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De Schepper S, Gnanasegaran G, De Vos W, Van de Casteele E, Dickson JC, Van den Wyngaert T. From SPECT/CT towards absolute quantification? - the case of unilateral condylar hyperplasia of the mandible. EJNMMI Phys 2024; 11:74. [PMID: 39177939 PMCID: PMC11343952 DOI: 10.1186/s40658-024-00676-6] [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: 03/26/2024] [Accepted: 08/05/2024] [Indexed: 08/24/2024] Open
Abstract
BACKGROUND Unilateral condylar hyperplasia (UCH) of the mandible is a rare condition characterized by asymmetric growth of the mandibular condyles. Bone scintigraphy with SPECT(/CT) is commonly used to diagnose UCH and guide treatment. Still, varying results have been reported using the traditional threshold of 55%:45% in relative tracer uptake. While absolute quantification of uptake on SPECT/CT could improve results, optimal correction and reconstruction settings are currently unknown. METHODS Three anthropomorphic phantoms representing UCH were developed from patient CT volumes and produced using 3D printing technology. Fillable spherical inserts of different sizes (Ø: 8-15 mm) were placed in the condylar positions representing symmetrical and asymmetrical distributions. Recovery coefficients were determined for SPECT/CT using various reconstruction corrections, including attenuation and scatter correction (ACSC), resolution modeling (RM), and partial volume correction (PVC) using phantom measurements. Uptake ratios between condyles and condyle to clivus were evaluated. Finally, the impact of these correction techniques on absolute activity and diagnostic accuracy was assessed in a retrospective patient cohort for the diagnostic threshold of 55%:45%. RESULTS The activity was only partially recovered in all spherical inserts (range: 22.5-64.9%). However, RM improved relative recovery by 20.2-62.3% compared to ACSC. In the symmetric phantoms, the 95% confidence interval (CI) of condyle ratios included the diagnostic threshold (57.6%:42.4%) for UCH when using ACSC potentially leading to false positives, but not for ACSCRM datasets. Partial volume corrections coefficients from the NEMA IQ phantom was positionally dependent, with improvements seen performing PVC using coefficients derived from anthropomorphic phantoms. Retrospective application in a patient cohort showed only a weak linear correlation (R²: 0.25-0.67) and large limits of agreement (9.6-12.5%) between different reconstructions. Up to 44% of patients were reclassified using the 55%:45% threshold. Using clinical outcome data, ACSCRM had highest sensitivity (91%; 95% CI 59-100%) and specificity (66%; 95% CI 47-81%), significantly improving specificity (P = 0.038). CONCLUSIONS Anthropomorphic phantoms were shown to be essential in determining optimal settings for acquisition, reconstruction, and analysis. SPECT/CT reconstructions with attenuation and scatter correction and resolution modeling are recommended and could improve specificity when using the 55%:45% threshold to assess condylar growth.
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Affiliation(s)
- Stijn De Schepper
- Department of Nuclear Medicine, Antwerp University Hospital, Drie Eikenstraat 655, Edegem, 2650, Belgium.
- Faculty of Medicine and Health Sciences (MICA - IPPON), University of Antwerp, Wilrijk, Belgium.
| | | | - Wouter De Vos
- Department of Oral and Maxillofacial Surgery, Antwerp University Hospital, Antwerp, Belgium
- Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium
| | - Elke Van de Casteele
- Department of Oral and Maxillofacial Surgery, Antwerp University Hospital, Antwerp, Belgium
- Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium
| | - John C Dickson
- Institute of Nuclear Medicine, University College of London Hospitals NHS, London, UK
| | - Tim Van den Wyngaert
- Department of Nuclear Medicine, Antwerp University Hospital, Drie Eikenstraat 655, Edegem, 2650, Belgium
- Faculty of Medicine and Health Sciences (MICA - IPPON), University of Antwerp, Wilrijk, Belgium
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Volpi T, Silvestri E, Aiello M, Lee JJ, Vlassenko AG, Goyal MS, Corbetta M, Bertoldo A. The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity? J Cereb Blood Flow Metab 2024; 44:1433-1449. [PMID: 38443762 PMCID: PMC11342718 DOI: 10.1177/0271678x241237974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 01/05/2024] [Accepted: 02/11/2024] [Indexed: 03/07/2024]
Abstract
Brain glucose metabolism, which can be investigated at the macroscale level with [18F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown. Here, using two multimodal datasets of healthy participants, we built a multivariable multilevel model of functional-metabolic associations, assessing multiple functional features, describing the 1) rs-fMRI signal, 2) hemodynamic response, 3) static and 4) time-varying functional connectivity, as predictors of the human brain's metabolic architecture. The full model was trained on one dataset and tested on the other to assess its reproducibility. We found that functional-metabolic spatial coupling is nonlinear and heterogeneous across the brain, and that local measures of rs-fMRI activity and synchrony are more tightly coupled to local metabolism. In the testing dataset, the degree of functional-metabolic spatial coupling was also related to peripheral metabolism. Overall, although a significant proportion of regional metabolic variability can be described by measures of spontaneous activity, additional efforts are needed to explain the remaining variance in the brain's 'dark energy'.
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Affiliation(s)
- Tommaso Volpi
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Erica Silvestri
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - John J Lee
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrei G Vlassenko
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Manu S Goyal
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
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Guo K, Quan Z, Li G, Li B, Kang F, Wang J. Decomposed FDG PET-based phenotypic heterogeneity predicting clinical prognosis and decision-making in temporal lobe epilepsy patients. Neurol Sci 2024; 45:3961-3969. [PMID: 38457084 DOI: 10.1007/s10072-024-07431-w] [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: 01/12/2024] [Accepted: 02/27/2024] [Indexed: 03/09/2024]
Abstract
OBJECTIVE This study utilized a data-driven Bayesian model to automatically identify distinct latent disease factors represented by overlapping glucose metabolism patterns from 18F-Fluorodeoxyglucose PET (18F-FDG PET) to analyze heterogeneity among patients with TLE. METHODS We employed unsupervised machine learning to estimate latent disease factors from 18F-FDG PET scans, representing whole-brain glucose metabolism patterns in seventy patients with TLE. We estimated the extent to which multiple distinct factors were expressed within each participant and analyzed their relevance to epilepsy burden, including seizure onset, duration, and frequency. Additionally, we established a predictive model for clinical prognosis and decision-making. RESULTS We identified three latent disease factors: hypometabolism in the unilateral temporal lobe and hippocampus (factor 1), hypometabolism in bilateral prefrontal lobes (factor 2), and hypometabolism in bilateral temporal lobes (factor 3), variably co-expressed within each patient. Factor 3 demonstrated the strongest negative correlation with the age of onset and duration (r = - 0.33, - 0.38 respectively, P < 0.05). The supervised classifier, trained on latent disease factors for predicting patient-specific antiepileptic drug (AED) responses, achieved an area under the curve (AUC) of 0.655. For post-surgical seizure outcomes, the AUC was 0.857, and for clinical decision-making, it was 0.965. CONCLUSIONS Decomposing 18F-FDG PET-based phenotypic heterogeneity facilitates individual-level predictions relevant to disease monitoring and personalized therapeutic strategies.
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Affiliation(s)
- Kun Guo
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, China
| | - Zhiyong Quan
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, China
| | - Guiyu Li
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, China
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fei Kang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, China.
| | - Jing Wang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, China.
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Kayal G, Van B, Andl G, Tu C, Wareing T, Wilderman S, Mikell J, Dewaraja YK. Linear Boltzmann equation solver for voxel-level dosimetry in radiopharmaceutical therapy: Comparison with Monte Carlo and kernel convolution. Med Phys 2024; 51:5604-5617. [PMID: 38436493 PMCID: PMC11321934 DOI: 10.1002/mp.16996] [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: 03/03/2023] [Revised: 01/12/2024] [Accepted: 01/28/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND With recent interest in patient-specific dosimetry for radiopharmaceutical therapy (RPT) and selective internal radiation therapy (SIRT), an increasing number of voxel-based algorithms are being evaluated. Monte Carlo (MC) radiation transport, generally considered to be the most accurate among different methods for voxel-level absorbed dose estimation, can be computationally inefficient for routine clinical use. PURPOSE This work demonstrates a recently implemented grid-based linear Boltzmann transport equation (LBTE) solver for fast and accurate voxel-based dosimetry in RPT and SIRT and benchmarks it against MC. METHODS A deterministic LBTE solver (Acuros MRT) was implemented within a commercial RPT dosimetry package (Velocity 4.1). The LBTE is directly discretized using an adaptive mesh refined grid and then the coupled photon-electron radiation transport is iteratively solved inside specified volumes to estimate radiation doses from both photons and charged particles in heterogeneous media. To evaluate the performance of the LBTE solver for RPT and SIRT applications, 177Lu SPECT/CT, 90Y PET/CT, and 131I SPECT/CT images of phantoms and patients were used. Multiple lesions (2-1052 mL) and normal organs were delineated for each study. Voxel dosimetry was performed with the LBTE solver, dose voxel kernel (DVK) convolution with density correction, and a validated in-house MC code using the same time-integrated activity and density maps as input to the different dose engines. The resulting dose maps, difference maps, and dose-volume-histogram (DVH) metrics were compared, to assess the voxel-level agreement. Evaluation of mean absorbed dose included comparison with structure-level estimates from OLINDA. RESULTS In the phantom inserts/compartments, the LBTE solver versus MC and DVK convolution demonstrated good agreement with mean absorbed dose and DVH metrics agreeing to within 5% except for the D90 and D70 metrics of a very low activity concentration insert of 90Y where the agreement was within 15%. In the patient studies (five patients imaged after 177Lu DOTATATE RPT, five after 90Y SIRT, and two after 131I radioimmunotherapy), in general, there was better agreement between the LBTE solver and MC than between LBTE solver and DVK convolution for mean absorbed dose and voxel-level evaluations. Across all patients for all three radionuclides, for soft tissue structures (kidney, liver, lesions), the mean absorbed dose estimates from the LBTE solver were in good agreement with those from MC (median difference < 1%, maximum 9%) and those from DVK (median difference < 5%, maximum 9%). The LBTE and OLINDA estimates for mean absorbed dose in kidneys and liver agreed to within 10%, but differences for lesions were larger with a maximum 14% for 177Lu, 23% for 90Y, and 26% for 131I. For bone regions, the agreement in mean absorbed doses between LBTE and both MC and DVK were similar (median < 11%, max 11%) while for lung the agreement between LBTE and MC (median < 1%, max 8%) was substantially better than between LBTE and DVK (median < 16%, max 33%). Voxel level estimates for soft tissue structures also showed good agreement between the LBTE solver and both MC and DVK with a median difference < 5% (maximum < 13%) for the DVH metrics with all three radionuclides. The largest difference in DVH metrics was for the D90 and D70 metric in lung and bone where the uptake was low. Here, the difference between LBTE and MC had a median value < 14% (maximum 23%) for bone and < 4% (maximum 37%) for lung, while the corresponding differences between LBTE and DVK were < 23% (maximum 31%) and < 67% (maximum 313%), respectively. For a typical patient with a matrix size of 166 × 166 × 129 (voxel size 3 × 3 × 3 mm3), voxel dosimetry using the LBTE solver was as fast as ∼2 min on a desktop computer. CONCLUSION Having established good agreement between the LBTE solver and MC for RPT and SIRT applications, the LBTE solver is a viable option for voxel dosimetry that can be faster than MC. Further analysis is being performed to encompass the broad range of radionuclides and conditions encountered clinically.
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Affiliation(s)
- Gunjan Kayal
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Benjamin Van
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - George Andl
- Varian Medical Systems, Atlanta, Georgia, USA
| | - Cheng Tu
- Varian Medical Systems, Atlanta, Georgia, USA
| | | | - Scott Wilderman
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Justin Mikell
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Yuni K. Dewaraja
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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Langley J, Bennett IJ, Hu XP. Examining iron-related off-target binding effects of 18F-AV1451 PET in the cortex of Aβ+ individuals. Eur J Neurosci 2024; 60:3614-3628. [PMID: 38722153 DOI: 10.1111/ejn.16362] [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: 02/10/2023] [Revised: 12/22/2023] [Accepted: 04/01/2024] [Indexed: 07/06/2024]
Abstract
The presence of neurofibrillary tangles containing hyper-phosphorylated tau is a characteristic of Alzheimer's disease (AD) pathology. The positron emission tomography (PET) radioligand sensitive to tau neurofibrillary tangles (18F-AV1451) also binds with iron. This off-target binding effect may be enhanced in older adults on the AD spectrum, particularly those with amyloid-positive biomarkers. Here, we examined group differences in 18F-AV1451 PET after controlling for iron-sensitive measures from magnetic resonance imaging (MRI) and its relationships to tissue microstructure and cognition in 40 amyloid beta positive (Aβ+) individuals, 20 amyloid beta negative (Aβ-) with MCI and 31 Aβ- control participants. After controlling for iron, increased 18F-AV1451 PET uptake was found in the temporal lobe and hippocampus of Aβ+ participants compared to Aβ- MCI and control participants. Within the Aβ+ group, significant correlations were seen between 18F-AV1451 PET uptake and tissue microstructure and these correlations remained significant after controlling for iron. These findings indicate that off-target binding of iron to the 18F-AV1451 ligand may not affect its sensitivity to Aβ status or cognition in early-stage AD.
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Affiliation(s)
- Jason Langley
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, California, USA
| | - Ilana J Bennett
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Xiaoping P Hu
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, California, USA
- Department of Bioengineering, University of California Riverside, Riverside, California, USA
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Guo ZH, Zhang JG, Shao XQ, Hu WH, Sang L, Zheng Z, Zhang C, Wang X, Li CD, Mo JJ, Zhang K. Neural network mapping of gelastic behavior in children with hypothalamus hamartoma. World J Pediatr 2024; 20:735-745. [PMID: 37938453 PMCID: PMC11269438 DOI: 10.1007/s12519-023-00763-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 09/17/2023] [Indexed: 11/09/2023]
Abstract
BACKGROUND Hypothalamus hamartomas (HHs) are rare, congenital, tumor-like, and nonprogressive malformations resulting in drug-resistant epilepsy, mainly affecting children. Gelastic seizures (GS) are an early hallmark of epilepsy with HH. The aim of this study was to explore the disease progression and the underlying physiopathological mechanisms of pathological laughter in HH. METHODS We obtained clinical information and metabolic images of 56 HH patients and utilized ictal semiology evaluation to stratify the specimens into GS-only, GS-plus, and no-GS subgroups and then applied contrasted trajectories inference (cTI) to calculate the pseudotime value and evaluate GS progression. Ordinal logistic regression was performed to identify neuroimaging-clinical predictors of GS, and then voxelwise lesion network-symptom mapping (LNSM) was applied to explore GS-associated brain regions. RESULTS cTI inferred the specific metabolism trajectories of GS progression and revealed increased complexity from GS to other seizure types. This was further validated via actual disease duration (Pearson R = 0.532, P = 0.028). Male sex [odds ratio (OR) = 2.611, P = 0.013], low age at seizure onset (OR = 0.361, P = 0.005), high normalized HH metabolism (OR = - 1.971, P = 0.037) and severe seizure burden (OR = - 0.006, P = 0.032) were significant neuroimaging clinical predictors. LNSM revealed that the dysfunctional cortico-subcortico-cerebellar network of GS and the somatosensory cortex (S1) represented a negative correlation. CONCLUSIONS This study sheds light on the clinical characteristics and progression of GS in children with HH. We identified distinct subtypes of GS and demonstrated the involvement of specific brain regions at the cortical-subcortical-cerebellar level. These valuable results contribute to our understanding of the neural correlates of GS.
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Affiliation(s)
- Zhi-Hao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiao-Qiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wen-Han Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Zhong Zheng
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chun-De Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
| | - Jia-Jie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
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Leube J, Claeys W, Gustafsson J, Salas-Ramirez M, Lassmann M, Koole M, Tran-Gia J. Position dependence of recovery coefficients in 177Lu-SPECT/CT reconstructions - phantom simulations and measurements. EJNMMI Phys 2024; 11:52. [PMID: 38937408 PMCID: PMC11211301 DOI: 10.1186/s40658-024-00662-y] [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: 03/11/2024] [Accepted: 06/17/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Although the importance of quantitative SPECT has increased tremendously due to newly developed therapeutic radiopharmaceuticals, there are still no accreditation programs to harmonize SPECT imaging. Work is currently underway to develop an accreditation for quantitative 177Lu SPECT/CT. The aim of this study is to verify whether the positioning of the spheres within the phantom has an influence on the recovery and thus needs to be considered in SPECT harmonization. In addition, the effects of these recovery coefficients on a potential partial volume correction as well as absorbed-dose estimates are investigated. METHODS Using a low-dose CT of a SPECT/CT acquisition, a computerized version of the NEMA body phantom was created using a semi-automatic threshold-based method. Based on the mass-density map, the detector orbit, and the sphere centers, realistic SPECT acquisitions of all possible 720 sphere configurations of both the PET and the SPECT versions of the NEMA Body Phantom were generated using Monte Carlo simulations. SPECT reconstructions with different numbers of updates were performed without (CASToR) and with resolution modeling (STIR). Recovery coefficients were calculated for all permutations, reconstruction methods, and phantoms, and their dependence on the sphere positioning was investigated. Finally, the simulation-based findings were validated using SPECT/CT acquisitions of six different sphere configurations. RESULTS Our analysis shows that sphere positioning has a significant impact on the recovery for both of the reconstruction methods and the phantom type. Although resolution modeling resulted in significantly higher recovery, the relative variation in recovery within the 720 permutations was even larger. When examining the extreme values of the recovery, reconstructions without resolution modeling were influenced primarily by the sphere position, while with resolution modeling the volume of the two adjacent spheres had a larger influence. The SPECT measurements confirmed these observations, and the recovery curves showed good overall agreement with the simulated data. CONCLUSION Our study shows that sphere positioning has a significant impact on the recovery obtained in NEMA sphere phantom measurements and should therefore be considered in a future SPECT accreditation. Furthermore, the single-measurement method normally performed for PVC should be reconsidered to account for the position dependency.
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Affiliation(s)
- Julian Leube
- Department of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacherstr. 6, Würzburg, 97080, Germany.
| | - Wies Claeys
- Department of Imaging and Pathology, KU Leuven, Herestraat 49, Leuven, 3000, Belgium
| | - Johan Gustafsson
- Medical Radiation Physics Lund, Lund University, Skåne University Hospital Lund, Lund, 221 85, Sweden
| | - Maikol Salas-Ramirez
- Department of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacherstr. 6, Würzburg, 97080, Germany
| | - Michael Lassmann
- Department of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacherstr. 6, Würzburg, 97080, Germany
| | - Michel Koole
- Department of Imaging and Pathology, KU Leuven, Herestraat 49, Leuven, 3000, Belgium
| | - Johannes Tran-Gia
- Department of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacherstr. 6, Würzburg, 97080, Germany
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Lee S, Kim SE, Jang H, Kim JP, Sohn G, Park YH, Ham H, Gu Y, Park CJ, Kim HJ, Na DL, Kim K, Seo SW. Distinct effects of blood pressure parameters on Alzheimer's and vascular markers in 1,952 Asian individuals without dementia. Alzheimers Res Ther 2024; 16:125. [PMID: 38863019 PMCID: PMC11167921 DOI: 10.1186/s13195-024-01483-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: 11/12/2023] [Accepted: 05/15/2024] [Indexed: 06/13/2024]
Abstract
BACKGROUND Risk factors for cardiovascular disease, including elevated blood pressure, are known to increase risk of Alzheimer's disease. There has been increasing awareness of the relationship between long-term blood pressure (BP) patterns and their effects on the brain. We aimed to investigate the association of repeated BP measurements with Alzheimer's and vascular disease markers. METHODS We recruited 1,952 participants without dementia between August 2015 and February 2022. During serial clinic visits, we assessed both systolic BP (SBP) and diastolic BP (DBP), and visit-to-visit BP variability (BPV) was quantified from repeated measurements. In order to investigate the relationship of mean SBP (or DBP) with Alzheimer's and vascular markers and cognition, we performed multiple linear and logistic regression analyses after controlling for potential confounders (Model 1). Next, we investigated the relationship of with variation of SBP (or DBP) with the aforementioned variables by adding it into Model 1 (Model 2). In addition, mediation analyses were conducted to determine mediation effects of Alzheimer's and vascular makers on the relationship between BP parameters and cognitive impairment. RESULTS High Aβ uptake was associated with greater mean SBP (β = 1.049, 95% confidence interval 1.016-1.083). High vascular burden was positively associated with mean SBP (odds ratio = 1.293, 95% CI 1.015-1.647) and mean DBP (1.390, 1.098-1.757). High tau uptake was related to greater systolic BPV (0.094, 0.001-0.187) and diastolic BPV (0.096, 0.007-0.184). High Aβ uptake partially mediated the relationship between mean SBP and the Mini-Mental State Examination (MMSE) scores. Hippocampal atrophy mediated the relationship between diastolic BPV and MMSE scores. CONCLUSIONS Each BP parameter affects Alzheimer's and vascular disease markers differently, which in turn leads to cognitive impairment. Therefore, it is necessary to appropriately control specific BP parameters to prevent the development of dementia. Furthermore, a better understanding of pathways from specific BP parameters to cognitive impairments might enable us to select the managements targeting the specific BP parameters to prevent dementia effectively.
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Affiliation(s)
- Sungjoo Lee
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 48108, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Gyeongmo Sohn
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 48108, Republic of Korea
| | - Yu Hyun Park
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Hongki Ham
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Yuna Gu
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Chae Jung Park
- Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Kyunga Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Department of Data Convergence & Future Medicine, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
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9
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Leube J, Gustafsson J, Lassmann M, Salas-Ramirez M, Tran-Gia J. A Deep-Learning-Based Partial-Volume Correction Method for Quantitative 177Lu SPECT/CT Imaging. J Nucl Med 2024; 65:980-987. [PMID: 38637141 PMCID: PMC11149598 DOI: 10.2967/jnumed.123.266889] [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: 10/27/2023] [Revised: 03/15/2024] [Indexed: 04/20/2024] Open
Abstract
With the development of new radiopharmaceutical therapies, quantitative SPECT/CT has progressively emerged as a crucial tool for dosimetry. One major obstacle of SPECT is its poor resolution, which results in blurring of the activity distribution. Especially for small objects, this so-called partial-volume effect limits the accuracy of activity quantification. Numerous methods for partial-volume correction (PVC) have been proposed, but most methods have the disadvantage of assuming a spatially invariant resolution of the imaging system, which does not hold for SPECT. Furthermore, most methods require a segmentation based on anatomic information. Methods: We introduce DL-PVC, a methodology for PVC of 177Lu SPECT/CT imaging using deep learning (DL). Training was based on a dataset of 10,000 random activity distributions placed in extended cardiac-torso body phantoms. Realistic SPECT acquisitions were created using the SIMIND Monte Carlo simulation program. SPECT reconstructions without and with resolution modeling were performed using the CASToR and STIR reconstruction software, respectively. The pairs of ground-truth activity distributions and simulated SPECT images were used for training various U-Nets. Quantitative analysis of the performance of these U-Nets was based on metrics such as the structural similarity index measure or normalized root-mean-square error, but also on volume activity accuracy, a new metric that describes the fraction of voxels in which the determined activity concentration deviates from the true activity concentration by less than a certain margin. On the basis of this analysis, the optimal parameters for normalization, input size, and network architecture were identified. Results: Our simulation-based analysis revealed that DL-PVC (0.95/7.8%/35.8% for structural similarity index measure/normalized root-mean-square error/volume activity accuracy) outperforms SPECT without PVC (0.89/10.4%/12.1%) and after iterative Yang PVC (0.94/8.6%/15.1%). Additionally, we validated DL-PVC on 177Lu SPECT/CT measurements of 3-dimensionally printed phantoms of different geometries. Although DL-PVC showed activity recovery similar to that of the iterative Yang method, no segmentation was required. In addition, DL-PVC was able to correct other image artifacts such as Gibbs ringing, making it clearly superior at the voxel level. Conclusion: In this work, we demonstrate the added value of DL-PVC for quantitative 177Lu SPECT/CT. Our analysis validates the functionality of DL-PVC and paves the way for future deployment on clinical image data.
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Affiliation(s)
- Julian Leube
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany; and
| | | | - Michael Lassmann
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany; and
| | - Maikol Salas-Ramirez
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany; and
| | - Johannes Tran-Gia
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany; and
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10
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Costoya-Sánchez A, Moscoso A, Sobrino T, Ruibal Á, Grothe MJ, Schöll M, Silva-Rodríguez J, Aguiar P. Partial volume correction in longitudinal tau PET studies: is it really needed? Neuroimage 2024; 289:120537. [PMID: 38367651 DOI: 10.1016/j.neuroimage.2024.120537] [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: 12/12/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/19/2024] Open
Abstract
BACKGROUND [18F]flortaucipir (FTP) tau PET quantification is known to be affected by non-specific binding in off-target regions. Although partial volume correction (PVC) techniques partially account for this effect, their inclusion may also introduce noise and variability into the quantification process. While the impact of these effects has been studied in cross-sectional designs, the benefits and drawbacks of PVC on longitudinal FTP studies is still under scrutiny. The aim of this work was to study the performance of the most common PVC techniques for longitudinal FTP imaging. METHODS A cohort of 247 individuals from the Alzheimer's Disease Neuroimaging Initiative with concurrent baseline FTP-PET, amyloid-beta (Aβ) PET and structural MRI, as well as with follow-up FTP-PET and MRI were included in the study. FTP-PET scans were corrected for partial volume effects using Meltzer's, a simple and popular analytical PVC, and both the region-based voxel-wise (RBV) and the iterative Yang (iY) corrections. FTP SUVR values and their longitudinal rates of change were calculated for regions of interest (ROI) corresponding to Braak Areas I-VI, for a temporal meta-ROI and for regions typically displaying off-target FTP binding (caudate, putamen, pallidum, thalamus, choroid plexus, hemispheric white matter, cerebellar white matter, and cerebrospinal fluid). The longitudinal correlation between binding in off-target and target ROIs was analysed for the different PVCs. Additionally, group differences in longitudinal FTP SUVR rates of change between Aβ-negative (A-) and Aβ-positive (A+), and between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, were studied. Finally, we compared the ability of different partial-volume-corrected baseline FTP SUVRs to predict longitudinal brain atrophy and cognitive decline. RESULTS Among off-target ROIs, hemispheric white matter showed the highest correlation with longitudinal FTP SUVR rates from cortical target ROIs (R2=0.28-0.82), with CSF coming in second (R2=0.28-0.42). Application of voxel-wise PVC techniques minimized this correlation, with RBV performing best (R2=0.00-0.07 for hemispheric white matter). PVC also increased group differences between CU and CI individuals in FTP SUVR rates of change across all target regions, with RBV again performing best (No PVC: Cohen's d = 0.26-0.66; RBV: Cohen's d = 0.43-0.74). These improvements were not observed for differentiating A- from A+ groups. Additionally, voxel-wise PVC techniques strengthened the correlation between baseline FTP SUVR and longitudinal grey matter atrophy and cognitive decline. CONCLUSION Quantification of longitudinal FTP SUVR rates of change is affected by signal from off-target regions, especially the hemispheric white matter and the CSF. Voxel-wise PVC techniques significantly reduce this effect. PVC provided a significant but modest benefit for tasks involving the measurement of group-level longitudinal differences. These findings are particularly relevant for the estimations of sample sizes and analysis methodologies of longitudinal group studies.
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Affiliation(s)
- Alejandro Costoya-Sánchez
- Molecular Imaging Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Av. Barcelona SN, 15782, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain
| | - Alexis Moscoso
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
| | - Tomás Sobrino
- NeuroAging Laboratory Group (NEURAL), Clinical Neurosciences Research Laboratories (LINC), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
| | - Álvaro Ruibal
- Molecular Imaging Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Av. Barcelona SN, 15782, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain
| | - Michel J Grothe
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain; Reina Sofía Alzheimer's Centre, CIEN Foundation, ISCIII, Madrid, 28031, Spain
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden; Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Jesús Silva-Rodríguez
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain; Reina Sofía Alzheimer's Centre, CIEN Foundation, ISCIII, Madrid, 28031, Spain.
| | - Pablo Aguiar
- Molecular Imaging Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Av. Barcelona SN, 15782, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Travesía da Choupana s/n, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain.
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11
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Providência L, van der Weijden CWJ, Mohr P, van Sluis J, van Snick JH, Slart RHJA, Dierckx RAJO, Lammertsma AA, Tsoumpas C. Can Internal Carotid Arteries Be Used for Noninvasive Quantification of Brain PET Studies? J Nucl Med 2024; 65:600-606. [PMID: 38485272 DOI: 10.2967/jnumed.123.266675] [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: 09/19/2023] [Revised: 01/23/2024] [Indexed: 04/04/2024] Open
Abstract
Because of the limited axial field of view of conventional PET scanners, the internal carotid arteries are commonly used to obtain an image-derived input function (IDIF) in quantitative brain PET. However, time-activity curves extracted from the internal carotids are prone to partial-volume effects due to the limited PET resolution. This study aimed to assess the use of the internal carotids for quantifying brain glucose metabolism before and after partial-volume correction. Methods: Dynamic [18F]FDG images were acquired on a 106-cm-long PET scanner, and quantification was performed with a 2-tissue-compartment model and Patlak analysis using an IDIF extracted from the internal carotids. An IDIF extracted from the ascending aorta was used as ground truth. Results: The internal carotid IDIF underestimated the area under the curve by 37% compared with the ascending aorta IDIF, leading to Ki values approximately 17% higher. After partial-volume correction, the mean relative Ki differences calculated with the ascending aorta and internal carotid IDIFs dropped to 7.5% and 0.05%, when using a 2-tissue-compartment model and Patlak analysis, respectively. However, microparameters (K 1, k 2, k 3) derived from the corrected internal carotid curve differed significantly from those obtained using the ascending aorta. Conclusion: These results suggest that partial-volume-corrected internal carotids may be used to estimate Ki but not kinetic microparameters. Further validation in a larger patient cohort with more variable kinetics is needed for more definitive conclusions.
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Affiliation(s)
- Laura Providência
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Chris W J van der Weijden
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Philipp Mohr
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Joyce van Sluis
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Johannes H van Snick
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Riemer H J A Slart
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rudi A J O Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Adriaan A Lammertsma
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Charalampos Tsoumpas
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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12
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Azimi MS, Kamali-Asl A, Ay MR, Zeraatkar N, Hosseini MS, Sanaat A, Dadgar H, Arabi H. Deep learning-based partial volume correction in standard and low-dose positron emission tomography-computed tomography imaging. Quant Imaging Med Surg 2024; 14:2146-2164. [PMID: 38545051 PMCID: PMC10963814 DOI: 10.21037/qims-23-871] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 11/20/2023] [Indexed: 08/05/2024]
Abstract
BACKGROUND Positron emission tomography (PET) imaging encounters the obstacle of partial volume effects, arising from its limited intrinsic resolution, giving rise to (I) considerable bias, particularly for structures comparable in size to the point spread function (PSF) of the system; and (II) blurred image edges and blending of textures along the borders. We set out to build a deep learning-based framework for predicting partial volume corrected full-dose (FD + PVC) images from either standard or low-dose (LD) PET images without requiring any anatomical data in order to provide a joint solution for partial volume correction and de-noise LD PET images. METHODS We trained a modified encoder-decoder U-Net network with standard of care or LD PET images as the input and FD + PVC images by six different PVC methods as the target. These six PVC approaches include geometric transfer matrix (GTM), multi-target correction (MTC), region-based voxel-wise correction (RBV), iterative Yang (IY), reblurred Van-Cittert (RVC), and Richardson-Lucy (RL). The proposed models were evaluated using standard criteria, such as peak signal-to-noise ratio (PSNR), root mean squared error (RMSE), structural similarity index (SSIM), relative bias, and absolute relative bias. RESULTS Different levels of error were observed for these partial volume correction methods, which were relatively smaller for GTM with a SSIM of 0.63 for LD and 0.29 for FD, IY with an SSIM of 0.63 for LD and 0.67 for FD, RBV with an SSIM of 0.57 for LD and 0.65 for FD, and RVC with an SSIM of 0.89 for LD and 0.94 for FD PVC approaches. However, large quantitative errors were observed for multi-target MTC with an RMSE of 2.71 for LD and 2.45 for FD and RL with an RMSE of 5 for LD and 3.27 for FD PVC approaches. CONCLUSIONS We found that the proposed framework could effectively perform joint de-noising and partial volume correction for PET images with LD and FD input PET data (LD vs. FD). When no magnetic resonance imaging (MRI) images are available, the developed deep learning models could be used for partial volume correction on LD or standard PET-computed tomography (PET-CT) scans as an image quality enhancement technique.
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Affiliation(s)
- Mohammad-Saber Azimi
- Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran
- Research Center for Molecular and Cellular Imaging (RCMCI), Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Alireza Kamali-Asl
- Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran
| | - Mohammad-Reza Ay
- Research Center for Molecular and Cellular Imaging (RCMCI), Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences (TUMS), Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | - Amirhossein Sanaat
- Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
| | - Habibollah Dadgar
- Cancer Research Center, Razavi Hospital, Imam Reza International University, Mashhad, Iran
| | - Hossein Arabi
- Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
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13
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Azimi M, Kamali-Asl A, Ay MR, Zeraatkar N, Hosseini MS, Sanaat A, Arabi H. Attention-based deep neural network for partial volume correction in brain 18F-FDG PET imaging. Phys Med 2024; 119:103315. [PMID: 38377837 DOI: 10.1016/j.ejmp.2024.103315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 10/04/2023] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Abstract
PURPOSE This work set out to propose an attention-based deep neural network to predict partial volume corrected images from PET data not utilizing anatomical information. METHODS An attention-based convolutional neural network (ATB-Net) is developed to predict PVE-corrected images in brain PET imaging by concentrating on anatomical areas of the brain. The performance of the deep neural network for performing PVC without using anatomical images was evaluated for two PVC methods, including iterative Yang (IY) and reblurred Van-Cittert (RVC) approaches. The RVC and IY PVC approaches were applied to PET images to generate the reference images. The training of the U-Net network for the partial volume correction was trained twice, once without using the attention module and once with the attention module concentrating on the anatomical brain regions. RESULTS Regarding the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and root mean square error (RMSE) metrics, the proposed ATB-Net outperformed the standard U-Net model (without attention compartment). For the RVC technique, the ATB-Net performed just marginally better than the U-Net; however, for the IY method, which is a region-wise method, the attention-based approach resulted in a substantial improvement. The mean absolute relative SUV difference and mean absolute relative bias improved by 38.02 % and 91.60 % for the RVC method and 77.47 % and 79.68 % for the IY method when using the ATB-Net model, respectively. CONCLUSIONS Our results propose that without using anatomical data, the attention-based DL model could perform PVC on PET images, which could be employed for PVC in PET imaging.
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Affiliation(s)
- MohammadSaber Azimi
- Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran
| | - Alireza Kamali-Asl
- Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran.
| | - Mohammad-Reza Ay
- Research Center for Molecular and Cellular Imaging (RCMCI), Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences (TUMS), Tehran, Iran; Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | - Amirhossein Sanaat
- Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland
| | - Hossein Arabi
- Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland.
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14
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Ananth MR, Gardus JD, Huang C, Palekar N, Slifstein M, Zaborszky L, Parsey RV, Talmage DA, DeLorenzo C, Role LW. Loss of cholinergic input to the entorhinal cortex is an early indicator of cognitive impairment in natural aging of humans and mice. RESEARCH SQUARE 2024:rs.3.rs-3851086. [PMID: 38260541 PMCID: PMC10802688 DOI: 10.21203/rs.3.rs-3851086/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
In a series of translational experiments using fully quantitative positron emission tomography (PET) imaging with a new tracer specific for the vesicular acetylcholine transporter ([18F]VAT) in vivo in humans, and genetically targeted cholinergic markers in mice, we evaluated whether changes to the cholinergic system were an early feature of age-related cognitive decline. We found that deficits in cholinergic innervation of the entorhinal cortex (EC) and decline in performance on behavioral tasks engaging the EC are, strikingly, early features of the aging process. In human studies, we recruited older adult volunteers that were physically healthy and without prior clinical diagnosis of cognitive impairment. Using [18F]VAT PET imaging, we demonstrate that there is measurable loss of cholinergic inputs to the EC that can serve as an early signature of decline in EC cognitive performance. These deficits are specific to the cholinergic circuit between the medial septum and vertical limb of the diagonal band (MS/vDB; CH1/2) to the EC. Using diffusion imaging, we further demonstrate impaired structural connectivity in the tracts between the MS/vDB and EC in older adults with mild cognitive impairment. Experiments in mouse, designed to parallel and extend upon the human studies, used high resolution imaging to evaluate cholinergic terminal density and immediate early gene (IEG) activity of EC neurons in healthy aging mice and in mice with genetic susceptibility to accelerated accumulation amyloid beta plaques and hyperphosphorylated mouse tau. Across species and aging conditions, we find that the integrity of cholinergic projections to the EC directly correlates with the extent of EC activation and with performance on EC-related object recognition memory tasks. Silencing EC-projecting cholinergic neurons in young, healthy mice during the object-location memory task impairs object recognition performance, mimicking aging. Taken together we identify a role for acetylcholine in normal EC function and establish loss of cholinergic input to the EC as an early, conserved feature of age-related cognitive decline in both humans and rodents.
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15
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Mandeville JB, Efthimiou N, Weigand-Whittier J, Hardy E, Knudsen GM, Jørgensen LM, Chen YCI. Partial volume correction of PET image data using geometric transfer matrices based on uniform B-splines. Phys Med Biol 2024; 69:055020. [PMID: 38271737 DOI: 10.1088/1361-6560/ad22a0] [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: 07/18/2023] [Accepted: 01/25/2024] [Indexed: 01/27/2024]
Abstract
Objective. Most methods for partial volume correction (PVC) of positron emission tomography (PET) data employ anatomical segmentation of images into regions of interest. This approach is not optimal for exploratory functional imaging beyond regional hypotheses. Here, we describe a novel method for unbiased voxel-wise PVC.Approach.B-spline basis functions were combined with geometric transfer matrices to enable a method (bsGTM) that provides PVC or alternatively provides smoothing with minimal regional crosstalk. The efficacy of the proposed method was evaluated using Monte Carlo simulations, human PET data, and murine functional PET data.Main results.In simulations, bsGTM provided recovery of partial volume signal loss comparable to iterative deconvolution, while demonstrating superior resilience to noise. In a real murine PET dataset, bsGTM yielded much higher sensitivity for detecting amphetamine-induced reduction of [11C]raclopride binding potential. In human PET data, bsGTM smoothing enabled increased signal-to-noise ratios with less degradation of binding potentials relative to Gaussian convolution or non-local means.Significance.bsGTM offers improved performance for PVC relative to iterative deconvolution, the current method of choice for voxel-wise PVC, especially in the common PET regime of low signal-to-noise ratio. The new method provides an anatomically unbiased way to compensate partial volume errors in cases where anatomical segmentation is unavailable or of questionable relevance or accuracy.
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Affiliation(s)
- Joseph B Mandeville
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Nikos Efthimiou
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Jonah Weigand-Whittier
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston MA, United States of America
- Department of Bioengineering, University of California, Berkeley CA, United States of America
| | - Erin Hardy
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston MA, United States of America
| | - Gitte M Knudsen
- Neurobiology Research Unit, Rigshospitalet and University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Louise M Jørgensen
- Neurobiology Research Unit, Rigshospitalet and University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Yin-Ching I Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
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16
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Salvadori J, Allegrini O, Opsommer T, Carullo J, Sarrut D, Porot C, Ritzenthaler F, Meyer P, Namer IJ. Anatomy-based correction of kidney PVE on [Formula: see text] SPECT images. EJNMMI Phys 2024; 11:15. [PMID: 38316677 PMCID: PMC11266336 DOI: 10.1186/s40658-024-00612-8] [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: 10/02/2023] [Accepted: 01/15/2024] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND In peptide receptor radionuclide therapy (PRRT), accurate quantification of kidney activity on post-treatment SPECT images paves the way for patient-specific treatment. Due to the limited spatial resolution of SPECT images, the partial volume effect (PVE) is a significant source of quantitative bias. In this study, we aimed to evaluate the performance and robustness of anatomy-based partial volume correction (PVC) algorithms to recover the accurate activity concentration of realistic kidney geometries on [Formula: see text]Lu SPECT images recorded under clinical conditions. METHODS Based on the CT scan data from patients, three sets of fillable kidneys with surface-to-volume (S:V) ratios ranging from 1.5 to 2.8 cm-1, were 3D printed and attached in a IEC phantom. Quantitative [Formula: see text]Lu SPECT/CT acquisitions were performed on a GE Discovery NM CT 870 DR camera for the three modified IEC phantoms and for 6 different Target-To-Background ratios (TBRs: 2, 4, 6, 8, 10, 12). Two region-based (GTM and Labbé) and five voxel-based (GTM + MTC, Labbé + MTC, GTM + RBV, Labbé + RBV and IY) methods were evaluated with this data set. Additionally, the robustness of PVC methods to Point Spread Function (PSF) discrepancies, registration mismatches and background heterogeneity was evaluated. RESULTS Without PVC, the average kidney RCs across all TBRs ranged from 0.66 ± 0.05 (smallest kidney) to 0.80 ± 0.03 (largest kidney). For a TBR of 12, all anatomy-based method were able to recover the kidneys activity concentration with an error < 6%. All methods result in a comparable decline in RC restoration with decreasing TBR. The Labbé method was the most robust against PSF and registration mismatches but was also the most sensitive to background heterogeneity. Among the voxel-based methods, MTC images were less uniform than RBV and IY images at the outer edge of high uptake areas (kidneys and spheres). CONCLUSION Anatomy-based PVE correction allows for accurate SPECT quantification of the [Formula: see text]Lu activity concentration with realistic kidney geometries. Combined with recent progress in deep-learning algorithms for automatic anatomic segmentation of whole-body CT, these methods could be of particular interest for a fully automated OAR dosimetry pipeline with PVE correction.
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Affiliation(s)
- Julien Salvadori
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France.
| | - Oreste Allegrini
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France
| | - Thomas Opsommer
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France
| | - Josefina Carullo
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France
| | - David Sarrut
- Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Centre Léon Bérard, Lyon, France
| | - Clemence Porot
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France
| | | | - Philippe Meyer
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France
- ICUBE, CNRS UMR-7357, University of Strasbourg, Strasbourg, France
| | - Izzie-Jacques Namer
- Institut de cancérologie Strasbourg Europe (ICANS), Strasbourg, France
- ICUBE, CNRS UMR-7357, University of Strasbourg, Strasbourg, France
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Moallemian S, Salmon E, Bahri MA, Beliy N, Delhaye E, Balteau E, Degueldre C, Phillips C, Bastin C. Multimodal imaging of microstructural cerebral alterations and loss of synaptic density in Alzheimer's disease. Neurobiol Aging 2023; 132:24-35. [PMID: 37717552 DOI: 10.1016/j.neurobiolaging.2023.08.001] [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: 04/11/2023] [Revised: 08/01/2023] [Accepted: 08/05/2023] [Indexed: 09/19/2023]
Abstract
Multiple neuropathological events are involved in Alzheimer's disease (AD). The current study investigated the concurrence of neurodegeneration, increased iron content, atrophy, and demyelination in AD. Quantitative multiparameter magnetic resonance imaging (MRI) maps providing neuroimaging biomarkers for myelination and iron content along with synaptic density measurements using [18F] UCB-H PET were acquired in 24 AD and 19 Healthy controls (19 males). The whole brain voxel-wise group comparison revealed demyelination in the right hippocampus, while no significant iron content difference was detected. Bilateral atrophy and synaptic density loss were observed in the hippocampus and amygdala. The multivariate GLM (mGLM) analysis shows a bilateral difference in the hippocampus and amygdala, right pallidum, left fusiform and temporal lobe suggesting that these regions are the most affected despite the diverse differences in brain tissue properties in AD. Demyelination was identified as the most affecting factor in the observed differences. Here, the mGLM is introduced as an alternative for multiple comparisons between different modalities, reducing the risk of false positives while informing about the co-occurrence of neuropathological processes in AD.
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Affiliation(s)
- Soodeh Moallemian
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Eric Salmon
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Mohamed Ali Bahri
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Nikita Beliy
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Emma Delhaye
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Evelyne Balteau
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Christian Degueldre
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Christophe Phillips
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
| | - Christine Bastin
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium.
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Cousins O, Schubert JJ, Chandra A, Veronese M, Valkimadi P, Creese B, Khan Z, Arathimos R, Hampshire A, Rosenzweig I, Ballard C, Corbett A, Aasland D, Velayudhan L, O'Neill M, Collier D, Awais R, Sander K, Årstad E, Howes O, Turkheimer F, Hodges A. Microglial activation, tau and amyloid deposition in TREM2 p.R47H carriers and mild cognitive impairment patients: a multi-modal/multi-tracer PET/MRI imaging study with influenza vaccine immune challenge. J Neuroinflammation 2023; 20:272. [PMID: 37990275 PMCID: PMC10664604 DOI: 10.1186/s12974-023-02945-0] [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: 03/21/2023] [Accepted: 10/31/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Microglia are increasingly understood to play an important role in the pathogenesis of Alzheimer's disease. The rs75932628 (p.R47H) TREM2 variant is a well-established risk factor for Alzheimer's disease. TREM2 is a microglial cell surface receptor. In this multi-modal/multi-tracer PET/MRI study we investigated the effect of TREM2 p.R47H carrier status on microglial activation, tau and amyloid deposition, brain structure and cognitive profile. METHODS We compared TREM2 p.R47H carriers (n = 8; median age = 62.3) and participants with mild cognitive impairment (n = 8; median age = 70.7). Participants underwent two [18F]DPA-714 PET/MRI scans to assess TSPO signal, indicative of microglial activation, before and after receiving the seasonal influenza vaccination, which was used as an immune stimulant. Participants also underwent [18F]florbetapir and [18F]AV1451 PET scans to assess amyloid and tau burden, respectively. Regional tau and TSPO signal were calculated for regions of interest linked to Braak stage. An additional comparison imaging healthy control group (n = 8; median age = 45.5) had a single [18F]DPA-714 PET/MRI. An expanded group of participants underwent neuropsychological testing, to determine if TREM2 status influenced clinical phenotype. RESULTS Compared to participants with mild cognitive impairment, TREM2 carriers had lower TSPO signal in Braak II (P = 0.04) and Braak III (P = 0.046) regions, despite having a similar burden of tau and amyloid. There were trends to suggest reduced microglial activation following influenza vaccine in TREM2 carriers. Tau deposition in the Braak VI region was higher in TREM2 carriers (P = 0.04). Furthermore, compared to healthy controls TREM2 carriers had smaller caudate (P = 0.02), total brain (P = 0.049) and white matter volumes (P = 0.02); and neuropsychological assessment revealed worse ADAS-Cog13 (P = 0.03) and Delayed Matching to Sample (P = 0.007) scores. CONCLUSIONS TREM2 p.R47H carriers had reduced levels of microglial activation in brain regions affected early in the Alzheimer's disease course and differences in brain structure and cognition. Changes in microglial response may underlie the increased Alzheimer's disease risk in TREM2 p.R47H carriers. Future therapeutic agents in Alzheimer's disease should aim to enhance protective microglial actions.
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Affiliation(s)
- Oliver Cousins
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Julia J Schubert
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Avinash Chandra
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Mattia Veronese
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
- Department of Information Engineering, University of Padua, 35131, Padua, Italy
| | - Polena Valkimadi
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Byron Creese
- College of Medicine and Health, University of Exeter, Exeter, EX1 2HZ, UK
- Division of Psychology, Department of Life Sciences, Brunel University London, London, UB8 3PH, UK
| | - Zunera Khan
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Ryan Arathimos
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Adam Hampshire
- Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Ivana Rosenzweig
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Clive Ballard
- College of Medicine and Health, University of Exeter, Exeter, EX1 2HZ, UK
| | - Anne Corbett
- College of Medicine and Health, University of Exeter, Exeter, EX1 2HZ, UK
| | - Dag Aasland
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Latha Velayudhan
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | | | | | - Ramla Awais
- Centre for Radiopharmaceutical Chemistry, University College London, London, WC1E 6BS, UK
| | - Kerstin Sander
- Centre for Radiopharmaceutical Chemistry, University College London, London, WC1E 6BS, UK
| | - Erik Årstad
- Centre for Radiopharmaceutical Chemistry, University College London, London, WC1E 6BS, UK
| | - Oliver Howes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Federico Turkheimer
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK
| | - Angela Hodges
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9RT, UK.
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19
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Silva-Rodríguez J, Labrador-Espinosa MA, Moscoso A, Schöll M, Mir P, Grothe MJ. Characteristics of amnestic patients with hypometabolism patterns suggestive of Lewy body pathology. Brain 2023; 146:4520-4531. [PMID: 37284793 PMCID: PMC10629761 DOI: 10.1093/brain/awad194] [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: 01/25/2023] [Revised: 04/27/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023] Open
Abstract
A clinical diagnosis of Alzheimer's disease dementia (ADD) encompasses considerable pathological and clinical heterogeneity. While Alzheimer's disease patients typically show a characteristic temporo-parietal pattern of glucose hypometabolism on 18F-fluorodeoxyglucose (FDG)-PET imaging, previous studies have identified a subset of patients showing a distinct posterior-occipital hypometabolism pattern associated with Lewy body pathology. Here, we aimed to improve the understanding of the clinical relevance of these posterior-occipital FDG-PET patterns in patients with Alzheimer's disease-like amnestic presentations. Our study included 1214 patients with clinical diagnoses of ADD (n = 305) or amnestic mild cognitive impairment (aMCI, n = 909) from the Alzheimer's Disease Neuroimaging Initiative, who had FDG-PET scans available. Individual FDG-PET scans were classified as being suggestive of Alzheimer's (AD-like) or Lewy body (LB-like) pathology by using a logistic regression classifier trained on a separate set of patients with autopsy-confirmed Alzheimer's disease or Lewy body pathology. AD- and LB-like subgroups were compared on amyloid-β and tau-PET, domain-specific cognitive profiles (memory versus executive function performance), as well as the presence of hallucinations and their evolution over follow-up (≈6 years for aMCI, ≈3 years for ADD). Around 12% of the aMCI and ADD patients were classified as LB-like. For both aMCI and ADD patients, the LB-like group showed significantly lower regional tau-PET burden than the AD-like subgroup, but amyloid-β load was only significantly lower in the aMCI LB-like subgroup. LB- and AD-like subgroups did not significantly differ in global cognition (aMCI: d = 0.15, P = 0.16; ADD: d = 0.02, P = 0.90), but LB-like patients exhibited a more dysexecutive cognitive profile relative to the memory deficit (aMCI: d = 0.35, P = 0.01; ADD: d = 0.85 P < 0.001), and had a significantly higher risk of developing hallucinations over follow-up [aMCI: hazard ratio = 1.8, 95% confidence interval = (1.29, 3.04), P = 0.02; ADD: hazard ratio = 2.2, 95% confidence interval = (1.53, 4.06) P = 0.01]. In summary, a sizeable group of clinically diagnosed ADD and aMCI patients exhibit posterior-occipital FDG-PET patterns typically associated with Lewy body pathology, and these also show less abnormal Alzheimer's disease biomarkers as well as specific clinical features typically associated with dementia with Lewy bodies.
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Affiliation(s)
- Jesús Silva-Rodríguez
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
| | - Miguel A Labrador-Espinosa
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
| | - Alexis Moscoso
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
| | - Michael Schöll
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, WC1ELondon, UK
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Departamento de Medicina, Facultad de Medicina, Universidad de Sevilla, 41009 Sevilla, Spain
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
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Gustafsson J, Taprogge J. Future trends for patient-specific dosimetry methodology in molecular radiotherapy. Phys Med 2023; 115:103165. [PMID: 37880071 DOI: 10.1016/j.ejmp.2023.103165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 10/03/2023] [Accepted: 10/17/2023] [Indexed: 10/27/2023] Open
Abstract
Molecular radiotherapy is rapidly expanding, and new radiotherapeutics are emerging. The majority of treatments is still performed using empirical fixed activities and not tailored for individual patients. Molecular radiotherapy dosimetry is often seen as a promising candidate that would allow personalisation of treatments as outcome should ultimately depend on the absorbed doses delivered and not the activities administered. The field of molecular radiotherapy dosimetry has made considerable progress towards the feasibility of routine clinical dosimetry with reasonably accurate absorbed-dose estimates for a range of molecular radiotherapy dosimetry applications. A range of challenges remain with respect to the accurate quantification, assessment of time-integrated activity and absorbed dose estimation. In this review, we summarise a range of technological and methodological advancements, mainly focussed on beta-emitting molecular radiotherapeutics, that aim to improve molecular radiotherapy dosimetry to achieve accurate, reproducible, and streamlined dosimetry. We describe how these new technologies can potentially improve the often time-consuming considered process of dosimetry and provide suggestions as to what further developments might be required.
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Affiliation(s)
| | - Jan Taprogge
- National Radiotherapy Trials Quality Assurance (RTTQA) Group, Joint Department of Physics, Royal Marsden NHSFT, Downs Road, Sutton SM2 5PT, United Kingdom; The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, United Kingdom
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21
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Balajoo SM, Eickhoff SB, Masouleh SK, Plachti A, Waite L, Saberi A, Bahri MA, Bastin C, Salmon E, Hoffstaedter F, Palomero-Gallagher N, Genon S. Hippocampal metabolic subregions and networks: Behavioral, molecular, and pathological aging profiles. Alzheimers Dement 2023; 19:4787-4804. [PMID: 37014937 PMCID: PMC10698199 DOI: 10.1002/alz.13056] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 04/06/2023]
Abstract
INTRODUCTION Hippocampal local and network dysfunction is the hallmark of Alzheimer's disease (AD). METHODS We characterized the spatial patterns of hippocampus differentiation based on brain co-metabolism in healthy elderly participants and demonstrated their relevance to study local metabolic changes and associated dysfunction in pathological aging. RESULTS The hippocampus can be differentiated into anterior/posterior and dorsal cornu ammonis (CA)/ventral (subiculum) subregions. While anterior/posterior CA show co-metabolism with different regions of the subcortical limbic networks, the anterior/posterior subiculum are parts of cortical networks supporting object-centered memory and higher cognitive demands, respectively. Both networks show relationships with the spatial patterns of gene expression pertaining to cell energy metabolism and AD's process. Finally, while local metabolism is generally lower in posterior regions, the anterior-posterior imbalance is maximal in late mild cognitive impairment with the anterior subiculum being relatively preserved. DISCUSSION Future studies should consider bidimensional hippocampal differentiation and in particular the posterior subicular region to better understand pathological aging.
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Affiliation(s)
- Somayeh Maleki Balajoo
- Institute of Systems Neuroscience, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
| | - Shahrzad Kharabian Masouleh
- Institute of Systems Neuroscience, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
| | - Anna Plachti
- Institute of Systems Neuroscience, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Laura Waite
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
| | - Amin Saberi
- Institute of Systems Neuroscience, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Mohamed Ali Bahri
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christine Bastin
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Eric Salmon
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
- Department of Neurology, University Hospital of Liège, Liège, Belgium
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM‑1), Research Centre Juelich, Juelich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
| | - Sarah Genon
- Institute of Systems Neuroscience, Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Juelich, Juelich, Germany
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
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22
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Mueller C, Fang YHD, Jones C, McConathy JE, Raman F, Lapi SE, Younger JW. Evidence of neuroinflammation in fibromyalgia syndrome: a [ 18 F]DPA-714 positron emission tomography study. Pain 2023; 164:2285-2295. [PMID: 37326674 PMCID: PMC10502894 DOI: 10.1097/j.pain.0000000000002927] [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: 09/26/2022] [Revised: 03/21/2023] [Accepted: 03/28/2023] [Indexed: 06/17/2023]
Abstract
ABSTRACT This observational study aimed to determine whether individuals with fibromyalgia (FM) exhibit higher levels of neuroinflammation than healthy controls (HCs), as measured with positron emission tomography using [ 18 F]DPA-714, a second-generation radioligand for the translocator protein (TSPO). Fifteen women with FM and 10 HCs underwent neuroimaging. Distribution volume (V T ) was calculated for in 28 regions of interest (ROIs) using Logan graphical analysis and compared between groups using multiple linear regressions. Group (FM vs HC) was the main predictor of interest and TSPO binding status (high- vs mixed-affinity) was added as a covariate. The FM group had higher V T in the right postcentral gyrus ( b = 0.477, P = 0.033), right occipital gray matter (GM; b = 0.438, P = 0.039), and the right temporal GM ( b = 0.466, P = 0.042). The FM group also had lower V T than HCs in the left isthmus of the cingulate gyrus ( b = -0.553, P = 0.014). In the subgroup of high-affinity binders, the FM group had higher V T in the bilateral precuneus, postcentral gyrus, parietal GM, occipital GM, and supramarginal gyrus. Group differences in the right parietal GM were associated with decreased quality of life, higher pain severity and interference, and cognitive problems. In support of our hypothesis, we found increased radioligand binding (V T ) in the FM group compared with HCs in several brain regions regardless of participants' TSPO binding status. The ROIs overlapped with prior reports of increased TSPO binding in FM. Overall, increasing evidence supports the hypothesis that FM involves microglia-mediated neuroinflammation in the brain.
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Affiliation(s)
| | - Yu-Hua D. Fang
- Radiology and Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Chloe Jones
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jonathan E. McConathy
- Department of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Fabio Raman
- Department of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Suzanne E. Lapi
- Department of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jarred W. Younger
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, United States
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23
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Costoya-Sánchez A, Moscoso A, Silva-Rodríguez J, Pontecorvo MJ, Devous MD, Aguiar P, Schöll M, Grothe MJ. Increased Medial Temporal Tau Positron Emission Tomography Uptake in the Absence of Amyloid-β Positivity. JAMA Neurol 2023; 80:1051-1061. [PMID: 37578787 PMCID: PMC10425864 DOI: 10.1001/jamaneurol.2023.2560] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 05/16/2023] [Indexed: 08/15/2023]
Abstract
Importance An increased tau positron emission tomography (PET) signal in the medial temporal lobe (MTL) has been observed in older individuals in the absence of amyloid-β (Aβ) pathology. Little is known about the longitudinal course of this condition, and its association with Alzheimer disease (AD) remains unclear. Objective To study the pathologic and clinical course of older individuals with PET-evidenced MTL tau deposition (TMTL+) in the absence of Aβ pathology (A-), and the association of this condition with the AD continuum. Design, Setting, and Participants A multicentric, observational, longitudinal cohort study was conducted using pooled data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and the AVID-A05 study, collected between July 2, 2015, and August 23, 2021. Participants in the ADNI, HABS, and AVID-A05 studies (N = 1093) with varying degrees of cognitive performance were deemed eligible if they had available tau PET, Aβ PET, and magnetic resonance imaging scans at baseline. Of these, 128 participants did not meet inclusion criteria based on Aβ PET and tau PET biomarker profiles (A+ TMTL-). Exposures Tau and Aβ PET, magnetic resonance imaging, cerebrospinal fluid biomarkers, and cognitive assessments. Main Outcomes and Measures Cross-sectional and longitudinal measures for tau and Aβ PET, cortical atrophy, cognitive scores, and core AD cerebrospinal fluid biomarkers (Aβ42/40 and tau phosphorylated at threonine 181 p-tau181 available in a subset). Results Among the 965 individuals included in the study, 503 were women (52.1%) and the mean (SD) age was 73.9 (8.1) years. A total of 51% of A- individuals and 78% of A+ participants had increased tau PET signal in the entorhinal cortex (TMTL+) compared with healthy younger (aged <39 years) controls. Compared with A- TMTL-, A- TMTL+ participants showed statistically significant, albeit moderate, longitudinal (mean [SD], 1.83 [0.84] years) tau PET increases that were largely limited to the temporal lobe, whereas those with A+ TMTL+ showed faster and more cortically widespread tau PET increases. In contrast to participants with A+ TMTL+, those with A- TMTL+ did not show any noticeable Aβ accumulation over follow-up (mean [SD], 2.36 [0.76] years). Complementary cerebrospinal fluid analysis confirmed longitudinal p-tau181 increases in A- TMTL+ in the absence of increased Aβ accumulation. Participants with A- TMTL+ had accelerated MTL atrophy, whereas those with A+ TMTL+ showed accelerated atrophy in widespread temporoparietal brain regions. Increased MTL tau PET uptake in A- individuals was associated with cognitive decline, but at a significantly slower rate compared with A+ TMTL+. Conclusions and Relevance In this study, individuals with A- TMTL+ exhibited progressive tau accumulation and neurodegeneration, but these processes were comparably slow, remained largely restricted to the MTL, were associated with only subtle changes in global cognitive performance, and were not accompanied by detectable accumulation of Aβ biomarkers. These data suggest that individuals with A- TMTL+ are not on a pathologic trajectory toward AD.
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Affiliation(s)
- Alejandro Costoya-Sánchez
- Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostel, Travesía da Choupana s/n, Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
| | - Alexis Moscoso
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
| | - Jesús Silva-Rodríguez
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Michael J. Pontecorvo
- Avid Radiopharmaceuticals, Philadelphia, Pennsylvania
- Eli Lilly and Company, Indianapolis, Indiana
| | - Michael D. Devous
- Avid Radiopharmaceuticals, Philadelphia, Pennsylvania
- Eli Lilly and Company, Indianapolis, Indiana
| | - Pablo Aguiar
- Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostel, Travesía da Choupana s/n, Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Physiology and Neuroscience, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Michel J. Grothe
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
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Brier MR, Taha F. Measuring Pathology in Patients with Multiple Sclerosis Using Positron Emission Tomography. Curr Neurol Neurosci Rep 2023; 23:479-488. [PMID: 37418219 DOI: 10.1007/s11910-023-01285-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2023] [Indexed: 07/08/2023]
Abstract
PURPOSE OF REVIEW Multiple sclerosis is characterized by a diverse and complex pathology. Clinical relapses, the hallmark of the disease, are accompanied by focal white matter lesions with intense inflammatory and demyelinating activity. Prevention of these relapses has been the major focus of pharmaceutical development, and it is now possible to dramatically reduce this inflammatory activity. Unfortunately, disability accumulation persists for many people living with multiple sclerosis owing to ongoing damage within existing lesions, pathology outside of discrete lesions, and other yet unknown factors. Understanding this complex pathological cascade will be critical to stopping progressive multiple sclerosis. Positron emission tomography uses biochemically specific radioligands to quantitatively measure pathological processes with molecular specificity. This review examines recent advances in the understanding of multiple sclerosis facilitated by positron emission tomography and identifies future avenues to expand understanding and treatment options. RECENT FINDINGS An increasing number of radiotracers allow for the quantitative measurement of inflammatory abnormalities, de- and re-myelination, and metabolic disruption associated with multiple sclerosis. The studies have identified contributions of ongoing, smoldering inflammation to accumulating tissue injury and clinical worsening. Myelin studies have quantified the dynamics of myelin loss and recovery. Lastly, metabolic changes have been found to contribute to symptom worsening. The molecular specificity facilitated by positron emission tomography in people living with multiple sclerosis will critically inform efforts to modulate the pathology leading to progressive disability accumulation. Existing studies show the power of this approach applied to multiple sclerosis. This armamentarium of radioligands allows for new understanding of how the brain and spinal cord of people is impacted by multiple sclerosis.
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Affiliation(s)
- Matthew R Brier
- Department of Neurology, John L Trotter MS Center, Washington University in St. Louis, St. Louis, USA.
| | - Farris Taha
- Department of Neurology, Medical University of South Carolina, Charleston, USA
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25
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Sanaat A, Shooli H, Böhringer AS, Sadeghi M, Shiri I, Salimi Y, Ginovart N, Garibotto V, Arabi H, Zaidi H. A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information. Eur J Nucl Med Mol Imaging 2023; 50:1881-1896. [PMID: 36808000 PMCID: PMC10199868 DOI: 10.1007/s00259-023-06152-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/12/2023] [Indexed: 02/23/2023]
Abstract
PURPOSE Partial volume effect (PVE) is a consequence of the limited spatial resolution of PET scanners. PVE can cause the intensity values of a particular voxel to be underestimated or overestimated due to the effect of surrounding tracer uptake. We propose a novel partial volume correction (PVC) technique to overcome the adverse effects of PVE on PET images. METHODS Two hundred and twelve clinical brain PET scans, including 50 18F-Fluorodeoxyglucose (18F-FDG), 50 18F-Flortaucipir, 36 18F-Flutemetamol, and 76 18F-FluoroDOPA, and their corresponding T1-weighted MR images were enrolled in this study. The Iterative Yang technique was used for PVC as a reference or surrogate of the ground truth for evaluation. A cycle-consistent adversarial network (CycleGAN) was trained to directly map non-PVC PET images to PVC PET images. Quantitative analysis using various metrics, including structural similarity index (SSIM), root mean squared error (RMSE), and peak signal-to-noise ratio (PSNR), was performed. Furthermore, voxel-wise and region-wise-based correlations of activity concentration between the predicted and reference images were evaluated through joint histogram and Bland and Altman analysis. In addition, radiomic analysis was performed by calculating 20 radiomic features within 83 brain regions. Finally, a voxel-wise two-sample t-test was used to compare the predicted PVC PET images with reference PVC images for each radiotracer. RESULTS The Bland and Altman analysis showed the largest and smallest variance for 18F-FDG (95% CI: - 0.29, + 0.33 SUV, mean = 0.02 SUV) and 18F-Flutemetamol (95% CI: - 0.26, + 0.24 SUV, mean = - 0.01 SUV), respectively. The PSNR was lowest (29.64 ± 1.13 dB) for 18F-FDG and highest (36.01 ± 3.26 dB) for 18F-Flutemetamol. The smallest and largest SSIM were achieved for 18F-FDG (0.93 ± 0.01) and 18F-Flutemetamol (0.97 ± 0.01), respectively. The average relative error for the kurtosis radiomic feature was 3.32%, 9.39%, 4.17%, and 4.55%, while it was 4.74%, 8.80%, 7.27%, and 6.81% for NGLDM_contrast feature for 18F-Flutemetamol, 18F-FluoroDOPA, 18F-FDG, and 18F-Flortaucipir, respectively. CONCLUSION An end-to-end CycleGAN PVC method was developed and evaluated. Our model generates PVC images from the original non-PVC PET images without requiring additional anatomical information, such as MRI or CT. Our model eliminates the need for accurate registration or segmentation or PET scanner system response characterization. In addition, no assumptions regarding anatomical structure size, homogeneity, boundary, or background level are required.
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Affiliation(s)
- Amirhossein Sanaat
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Hossein Shooli
- Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy (MIRT), Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Andrew Stephen Böhringer
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Maryam Sadeghi
- Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Schoepfstr. 41, Innsbruck, Austria
| | - Isaac Shiri
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Yazdan Salimi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Nathalie Ginovart
- Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Geneva University, Geneva, Switzerland
- Department of Basic Neuroscience, Geneva University, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
- Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
| | - Hossein Arabi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland.
- Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, Groningen, Netherlands.
- Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark.
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Fang YHD, Perucho JU, Chiu SC, Lin YC, McConathy JE. Prediction of MCI-to-AD progression with atrophy-weighted standard uptake value ratios of 18 F-Florbetapir PET. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.09.23287059. [PMID: 36993442 PMCID: PMC10055450 DOI: 10.1101/2023.03.09.23287059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
UNLABELLED Accurate prediction of MCI-to-AD progression is an important yet challenging task. We introduce a new quantitative parameter: the atrophy-weighted standard uptake value ratio (awSUVR), defined as the PET SUVR divided by the hippocampal volume measured with MR, and evaluate whether it may provide better prediction of the MCI-to-AD progression. MATERIALS AND METHODS We used ADNI data to evaluate the prediction performances of the awSUVR against SUVR. 571, 363 and 252 18-F-Florbetaipir scans were selected based on criteria of conversion at the third, fifth and seventh year after the PET scans, respectively. Corresponding MR scans were segmented with Freesurfer and applied on PET for SUVR and awSUVR computation. We also searched for the optimal combination of target and reference regions. In addition to evaluating the overall prediction performances, we also evaluated the prediction for APOE4 carriers and non-carriers. For the scans with false predictions, we used 18-F-Flortaucipir scans to investigate the potential source of error. RESULTS awSUVR provides more accurate prediction than the SUVR in all three progression criteria. The 5-year prediction accuracy/sensitivity/specificity is 90/81/93% for awSUVR and 86/81/88% for SUV. awSUVR also yields good 3- and 7-year prediction accuracy/sensitivity/specificity of 91/57/96 and 92/89/93, respectively. APOE4 carriers generally are slightly more difficult to predict for the progression. False negative prediction is found to either due to a near-cutoff mis-classification or potentially non-AD dementia pathology. False positive prediction is mainly due to the slightly delayed progression than the expected progression time. CONCLUSION We demonstrated with ADNI data that 18-F-Florbetapir SUVR weighted with hippocampus volume may provide good prediction power with over 90% accuracy in MCI-to-AD progression.
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Yacoubian TA, Fang YHD, Gerstenecker A, Amara A, Stover N, Ruffrage L, Collette C, Kennedy R, Zhang Y, Hong H, Qin H, McConathy J, Benveniste EN, Standaert DG. Brain and Systemic Inflammation in De Novo Parkinson's Disease. Mov Disord 2023. [PMID: 36853618 DOI: 10.1002/mds.29363] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 02/01/2023] [Accepted: 02/07/2023] [Indexed: 03/01/2023] Open
Abstract
OBJECTIVE To assess the presence of brain and systemic inflammation in subjects newly diagnosed with Parkinson's disease (PD). BACKGROUND Evidence for a pathophysiologic role of inflammation in PD is growing. However, several key gaps remain as to the role of inflammation in PD, including the extent of immune activation at early stages, potential effects of PD treatments on inflammation and whether pro-inflammatory signals are associated with clinical features and/or predict more rapid progression. METHODS We enrolled subjects with de novo PD (n = 58) and age-matched controls (n = 62). Subjects underwent clinical assessments, including the Movement Disorder Society-United Parkinson's Disease rating scale (MDS-UPDRS). Comprehensive cognitive assessment meeting MDS Level II criteria for mild cognitive impairment testing was performed. Blood was obtained for flow cytometry and cytokine/chemokine analyses. Subjects underwent imaging with 18 F-DPA-714, a translocator protein 18kd ligand, and lumbar puncture if eligible and consented. RESULTS Baseline demographics and medical history were comparable between groups. PD subjects showed significant differences in University of Pennsylvania Smell Identification Test, Schwab and England Activities of Daily Living, Scales for Outcomes in PD autonomic dysfunction, and MDS-UPDRS scores. Cognitive testing demonstrated significant differences in cognitive composite, executive function, and visuospatial domain scores at baseline. Positron emission tomography imaging showed increased 18 F-DPA-714 signal in PD subjects. 18 F-DPA-714 signal correlated with several cognitive measures and some chemokines. CONCLUSIONS 18 F-DPA-714 imaging demonstrated increased central inflammation in de novo PD subjects compared to controls. Longitudinal follow-up will be important to determine whether the presence of inflammation predicts cognitive decline. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Talene A Yacoubian
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Yu-Hua Dean Fang
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Adam Gerstenecker
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Amy Amara
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Natividad Stover
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Lauren Ruffrage
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Christopher Collette
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Richard Kennedy
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Yue Zhang
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Huixian Hong
- Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Hongwei Qin
- Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jonathan McConathy
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Etty N Benveniste
- Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - David G Standaert
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
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Youn J, Won JH, Kim M, Kwon J, Moon SH, Kim M, Ahn JH, Mun JK, Park H, Cho JW. Extra-Basal Ganglia Brain Structures Are Related to Motor Reserve in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2023; 13:39-48. [PMID: 36565134 PMCID: PMC9912725 DOI: 10.3233/jpd-223542] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND The "motor reserve" is an emerging concept based on the discrepancy between the severity of parkinsonism and dopaminergic degeneration; however, the related brain structures have not yet been elucidated. OBJECTIVE We investigated brain structures relevant to the motor reserve in Parkinson's disease (PD) in this study. METHODS Patients with drug-naïve, early PD were enrolled, who then underwent dopamine transporter (DAT) scan and diffusion tensor imaging (DTI). The severity of motor symptoms was evaluated with the Unified Parkinson's Disease Rating Scale score of bradykinesia and rigidity on the more affected side and dopaminergic degeneration of DAT uptake of the more affected putamen. Individual motor reserve estimate (MRE) was evaluated based on the discrepancy between the severity of motor symptoms and dopaminergic degeneration. Using DTI and the Brainnetome atlas, brain structures correlated with MRE were identified. RESULTS We enrolled 193 patients with drug-naïve PD (mean disease duration of 15.6±13.2 months), and the MRE successfully predicted the increase of levodopa equivalent dose after two years. In the DTI analysis, fractional anisotropy values of medial, inferior frontal, and temporal lobes, limbic structures, nucleus accumbens, and thalamus were positively correlated with the MRE, while no brain structures were correlated with mean diffusivity. Additionally, degree centrality derived from the structural connectivity of the frontal and temporal lobes and limbic structures was positively correlated with the MRE. CONCLUSION Our results show empirical evidence for MR in PD and brain structures relevant to MR, particularly, the extra-basal ganglia system including the limbic and frontal structures.
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Affiliation(s)
- Jinyoung Youn
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Ji Hye Won
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea
| | - Mansu Kim
- Department of Artificial Intelligence, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Junmo Kwon
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea
| | - Seung Hwan Moon
- Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Minkyeong Kim
- Department of Neurology, Gyeongsang National University Hospital, Jinju, Korea
| | - Jong Hyun Ahn
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Jun Kyu Mun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Hyunjin Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea,School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Korea,Correspondence to: Jin Whan Cho, MD, PhD, Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 81, Gangnam-Gu, Seoul, 06351, Korea. Tel.: +82 2 3410 1279; Fax: +82 2 3410 0052; E-mail: and Hyunjin Park, PhD, Center for Neuroscience Imaging Research and School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, 16419, Korea. Tel.: +82 31 299 4956; Fax: +82 31 290 5819; E-mail:
| | - Jin Whan Cho
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea,Neuroscience Center, Samsung Medical Center, Seoul, Korea,Correspondence to: Jin Whan Cho, MD, PhD, Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 81, Gangnam-Gu, Seoul, 06351, Korea. Tel.: +82 2 3410 1279; Fax: +82 2 3410 0052; E-mail: and Hyunjin Park, PhD, Center for Neuroscience Imaging Research and School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, 16419, Korea. Tel.: +82 31 299 4956; Fax: +82 31 290 5819; E-mail:
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SPECT/CT-based dosimetry of salivary glands and iodine-avid lesions following 131I therapy. HEALTH AND TECHNOLOGY 2023; 13:101-110. [PMID: 36628262 PMCID: PMC9817440 DOI: 10.1007/s12553-022-00718-y] [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: 09/10/2022] [Accepted: 12/19/2022] [Indexed: 01/07/2023]
Abstract
Objective The purpose was to provide uptake and radiation dose estimates to salivary glands (SG) and pathologic lesions following radioiodine therapy (RIT) of differentiated thyroid cancer patients (DTC). Methods A group of DTC patients (n = 25) undergoing 131I therapy joined this study with varying amounts of therapeutic activity. Sequential SPECT/CT scans were acquired at 4 ± 2, 24 ± 2, and 168 ± 3 h following administration of 3497-9250 MBq 131I. An earlier experiment with Acrylic glass body phantom (PET Phantom NEMA 2012 / IEC 2008) was conducted for system calibration including scatter, partial volume effect and count loss correction. Dose calculation was made via IDAC-Dose 2.1 code. Results The absorbed dose to parotid glands was 0.04-0.97 Gy/GBq (median: 0.26 Gy/GBq). The median absorbed dose to submandibular glands was 0.14 Gy/GBq (0.05 to 0.56 Gy/GBq). The absorbed dose to thyroid residues was from 0.55 to 399.5 Gy/GBq (median: 21.8 Gy/GBq), and that to distal lesions ranged from 0.78 to 28.0 Gy/GBq (median: 3.12 Gy/GBq). 41% of the thyroid residues received dose > 80 Gy, 18% between 70-80 Gy, 18% between 40-70 Gy, and 23% has dose < 40 Gy. In contrast, 18% of the metastases exhibited a dose > 80 Gy, 9% between 40-60 Gy, and the dose to the vast majority of lesions (64%) was < 40 Gy. Conclusion It was inferred that dose estimation after RIT with SPECT/CT is feasible to apply, together with good agreement with published 124I PET/CT dose estimates. A broad and sub-effective dose range was estimated for thyroid residues and distal lesions. Moreover, the current methodology might be useful for establishing a dose-effect relationship and radiation-induced salivary glands damage after RIT.
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Katzdobler S, Nitschmann A, Barthel H, Bischof G, Beyer L, Marek K, Song M, Wagemann O, Palleis C, Weidinger E, Nack A, Fietzek U, Kurz C, Häckert J, Stapf T, Ferschmann C, Scheifele M, Eckenweber F, Biechele G, Franzmeier N, Dewenter A, Schönecker S, Saur D, Schroeter ML, Rumpf JJ, Rullmann M, Schildan A, Patt M, Stephens AW, van Eimeren T, Neumaier B, Drzezga A, Danek A, Classen J, Bürger K, Janowitz D, Rauchmann BS, Stöcklein S, Perneczky R, Schöberl F, Zwergal A, Höglinger GU, Bartenstein P, Villemagne V, Seibyl J, Sabri O, Levin J, Brendel M. Additive value of [ 18F]PI-2620 perfusion imaging in progressive supranuclear palsy and corticobasal syndrome. Eur J Nucl Med Mol Imaging 2023; 50:423-434. [PMID: 36102964 PMCID: PMC9816230 DOI: 10.1007/s00259-022-05964-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 09/01/2022] [Indexed: 01/11/2023]
Abstract
PURPOSE Early after [18F]PI-2620 PET tracer administration, perfusion imaging has potential for regional assessment of neuronal injury in neurodegenerative diseases. This is while standard late-phase [18F]PI-2620 tau-PET is able to discriminate the 4-repeat tauopathies progressive supranuclear palsy and corticobasal syndrome (4RTs) from disease controls and healthy controls. Here, we investigated whether early-phase [18F]PI-2620 PET has an additive value for biomarker based evaluation of 4RTs. METHODS Seventy-eight patients with 4RTs (71 ± 7 years, 39 female), 79 patients with other neurodegenerative diseases (67 ± 12 years, 35 female) and twelve age-matched controls (69 ± 8 years, 8 female) underwent dynamic (0-60 min) [18F]PI-2620 PET imaging. Regional perfusion (0.5-2.5 min p.i.) and tau load (20-40 min p.i.) were measured in 246 predefined brain regions [standardized-uptake-value ratios (SUVr), cerebellar reference]. Regional SUVr were compared between 4RTs and controls by an ANOVA including false-discovery-rate (FDR, p < 0.01) correction. Hypoperfusion in resulting 4RT target regions was evaluated at the patient level in all patients (mean value - 2SD threshold). Additionally, perfusion and tau pattern expression levels were explored regarding their potential discriminatory value of 4RTs against other neurodegenerative disorders, including validation in an independent external dataset (n = 37), and correlated with clinical severity in 4RTs (PSP rating scale, MoCA, activities of daily living). RESULTS Patients with 4RTs had significant hypoperfusion in 21/246 brain regions, most dominant in thalamus, caudate nucleus, and anterior cingulate cortex, fitting to the topology of the 4RT disease spectrum. However, single region hypoperfusion was not specific regarding the discrimination of patients with 4RTs against patients with other neurodegenerative diseases. In contrast, perfusion pattern expression showed promise for discrimination of patients with 4RTs from other neurodegenerative diseases (AUC: 0.850). Discrimination by the combined perfusion-tau pattern expression (AUC: 0.903) exceeded that of the sole tau pattern expression (AUC: 0.864) and the discriminatory power of the combined perfusion-tau pattern expression was replicated in the external dataset (AUC: 0.917). Perfusion but not tau pattern expression was associated with PSP rating scale (R = 0.402; p = 0.0012) and activities of daily living (R = - 0.431; p = 0.0005). CONCLUSION [18F]PI-2620 perfusion imaging mirrors known topology of regional hypoperfusion in 4RTs. Single region hypoperfusion is not specific for 4RTs, but perfusion pattern expression may provide an additive value for the discrimination of 4RTs from other neurodegenerative diseases and correlates closer with clinical severity than tau pattern expression.
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Affiliation(s)
- Sabrina Katzdobler
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Alexander Nitschmann
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Henryk Barthel
- grid.411339.d0000 0000 8517 9062Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
| | - Gerard Bischof
- grid.411097.a0000 0000 8852 305XDepartment of Nuclear Medicine, University Hospital Cologne, Cologne, Germany ,Molecular Organization of the Brain, Institute for Neuroscience and Medicine, INM-2), Jülich, Germany
| | - Leonie Beyer
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Ken Marek
- grid.452597.8InviCRO, LLC, Boston, MA USA ,grid.452597.8Molecular Neuroimaging, A Division of inviCRO, New Haven, CT USA
| | - Mengmeng Song
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Olivia Wagemann
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Carla Palleis
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Endy Weidinger
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Anne Nack
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Urban Fietzek
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Carolin Kurz
- grid.411095.80000 0004 0477 2585Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Jan Häckert
- grid.411095.80000 0004 0477 2585Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany ,grid.7307.30000 0001 2108 9006Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, BKH Augsburg, Augsburg, Germany
| | - Theresa Stapf
- grid.411095.80000 0004 0477 2585Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Christian Ferschmann
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Maximilian Scheifele
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Florian Eckenweber
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Gloria Biechele
- grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Nicolai Franzmeier
- grid.411095.80000 0004 0477 2585Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Anna Dewenter
- grid.411095.80000 0004 0477 2585Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Sonja Schönecker
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Dorothee Saur
- grid.9647.c0000 0004 7669 9786Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Matthias L. Schroeter
- grid.9647.c0000 0004 7669 9786Clinic for Cognitive Neurology, University of Leipzig, Leipzig, Germany ,grid.9647.c0000 0004 7669 9786LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany ,grid.419524.f0000 0001 0041 5028Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jost-Julian Rumpf
- grid.9647.c0000 0004 7669 9786Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Michael Rullmann
- grid.411339.d0000 0000 8517 9062Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
| | - Andreas Schildan
- grid.411339.d0000 0000 8517 9062Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
| | - Marianne Patt
- grid.411339.d0000 0000 8517 9062Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
| | | | - Thilo van Eimeren
- grid.411097.a0000 0000 8852 305XDepartment of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Bernd Neumaier
- grid.411097.a0000 0000 8852 305XDepartment of Nuclear Medicine, University Hospital Cologne, Cologne, Germany ,grid.8385.60000 0001 2297 375XInstitute for Neuroscience and Medicine (INM-3), Cognitive Neuroscience, Research Centre Juelich, Juelich, Germany
| | - Alexander Drzezga
- grid.411097.a0000 0000 8852 305XDepartment of Nuclear Medicine, University Hospital Cologne, Cologne, Germany ,Molecular Organization of the Brain, Institute for Neuroscience and Medicine, INM-2), Jülich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Adrian Danek
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Joseph Classen
- grid.9647.c0000 0004 7669 9786Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Katharina Bürger
- grid.411095.80000 0004 0477 2585Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- grid.411095.80000 0004 0477 2585Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Boris-Stephan Rauchmann
- grid.7307.30000 0001 2108 9006Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, BKH Augsburg, Augsburg, Germany ,grid.411095.80000 0004 0477 2585Department of Radiology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Sophia Stöcklein
- grid.411095.80000 0004 0477 2585Department of Radiology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Robert Perneczky
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany ,grid.7307.30000 0001 2108 9006Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, BKH Augsburg, Augsburg, Germany ,grid.7445.20000 0001 2113 8111Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College, London, UK
| | - Florian Schöberl
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Andreas Zwergal
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Günter U. Höglinger
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany ,grid.10423.340000 0000 9529 9877Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Peter Bartenstein
- grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany ,grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Victor Villemagne
- grid.410678.c0000 0000 9374 3516Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, VIC Australia ,grid.1008.90000 0001 2179 088XDepartment of Medicine, Austin Health, The University of Melbourne, Melbourne, VIC Australia ,grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - John Seibyl
- grid.452597.8InviCRO, LLC, Boston, MA USA ,grid.452597.8Molecular Neuroimaging, A Division of inviCRO, New Haven, CT USA
| | - Osama Sabri
- grid.411339.d0000 0000 8517 9062Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
| | - Johannes Levin
- grid.411095.80000 0004 0477 2585Department of Neurology, University Hospital of Munich, LMU Munich, Munich, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Matthias Brendel
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy), Munich, Germany ,grid.411095.80000 0004 0477 2585Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Marchioninistraße 15, 81377 Munich, Germany
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Haeger A, Boumezbeur F, Bottlaender M, Rabrait-Lerman C, Lagarde J, Mirzazade S, Krahe J, Hohenfeld C, Sarazin M, Schulz JB, Romanzetti S, Reetz K. 3T sodium MR imaging in Alzheimer's disease shows stage-dependent sodium increase influenced by age and local brain volume. NEUROIMAGE: CLINICAL 2022; 36:103274. [PMID: 36451374 PMCID: PMC9723320 DOI: 10.1016/j.nicl.2022.103274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 11/12/2022] [Accepted: 11/20/2022] [Indexed: 11/23/2022] Open
Abstract
INTRODUCTION Application of MRI in clinical routine mainly addresses structural alterations. However, pathological changes at a cellular level are expected to precede the occurrence of brain atrophy clusters and of clinical symptoms. In this context, 23Na-MRI examines sodium changes in the brain as a potential metabolic parameter. Recently, we have shown that 23Na-MRI at ultra-high-field (7 T) was able to detect increased tissue sodium concentration (TSC) in Alzheimer's disease (AD). In this work, we aimed at assessing AD-pathology with 23Na-MRI in a larger cohort and on a clinical 3T MR scanner. METHODS We used a multimodal MRI protocol on 52 prodromal to mild AD patients and 34 cognitively healthy control subjects on a clinical 3T MR scanner. We examined the TSC, brain volume, and cortical thickness in association with clinical parameters. We further compared TSC with intra-individual normalized TSC for the reduction of inter-individual TSC variability resulting from physiological as well as experimental conditions. Normalized TSC maps were created by normalizing each voxel to the mean TSC inside the brain stem. RESULTS We found increased normalized TSC in the AD cohort compared to elderly control subjects both on global as well as on a region-of-interest-based level. We further confirmed a significant association of local brain volume as well as age with TSC. TSC increase in the left temporal lobe was further associated with the cognitive state, evaluated via the Montreal cognitive assessment (MoCA) screening test. An increase of normalized TSC depending on disease stage reflected by the Clinical Dementia Rating (CDR) was found in our AD patients in temporal lobe regions. In comparison to classical brain volume and cortical thickness assessments, normalized TSC had a higher discriminative power between controls and prodromal AD patients in several regions of the temporal lobe. DISCUSSION We confirm the feasibility of 23Na-MRI at 3T and report an increase of TSC in AD in several regions of the brain, particularly in brain regions of the temporal lobe. Furthermore, to reduce inter-subject variability caused by physiological factors such as circadian rhythms and experimental conditions, we introduced normalized TSC maps. This showed a higher discriminative potential between different clinical groups in comparison to the classical TSC analysis. In conclusion, 23Na-MRI represents a potential translational imaging marker applicable e.g.for diagnostics and the assessment of intervention outcomes in AD even under clinically available field strengths such as 3T. Implication of 23Na-MRI in association with other metabolic imaging marker needs to be further elucidated.
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Affiliation(s)
- Alexa Haeger
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Fawzi Boumezbeur
- NeuroSpin, CEA, CNRS UMR9027, Paris-Saclay University, Gif-sur-Yvette, France
| | - Michel Bottlaender
- NeuroSpin, CEA, CNRS UMR9027, Paris-Saclay University, Gif-sur-Yvette, France,Paris-Saclay University, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay, France
| | | | - Julien Lagarde
- Paris-Saclay University, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay, France,Department of Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France,Université Paris-Cité, F-75006 Paris, France
| | - Shahram Mirzazade
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Janna Krahe
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Christian Hohenfeld
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Marie Sarazin
- Paris-Saclay University, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay, France,Department of Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France,Université Paris-Cité, F-75006 Paris, France
| | - Jörg B. Schulz
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Sandro Romanzetti
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany,Corresponding author at: Department of Neurology, University Hospital, RWTH Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany.
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Ricigliano VAG, Louapre C, Poirion E, Colombi A, Yazdan Panah A, Lazzarotto A, Morena E, Martin E, Bottlaender M, Bodini B, Seilhean D, Stankoff B. Imaging Characteristics of Choroid Plexuses in Presymptomatic Multiple Sclerosis: A Retrospective Study. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:9/6/e200026. [PMID: 36229188 PMCID: PMC9562043 DOI: 10.1212/nxi.0000000000200026] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 07/18/2022] [Indexed: 11/06/2022]
Abstract
Background and Objectives Recent imaging studies have suggested a possible involvement of the choroid plexus (CP) in multiple sclerosis (MS). Here, we investigated whether CP changes are already detectable at the earliest stage of MS, preceding symptom onset. Methods This study is a retrospective analysis of 27 patients with presymptomatic MS, 97 patients with clinically definite MS (CDMS), and 53 healthy controls (HCs) who underwent a cross-sectional 3T-MRI acquisition; of which, 22 MS, 19 HCs, and 1 presymptomatic MS (evaluated 8 months before conversion to CDMS) also underwent translocator protein (TSPO) 18F-DPA-714 PET and were included in the analysis. CPs were manually segmented on 3D T1-weighted images for volumetric analysis. CP 18F-DPA-714 uptake, reflecting inflammation, was calculated as the average standardized uptake value (SUV). Multivariable regressions adjusted for age, sex, and ventricular and brain volume were fitted to test CP volume differences between presymptomatic patients and MS or HCs. For the presymptomatic case who also had 18F-DPA-714 PET, CP SUV differences with MS and HCs were assessed through Crawford-Howell tests. To provide further insight into the interpretation of 18F-DPA-714-PET uptake at the CP level, a postmortem analysis of CPs in MS vs HCs was performed to characterize the cellular localization of TSPO expression. Results Compared with HCs, patients with presymptomatic MS had 32% larger CPs (β = 0.38, p = 0.001), which were not dissimilar to MS CPs (p = 0.69). Moreover, in the baseline scan of the presymptomatic case who later on developed MS, TSPO PET showed 33% greater CP inflammation vs HCs (p = 0.04), although no differences in 18F-DPA-714 uptake were found in parenchymal regions vs controls. CP postmortem analysis identified a population of CD163+ mononuclear phagocytes expressing TSPO in MS, possibly contributing to the increased 18F-DPA-714 uptake. Discussion We identified an imaging signature in CPs at the presymptomatic MS stage using MRI; in addition, we found an increased CP inflammation with PET in a single presymptomatic patient. These findings suggest a role of CP imaging as an early biomarker and argue for the involvement of the blood-CSF barrier dysfunction in disease development. Trial Registration Information APHP-20210727144630, EudraCT-Number: 2008-004174-40; ClinicalTrials.gov: NCT02305264, NCT01651520, and NCT02319382.
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Affiliation(s)
- Vito A G Ricigliano
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Céline Louapre
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Emilie Poirion
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Annalisa Colombi
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Arya Yazdan Panah
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Andrea Lazzarotto
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Emanuele Morena
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Elodie Martin
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Michel Bottlaender
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Benedetta Bodini
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Danielle Seilhean
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France
| | - Bruno Stankoff
- From the Sorbonne Université (V.A.G.R., C.L., E.P., A.C., A.Y.P., A.L., Emanuele Morena, Elodie Martin, B.B., D.S., B.S.), Paris Brain Institute, ICM, CNRS, Inserm; Neurology Department (V.A.G.R., A.L., B.B., B.S.), St Antoine Hospital, APHP-Sorbonne, Paris; Neurology Department (C.L.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris; Service D'Imagerie Médicale (E.P.), Hôpital Fondation Adolphe de Rothschild, Paris; Université Paris-Saclay (M.B.), CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay; and Neuropathology Department (D.S.), Pitié-Salpêtrière Hospital, APHP-Sorbonne, Paris, France.
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López-González FJ, Costoya-Sánchez A, Paredes-Pacheco J, Moscoso A, Silva-Rodríguez J, Aguiar P. Impact of spill-in counts from off-target regions on [ 18F]Flortaucipir PET quantification. Neuroimage 2022; 259:119396. [PMID: 35753593 DOI: 10.1016/j.neuroimage.2022.119396] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 05/23/2022] [Accepted: 06/15/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND [18F]Flortaucipir (FTP) PET quantification is usually hindered by spill-in counts from off-target binding (OFF) regions. The present work aims to provide an in-depth analysis of the impact of OFF in FTP PET quantification, as well as to identify optimal partial volume correction (PVC) strategies to minimize this problem. METHODS 309 amyloid-beta (Aβ) negative cognitively normal subjects were included in the study. Additionally, 510 realistic FTP images with different levels of OFF were generated using Monte Carlo simulation (MC). Images were corrected for PVC using both a simple two-compartment and a multi-region method including OFF regions. FTP standardized uptake value ratio (SUVR) was quantified in Braak Areas (BA), the hippocampus (which was not included in Braak I/II) and different OFF regions (caudate, putamen, pallidum, thalamus, choroid plexus (ChPlex), cerebellar white matter (cerebWM), hemispheric white matter (hemisWM) and cerebrospinal fluid (CSF)) using the lower portion of the cerebellum as a reference region. The correlations between OFF and cortical SUVRs were studied both in real and in simulated PET images, with and without PVC. RESULTS In-vivo, we found correlations between all OFF and target regions, especially strong for the hemisWM (slope>0.63, R2>0.4). All the correlations were attenuated but remained significant after applying PVC, except for the ChPlex. In MC simulations, the hemisWM and CSF were the main contributors to PVE in all BA (slopes 0.15-0.26 and 0.13-0.21 respectively). The hemisWM (slope=0.2), as well as the ChPlex (slope=0.02), influenced SUVRs in the hippocampus. The CerebWM was negatively correlated with all target regions (slope<-0.02, R2>0.8). While no other correlations between OFF and target regions were found, hemisWM was correlated with all OFF regions but the cerebWM (slopes 0.06-0.33). HemisWM correlations attenuated (slopes<0.06) when applying two-compartment PVC, but the hippocampus-ChPlex and the cerebWM correlations required more complex PVC with dedicated compartments for these regions. In-vivo, PVC removed a notably higher fraction of the correlation between OFF regions found to be affected by PVE in the simulation studies and BA (≈50%) than for OFF regions not affected by PVE (16%). CONCLUSION HemisWM is the main driver of spill-in effects in FTP PET, affecting both target regions and the rest of OFF regions. PVC successfully reduces PVE, even when using a simple two-compartment method. Despite PVC, non-zero correlations were still observed between target and OFF regions in vivo, which suggests the existence of biological or tracer-related contributions to these correlations.
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Affiliation(s)
- Francisco J López-González
- Molecular Imaging Group, Department of Radiology, Faculty of Medicine and Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Galicia, Spain; Molecular Imaging Unit (UIM), Centro de Investigaciones Médico-Sanitarias (CIMES), General Foundation of the University of Málaga (Fguma), Málaga, Spain
| | - Alejandro Costoya-Sánchez
- Molecular Imaging Group, Department of Radiology, Faculty of Medicine and Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Travesía da Choupana s/n, Santiago de Compostela, 15706, Spain
| | - José Paredes-Pacheco
- Molecular Imaging Group, Department of Radiology, Faculty of Medicine and Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Galicia, Spain; Molecular Imaging Unit (UIM), Centro de Investigaciones Médico-Sanitarias (CIMES), General Foundation of the University of Málaga (Fguma), Málaga, Spain
| | - Alexis Moscoso
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, and The Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Jesús Silva-Rodríguez
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Travesía da Choupana s/n, Santiago de Compostela, 15706, Spain; Movement Disorders Unit, Clinical Neurology and Neurophysiology Department, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain.
| | - Pablo Aguiar
- Molecular Imaging Group, Department of Radiology, Faculty of Medicine and Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Travesía da Choupana s/n, Santiago de Compostela, 15706, Spain
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Dewenter A, Jacob MA, Cai M, Gesierich B, Hager P, Kopczak A, Biel D, Ewers M, Tuladhar AM, de Leeuw FE, Dichgans M, Franzmeier N, Duering M. Disentangling the effects of Alzheimer's and small vessel disease on white matter fibre tracts. Brain 2022; 146:678-689. [PMID: 35859352 PMCID: PMC9924910 DOI: 10.1093/brain/awac265] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/30/2022] [Accepted: 06/25/2022] [Indexed: 12/27/2022] Open
Abstract
Alzheimer's disease and cerebral small vessel disease are the two leading causes of cognitive decline and dementia and coexist in most memory clinic patients. White matter damage as assessed by diffusion MRI is a key feature in both Alzheimer's and cerebral small vessel disease. However, disease-specific biomarkers of white matter alterations are missing. Recent advances in diffusion MRI operating on the fixel level (fibre population within a voxel) promise to advance our understanding of disease-related white matter alterations. Fixel-based analysis allows derivation of measures of both white matter microstructure, measured by fibre density, and macrostructure, measured by fibre-bundle cross-section. Here, we evaluated the capacity of these state-of-the-art fixel metrics to disentangle the effects of cerebral small vessel disease and Alzheimer's disease on white matter integrity. We included three independent samples (total n = 387) covering genetically defined cerebral small vessel disease and age-matched controls, the full spectrum of biomarker-confirmed Alzheimer's disease including amyloid- and tau-PET negative controls and a validation sample with presumed mixed pathology. In this cross-sectional analysis, we performed group comparisons between patients and controls and assessed associations between fixel metrics within main white matter tracts and imaging hallmarks of cerebral small vessel disease (white matter hyperintensity volume, lacune and cerebral microbleed count) and Alzheimer's disease (amyloid- and tau-PET), age and a measure of neurodegeneration (brain volume). Our results showed that (i) fibre density was reduced in genetically defined cerebral small vessel disease and strongly associated with cerebral small vessel disease imaging hallmarks; (ii) fibre-bundle cross-section was mainly associated with brain volume; and (iii) both fibre density and fibre-bundle cross-section were reduced in the presence of amyloid, but not further exacerbated by abnormal tau deposition. Fixel metrics were only weakly associated with amyloid- and tau-PET. Taken together, our results in three independent samples suggest that fibre density captures the effect of cerebral small vessel disease, while fibre-bundle cross-section is largely determined by neurodegeneration. The ability of fixel-based imaging markers to capture distinct effects on white matter integrity can propel future applications in the context of precision medicine.
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Affiliation(s)
- Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
| | - Mina A Jacob
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mengfei Cai
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Benno Gesierich
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
- Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Paul Hager
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
- Institute for AI and Informatics in Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Anna Kopczak
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
| | - Davina Biel
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | | | - Marco Duering
- Correspondence to: Marco Duering Medical Image Analysis Center (MIAC AG) Marktgasse 8 CH-4051 Basel Switzerland E-mail:
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Mertens N, Michiels L, Vanderlinden G, Vandenbulcke M, Lemmens R, Van Laere K, Koole M. Impact of meningeal uptake and partial volume correction techniques on [ 18F]MK-6240 binding in aMCI patients and healthy controls. J Cereb Blood Flow Metab 2022; 42:1236-1246. [PMID: 35062837 PMCID: PMC9207493 DOI: 10.1177/0271678x221076023] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
[18F]MK-6240 is a second-generation tau PET-tracer to quantify neurofibrillary tangles in-vivo. However, individually variable levels of meningeal uptake induce spill-in-effects into the cortex, complicating [18F]MK-6240 PET quantification. Group SUVR differences between age-matched HC subgroups with varying extracerebral uptake (EC-low/mixed/high), and between aMCI and each HC subgroup were assessed without and with partial volume correction (PVC). Both Müller-Gartner (MG-)PVC and region-based voxelwise (RBV-)PVC, with the latter also correcting for extracerebral spill-in-effects, were implemented. Between HC groups, where no differences are to be expected, HC EC-high showed spill-in differences compared to HC EC-low when no PVC was applied while for MG-PVC, differences were reduced and, for RBV-PVC, no statistically significant differences were observed. Between aMCI and HC, cortical SUVR differences were statistically significant, both without and with PVC, but modulated by the varying meningeal uptake in HC subgroups when no PVC was applied. After applying PVC, correlations to clinical parameters improved and effect sizes between HC and aMCI increased, independent of the HC-subgroup. Therefore, appropriate PVC with correction for extracerebral spill-in-effects is recommended to minimize the impact of varying meningeal uptake on cortical differences between HC and aMCI.
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Affiliation(s)
- Nathalie Mertens
- Nuclear Medicine and Molecular Imaging, University Hospital and KU Leuven, Leuven, Belgium
| | - Laura Michiels
- Department of Neurosciences, Experimental Neurology, KU Leuven - University of Leuven, Leuven, Belgium.,VIB, Center for Brain & Disease Research, Laboratory of Neurobiology, Leuven, Belgium.,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Greet Vanderlinden
- Nuclear Medicine and Molecular Imaging, University Hospital and KU Leuven, Leuven, Belgium
| | - Mathieu Vandenbulcke
- Department of Neurosciences, Experimental Neurology, KU Leuven - University of Leuven, Leuven, Belgium.,Old-Age Psychiatry, University Hospital and KU Leuven, Leuven, Belgium
| | - Robin Lemmens
- Department of Neurosciences, Experimental Neurology, KU Leuven - University of Leuven, Leuven, Belgium.,VIB, Center for Brain & Disease Research, Laboratory of Neurobiology, Leuven, Belgium.,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, University Hospital and KU Leuven, Leuven, Belgium.,Division of Nuclear Medicine, University Hospitals Leuven, Belgium
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, University Hospital and KU Leuven, Leuven, Belgium
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Pan Y, Liu S, Zeng Y, Ye C, Qiao H, Song T, Lv H, Chan P, Lu J, Ma T. A Multi-Atlas-Based [18F]9-Fluoropropyl-(+)-Dihydrotetrabenazine Positron Emission Tomography Image Segmentation Method for Parkinson's Disease Quantification. Front Aging Neurosci 2022; 14:902169. [PMID: 35769601 PMCID: PMC9234266 DOI: 10.3389/fnagi.2022.902169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives [18F]9-fluoropropyl-(+)-dihydrotetrabenazine ([18F]-FP-DTBZ) positron emission tomography (PET) provides reliable information for the diagnosis of Parkinson's disease (PD). In this study, we proposed a multi-atlas-based [18F]-FP-DTBZ PET image segmentation method for PD quantification assessment. Methods A total of 99 subjects from Xuanwu Hospital of Capital Medical University were included in this study, and both brain PET and magnetic resonance (MR) scans were conducted. Data from 20 subjects were used to generate atlases, based on which a multi-atlas-based [18F]-FP-DTBZ PET segmentation method was developed especially for striatum and its subregions. The proposed method was compared with the template-based method through striatal subregion parcellation performance and the standard uptake value ratio (SUVR) quantification accuracy. Discriminant analysis between healthy controls (HCs) and PD patients was further performed. Results Segmentation results of the multi-atlas-based method showed better consistency than the template-based method with the ground truth, yielding a dice coefficient of 0.81 over 0.73 on the full striatum. The SUVRs calculated by the multi-atlas-based method had an average interclass correlation coefficient (ICC) of 0.953 with the standardized result, whereas the template-based method only reached 0.815. The SUVRs of HCs were generally higher than that of patients with PD and showed significant differences in all of the striatal subregions (all p < 0.001). The median and posterior putamen performed best in discriminating patients with PD from HCs. Conclusion The proposed multi-atlas-based [18F]-FP-DTBZ PET image segmentation method achieved better performance than the template-based method, indicating great potential in improving accuracy and efficiency for PD diagnosis in clinical routine.
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Affiliation(s)
- Yiwei Pan
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Shuying Liu
- Department of Neurology and Neurobiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Chinese Institute for Brain Research (CIBR), Beijing, China
| | - Yao Zeng
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Chenfei Ye
- International Research Institute for Artificial Intelligence, Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Hongwen Qiao
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Tianbing Song
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Haiyan Lv
- Mindsgo Life Science Shenzhen Co. Ltd., Shenzhen, China
| | - Piu Chan
- Department of Neurology and Neurobiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center of Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Ting Ma
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- Peng Cheng Laboratory, Shenzhen, China
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Fang YHD, McConathy JE, Yacoubian TA, Zhang Y, Kennedy RE, Standaert DG. Image Quantification for TSPO PET with a Novel Image-Derived Input Function Method. Diagnostics (Basel) 2022; 12:1161. [PMID: 35626315 PMCID: PMC9140104 DOI: 10.3390/diagnostics12051161] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/02/2022] [Accepted: 05/03/2022] [Indexed: 01/27/2023] Open
Abstract
There is a growing interest in using 18F-DPA-714 PET to study neuroinflammation and microglial activation through imaging the 18-kDa translocator protein (TSPO). Although quantification of 18F-DPA-714 binding can be achieved through kinetic modeling analysis with an arterial input function (AIF) measured with blood sampling procedures, the invasiveness of such procedures has been an obstacle for wide application. To address these challenges, we developed an image-derived input function (IDIF) that noninvasively estimates the arterial input function from the images acquired for 18F-DPA-714 quantification. Methods: The method entails three fully automatic steps to extract the IDIF, including a segmentation of voxels with highest likelihood of being the arterial blood over the carotid artery, a model-based matrix factorization to extract the arterial blood signal, and a scaling optimization procedure to scale the extracted arterial blood signal into the activity concentration unit. Two cohorts of human subjects were used to evaluate the extracted IDIF. In the first cohort of five subjects, arterial blood sampling was performed, and the calculated IDIF was validated against the measured AIF through the comparison of distribution volumes from AIF (VT,AIF) and IDIF (VT,IDIF). In the second cohort, PET studies from twenty-eight healthy controls without arterial blood sampling were used to compare VT,IDIF with VT,REF measured using a reference region-based analysis to evaluate whether it can distinguish high-affinity (HAB) and mixed-affinity (MAB) binders. Results: In the arterial blood-sampling cohort, VT derived from IDIF was found to be an accurate surrogate of the VT from AIF. The bias of VT, IDIF was −5.8 ± 7.8% when compared to VT,AIF, and the linear mixed effect model showed a high correlation between VT,AIF and VT, IDIF (p < 0.001). In the nonblood-sampling cohort, VT, IDIF showed a significance difference between the HAB and MAB healthy controls. VT, IDIF and standard uptake values (SUV) showed superior results in distinguishing HAB from MAB subjects than VT,REF. Conclusions: A novel IDIF method for 18F-DPA-714 PET quantification was developed and evaluated in this study. This IDIF provides a noninvasive alternative measurement of VT to quantify the TSPO binding of 18F-DPA-714 in the human brain through dynamic PET scans.
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Affiliation(s)
- Yu-Hua Dean Fang
- Department of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA;
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (T.A.Y.); (D.G.S.)
| | - Jonathan E. McConathy
- Department of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA;
| | - Talene A. Yacoubian
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (T.A.Y.); (D.G.S.)
| | - Yue Zhang
- Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (Y.Z.); (R.E.K.)
| | - Richard E. Kennedy
- Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (Y.Z.); (R.E.K.)
| | - David G. Standaert
- Center for Neurodegeneration and Experimental Therapeutics, Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (T.A.Y.); (D.G.S.)
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Wei S, Joshi N, Salerno M, Ouellette D, Saleh L, Delorenzo C, Woody C, Schlyer D, Purschke ML, Pratte JF, Junnarkar S, Budassi M, Cao T, Fried J, Karp JS, Vaska P. PET Imaging of Leg Arteries for Determining the Input Function in PET/MRI Brain Studies Using a Compact, MRI-Compatible PET System. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022; 6:583-591. [PMID: 36212108 PMCID: PMC9541963 DOI: 10.1109/trpms.2021.3111841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
In this study, we used a compact, high-resolution, and MRI-compatible PET camera (VersaPET) to assess the feasibility of measuring the image-derived input function (IDIF) from arteries in the leg with the ultimate goal of enabling fully quantitative PET brain imaging without blood sampling. We used this approach in five 18F-FDG PET/MRI brain studies in which the input function was also acquired using the gold standard of serial arterial blood sampling. After accounting for partial volume, dispersion, and calibration effects, we compared the metabolic rates of glucose (MRglu) quantified from VersaPET IDIFs in 80 brain regions to those using the gold standard and achieved a bias and variability of <5% which is within the range of reported test-retest values for this type of study. We also achieved a strong linear relationship (R2 >0.97) against the gold standard across regions. The results of this preliminary study are promising and support further studies to optimize methods, validate in a larger cohort, and extend to the modeling of other radiotracers.
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Affiliation(s)
- Shouyi Wei
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Nandita Joshi
- Department of Electrical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Michael Salerno
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - David Ouellette
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Lemise Saleh
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Christine Delorenzo
- Department of Psychiatry and Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Craig Woody
- Department of Physics, Brookhaven National Laboratory, Upton, NY, USA
| | - David Schlyer
- Department of Physics, Brookhaven National Laboratory, Upton, NY, USA
| | | | - Jean-Francois Pratte
- Interdisciplinary Institute for Technological Innovation, Université de Sherbrooke, Sherbrooke, Canada
| | | | - Michael Budassi
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | | | - Jack Fried
- Department of Physics, Brookhaven National Laboratory, Upton, NY, USA
| | - Joel S. Karp
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul Vaska
- Department of Biomedical Engineering and Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA
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Krahe J, Dogan I, Didszun C, Mirzazade S, Haeger A, Joni Shah N, Giordano IA, Klockgether T, Madelin G, Schulz JB, Romanzetti S, Reetz K. Increased brain tissue sodium concentration in Friedreich ataxia: A multimodal MR imaging study. NEUROIMAGE: CLINICAL 2022; 34:103025. [PMID: 35500368 PMCID: PMC9065922 DOI: 10.1016/j.nicl.2022.103025] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 04/01/2022] [Accepted: 04/24/2022] [Indexed: 11/28/2022] Open
Abstract
In patients with Friedreich ataxia, structural MRI is typically used to detect abnormalities primarily in the brainstem, cerebellum, and spinal cord. The aim of the present study was to additionally investigate possible metabolic changes in Friedreich ataxia using in vivo sodium MRI that may precede macroanatomical alterations, and to explore potential associations with clinical parameters of disease progression. Tissue sodium concentration across the whole brain was estimated from sodium MRI maps acquired at 3 T and compared between 24 patients with Friedreich ataxia (21-57 years old, 13 females) and 23 controls (21-60 years old, 12 females). Tensor-based morphometry was used to assess volumetric changes. Total sodium concentrations and volumetric data in brainstem and cerebellum were correlated with clinical parameters, such as severity of ataxia, activity of daily living and disability stage, age, age at onset, and disease duration. Compared to controls, patients showed reduced brain volume in the right cerebellar lobules I-V (difference in means: -0.039% of total intracranial volume [TICV]; Cohen's d = 0.83), cerebellar white matter (WM) (-0.105%TICV; d = 1.16), and brainstem (-0.167%TICV; d = 1.22), including pons (-0.102%TICV; d = 1.00), medulla (-0.036%TICV; d = 1.72), and midbrain (-0.028%TICV; d = 1.05). Increased sodium concentration was additionally detected in the total cerebellum (difference in means: 2.865 mmol; d = 0.68), and in several subregions with highest effect sizes in left (5.284 mmol; d = 1.01) and right cerebellar lobules I-V (5.456 mmol; d = 1.00), followed by increases in the vermis (4.261 mmol; d = 0.72), and in left (2.988 mmol; d = 0.67) and right lobules VI-VII (2.816 mmol; d = 0.68). In addition, sodium increases were also detected in all brainstem areas (3.807 mmol; d = 0.71 to 5.42 mmol; d = 1.19). After controlling for age, elevated total sodium concentrations in right cerebellar lobules IV were associated with younger age at onset (r = -0.43) and accordingly with longer disease duration in patients (r = 0.43). Our findings support the potential of in vivo sodium MRI to detect metabolic changes of increased total sodium concentration in the cerebellum and brainstem, the key regions in Friedreich ataxia. In addition to structural changes, sodium changes were present in cerebellar hemispheres and vermis without concomitant significant atrophy. Given the association with age at disease onset or disease duration, metabolic changes should be further investigated longitudinally and in larger cohorts of early disease stages to determine the usefulness of sodium MRI as a biomarker for early neuropathological changes in Friedreich ataxia and efficacy measure for future clinical trials.
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Affiliation(s)
- Janna Krahe
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany
| | - Claire Didszun
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany
| | - Shahram Mirzazade
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany
| | - Alexa Haeger
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany
| | - Nadim Joni Shah
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany,Institute of Neuroscience and Medicine 4 (INM-4), Research Centre Juelich GmbH, 52428 Juelich, Germany,Monash Institute of Medical Engineering, Department of Electrical and Computer Systems Engineering, and Monash Biomedical Imaging, School of Psychological Sciences, Monash University, Melbourne, VIC 3800, Australia
| | - Ilaria A. Giordano
- Department of Neurology, University Hospital of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany,German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127 Bonn, Germany
| | - Thomas Klockgether
- Department of Neurology, University Hospital of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany,German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127 Bonn, Germany
| | - Guillaume Madelin
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York NY10016, USA
| | - Jörg B. Schulz
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany
| | - Sandro Romanzetti
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany; JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Centre Juelich GmbH and RWTH Aachen University, 52074 Aachen, Germany.
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40
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An efficient combination of quadruple biomarkers in binary classification using ensemble machine learning technique for early onset of Alzheimer disease. Neural Comput Appl 2022. [DOI: 10.1007/s00521-022-07076-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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41
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Lee J, Ha S, Kim REY, Lee M, Kim D, Lim HK. Development of Amyloid PET Analysis Pipeline Using Deep Learning-Based Brain MRI Segmentation—A Comparative Validation Study. Diagnostics (Basel) 2022; 12:diagnostics12030623. [PMID: 35328176 PMCID: PMC8947654 DOI: 10.3390/diagnostics12030623] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 02/25/2022] [Accepted: 02/27/2022] [Indexed: 02/04/2023] Open
Abstract
Amyloid positron emission tomography (PET) scan is clinically essential for the non-invasive assessment of the presence and spatial distribution of amyloid-beta deposition in subjects with cognitive impairment suspected to have been a result of Alzheimer’s disease. Quantitative assessment can enhance the interpretation reliability of PET scan; however, its clinical application has been limited due to the complexity of preprocessing. This study introduces a novel deep-learning-based approach for SUVR quantification that simplifies the preprocessing step and significantly reduces the analysis time. Using two heterogeneous amyloid ligands, our proposed method successfully distinguished standardized uptake value ratio (SUVR) between amyloidosis-positive and negative groups. The proposed method’s intra-class correlation coefficients were 0.97 and 0.99 against PETSurfer and PMOD, respectively. The difference of global SUVRs between the proposed method and PETSurfer or PMOD were 0.04 and −0.02, which are clinically acceptable. The AUC-ROC exceeded 0.95 for three tools in the amyloid positive assessment. Moreover, the proposed method had the fastest processing time and had a low registration failure rate (1%). In conclusion, our proposed method calculates SUVR that is consistent with PETSurfer and PMOD, and has advantages of fast processing time and low registration failure rate. Therefore, PET quantification provided by our proposed method can be used in clinical practice.
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Affiliation(s)
- Jiyeon Lee
- Research Institute, Neurophet Inc., Seoul 06234, Korea; (J.L.); (R.E.Y.K.); (M.L.)
| | - Seunggyun Ha
- Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea;
| | - Regina E. Y. Kim
- Research Institute, Neurophet Inc., Seoul 06234, Korea; (J.L.); (R.E.Y.K.); (M.L.)
| | - Minho Lee
- Research Institute, Neurophet Inc., Seoul 06234, Korea; (J.L.); (R.E.Y.K.); (M.L.)
| | - Donghyeon Kim
- Research Institute, Neurophet Inc., Seoul 06234, Korea; (J.L.); (R.E.Y.K.); (M.L.)
- Correspondence: (D.K.); (H.K.L.); Tel.: +82-10-9361-3781 (D.K.); +82-10-3797-6315 (H.K.L.)
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 07345, Korea
- Correspondence: (D.K.); (H.K.L.); Tel.: +82-10-9361-3781 (D.K.); +82-10-3797-6315 (H.K.L.)
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Tian Q, Bilgel M, Moghekar AR, Ferrucci L, Resnick SM. Olfaction, Cognitive Impairment, and PET Biomarkers in Community-Dwelling Older Adults. J Alzheimers Dis 2022; 86:1275-1285. [PMID: 35180111 DOI: 10.3233/jad-210636] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Olfactory deficits are early features of preclinical Alzheimer's disease (AD). Whether olfaction is associated with PET biomarkers among community-dwelling older adults is less clear. OBJECTIVE Investigate cross-sectional and longitudinal associations of olfaction with mild cognitive impairment (MCI) and amyloid-β (Aβ) and tau deposition. METHODS We analyzed 364 initially cognitively normal participants (58% women, 24% black) who had baseline olfaction data and subsequent cognitive assessments during an average 2.4-year. A subset of 129 had PET-PiB (Aβ) (n = 72 repeated) and 105 had 18F-flortaucipir (FTP)-PET (tau) (n = 44 repeated). Olfaction was measured using a 16-item Sniffin' Sticks Odor Identification Test. The association of olfaction with incident MCI was examined using Cox regression. Associations with PiB-distribution volume ratio (DVR) and FTP-standardized uptake value ratio (SUVR) were examined using partial correlation. We tested whether PiB+/-status modified these associations. Analyses were adjusted for demographics and olfactory test version. RESULTS 17 (5%) participants developed MCI. Each unit lower odor identification score was associated with 22% higher risk of developing MCI (p = 0.04). In the PET subset, lower scores were associated with higher mean cortical DVR and DVR in orbitofrontal cortex (OFC), precuneus, and middle temporal gyrus (p≤0.04). The "olfaction*PiB+/-" interaction in OFC DVR was significant (p = 0.03), indicating the association was limited to PiB positive individuals. Greater decline in odor identification score was associated with greater increase in anterior OFC DVR and entorhinal tau SUVR (p≤0.03). CONCLUSION Among community-dwelling older adults, poorer olfaction predicts incident MCI and is associated with overall and regional Aβ. Greater olfaction decline is associated with faster Aβ and tau accumulation in olfaction-related regions. Whether olfaction predicts AD-related neurodegenerative changes warrants further investigations.
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Affiliation(s)
- Qu Tian
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Abhay R Moghekar
- Department of Neurology and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
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43
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Kim JP, Chun MY, Kim SJ, Jang H, Kim HJ, Jeong JH, Na DL, Seo SW. Distinctive Temporal Trajectories of Alzheimer’s Disease Biomarkers According to Sex and APOE Genotype: Importance of Striatal Amyloid. Front Aging Neurosci 2022; 14:829202. [PMID: 35197846 PMCID: PMC8859452 DOI: 10.3389/fnagi.2022.829202] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 01/14/2022] [Indexed: 01/09/2023] Open
Abstract
PurposePreviously, sex and apolipoprotein E (APOE) genotype had distinct effects on the cognitive trajectory across the Alzheimer’s disease (AD) continuum. We therefore aimed to investigate whether these trajectory curves including β-amyloid (Aβ) accumulation in the cortex and striatum, and tau accumulation would differ according to sex and APOE genotype.MethodsWe obtained 534 subjects for 18F-florbetapir (AV45) PET analysis and 163 subjects for 18F-flortaucipir (AV1451) PET analysis from the Alzheimer’s Disease Neuroimaging Initiative database. For cortical Aβ, striatal Aβ, and tau SUVR, we fitted penalized splines to model the slopes of SUVR value as a non-linear function of baseline SUVR value. By integrating the fitted splines, we obtained the predicted SUVR curves as a function of time.ResultsThe time from initial SUVR to the cutoff values were 14.9 years for cortical Aβ, 18.2 years for striatal Aβ, and 22.7 years for tau. Although there was no difference in cortical Aβ accumulation rate between women and men, striatal Aβ accumulation was found to be faster in women than in men, and this temporal difference according to sex was more pronounced in tau accumulation. However, APOE ε4 carriers showed faster progression than non-carriers regardless of kinds of AD biomarkers’ trajectories.ConclusionOur temporal trajectory models illustrate that there is a distinct progression pattern of AD biomarkers depending on sex and APOE genotype. In this regard, our models will be able to contribute to designing personalized treatment and prevention strategies for AD in clinical practice.
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Affiliation(s)
- Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Center for Neuroimaging, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Min Young Chun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Soo-Jong Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Jee Hyang Jeong
- Departments of Neurology, Ewha Womans University Seoul Hospital, Ewha Womans University College of Medicine, Seoul, South Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
- *Correspondence: Sang Won Seo,
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Kaulen N, Rajkumar R, Régio Brambilla C, Mauler J, Ramkiran S, Orth L, Sbaihat H, Lang M, Wyss C, Rota Kops E, Scheins J, Neumaier B, Ermert J, Herzog H, Langen K, Lerche C, Shah NJ, Veselinović T, Neuner I. mGluR
5
and
GABA
A
receptor‐specific parametric
PET
atlas construction—
PET
/
MR
data processing pipeline, validation, and application. Hum Brain Mapp 2022; 43:2148-2163. [PMID: 35076125 PMCID: PMC8996359 DOI: 10.1002/hbm.25778] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 12/14/2021] [Accepted: 12/24/2021] [Indexed: 12/15/2022] Open
Abstract
The glutamate and γ‐aminobutyric acid neuroreceptor subtypes mGluR5 and GABAA are hypothesized to be involved in the development of a variety of psychiatric diseases. However, detailed information relating to their in vivo distribution is generally unavailable. Maps of such distributions could potentially aid clinical studies by providing a reference for the normal distribution of neuroreceptors and may also be useful as covariates in advanced functional magnetic resonance imaging (MR) studies. In this study, we propose a comprehensive processing pipeline for the construction of standard space, in vivo distributions of non‐displaceable binding potential (BPND), and total distribution volume (VT) based on simultaneously acquired bolus‐infusion positron emission tomography (PET) and MR data. The pipeline was applied to [11C]ABP688‐PET/MR (13 healthy male non‐smokers, 26.6 ± 7.0 years) and [11C]Flumazenil‐PET/MR (10 healthy males, 25.8 ± 3.0 years) data. Activity concentration templates, as well as VT and BPND atlases of mGluR5 and GABAA, were generated from these data. The maps were validated by assessing the percent error δ from warped space to native space in a selection of brain regions. We verified that the average δABP = 3.0 ± 1.0% and δFMZ = 3.8 ± 1.4% were lower than the expected variabilities σ of the tracers (σABP = 4.0%–16.0%, σFMZ = 3.9%–9.5%). An evaluation of PET‐to‐PET registrations based on the new maps showed higher registration accuracy compared to registrations based on the commonly used [15O]H2O‐template distributed with SPM12. Thus, we conclude that the resulting maps can be used for further research and the proposed pipeline is a viable tool for the construction of standardized PET data distributions.
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Affiliation(s)
- Nicolas Kaulen
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
| | - Ravichandran Rajkumar
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
- JARA BRAIN Translational Medicine Aachen Germany
| | - Cláudia Régio Brambilla
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
- JARA BRAIN Translational Medicine Aachen Germany
| | - Jörg Mauler
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
| | - Shukti Ramkiran
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
- JARA BRAIN Translational Medicine Aachen Germany
| | - Linda Orth
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
| | - Hasan Sbaihat
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
- Department of Medical Imaging Arab‐American University Palestine Jenin Palestine
| | - Markus Lang
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 5, INM‐5 Jülich Germany
| | - Christine Wyss
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department for Psychiatry, Psychotherapy and Psychosomatics Social Psychiatry University Hospital of Psychiatry Zurich Zurich Switzerland
| | - Elena Rota Kops
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
| | - Jürgen Scheins
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
| | - Bernd Neumaier
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 5, INM‐5 Jülich Germany
| | - Johannes Ermert
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 5, INM‐5 Jülich Germany
| | - Hans Herzog
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
| | - Karl‐Joseph Langen
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- JARA BRAIN Translational Medicine Aachen Germany
- Department of Nuclear Medicine RWTH Aachen University Aachen Germany
| | - Christoph Lerche
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
| | - N. Jon Shah
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- JARA BRAIN Translational Medicine Aachen Germany
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 11, INM‐11 Jülich Germany
- Department of Neurology RWTH Aachen University Aachen Germany
| | - Tanja Veselinović
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
| | - Irene Neuner
- Forschungszentrum Jülich Institute of Neuroscience and Medicine 4, INM‐4 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics RWTH Aachen University Aachen Germany
- JARA BRAIN Translational Medicine Aachen Germany
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Momin N, Palmeri JR, Lutz EA, Jailkhani N, Mak H, Tabet A, Chinn MM, Kang BH, Spanoudaki V, Hynes RO, Wittrup KD. Maximizing response to intratumoral immunotherapy in mice by tuning local retention. Nat Commun 2022; 13:109. [PMID: 35013154 PMCID: PMC8748612 DOI: 10.1038/s41467-021-27390-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Accepted: 11/17/2021] [Indexed: 01/08/2023] Open
Abstract
Direct injection of therapies into tumors has emerged as an administration route capable of achieving high local drug exposure and strong anti-tumor response. A diverse array of immune agonists ranging in size and target are under development as local immunotherapies. However, due to the relatively recent adoption of intratumoral administration, the pharmacokinetics of locally-injected biologics remains poorly defined, limiting rational design of tumor-localized immunotherapies. Here we define a pharmacokinetic framework for biologics injected intratumorally that can predict tumor exposure and effectiveness. We find empirically and computationally that extending the tumor exposure of locally-injected interleukin-2 by increasing molecular size and/or improving matrix-targeting affinity improves therapeutic efficacy in mice. By tracking the distribution of intratumorally-injected proteins using positron emission tomography, we observe size-dependent enhancement in tumor exposure occurs by slowing the rate of diffusive escape from the tumor and by increasing partitioning to an apparent viscous region of the tumor. In elucidating how molecular weight and matrix binding interplay to determine tumor exposure, our model can aid in the design of intratumoral therapies to exert maximal therapeutic effect.
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Affiliation(s)
- Noor Momin
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Joseph R Palmeri
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Emi A Lutz
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Noor Jailkhani
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Howard Mak
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Anthony Tabet
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Magnolia M Chinn
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Byong H Kang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Virginia Spanoudaki
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Richard O Hynes
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - K Dane Wittrup
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA.
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA.
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA.
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Ibaraki M, Matsubara K, Shinohara Y, Shidahara M, Sato K, Yamamoto H, Kinoshita T. Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET: comparison with an MR-based method in FDG imaging. Ann Nucl Med 2022; 36:717-727. [PMID: 35616808 PMCID: PMC9304042 DOI: 10.1007/s12149-022-01753-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 05/06/2022] [Indexed: 12/29/2022]
Abstract
OBJECTIVE In quantitative positron emission tomography (PET) of the brain, partial volume effect due mainly to the finite spatial resolution of the PET scanner (> 3 mm full width at half maximum [FWHM]) is a primary source of error in the measurement of tracer uptake, especially in small structures such as the cerebral cortex (typically < 3 mm thickness). The aim of this study was to evaluate the partial volume correction (PVC) performance of point spread function-incorporated reconstruction (PSF reconstruction) in combination with the latest digital PET scanner. This evaluation was performed through direct comparisons with magnetic resonance imaging (MR)-based PVC (used as a reference method) in a human brain study. METHODS Ten healthy subjects underwent brain 18F-FDG PET (30-min acquisition) on a digital PET/CT system (Siemens Biograph Vision, 3.5-mm FWHM scanner resolution at the center of the field of view) and anatomical T1-weighted MR imaging for MR-based PVC. PSF reconstruction was applied with a wide range of iterations (4 to 256; 5 subsets). FDG uptake in the cerebral cortex was evaluated using the standardized uptake value ratio (SUVR) and compared between PSF reconstruction and MR-based PVC. RESULTS Cortical structures were visualized by PSF reconstruction with several tens of iterations and were anatomically well matched with the MR-derived cortical segments. Higher numbers of iterations resulted in higher cortical SUVRs, which approached those of MR-based PVC (1.76), although even with the maximum number of iterations they were still smaller by 16% (1.47), corresponding to approximately 1.5-mm FWHM of the effective spatial resolution. CONCLUSION With the latest digital PET scanner, PSF reconstruction can be used as a PVC technique in brain PET, albeit with suboptimal resolution recovery. A relative advantage of PSF reconstruction is that it can be applied not only to cerebral cortical regions, but also to various small structures such as small brain nuclei that are hardly visualized on anatomical T1-weighted imaging, and thus hardly recovered by MR-based PVC.
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Affiliation(s)
- Masanobu Ibaraki
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874 Japan
| | - Keisuke Matsubara
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874 Japan ,Department of Management Science and Engineering, Faculty of System Science and Technology, Akita Prefectural University, Yurihonjo, Japan
| | - Yuki Shinohara
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874 Japan
| | - Miho Shidahara
- Department of Quantum Science and Energy Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan
| | - Kaoru Sato
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874 Japan
| | - Hiroyuki Yamamoto
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874 Japan
| | - Toshibumi Kinoshita
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874 Japan
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Althubaity N, Schubert J, Martins D, Yousaf T, Nettis MA, Mondelli V, Pariante C, Harrison NA, Bullmore ET, Dima D, Turkheimer FE, Veronese M. Choroid plexus enlargement is associated with neuroinflammation and reduction of blood brain barrier permeability in depression. Neuroimage Clin 2021; 33:102926. [PMID: 34972034 PMCID: PMC8718974 DOI: 10.1016/j.nicl.2021.102926] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 12/08/2021] [Accepted: 12/21/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Recent studies have shown that choroid plexuses (CP) may be involved in the neuro-immune axes, playing a role in the interaction between the central and peripheral inflammation. Here we aimed to investigate CP volume alterations in depression and their associations with inflammation. METHODS 51 depressed participants (HDRS score > 13) and 25 age- and sex-matched healthy controls (HCs) from the Wellcome Trust NIMA consortium were re-analysed for the study. All the participants underwent full peripheral cytokine profiling and simultaneous [11C]PK11195 PET/structural MRI imaging for measuring neuroinflammation and CP volume respectively. RESULTS We found a significantly greater CP volume in depressed subjects compared to HCs (t(76) = +2.17) that was positively correlated with [11C]PK11195 PET binding in the anterior cingulate cortex (r = 0.28, p = 0.02), prefrontal cortex (r = 0.24, p = 0.04), and insular cortex (r = 0.24, p = 0.04), but not with the peripheral inflammatory markers: CRP levels (r = 0.07, p = 0.53), IL-6 (r = -0.08, p = 0.61), and TNF-α (r = -0.06, p = 0.70). The CP volume correlated with the [11C]PK11195 PET binding in CP (r = 0.34, p = 0.005). Integration of transcriptomic data from the Allen Human Brain Atlas with the brain map depicting the correlations between CP volume and PET imaging found significant gene enrichment for several pathways involved in neuroinflammatory response. CONCLUSION This result supports the hypothesis that changes in brain barriers may cause reduction in solute exchanges between blood and CSF, disturbing the brain homeostasis and ultimately contributing to inflammation in depression. Given that CP anomalies have been recently detected in other brain disorders, these results may not be specific to depression and might extend to other conditions with a peripheral inflammatory component.
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Affiliation(s)
- Noha Althubaity
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Department of Radiological Sciences, College of Applied Medical Science, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
| | - Julia Schubert
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Tayyabah Yousaf
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Maria A Nettis
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Valeria Mondelli
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Carmine Pariante
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Neil A Harrison
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK; Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK
| | - Edward T Bullmore
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK; Immuno-Psychiatry, Immuno-Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage, UK
| | - Danai Dima
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Department of Psychology, School of Arts and Social Sciences, City University of London, London, UK
| | - Federico E Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Department of Information Engineering, University of Padua, Padua, Italy
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48
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Li Z, Fessler JA, Mikell JK, Wilderman SJ, Dewaraja YK. DblurDoseNet: A deep residual learning network for voxel radionuclide dosimetry compensating for single-photon emission computerized tomography imaging resolution. Med Phys 2021; 49:1216-1230. [PMID: 34882821 PMCID: PMC10041998 DOI: 10.1002/mp.15397] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 11/18/2021] [Accepted: 11/18/2021] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Current methods for patient-specific voxel-level dosimetry in radionuclide therapy suffer from a trade-off between accuracy and computational efficiency. Monte Carlo (MC) radiation transport algorithms are considered the gold standard for voxel-level dosimetry but can be computationally expensive, whereas faster dose voxel kernel (DVK) convolution can be suboptimal in the presence of tissue heterogeneities. Furthermore, the accuracies of both these methods are limited by the spatial resolution of the reconstructed emission image. To overcome these limitations, this paper considers a single deep convolutional neural network (CNN) with residual learning (named DblurDoseNet) that learns to produce dose-rate maps while compensating for the limited resolution of SPECT images. METHODS We trained our CNN using MC-generated dose-rate maps that directly corresponded to the true activity maps in virtual patient phantoms. Residual learning was applied such that our CNN learned only the difference between the true dose-rate map and DVK dose-rate map with density scaling. Our CNN consists of a 3D depth feature extractor followed by a 2D U-Net, where the input was 11 slices (3.3 cm) of a given Lu-177 SPECT/CT image and density map, and the output was the dose-rate map corresponding to the center slice. The CNN was trained with nine virtual patient phantoms and tested on five different phantoms plus 42 SPECT/CT scans of patients who underwent Lu-177 DOTATATE therapy. RESULTS When testing on virtual patient phantoms, the lesion/organ mean dose-rate error and the normalized root mean square error (NRMSE) relative to the ground truth of the CNN method was consistently lower than DVK and MC, when applied to SPECT images. Compared to DVK/MC, the average improvement for the CNN in mean dose-rate error was 55%/53% and 66%/56%; and in NRMSE was 18%/17% and 10%/11% for lesion and kidney regions, respectively. Line profiles and dose-volume histograms demonstrated compensation for SPECT resolution effects in the CNN-generated dose-rate maps. The ensemble noise standard deviation, determined from multiple Poisson realizations, was improved by 21%/27% compared to DVK/MC. In patients, potential improvements from CNN dose-rate maps compared to DVK/MC were illustrated qualitatively, due to the absence of ground truth. The trained residual CNN took about 30 s on a single GPU (Tesla V100) to generate a 512 × 512 × 130 dose-rate map for a patient. CONCLUSION The proposed residual CNN, trained using phantoms generated from patient images, has potential for real-time patient-specific dosimetry in clinical treatment planning due to its demonstrated improvement in accuracy, resolution, noise, and speed over the DVK/MC approaches.
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Affiliation(s)
- Zongyu Li
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeffrey A Fessler
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Justin K Mikell
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Scott J Wilderman
- Department of Nuclear Engineering and Radiologic Sciences, University of Michigan, Ann Arbor, Michigan, USA
| | - Yuni K Dewaraja
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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49
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Haeger A, Bottlaender M, Lagarde J, Porciuncula Baptista R, Rabrait-Lerman C, Luecken V, Schulz JB, Vignaud A, Sarazin M, Reetz K, Romanzetti S, Boumezbeur F. What can 7T sodium MRI tell us about cellular energy depletion and neurotransmission in Alzheimer's disease? Alzheimers Dement 2021; 17:1843-1854. [PMID: 34855281 DOI: 10.1002/alz.12501] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 08/09/2021] [Accepted: 09/22/2021] [Indexed: 12/20/2022]
Abstract
The pathophysiological processes underlying the development and progression of Alzheimer's disease (AD) on the neuronal level are still unclear. Previous research has hinted at metabolic energy deficits and altered sodium homeostasis with impaired neuronal function as a potential metabolic marker relevant for neurotransmission in AD. Using sodium (23 Na) magnetic resonance (MR) imaging on an ultra-high-field 7 Tesla MR scanner, we found increased cerebral tissue sodium concentration (TSC) in 17 biomarker-defined AD patients compared to 22 age-matched control subjects in vivo. TSC was highly discriminative between controls and early AD stages and was predictive for cognitive state, and associated with regional tau load assessed with flortaucipir-positron emission tomography as a possible mediator of TSC-associated neurodegeneration. TSC could therefore serve as a non-invasive, stage-dependent, metabolic imaging marker. Setting a focus on cellular metabolism and potentially disturbed interneuronal communication due to energy-dependent altered cell homeostasis could hamper progressive cognitive decline by targeting these processes in future interventions.
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Affiliation(s)
- Alexa Haeger
- NeuroSpin, CEA, CNRS, Paris-Saclay University, Gif-sur-Yvette, France.,Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Michel Bottlaender
- NeuroSpin, CEA, CNRS, Paris-Saclay University, Gif-sur-Yvette, France.,Paris-Saclay University, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay, France
| | - Julien Lagarde
- Paris-Saclay University, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay, France.,Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Sainte-Anne Hospital, Paris, France.,Université de Paris, Paris, France
| | | | | | - Volker Luecken
- NeuroSpin, CEA, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Jörg B Schulz
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Alexandre Vignaud
- NeuroSpin, CEA, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Marie Sarazin
- Paris-Saclay University, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, Orsay, France.,Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Sainte-Anne Hospital, Paris, France.,Université de Paris, Paris, France
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Sandro Romanzetti
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Fawzi Boumezbeur
- NeuroSpin, CEA, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
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50
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Bilgel M, Bannerjee A, Shafer A, An Y, Resnick SM. Vascular risk is not associated with PET measures of Alzheimer's disease neuropathology among cognitively normal older adults. NEUROIMAGE. REPORTS 2021; 1:100068. [PMID: 34927122 PMCID: PMC8682073 DOI: 10.1016/j.ynirp.2021.100068] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Cardiovascular disease (CVD) is associated with a higher risk of developing dementia. Studies have found that vascular risk factors are associated with greater amyloid-β (Aβ) and tau burden, which are hallmark neuropathologies of Alzheimer's disease (AD). Evidence for these associations during the preclinical stages of AD, when Aβ and tau pathologies first become detectable, is mixed. Quantifying the effect of vascular risk among cognitively normal individuals can help focus the efforts to develop therapeutic approaches aimed at modifying the course of preclinical AD. Using Bayesian analysis, we examined the relationship of Aβ and tau pathology with concurrent vascular risk among 87 cognitively normal individuals (median age 77, interquartile range 70-83) in the Baltimore Longitudinal Study of Aging. We quantified vascular risk as the probability of developing CVD within 10 years using published equations from the Framingham Heart Study. Aβ and tau pathologies were measured using positron emission tomography. As expected, Aβ positive participants had greater tau in the entorhinal cortex (EC) and inferior temporal gyrus (ITG) (difference in means = 0.09, p < 0.05 for each region), and 10-year CVD risk was positively correlated with white matter lesion burden (r = 0.24, p = 0.03). However, we did not find any associations between CVD risk and Aβ or tau. The data provided over two- and four-fold evidence towards the lack of a correlation between CVD risk and tau in the EC (Bayes factor BF = 2.4) and ITG (BF = 4.0), respectively. We found over three-fold evidence towards the lack of a difference in mean CVD risk by Aβ group (BF = 3.4). These null findings were replicated using a data-driven vascular risk score in the BLSA based on a principal component analysis of eight indicators of vascular health. Our data provide moderate evidence towards the lack of an association between vascular risk and concurrent AD neuropathology among cognitively normal older adults. This finding suggests that vascular risk and AD neuropathology may constitute independent pathways in the development of cognitive impairment and dementia.
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