Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p &lt; 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.</p

Investigations into the Early Life-history of Naturally Produced Spring Chinook Salmon and Summer Steelhead in the Grande Ronde River Basin, Annual Report 2001.

We determined migration timing and abundance of juvenile spring chinook salmon Oncorhynchus tshawytscha and juvenile steelhead/rainbow trout Oncorhynchus mykiss using rotary screw traps on four streams in the Grande Ronde River basin during the 2001 migratory year (MY 2001) from 1 July 2000 through 30 June 2001. Based on migration timing and abundance, two distinct life-history strategies of juvenile spring chinook and O. mykiss could be distinguished. An 'early' migrant group left upper rearing areas from 1 July 2000 through 29 January 2001 with a peak in the fall. A 'late' migrant group descended from upper rearing areas from 30 January 2001 through 30 June 2001 with a peak in the spring. The migrant population of juvenile spring chinook salmon in the upper Grande Ronde River in MY 2001 was very low in comparison to previous migratory years. We estimated 51 juvenile spring chinook migrated out of upper rearing areas with approximately 12% of the migrant population leaving as early migrants to overwinter downstream. In the same migratory year, we estimated 16,067 O. mykiss migrants left upper rearing areas with approximately 4% of these fish descending the upper Grande Ronde River as early migrants. At the Catherine Creek trap, we estimated 21,937 juvenile spring chinook migrants in MY 2001. Of these migrants, 87% left upper rearing areas early to overwinter downstream. We also estimated 20,586 O. mykiss migrants in Catherine Creek with 44% leaving upper rearing areas early to overwinter downstream. At the Lostine River trap, we estimated 13,610 juvenile spring chinook migrated out of upper rearing areas with approximately 77% migrating early. We estimated 16,690 O. mykiss migrated out of the Lostine River with approximately 46% descending the river as early migrants. At the Minam River trap, we estimated 28,209 juvenile spring chinook migrated out of the river with 36% migrating early. During the same period, we estimated 28,113 O. mykiss with approximately 14% of these fish leaving as early migrants. Juvenile spring chinook salmon PIT-tagged at trap sites in the fall and in upper rearing areas during winter were used to compare migration timing and survival to Lower Granite Dam of the early and late migrant groups. Juvenile spring chinook tagged on the upper Grande Ronde River were detected at Lower Granite Dam from 4 May to 20 May 2001, with a median passage date of 17 May. Too few fish were collected and tagged to conduct detection rate and survival comparisons between migrant groups. PIT-tagged salmon from Catherine Creek trap were detected at Lower Granite Dam from 27 April to 13 July 2001. Early migrants were detected significantly earlier (median = 10 May) than late migrants (median = 1 June). Also, early migrants from Catherine Creek were detected at a significantly higher rate than fish tagged in upper rearing areas in the winter, suggesting better survival for fish that migrated out of upper rearing areas in the fall. Juvenile spring chinook salmon from the Lostine River were detected at Lower Granite Dam from 2 April through 4 July 2001. Early migrants were detected significantly earlier (median = 27 April) than late migrants (median = 14 May). However, there was no difference in detection rates between early and late migrants. Survival probabilities showed similar patterns as dam detection rates. Juvenile spring chinook salmon from the Minam River were detected at Lower Granite Dam from 8 April through 18 August 2001. Early migrants were detected significantly earlier (median = 28 April) than late migrants (median = 14 May). Late migrants from the Minam River were tagged at the trap in the spring. Spring chinook salmon parr PIT-tagged in summer 2000 on Catherine Creek and the Imnaha, Lostine, and Minam rivers were detected at Lower Granite Dam over an 87 d period from 8 April to 3 July 2001. The migratory period of individual populations ranged from 51 d (Imnaha River) to 67 d (Catherine Creek) in length. Median dates of migration ranged from 30 April (Imnaha River) to 17 May (Catherine Creek). Detection rates differed between populations with Catherine Creek spring chinook salmon detected at the lowest rate (8.2%). Imnaha, Lostine, and Minam detection rates were not significantly different from each other. A similar pattern was seen for survival probabilities. Using mark-and-recapture and scale-aging techniques, we determined the population size and age-structure of spring chinook salmon parr in Catherine Creek and the Lostine River during the summer of 2001. In Catherine Creek, we estimated that 986 mature age-1 parr (precocious males) and 15,032 immature age-0 parr were present during August 2001. We estimated there were 7.5 mature male parr for every anadromous female spawner in Catherine Creek in 2001. We estimated 33,086 immature, age-0 parr inhabited the Lostine River in August 2001

Further investigation of green sturgeon (Acipenser medirostris) distinct population segment composition in non-natal estuaries and preliminary evidence of Columbia River spawning

Green sturgeon (Acipenser medirostris) is a highly migratory, marine oriented species that congregates in non-natal estuaries during summer and early fall. Individuals from the threatened Southern Distinct Population Segment (SDPS) and non-listed Northern Distinct Population Segment (NDPS) regularly co-occur in non-natal estuaries including the Columbia River estuary, Willapa Bay, and Grays Harbor in relative proportions not explained by abundance or distance from natal river. We used genetic markers to assign green sturgeon sampled in these estuaries from 2010 to 2012 to distinct population segments (DPS). We then examined interannual differences in DPS composition among estuaries. Fork length distributions were compared between SDPS and NDPS green sturgeon to determine whether size varied within and among DPSs and estuaries. The majority of green sturgeon sampled in the Columbia River estuary and Willapa Bay were assigned to the SDPS, while we assigned nearly even DPS proportions to our Grays Harbor samples. NDPS green sturgeon were significantly smaller than those originating from the SDPS within and among estuaries. We used these findings to develop several hypotheses about the mechanisms that may lead to specific patterns of non-natal estuary use. Genetic markers also assigned a single age-0 green sturgeon sampled in the Columbia River to the NDPS, although our analyses suggest that this individual’s parents may not have originated from known NDPS spawning populations. Because the Columbia River may serve as alternative spawning habitat for green sturgeon as climate change occurs, we recommend monitoring the Columbia River more closely for further evidence of green sturgeon spawning

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B 0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed