Decreased left temporal lobe volume of panic patients measured by magnetic resonance imaging

Reported neuroimaging studies have shown functional and morphological changes of temporal lobe structures in panic patients, but only one used a volumetric method. The aim of the present study was to determine the volume of temporal lobe structures in patients with panic disorder, measured by magnetic resonance imaging. Eleven panic patients and eleven controls matched for age, sex, handedness, socioeconomic status and years of education participated in the study. The mean volume of the left temporal lobe of panic patients was 9% smaller than that of controls (t21 = 2.37, P = 0.028). In addition, there was a trend (P values between 0.05 and 0.10) to smaller volumes of the right temporal lobe (7%, t21 = 1.99, P = 0.06), right amygdala (8%, t21 = 1.83, P = 0.08), left amygdala (5%, t21 = 1.78, P = 0.09) and left hippocampus (9%, t21 = 1.93, P = 0.07) in panic patients compared to controls. There was a positive correlation between left hippocampal volume and duration of panic disorder (r = 0.67, P = 0.025), with recent cases showing more reduction than older cases. The present results show that panic patients have a decreased volume of the left temporal lobe and indicate the presence of volumetric abnormalities of temporal lobe structures.

Abnormalities of hippocampal signal intensity in patients with familial mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is associated with hippocampal atrophy and hippocampal signal abnormalities. In our series of familial MTLE (FMTLE), we found a high proportion of hippocampal abnormalities. To quantify signal abnormalities in patients with FMTLE we studied 152 individuals (46 of them asymptomatic) with FMTLE. We used NIH-Image® for volumetry and signal quantification in coronal T1 inversion recovery and T2 for all cross-sections of the hippocampus. Values diverging by 2 or more SD from the control mean were considered abnormal. T2 hippocampal signal abnormalities were found in 52% of all individuals: 54% of affected subjects and 48% of asymptomatic subjects. T1 hippocampal signal changes were found in 34% of all individuals: 42.5% of affected subjects and 15% of asymptomatic subjects. Analysis of the hippocampal head (first three slices) revealed T2 abnormalities in 73% of all individuals (74% of affected subjects and 72% of asymptomatic subjects) and T1 abnormalities in 59% (67% of affected subjects and 41% of asymptomatic subjects). Affected individuals had smaller volumes than controls (P < 0.0001). There was no difference in hippocampal volumes between asymptomatic subjects and controls, although 39% of asymptomatic patients had hippocampal atrophy. Patients with an abnormal hippocampal signal (133 individuals) had smaller ipsilateral volume, but no linear correlation could be determined. Hippocampal signal abnormalities in FMTLE were more frequently found in the hippocampal head in both affected and asymptomatic family members, including those with normal volumes. These results indicate that subtle abnormalities leading to an abnormal hippocampal signal in FMTLE are not necessarily related to seizures and may be determined by genetic factors.

The importance of accurate anatomic assessment for the volumetric analysis of the amygdala

There is a wide range of values reported in volumetric studies of the amygdala. The use of single plane thick magnetic resonance imaging (MRI) may prevent the correct visualization of anatomic landmarks and yield imprecise results. To assess whether there is a difference between volumetric analysis of the amygdala performed with single plane MRI 3-mm slices and with multiplanar analysis of MRI 1-mm slices, we studied healthy subjects and patients with temporal lobe epilepsy. We performed manual delineation of the amygdala on T1-weighted inversion recovery, 3-mm coronal slices and manual delineation of the amygdala on three-dimensional volumetric T1-weighted images with 1-mm slice thickness. The data were compared using a dependent t-test. There was a significant difference between the volumes obtained by the coronal plane-based measurements and the volumes obtained by three-dimensional analysis (P < 0.001). An incorrect estimate of the amygdala volume may preclude a correct analysis of the biological effects of alterations in amygdala volume. Three-dimensional analysis is preferred because it is based on more extensive anatomical assessment and the results are similar to those obtained in post-mortem studies.

Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains

The aim of the present study was to compare heart rate variability (HRV) at rest and during exercise using a temporal series obtained with the Polar S810i monitor and a signal from a LYNX® signal conditioner (BIO EMG 1000 model) with a channel configured for the acquisition of ECG signals. Fifteen healthy subjects aged 20.9 ± 1.4 years were analyzed. The subjects remained at rest for 20 min and performed exercise for another 20 min with the workload selected to achieve 60% of submaximal heart rate. RR series were obtained for each individual with a Polar S810i instrument and with an ECG analyzed with a biological signal conditioner. The HRV indices (rMSSD, pNN50, LFnu, HFnu, and LF/HF) were calculated after signal processing and analysis. The unpaired Student t-test and intraclass correlation coefficient were used for data analysis. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV at rest and during exercise. The intraclass correlation coefficient demonstrated satisfactory correlation between the values obtained by the devices at rest (pNN50 = 0.994; rMSSD = 0.995; LFnu = 0.978; HFnu = 0.978; LF/HF = 0.982) and during exercise (pNN50 = 0.869; rMSSD = 0.929; LFnu = 0.973; HFnu = 0.973; LF/HF = 0.942). The calculation of HRV values by means of temporal series obtained from the Polar S810i instrument appears to be as reliable as those obtained by processing the ECG signal captured with a signal conditioner.