The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability
Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies frequently applied the spatial normalization on fMRI time series before the calculation of temporal features (here referred to as “Prenorm”). We hypothesized that calculating the rs-fMRI features, for example, functional...
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| Format: | Article |
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Frontiers Media S.A.
2019-11-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2019.01249/full |
| _version_ | 1819160291160621056 |
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| author | Zhao Qing Zhao Qing Xin Zhang Meiping Ye Sichu Wu Xin Wang Zuzana Nedelska Zuzana Nedelska Jakub Hort Jakub Hort Bin Zhu Bing Zhang Bing Zhang |
| author_facet | Zhao Qing Zhao Qing Xin Zhang Meiping Ye Sichu Wu Xin Wang Zuzana Nedelska Zuzana Nedelska Jakub Hort Jakub Hort Bin Zhu Bing Zhang Bing Zhang |
| author_sort | Zhao Qing |
| collection | DOAJ |
| description | Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies frequently applied the spatial normalization on fMRI time series before the calculation of temporal features (here referred to as “Prenorm”). We hypothesized that calculating the rs-fMRI features, for example, functional connectivity (FC), regional homogeneity (ReHo), or amplitude of low-frequency fluctuation (ALFF) in individual space, before the spatial normalization (referred to as “Postnorm”) can be an improvement to avoid artifacts and increase the results’ reliability. We utilized two datasets: (1) simulated images where temporal signal-to-noise ratio (tSNR) is kept a constant and (2) an empirical fMRI dataset with 50 healthy young subjects. For simulated images, the tSNR is constant as generated in individual space but increased after Prenorm and intersubject variability of tSNR was induced. In contrast, tSNR was kept constant after Postnorm. Consistently, for empirical images, higher tSNR, ReHo, and FC (default mode network, seed in precuneus) and lower ALFF were found after Prenorm compared to those of Postnorm. Coefficient of variability of tSNR and ALFF was higher after Prenorm compared to those of Postnorm. Moreover, the significant correlation was found between simulated tSNR after Prenorm and empirical tSNR, ALFF, and ReHo after Prenorm, indicating algorithmic variation in empirical rs-fMRI features. Furthermore, comparing to Prenorm, ALFF and ReHo showed higher intraclass correlation coefficients between two serial scans after Postnorm. Our results indicated that Prenorm may induce algorithmic intersubject variability on tSNR and reduce its reliability, which also significantly affected ALFF and ReHo. We suggest using Postnorm instead of Prenorm for future rs-fMRI studies using ALFF/ReHo. |
| first_indexed | 2024-12-22T16:54:07Z |
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| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-22T16:54:07Z |
| publishDate | 2019-11-01 |
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| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-3f0f09cf9f26400f8598c8e54548fb962022-12-21T18:19:30ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2019-11-011310.3389/fnins.2019.01249470768The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the ReliabilityZhao Qing0Zhao Qing1Xin Zhang2Meiping Ye3Sichu Wu4Xin Wang5Zuzana Nedelska6Zuzana Nedelska7Jakub Hort8Jakub Hort9Bin Zhu10Bing Zhang11Bing Zhang12Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaInstitute for Brain Sciences, Nanjing University, Nanjing, ChinaDepartment of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaInternational Clinical Research Center, St. Anne’s University Hospital Brno, Brno, CzechiaMemory Clinic, Department of Neurology, Second Faculty of Medicine Charles University and Motol University Hospital, Prague, CzechiaInternational Clinical Research Center, St. Anne’s University Hospital Brno, Brno, CzechiaMemory Clinic, Department of Neurology, Second Faculty of Medicine Charles University and Motol University Hospital, Prague, CzechiaDepartment of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, ChinaInstitute for Brain Sciences, Nanjing University, Nanjing, ChinaPrevious resting-state functional magnetic resonance imaging (rs-fMRI) studies frequently applied the spatial normalization on fMRI time series before the calculation of temporal features (here referred to as “Prenorm”). We hypothesized that calculating the rs-fMRI features, for example, functional connectivity (FC), regional homogeneity (ReHo), or amplitude of low-frequency fluctuation (ALFF) in individual space, before the spatial normalization (referred to as “Postnorm”) can be an improvement to avoid artifacts and increase the results’ reliability. We utilized two datasets: (1) simulated images where temporal signal-to-noise ratio (tSNR) is kept a constant and (2) an empirical fMRI dataset with 50 healthy young subjects. For simulated images, the tSNR is constant as generated in individual space but increased after Prenorm and intersubject variability of tSNR was induced. In contrast, tSNR was kept constant after Postnorm. Consistently, for empirical images, higher tSNR, ReHo, and FC (default mode network, seed in precuneus) and lower ALFF were found after Prenorm compared to those of Postnorm. Coefficient of variability of tSNR and ALFF was higher after Prenorm compared to those of Postnorm. Moreover, the significant correlation was found between simulated tSNR after Prenorm and empirical tSNR, ALFF, and ReHo after Prenorm, indicating algorithmic variation in empirical rs-fMRI features. Furthermore, comparing to Prenorm, ALFF and ReHo showed higher intraclass correlation coefficients between two serial scans after Postnorm. Our results indicated that Prenorm may induce algorithmic intersubject variability on tSNR and reduce its reliability, which also significantly affected ALFF and ReHo. We suggest using Postnorm instead of Prenorm for future rs-fMRI studies using ALFF/ReHo.https://www.frontiersin.org/article/10.3389/fnins.2019.01249/fullspatial normalizationresting-state fMRIfMRI methodsreliabilityfMRI preprocessing |
| spellingShingle | Zhao Qing Zhao Qing Xin Zhang Meiping Ye Sichu Wu Xin Wang Zuzana Nedelska Zuzana Nedelska Jakub Hort Jakub Hort Bin Zhu Bing Zhang Bing Zhang The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability Frontiers in Neuroscience spatial normalization resting-state fMRI fMRI methods reliability fMRI preprocessing |
| title | The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability |
| title_full | The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability |
| title_fullStr | The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability |
| title_full_unstemmed | The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability |
| title_short | The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May Reduce the Reliability |
| title_sort | impact of spatial normalization strategies on the temporal features of the resting state functional mri spatial normalization before rs fmri features calculation may reduce the reliability |
| topic | spatial normalization resting-state fMRI fMRI methods reliability fMRI preprocessing |
| url | https://www.frontiersin.org/article/10.3389/fnins.2019.01249/full |
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