. Fugl-Meyer Assessments (FMA) revealed significant motor improvement in the chronic stroke group receiving active stimulation (p = 0.0005). Motor changes in this group were correlated in a data-driven fashion with imaging features, including functional connectivity (FC), surface-based morphometry, electric field modeling and network topology, focusing on relevant regions of interest. We observed stimulation-related changes in FC in supplementary motor (p = 0.0029), inferior frontal gyrus (p = 0.0058), and temporo-occipital (p = 0.0095) areas, though these were not directly related to motor improvement. The feature most strongly associated with FMA improvement in the chronic stroke cohort was graph topology of the dorsal attention network (DAN), one of the regions surveyed and one with direct connections to each of the areas with FC changes. Chronic stroke subjects with a greater degree of motor improvement had lower signal transmission cost through the DAN (p = 0.029). While the study was limited by a small stroke cohort with moderate severity and variable lesion location, these results nevertheless suggest a top-down role for higher order areas such as attention in helping to orchestrate the stroke recovery process.
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Affiliation(s)
- Claudia A Salazar
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, 96 Jonathan Lucas St., CSB301 MSC606, Charleston, SC, 29425, USA
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA
| | - James M Welsh
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, 96 Jonathan Lucas St., CSB301 MSC606, Charleston, SC, 29425, USA
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA
| | - Daniel Lench
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Irene E Harmsen
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada
| | - Jens H Jensen
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Parneet Grewal
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Milad Yazdani
- Department of Radiology and Radiological Science, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Sami Al Kasab
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, 96 Jonathan Lucas St., CSB301 MSC606, Charleston, SC, 29425, USA
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Alex Spiotta
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, 96 Jonathan Lucas St., CSB301 MSC606, Charleston, SC, 29425, USA
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Leonardo Bonilha
- Department of Neurology, College of Medicine, University of South Carolina, Columbia, SC, USA
| | - Mark S George
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA
- Ralph H. Johnson VA Medical Center, Charleston, SC, USA
- Department of Psychiatry, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Steven A Kautz
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA
- MUSC Institute for Neuroscience Discovery (MIND), Medical University of South Carolina, Charleston, SC, USA
| | - Nathan C Rowland
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, 96 Jonathan Lucas St., CSB301 MSC606, Charleston, SC, 29425, USA.
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA.
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA.
- MUSC Institute for Neuroscience Discovery (MIND), Medical University of South Carolina, Charleston, SC, USA.
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13
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Karat BG, Genc S, Raven EP, Palombo M, Khan AR, Jones DK. The developing hippocampus: Microstructural evolution through childhood and adolescence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.19.608590. [PMID: 39229062 PMCID: PMC11370384 DOI: 10.1101/2024.08.19.608590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.
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Affiliation(s)
- Bradley G Karat
- Robarts Research Institute, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
| | - Sila Genc
- Department of Neurosurgery, The Royal Children's Hospital, Melbourne, Australia
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | - Ali R Khan
- Robarts Research Institute, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
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14
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Sacchi L, D'Agata F, Campisi C, Arcaro M, Carandini T, Örzsik B, Dal Maschio VP, Fenoglio C, Pietroboni AM, Ghezzi L, Serpente M, Pintus M, Conte G, Triulzi F, Lopiano L, Galimberti D, Cercignani M, Bozzali M, Arighi A. A "glympse" into neurodegeneration: Diffusion MRI and cerebrospinal fluid aquaporin-4 for the assessment of glymphatic system in Alzheimer's disease and other dementias. Hum Brain Mapp 2024; 45:e26805. [PMID: 39185685 PMCID: PMC11345637 DOI: 10.1002/hbm.26805] [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: 02/03/2024] [Revised: 06/17/2024] [Accepted: 07/17/2024] [Indexed: 08/27/2024] Open
Abstract
The glymphatic system (GS) is a whole-brain perivascular network, consisting of three compartments: the periarterial and perivenous spaces and the interposed brain parenchyma. GS dysfunction has been implicated in neurodegenerative diseases, particularly Alzheimer's disease (AD). So far, comprehensive research on GS in humans has been limited by the absence of easily accessible biomarkers. Recently, promising non-invasive methods based on magnetic resonance imaging (MRI) along with aquaporin-4 (AQP4) quantification in the cerebrospinal fluid (CSF) were introduced for an indirect assessment of each of the three GS compartments. We recruited 111 consecutive subjects presenting with symptoms suggestive of degenerative cognitive decline, who underwent 3 T MRI scanning including multi-shell diffusion-weighted images. Forty nine out of 111 also underwent CSF examination with quantification of CSF-AQP4. CSF-AQP4 levels and MRI measures-including perivascular spaces (PVS) counts and volume fraction (PVSVF), white matter free water fraction (FW-WM) and mean kurtosis (MK-WM), diffusion tensor imaging analysis along the perivascular spaces (DTI-ALPS) (mean, left and right)-were compared among patients with AD (n = 47) and other neurodegenerative diseases (nAD = 24), patients with stable mild cognitive impairment (MCI = 17) and cognitively unimpaired (CU = 23) elderly people. Two runs of analysis were conducted, the first including all patients; the second after dividing both nAD and AD patients into two subgroups based on gray matter atrophy as a proxy of disease stage. Age, sex, years of education, and scanning time were included as confounding factors in the analyses. Considering the whole cohort, patients with AD showed significantly higher levels of CSF-AQP4 (exp(b) = 2.05, p = .005) and FW-WM FW-WM (exp(b) = 1.06, p = .043) than CU. AQP4 levels were also significantly higher in nAD in respect to CU (exp(b) = 2.98, p < .001). CSF-AQP4 and FW-WM were significantly higher in both less atrophic AD (exp(b) = 2.20, p = .006; exp(b) = 1.08, p = .019, respectively) and nAD patients (exp(b) = 2.66, p = .002; exp(b) = 1.10, p = .019, respectively) compared to CU subjects. Higher total (exp(b) = 1.59, p = .013) and centrum semiovale PVS counts (exp(b) = 1.89, p = .016), total (exp(b) = 1.50, p = .036) and WM PVSVF (exp(b) = 1.89, p = .005) together with lower MK-WM (exp(b) = 0.94, p = .006), mean and left ALPS (exp(b) = 0.91, p = .043; exp(b) = 0.88, p = .010 respectively) were observed in more atrophic AD patients in respect to CU. In addition, more atrophic nAD patients exhibited higher levels of AQP4 (exp(b) = 3.39, p = .002) than CU. Our results indicate significant changes in putative MRI biomarkers of GS and CSF-AQP4 levels in AD and in other neurodegenerative dementias, suggesting a close interaction between glymphatic dysfunction and neurodegeneration, particularly in the case of AD. However, the usefulness of some of these biomarkers as indirect and standalone indices of glymphatic activity may be hindered by their dependence on disease stage and structural brain damage.
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Affiliation(s)
- Luca Sacchi
- Department of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | - Federico D'Agata
- Department of Neurosciences “Rita Levi Montalcini”University of TurinTurinItaly
| | - Corrado Campisi
- Department of Neurosciences “Rita Levi Montalcini”University of TurinTurinItaly
| | - Marina Arcaro
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
| | - Tiziana Carandini
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
| | - Balázs Örzsik
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Vera Pacoova Dal Maschio
- Department of Neurosciences “Rita Levi Montalcini”University of TurinTurinItaly
- Neurology 2 Unit, A.O.U. Città della Salute e Della Scienza di TorinoTurinItaly
| | - Chiara Fenoglio
- Department of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | | | - Laura Ghezzi
- Department of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | - Maria Serpente
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
| | - Manuela Pintus
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
| | - Giorgio Conte
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
- Department of Pathophysiology and TransplantationUniversity of MilanMilanItaly
| | - Fabio Triulzi
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
- Department of Pathophysiology and TransplantationUniversity of MilanMilanItaly
| | - Leonardo Lopiano
- Department of Neurosciences “Rita Levi Montalcini”University of TurinTurinItaly
- Neurology 2 Unit, A.O.U. Città della Salute e Della Scienza di TorinoTurinItaly
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | | | - Marco Bozzali
- Department of Neurosciences “Rita Levi Montalcini”University of TurinTurinItaly
- Neurology 2 Unit, A.O.U. Città della Salute e Della Scienza di TorinoTurinItaly
| | - Andrea Arighi
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore PoliclinicoMilanItaly
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15
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Mohamed GA, Lench DH, Grewal P, Rosenberg M, Voeks J. Stem cell therapy: a new hope for stroke and traumatic brain injury recovery and the challenge for rural minorities in South Carolina. Front Neurol 2024; 15:1419867. [PMID: 39184380 PMCID: PMC11342809 DOI: 10.3389/fneur.2024.1419867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 07/16/2024] [Indexed: 08/27/2024] Open
Abstract
Stroke and traumatic brain injury (TBI) are a significant cause of death and disability nationwide. Both are considered public health concerns in rural communities in the state of South Carolina (SC), particularly affecting the African American population resulting in considerable morbidity, mortality, and economic burden. Stem cell therapy (SCT) has emerged as a potential intervention for both diseases with increasing research trials showing promising results. In this perspective article, the authors aim to discuss the current research in the field of SCT, the results of early phase trials, and the utilization of outcome measures and biomarkers of recovery. We searched PubMed from inception to December 2023 for articles on stem cell therapy in stroke and traumatic brain injury and its impact on rural communities, particularly in SC. Early phase trials of SCT in Stroke and Traumatic Brain injury yield promising safety profile and efficacy results, but the findings have not yet been consistently replicated. Early trials using mesenchymal stem cells for stroke survivors showed safety, feasibility, and improved functional outcomes using broad and domain-specific outcome measures. Neuroimaging markers of recovery such as Functional Magnetic Resonance Imaging (fMRI) and electroencephalography (EEG) combined with neuromodulation, although not widely used in SCT research, could represent a breakthrough when evaluating brain injury and its functional consequences. This article highlights the role of SCT as a promising intervention while addressing the underlying social determinants of health that affect therapeutic outcomes in relation to rural communities such as SC. It also addresses the challenges ethical concerns of stem cell sourcing, the high cost of autologous cell therapies, and the technical difficulties in ensuring transplanted cell survival and strategies to overcome barriers to clinical trial enrollment such as the ethical concerns of stem cell sourcing, the high cost of autologous cell therapies, and the technical difficulties in ensuring transplanted cell survival and equitable healthcare.
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Affiliation(s)
- Ghada A. Mohamed
- Department of Neurology, Medical University of South Carolina, Charleston, SC, United States
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16
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Nelson MR, Keeling EG, Stokes AM, Bergamino M. Exploring white matter microstructural alterations in mild cognitive impairment: a multimodal diffusion MRI investigation utilizing diffusion kurtosis and free-water imaging. Front Neurosci 2024; 18:1440653. [PMID: 39170682 PMCID: PMC11335656 DOI: 10.3389/fnins.2024.1440653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 07/22/2024] [Indexed: 08/23/2024] Open
Abstract
Background Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear. Methods This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI). Results Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment. Conclusion In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline.
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Affiliation(s)
- Megan R. Nelson
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Elizabeth G. Keeling
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Ashley M. Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Maurizio Bergamino
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
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17
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Chacko AN, Miller ADC, Dhanabalan KM, Mukherjee A. Exploring the potential of water channels for developing genetically encoded reporters and biosensors for diffusion-weighted MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2024; 365:107743. [PMID: 39053029 DOI: 10.1016/j.jmr.2024.107743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 07/02/2024] [Accepted: 07/17/2024] [Indexed: 07/27/2024]
Abstract
Genetically encoded reporters for magnetic resonance imaging (MRI) offer a valuable technology for making molecular-scale measurements of biological processes within living organisms with high anatomical resolution and whole-organ coverage without relying on ionizing radiation. However, most MRI reporters rely on synthetic contrast agents, typically paramagnetic metals and metal complexes, which often need to be supplemented exogenously to create optimal contrast. To eliminate the need for synthetic contrast agents, we previously introduced aquaporin-1, a mammalian water channel, as a new reporter gene for the fully autonomous detection of genetically labeled cells using diffusion-weighted MRI. In this study, we aimed to expand the toolbox of diffusion-based genetic reporters by modulating aquaporin membrane trafficking and harnessing the evolutionary diversity of water channels across species. We identified a number of new water channels that functioned as diffusion-weighted reporter genes. In addition, we show that loss-of-function variants of yeast and human aquaporins can be leveraged to design first-in-class diffusion-based sensors for detecting the activity of a model protease within living cells.
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Affiliation(s)
- Asish N Chacko
- Department of Chemistry, University of California, Santa Barbara, CA 93106-5080, USA
| | - Austin D C Miller
- Biomolecular Science and Engineering Graduate Program, University of California, Santa Barbara, CA 93106-5080, USA
| | - Kaamini M Dhanabalan
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, USA
| | - Arnab Mukherjee
- Department of Chemistry, University of California, Santa Barbara, CA 93106-5080, USA; Biomolecular Science and Engineering Graduate Program, University of California, Santa Barbara, CA 93106-5080, USA; Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, USA; Department of Bioengineering, University of California, Santa Barbara, CA 93106-5080, USA.
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18
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Kisohara M, Hiwatashi A. Editorial for "MR Diffusion Kurtosis Imaging (DKI) of the Normal Human Uterus in Vivo During the Menstrual Cycle". J Magn Reson Imaging 2024; 60:481-482. [PMID: 38014864 DOI: 10.1002/jmri.29151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 11/29/2023] Open
Affiliation(s)
- Masaya Kisohara
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Akio Hiwatashi
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
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Li Y, Chen Y, Fu C, Li Q, Liu H, Zhang Q. MR Diffusion Kurtosis Imaging (DKI) of the Normal Human Uterus in Vivo During the Menstrual Cycle. J Magn Reson Imaging 2024; 60:471-480. [PMID: 37994206 DOI: 10.1002/jmri.29153] [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: 08/02/2023] [Revised: 11/10/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND The uterus undergoes dynamic changes throughout the menstrual cycle. Diffusion kurtosis imaging (DKI) is based on the non-Gaussian distribution of water molecules and can perhaps represent the changes of uterine microstructure. PURPOSE To investigate the temporal changes in DKI-parameters of the normal uterine corpus and cervix during the menstrual cycle. STUDY TYPE Prospective. POPULATION 21 healthy female volunteers (26.64 ± 4.72 years) with regular menstrual cycles (28 ± 7 days). FIELD STRENGTH/SEQUENCE Readout segmentation of long variable echo-trains (RESOLVE)-based DKI and fast spin-echo T2-weighted sequences at 3.0T. ASSESSMENT Each volunteer was scanned during the menstrual phase, ovulatory phase, and luteal phase. Regions of interest (ROI) were manually delineated in the endometrium, junctional zone, and myometrium of the uterine body, and in the mucosal layer, fibrous stroma layer, and loose stroma layer of the cervix. The mean Kapp (diffusion kurtosis coefficient), Dapp (diffusion coefficient), and ADC (apparent diffusion coefficient) values were measured in the ROI. STATISTICAL TESTS ANOVA with Bonferroni or Tamhane correction. Intraclass correlation coefficient (ICC) for assessing agreement. P < 0.05 was considered statistically significant. RESULTS During the menstrual cycle, the highest Kapp (0.848 ± 0.184) and lowest Dapp (1.263 ± 0.283 *10-3 mm2/sec) values were found in the endometrium during the menstrual phase. The Dapp values for the myometrium were significantly higher than those of the endometrium and the junctional zone in every phase. Meanwhile, the Dapp values for the three zonal structures of the cervix during ovulation were significantly higher than those during the luteal phase. However, there was no significant difference in the ADC values of the loose stroma between ovulation and the luteal phase (P = 0.568). The reproducibility of DKI parameters was good (ICC, 0.857-0.944). DATA CONCLUSION DKI can show dynamic changes of the normal uterus during the menstrual cycle. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yajie Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Shanghai Institute of Medical Imaging, Shanghai, China
| | - Ye Chen
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Caixia Fu
- MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | - Qing Li
- MR Collaborations, Siemens Healthineers Digital Technology (Shanghai) Co., Ltd., Shanghai, China
| | - Hanqiu Liu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Shanghai Institute of Medical Imaging, Shanghai, China
| | - Qi Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
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Zerweck L, Hauser TK, Klose U, Han T, Nägele T, Shen M, Gohla G, Estler A, Xie C, Hu H, Yang S, Cao Z, Erb G, Ernemann U, Richter V. Glioma Type Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Kurtosis Imaging-A Standardized Multicenter Study. Cancers (Basel) 2024; 16:2644. [PMID: 39123372 PMCID: PMC11311685 DOI: 10.3390/cancers16152644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/23/2024] [Accepted: 07/23/2024] [Indexed: 08/12/2024] Open
Abstract
The aim was to explore the performance of dynamic contrast-enhanced (DCE) MRI and diffusion kurtosis imaging (DKI) in differentiating the molecular subtypes of adult-type gliomas. A multicenter MRI study with standardized imaging protocols, including DCE-MRI and DKI data of 81 patients with WHO grade 2-4 gliomas, was performed at six centers. The DCE-MRI and DKI parameter values were quantitatively evaluated in ROIs in tumor tissue and contralateral normal-appearing white matter. Binary logistic regression analyses were performed to differentiate between high-grade (HGG) vs. low-grade gliomas (LGG), IDH1/2 wildtype vs. mutated gliomas, and high-grade astrocytic tumors vs. high-grade oligodendrogliomas. Receiver operating characteristic (ROC) curves were generated for each parameter and for the regression models to determine the area under the curve (AUC), sensitivity, and specificity. Significant differences between tumor groups were found in the DCE-MRI and DKI parameters. A combination of DCE-MRI and DKI parameters revealed the best prediction of HGG vs. LGG (AUC = 0.954 (0.900-1.000)), IDH1/2 wildtype vs. mutated gliomas (AUC = 0.802 (0.702-0.903)), and astrocytomas/glioblastomas vs. oligodendrogliomas (AUC = 0.806 (0.700-0.912)) with the lowest Akaike information criterion. The combination of DCE-MRI and DKI seems helpful in predicting glioma types according to the 2021 World Health Organization's (WHO) classification.
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Affiliation(s)
- Leonie Zerweck
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Till-Karsten Hauser
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Uwe Klose
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Tong Han
- Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Thomas Nägele
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Mi Shen
- Department of Radiology, Beijing Tian Tan Hospital, Capital Medical University, Beijing 100050, China
| | - Georg Gohla
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Arne Estler
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Chuanmiao Xie
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Hongjie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310018, China
| | - Songlin Yang
- Department of Radiology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519082, China
| | - Zhijian Cao
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Gunter Erb
- Bracco Group, Medical and Regulatory Affairs, 78467 Konstanz, Germany
| | - Ulrike Ernemann
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
| | - Vivien Richter
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tuebingen, 72076 Tuebingen, Germany; (T.-K.H.); (U.K.); (V.R.)
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21
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Cao Y, Huang M, Fu F, Chen K, Liu K, Cheng J, Li Y, Liu X. Abnormally glymphatic system functional in patients with migraine: a diffusion kurtosis imaging study. J Headache Pain 2024; 25:118. [PMID: 39039435 PMCID: PMC11265182 DOI: 10.1186/s10194-024-01825-z] [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: 06/16/2024] [Accepted: 07/11/2024] [Indexed: 07/24/2024] Open
Abstract
BACKGROUND The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) method has been used to evaluate glymphatic system function in patients with migraine. However, since the diffusion tensor model cannot accurately describe the diffusion coefficient of the nerve fibre crossing region, we proposed a diffusion kurtosis imaging ALPS (DKI-ALPS) method to evaluate glymphatic system function in patients with migraine. METHODS The study included 29 healthy controls and 37 patients with migraine. We used diffusion imaging data from a 3T MRI scanner to calculate DTI-ALPS and DKI-ALPS indices of the two groups. We compared the DTI-ALPS and DKI-ALPS indices between the two groups using a two-sample t-test and performed correlation analyses with clinical variables. RESULTS There was no significant difference in DTI-ALPS index between the two groups. Patients with migraine showed a significantly increased right DKI-ALPS index compared to healthy controls (1.6858 vs. 1.5729; p = 0.0301). There was no significant correlation between ALPS indices and clinical variables. CONCLUSIONS DKI-ALPS is a potential method to assess glymphatic system function and patients with migraine do not have impaired glymphatic system function.
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Affiliation(s)
- Yungang Cao
- Department of Neurology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China
| | - Mei Huang
- Department of Radiology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China
- Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, Zhejiang, 325027, China
| | - Fangwang Fu
- Department of Neurology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China
| | - Keyang Chen
- Department of Neurology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China
| | - Kun Liu
- Department of Radiology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China
- Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, Zhejiang, 325027, China
| | - Jinming Cheng
- Department of Neurology of the Hebei General Hospital, Shijiazhuang, Hebei, 050051, China
| | - Yan Li
- Department of Neurology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China.
| | - Xiaozheng Liu
- Department of Radiology of the Second Affiliated Hospital, Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China.
- Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, Zhejiang, 325027, China.
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22
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Gao C, Bao S, Kim ME, Newlin NR, Kanakaraj P, Yao T, Rudravaram G, Huo Y, Moyer D, Schilling K, Kukull WA, Toga AW, Archer DB, Hohman TJ, Landman BA, Li Z. Field-of-view extension for brain diffusion MRI via deep generative models. J Med Imaging (Bellingham) 2024; 11:044008. [PMID: 39185475 PMCID: PMC11344266 DOI: 10.1117/1.jmi.11.4.044008] [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: 03/25/2024] [Revised: 08/01/2024] [Accepted: 08/01/2024] [Indexed: 08/27/2024] Open
Abstract
Purpose In brain diffusion magnetic resonance imaging (dMRI), the volumetric and bundle analyses of whole-brain tissue microstructure and connectivity can be severely impeded by an incomplete field of view (FOV). We aim to develop a method for imputing the missing slices directly from existing dMRI scans with an incomplete FOV. We hypothesize that the imputed image with a complete FOV can improve whole-brain tractography for corrupted data with an incomplete FOV. Therefore, our approach provides a desirable alternative to discarding the valuable brain dMRI data, enabling subsequent tractography analyses that would otherwise be challenging or unattainable with corrupted data. Approach We propose a framework based on a deep generative model that estimates the absent brain regions in dMRI scans with an incomplete FOV. The model is capable of learning both the diffusion characteristics in diffusion-weighted images (DWIs) and the anatomical features evident in the corresponding structural images for efficiently imputing missing slices of DWIs in the incomplete part of the FOV. Results For evaluating the imputed slices, on the Wisconsin Registry for Alzheimer's Prevention (WRAP) dataset, the proposed framework achievedPSNR b 0 = 22.397 ,SSIM b 0 = 0.905 ,PSNR b 1300 = 22.479 , andSSIM b 1300 = 0.893 ; on the National Alzheimer's Coordinating Center (NACC) dataset, it achievedPSNR b 0 = 21.304 ,SSIM b 0 = 0.892 ,PSNR b 1300 = 21.599 , andSSIM b 1300 = 0.877 . The proposed framework improved the tractography accuracy, as demonstrated by an increased average Dice score for 72 tracts ( p < 0.001 ) on both the WRAP and NACC datasets. Conclusions Results suggest that the proposed framework achieved sufficient imputation performance in brain dMRI data with an incomplete FOV for improving whole-brain tractography, thereby repairing the corrupted data. Our approach achieved more accurate whole-brain tractography results with an extended and complete FOV and reduced the uncertainty when analyzing bundles associated with Alzheimer's disease.
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Affiliation(s)
- Chenyu Gao
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
| | - Shunxing Bao
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
| | - Michael E. Kim
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Nancy R. Newlin
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Praitayini Kanakaraj
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Tianyuan Yao
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Gaurav Rudravaram
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
| | - Yuankai Huo
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Daniel Moyer
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Kurt Schilling
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, Tennessee, United States
| | - Walter A. Kukull
- University of Washington, Department of Epidemiology, Seattle, Washington, United States
| | - Arthur W. Toga
- University of Southern California, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Laboratory of Neuro Imaging, Los Angeles, California, United States
| | - Derek B. Archer
- Vanderbilt University Medical Center, Vanderbilt Memory and Alzheimer’s Center, Nashville, Tennessee, United States
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee, United States
| | - Timothy J. Hohman
- Vanderbilt University Medical Center, Vanderbilt Memory and Alzheimer’s Center, Nashville, Tennessee, United States
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee, United States
| | - Bennett A. Landman
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, Tennessee, United States
| | - Zhiyuan Li
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
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23
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Jahn M, Layer G. [Multiparametric MRI in hepatocellular carcinoma, part 2 : Diffusion-weighted imaging in the primary diagnostics and treatment monitoring]. RADIOLOGIE (HEIDELBERG, GERMANY) 2024; 64:587-596. [PMID: 38884639 DOI: 10.1007/s00117-024-01323-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/06/2024] [Indexed: 06/18/2024]
Abstract
In addition to morphology and tissue perfusion, diffusion-weighted imaging (DWI) is the third pillar of multiparametric diagnostics in oncology. Due to the strong correlation between the apparent diffusion coefficient (ADC) and cell count in hepatocellular carcinoma (HCC), it can be used as a surrogate marker for tumor cell quantity. Therefore, ADC effectively reflects the effects of cytoreductive treatment, such as transarterial chemoembolization (TACE) and systemic chemotherapy and becomes an important clinical marker for treatment response. The DWI should remain an integral part of a magnetic resonance imaging (MRI) protocol in primary HCC diagnostics and treatment monitoring but is of secondary clinical importance compared to contrast-enhanced MRI perfusion sequences and the use of liver-specific contrast agents. For the future, standardization of DWI sequences for better comparability of various study protocols would be desirable.
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Affiliation(s)
- Mona Jahn
- Zentralinstitut für Diagnostische und Interventionelle Radiologie, Klinikum der Stadt Ludwigshafen am Rhein gGmbH, Bremserstraße 79, 67063, Ludwigshafen, Deutschland.
| | - Günter Layer
- Zentralinstitut für Diagnostische und Interventionelle Radiologie, Klinikum der Stadt Ludwigshafen am Rhein gGmbH, Bremserstraße 79, 67063, Ludwigshafen, Deutschland
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24
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Yang L, Hu H, Yang X, Yan Z, Shi G, Yang L, Wang Y, Han R, Yan X, Wang M, Ban X, Duan X. Whole-tumor histogram analysis of multiple non-Gaussian diffusion models at high b values for assessing cervical cancer. Abdom Radiol (NY) 2024; 49:2513-2524. [PMID: 38995401 DOI: 10.1007/s00261-024-04486-3] [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: 05/05/2024] [Revised: 06/26/2024] [Accepted: 06/30/2024] [Indexed: 07/13/2024]
Abstract
PURPOSE To assess the diagnostic potential of whole-tumor histogram analysis of multiple non-Gaussian diffusion models for differentiating cervical cancer (CC) aggressive status regarding of pathological types, differentiation degree, stage, and p16 expression. METHODS Patients were enrolled in this prospective single-center study from March 2022 to July 2023. Diffusion-weighted images (DWI) were obtained including 15 b-values (0 ~ 4000 s/mm2). Diffusion parameters derived from four non-Gaussian diffusion models including continuous-time random-walk (CTRW), diffusion-kurtosis imaging (DKI), fractional order calculus (FROC), and intravoxel incoherent motion (IVIM) were calculated, and their histogram features were analyzed. To select the most significant features and establish predictive models, univariate analysis and multivariate logistic regression were performed. Finally, we evaluated the diagnostic performance of our models by using receiver operating characteristic (ROC) analyses. RESULTS 89 women (mean age, 55 ± 11 years) with CC were enrolled in our study. The combined model, which incorporated the CTRW, DKI, FROC, and IVIM diffusion models, offered a significantly higher AUC than that from any individual models (0.836 vs. 0.664, 0.642, 0.651, 0.649, respectively; p < 0.05) in distinguishing cervical squamous cell cancer from cervical adenocarcinoma. To distinguish tumor differentiation degree, except the combined model showed a better predictive performance compared to the DKI model (AUC, 0.839 vs. 0.697, respectively; p < 0.05), no significant differences in AUCs were found among other individual models and combined model. To predict the International Federation of Gynecology and Obstetrics (FIGO) stage, only DKI and FROC model were established and there was no significant difference in predictive performance among different models. In terms of predicting p16 expression, the predictive ability of DKI model is significantly lower than that of FROC and combined model (AUC, 0.693 vs. 0.850, 0.859, respectively; p < 0.05). CONCLUSION Multiple non-Gaussian diffusion models with whole-tumor histogram analysis show great promise to assess the aggressive status of CC.
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Affiliation(s)
- Lu Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Huijun Hu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Xiaojun Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Zhuoheng Yan
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Guangzi Shi
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, China
| | - Lingjie Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Yu Wang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Riyu Han
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Xu Yan
- MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China
| | - Mengzhu Wang
- MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China
| | - Xiaohua Ban
- Department of Radiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
| | - Xiaohui Duan
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, China.
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Lindhardt TB, Skoven CS, Bordoni L, Østergaard L, Liang Z, Hansen B. Anesthesia-related brain microstructure modulations detected by diffusion magnetic resonance imaging. NMR IN BIOMEDICINE 2024; 37:e5033. [PMID: 37712335 DOI: 10.1002/nbm.5033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 07/06/2023] [Accepted: 08/09/2023] [Indexed: 09/16/2023]
Abstract
Recent studies have shown significant changes to brain microstructure during sleep and anesthesia. In vivo optical microscopy and magnetic resonance imaging (MRI) studies have attributed these changes to anesthesia and sleep-related modulation of the brain's extracellular space (ECS). Isoflurane anesthesia is widely used in preclinical diffusion MRI (dMRI) and it is therefore important to investigate if the brain's microstructure is affected by anesthesia to an extent detectable with dMRI. Here, we employ diffusion kurtosis imaging (DKI) to assess brain microstructure in the awake and anesthetized mouse brain (n = 22). We find both mean diffusivity (MD) and mean kurtosis (MK) to be significantly decreased in the anesthetized mouse brain compared with the awake state (p < 0.001 for both). This effect is observed in both gray matter and white matter. To further investigate the time course of these changes we introduce a method for time-resolved fast DKI. With this, we show the time course of the microstructural alterations in mice (n = 5) as they transition between states in an awake-anesthesia-awake paradigm. We find that the decrease in MD and MK occurs rapidly after delivery of gas isoflurane anesthesia and that values normalize only slowly when the animals return to the awake state. Finally, time-resolved fast DKI is employed in an experimental mouse model of brain edema (n = 4), where cell swelling causes the ECS volume to decrease. Our results show that isoflurane affects DKI parameters and metrics of brain microstructure and point to isoflurane causing a reduction in the ECS volume. The demonstrated DKI methods are suitable for in-bore perturbation studies, for example, for investigating microstructural modulations related to sleep/wake-dependent functions of the glymphatic system. Importantly, our study shows an effect of isoflurane anesthesia on rodent brain microstructure that has broad relevance to preclinical dMRI.
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Affiliation(s)
- Thomas Beck Lindhardt
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Sino-Danish Center for Education and Research, Aarhus, Denmark
- University of the Chinese Academy of Sciences, Beijing, China
| | - Christian Stald Skoven
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Luca Bordoni
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Letten Center, University of Oslo, Oslo, Norway
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Radiology, Neuroradiology Research Unit, Aarhus University Hospital, Aarhus, Denmark
| | - Zhifeng Liang
- CAS Center for Excellence in Brain Sciences and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Brian Hansen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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Yu W, Yan W, Yi J, Cheng L, Luo P, Sun J, Gou S, Fu P. Application of Diffusion Kurtosis Imaging and Blood Oxygen Level-Dependent Magnetic Resonance Imaging in Kidney Injury Associated with ANCA-Associated Vasculitis. Tomography 2024; 10:970-982. [PMID: 39058045 PMCID: PMC11280752 DOI: 10.3390/tomography10070073] [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: 05/05/2024] [Revised: 06/17/2024] [Accepted: 06/18/2024] [Indexed: 07/28/2024] Open
Abstract
OBJECTIVE Functional magnetic resonance imaging (fMRI) has been applied to assess the microstructure of the kidney. However, it is not clear whether fMRI could be used in the field of kidney injury in patients with Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). METHODS This study included 20 patients with AAV. Diffusion kurtosis imaging (DKI) and blood oxygen level-dependent (BOLD) scanning of the kidneys were performed in AAV patients and healthy controls. The mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) parameters of DKI, the R2* parameter of BOLD, and clinical data were further analyzed. RESULTS In AAV patients, the cortex exhibited lower MD but higher R2* values compared to the healthy controls. Medullary MK values were elevated in AAV patients. Renal medullary MK values showed a positive correlation with serum creatinine levels and negative correlations with hemoglobin levels and estimated glomerular filtration rate. To assess renal injury in AAV patients, AUC values for MK, MD, FA, and R2* in the cortex were 0.66, 0.67, 0.57, and 0.55, respectively, and those in the medulla were 0.81, 0.77, 0.61, and 0.53, respectively. CONCLUSIONS Significant differences in DKI and BOLD MRI parameters were observed between AAV patients with kidney injuries and the healthy controls. The medullary MK value in DKI may be a noninvasive marker for assessing the severity of kidney injury in AAV patients.
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Affiliation(s)
- Wenhui Yu
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.Y.); (L.C.); (P.L.); (P.F.)
| | - Weijie Yan
- Division of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.S.)
| | - Jing Yi
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.Y.); (L.C.); (P.L.); (P.F.)
- Division of Nephrology, West China Airport Hospital of Sichuan University, Chengdu 610200, China
| | - Lu Cheng
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.Y.); (L.C.); (P.L.); (P.F.)
| | - Peiyi Luo
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.Y.); (L.C.); (P.L.); (P.F.)
| | - Jiayu Sun
- Division of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.S.)
| | - Shenju Gou
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.Y.); (L.C.); (P.L.); (P.F.)
| | - Ping Fu
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, China; (W.Y.); (J.Y.); (L.C.); (P.L.); (P.F.)
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Chen J, Liu T, Shi H. End-stage renal disease accompanied by mild cognitive impairment: A study and analysis of trimodal brain network fusion. PLoS One 2024; 19:e0305079. [PMID: 38870175 PMCID: PMC11175492 DOI: 10.1371/journal.pone.0305079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024] Open
Abstract
The function and structure of brain networks (BN) may undergo changes in patients with end-stage renal disease (ESRD), particularly in those accompanied by mild cognitive impairment (ESRDaMCI). Many existing methods for fusing BN focus on extracting interaction features between pairs of network nodes from each mode and combining them. This approach overlooks the correlation between different modal features during feature extraction and the potentially valuable information that may exist between more than two brain regions. To address this issue, we propose a model using a multi-head self-attention mechanism to fuse brain functional networks, white matter structural networks, and gray matter structural networks, which results in the construction of brain fusion networks (FBN). Initially, three networks are constructed: the brain function network, the white matter structure network, and the individual-based gray matter structure network. The multi-head self-attention mechanism is then applied to fuse the three types of networks, generating attention weights that are transformed into an optimized model. The optimized model introduces hypergraph popular regular term and L1 norm regular term, leading to the formation of FBN. Finally, FBN is employed in the diagnosis and prediction of ESRDaMCI to evaluate its classification performance and investigate the correlation between discriminative brain regions and cognitive dysfunction. Experimental results demonstrate that the optimal classification accuracy achieved is 92.80%, which is at least 3.63% higher than the accuracy attained using other methods. This outcome confirms the effectiveness of our proposed method. Additionally, the identification of brain regions significantly associated with scores on the Montreal cognitive assessment scale may shed light on the underlying pathogenesis of ESRDaMCI.
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Affiliation(s)
- Jie Chen
- Department of Security, Huaide College of Changzhou University, Jingjiang, Jiangsu, China
| | - Tongqiang Liu
- Department of Nephrology, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
| | - Haifeng Shi
- Department of Radiology, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
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Karat BG, Köhler S, Khan AR. Diffusion MRI of the Hippocampus. J Neurosci 2024; 44:e1705232024. [PMID: 38839341 PMCID: PMC11154849 DOI: 10.1523/jneurosci.1705-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 03/22/2024] [Accepted: 04/06/2024] [Indexed: 06/07/2024] Open
Abstract
The hippocampus is a brain structure that plays key roles in a variety of cognitive processes. Critically, a wide range of neurological disorders are associated with degeneration of the hippocampal microstructure, defined as neurons, dendrites, glial cells, and more. Thus, the hippocampus is a key target for methods that are sensitive to these microscale properties. Diffusion MRI is one such method, which can noninvasively probe neural architecture. Here we review the extensive use of diffusion MRI to capture hippocampal microstructure in both health and disease. The results of these studies indicate that (1) diffusion tensor imaging is sensitive but not specific to the hippocampal microstructure; (2) biophysical modeling of diffusion MRI signals is a promising avenue to capture more specific aspects of the hippocampal microstructure; (3) use of ultra-short diffusion times have shown unique laminar-specific microstructure and response to hippocampal injury; (4) dispersion of microstructure is likely abundant in the hippocampus; and (5) the angular richness of the diffusion MRI signal can be leveraged to improve delineation of the internal hippocampal circuitry. Overall, extant findings suggest that diffusion MRI offers a promising avenue for characterizing hippocampal microstructure.
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Affiliation(s)
- Bradley G Karat
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario N6A 3K7, Canada
- Neuroscience Graduate Program, University of Western Ontario, London, Ontario N6A 3K7, Canada
| | - Stefan Köhler
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario N6A 3K7, Canada
- Department of Psychology, University of Western Ontario, London, Ontario N6A 3K7, Canada
| | - Ali R Khan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario N6A 3K7, Canada
- Western Institute for Neuroscience, University of Western Ontario, London, Ontario N6A 3K7, Canada
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Hu W, Qiu Z, Huang Q, Lin Y, Mo J, Wang L, Wang J, Deng K, Feng Y, Zhang X, Tan X. Microstructural changes of the white matter in systemic lupus erythematosus patients without neuropsychiatric symptoms: a multi-shell diffusion imaging study. Arthritis Res Ther 2024; 26:110. [PMID: 38807248 PMCID: PMC11134659 DOI: 10.1186/s13075-024-03344-3] [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: 01/22/2024] [Accepted: 05/22/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) provide more comprehensive and informative perspective on microstructural alterations of cerebral white matter (WM) than single-shell diffusion tensor imaging (DTI), especially in the detection of crossing fiber. However, studies on systemic lupus erythematosus patients without neuropsychiatric symptoms (non-NPSLE patients) using multi-shell diffusion imaging remain scarce. METHODS Totally 49 non-NPSLE patients and 41 age-, sex-, and education-matched healthy controls underwent multi-shell diffusion magnetic resonance imaging. Totally 10 diffusion metrics based on DKI (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis and radial kurtosis) and NODDI (neurite density index, orientation dispersion index and volume fraction of the isotropic diffusion compartment) were evaluated. Tract-based spatial statistics (TBSS) and atlas-based region-of-interest (ROI) analyses were performed to determine group differences in brain WM microstructure. The associations of multi-shell diffusion metrics with clinical indicators were determined for further investigation. RESULTS TBSS analysis revealed reduced FA, AD and RK and increased ODI in the WM of non-NPSLE patients (P < 0.05, family-wise error corrected), and ODI showed the best discriminative ability. Atlas-based ROI analysis found increased ODI values in anterior thalamic radiation (ATR), inferior frontal-occipital fasciculus (IFOF), forceps major (F_major), forceps minor (F_minor) and uncinate fasciculus (UF) in non-NPSLE patients, and the right ATR showed the best discriminative ability. ODI in the F_major was positively correlated to C3. CONCLUSION This study suggested that DKI and NODDI metrics can complementarily detect WM abnormalities in non-NPSLE patients and revealed ODI as a more sensitive and specific biomarker than DKI, guiding further understanding of the pathophysiological mechanism of normal-appearing WM injury in SLE.
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Affiliation(s)
- Wenjun Hu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Ziru Qiu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Qin Huang
- Department of Rheumatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuhao Lin
- Departments of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Jiaying Mo
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Linhui Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jingyi Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kan Deng
- Philips Healthcare, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Xinyuan Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.
| | - Xiangliang Tan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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Hashim Z, Gupta M, Neyaz Z, Srivastava S, Mani V, Nath A, Khan AR. Biophysical modeling and diffusion kurtosis imaging reveal microstructural alterations in normal-appearing white-matter regions of the brain in obstructive sleep apnea. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2024; 5:zpae031. [PMID: 38903701 PMCID: PMC11187986 DOI: 10.1093/sleepadvances/zpae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 05/17/2024] [Indexed: 06/22/2024]
Abstract
Study Objectives Studies have indicated that sleep abnormalities are a strong risk factor for developing cognitive impairment, cardiomyopathies, and neurodegenerative disorders. However, neuroimaging modalities are unable to show any consistent markers in obstructive sleep apnea (OSA) patients. We hypothesized that, compared with those of the control cohort, advanced diffusion MRI metrics could show subtle microstructural alterations in the brains of patients with OSA. Methods Sixteen newly diagnosed patients with moderate to severe OSA and 15 healthy volunteers of the same age and sex were considered healthy controls. Multishell diffusion MRI data of the brain, along with anatomical data (T1 and T2 images), were obtained on a 3T MRI system (Siemens, Germany) after a polysomnography (PSG) test for sleep abnormalities and a behavioral test battery to evaluate cognitive and executive brain functions. Diffusion MRI data were used to compute diffusion tensor imaging and diffusion kurtosis imaging (DKI) parameters along with white-matter tract integrity (WMTI) metrics for only parallel white-matter fibers. Results OSA was diagnosed when the patient's apnea-hypopnea index was ≥ 15. No significant changes in cognitive or executive functions were observed in the OSA cohort. DKI parameters can show significant microstructural alterations in the white-matter region, while the WMTI metric, the axonal-water-fraction (fp), reveals a significant decrease in OSA patients concerning the control cohort. Conclusions Advanced diffusion MRI-based microstructural alterations in the white-matter region of the brain suggest that white-matter tracts are more sensitive to OSA-induced intermittent hypoxia.
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Affiliation(s)
- Zia Hashim
- Department of Pulmonary Medicine, SGPGIMS, Lucknow, India
| | - Mansi Gupta
- Department of Pulmonary Medicine, SGPGIMS, Lucknow, India
| | - Zafar Neyaz
- Department of Radio-diagnosis, SGPGIMS, Lucknow, India
| | | | - Vinita Mani
- Department of Neurology, SGPGIMS, Lucknow, India
| | - Alok Nath
- Department of Pulmonary Medicine, SGPGIMS, Lucknow, India
| | - Ahmad Raza Khan
- Department of Advanced Spectroscopy and Imaging, CBMR, SGPGIMS Campus, Lucknow, India
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Dhiman S, Hickey RE, Thorn KE, Moss HG, McKinnon ET, Adisetiyo V, Ades-Aron B, Jensen JH, Benitez A. PyDesigner v1.0: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Magnetic Resonance Imaging. J Vis Exp 2024. [PMID: 38829110 PMCID: PMC11378319 DOI: 10.3791/66397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024] Open
Abstract
PyDesigner is a Python-based software package based on the original Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline (Dv1) for dMRI preprocessing and tensor estimation. This software is openly provided for non-commercial research and may not be used for clinical care. PyDesigner combines tools from FSL and MRtrix3 to perform denoising, Gibbs ringing correction, eddy current motion correction, brain masking, image smoothing, and Rician bias correction to optimize the estimation of multiple diffusion measures. It can be used across platforms on Windows, Mac, and Linux to accurately derive commonly used metrics from DKI, DTI, WMTI, FBI, and FBWM datasets as well as tractography ODFs and .fib files. It is also file-format agnostic, accepting inputs in the form of .nii, .nii.gz, .mif, and dicom format. User-friendly and easy to install, this software also outputs quality control metrics illustrating signal-to-noise ratio graphs, outlier voxels, and head motion to evaluate data integrity. Additionally, this dMRI processing pipeline supports multiple echo-time dataset processing and features pipeline customization, allowing the user to specify which processes are employed and which outputs are produced to meet a variety of user needs.
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Affiliation(s)
| | - Reyna E Hickey
- Department of Neurology, Medical University of South Carolina
| | - Kathryn E Thorn
- Department of Neurology, Medical University of South Carolina
| | - Hunter G Moss
- Department of Neuroscience, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina
| | - Emilie T McKinnon
- Department of Neuroscience, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina
| | - Vitria Adisetiyo
- Department of Neuroscience, Medical University of South Carolina
| | - Benjamin Ades-Aron
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine
| | - Jens H Jensen
- Department of Neuroscience, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina; Department of Radiology and Radiological Science, Medical University of South Carolina;
| | - Andreana Benitez
- Department of Neurology, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina;
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Farrher E, Grinberg F, Khechiashvili T, Neuner I, Konrad K, Shah NJ. Spatiotemporal Patterns of White Matter Maturation after Pre-Adolescence: A Diffusion Kurtosis Imaging Study. Brain Sci 2024; 14:495. [PMID: 38790472 PMCID: PMC11119177 DOI: 10.3390/brainsci14050495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/03/2024] [Accepted: 05/07/2024] [Indexed: 05/26/2024] Open
Abstract
Diffusion tensor imaging (DTI) enables the assessment of changes in brain tissue microstructure during maturation and ageing. In general, patterns of cerebral maturation and decline render non-monotonic lifespan trajectories of DTI metrics with age, and, importantly, the rate of microstructural changes is heterochronous for various white matter fibres. Recent studies have demonstrated that diffusion kurtosis imaging (DKI) metrics are more sensitive to microstructural changes during ageing compared to those of DTI. In a previous work, we demonstrated that the Cohen's d of mean diffusional kurtosis (dMK) represents a useful biomarker for quantifying maturation heterochronicity. However, some inferences on the maturation grades of different fibre types, such as association, projection, and commissural, were of a preliminary nature due to the insufficient number of fibres considered. Hence, the purpose of this follow-up work was to further explore the heterochronicity of microstructural maturation between pre-adolescence and middle adulthood based on DTI and DKI metrics. Using the effect size of the between-group parametric changes and Cohen's d, we observed that all commissural fibres achieved the highest level of maturity, followed by the majority of projection fibres, while the majority of association fibres were the least matured. We also demonstrated that dMK strongly correlates with the maxima or minima of the lifespan curves of DTI metrics. Furthermore, our results provide substantial evidence for the existence of spatial gradients in the timing of white matter maturation. In conclusion, our data suggest that DKI provides useful biomarkers for the investigation of maturation spatial heterogeneity and heterochronicity.
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Affiliation(s)
- Ezequiel Farrher
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, 52425 Jülich, Germany; (F.G.); (T.K.); (I.N.); (N.J.S.)
| | - Farida Grinberg
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, 52425 Jülich, Germany; (F.G.); (T.K.); (I.N.); (N.J.S.)
- Department of Neurology, RWTH Aachen University, 52074 Aachen, Germany
| | - Tamara Khechiashvili
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, 52425 Jülich, Germany; (F.G.); (T.K.); (I.N.); (N.J.S.)
| | - Irene Neuner
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, 52425 Jülich, Germany; (F.G.); (T.K.); (I.N.); (N.J.S.)
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, 52074 Aachen, Germany
- JARA—BRAIN—Translational Medicine, 52074 Aachen, Germany;
| | - Kerstin Konrad
- JARA—BRAIN—Translational Medicine, 52074 Aachen, Germany;
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry and Psychotherapy, RWTH Aachen University, 52074 Aachen, Germany
- Institute of Neuroscience and Medicine 3, INM-3, Forschungszentrum Jülich, 52425 Jülich, Germany
- Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, 52425 Jülich, Germany; (F.G.); (T.K.); (I.N.); (N.J.S.)
- Department of Neurology, RWTH Aachen University, 52074 Aachen, Germany
- JARA—BRAIN—Translational Medicine, 52074 Aachen, Germany;
- Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, 52425 Jülich, Germany
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Nagai Y, Kirino E, Tanaka S, Usui C, Inami R, Inoue R, Hattori A, Uchida W, Kamagata K, Aoki S. Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI. Cereb Cortex 2024; 34:129-145. [PMID: 38012112 PMCID: PMC11065111 DOI: 10.1093/cercor/bhad451] [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: 07/22/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.
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Affiliation(s)
- Yasuhito Nagai
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Department of Psychiatry, Juntendo University Shizuoka Hospital, 1129 Nagaoka Izunokuni-shi Shizuoka 410-2295, Japan
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Shoji Tanaka
- Department of Information and Communication Sciences, Sophia University, 7-1 Kioi-cho Chiyoda-ku Tokyo 102-8554, Japan
| | - Chie Usui
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Rie Inami
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Reiichi Inoue
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Aki Hattori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode Urayasu-shi Chiba 279-0013, Japan
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Shen Y, Zhao X, Wang K, Sun Y, Zhang X, Wang C, Yang Z, Feng Z, Zhang X. Exploring White Matter Abnormalities in Young Children with Autism Spectrum Disorder: Integrating Multi-shell Diffusion Data and Machine Learning Analysis. Acad Radiol 2024; 31:2074-2084. [PMID: 38185571 DOI: 10.1016/j.acra.2023.12.023] [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: 11/18/2023] [Revised: 12/09/2023] [Accepted: 12/14/2023] [Indexed: 01/09/2024]
Abstract
RATIONALE AND OBJECTIVES This study employed tract-based spatial statistics (TBSS) to investigate abnormalities in the white matter microstructure among children with autism spectrum disorder (ASD). Additionally, an eXtreme Gradient Boosting (XGBoost) model was developed to effectively classify individuals with ASD and typical developing children (TDC). METHODS AND MATERIALS Multi-shell diffusion weighted images were acquired from 62 children with ASD and 44 TDC. Using the Pydesigner procedure, diffusion tensor (DT), diffusion kurtosis (DK), and white matter tract integrity (WMTI) metrics were computed. Subsequently, TBSS analysis was applied to discern differences in these diffusion parameters between ASD and TDC groups. The XGBoost model was then trained using metrics showing significant differences, and Shapley Additive explanations (SHAP) values were computed to assess the feature importance in the model's predictions. RESULTS TBSS analysis revealed a significant reduction in axonal diffusivity (AD) in the left posterior corona radiata and the right superior corona radiata. Among the DK indicators, mean kurtosis, axial kurtosis, and kurtosis fractional anisotropy were notably increased in children with ASD, with no significant difference in radial kurtosis. WMTI metrics such as axonal water fraction, axonal diffusivity of the extra-axonal space (EAS_AD), tortuosity of the extra-axonal space (EAS_TORT), and diffusivity of intra-axonal space (IAS_Da) were significantly increased, primarily in the corpus callosum and fornix. Notably, there was no significant difference in radial diffusivity of the extra-axial space (EAS_RD). The XGBoost model demonstrated excellent classification ability, and the SHAP analysis identified EAS_TORT as the feature with the highest importance in the model's predictions. CONCLUSION This study utilized TBSS analyses with multi-shell diffusion data to examine white matter abnormalities in pediatric autism. Additionally, the developed XGBoost model showed outstanding performance in classifying ASD and TDC. The ranking of SHAP values based on the XGBoost model underscored the significance of features in influencing model predictions.
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Affiliation(s)
- Yanyong Shen
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Kaiyu Wang
- MR Research China, GE Healthcare, Beijing, 100000, PR China (K.W.)
| | - Yongbing Sun
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, 450000, China (Y.S.)
| | - Xiaoxue Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Changhao Wang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Zhexuan Yang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Zhanqi Feng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.).
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Chiu SY, Chen R, Wang WE, Armstrong MJ, Boeve BF, Savica R, Ramanan V, Fields JA, Graff-Radford N, Ferman TJ, Kantarci K, Vaillancourt DE. Longitudinal Free-Water Changes in Dementia with Lewy Bodies. Mov Disord 2024; 39:836-846. [PMID: 38477399 PMCID: PMC11102324 DOI: 10.1002/mds.29763] [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: 10/16/2023] [Revised: 01/06/2024] [Accepted: 02/16/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Diffusion-weighted magnetic resonance imaging (dMRI) examines tissue microstructure integrity in vivo. Prior dementia with Lewy bodies (DLB) diffusion tensor imaging studies yielded mixed results. OBJECTIVE We employed free-water (FW) imaging to assess DLB progression and correlate with clinical decline in DLB. METHODS Baseline and follow-up MRIs were obtained at 12 and/or 24 months for 27 individuals with DLB or mild cognitive impairment with Lewy bodies (MCI-LB). FW was analyzed using the Mayo Clinic Adult Lifespan Template. Primary outcomes were FW differences between baseline and 12 or 24 months. To compare FW change longitudinally, we included 20 cognitively unimpaired individuals from the Alzheimer's Disease Neuroimaging Initiative. RESULTS We followed 23 participants to 12 months and 16 participants to 24 months. Both groups had worsening in Montreal Cognitive Assessment (MoCA) and Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores. We found significant FW increases at both time points compared to baseline in the insula, amygdala, posterior cingulum, parahippocampal, entorhinal, supramarginal, fusiform, retrosplenial, and Rolandic operculum regions. At 24 months, we found more widespread microstructural changes in regions implicated in visuospatial processing, motor, and cholinergic functions. Between-group analyses (DLB vs. controls) confirmed significant FW changes over 24 months in most of these regions. FW changes were associated with longitudinal worsening of MDS-UPDRS and MoCA scores. CONCLUSIONS FW increased in gray and white matter regions in DLB, likely due to neurodegenerative pathology associated with disease progression. FW change was associated with clinical decline. The findings support dMRI as a promising tool to track disease progression in DLB. © 2024 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Shannon Y. Chiu
- Department of Neurology, University of Florida, Gainesville, FL
- Department of Neurology, Mayo Clinic, Scottsdale, AZ
| | - Robin Chen
- Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL
| | - Wei-en Wang
- Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL
| | | | | | | | | | - Julie A. Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | | | - Tanis J. Ferman
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL
| | - Kejal Kantarci
- Department of Neuroradiology, Mayo Clinic, Rochester, MN
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Ahmadi K, Pereira JB, van Westen D, Pasternak O, Zhang F, Nilsson M, Stomrud E, Spotorno N, Hansson O. Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease. J Neurosci 2024; 44:e0538232024. [PMID: 38565289 PMCID: PMC11063818 DOI: 10.1523/jneurosci.0538-23.2024] [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: 03/24/2023] [Revised: 03/07/2024] [Accepted: 03/08/2024] [Indexed: 04/04/2024] Open
Abstract
Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aβ-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aβ-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.
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Affiliation(s)
- Khazar Ahmadi
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22362, Sweden
- Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum 44801, Germany
| | - Joana B Pereira
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22362, Sweden
- Division of Neuro, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm 17176, Sweden
| | - Danielle van Westen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22362, Sweden
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund 22185, Sweden
| | - Ofer Pasternak
- Departments of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Fan Zhang
- Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Markus Nilsson
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund 22185, Sweden
- Department of Medical Radiation Physics, Lund University, Lund 22185, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22362, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 21428, Sweden
| | - Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22362, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22362, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 21428, Sweden
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Liu F, Yao Y, Zhu B, Yu Y, Ren R, Hu Y. The novel imaging methods in diagnosis and assessment of cerebrovascular diseases: an overview. Front Med (Lausanne) 2024; 11:1269742. [PMID: 38660416 PMCID: PMC11039813 DOI: 10.3389/fmed.2024.1269742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 03/27/2024] [Indexed: 04/26/2024] Open
Abstract
Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.
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Affiliation(s)
- Fei Liu
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ying Yao
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Bingcheng Zhu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yue Yu
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Reng Ren
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yinghong Hu
- Neuroscience Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Li HJ, Cao K, Li XT, Zhu HT, Zhao B, Gao M, Song X, Sun YS. A comparative study of mono-exponential and advanced diffusion-weighted imaging in differentiating stage IA endometrial carcinoma from benign endometrial lesions. J Cancer Res Clin Oncol 2024; 150:141. [PMID: 38504026 PMCID: PMC10951008 DOI: 10.1007/s00432-024-05668-8] [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: 11/07/2023] [Accepted: 02/25/2024] [Indexed: 03/21/2024]
Abstract
PURPOSE The purpose of the current investigation is to compare the efficacy of different diffusion models and diffusion kurtosis imaging (DKI) in differentiating stage IA endometrial carcinoma (IAEC) from benign endometrial lesions (BELs). METHODS Patients with IAEC, endometrial hyperplasia (EH), or a thickened endometrium confirmed between May 2016 and August 2022 were retrospectively enrolled. All of the patients underwent a preoperative pelvic magnetic resonance imaging (MRI) examination. The apparent diffusion coefficient (ADC) from the mono-exponential model, pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) from the bi-exponential model, distributed diffusion coefficient (DDC), water molecular diffusion heterogeneity index from the stretched-exponential model, diffusion coefficient (Dk) and diffusion kurtosis (K) from the DKI model were calculated. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic efficiency. RESULTS A total of 90 patients with IAEC and 91 patients with BELs were enrolled. The values of ADC, D, DDC and Dk were significantly lower and D* and K were significantly higher in cases of IAEC (p < 0.05). Multivariate analysis showed that K was the only predictor. The area under the ROC curve of K was 0.864, significantly higher compared with the ADC (0.601), D (0.811), D* (0.638), DDC (0.743) and Dk (0.675). The sensitivity, specificity and accuracy of K were 78.89%, 85.71% and 80.66%, respectively. CONCLUSION Advanced diffusion-weighted imaging models have good performance for differentiating IAEC from EH and endometrial thickening. Among all of the diffusion parameters, K showed the best performance and was the only independent predictor. Diffusion kurtosis imaging was defined as the most valuable model in the current context.
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Affiliation(s)
- Hai-Jiao Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China
| | - Kun Cao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China
| | - Xiao-Ting Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China
| | - Hai-Tao Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China
| | - Bo Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China
| | - Min Gao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gynecological Oncology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China
| | - Xiang Song
- Siemens Healthineers Digital Technology (Shanghai) Co., Ltd, Customer Services CRM, No.7 Wangjing Zhonghuan Nanlu, Beijing, 100102, China
| | - Ying-Shi Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road, Hai Dian District, Beijing, 100142, China.
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Jensen JH. Diffusional kurtosis time dependence and the water exchange rate for the multi-compartment Kärger model. Magn Reson Med 2024; 91:1122-1135. [PMID: 37957820 PMCID: PMC11027117 DOI: 10.1002/mrm.29926] [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: 07/31/2023] [Revised: 10/02/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023]
Abstract
PURPOSE To demonstrate an analytic formula giving the time dependence of the diffusional kurtosis for the Kärger model (KM) with an arbitrary number of exchanging compartments and its application in estimating the mean KM water exchange rate. THEORY AND METHODS The general formula for the kurtosis is derived from a power series solution for the multi-compartment KM. A lower bound on the exchange rate is established from the observation that the kurtosis is always a logarithmically convex function of time. Both the kurtosis time dependence and the lower bound are illustrated with numerical calculations. The lower bound is also applied to previously published data for the time dependence of the kurtosis in both brain and tumors. RESULTS The kurtosis for the multi-compartment KM is given by a sum in which each term is associated with an eigenvector of the exchange rate matrix. The lower bound is determined from the most negative value for the logarithmic derivative of the kurtosis with respect to time. In the cerebral cortex, the lower bound is found to vary from 15 to 76 s-1 , depending on the experimental details, while for the tumors considered, it varies from 2 to 4 s-1 . CONCLUSION The time dependence of the kurtosis for the multi-compartment KM has a simple analytic solution that allows a lower bound for the mean KM water exchange rate to be determined directly from experiment. This may be useful in tissues with complex microstructure that is difficult to model explicitly.
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Affiliation(s)
- Jens H. Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
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Zhang F, Cho KIK, Seitz-Holland J, Ning L, Legarreta JH, Rathi Y, Westin CF, O'Donnell LJ, Pasternak O. DDParcel: Deep Learning Anatomical Brain Parcellation From Diffusion MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:1191-1202. [PMID: 37943635 PMCID: PMC10994696 DOI: 10.1109/tmi.2023.3331691] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Parcellation of anatomically segregated cortical and subcortical brain regions is required in diffusion MRI (dMRI) analysis for region-specific quantification and better anatomical specificity of tractography. Most current dMRI parcellation approaches compute the parcellation from anatomical MRI (T1- or T2-weighted) data, using tools such as FreeSurfer or CAT12, and then register it to the diffusion space. However, the registration is challenging due to image distortions and low resolution of dMRI data, often resulting in mislabeling in the derived brain parcellation. Furthermore, these approaches are not applicable when anatomical MRI data is unavailable. As an alternative we developed the Deep Diffusion Parcellation (DDParcel), a deep learning method for fast and accurate parcellation of brain anatomical regions directly from dMRI data. The input to DDParcel are dMRI parameter maps and the output are labels for 101 anatomical regions corresponding to the FreeSurfer Desikan-Killiany (DK) parcellation. A multi-level fusion network leverages complementary information in the different input maps, at three network levels: input, intermediate layer, and output. DDParcel learns the registration of diffusion features to anatomical MRI from the high-quality Human Connectome Project data. Then, to predict brain parcellation for a new subject, the DDParcel network no longer requires anatomical MRI data but only the dMRI data. Comparing DDParcel's parcellation with T1w-based parcellation shows higher test-retest reproducibility and a higher regional homogeneity, while requiring much less computational time. Generalizability is demonstrated on a range of populations and dMRI acquisition protocols. Utility of DDParcel's parcellation is demonstrated on tractography analysis for fiber tract identification.
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Voltin J, Nunn LM, Watson Z, Brasher ZE, Adisetiyo V, Hanlon CA, Nietert PJ, McRae-Clark AL, Jensen JH. Comparison of three magnetic resonance imaging measures of brain iron in healthy and cocaine use disorder participants. NMR IN BIOMEDICINE 2024; 37:e5072. [PMID: 38009303 PMCID: PMC10922943 DOI: 10.1002/nbm.5072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/28/2023] [Accepted: 10/23/2023] [Indexed: 11/28/2023]
Abstract
Several magnetic resonance imaging (MRI) measures for quantifying endogenous nonheme brain iron have been proposed. These correspond to distinct physical properties with varying sensitivities and specificities to iron. Moreover, they may depend not only on tissue iron concentration, but also on the intravoxel spatial pattern of iron deposition, which is complex in many brain regions. Here, the three MRI brain iron measures of R 2 * , magnetic field correlation (MFC), and magnetic susceptibility are compared in several deep gray matter regions for both healthy participants (HPs) and individuals with cocaine use disorder (CUD). Their concordance is assessed from their correlations with each other and their relative dependencies on age. In addition, associations between the iron measures and microstructure in adjacent white matter regions are investigated by calculating their correlations with diffusion MRI measures from the internal capsule, and associations with cognition are determined by using results from a battery of standardized tests relevant to CUD. It is found that all three iron measures are strongly correlated with each other for the considered gray matter regions, but with correlation coefficients substantially less than one indicating important differences. The age dependencies of all three measures are qualitatively similar in most regions, except for the red nucleus, where the susceptibility has a significantly stronger correlation with age than R 2 * . Weak to moderate correlations are seen for the iron measures with several of the diffusion and cognitive measures, with the strongest correlations being obtained for R 2 * . The iron measures differ little between the HP and CUD groups, although susceptibility is significantly lower in the red nucleus for the CUD group. For the comparisons made, the iron measures behave similarly in most respects, but with notable quantitative differences. It is suggested that these differences may be, in part, attributable to a higher sensitivity to the spatial pattern of iron deposition for R 2 * and MFC than for susceptibility. This is supported most strongly by a sharp contrast between the values of the iron measures in the globus pallidus relative to those in the red nucleus. The observed correlations of the iron measures with diffusion and cognitive scores point to possible connections between gray matter iron, white matter microstructure, and cognition.
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Affiliation(s)
- Joshua Voltin
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
| | - Lisa M. Nunn
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Zoe Watson
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Zoe E. Brasher
- Department of Behavioral Science and Neuroscience, Duke University Medical Center, Durham, North Carolina
| | - Vitria Adisetiyo
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
| | - Colleen A. Hanlon
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Paul J. Nietert
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina
| | - Aimee L. McRae-Clark
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Jens H. Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
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Pei C, He C, Li H, Li X, Huang W, Liu J, Yin J. Clinical and imaging markers for the prognosis of acute ischemic stroke. Front Neurol 2024; 15:1345914. [PMID: 38487321 PMCID: PMC10937465 DOI: 10.3389/fneur.2024.1345914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 02/19/2024] [Indexed: 03/17/2024] Open
Abstract
Background and purpose Significant differences in the outcomes observed in patients with acute ischemic stroke (AIS) have led to research investigations for identifying the predictors. In this retrospective study, we aimed to investigate the relationship of different clinical and imaging factors with the prognosis of AIS. Materials and methods All clinical and imaging metrics were compared between the good and poor prognosis groups according to the modified Rankin Scale (mRS) score at 90 days after discharge. Clinical factors included gender, age, NIHSS scores at admission, and other medical history risk factors. Imaging markers included the lesion's size and location, diffusion, and perfusion metrics of infarction core and peripheral regions, and the state of collateral circulation. Spearman's correlations were analyzed for age and imaging markers between the different groups. The Chi-square test and Cramer's V coefficient analysis were performed for gender, collateral circulation status, NIHSS score, and other stroke risk factors. Results A total of 89 patients with AIS were divided into the good (mRS score ≤ 2) and poor prognosis groups (mRS score ≥ 3). There were differences in NIHSS score at the admission; relative MK (rMK), relative MD (rMD), relative CBF (rCBF) of the infarction core; relative mean transit time (rMTT), relative time to peak (rTTP), and relative CBF (rCBF) of peripheral regions; and collateral circulation status between the two groups (p < 0.05). Among them, the rMK of infarction lesions had the strongest correlation with the mRS score at 90 days after discharge (r = 0.545, p < 0.001). Conclusion Perfusion and diffusion metrics could reflect the microstructure and blood flow characteristics of the lesion, which were the key factors for the salvage ability and prognosis of the infarction tissue. The characteristics of the infarction core and peripheral regions have different effects on the outcomes. Diffusion of infarction core has strong relations with the prognosis, whereas the time metrics (MTT, TTP) were more important for peripheral regions. MK had a more significant association with prognosis than MD. These factors were the primary markers influencing the prognosis of cerebral infarction patients.
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Affiliation(s)
- Chenyang Pei
- Tianjin Medical University, Tianjin, China
- Department of Radiology, Haikou People's Hospital, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, Hainan, China
| | - Che He
- Medical Imaging Center, The First People's Hospital of Qujing, Qujing, Yunnan, China
| | - Han Li
- Tianjin Medical University, Tianjin, China
| | - Xiangying Li
- Department of Radiology, Haikou People's Hospital, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, Hainan, China
| | - Weihui Huang
- Department of Neurology, Tianjin First Central Hospital, Tianjin, China
| | - Jun Liu
- Department of Radiology, Tianjin Fourth Central Hospital, Tianjin, China
| | - Jianzhong Yin
- Department of Radiology, Haikou People's Hospital, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, Hainan, China
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Zhang Z, Zhang Y, Hu F, Xie T, Liu W, Xiang H, Li X, Chen L, Zhou Z. Value of diffusion kurtosis MR imaging and conventional diffusion weighed imaging for evaluating response to first-line chemotherapy in unresectable pancreatic cancer. Cancer Imaging 2024; 24:29. [PMID: 38409049 PMCID: PMC10898033 DOI: 10.1186/s40644-024-00674-y] [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: 01/02/2024] [Accepted: 02/15/2024] [Indexed: 02/28/2024] Open
Abstract
OBJECTIVE To investigate the diagnostic value of diffusion kurtosis magnetic resonance imaging (DKI) and conventional diffusion-weighted imaging (DWI) for evaluating the response to first-line chemotherapy in unresectable pancreatic cancer. MATERIALS AND METHODS We retrospectively analyzed 21 patients with clinically and pathologically confirmed unresected pancreatic cancer who received palliative chemotherapy. Three-tesla MRI examinations containing DWI sequences with b values of 0, 100, 700, 1400, and 2100 s/mm2 were performed before and after chemotherapy. Parameters included the apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), and mean diffusional kurtosis (MK). The performances of the DWI and DKI parameters in distinguishing the response to chemotherapy were evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Overall survival (OS) was calculated from the date of first treatment to the date of death or the latest follow-up date. RESULTS The ADCchange and MDchange were significantly higher in the responding group (PR group) than in the nonresponding group (non-PR group) (ADCchange: 0.21 ± 0.05 vs. 0.11 ± 0.09, P = 0.02; MDchange: 0.37 ± 0.24 vs. 0.10 ± 0.12, P = 0.002). No statistical significance was shown when comparing ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost between the PR and non-PR groups. The ROC curve analysis indicated that MDchange (AUC = 0.898, cutoff value = 0.7143) performed better than ADCchange (AUC = 0.806, cutoff value = 0.1369) in predicting the response to chemotherapy. CONCLUSION The ADCchange and MDchange demonstrated strong potential for evaluating the response to chemotherapy in unresectable pancreatic cancer. The MDchange showed higher specificity in the classification of PR and non-PR than the ADCchange. Other parameters, including ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost, are not suitable for response evaluation. The combined model SUMchange demonstrated superior performance compared to the individual DWI and DKI models. Further experiments are needed to evaluate the potential of DWI and DKI parameters in predicting the prognosis of patients with unresectable pancreatic cancer.
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Affiliation(s)
- Zehua Zhang
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, No. 106, Ruili Road, 201100, Shanghai, China
| | - Yuqin Zhang
- Department of Colorectal Surgery, Minhang Branch, Fudan University Shanghai Cancer Center, No. 106, Ruili Road, 201100, Shanghai, China
| | - Feixiang Hu
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270, Dongan Road, 200032, Shanghai, China
| | - Tiansong Xie
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270, Dongan Road, 200032, Shanghai, China
| | - Wei Liu
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270, Dongan Road, 200032, Shanghai, China
| | - Huijing Xiang
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, No. 106, Ruili Road, 201100, Shanghai, China
| | - Xiangxiang Li
- Nursing department, Minhang Branch, Fudan University Shanghai Cancer Center, No. 106. Ruili Road, 201100, Shanghai, China
| | - Lei Chen
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, No. 106, Ruili Road, 201100, Shanghai, China.
| | - Zhengrong Zhou
- Department of Radiology, Minhang Branch, Fudan University Shanghai Cancer Center, No. 106, Ruili Road, 201100, Shanghai, China.
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270, Dongan Road, 200032, Shanghai, China.
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Foesleitner O, Sturm V, Hayes J, Weiler M, Sam G, Wildemann B, Wick W, Bendszus M, Heiland S, Jäger LB. Microstructural changes of peripheral nerves in early multiple sclerosis: A prospective magnetic resonance neurography study. Eur J Neurol 2024; 31:e16126. [PMID: 37932921 PMCID: PMC11236022 DOI: 10.1111/ene.16126] [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: 06/03/2023] [Revised: 10/07/2023] [Accepted: 10/19/2023] [Indexed: 11/08/2023]
Abstract
BACKGROUND AND PURPOSE Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system (CNS). However, there is increasing evidence of peripheral nerve involvement. This study aims to characterize the pattern of peripheral nerve changes in patients with newly diagnosed MS using quantitative magnetic resonance (MR) neurography. METHODS In this prospective study, 25 patients first diagnosed with MS according to the revised McDonald criteria (16 female, mean age = 32.8 ± 10.6 years) and 14 healthy controls were examined with high-resolution 3-T MR neurography of the sciatic nerve using diffusion kurtosis imaging (DKI; 20 diffusional directions, b = 0, 700, 1200 s/mm2 ) and magnetization transfer imaging (MTI). In total, 15 quantitative MR biomarkers were analyzed and correlated with clinical symptoms, intrathecal immunoglobulin synthesis, electrophysiology, and lesion load on brain and spine MR imaging. RESULTS Patients showed decreased fractional anisotropy (mean = 0.51 ± 0.04 vs. 0.56 ± 0.03, p < 0.001), extra-axonal tortuosity (mean = 2.32 ± 0.17 vs. 2.49 ± 0.17, p = 0.008), and radial kurtosis (mean = 1.40 ± 0.23 vs. 1.62 ± 0.23, p = 0.014) and higher radial diffusivity (mean = 1.09 ∙ 10-3 mm2 /s ± 0.16 vs. 0.98 ± 0.11 ∙ 10-3 mm2 /s, p = 0.036) than controls. Groups did not differ in MTI. No significant association was found between MR neurography markers and clinical/laboratory parameters or CNS lesion load. CONCLUSIONS This study provides further evidence of peripheral nerve involvement in MS already at initial diagnosis. The characteristic pattern of DKI parameters indicates predominant demyelination and suggests a primary coaffection of the peripheral nervous system in MS. This first human study using DKI for peripheral nerves shows its potential and clinical feasibility in providing novel biomarkers.
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Affiliation(s)
- Olivia Foesleitner
- Department of NeuroradiologyHeidelberg University HospitalHeidelbergGermany
| | - Volker Sturm
- Department of NeuroradiologyHeidelberg University HospitalHeidelbergGermany
| | - Jennifer Hayes
- Department of NeuroradiologyHeidelberg University HospitalHeidelbergGermany
| | - Markus Weiler
- Department of NeurologyHeidelberg University HospitalHeidelbergGermany
- Clinical Cooperation Unit Neuro‐oncology, German Cancer ConsortiumGerman Cancer Research CenterHeidelbergGermany
| | - Georges Sam
- Department of NeurologyHeidelberg University HospitalHeidelbergGermany
| | | | - Wolfgang Wick
- Department of NeurologyHeidelberg University HospitalHeidelbergGermany
- Clinical Cooperation Unit Neuro‐oncology, German Cancer ConsortiumGerman Cancer Research CenterHeidelbergGermany
| | - Martin Bendszus
- Department of NeuroradiologyHeidelberg University HospitalHeidelbergGermany
| | - Sabine Heiland
- Department of NeuroradiologyHeidelberg University HospitalHeidelbergGermany
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Zhu J, Chen A, Gao J, Zou M, Du J, Wu PY, Zhang J, Mao Y, Song Y, Chen M. Diffusion-weighted, intravoxel incoherent motion, and diffusion kurtosis tensor MR imaging in chronic kidney diseases: Correlations with histology. Magn Reson Imaging 2024; 106:1-7. [PMID: 37414367 DOI: 10.1016/j.mri.2023.07.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 06/30/2023] [Accepted: 07/02/2023] [Indexed: 07/08/2023]
Abstract
OBJECTIVES To probe the correlations of parameters derived from standard DWI and its extending models including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) with the pathological and functional alterations in CKD. MATERIAL AND METHODS Seventy-nine CKD patients with renal biopsy and 10 volunteers were performed with DWI, IVIM, diffusion kurtosis tensor imaging (DKTI) scanning. Correlations between imaging results and the pathological damage [glomerulosclerosis index (GSI) and tubulointerstitial fibrosis index (TBI)], as well as eGFR, 24 h urinary protein and Scr) were evaluated.CKD patients were divided into 2 groups: group 1: both GSI and TBI scores <2 points (61 cases); group 2: both GSI and TBI scores ≥2 points (18 cases). RESULTS There were significant difference in cortical and medullary MD, and cortical D among 3 groups and between group 1 and 2. Cortical and medullary MD, cortical D, and medullary FA were negatively correlated with GSI score (r = -0.322 to -0.386, P < 0.05). Cortical and medullary MD and D, medullary FA were also negatively correlated with TBI score (r = -0.257 to -0.395, P < 0.05). These parameters were all correlated with eGFR and Scr. Cortical MD and D showed the highest AUC of 0.790 and 0.745 in discriminating mild and moderate-severe glomerulosclerosis and tubular interstitial fibrosis, respectively. CONCLUSIONS The corrected diffusion-related indices, including cortical and medullary D and MD, as well as medullary FA were superior to ADC, perfusion-related and kurtosis indices for evaluating the severity of renal pathology and function in CKD patients.
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Affiliation(s)
- Jie Zhu
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Aiqun Chen
- Department of Nephrology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Jiayin Gao
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Mingzhu Zou
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Jun Du
- Department of Pathology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Pu-Yeh Wu
- GE Healthcare, Beijing 100176, China
| | - Jintao Zhang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Yonghui Mao
- Department of Nephrology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Yan Song
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
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Li Y, Wen H, Li W, Peng Y, Li H, Tai J, Ji T, Mei L, Liu Y. Diffusion kurtosis imaging tractography reveals disrupted white matter structural networks in children with obstructive sleep apnea syndrome. Brain Imaging Behav 2024; 18:92-105. [PMID: 37906404 DOI: 10.1007/s11682-023-00809-y] [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] [Accepted: 10/09/2023] [Indexed: 11/02/2023]
Abstract
To assess the disruptions of brain white matter (WM) structural network in children with obstructive sleep apnea (OSA) using diffusion kurtosis imaging (DKI). We use DKI tractography to construct individual whole-brain, region-level WM networks in 40 OSA and 28 healthy children. Then, we apply graph theory approaches to analyze whether OSA children would show altered global and regional network topological properties and whether these alterations would significantly correlate with the clinical characteristics of OSA. We found that both OSA and healthy children showed an efficient small-world organization and highly similar hub distributions in WM networks. However, characterized by kurtosis fractional anisotropy (KFA) weighted networks, OSA children exhibited decreased global and local efficiency, increased shortest path length compared with healthy children. For regional topology, OSA children exhibited significant decreased nodal betweenness centrality (BC) in the bilateral medial orbital superior frontal gyrus (ORBsupmed), right orbital part superior frontal gyrus (ORBsup), insula, postcentral gyrus, left middle temporal gyrus (MTG), and increased nodal BC in the superior parietal gyrus, pallidum. Intriguingly, the altered nodal BC of multiple regions (right ORBsupmed, ORBsup and left MTG) within default mode network showed significant correlations with sleep parameters for OSA patients. Our results suggest that children with OSA showed decreased global integration and local specialization in WM networks, typically characterized by DKI tractography and KFA metric. This study may advance our current understanding of the pathophysiological mechanisms of impaired cognition underlying OSA.
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Affiliation(s)
- Yanhua Li
- Department of Radiology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, 56 Nanlishilu, Beijing, 100045, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Hongwei Wen
- Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing, 400715, China
| | - Wenfeng Li
- Department of Radiology, Beijing Daxing District Hospital of Integrated Chinese and Western Medicine, Beijing, 100163, China
| | - Yun Peng
- Department of Radiology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, 56 Nanlishilu, Beijing, 100045, China
| | - Hongbin Li
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Jun Tai
- Department of Otolaryngology, Head and Neck Surgery, Children's Hospital, Capital Institute of Pediatrics, Beijing, 100020, China
| | - Tingting Ji
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Lin Mei
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China
| | - Yue Liu
- Department of Radiology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, 56 Nanlishilu, Beijing, 100045, China.
- Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, 450018, China.
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Ribeiro M, Yordanova YN, Noblet V, Herbet G, Ricard D. White matter tracts and executive functions: a review of causal and correlation evidence. Brain 2024; 147:352-371. [PMID: 37703295 DOI: 10.1093/brain/awad308] [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: 10/08/2022] [Revised: 08/17/2023] [Accepted: 08/25/2023] [Indexed: 09/15/2023] Open
Abstract
Executive functions are high-level cognitive processes involving abilities such as working memory/updating, set-shifting and inhibition. These complex cognitive functions are enabled by interactions among widely distributed cognitive networks, supported by white matter tracts. Executive impairment is frequent in neurological conditions affecting white matter; however, whether specific tracts are crucial for normal executive functions is unclear. We review causal and correlation evidence from studies that used direct electrical stimulation during awake surgery for gliomas, voxel-based and tract-based lesion-symptom mapping, and diffusion tensor imaging to explore associations between the integrity of white matter tracts and executive functions in healthy and impaired adults. The corpus callosum was consistently associated with all executive processes, notably its anterior segments. Both causal and correlation evidence showed prominent support of the superior longitudinal fasciculus to executive functions, notably to working memory. More specifically, strong evidence suggested that the second branch of the superior longitudinal fasciculus is crucial for all executive functions, especially for flexibility. Global results showed left lateralization for verbal tasks and right lateralization for executive tasks with visual demands. The frontal aslant tract potentially supports executive functions, however, additional evidence is needed to clarify whether its involvement in executive tasks goes beyond the control of language. Converging evidence indicates that a right-lateralized network of tracts connecting cortical and subcortical grey matter regions supports the performance of tasks assessing response inhibition, some suggesting a role for the right anterior thalamic radiation. Finally, correlation evidence suggests a role for the cingulum bundle in executive functions, especially in tasks assessing inhibition. We discuss these findings in light of current knowledge about the functional role of these tracts, descriptions of the brain networks supporting executive functions and clinical implications for individuals with brain tumours.
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Affiliation(s)
- Monica Ribeiro
- Service de neuro-oncologie, Hôpital La Pitié-Salpêtrière, Groupe Hospitalier Universitaire Pitié Salpêtrière-Charles Foix, Sorbonne Université, 75013 Paris, France
- Université Paris Saclay, ENS Paris Saclay, Service de Santé des Armées, CNRS, Université Paris Cité, INSERM, Centre Borelli UMR 9010, 75006 Paris, France
| | - Yordanka Nikolova Yordanova
- Service de neurochirurgie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, 92140 Clamart, France
| | - Vincent Noblet
- ICube, IMAGeS team, Université de Strasbourg, CNRS, UMR 7357, 67412 Illkirch, France
| | - Guillaume Herbet
- Praxiling, UMR 5267, CNRS, Université Paul Valéry Montpellier 3, 34090 Montpellier, France
- Département de Neurochirurgie, Hôpital Gui de Chauliac, Centre Hospitalier Universitaire de Montpellier, 34295 Montpellier, France
- Institut Universitaire de France
| | - Damien Ricard
- Université Paris Saclay, ENS Paris Saclay, Service de Santé des Armées, CNRS, Université Paris Cité, INSERM, Centre Borelli UMR 9010, 75006 Paris, France
- Département de neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, 92140 Clamart, France
- Ecole du Val-de-Grâce, 75005 Paris, France
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Raya JG, Duarte A, Wang N, Mazzoli V, Jaramillo D, Blamire AM, Dietrich O. Applications of Diffusion-Weighted MRI to the Musculoskeletal System. J Magn Reson Imaging 2024; 59:376-396. [PMID: 37477576 DOI: 10.1002/jmri.28870] [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: 02/22/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 07/22/2023] Open
Abstract
Diffusion-weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application-specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2-70 msec) and the need for sub-millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion-weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- José G Raya
- Department of Radiology, NYU Langone Health, New York, New York, USA
| | - Alejandra Duarte
- Division of Musculoskeletal Radiology, Department of Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana, USA
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, Indiana, USA
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Diego Jaramillo
- Department of Radiology, Columbia University Medical Center, New York, New York, USA
| | - Andrew M Blamire
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Olaf Dietrich
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
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Motegi H, Kufukihara K, Kitagawa S, Sekiguchi K, Hata J, Fujiwara H, Jinzaki M, Okano H, Nakamura M, Iguchi Y, Nakahara J. Non-lesional white matter changes depicted by q-space diffusional MRI correlate with clinical disabilities in multiple sclerosis. J Neurol Sci 2024; 456:122851. [PMID: 38181653 DOI: 10.1016/j.jns.2023.122851] [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: 07/12/2023] [Revised: 11/20/2023] [Accepted: 12/17/2023] [Indexed: 01/07/2024]
Abstract
BACKGROUND We previously developed an optimized q-space diffusional MRI technique (normalized leptokurtic diffusion [NLD] map) to delineate the demyelinated lesions of multiple sclerosis (MS) patients. Herein, we evaluated the utility of NLD maps to discern the white matter abnormalities in normal-appearing white matter (NAWM) and the abnormalities' possible associations with physical and cognitive disabilities in MS. METHODS We conducted a retrospective observational study of MS patients treated at our hospital (Jan. 2012 to Dec. 2022). Clinical and MRI data were collected; Processing Speed Test (PST) data were obtained when possible. For a quantitative analysis of the NLD maps, we calculated the NLD index as GVROI/GVREF, where GV is a mean grayscale value in the regions of interest (ROIs) and the reference area (REF; cerebrospinal fluid). RESULTS One hundred-one individuals with MS were included. The lower corpus callosum and non-lesional WM NLD index were associated with worse Expanded Disability Status Scale (EDSS) and PST scores. The NLD indexes in the corpus callosum (p < 0.0001) and non-lesional white matter (p < 0.0001) were significantly reduced in progressive MS compared to relapsing-remitting MS. We categorized MS severity as moderate/severe (EDSS score ≥ 4 points) and mild (EDSS score < 4 points). The NLD indexes in the corpus callosum (p < 0.0001) and non-lesional white matter (p < 0.0001) were significantly lower in the moderate/severe MS group compared to the mild MS group. CONCLUSION The NLD map revealed abnormalities in the non-lesional white matter, providing valuable insights for evaluating manifestations in MS patients.
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Affiliation(s)
- Haruhiko Motegi
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan; Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
| | - Kenji Kufukihara
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan; Department of Neurology, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
| | - Satoshi Kitagawa
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan.
| | - Koji Sekiguchi
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan.
| | - Junichi Hata
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan; Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Japan.
| | - Hirokazu Fujiwara
- Center of Preventive Medicine, Keio University School of Medicine, Tokyo, Japan.
| | - Masahiro Jinzaki
- Department of Radiology, Keio University School of Medicine, Tokyo, Japan.
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Japan.
| | - Masaya Nakamura
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan.
| | - Yasuyuki Iguchi
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
| | - Jin Nakahara
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan.
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Zuo L, Tian T, Wang B, Gu H, Wang S. Microstructural white matter abnormalities in overactive bladder syndrome evaluation with diffusion kurtosis imaging tract-based spatial statistics analysis. World J Urol 2024; 42:36. [PMID: 38217714 DOI: 10.1007/s00345-023-04709-0] [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: 05/02/2023] [Accepted: 10/16/2023] [Indexed: 01/15/2024] Open
Abstract
PURPOSE This prospective study aimed to explore the microstructural alterations of the white matter in overactive bladder syndrome (OAB) using the Tract-based Spatial Statistics (TBSS) method of diffusion kurtosis imaging (DKI). METHODS A total of 30 patients were enrolled and compared with 30 controls. White matter (WM) status was assessed using tract-based spatial statistics for DKI. The differences in DKI-derived parameters, including kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), mean diffusivity (MD), radial kurtosis (RK), axial kurtosis (AK), axial diffusivity (AD), and radial diffusivity (RD), were compared between the two groups using the TBSS method. The correlation between the altered DKI-derived parameters and the (OABSS) scores was analyzed. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of different white matter parameters. RESULTS As a result, compared with the HC group, the KFA, and FA values decreased significantly in the OAB group. Compared with the HC group, the MK and MD values increased significantly in the OAB group. The KFA values of the genu of corpus callosum (GCC) were significantly correlated with the OABSS scores (r = - 0.509; p = 0.004). The FA values of anterior corona radiata (ACR) were significantly correlated with OABSS scores (r = - 0.447; p = 0.013). The area under the ROC curve (AUC) for the genu of corpus callosum KFA values was higher than FA for the diagnosis of OAB patients. CONCLUSION DKI is a promising approach to the investigation of the pathophysiology of OAB and a potential biomarker for clinical diagnosis of OAB.
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Affiliation(s)
- Long Zuo
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China
| | - Tian Tian
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China
| | - Biao Wang
- Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Hua Gu
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China
| | - Shuangkun Wang
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China.
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