Frequency drift in MR spectroscopy at 3T

PURPOSE

Heating of gradient coils and passive shim components is a common cause of instability in the B0 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.

Unique prefrontal GABA and glutamate disturbances in co-occurring bipolar disorder and alcohol dependence

Bipolar disorder (BD) and alcohol dependence (AD) frequently co-occur, and co-occurring BD and AD are associated with devastating public health costs. Minimal neurobiological research exists to guide the development of effective treatments for this treatment-resistant population. We believe the present study represents the first investigation of prefrontal gamma-aminobutyric acid (GABA) and glutamate levels in co-occurring BD and current AD. The participants were 78 individuals who met DSM-IV criteria for BD I/II and current AD (n=20), BD I/II alone (n=19), current AD alone (n=20) or no diagnosis (n=19). The participants completed a baseline diagnostic visit, then returned approximately 4 days later for a two-dimensional J-resolved proton magnetic resonance spectroscopy (¹H-MRS) acquisition in dorsal anterior cingulate cortex (dACC). All participants were required to demonstrate ⩾1 week of abstinence from alcohol/drugs via serial biomarker testing before ¹H-MRS. A 2 × 2 factorial analysis of variance of cerebrospinal fluid (CSF)-corrected GABA/water concentrations demonstrated a significant BD × AD interaction (F=2.91, P<0.05), signifying uniquely low levels of GABA in BD+AD; this effect doubled when the sample was restricted to individuals who consumed alcohol within 2 weeks of ¹H-MRS. There were no overall effects of BD/AD on CSF-corrected glutamate/water levels. However, the BD × AD interaction, signifying uniquely low levels of glutamate in BD+AD, approached statistical significance (F=3.83, P=0.06) in individuals who consumed alcohol within 2 weeks of ¹H-MRS. The dACC GABA levels were significantly, negatively associated with Barratt Impulsiveness Scale (r=-0.28, P=0.02) and Obsessive Compulsive Drinking Scale (r=-0.35, P<0.01) scores. If replicated, these results may suggest that future treatment studies should preferentially evaluate therapeutics in BD+AD known to increase prefrontal GABA and glutamate levels.

Evidence for the continuous latent structure of mania and depression in out-patients with bipolar disorder: results from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD)

BACKGROUND

Evidence supporting the continuous latent structure of mood phenomena has not been incorporated into psychiatric diagnostic systems, in part because the evidence has been incomplete. For example, no studies have investigated the boundary between 'sick' and 'well' periods in individuals with bipolar disorder, despite agreement that characterization of mood disorders as having a discrete episodic course is inaccurate. The present study examined the validity of mood episode symptom thresholds in out-patients with bipolar disorder using multiple methodologies: taxometrics and information-theoretic latent distribution modeling (ITLDM), to evaluate the continuity/discontinuity of mood symptoms; and structural equation mixture modeling (SEMM), to evaluate the continuity/discontinuity of associations between mood symptoms and general functioning.

METHOD

A total of 3721 out-patients with bipolar disorder from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) were available for analysis. Data were collected at participants' baseline STEP-BD visit. Taxometric [maximum covariance/means above minus below a cut (MAXCOV/MAMBAC) with simulated comparison data], ITLDM and SEMM methods were applied twice, once to the Montgomery-Åsberg Depression Rating Scale and again to the Young Mania Rating Scale.

RESULTS

Taxometric results unequivocally supported a continuous interpretation of the data. ITLDM results favored many valued 'discrete metrical' models, suggesting that mood symptoms have continuous, but potentially non-normally distributed, latent structures in out-patients with bipolar disorder. Finally, SEMM results demonstrated that latent associations between mood symptoms and general functioning were linear.

CONCLUSIONS

Results from the present study argue against the validity of DSM mood episode thresholds and argue for a graded continuum of care of bipolar symptom management.

The structure of depression, anxiety and somatic symptoms in primary care

BACKGROUND

Observed co-morbidity among the mood and anxiety disorders has led to the development of increasingly sophisticated dimensional models to represent the common and unique features of these disorders. Patients often present to primary care settings with a complex mixture of anxiety, depression and somatic symptoms. However, relatively little is known about how somatic symptoms fit into existing dimensional models.

METHOD

We examined the structure of 91 anxiety, depression and somatic symptoms in a sample of 5433 primary care patients drawn from 14 countries. One-, two- and three-factor lower-order models were considered; higher-order and hierarchical variants were studied for the best-fitting lower-order model.

RESULTS

A hierarchical, bifactor model with all symptoms loading simultaneously on a general factor, along with one of three specific anxiety, depression and somatic factors, was the best-fitting model. The general factor accounted for the bulk of symptom variance and was associated with psychosocial dysfunction. Specific depression and somatic symptom factors accounted for meaningful incremental variance in diagnosis and dysfunction, whereas anxiety variance was associated primarily with the general factor.

CONCLUSIONS

The results (a) are consistent with previous studies showing the presence and importance of a broad internalizing or distress factor linking diverse emotional disorders, and (b) extend the bounds of internalizing to include somatic complaints with non-physical etiologies.

Evidence for the continuous latent structure of mania in the Epidemiologic Catchment Area from multiple latent structure and construct validation methodologies

BACKGROUND

Although psychiatric diagnostic systems have conceptualized mania as a discrete phenomenon, appropriate latent structure investigations testing this conceptualization are lacking. In contrast to these diagnostic systems, several influential theories of mania have suggested a continuous conceptualization. The present study examined whether mania has a continuous or discrete latent structure using a comprehensive approach including taxometric, information-theoretic latent distribution modeling (ITLDM) and predictive validity methodologies in the Epidemiologic Catchment Area (ECA) study.

METHOD

Eight dichotomous manic symptom items were submitted to a variety of latent structural analyses, including factor analyses, taxometric procedures and ITLDM, in 10105 ECA community participants. In addition, a variety of continuous and discrete models of mania were compared in terms of their relative abilities to predict outcomes (i.e. health service utilization, internalizing and externalizing disorders, and suicidal behavior).

RESULTS

Taxometric and ITLDM analyses consistently supported a continuous conceptualization of mania. In ITLDM analyses, a continuous model of mania demonstrated 6.52:1 odds over the best-fitting latent class model (LCM) of mania. Factor analyses suggested that the continuous structure of mania was best represented by a single latent factor. Predictive validity analyses demonstrated a consistent superior ability of continuous models of mania relative to discrete models.

CONCLUSIONS

The present study provided three independent lines of support for a continuous conceptualization of mania. The implications of a continuous model of mania are discussed.

A comparison of the predictive abilities of dimensional and categorical models of unipolar depression in the National Comorbidity Survey

BACKGROUND

Taxometric research on depression has yielded mixed results, with some studies supporting dimensional solutions and others supporting taxonic solutions. Although supplementary tests of construct validity might clarify these mixed findings, to date such analyses have not been reported. The present study represents a follow-up to our previous taxometric study of depression designed to evaluate the relative predictive validities of dimensional and categorical models of depression.

METHOD

Two sets of dimensional and categorical models of depression were constructed from the depression items of the Composite International Diagnostic Interview: (1) empirically derived models obtained using latent structure analyses and (2) rationally selected models, including an additive depressive symptoms scale (dimensional) and DSM major depressive episodes (categorical). Both sets of dimensional and categorical models were compared in terms of their abilities to predict various clinically relevant outcomes (psychiatric diagnoses and impairment).

RESULTS

Factor analyses suggested a two-factor model ('cognitive-affective' and 'somatic' symptoms) and latent class analyses suggested a three-class model ('severe depression', 'moderate depression' and 'cognitive-affective distress'). In predictive analyses that simultaneously included dimensional and categorical models as predictors, the dimensional models remained significant unique predictors of outcomes while the categorical models did not.

CONCLUSIONS

Both dimensional models provided superior predictive validity relative to their categorical counterparts. These results provide construct validity evidence for the dimensional findings from our previous taxometric study and thus inspire confidence in dimensional conceptualizations of depression. It remains for future research to evaluate the construct validity of the taxonic solutions reported in the literature.