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2. Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer’s disease (DEBBIE-AD): a prospective observational multicohort study protocol

Author

Padrela, B., Mahroo, A., Tee, M., Sneve, M. H., Moyaert, P., Geier, O., Kuijer, J. P. A., Beun, S., Nordhøy, W., David Zhu, Y., Buck, M. A., Hoinkiss, D. C., Konstandin, S., Huber, J., Wiersinga, J., Rikken, R., Leeuw, D., Grydeland, H., Tippett, L., Cawston, E. E., Ozturk-Isik, E., Linn, J., Brandt, M., Tijms, B. M., Giessen, E. M., Muller, M., Fjell, A., Walhovd, K., Bjørnerud, A., Pålhaugen, L., Selnes, P., Clement, P., Achten, E., Anazodo, U., Barkhof, F., Hilal, S., Fladby, T., Eickel, K., Morgan, C., Thomas, D. L., (0000-0002-3201-6002) Petr, J., Günther, M., Mutsaerts, H. J. M. M., Padrela, B., Mahroo, A., Tee, M., Sneve, M. H., Moyaert, P., Geier, O., Kuijer, J. P. A., Beun, S., Nordhøy, W., David Zhu, Y., Buck, M. A., Hoinkiss, D. C., Konstandin, S., Huber, J., Wiersinga, J., Rikken, R., Leeuw, D., Grydeland, H., Tippett, L., Cawston, E. E., Ozturk-Isik, E., Linn, J., Brandt, M., Tijms, B. M., Giessen, E. M., Muller, M., Fjell, A., Walhovd, K., Bjørnerud, A., Pålhaugen, L., Selnes, P., Clement, P., Achten, E., Anazodo, U., Barkhof, F., Hilal, S., Fladby, T., Eickel, K., Morgan, C., Thomas, D. L., (0000-0002-3201-6002) Petr, J., Günther, M., and Mutsaerts, H. J. M. M.

Abstract

Introduction Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer’s disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). Methods and analysis DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and ADrelated pathologies. Ethics and dissemination Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Published
2024

3. Multimodal MRI study on the relation between WM integrity and connected GM atrophy and its effect on disability in early multiple sclerosis

Author

Weeda, Merlin M., primary, van Nederpelt, D. R., additional, Twisk, J. W. R., additional, Brouwer, I., additional, Kuijer, J. P. A., additional, van Dam, M., additional, Hulst, H. E., additional, Killestein, J., additional, Barkhof, F., additional, Vrenken, H., additional, and Pouwels, P. J. W., additional

Published
2023
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4. DEveloping BBB-ASL as non-Invasive Early biomarker of Alzheimer’s Disease (DEBBIE-AD): Study design

Author

Padrela, B. E., Mahroo, A., Tee, M., Sneve, M. H., Moyaert, P., Geier, O., Kuijer, J. P. A., Beun, S., Nordhøy, W., Zhu, Y. D., Buck, M. A., Hoinkiss, D. C., Konstandin, S., Huber, J., Wiersinga, J., Rikken, R., Leeuw, D., Grydeland, H., Tippett, L., Cawston, E. E., Ozturk-Isik, E., Linn, J., Brandt, M., Tijms, B., Giessen, E., Muller, M., Fjell, A. M., Walhovd, K. B., Pålhaugen, L., Selnes, P., Clement, P., Achten, E., Anazodo, U., Barkhof, F., Hilal, S., Fladby, T., Eickel, K., Morgan, C., Thomas, D. L., (0000-0002-3201-6002) Petr, J., Günther, M., Mutsaerts, H. J. M. M., Padrela, B. E., Mahroo, A., Tee, M., Sneve, M. H., Moyaert, P., Geier, O., Kuijer, J. P. A., Beun, S., Nordhøy, W., Zhu, Y. D., Buck, M. A., Hoinkiss, D. C., Konstandin, S., Huber, J., Wiersinga, J., Rikken, R., Leeuw, D., Grydeland, H., Tippett, L., Cawston, E. E., Ozturk-Isik, E., Linn, J., Brandt, M., Tijms, B., Giessen, E., Muller, M., Fjell, A. M., Walhovd, K. B., Pålhaugen, L., Selnes, P., Clement, P., Achten, E., Anazodo, U., Barkhof, F., Hilal, S., Fladby, T., Eickel, K., Morgan, C., Thomas, D. L., (0000-0002-3201-6002) Petr, J., Günther, M., and Mutsaerts, H. J. M. M.

Abstract

Introduction: Loss of blood-brain barrier (BBB) integrity is hypothesized to be one of the earliest microvascular signs of Alzheimer’s disease (AD). Arterial spin labeling (ASL) perfusion MRI has recently been adapted to map the BBB permeability non-invasively. This article outlines the study design of the DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium, focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). Methods: DEBBIE-AD consists of 13 cohorts enrolling participants from subjective cognitive decline to AD, as well as healthy controls across the lifespan. The reproducibility and accuracy of BBB-ASL will be evaluated in healthy participants, and its clinical value will be evaluated with both established and novel AD biomarkers. Expected endpoints: DEBBIE-AD aims to provide evidence on the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD-related pathologies, which may provide new targets for treatment.

Published
2023

5. Reproducibility of 3T APT-CEST in healthy volunteers and brain glioma patients

Author

Wamelink, I. J. H. G., Kuijer, J. P. A., Padrela, B. E., Zhang, Y., Barkhof, F., Mutsaerts, H. J. M. M., (0000-0002-3201-6002) Petr, J., Giessen, E., Keil, V. C., Wamelink, I. J. H. G., Kuijer, J. P. A., Padrela, B. E., Zhang, Y., Barkhof, F., Mutsaerts, H. J. M. M., (0000-0002-3201-6002) Petr, J., Giessen, E., and Keil, V. C.

Abstract

BACKGROUND Amide proton transfer (APT) imaging is a chemical exchange saturation transfer (CEST) technique offering potential clinical applications in patients with brain tumors. PURPOSE To investigate whether cerebral APT-CEST is sufficiently reproducible in healthy tissue and glioma for clinical use at 3T. STUDY TYPE Prospective, longitudinal SUBJECTS Twenty-one healthy volunteers (M:F = 10:11; age 39±11 years) and six glioma patients (M:F = 3:3; age 50±17 years: four glioblastomas, one oligodendroglioma, one suspected low-grade glioma). FIELD STRENGTH/SEQUENCE 3T, SPACE-CEST ASSESSMENT APT-CEST measurement reproducibility was assessed within-session (glioma patients, healthy volunteers), and between-sessions and between-days (healthy volunteers). The standard deviation of the within-subject difference (SDdiff) was calculated in tumor regions of interest (ROI), and eight ROIs at relevant locations including a whole-brain ROI. STATISTICAL TESTS Brown-Forsythe tests and variance component analyses (VCA) were used to assess the reproducibility of ROIs for the three reproducibility time intervals. Intraclass correlation coefficient (ICC) was used to assess agreement between the ROIs for the three reproducibility time intervals. RESULTS APT-CEST magnetization transfer ratio asymmetry (MTRasym) was 0.89±0.96% on average in healthy brain tissue and 1.59±0.67% in tumor tissue. Intratumoral mean MTRasym was significantly higher than MTRasym in healthy-appearing tissue in patients (0.5±0.46%; P< 0.001). The APTCEST difference between GBMs and contralateral tissue was 1.11%. The average within-session, between-sessions, and between-days SDdiff of healthy control brains was 0.2%. The within-session SDdiff of whole-brain was 0.2% in both healthy volunteers and patients, and 0.21% in the segmented tumor. The orbitofrontal gyri were the ROI with the highest within-session SDdiff (0.61%). Within-session reproducibility of ROIs did not differ significantly from between-sessions or

Published
2023

6. Multimodal MRI-derived phenotypes in preclinical Alzheimer’s Disease: results from the EPAD cohort

Author

Lorenzini, L., Ingala, S., Wink, A. M., Kuijer, J. P. A., Wottschel, V., Sudre, C. H., Haller, S., Molinuevo, J. L., Gispert, J. D., Cash, D. M., Thomas, D. L., Vos, S. B., Ferran, P., (0000-0002-3201-6002) Petr, J., Wolz, R., Palombit, A., Schwarz, A. J., Chételat, G., Payoux, P., Di Perri, C., Pernet, C., Frisoni, G., Fox, N. C., Ritchie, C., Wardlaw, J., Waldman, A., Barkhof, F., Mutsaerts, H. J. M. M., Lorenzini, L., Ingala, S., Wink, A. M., Kuijer, J. P. A., Wottschel, V., Sudre, C. H., Haller, S., Molinuevo, J. L., Gispert, J. D., Cash, D. M., Thomas, D. L., Vos, S. B., Ferran, P., (0000-0002-3201-6002) Petr, J., Wolz, R., Palombit, A., Schwarz, A. J., Chételat, G., Payoux, P., Di Perri, C., Pernet, C., Frisoni, G., Fox, N. C., Ritchie, C., Wardlaw, J., Waldman, A., Barkhof, F., and Mutsaerts, H. J. M. M.

Abstract

Image-derived phenotypes (IDPs) from multimodal MRI sequences constitute an important resource that allows the characterization of brain alterations in the early stages of Alzheimer diseases and other neurodegenerative conditions. Here, we showed the computation of multimodal IDPs from the European Prevention of Alzheimer Dementia (EPAD) cohort and assessed their relationship with non-imaging markers of neurodegeneration. We demonstrated the clinical relevance of IDPs to uncover early brain alteration in AD by showing expected association with non-imaging data.

Published
2022

7. Diffuse glioma perfusion quantification with ASL and DSC: head-to-head comparison with 15O-H2O PET

Author

(0000-0002-3201-6002) Petr, J., Verburg, N., Kuijer, J. P. A., Koopman, T., Keil, V. C., Warnert, E. A. H., Barkhof, F., Hoff, J., Boellaard, R., Witt Hamer, P. C., J. M. M. Mutsaerts, H., (0000-0002-3201-6002) Petr, J., Verburg, N., Kuijer, J. P. A., Koopman, T., Keil, V. C., Warnert, E. A. H., Barkhof, F., Hoff, J., Boellaard, R., Witt Hamer, P. C., and J. M. M. Mutsaerts, H.

Abstract

Background: Arterial spin-labeling (ASL) is a viable non-invasive alternative to dynamic susceptibility contrast (DSC) for measuring cerebral blood flow (CBF). While quantitative accuracy of ASL and DSC was compared in healthy volunteers and patients, a comparison to a reference standard in patients diagnosed with glioma is still missing. Purpose: To probe the quantitative agreement between perfusion measurements based on ASL and DSC in comparison to the gold standard of PET in patients with glioma. Materials and Methods: This secondary analysis included pre-surgical ASL and DSC perfusion measurements in participants diagnosed with grade 2-4 gliomas drawn from the prospective FRONTIER study (Dutch National Trial Register - NTR5354) and compared the two techniques with the gold-standard perfusion measurement 15O-H2O-PET. The quantitative comparison was performed both in normal-appearing tissue as well as in the tumor region. The mean, maximum, and voxel-wise perfusion values were with and without normalization to normal-appearing tissue. And finally, a qualitative analysis was performed on individual cases to help interpret the quantitative results. Results: Eight patients (age 40.5 ± 17.0 years, 3 women) were analyzed. ASL showed better voxel-wise agreement with PET in the normal-appearing tissue than DSC (mean relative error of 26.8% vs. 33.8%). Within the tumor, cerebral blood flow (CBF) normalized contralateral gray matter showed similar tumor maximum values in both techniques - mean relative error of 23.2% for ASL and 22.0% for DSC. However, the mean relative error on a voxel-wise basis was better for ASL (27.2%) than for DSC (35.0%). Qualitatively, ASL tended to overestimate CBF in macrovessels, and DSC tended to overestimate CBF in non-enhancing tumors with small vessel diameters. Conclusion: While neither ASL nor DSC can readily replace 15O-H2O-PET in tumor quantitative perfusion measurement, ASL CBF presents a viable non-invasive semi-quantitative alternativ

Published
2022

8. A Beginner’s Guide to Arterial Spin Labeling (ASL) Image Processing

Author

Clement, P., (0000-0002-3201-6002) Petr, J., Dijsselhof, M. B., Padrela, B., Pasternak, M., Dolui, S., Jarutyte, L., Pinter, N., Hernandez Garcia, L., Jahn, A., Kuijer, J. P., Barkhof, F., Mutsaerts, H. J., Keil, V. C., Clement, P., (0000-0002-3201-6002) Petr, J., Dijsselhof, M. B., Padrela, B., Pasternak, M., Dolui, S., Jarutyte, L., Pinter, N., Hernandez Garcia, L., Jahn, A., Kuijer, J. P., Barkhof, F., Mutsaerts, H. J., and Keil, V. C.

Abstract

Arterial spin labeling (ASL) is a non-invasive and cost-effective MRI technique for brain perfusion measurements. While it has developed into a robust technique for scientific and clinical use, its image processing can still be daunting. The 2019 Ann Arbor ISMRM ASL working group established that education is one of the main areas that can accelerate the use of ASL in research and clinical practice. Specifically, the post-acquisition processing of ASL images and their preparation for region- of-interest or voxel-wise statistical analyses is a topic that has not yet received much educational attention. This educational review is aimed at medical and technical researchers with an interest in ASL image processing and analysis. We provide summaries of all typical ASL processing steps on both single-subject and group levels. The readers are assumed to have a basic understanding of cerebral perfusion (patho)physiology; a basic level of programming or image analysis is not required. Starting with an introduction of the physiology and MRI technique behind ASL, and how they interact with the image processing, we present an overview of processing pipelines and explain the specific ASL processing steps. Example video and image illustrations of ASL studies of different cases, as well as model calculations, help the reader develop an understanding of which processing steps to check for their own studies. Some of the educational content can be extrapolated to the processing of other MRI data. We anticipate that this educational review will help accelerate the application of ASL MRI for clinical brain research.

Published
2022

9. ASL-BIDS, the brain imaging data structure extension for arterial spin labeling

Author

Clement, P., Castellaro, M., Okell, T. W., Thomas, D. L., Vandemaele, P., Elgayar, S., Oliver-Taylor, A., Kirk, T., Woods, J. G., Vos, S., Kuijer, J. P. A., Achten, E., Osch, M. J. P., Gau, R., Detre, J., Lu, H., Alsop, D. C., Chappell, M. A., Hernandez-Garcia, L., (0000-0002-3201-6002) Petr, J., Mutsaerts, H. J. M. M., Clement, P., Castellaro, M., Okell, T. W., Thomas, D. L., Vandemaele, P., Elgayar, S., Oliver-Taylor, A., Kirk, T., Woods, J. G., Vos, S., Kuijer, J. P. A., Achten, E., Osch, M. J. P., Gau, R., Detre, J., Lu, H., Alsop, D. C., Chappell, M. A., Hernandez-Garcia, L., (0000-0002-3201-6002) Petr, J., and Mutsaerts, H. J. M. M.

Abstract

Arterial spin labeling (ASL) is a non-invasive MRI technique, allowing quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. Therefore, there is a strong need for standardization of ASL data storage, including acquisition metadata. Recently ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. The structure of the ASL data, focusing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information, are discussed. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. It is anticipated that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Published
2022

10. The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow

Author

Lorenzini, L., Ingala, S., Wink, A. M., Kuijer, J. P. A., Wottschel, V., Dijsselhof, M., Sudre, C. H., Haller, S., Molinuevo, J. L., Gispert, J. D., Cash, D. M., Thomas, D. L., Vos, S. B., Prados, F., (0000-0002-3201-6002) Petr, J., Wolz, R., Palombit, A., Schwarz, A. J., Chételat, G., Payoux, P., Di Perri, C., Wardlaw, J. M., Frisoni, G. B., Foley, C., Fox, N. C., Ritchie, C., Pernet, C., Waldman, A., Barkhof, F., Mutsaerts, H. J. M. M., Lorenzini, L., Ingala, S., Wink, A. M., Kuijer, J. P. A., Wottschel, V., Dijsselhof, M., Sudre, C. H., Haller, S., Molinuevo, J. L., Gispert, J. D., Cash, D. M., Thomas, D. L., Vos, S. B., Prados, F., (0000-0002-3201-6002) Petr, J., Wolz, R., Palombit, A., Schwarz, A. J., Chételat, G., Payoux, P., Di Perri, C., Wardlaw, J. M., Frisoni, G. B., Foley, C., Fox, N. C., Ritchie, C., Pernet, C., Waldman, A., Barkhof, F., and Mutsaerts, H. J. M. M.

Abstract

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer’s Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI pre- processing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features — i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features — Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) — were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.

Published
2022

11. Diffuse glioma perfusion quantification with ASL and DSC: head-to-head comparison with 15O-H2O PET

Author

Petr, J., Verburg, N., Kuijer, J. P. A., Koopman, T., Keil, V. C., Warnert, E. A. H., Barkhof, F., Hoff, J., Boellaard, R., Witt Hamer, P. C., and J. M. M. Mutsaerts, H.

Abstract

Background: Arterial spin-labeling (ASL) is a viable non-invasive alternative to dynamic susceptibility contrast (DSC) for measuring cerebral blood flow (CBF). While quantitative accuracy of ASL and DSC was compared in healthy volunteers and patients, a comparison to a reference standard in patients diagnosed with glioma is still missing. Purpose: To probe the quantitative agreement between perfusion measurements based on ASL and DSC in comparison to the gold standard of PET in patients with glioma. Materials and Methods: This secondary analysis included pre-surgical ASL and DSC perfusion measurements in participants diagnosed with grade 2-4 gliomas drawn from the prospective FRONTIER study (Dutch National Trial Register - NTR5354) and compared the two techniques with the gold-standard perfusion measurement 15O-H2O-PET. The quantitative comparison was performed both in normal-appearing tissue as well as in the tumor region. The mean, maximum, and voxel-wise perfusion values were with and without normalization to normal-appearing tissue. And finally, a qualitative analysis was performed on individual cases to help interpret the quantitative results. Results: Eight patients (age 40.5 ± 17.0 years, 3 women) were analyzed. ASL showed better voxel-wise agreement with PET in the normal-appearing tissue than DSC (mean relative error of 26.8% vs. 33.8%). Within the tumor, cerebral blood flow (CBF) normalized contralateral gray matter showed similar tumor maximum values in both techniques - mean relative error of 23.2% for ASL and 22.0% for DSC. However, the mean relative error on a voxel-wise basis was better for ASL (27.2%) than for DSC (35.0%). Qualitatively, ASL tended to overestimate CBF in macrovessels, and DSC tended to overestimate CBF in non-enhancing tumors with small vessel diameters. Conclusion: While neither ASL nor DSC can readily replace 15O-H2O-PET in tumor quantitative perfusion measurement, ASL CBF presents a viable non-invasive semi-quantitative alternative to DSC for glioma imaging.

Published
2022

12. ASL-BIDS, the brain imaging data structure extension for arterial spin labeling

Author

Clement, P., Castellaro, M., Okell, T. W., Thomas, D. L., Vandemaele, P., Elgayar, S., Oliver-Taylor, A., Kirk, T., Woods, J. G., Vos, S., Kuijer, J. P. A., Achten, E., Osch, M. J. P., Gau, R., Detre, J., Lu, H., Alsop, D. C., Chappell, M. A., Hernandez-Garcia, L., (0000-0002-3201-6002) Petr, J., Mutsaerts, H. J. M. M., Clement, P., Castellaro, M., Okell, T. W., Thomas, D. L., Vandemaele, P., Elgayar, S., Oliver-Taylor, A., Kirk, T., Woods, J. G., Vos, S., Kuijer, J. P. A., Achten, E., Osch, M. J. P., Gau, R., Detre, J., Lu, H., Alsop, D. C., Chappell, M. A., Hernandez-Garcia, L., (0000-0002-3201-6002) Petr, J., and Mutsaerts, H. J. M. M.

Abstract

Arterial spin labeling (ASL) is a non-invasive MRI technique, allowing quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. Therefore, there is a strong need for standardization of ASL data storage, including acquisition metadata. Recently ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. The structure of the ASL data, focusing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information, are discussed. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. It is anticipated that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Published
2021

14. Poster abstracts

Author

Ferrie, J., Shipley, M., Cappuccio, F., Brunner, E., Miller, M., Kumari, M., Marmot, M., Coenen, A., Castillo, J. L., Araya, F., Bustamante, G., Montecino, L., Torres, C., Oporto, S., Gronli, J., Fiske, E., Murison, R., Bjorvatn, B., Sorensen, E., Ursin, R., Portas, C. M., Rajaraman, S., Gribok, A., Wesensten, N., Balkin, T., Reifman, J., Dursunoglu, N., Ozkurt, S., Baser, S., Delen, O., Sarikaya, S., Sadler, P., Mitchell, P., Françon, D., Decobert, M., Herve, B., Richard, A., Griebel, G., Avenet, P., Scatton, B., Fur, G. L., Eckert, D., Jordan, A., Wellman, A., Smith, S., Malhotra, A., White, D., Bruck, D., Thomas, I., Kritikos, A., Oertel, W., Stiasny-Kolster, K., Garcia-Borreguero, D., Poewe, W., Hoegl, B., Kohnen, R., Schollmayer, E., Keffel, J., Trenkwalder, C., Valle, A., Roizenblatt, S., Fregni, F., Boggio, P., Tufik, S., Ward, K., Robertson, L., Palmer, L., Eastwood, P., Hillman, D., Lee, J., Mukherjee, S., de Padova, V., Barbato, G., Ficca, G., Zilli, I., Salzarulo, P., Veldi, M., Hion, T., Vasar, V., Kull, M., Nowak, L., Davis, J., Latzer, Y., Tzischinsky, O., Crowley, S., Carskadon, M., Anca-Herschkovitsch, M., Frey, D., Ortega, J., Wiseman, C., Farley, C., Wright, K., Campbell, A., Neill, A., Spiegel, K., Leproult, R., Tasali, E., Scherberg, N., van Cauter, E., Noradina, A. T., Karim, N. A., Norlinah, I., Raymond, A. A., Sahathevan, R., Hamidon, B., Werth, E., Poryazova, R., Khatami, R., Bassetti, C., Beran, R. 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F., Moisello, C., Bove, M., Busi, M., Pelosin, E., Tononi, G., Eguchi, N., Sakata, M., Urade, Y., Doe, N., Yoshihara, K., Abe, K., Manabe, Y., Iwatsuki, K., Hayashi, T., Shoji, M., Kamiya, T., Gooley, J., Brainard, G., Rajaratnam, S., Kronauer, R., Czeisler, C., Lockley, S., Phillips, A., Robinson, P., Burgess, H., Revell, V., Eastman, C., Bihari, S., Ramakrishnan, N., Camerino, D., Conway, P. M., Costa, G., Vandewalle, G., Albouy, G., Sterpenich, V., Darsaud, A., Rauchs, G., Berken, P.-Y, Balteau, E., Maquet, P., Tendero, J. A., Domenech, M. P., Isern, F. S., Martínez, C., Roure, N., Sancho, E. E., Moreno, C. R., Silva, M., Marqueze, E. C., Waage, S., Bobko, N., Chernyuk, V., Yavorskiy, Y., Saxvig, I., Sørensen, E., de Mello, M. T., Esteves, A., Teixeira, C., Bittencourt, L. R., Silva, R., Pires, M. 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Y. S., Cassaglia, P., Yu, V. Y. H., Walker, A. M., Kohler, M., Kennedy, D., Martin, J., van Den Heuvel, C., Lushington, K., Herron, K., Khurana, C., Sterr, A., Olivadoti, M., Toth, L., Opp, M., Dang-Vu, T., Degueldre, C., Gais, S., Dang-Vu, T. T., Desseilles, M., Philips, C., Chijavadze, E., Babilodze, M., Chkhartishvili, E., Nachkebia, N., Mchedlidze, O., Dzadzamia, S., Griffiths, R., Walker, A., Horovitz, S., Fukunaga, M., Carr, W., Picchioni, D., de Zwart, J., van Gelderen, P., Braun, A., Duyn, J., Hanlon, E. H., Faraguna, U., Vyazovskiy, V., Cirelli, C., Ocampo-Garcés, A., Ibáñez, F., López, S., Vivaldi, E., Torrealba, F., Romanowski, C. P. 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L., Nagai, R., do Rosário Dias De Oliveira Latorre, M., Marina, F., Paterson, J., Jackson, M., Johnston, P., Papafotiou, K., Croft, R., Dawson, S., Leenaars, C., Sandberg, H., Joosten, R., Dematteis, M., Feenstra, M., Wehrle, R., Rieger, M., Widmann, A., Dietl, T., Philipp, S., Wetter, T., Drummond, S., Czisch, M., Cairns, A., Lebourgeois, M., Harsh, J., Baulk, S., Vakulin, A., Catcheside, P., Antic, N., Mcevoy, D., Orff, H., Salamat, J., Meloy, M. 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V., Faria Sa, P., Yoon, I.-Y., Chung, S., Hee Lee, C., Kim, J.-W., Faludi, B., Wang, X., Li, Q., Wan, H., Li, M., Pallayova, M., Donic, V., Tomori, Z., Ioacara, S., Olech, T., Mccallum, C., Bowes, M., Bowes, J., Chia, M., Gilbert, S. S., Sajkov, D., Teichtahl, H., Stevenson, I., Cunnington, D., Kalman, J., Szaboova, E., Higami, S., Kryger, M., Higami, Y., Suzuki, C., Kitano, H., Carin, S., Olof, S., Yngve, G., Gösta, B., Carlberg, B., Stenlund, H., Franklin, K. A., Oliveira, A., Vasconcelos, L., Martinez, D., Goncalves, S. C., Gus, M., Silva, E. O. A., Fuchs, S. C., Fuchs, F. D., Li, A., Au, J., Ho, C., Sung, R., Wing, Y., Tada, H., Terada, N., Togawa, K., Nakagawa, Y., Kishida, K., Kihara, S., Hirata, A., Sonoda, M., Nishizawa, H., Nakamura, T., Shimomura, I., Funahashi, T., Andrewartha, P., Sasse, A., Becker, M., Troester, N., Olschewski, H., Lisamayerkard, L., Glos, M., Blau, A., Peter, J.-G., Chesworth, W., Wilson, G., Piper, A., Chuang, L.-P., Lin, S.-W., Wang, C.-J., Li, H.-Y., Chou, Y.-T., Fu, J.-Y., Liao, Y.-F., Tsai, Y.-H., Chan, K., Laks, L., Nishibayashi, M., Miyamoto, M., Miyamoto, T., Hirata, K., Hoever, P., De Haas, S., Chiossi, E., Van Gerven, J., Dingemanse, J., Winkler, J., Cavallaro, M., Narui, K., Kasai, T., Dohl, T., Takaya, H., Kawana, F., Ueno, K., Panjwani, U., Thakur, L., Anand, J. P., Banerjee, P. K., Leigh, M., Paduch, A., Armstrong, J., Sampson, D., Kotajima, F., Mochizuki, T., Lorr, D., Harder, H., Chesworth, M., Becker, H., Abd-Elaty, N. M., Elprince, M., Ismail, N., Elserogi, W., Yeo, A., George, K., Thomson, K., Stadler, D., Bradley, J., Paul, D., Schwartz, A., Hagander, L., Harlid, R., Hultcrantz, E., Haraldsson, P., Cho, J.-G., Narayan, J., Nagarajah, M., Perri, R., Johnson, P., Burgess, K., Chau, N., Mcevoy, R. D., Arnardottir, E. S., Thorleifsdottir, B., Olafsson, I., Gislason, T., Tsuiki, S., Fujimatsu, S., Munezawa, T., Sato, Y., Subedi, P., Ainslie, P., Topor, Z., Whitelaw, W., Chan, M., So, H., Lam, H., Ng, S., Chan, I., Lam, C., Saigusa, H., Higurashi, N., He, Z. M., Cui, X. C., Li, J., Dong, X., Lv, Y., Zhou, M., Han, X., An, P., Wang, L., Macey, P. M., Serber, S., Cross, R., Yan-Go, F., Marshall, M., Rees, D., Lee, S. H., Ho Cho, J. I., Shin, C., Lee, J. Y., Kwon, S. Y., Kim, T.-H., Vedam, H., Barnes, D., Walter, H., Karin, J., Hermann, P., Belyavskiy, E., Galitsyn, P., Arbolishvili, G., Litvin, A., Chazova, I., Mareev, V., Ramar, K., Khan, A., Gay, P., Strömberg, A., Ulander, M., Fridlund, B., Mårtensson, J., Yee, B., Desai, A., Buchanan, P., Crompton, R., Melehan, K., Wong, P., Tee, A., Ng, A., Darendeliler, M. A., Ye, L., Maislin, G., Hurley, S., Mccluskey, S., Weaver, T., Yun, C.-H., Ji, K.-H., Ahn, J. Y., Lee, H.-W., Zhang, X., Yin, K., Zhaofang, G., Chong, L., Navailles, B., Zenou, E., Cheze, L., Pignat, J.-C., Tang, T., Remmers, J., Vasilakos, K., Denotti, A., Gilholme, J., Castronovo, V., Marelli, S., Aloia, M., Fantini, M. L., Kuo, T., Manconi, M., Zucconi, M., Ferini-Strambi, L., Livia Fantini, M., Giarolli, L., Oldani, A., Lee, Y., Trenell, M., Berend, N., Wang, M., Liang, Z., Lei, F., Komada, I., Nishikawa, M., Sriram, K., Mignone, L., Antic, R., Fujiwara, K., Beaudry, M., Gauthier, L., Laforte, M., Lavigne, G., Wylie, P., Orr, W., Grover, S., Geisler, P., Engelke, E., Cossa, G., Veitch, E., Brillante, R., Mcardle, N., Murphy, M., Singh, B., Gain, K., Maguire, C., Mutch, S., Brown, S., Asciuto, T., Newsam, C., Fransson, A., Ísacsson, G., Tsou, M.-C., Hsu, S.-P., Almendros, I., Acerbi, I., Vilaseca, I., Dcruz, O., Vaughn, B., Muenzer, J., Lacassagne, L., Montemayor, T., Roch-Paoli, J., Qian, J., Petocz, P., Chan, M. R., Munro, J., Zimmerman, M., Stanchina, M., Millman, R., Cassel, W., Ploch, T., Loh, A., Koehler, U., Jerrentrup, A., Greulich, T., Doyle, G., Pascoe, T., Jorgensen, G., Baglioni, C., Lombardo, C., Espie, C., Violani, C., Edell-Gustafsson, U., Swahn, E., Ejdeback, J., Tygesen, H., Johansson, A., Neckelmann, D., Hilde Nordhus, I., Zs-Kovács, Á., Vámos, E., Zs-Molnár, M., Maisuradze, L., Gugushvili, J., Darchia, N., Gvilia, I., Lortkipanidze, N., Oniani, N., Wang-Weigand, S., Mayer, G., Roth-Schechter, B., Hsu, S.-C., Yang, C.-M., Liu, C.-Y., Ito, H., Omvik, S., Nordhus, I. H., Farber, R., Scharf, M., Harris-Collazo, R., Pereira, J., Andras, S., Ohayon, M., David, B., Morgan, K., Voorn, T., Vis, J., Kuijer, J., Fortier-Brochu, E., Beaulieu-Bonneau, S., Ivers, H., Morin, C., Beaulieu-Benneau, S., Harris, J., Bartlett, D., Paisley, L., Moncada, S., Toelle, B., Bonnet, M. H., Arand, D., Bonnet, J., Bonnet, M., Doi, Y., Edéll-Gustafsson, U., Strijers, R., Fernando, A., Arroll, B., Warman, G., Funakura, M., Shikano, S., Unemoto, Y., Fujisawa, M., Hong, S.-C., Jeong, J.-H., Shin, Y.-K., Han, J.-H., Lee, S.-P., Lee, J.-H., Mignot, E., Nakajima, T., Hayashida, K., Honda, M., Ardestani, P., Etemadifar, M., Nejadnik, H., Maghzi, A. H., Basiri, K., Ebrahimi, A., Davoodi, M., Peraita-Adrados, R., Vicario, J. L., Shin, H.-B., Marti, I., Carriero, L., Fulda, S., Beitinger, P., Pollmacher, T., Lam, J. S. P., Fong, S. Y. Y., Tang, N. L. S., Ho, C. K. W., Li, A. M. C., Wing, Y. K., Guilleminault, C., Black, J., Wells, C., Kantor, S., Janisiewicz, A., Scammell, T., Tanaka, S., Smith, A., Neufing, P., Gordon, T., Fuller, P., Gompf, H., Pedersen, N., Saper, C., Lu, J., Sasai, T., Donjacour, C., Fronczek, R., Le Cessie, S., Lammers, G. J., van Dijk, J. G., Hayashi-Ogawa, Y., Okuda, M., Lam, V. K.-H., Chen, A. L., Ho, C. K.-W., Wing, Y.-K., Lehrhaft, B., Brilliante, R., van Der Zande, W., Overeem, S., van Dijk, G., Lammers, J. G., Opazo, C. J., Jeong, D.-U., Sung, Y. H., Lyoo, I. K., Takahashi, Y., Murasaki, M., Bloch, K., Jung, H., Dahab, M. M., Campos, T. F., Mccabe, S., Maravic, K., Wiggs, L., Connelly, V., Barnes, J., Saito, Y., Ogawa, M., Murata, M., Nadig, U., Rahman, A., Aritake, K., D’Cruz, O., Suzuki, K., Kaji, Y., Takekawa, H., Nomura, T., Yasui, K., Nakashima, K., Bahammam, A., Rab, M. G., Owais, S., Alsuwat, K., Hamam, K., Zs, M., Boroojerdi, B., Giladi, N., Wood, D., Sherman, D., Chaudhuri, R., Partinen, M., Abdo, F., Bloem, B., Kremer, B., Verbeek, M., Cronlein, T., Mueller, U., Hajak, G., Zulley, J., Namba, K., Li, L., Mtsuura, M., Kaneita, Y., Ohida, T., Cappeliez, B., Moutrier, R., De, S., Dwivedi, S., Chambers, D., Gabbay, E., Watanabe, A., Valle, C., Kauati, A., Watanabe, R., Chediek, F., Botte, S., Azevedo, E., Kempf, J., Cizza, G., Torvik, S., Brancati, G., Smirne, N., Bruni, A., Goff, E., Freilich, S., Malaweera, A., Simonds, A., Mathias, C., Morrell, M., Rinsky, B., Fonarow, G., Gradinger, F. P., Boldt, C., Geyh, S., Stucki, A., Dahlberg, A., Michel, F., Savard, M.-H., Savard, J., Quesnel, C., Hirose, K., Takahara, M., Mizuno, K., Sadachi, H., Nagashima, Y., Yada, Y., Cheung, C.-F., Lau, C., Lai, W., Sin, K., Tam, C., Hellgren, J., Omenaas, E., Gíslason, T., Jögi, R., Franklin, K., Torén, K., Wang, F., Kadono, M., Shigeta, M., Nakazawa, A., Ueda, M., Fukui, M., Hasegawa, G., Yoshikawa, T., de Niet, G., Tiemens, B., Lendemeijer, B., Hutschemaekers, G., Gauthier, A.-K., Chevrette, T., Chevrier, E., Bouvier, H., Parry, B., Meliska, C., Nowakowski, S., Lopez, A., Martinez, F., Sorenson, D., Lien, M. L., Lattova, Z., Maurovich-Horvat, E., Nia, S., Pollmächer, T., Poulin, J., Chouinard, S., Stip, E., Guillem, F., Venne, D., Caouette, M., Lamont, M.-E., Lázár, A., Lázár, Z., Bíró, A., Gyõri, M., Tárnok, Z., Prekop, C., Gádoros, J., Halász, P., Bódizs, R., Okun, M., Hanusa, B., Hall, M., Wisner, K., Pereira, M., Kumar, R. A. J. E. S. H., Macey, P. A. U. L., Woo, M. A. R. Y., Serber, S. T. A. C. Y., Valladares, E. D. W. I. N., Harper, R. E. B. E. C. C. A., Harper, R. O. N. A. L. D., Puttonen, S., Härmä, M., Vahtera, J., Kivimäki, M., Lamarche, L., Hemmeter, U. M., Thum, A., Rocamora, R., Giesler, M., Haag, A., Dodel, R., Krieg, J. C., Shechter, A., L’Esperance, P., Boivin, D. B., Vu, M.-T., and Richards, H.

Published
2007
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15. ExploreASL: a collaborative effort to process and explore multi-center ASL data

Author

Mutsaerts, H. J., Petr, J., Groot, P., Ingala, S., Robertson, A., Vaclavu, L., Groote, I., Kuijf, H., O'Daly, O., Zelaya, F., Vandemaele, P., Wink, A. M., Kant, I., Caan, M., Morgan, C., Bresser, J., Lysvik, E., Schrantee, A., Shirzadi, Z., Kuijer, J. P. A., Anazodo, U., Richard, E., Bokkers, R., Reneman, L., Masellis, M., Achten, E., Günther, M., Macintosh, B., Golay, X., Hendrikse, J., Chapell, M., Osch, M., Thomas, D., Vita, E., Bjornerud, A., Nederveen, A., Asllani, I., and Barkhof, F.

Abstract

Arterial spin labeling (ASL) has undergone significant development since its inception; yet, standardized images processing procedures remain elusive. We present ExploreASL, a robust open source ASL image processing pipeline for clinical studies. Initiated through the European COST action ASL network, this joint effort provides integration and analysis of both single- and multi-center datasets across different operating systems. ExploreASL is optimized for both native- and standard-space analyses, and provides visual and automatic quality control on all intermediate and final images, allowing exploration of ASL datasets from multiple perspectives.

Published
2019

16. A multi-site round robin assessment of ASL using a perfusion phantom

Author

Oliver-Taylor, A., Hampshire, T., Mutsaerts, H.-J., Clement, P., Warnert, E., Kuijer, J. P. A., Baas, K., Petr, J., Siero, J. C. W., Marques, J. P., Sunaert, S., Borra, R. J. H., Osch, M. J. P., Golay, X., and Achten, E.

Abstract

Arterial Spin Labelling shows great promise for perfusion measurements; however, despite numerous volunteer reproducibility studies, comparisons have not been made using a phantom to establish differences due to the acquisition hardware and pulse sequences. We present data from a multi-site study using a perfusion phantom, targeting 3T MRI systems from a single vendor running the same software version.

Published
2019

17. Multi-modality perfusion imaging in gliomas: quantitative and visual comparison between ASL, DSC, and [15O]H20 PET

Author

Petr, J., Verburg, N., Koopman, T., Kuijer, J. P., Barkhof, F., Hoff, J., Boellaard, R., Witt Hamer, P. C., and Mutsaerts, H. J.

Subjects
otorhinolaryngologic diseases
Abstract

Purpose/Introduction Glioma vascularization and perfusion are important factors for tumor diagnostics. Dynamic Susceptibility Contrast (DSC) provides a proxy of perfusion by measuring mean transit time and blood volume and is sensitive to blood-brain-barrier breakdown. Arterial spin labeling (ASL) measures true tissue perfusion and can thus provide complementary information to DSC that may aid in tumor grading and in imaging the treatment response to, e.g., antiangiogenic drugs. Agreement of ASL and PET was shown in volunteers 1 . However, ASL can also partly show intravascular signal making ASL imaging of tumors challenging especially in the presence of vascular shunting. We compared ASL and DSC to the gold-standard for perfusion, [ 15 O]H 2 0 PET, to understand their limits as a surrogate of true regional perfusion. Subjects and Methods As part of the FRONTIER study, 8 glioma patients underwent multiple biopsies before scanning using Philips 3T Achieva MR and Gemini PET-CT 2 . PET (10min, 370 MBq of [ 15 O]H 2 0, simultaneous arterial blood sampling), ASL (pCASL 2D EPI, post-labeling delay and labeling duration 1800ms, 3x3x5 mm 3 ), DSC (TR 1.9s, TE 30ms, 1.7x2.4x3.6mm 3 , preloaded contrast) images were acquired. Cerebral blood flow (CBF) was quantified for ASL with ExploreASL, for DSC with Olea Sphere 3.0 with AIF obtained manually from MCA 3 . CBF images were aligned to PET and downsampled 6x6x6mm 3 resolution. Mean and voxel-wise CBF was compared between modalities in tumors and in contralateral-hemisphere gray matter (GM). Absolute and relative CBF (divided by subject’s mean whole-hemisphere contralateral GM CBF) were assessed. Results Mean hemispheric and voxelwise GM CBF values in the contralateral hemisphere were compared before and after normalization to global GM mean. For relative CBF, we observed a linear relationship between modalities in the tumor maximum values. Voxelwise analysis shows good agreement of PET and ASL for CBF ratio

Published
2019

18. Multi-modality perfusion imaging in gliomas: quantitative and visual comparison between ASL, DSC, and [15O]H20 PET

Author

(0000-0002-3201-6002) Petr, J., Verburg, N., Koopman, T., Kuijer, J. P., Barkhof, F., (0000-0003-4039-4780) Hoff, J., Boellaard, R., Witt Hamer, P. C., Mutsaerts, H. J., (0000-0002-3201-6002) Petr, J., Verburg, N., Koopman, T., Kuijer, J. P., Barkhof, F., (0000-0003-4039-4780) Hoff, J., Boellaard, R., Witt Hamer, P. C., and Mutsaerts, H. J.

Abstract

Purpose/Introduction Glioma vascularization and perfusion are important factors for tumor diagnostics. Dynamic Susceptibility Contrast (DSC) provides a proxy of perfusion by measuring mean transit time and blood volume and is sensitive to blood-brain-barrier breakdown. Arterial spin labeling (ASL) measures true tissue perfusion and can thus provide complementary information to DSC that may aid in tumor grading and in imaging the treatment response to, e.g., antiangiogenic drugs. Agreement of ASL and PET was shown in volunteers 1 . However, ASL can also partly show intravascular signal making ASL imaging of tumors challenging especially in the presence of vascular shunting. We compared ASL and DSC to the gold-standard for perfusion, [ 15 O]H 2 0 PET, to understand their limits as a surrogate of true regional perfusion. Subjects and Methods As part of the FRONTIER study, 8 glioma patients underwent multiple biopsies before scanning using Philips 3T Achieva MR and Gemini PET-CT 2 . PET (10min, 370 MBq of [ 15 O]H 2 0, simultaneous arterial blood sampling), ASL (pCASL 2D EPI, post-labeling delay and labeling duration 1800ms, 3x3x5 mm 3 ), DSC (TR 1.9s, TE 30ms, 1.7x2.4x3.6mm 3 , preloaded contrast) images were acquired. Cerebral blood flow (CBF) was quantified for ASL with ExploreASL, for DSC with Olea Sphere 3.0 with AIF obtained manually from MCA 3 . CBF images were aligned to PET and downsampled 6x6x6mm 3 resolution. Mean and voxel-wise CBF was compared between modalities in tumors and in contralateral-hemisphere gray matter (GM). Absolute and relative CBF (divided by subject’s mean whole-hemisphere contralateral GM CBF) were assessed. Results Mean hemispheric and voxelwise GM CBF values in the contralateral hemisphere were compared before and after normalization to global GM mean. For relative CBF, we observed a linear relationship between modalities in the tumor maximum values. Voxelwise analysis shows good agreement of PET and ASL for CBF ratio<1.5. For higher val

Published
2019

20. Comparing pCASL measurement of CBF between 3D GRASE and 2D EPI on 1.5T and 3T systems

Author

Baas, K. P. A., Mutsaerts, H. J. M. M., Petr, J., Kuijer, J. P. A., and Ven, K. C. C.

Abstract

We have compared CBF value agreement in healthy subjects across two readouts, 3D-GraSE and 2D-EPI, and two field strength, 1.5 and 3T, and investigated for which acquisition parameters we can reach the best agreement. Significantly higher GM CBF was observed with a 2D-EPI readout compared to a 3D-GraSE readout with equivalent acquisition resolution (p < 0.005 for 1.5T and p < 0.05 for 3T). A better agreement was observed between 3D-GraSE and 2D-EPI on 3T systems when the resolution of the 3D-GraSE readout was increased to match the effective resolution to the 2D-EPI scan (ICC = 0.772 and ICC = 0.932 respectively).

Published
2018

22. Identifying confounds to increase specificity during a 'no task condition'. Evidence for hippocampal connectivity using fMRI

Author

Rombouts, S A R B, Stam, C J, Kuijer, J P A, Scheltens, Ph, Barkhof, F, Physics and medical technology, Neurology, Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, and Amsterdam Neuroscience - Cellular & Molecular Mechanisms

Abstract

Functional MRI can be applied to study connectivity in the brain during a "no task condition." This study focuses on applying a multiple linear regression analysis to identify spurious connectivity caused by confounding factors such as physiologic noise and to separate these from hippocampal connectivity caused by the blood oxygen level dependent (BOLD) signal during a no-task condition. Regressors of interest (hippocampal time courses) as well as regressors of no interest (respiratory signal and cerebrospinal fluid), were included in the analysis, and each yielded a connectivity map. This method was applied at high sampling rate (limited volume, proper physiologic noise sampling), low sampling rate (whole brain scans possible), and at high and low spatial resolution in five healthy control subjects. Regressors of no interest showed specific connectivity patterns, different from hippocampal regressors. The latter showed connectivity between left and right hippocampus. The current study shows successful application of a multiple regression analysis to study connectivity between left and right hippocampus. Both maps of hippocampal connectivity caused by BOLD signal and connectivity caused by spurious signals could be identified.

Published
2003

24. Development of a diffusion-weighted MRI protocol for multicentre abdominal imaging and evaluation of the effects of fasting on measurement of apparent diffusion coefficients (ADCs) in healthy liver.

Author

WINFIELD, J. M., PAPOUTSAKI, M-V., RAGHEB, H., MORRIS, D. M., HEERSCHAP, A., TER VOERT, E. G. W., KUIJER, J. P. A., PIETERS, I. C., DOUGLAS, N. H. M., ORTON, M., and DE SOUZA, N. M.

Subjects
MAGNETIC resonance imaging, ABDOMINAL radiography, LIVER analysis, ANALYSIS of variance, PERFUSION, BLOOD flow
Abstract

Objective: To assess the effect of fasting and eating on estimates of apparent diffusion coefficient (ADC) in the livers of healthy volunteers using a diffusion-weighted MRI protocol with b-values of 100, 500 and 900sm rrr2 in a multicentre study at 1.5 T. Methods: 20 volunteers were scanned using 4 clinical 1.5-T MR scanners. Volunteers were scanned after fasting for at least 4 h and after eating a meal; the scans were repeated on a subsequent day. Median ADC estimates were calculated from all pixels in three slices near the centre of the liver. Analysis of variance (ANOVA) was used to assess the difference between ADC estimates in fasted and nonfasted states and between ADC estimates on different days. Results: ANOVA showed no difference between ADC estimates in fasted and non-fasted states (p = 0.8) nor between ADC estimates on different days (p = 0.8). There peat ability of the measurements was good, with coefficients of variation of 5.1% and 4.6% in fasted and non-fasted states, respectively. Conclusion: There was no significant difference in ADC estimates between fasted and non-fasted measurements, indicating that the perfusion sensitivity of ADC estimates obtained from b-values of 100, 500 and 900sm rrr2 is sufficiently low that changes in blood flow in the liver after eating are undetectable beyond the variability in the measurements. Advances in knowledge: Assessment of the effect of prandial state on ADC estimates is critical, in order to determine the appropriate patient preparation for biological validation in clinical trials. [ABSTRACT FROM AUTHOR]

Published
2015
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32. Abstracts

Author

Treibel, Thomas A., Fridman, Yaron, Hackman, Brianne, Kadakkal, Ajay, Sayeed, Aatif, Maanja, Maren, Daya, Hussein Abu, Moon, James C., Wong, Timothy C., Schelbert, Erik B., Duca, Franz, Kammerlander, Andreas A., Zotter-Tufaro, Caroline, Aschauer, Stefan, Bonderman, Diana, Mascherbauer, Julia, Schwitter, Juerg, Beigelman-Aubry, Catherine, Peguret, Nicolas, Stuber, Matthias, Delacoste, Jean, Belmondo, Bastien, Lovis, Alban, Simons, Julien, Long, Olivier, Grant, Kathleen, Berchier, Gregoire, Rohner, Chantal, Bonanno, Gabriele, Coppo, Simone, Ozsahin, Esat-Mahmut, Qanadli, Salah, Meuli, Reto, Bourhis, Jean, Ide, Seiko, Riesenkampff, Eugenie, Chiasson, David, Dipchand, Anne I., Kantor, Paul F., Chaturvedi, Rajiv R., Yoo, Shi-Joon, Grosse-Wortmann, Lars, Sandrini, C., Aquaro, GD, De Marchi, D, Ait Ali, L, Khraiche, D, Boddaert, N, Bonnet, D, Raimondi, F, Fridman, Yaron, Hackman, Brianne E., Kadakkal, Ajay, Daya, Hussein Abu, Wong, Timothy C., Schelbert, Erik B., Angela, Susana, Alberto, Cipriani, Manuel, De Lazzari, Federico, Marin, Francesca, Prevedello, Bendetta, Giorgi, Giorgio, De Conti, Giuseppe, Tarantini, Luisa, Cacciavillani, Emanuele, Bertaglia, Domenico, Corrado, Sabino, Iliceto, Martina, Perazzolo Marra, Camaioni, Claudia, Morlon, Lucas, Vergé, Marie-Philippe, Jais, Pierre, Roudaut, Raymond, Laurent, Francois, Lafitte, Stéphane, Cochet, Hubert, Réant, Patricia, Bohnen, S., Radunski, U. K., Lund, G. K., Senel, M., Avanesov, M., Tahir, E., Stehning, C., Adam, G., Blankenberg, S., Muellerleile, K., Khanji, Mohammed Y., Balawon, Armida, Boubertakh, Redha, Petersen, Steffen E, Hilbert, Sebastian, Spampinato, Ricardo, Oebel, Sabrina, Hindricks, Gerhard, Bollmann, Andreas, Jahnke, Cosima, Paetsch, Ingo, Goetschalckx, K., Bogaert, J., Desmet, W., Toth, A., Merkely, B., Janssens, S., Claus, P., Calvieri, C., Preda, M. B., Perfetti, A., Valaperta, R., Secchi, F., Fedele, F., Martelli, F., Lombardi, M., Reinstadler, Sebastian J., Eitel, Charlotte, Fuernau, Georg, de Waha, Suzanne, Desch, Steffen, Mende, Meinhard, Metzler, Bernhard, Schuler, Gerhard, Thiele, Holger, Eitel, Ingo, Maestrini, Viviana, Mun, Hong Cheang, Kotwinski, Paul, Rosmini, Stefania, Sanders, Julie, Lloyd, Guy, Dudley, J. Pennell, Kellman, Peter, Hugh, E. Montgomery, Manisty, Charlotte, James, C. Moon, James, S., Waterhouse, D.F., Murphy, T.M., Kenny, C., O'Hanlon, R., Bastiaenen, Rachel, Cox, Andrew T., Wijeyeratne, Yanushi, Colbeck, Nicholas, Pakroo, Nadia, Ahmed, Hammad, Bunce, Nick, Anderson, Lisa, Prasad, Sanjay, Sharma, Sanjay, Behr, Elijah R., Reid, A. B., Miller, C., Jovanovic, A., Woolfson, P., Abidin, N., Schmitt, M., Amadu, A.M., Rodrigues, J.C.L., Dastidar, A. Ghosh, Baritussio, A., Lawton, C., Venuti, G., Meloni, G.B., Conti, M., Bucciarelli-Ducci, C., Pontone, Gianluca, Andreini, Daniele, SoLbiati, Anna, Guglielmo, Marco, Mushtaq, Saima, Baggiano, Andrea, Beltrama, Virginia, Rota, Cristina, Guaricci, Andrea I., Pepi, Mauro, Wang, Yufei, Joannic, David, Juillion, Patrick, Delassus, P., Monnet, Aurélien, Lalande, Alain, Fontaine, Jean-Francois, Zweerink, A, Allaart, CP, Wu, L, Kuijer, JPA, Beek, AM, Croisille, P, Clarysse, P, van Rossum, AC, Nijveldt, R, Bulluck, Heerajnarain, Rosmini, Stefania, Abdel-Gadir, Amna, Bhuva, Anish, Treibel, Thomas A, White, Steven K, Hammond-Haley, Matthew, Sirker, Alex, Herrey, Anna, Manisty, Charlotte, Yellon, Derek M, Kellman, Peter, Moon, James C, Hausenloy, Derek J, Garg, P., Hassell, M, Foley, J., Ripley, D.P., Dobson, L., Swoboda, P.P., Fent, G., Musa, T.A., Erhayiem, B., Haaf, P., Greenwood, J.P., Nijveldt, R., Westenberg, J.J.M., Geest, R.J.V.D., Plein, S., Rodrigues, Jonathan C L, Amadu, Antonio Matteo, Dastidar, Amardeep Ghosh, Szantho, Gergley, Lyen, Stephen, Godsave, Cattleya, Ratcliffe, Laura E K, Burchell, Amy E, Hart, Emma C, Hamilton, Mark C K, Nightingale, Angus K, Paton, Julian F R, Manghat, Nathan E, Bucciarelli-Ducci, Chiara, Hafyane, Tarik, Teixeira, Tiago, Greiser, Andreas, Mongeon, Francois Pierre, Haifa, Almutairi, Mohammed, Khanji, Redha, Boubertakh, Marc, Miquel, Steffen, Petersen, Greulich, S., Kitterer, D., Latus, J., Henes, J., Kurmann, R., Gloekler, S., Wahl, A., Buss, S., Katus, H., Bobbo, M., Lombardi, M., Braun, N., Alscher, M.D., Sechtem, U., Mahrholdt, H., Meloni, A., Neri, M.G., Preziosi, P., Grassedonio, E., Schicchi, N., Keilberg, P., Pulini, S., Facchini, E., Positano, V., Pepe, A., Nazir, Sheraz A., Shetye, Abhishek, Khan, Jamal N., Singh, Anvesha, Kanagala, Prathap, Swarbrick, Daniel, Gulsin, Gaurav, Graham-Brown, Matthew, Squire, Iain, Gershlick, Anthony, McCann, Gerry P., Stefan Biesbroek, P., Amier, Raquel P., Teunissen, Paul F.A., Robbers, Lourens F.H.J., Beek, Aernout M., van Rossum, Albert C., Hofman, Mark B.M., van Royen, Niels, Nijveldt, Robin, Arenja, Nisha, Riffel, Johannes H, Djiokou, Charly Noel, Andre, Florian, Fritz, Thomas, Halder, Manuel, Thomas, Zelniker, Korosoglou, Grigorios, Katus, Hugo A, Buss, Sebastian J, Kammerlander, Andreas A., Schwaiger, Marianne L., Duca, Franz, Aschauer, Stefan, Marzluf, Beatrice A., Zotter-Tufaro, Caroline, Dalos, Daniel, Pfaffenberger, Stefan, Bonderman, Diana, Mascherbauer, Julia, Sayeed, Aatif, Fridman, Yaron, Hackman, Brianne, Kadakkal, Ajay, Maanja, Maren, Daya, Hussein Abu, Wong, Timothy C., Schelbert, Erik B., Ricci, F., Barison, A., Todiere, G., Gaeta, R., Galllina, S., Emdin, M., De Caterina, R., Aquaro, G.D., Bernhardt, Peter, Buckert, Dominik, Dyckmanns, Nils, Rottbauer, Wolfgang, Meierhofer, Christian, Kühn, Andreas, Shehu, Nerejda, Müller, Jan, Stern, Heiko, Ewert, Peter, Fratz, Sohrab, Vogt, Manfred, Devos, Daniel G.H., De Groote, Katya, Babin, Danilo, Demulier, Laurent, Taeymans, Yves, Westenberg, Jos J., Van Bortel, Luc, Segers, Patrick, Achten, Eric, De Schepper, Jean, Rietzschel, Ernst, Ruecker, Beate, Geiger, Julia, Makki, Malek, Burkhardt, Barbara, Kellenberger, Christian J., Buechel, Emanuela R. Valsangiacomo, Burkhardt, B.E.U., Kellenberger, C.J., Geiger, J., Ruecker, B., Buechel, E.R. Valsangiacomo, Kamphuis, Vivian P., Elbaz, Mohammed S.M., Kroft, Lucia J.M., van der Geest, Rob J., de Roos, Albert, Blom, Nico A., Westenberg, Jos J.M., Roest, Arno A.W., De Lazzari, Manuel, Cipriani, Alberto, Susana, Angela, Rizzo, Stefania, Giorgi, Benedetta, Carmelo, Lacognata, Bertaglia, Emanuele, Bauce, Barbara, Corrado, Domenico, Thiene, Gaetano, Marra, Martina Perazzolo, Basso, Cristina, Iliceto, Sabino, Nederend, I., Roest, A.A.W., van den Boogaard, P.J., ten Harkel, A.D.J., de Geus, J.C.N., Kroft, L.J.M., de Roos, A., Westenberg, J.J.M., Dux-Santoy, Lydia, Kale, Raquel, Teixido-Tura, Gisela, Maldonado, Giuliana, Huguet, Marina, Garcia-Dorado, David, Evangelista, Artur, Rodriguez-Palomares, Jose, Cavalcante, João L., Rijal, Shasank, Schindler, John T., Gleason, Thomas G., Lee, Joon S., Schelbert, Erik B., Rosmini, Stefania, Bulluck, Heerajnarain, Treibel, Thomas A, Bhuva, Anish, Abdel-Gadir, Amna, Culotta, Veronica, Merghani, Ahmed, Maestrini, Viviana, Herrey, Anna S, Kellman, Peter, Manisty, Charlotte, Moon, James C, Liu, B., Hayer, M.K., Baig, S., Shah, T., Rooney, S.J., Edwards, N.C., Steeds, R.P., Fent, G.J., Garg, P., Swoboda, P., Dobson, L.E., Musa, T.A., Foley, J.F., Haaf, P., Greenwood, J.P., Plein, S., Claessen, G., Schnell, F., Bogaert, J., Dymarkowski, S., Pattyn, N., Claus, P., Van Cleemput, J., Gerche, A. La, Heidbuchel, H., Behar, Jonathan, Toth, Daniel, Reiml, Sabrina, Panayiotou, Maria, Claridge, Simon, Jackson, Tom, Sohal, Manav, Webb, Jessica, O'Neill, Mark, Brost, Alexander, Mountney, Peter, Razavi, Reza, Rhode, Kawal, Rinaldi, Christopher Aldo, Oebel, S., Arya, A., Hilbert, S., Bollmann, A., Hindricks, G., Jahnke, C., Paetsch, I., Dinov, B., Baritussio, A., Perazzolo Marra, M., Ghosh Dastidar, A., Rodrigues, J., Zorzi, A., Susana, A., Scatteia, A., De Garate, E., Mattesi, G., Strange, J., Corrado, D., Bucciarelli-Ducci, C., Ranjit Arnold, J., Jerosch-Herold, Michael, Karamitsos, Theodoros D., Francis, Jane M., Bhamra-Ariza, Paul, Sarwar, Rizwan, Choudhury, Robin, Selvanayagam, Joseph B., Neubauer, Stefan, Tayal, Upasana, Scott, Andrew D, Wage, Rick, Ferreira, Pedro, Pennell, Dudley, Zhong, Xiaodong, Epstein, Fred, Firmin, David, Prasad, Sanjay, Kallifatidis, Alexandros, Prousalis, Anastasios, Mouratoglou, Sophia-Anastasia, Giannakoulas, George, Deligianni, Xenia, Bakaloudis, Michail, Magganaris, Nikolaos, Sianos, George, Karvounis, Haralampos, Santini, Francesco, Garg, P., Aziz, R., Foley, J.R.J., Fent, G., Musa, T.A., Haaf, P., Dobson, L., Swoboda, P.P., Greenwood, J.P., Plein, S., Geest, R.J.V.D., Westenberg, J.J.M., Beitzke, D., Rasul, S., Wadsak, W., Mitterhauser, M., Nolz, R., Stelzmueller, M., Loewe, C., Hacker, M., Funk, Stephanie, Kermer, Josephine, Dogangüzel, Serkan, von Knobelsdorff-Brenkenhoff, Florian, Schulz-Menger, Jeanette, Kolker, Shimon, Weisz, Giora, Bogot, Naama, Halpern, Irit Hadas, Wolak, Arik, Rutz, Tobias, Ginami, Giulia, Piccini, Davide, Coppo, Simone, Vincenti, Gabriella, Stuber, Matthias, Schwitter, Jürg, Safdar, Komal S, Gao, Xuexin, Ambach, Stephanie, Taylor, Michal D, Moore, Ryan, Taylor, Robin J, Toro-Salazar, Olga, Jeffries, John L, Bartone, Cheryl, Raman, Subha V, Mazur, Wojciech, Valente, F., Rodriguez-Palomares, J.F., Gutierrez, L., Pineda, V., Agliano, B., Galian, L., Teixido, G., Gonzalez-Alujas, M.T., Evangelista, A., Garcia-Dorado, D., Murdoch, R., Gandy, S., Nicholas, R., Houston, G., Martin, P., Muir, J., Matthew, S., Ramkumar, P. Guntur-, Cavin, I., Macaione, F., Barison, A., Pescetelli, I., Pali, F., Pizzino, F., Terrizzi, A., Di Lisi, D., Novo, G., Todiere, G., Assennato, P., Novo, S., Aquaro, G.D., Dastidar, Amardeep Ghosh, McAlindon, Elisa, Rodrigues, Jonathan, Baritussio, Anna, Scatteia, Alessandra, De Garate, Estefania, Benny Lawton, Chris, Erdei, Tamas, Szantho, Gergely, Hamilton, Mark, Bucciarelli-Ducci, Chiara, Pontone, Gianluca, Andreini, Daniele, Rota, Cristina, Guglielmo, Marco, Mushtaq, Saima, Baggiano, Andrea, Beltrama, Virginia, Solbiati, Anna, Guaricci, Andrea I., Pepi, Mauro, Grigoratos, Chrysanthos, Bratis, Konstantinos, Henningson, Markus, Dell'Omodarme, Matteo, Puntmann, Valentina O., Nagel, Eike, Meloni, Antonella, Giunta, Nicola, Giuliano, Pietro, Neri, Maria Giovanna, Restaino, Gennaro, Renne, Stefania, Quota, Alessandra, Positano, Vincenzo, De Marchi, Daniele, Pepe, Alessia, Pedrotti, Patrizia, Campadello, Paola, Masciocco, Gabriella, Facchetti, Rita, Milazzo, Angela, Quattrocchi, Giuseppina, Giannattasio, Cristina, Frigerio, Maria, Roghi, Alberto, Rimoldi, Ornella, De Garate, Estefania, Ghosh Dastidar, Amardeep, Baritussio, Anna, Scatteia, Alessandra, Amadu, Antonio, Venuti, Giuseppe, Rodrigues, Jonathan C., Bucciarelli-Ducci, Chiara, Careri, Giulia, Castelvecchio, Serenella, Camporeale, Antonia, Secchi, Francesco, Menicanti, Lorenzo, Lombardi, Massimo, Kockova, R., Sedlacek, K., Wichterle, D., Sikula, V., Tintera, J., Sukupova, L., Kautznerova, D., Segetova, M., Praveckova, A., Langova, R., Kryze, L., El-Husseini, W., Kautzner, J., Oebel, S., Dinov, B., Arya, A., Hilbert, S., Sommer, P., Bollmann, A., Hindricks, G., Paetsch, I., Jahnke, C., Nazir, Sheraz A., Greenwood, John P., Shetye, Abhishek, Khan, Jamal N., Singh, Anvesha, Kanagala, Prathap, Swarbrick, Daniel, Gulsin, Gaurav, Graham-Brown, Matthew, Gershlick, Anthony, McCann, Gerry P., Grigoratos, Chrysanthos, Liga, Riccardo, Bennatti, Elena, Barison, Andrea, Todiere, Giancarlo, Aquaro, Giovanni Donato, Dell'Omodarme, Matteo, Lombardi, Massimo, Emdin, Michele, Masci, Pier Giorgio, Barison, A, Ortalda, A, Todiere, G, Grigoratos, C, Vergaro, G, Mirizzi, G, Martini, N, De Marchi, D, Keilberg, P, Passino, C, Aquaro, GD, Emdin, M, Swoboda, Peter P, McDiarmid, Adam K, Erhayiem, Bara, Fent, Graham J, Dobson, Laura E, Garg, Pankaj, Musa, Tarique A, Foley, James R, Page, Stephen P, Greenwood, John P, Plein, Sven, Bulluck, Heerajnarain, Rosmini, Stefania, Abdel-Gadir, Amna, Bhuva, Anish, Treibel, Thomas A, White, Steven K, Fontana, Marianna, Ramlall, Manish, Hamarneh, Ashraf, Sirker, Alex, Herrey, Anna, Manisty, Charlotte, Yellon, Derek M, Kellman, Peter, Moon, James C, Hausenloy, Derek J, Broncano, J., Luna, A., Noguerol, T. Martin –, Caro, P., Toro-Cebada, R., Gonzalez, J. Sanchez –, Desroche, L.M., Milleron, O., Safar, B., Lavie-Badie, Y., Millischer, D., Abtan, J., Jondeau, G., Bermejo, Zorba Blázquez, Cuesta, Emilio, Rosillo, Sandra O., Guzmán, Gabriela, Pinilla, Inmaculada, González, Óscar, Caro, Juan, Ponz, Inés, López, Teresa, Refoyo, Elena, Kozor, Rebecca, Nordin, Sabrina, Treibel, Thomas A, Rosmini, Stefania, Castelleti, Silvia, Fontana, Marianna, Captur, Gabriella, Steeds, Rick, Baig, Shanat, Manisty, Charlotte, Grieve, Stuart M, Figtree, Gemma A, Moon, James C, Dastidar, Amardeep Ghosh, Rodrigues, Jonathan, De Garate, Estefania, Singhal, Priyanka, McAlindon, Elisa, Baritussio, Anna, Scatteia, Alessandra, Erdei, Tamas, Strange, Julian, Nightingale, Angus, Baumbach, Andreas, Johnson, Tom, Delgado, Victoria, Bucciarelli-Ducci, Chiara, Lapinskas, Tomas, Bucius, Paulius, Fedaravicius, Augustinas P., Urbonaite, Laura, Stabinskaite, Agnieta, Zaliunas, Remigijus, Elisabetta, Chiodi, Teresa, Cannizzaro Maria, Daniele, De Falco Alfano, Righi, Riccardo, Zerbini, Michela, Vincenzo, Positano, Cittanti, Corrado, Giganti, Melchiore, Giorgio, Benea, Grigoratos, Chrysanthos, Genovesi, Dario, Giorgetti, Assuero, Chiappino, Sara, Barison, Andrea, Vergaro, Giuseppe, Todiere, Giancarlo, Emdin, Michele, Marzullo, Paolo, Aquaro, Giovanni Donato, Ladeiras-Lopes, Ricardo, Turin-Moreira, Henrique, Bettencourt, Nuno, Fontes-Carvalho, Ricardo, Sampaio, Francisco, Ambale-Venkatesh, Bharath, Wu, Colin, Liu, Kiang, Bertoni, Alain, Ouyang, Pamela, Bluemke, David, Lima, João, Fent, GJ., Garg, P., Dobson, LE., Musa, TA., Foley, JF., Haaf, P., Greenwood, JP., Plein, S., Swoboda, PP., Abdul Rahman, E., Ismail, JR., Najme Khir, R., Lim, CW., Chua, N., Ibrahim, ZO., Zainal Abidin, HA., Mohd Arshad, MK., Kasim, SS., Rodrigues, Jonathan, Rooms, Ben, Hyde, Katie, Rohan, Stephen, Dastidar, Amardeep Ghosh, Hamilton, Mark, Bucciarelli-Ducci, Chiara, Nightingale, Angus, Paton, Julian, Manghat, Nathan, MacIver, David, Gibelli, Giuseppe, Demolli, Walter, Russo, Alessandra, Minoia, Chiara, Biasi, Salvatore, Mkrtchyan, Naira, Eltschkner, Christin, Christian, Meierhofer, Ewert, Peter, Martinoff, Stefan, Stern, Heiko, Fratz, Sohrab, Valinoti, Maddalena, Fabbri, Claudio, Mantovan, Roberto, Severi, Stefano, Corsi, Cristiana, Nyktari, E., Vassiliou, V., Arzanauskaite, M., Izgi, C., Lam, W., Prasad, S., Reindl, Martin, Reinstadler, Sebastian Johannes, Feistritzer, Hans-Josef, Klug, Gert, Mair, Johannes, Mayr, Agnes, Jaschke, Werner, Franz, Wolfgang-Michael, Metzler, Bernhard, Arnhold, K., Muehlberg, F., Fritschi, S., Funk, S., Prothmann, M., von Knobelsdorff-Brenkenhoff, F., Schulz-Menger, J., Lakhani, Zeeshan S. A., Mohan, B., karthik, G A., Raj, Vimal, Weir-McCall, Jonathan, Cassidy, Deirdre B, Belch, Jill JF, Gandy, Stephen J, Houston, Graeme, Lambert, Matthew A, Littleford, Roberta, Rowland, Janice, Struthers, Allan D, Khan, Faisel, Camaioni, Claudia, Salel, Marjorie, Hennig, Alexia, Corneloup, Olivier, Montaudon, Michel, Laurent, Francois, Cochet, Hubert, Kan, Rachel, Erhayiem, Bara, McDiarmid, Adam K., Garg, Pankaj, Dobson, Laura E., Musa, Tarique A., Ripley, David, Ajjan, Ramzi, Greenwood, John P., Plein, Sven, Swoboda, Peter P., Reinstadler, Sebastian J., Fuernau, Georg, Eitel, Charlotte, de Waha, Suzanne, Desch, Steffen, Metzler, Bernhard, Schuler, Gerhard, Thiele, Holger, Eitel, Ingo, Feistritzer, Hans-Josef, Reinstadler, Sebastian Johannes, Klug, Gert, Reindl, Martin, Mair, Johannes, Mayr, Agnes, Franz, Wolfgang-Michael, Metzler, Bernhard, Feistritzer, Hans-Josef, Klug, Gert, Reinstadler, Sebastian Johannes, Reindl, Martin, Mayr, Agnes, Franz, Wolfgang-Michael, Metzler, Bernhard, Festa, P., Cadoni, A., D'andrea, C., Costa, S., Keilberg, P., Lunardini, A., Ali, L. Ait, Ali, L. Ait, Aquaro, GD., Peritore, G., Ricci, F., De Marchi, D., Passino, C., Festa, P., Martínez, A. Tercero, Cuartero, J. Navarro, Soriano, J.G. Córdoba, Núñez, S. Calero, de Galarreta, T. Cros Ruiz, García, M. Villar, Page, J.C. Gallego, López, J.C. García, Ruiz, M. 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Abstract

Objectives: Myocardial fibrosis in noninfarcted myocardium is emerging as a principal phenotype of vulnerability to adverse events such as mortality and hospitalization for heart failure (HHF), but its optimal noninvasive measurement remains uncertain despite consistently robust histologic validation data for extracellular volume fraction (ECV). We therefore compared ECV, native T1, post contrast T1, the gadolinium contrast partition coefficient (lambda), and the presence of nonischemic scar in their associations with mortality and HHF outcomes. Method: To quantify of myocardial fibrosis, we performed T1 mapping (MOLLI) in basal and mid short axis slices with cardiovascular magnetic resonance (CMR) before contrast and 12-30 minutes post contrast bolus in 1185 consecutive patients without amyloidosis, hypertrophic or stress cardiomyopathy. We assessed associations with outcomes using Kaplan-Meier plots and chi square values from univariable Cox regression models. All standard T1 mapping parameters were obtained: native and post contrast myocardial T1, the partition coefficient lambda, and ECV. ECV = (1-hematocrit) · [ΔR1myocardium]/[ΔR1bloodpool], where R1 = 1/T1 Late gadolinium enhancement imaging with phase sensitive reconstruction identified nonischemic scar. Results: Over a median of 1.7 years, 111 individuals experienced events after CMR: 55 HHF events and 74 deaths. ECV yielded better separation of Kaplan-Meier curves in a dose dependent fashion (Figure) and also stronger associations with the combined endpoint of death or HHF. The ECV chi square (77.3, p < 0.001) was at least twice as large as the Native T1 chi square (37.5, p < 0.001), the lambda chi square (34.8, p < 0.001) and nonischemic scar (chi square = 20.5, p<0.001). Post-contrast T1 was not associated with outcomes, even when adjusting further for time after contrast bolus, renal function, and patient weight (chi square <3, p >0.10). Conclusion: Analogous to histologic previously published validation data, quantitative ECV myocardial fibrosis measures associated with outcomes far stronger than other surrogate measures outcome measures such as native T1, post contrast T1 and nonischemic scar on LGE images. These data suggest that ECV is the noninvasive metric of choice to measure myocardial fibrosis. Figure. Kaplan-Meier Plots for T1 mapping parameters.

Published
2016
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33. Effects of Acquisition Parameter Modifications and Field Strength on the Reproducibility of Brain Perfusion Measurements Using Arterial Spin-Labeling.

Author

Baas KPA, Petr J, Kuijer JPA, Nederveen AJ, Mutsaerts HJMM, and van de Ven KCC

Subjects
Adult, Aged, Aged, 80 and over, Cerebrovascular Circulation, Female, Humans, Imaging, Three-Dimensional methods, Male, Middle Aged, Perfusion Imaging methods, Reproducibility of Results, Spin Labels, Young Adult, Brain blood supply, Electron Spin Resonance Spectroscopy methods, Magnetic Resonance Imaging methods, Neuroimaging methods
Abstract

Background and Purpose: Although the added diagnostic value of arterial spin-labeling is shown in various cerebral pathologies, its use in clinical practice is limited. To encourage clinical adoption of ASL, we investigated the reproducibility of CBF measurements and the effects of variations in acquisition parameters compared to the recommended ASL implementation., Materials and Methods: Thirty-four volunteers (mean age, 57.8 ± 17.0 years; range, 22-80 years) underwent two separate sessions (1.5T and 3T scanners from a single vendor) using a 15-channel head coil. Both sessions contained repeated 3D and 2D pseudocontinuous arterial spin-labeling scans using vendor-recommended acquisition parameters (recommendation paper-based), followed by three 3D pseudocontinuous arterial spin-labeling scans, two with postlabeling delays of 1600  and 2000 ms and one with increased spatial resolution. All scans were single postlabeling delay. Intrasession (identical acquisitions, scanned five minutes apart) and intersession (first 2D and 3D acquisitions of two sessions) reproducibility was examined as well as the effect of parameter variations on CBF., Results: Intrasession CBF reproducibility was similar across image readouts and field strengths (within-subject coefficient of variation between 4.0% and 6.7%). Intersession within-subject coefficient of variation ranged from 6.6% to 14.8%. At 3T, the 3D acquisition with a higher spatial resolution resulted in less mixing of GM and WM signal, thus decreasing the bias in GM CBF between the 2D and 3D acquisitions (ΔCBF = 2.49 mL/100g/min [ P  < .001]). Postlabeling delay variations caused a modest bias (ΔCBF between -3.78 [ P  < .001] and 2.83 [ P  < .001] mL/100g/min)., Conclusions: Arterial spin-labeling imaging is reproducible at both field strengths, and the reproducibility is not significantly correlated with age. Furthermore, 3T tolerates more acquisition parameter variations and allows more extensive optimizations so that 3D and 2D acquisitions can be compared., (© 2021 by American Journal of Neuroradiology.)

Published
2021
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34. Multicontrast MR imaging at 7T in multiple sclerosis: highest lesion detection in cortical gray matter with 3D-FLAIR.

Author

Kilsdonk ID, de Graaf WL, Soriano AL, Zwanenburg JJ, Visser F, Kuijer JP, Geurts JJ, Pouwels PJ, Polman CH, Castelijns JA, Luijten PR, Barkhof F, and Wattjes MP

Subjects
Adolescent, Adult, Female, Humans, Male, Middle Aged, Prospective Studies, Severity of Illness Index, Young Adult, Cerebral Cortex pathology, Imaging, Three-Dimensional methods, Magnetic Resonance Imaging methods, Multiple Sclerosis pathology
Abstract

Background and Purpose: 7T MR imaging has led to improved detection and classification of cortical MS lesions, mainly based on T2*-weighted gradient-echo sequences. Depiction of cortical GM by using the recommended MS imaging protocol has not yet been investigated at 7T. We aimed to investigate prospectively which recommended sequence for clinical use has the highest value at 7T, in terms of GM and WM lesion detection., Materials and Methods: Thirty-seven patients with MS (mean age, 43.8 years; 25 women) and 7 healthy controls (mean age, 40.4 years; 5 women) underwent multicontrast 7T MR imaging including the recommended clinical 2D-T2WI, 3D-T1WI, 3D-FLAIR, and GM-specific 3D-DIR. Lesions were scored and categorized anatomically by 3 raters, in consensus. The value of sequences was evaluated lesion-wise and patient-wise (Wilcoxon signed-rank test)., Results: At 7T, 3D-FLAIR detected the highest number of total cortical GM lesions (217), 89% more than 3D-DIR and 87% and 224% more than 2D-T2WI and 3D-T1WI. Patient-wise analysis showed that this difference between 3D-FLAIR and 3D-DIR was statistically significant (P<.04), and most pronounced for the number of mixed lesions (P<.03). 3D-FLAIR also detected the highest number of total WM lesions (2605), but the difference with 3D-DIR and 3D-T1WI was not significant., Conclusions: When using recommended clinical sequences at 7T, the best way to detect cortical GM lesions is with 3D-FLAIR and not by GM-specific 3D-DIR or by conventional 2D-T2WI and 3D-T1WI sequences.

Published
2013
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35. Retinoblastoma: value of dynamic contrast-enhanced MR imaging and correlation with tumor angiogenesis.

Author

Rodjan F, de Graaf P, van der Valk P, Moll AC, Kuijer JP, Knol DL, Castelijns JA, and Pouwels PJ

Subjects
Child, Child, Preschool, Contrast Media, Female, Humans, Infant, Male, Reproducibility of Results, Sensitivity and Specificity, Statistics as Topic, Magnetic Resonance Imaging methods, Neovascularization, Pathologic complications, Neovascularization, Pathologic pathology, Retinal Neoplasms complications, Retinal Neoplasms pathology, Retinoblastoma complications, Retinoblastoma pathology
Abstract

Background and Purpose: Noninvasive evaluation of retinoblastoma treatment response has become more important due to increased use of eye-sparing treatments. We evaluated the relation between DCE-MR imaging and histopathologic parameters to determine the value of DCE-MR imaging in assessing tumor angiogenesis and prognostic features., Materials and Methods: Fifteen consecutive patients with retinoblastoma (mean age, 24 months; range, 2-70 months) undergoing enucleation as the primary treatment (15 eyes) were scanned at 1.5T by using dedicated surface coils. Pretreatment DCE-MR imaging of the most affected eye was evaluated by 2 observers by using curve-pattern analysis, with the first 5 minutes of each curve and the full time-series described as κ(5min) and κ(17min), respectively. Assessed histopathologic and immunologic parameters included optic nerve invasion, choroid invasion, MVD, tumor necrosis, and expression of VEGF and Flt-1., Results: The median value of κ(5min) was 1.28 (range, 0.87-2.07) and correlated positively with MVD (P = .008). The median value of κ(17min) was 1.33 (range, 0.35-3.08) and correlated negatively with tumor necrosis (P = .002). Other histopathologic and immunohistopathologic parameters did not correlate with DCE-MR imaging parameters. Interobserver agreement was 0.53 for κ(5min) and 0.91 for κ(17min)., Conclusions: In retinoblastoma, the early phase of the DCE time curve positively correlates with MVD, while the presence of late enhancement is correlated with necrosis. Thus, the potential for DCE-MR imaging to noninvasively assess tumor angiogenesis and necrosis in retinoblastoma is promising and warrants further investigation.

Published
2012
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36. A study of the brain's resting state based on alpha band power, heart rate and fMRI.

Author

de Munck JC, Gonçalves SI, Faes TJ, Kuijer JP, Pouwels PJ, Heethaar RM, and Lopes da Silva FH

Subjects
Adult, Computer Simulation, Female, Humans, Male, Alpha Rhythm methods, Brain physiology, Heart Rate physiology, Magnetic Resonance Imaging methods, Models, Cardiovascular, Models, Neurological, Rest physiology
Abstract

Considering that there are several theoretical reasons why fMRI data is correlated to variations in heart rate, these correlations are explored using experimental resting state data. In particular, the possibility is discussed that the "default network", being a brain area that deactivates during non-specific general tasks, is a hemodynamic effect caused by heart rate variations. Of fifteen healthy controls ECG, EEG and fMRI were co-registered. Slice time dependent heart rate regressors were derived from the ECG data and correlated to fMRI using a linear correlation analysis where the impulse response is estimated from the data. It was found that in most subjects substantial correlations between heart rate variations and fMRI exist, both within the brain and at the ventricles. The brain areas with high correlation to heart rate are different from the "default network" and the response functions deviate from the canonical hemodynamic response function. Furthermore, a general negative correlation was found between heart beat intervals (reverse of heart rate) and alpha power. We interpret this finding by assuming that subject's state varies between drowsiness and wakefulness. Finally, given this large correlation, we re-examined the contribution of heart rate variations to earlier reported fMRI/alpha band correlations, by adding heart rate regressors as confounders. It was found that inclusion of these confounders most often had a negligible effect. From its strong correlation to alpha power, we conclude that the heart rate variations contain important physiological information about subject's resting state. However, it does not provide a full explanation of the behaviour of the "default network". Its application as confounder in fMRI experiments is a relatively small computational effort, but may have a substantial impact in paradigms where heart rate is controlled by the stimulus.

Published
2008
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37. Cerebral blood flow by using pulsed arterial spin-labeling in elderly subjects with white matter hyperintensities.

Author

Bastos-Leite AJ, Kuijer JP, Rombouts SA, Sanz-Arigita E, van Straaten EC, Gouw AA, van der Flier WM, Scheltens P, and Barkhof F

Subjects
Aged, Aged, 80 and over, Blood Flow Velocity physiology, Brain blood supply, Female, Humans, Male, Microcirculation pathology, Regional Blood Flow physiology, Sensitivity and Specificity, Brain Ischemia diagnosis, Image Processing, Computer-Assisted methods, Leukoaraiosis diagnosis, Magnetic Resonance Angiography methods, Magnetic Resonance Imaging methods
Abstract

Background and Purpose: On MR imaging, white matter hyperintensities (WMH) on T2-weighted images are generally considered as a surrogate marker of ischemic small vessel disease in elderly subjects. Pulsed arterial spin-labeling (PASL) is a noninvasive MR perfusion-weighted technique. We hypothesized that elderly subjects with diffuse confluent WMH should have lower cerebral blood flow (CBF) measurements than subjects with punctiform or beginning confluent WMH., Materials and Methods: MR images of 21 subjects (13 women; mean age, 76 years; SD, 5), stratified for the degree of WMH, from a single center within the multinational Leukoaraiosis and Disability (LADIS) study, were investigated. CBF images were obtained by means of quantitative imaging of perfusion by using a single-subtraction second version, with thin-section TI periodic saturation PASL. Values of cortical gray matter, subcortical (including white matter and deep gray matter), and global CBF were calculated. CBF measurements of subjects with diffuse confluent WMH (n = 7) were compared with those of subjects with punctiform or beginning confluent WMH (n = 14)., Results: Subjects with diffuse confluent WMH were found to have approximately 20% lower mean global CBF (43.5 mL/100 mL/min; SD, 6.3) than subjects with punctiform or beginning confluent WMH (57.9 mL/100 mL/min; SD, 8.6; P < .01), as well as approximately 20% lower mean subcortical (P < .01) and cortical gray matter CBF (P < .05)., Conclusion: PASL revealed a significant reduction of CBF measurements in elderly subjects with diffuse confluent WMH.

Published
2008
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38. Artifact removal in co-registered EEG/fMRI by selective average subtraction.

Author

Gonçalves SI, Pouwels PJ, Kuijer JP, Heethaar RM, and de Munck JC

Subjects
Adolescent, Adult, Brain blood supply, Brain physiology, Carbamide Peroxide, Drug Combinations, Evoked Potentials, Visual physiology, Female, Humans, Image Processing, Computer-Assisted methods, Male, Peroxides blood, Phantoms, Imaging, Photic Stimulation methods, Principal Component Analysis, Spectrum Analysis, Urea analogs & derivatives, Urea blood, Artifacts, Electroencephalography, Magnetic Resonance Imaging, Subtraction Technique
Abstract

Objective: Co-registration of EEG (electroencephalogram) and fMRI (functional magnetic resonance imaging) remains a challenge due to the large artifacts induced on the EEG by the MR (magnetic resonance) sequence magnetic fields. Thus, we present an algorithm, based on the average-subtraction method, which is able to correct EEG data for gradient and pulse artifacts., Methods: MR sequence timing parameters are estimated from the EEG data and both slice and volume artifact templates are subtracted from the data. A clustering algorithm is proposed to account for the variability of the pulse artifact., Results: The algorithm is able to keep the spontaneous EEG as well as visual evoked potentials (VEPs), while removing gradient and pulse artifacts with only a subtraction of selectively averaged data. In the frequency domain, the artifact frequencies are strongly attenuated. Estimated MR sequence time parameters showed that the correction is extremely sensitive to the slice time value. Pulse artifact clustering showed that most of the variability is due to the time jitter of the pulse artifact markers., Conclusions: Selective subtraction of averages in combination with proper time alignment is enough to remove most of the MR-induced artifacts., Significance: Clean EEG can be obtained from raw signals that are corrupted by MR-induced artifacts during simultaneous EEG-fMRI scanning without using dedicated hardware to synchronize EEG and fMRI clocks.

Published
2007
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39. The hemodynamic response of the alpha rhythm: an EEG/fMRI study.

Author

de Munck JC, Gonçalves SI, Huijboom L, Kuijer JP, Pouwels PJ, Heethaar RM, and Lopes da Silva FH

Subjects
Adult, Blood Flow Velocity physiology, Female, Humans, Male, Reproducibility of Results, Sensitivity and Specificity, Alpha Rhythm methods, Brain blood supply, Brain physiology, Brain Mapping methods, Cerebrovascular Circulation physiology, Magnetic Resonance Imaging methods
Abstract

EEG was recorded during fMRI scanning of 16 normal controls in resting condition with eyes closed. Time variations of the occipital alpha band amplitudes were correlated to the fMRI signal variations to obtain insight into the hemodynamic correlates of the EEG alpha activity. Contrary to earlier studies, no a priori assumptions were made on the expected shape of the alpha band response function (ARF). The ARF of different brain regions and subjects were explored and compared. It was found that: (1) the ARF of the thalamus is mainly positive. (2) The ARFs at the occipital and left and right parietal points are similar in amplitude and timing. (3) The peak time of the thalamus is a few seconds earlier than that of occipital and parietal cortex. (4) No systematic BOLD activity was found preceding the alpha band activity, although in the two subjects with the strongest alpha band power such correlation was present. (5) There is a strong and immediate positive correlation at the eyeball, and a strong negative correlation at the back of the eye. Furthermore, it was found that in one subject the cortical ARF was positive, contrary to the other subjects. Finally, a cluster analysis of the observed ARF, in combination with a Modulated Sine Model (MSM) fit to the estimated ARF, revealed that within the cortex the ARF peak time shows a spatial pattern that may be interpreted as a traveling wave. The spatial pattern of alpha band response function represents the combined effect of local differences in electrical alpha band activity and local differences in the hemodynamic response function (HRF) onto these electrical activities. To disentangle the contributions of both factors, more advanced integration of EEG inverse modeling and hemodynamic response modeling is required in future studies.

Published
2007
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40. Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: inter-subject variability.

Author

Gonçalves SI, de Munck JC, Pouwels PJ, Schoonhoven R, Kuijer JP, Maurits NM, Hoogduin JM, Van Someren EJ, Heethaar RM, and Lopes da Silva FH

Subjects
Adult, Brain Mapping, Cerebral Cortex blood supply, Female, Humans, Male, Reference Standards, Sensitivity and Specificity, Statistics as Topic, Thalamus blood supply, Thalamus physiology, Alpha Rhythm, Cerebral Cortex physiology, Electroencephalography, Image Enhancement, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Oxygen blood, Signal Processing, Computer-Assisted
Abstract

Simultaneous recording of electroencephalogram/functional magnetic resonance images (EEG/fMRI) was applied to identify blood oxygenation level-dependent (BOLD) changes associated with spontaneous variations of the alpha rhythm, which is considered the hallmark of the brain resting state. The analysis was focused on inter-subject variability associated with the resting state. Data from 7 normal subjects are presented. Confirming earlier findings, three subjects showed a negative correlation between the BOLD signal and the average power time series within the alpha band (8--12 Hz) in extensive areas of the occipital, parietal and frontal lobes. In small thalamic areas, the BOLD signal was positively correlated with the alpha power. For subjects 3 and 4, who displayed two different states during the data acquisition time, it was shown that the corresponding correlation patterns were different, thus demonstrating the state dependency of the results. In subject 5, the changes in BOLD were observed mainly in the frontal and temporal lobes. Subject 6 only showed positive correlations, thus contradicting the negative BOLD alpha power cortical correlations that were found in most subjects. Results suggest that the resting state varies over subjects and, sometimes, even within one subject. As the resting state plays an important role in many fMRI experiments, the inter-subject variability of this state should be addressed when comparing fMRI results from different subjects.

Published
2006
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41. Regional timing of myocardial shortening is related to prestretch from atrial contraction: assessment by high temporal resolution MRI tagging in humans.

Author

Zwanenburg JJ, Götte MJ, Kuijer JP, Hofman MB, Knaapen P, Heethaar RM, van Rossum AC, and Marcus JT

Subjects
Adult, Female, Humans, Male, Middle Aged, Systole physiology, Atrial Function physiology, Magnetic Resonance Imaging, Myocardial Contraction physiology, Ventricular Function, Left physiology
Abstract

Earlier studies have shown substantial nonuniformity in normal left ventricular (LV) myocardial function concerning both the degree of shortening and timing of shortening. We hypothesized that nonuniform LV function may be related to nonuniform prestretch induced by atrial contraction. Eleven healthy human subjects were studied using MRI myocardial tagging and strain analysis. The amount of circumferential prestretch was assessed in 30 LV segments. Prestretch was defined as the difference in strain between end diastole (at ECG R wave) and diastasis. Furthermore, both the degree of shortening (quantified as peak circumferential shortening, peak systolic shortening rate, and amount of postsystolic shortening) and timing of shortening (quantified as the onset time of shortening and time to peak shortening) were assessed. LV prestretch was found to be nonuniform, with the highest values in the lateral wall. The amount of segmental prestretch correlated significantly with peak shortening (r = 0.79), peak shortening rate (r = 0.50), amount of postsystolic shortening (r = 0.67), onset time of shortening (r = -0.57), and time to peak shortening (r = 0.71) (P < 0.001 for each of these relations). These relations may be explained by regional differences in wall stress or by a regional Frank-Starling effect. The correlation between timing of shortening and prestretch demonstrates that mechanical timing is not determined by electrical phenomena alone. In conclusion, regional variation in LV function correlates with the nonuniform prestretch from atrial contraction.

Published
2005
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42. Timing of cardiac contraction in humans mapped by high-temporal-resolution MRI tagging: early onset and late peak of shortening in lateral wall.

Author

Zwanenburg JJ, Götte MJ, Kuijer JP, Heethaar RM, van Rossum AC, and Marcus JT

Subjects
Adult, Aortic Valve physiology, Electrocardiography, Female, Humans, Male, Middle Aged, Reference Values, Systole, Time Factors, Heart physiology, Magnetic Resonance Imaging methods, Myocardial Contraction physiology
Abstract

Mechanical asynchrony is an important parameter in predicting the response to cardiac resynchronization therapy, but detailed knowledge of cardiac contraction timing in healthy persons is scarce. In this work, timing of cardiac contraction was mapped in 17 healthy subjects with high-temporal-resolution (14 ms) MRI myocardial tagging and strain analysis. Both the onset time of circumferential shortening (T(onset)) in early systole and the time of peak circumferential shortening (T(peak)) at end systole were determined. The onset of shortening width (time needed for 20-90% of the left ventricle to start shortening) was small (35 +/- 9 ms). A distinct spatial pattern for T(onset) was found, with earliest onset in the lateral wall and latest onset in the septum (P = 0.001). Compared with T(onset), T(peak) had a larger width (121 +/- 22 ms) and an opposite spatial pattern, with peak shortening occurring earlier in the septum than in the lateral wall (P < 0.001). Postsystolic shortening (T(peak) later than aortic valve closure; P < 0.05) was observed in 13 of the 30 cardiac segments, mainly in the lateral and basal segments. Shortening in these segments continued 58 +/- 14 ms after aortic valve closure, during which circumferential shortening increased from 16.9 +/- 1.2% to 20.0 +/- 1.5%. Maps of the timing of contraction in normal subjects may serve as a reference in detecting mechanical asynchrony due to intraventricular conduction defects or ischemia.

Published
2004
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43. Interindividual differences of medial temporal lobe activation during encoding in an elderly population studied by fMRI.

Author

Vandenbroucke MW, Goekoop R, Duschek EJ, Netelenbos JC, Kuijer JP, Barkhof F, Scheltens P, and Rombouts SA

Subjects
Aged, Attention physiology, Brain Mapping, Dominance, Cerebral physiology, Face, Female, Humans, Male, Middle Aged, Reference Values, Aging physiology, Image Processing, Computer-Assisted, Individuality, Magnetic Resonance Imaging, Memory, Short-Term physiology, Pattern Recognition, Visual physiology, Temporal Lobe physiology
Abstract

Functional MRI (fMRI) is used to study medial temporal lobe (MTL) activation during encoding of new information into memory. In most studies, fMRI data of different subjects are averaged in standard coordinate space. However, interindividual differences in activation can be extensive, reflecting functional heterogeneity. Further, anatomical differences in brain structure cause additional variance and loss of registration accuracy. Such differences in structural and functional MTL characteristics may interfere with the efficiency of averaging data across subjects, and may become more significant with aging and dementia. The current study concerns the analysis of individual differences in MTL activation associated with episodic encoding.Twenty-nine healthy elderly men between 60 and 70 years old performed a simple face encoding task during fMRI scanning. Individual data were analyzed in native space, and compared to the group average in standard space (Talairach and Tournoux).MTL volumes between subjects varied between 6.34 and 11.27 cm(3), and had considerable variation when mapped to standard space. Eighteen of the 29 subjects showed MTL activity and activation patterns varied both in location and size (ranging from 0.11 to 1.78 cm(3)), with the strongest activation in the left posterior part of the MTL. In standard space, no region was significantly activated on a group level at a comparable alpha level. We conclude that while the majority of elderly subjects show MTL activation during episodic encoding of faces, there is considerable structural and functional variability between subjects. Group analysis in standard space may not be appropriate for studies of a complex structure such as the MTL, particularly not in aging and dementia.

Published
2004
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44. Identifying confounds to increase specificity during a "no task condition". Evidence for hippocampal connectivity using fMRI.

Author

Rombouts SA, Stam CJ, Kuijer JP, Scheltens P, and Barkhof F

Subjects
Adult, Algorithms, Brain Mapping, Female, Functional Laterality physiology, Humans, Image Interpretation, Computer-Assisted, Linear Models, Magnetic Resonance Imaging, Male, Nerve Net physiology, Oxygen blood, Hippocampus physiology, Neural Pathways physiology
Abstract

Functional MRI can be applied to study connectivity in the brain during a "no task condition." This study focuses on applying a multiple linear regression analysis to identify spurious connectivity caused by confounding factors such as physiologic noise and to separate these from hippocampal connectivity caused by the blood oxygen level dependent (BOLD) signal during a no-task condition. Regressors of interest (hippocampal time courses) as well as regressors of no interest (respiratory signal and cerebrospinal fluid), were included in the analysis, and each yielded a connectivity map. This method was applied at high sampling rate (limited volume, proper physiologic noise sampling), low sampling rate (whole brain scans possible), and at high and low spatial resolution in five healthy control subjects. Regressors of no interest showed specific connectivity patterns, different from hippocampal regressors. The latter showed connectivity between left and right hippocampus. The current study shows successful application of a multiple regression analysis to study connectivity between left and right hippocampus. Both maps of hippocampal connectivity caused by BOLD signal and connectivity caused by spurious signals could be identified.

Published
2003
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