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Sakaie K, Koenig K, Lerner A, Appleby B, Ogrocki P, Pillai JA, Rao S, Leverenz JB, Lowe MJ. Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease. Magn Reson Imaging 2024; 109:221-226. [PMID: 38521367 DOI: 10.1016/j.mri.2024.03.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 03/05/2024] [Accepted: 03/19/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND AND PURPOSE A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD. METHODS Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5). RESULTS Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language. CONCLUSION This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.
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Affiliation(s)
- Ken Sakaie
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA.
| | - Katherine Koenig
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
| | - Alan Lerner
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Brian Appleby
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Paula Ogrocki
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jagan A Pillai
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - Stephen Rao
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - Mark J Lowe
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
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Kafkaletos A, Mix M, Sachpazidis I, Carles M, Rühle A, Ruf J, Grosu AL, Nicolay NH, Baltas D. The significance of partial volume effect on the estimation of hypoxic tumour volume with [ 18F]FMISO PET/CT. EJNMMI Phys 2024; 11:43. [PMID: 38722446 PMCID: PMC11082115 DOI: 10.1186/s40658-024-00643-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/24/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND The purpose of this study was to evaluate how a retrospective correction of the partial volume effect (PVE) in [18F]fluoromisonidazole (FMISO) PET imaging, affects the hypoxia discoverability within a gross tumour volume (GTV). This method is based on recovery coefficients (RC) and is tailored for low-contrast tracers such as FMISO. The first stage was the generation of the scanner's RC curves, using spheres with diameters from 10 to 37 mm, and the same homogeneous activity concentration, positioned in lower activity concentration background. Six sphere-to-background contrast ratios were used, from 10.0:1, down to 2.0:1, in order to investigate the dependence of RC on both the volume and the contrast ratio. The second stage was to validate the recovery-coefficient correction method in a more complex environment of non-spherical lesions of different volumes and inhomogeneous activity concentration. Finally, we applied the correction method to a clinical dataset derived from a prospective imaging trial (DRKS00003830): forty nine head and neck squamous cell carcinoma (HNSCC) cases who had undergone FMISO PET/CT scanning for the quantification of tumour hypoxia before (W0), 2 weeks (W2) and 5 weeks (W5) after the beginning of radiotherapy. Here, PVE was found to cause an underestimation of the activity in small volumes with high FMISO signal. RESULTS The application of the proposed correction method resulted in a statistically significant increase of both the hypoxic subvolume (171% at W0, 691% at W2 and 4.60 × 103% at W5 with p < 0.001) and the FMISO standardised uptake value (SUV) (27% at W0, 21% at W2 and by 25% at W5 with p < 0.001) within the primary GTV. CONCLUSIONS The proposed PVE-correction method resulted in a statistically significant increase of the hypoxic fraction (HF) with p < 0.001 and demonstrated results in better agreement with published HF data for HNSCC. To summarise, the proposed RC-based correction method can be a useful tool for a retrospective compensation against PVE.
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Affiliation(s)
- Athanasios Kafkaletos
- Division of Medical Physics, Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany.
- German Cancer Consortium (DKTK), Partner Site Freiburg, a partnership between DKFZ and Medical Center - University of Freiburg, Freiburg, Germany.
| | - Michael Mix
- Department of Nuclear Medicine, Medical Centre - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
| | - Ilias Sachpazidis
- Division of Medical Physics, Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
| | - Montserrat Carles
- Biomedical Imaging Research Group (GIBI230-PREBI) and Imaging La Fe Node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), La Fe Health Research Institute, Valencia, Spain
| | - Alexander Rühle
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
- Department of Radiation Oncology, University of Leipzig Medical Centre, Leipzig, Germany
| | - Juri Ruf
- Department of Nuclear Medicine, Medical Centre - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
- Department of Radiation Oncology, University of Leipzig Medical Centre, Leipzig, Germany
| | - Dimos Baltas
- Division of Medical Physics, Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, German Cancer Consortium (DKTK), partner site DKTK-Freiburg, University of Freiburg, Freiburg, Germany
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Anania V, Collier Q, Veraart J, Buikema AE, Vanhevel F, Billiet T, Jeurissen B, den Dekker AJ, Sijbers J. Improved diffusion parameter estimation by incorporating T 2 relaxation properties into the DKI-FWE model. Neuroimage 2022;:119219. [PMID: 35447354 DOI: 10.1016/j.neuroimage.2022.119219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 04/08/2022] [Accepted: 04/14/2022] [Indexed: 11/23/2022] Open
Abstract
The free water elimination (FWE) model and its kurtosis variant (DKI-FWE) can separate tissue and free water signal contributions, thus providing tissue-specific diffusional information. However, a downside of these models is that the associated parameter estimation problem is ill-conditioned, necessitating the use of advanced estimation techniques that can potentially bias the parameter estimates. In this work, we propose the T2-DKI-FWE model that exploits the T2 relaxation properties of both compartments, thereby better conditioning the parameter estimation problem and providing, at the same time, an additional potential biomarker (the T2 of tissue). In our approach, the T2 of tissue is estimated as an unknown parameter, whereas the T2 of free water is assumed known a priori and fixed to a literature value (1573 ms). First, the error propagation of an erroneous assumption on the T2 of free water is studied. Next, the improved conditioning of T2-DKI-FWE compared to DKI-FWE is illustrated using the Cramér-Rao lower bound matrix. Finally, the performance of the T2-DKI-FWE model is compared to that of the DKI-FWE and T2-DKI models on both simulated and real datasets. The error due to a biased approximation of the T2 of free water was found to be relatively small in various diffusion metrics and for a broad range of erroneous assumptions on its underlying ground truth value. Compared to DKI-FWE, using the T2-DKI-FWE model is beneficial for the identifiability of the model parameters. Our results suggest that the T2-DKI-FWE model can achieve precise and accurate diffusion parameter estimates, through effective reduction of free water partial volume effects and by using a standard nonlinear least squares approach. In conclusion, incorporating T2 relaxation properties into the DKI-FWE model improves the conditioning of the model fitting, while only requiring an acquisition scheme with at least two different echo times.
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Henf J, Grothe MJ, Brueggen K, Teipel S, Dyrba M. Mean diffusivity in cortical gray matter in Alzheimer's disease: The importance of partial volume correction. Neuroimage Clin 2017; 17:579-586. [PMID: 29201644 PMCID: PMC5702878 DOI: 10.1016/j.nicl.2017.10.005] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Revised: 09/06/2017] [Accepted: 10/03/2017] [Indexed: 01/08/2023]
Abstract
Mean diffusivity (MD) measured by diffusion tensor imaging can reflect microstructural alterations of the brain's gray matter (GM). Therefore, GM MD may be a sensitive marker of neurodegeneration related to Alzheimer's Disease (AD). However, due to partial volume effects (PVE), differences in MD may be overestimated because of a higher degree of brain atrophy in AD patients and in cases with mild cognitive impairment (MCI). Here, we evaluated GM MD changes in AD and MCI compared with healthy controls, and the effect of partial volume correction (PVC) on diagnostic utility of MD. We determined region of interest (ROI) and voxel-wise group differences and diagnostic accuracy of MD and volume measures between matched samples of 39 AD, 39 MCI and 39 healthy subjects before and after PVC. Additionally, we assessed whether effects of GM MD values on diagnosis were mediated by volume. ROI and voxel-wise group differences were reduced after PVC. When using these ROIs for predicting group separation in logistic models, both PVE corrected and uncorrected GM MD values yielded a poorer diagnostic accuracy in single predictor models than regional volume. For the discrimination of AD patients and healthy controls, the effect of GM MD on diagnosis was significantly mediated by volume of hippocampus and posterior cingulate ROIs. Our results suggest that GM MD measurements are strongly confounded by PVE in the presence of brain atrophy, underlining the necessity of PVC when using these measurements as specific metrics of microstructural tissue degeneration. Independently of PVC, regional MD was not superior to regional volume in separating prodromal and clinical stages of AD from healthy controls.
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Key Words
- AD, Alzheimer's Disease
- Alzheimer's disease
- DTI, diffusion tensor imaging
- Diffusion tensor imaging
- FLAIR, fluid-attenuated inversion recovery
- GM, gray matter
- Gray matter
- MCI, mild cognitive impairment
- MD, mean diffusivity
- Mean diffusivity
- Mild cognitive impairment
- PCC, posterior cingulate cortex
- PVC, partial volume correction
- PVE, partial volume effects
- Partial volume effects
- ROI, region of interest
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Affiliation(s)
- Judith Henf
- DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany; Department for Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany.
| | - Michel J Grothe
- DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany
| | | | - Stefan Teipel
- DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany; Department for Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Martin Dyrba
- DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany; MMIS Group, University of Rostock, Rostock, Germany
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Salminen LE, Conturo TE, Bolzenius JD, Cabeen RP, Akbudak E, Paul RH. REDUCING CSF PARTIAL VOLUME EFFECTS TO ENHANCE DIFFUSION TENSOR IMAGING METRICS OF BRAIN MICROSTRUCTURE. Technol Innov 2016; 18:5-20. [PMID: 27721931 DOI: 10.21300/18.1.2016.5] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Technological advances over recent decades now allow for in vivo observation of human brain tissue through the use of neuroimaging methods. While this field originated with techniques capable of capturing macrostructural details of brain anatomy, modern methods such as diffusion tensor imaging (DTI) that are now regularly implemented in research protocols have the ability to characterize brain microstructure. DTI has been used to reveal subtle micro-anatomical abnormalities in the prodromal phase ofº various diseases and also to delineate "normal" age-related changes in brain tissue across the lifespan. Nevertheless, imaging artifact in DTI remains a significant limitation for identifying true neural signatures of disease and brain-behavior relationships. Cerebrospinal fluid (CSF) contamination of brain voxels is a main source of error on DTI scans that causes partial volume effects and reduces the accuracy of tissue characterization. Several methods have been proposed to correct for CSF artifact though many of these methods introduce new limitations that may preclude certain applications. The purpose of this review is to discuss the complexity of signal acquisition as it relates to CSF artifact on DTI scans and review methods of CSF suppression in DTI. We will then discuss a technique that has been recently shown to effectively suppress the CSF signal in DTI data, resulting in fewer errors and improved measurement of brain tissue. This approach and related techniques have the potential to significantly improve our understanding of "normal" brain aging and neuropsychiatric and neurodegenerative diseases. Considerations for next-level applications are discussed.
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Affiliation(s)
- Lauren E Salminen
- Department of Psychology, University of Missouri - Saint Louis, St. Louis, MO, USA
| | - Thomas E Conturo
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Ryan P Cabeen
- Computer Science Department, Brown University, Providence, RI, USA
| | - Erbil Akbudak
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Robert H Paul
- Missouri Institute of Mental Health, St. Louis, MO, USA
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Reilhac A, Charil A, Wimberley C, Angelis G, Hamze H, Callaghan P, Garcia MP, Boisson F, Ryder W, Meikle SR, Gregoire MC. 4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging. Neuroimage 2015; 118:484-93. [PMID: 26080302 DOI: 10.1016/j.neuroimage.2015.06.029] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Revised: 05/25/2015] [Accepted: 06/09/2015] [Indexed: 11/19/2022] Open
Abstract
Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity.
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Affiliation(s)
- Anthonin Reilhac
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia.
| | - Arnaud Charil
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Catriona Wimberley
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Georgios Angelis
- Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Hasar Hamze
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Paul Callaghan
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Marie-Paule Garcia
- UMR 1037 INSERM/UPS, CRCT, 31062 Toulouse, France; Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia
| | - Frederic Boisson
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Will Ryder
- Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Steven R Meikle
- Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Marie-Claude Gregoire
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
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Wimberley C, Angelis G, Boisson F, Callaghan P, Fischer K, Pichler BJ, Meikle SR, Grégoire MC, Reilhac A. Simulation-based optimisation of the PET data processing for partial saturation approach protocols. Neuroimage 2014; 97:29-40. [PMID: 24742918 DOI: 10.1016/j.neuroimage.2014.04.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Revised: 03/27/2014] [Accepted: 04/03/2014] [Indexed: 11/27/2022] Open
Abstract
Positron emission tomography (PET) with [(11)C]Raclopride is an important tool for studying dopamine D2 receptor expression in vivo. [(11)C]Raclopride PET binding experiments conducted using the Partial Saturation Approach (PSA) allow the estimation of receptor density (B(avail)) and the in vivo affinity appK(D). The PSA is a simple, single injection, single scan experimental protocol that does not require blood sampling, making it ideal for use in longitudinal studies. In this work, we generated a complete Monte Carlo simulated PET study involving two groups of scans, in between which a biological phenomenon was inferred (a 30% decrease of B(avail)), and used it in order to design an optimal data processing chain for the parameter estimation from PSA data. The impact of spatial smoothing, noise removal and image resolution recovery technique on the statistical detection was investigated in depth. We found that image resolution recovery using iterative deconvolution of the image with the system point spread function associated with temporal data denoising greatly improves the accuracy and the statistical reliability of detecting the imposed phenomenon. Before optimisation, the inferred B(avail) variation between the two groups was underestimated by 42% and detected in 66% of cases, while a false decrease of appK(D) by 13% was detected in more than 11% of cases. After optimisation, the calculated B(avail) variation was underestimated by only 3.7% and detected in 89% of cases, while a false slight increase of appK(D) by 3.7% was detected in only 2% of cases. We found during this investigation that it was essential to adjust a factor that accounts for difference in magnitude between the non-displaceable ligand concentrations measured in the target and in the reference regions, for different data processing pathways as this ratio was affected by different image resolutions.
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Affiliation(s)
- Catriona Wimberley
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia.
| | - Georgios Angelis
- Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Frederic Boisson
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Paul Callaghan
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Kristina Fischer
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard-Karls University of Tübingen, Germany
| | - Bernd J Pichler
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard-Karls University of Tübingen, Germany
| | - Steven R Meikle
- Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Marie-Claude Grégoire
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
| | - Anthonin Reilhac
- Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia; Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia
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Berlot R, Metzler-Baddeley C, Jones DK, O'Sullivan MJ. CSF contamination contributes to apparent microstructural alterations in mild cognitive impairment. Neuroimage 2014; 92:27-35. [PMID: 24503415 DOI: 10.1016/j.neuroimage.2014.01.031] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Revised: 01/14/2014] [Accepted: 01/16/2014] [Indexed: 12/04/2022] Open
Abstract
Diffusion MRI is used widely to probe microstructural alterations in neurological and psychiatric disease. However, ageing and neurodegeneration are also associated with atrophy, which leads to artefacts through partial volume effects due to cerebrospinal-fluid contamination (CSFC). The aim of this study was to explore the influence of CSFC on apparent microstructural changes in mild cognitive impairment (MCI) at several spatial levels: individually reconstructed tracts; at the level of a whole white matter skeleton (tract-based spatial statistics); and histograms derived from all white matter. 25 individuals with MCI and 20 matched controls underwent diffusion MRI. We corrected for CSFC using a post-acquisition voxel-by-voxel approach of free-water elimination. Tracts varied in their susceptibility to CSFC. The apparent pattern of tract involvement in disease shifted when correction was applied. Both spurious group differences, driven by CSFC, and masking of true differences were observed. Tract-based spatial statistics were found to be robust across much of the skeleton but with some localised CSFC effects. Diffusivity measures were affected disproportionately in MCI, and group differences in fornix microstructure were exaggerated. Group differences in white matter histogram measures were also partly driven by CSFC. For diffusivity measures, up to two thirds of observed group differences were due to CSFC. Our results demonstrate that CSFC has an impact on quantitative differences between MCI and controls. Furthermore, it affects the apparent spatial pattern of white matter involvement. Free-water elimination provides a step towards disentangling intrinsic and volumetric alterations in individuals prone to atrophy. We examine the effect of CSFC on perceived microstructural alterations in MCI. We correct for CSFC with free-water elimination and assess at three spatial levels. The pattern of individual tract involvement is shifted due to CSFC. TBSS is robust to CSFC in much of the skeleton. Group differences in white matter diffusion histograms are partly driven by CSFC.
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Lee H, Caparelli E, Li H, Mandal A, Smith SD, Zhang S, Bilfinger TV, Benveniste H. Computerized MRS voxel registration and partial volume effects in single voxel 1H-MRS. Magn Reson Imaging 2013; 31:1197-205. [PMID: 23659770 DOI: 10.1016/j.mri.2013.04.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2012] [Revised: 02/23/2013] [Accepted: 04/02/2013] [Indexed: 01/01/2023]
Abstract
Partial volume effects in proton magnetic resonance spectroscopy in the brain have been studied previously in terms of proper water concentration calculations, but there is a lack of disclosure in terms of voxel placement techniques that would affect the calculations. The purpose of this study is to facilitate a fully automated MRS voxel registration method which is time efficient, accurate, and can be extended to all imaging modalities. A total of thirteen healthy adults underwent single voxel 1H-MRS scans in 3.0T MRI scanners. Transposition of a MRS voxel onto an anatomical scan is derived along with a full calculation of water concentration with a correction term to account for the partial volume effects. Five metabolites (tNAA, Glx, tCr, mI, and tCho) known to yield high reliability are studied. Pearson's correlation analyses between tissue volume fractions and metabolite concentrations were statistically significant in parietal (tCr, Glx, and tNAA) lobe and occipital lobe (tNAA). MRS voxel overlaps quantified by dice metric over repeated visits yielded 60%~70% and coefficients of variance in metabolites concentration were 4%~10%. These findings reiterate an importance of considering the partial volume effects when tissue water is used as an internal concentration reference so as to avoid misinterpreting a morphometric difference as a metabolic difference.
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Affiliation(s)
- Hedok Lee
- Department of Anesthesiology, State University of New York at Stony Brook, Stony Brook, NY 11794, USA.
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