Characteristics of an ideal psychotherapist for eating-disordered patients.

Psychotherapy is an essential component of the treatment of eating disorders. A fully competent ideal psychotherapist needs a body of knowledge; personality characteristics of nonpossessive warmth and perseverance; training in scientific, manual-based psychotherapy; and experience, including supervision. The formal discipline of the therapist is less important than are these qualifications. Ideal means fully competent, not perfect. An ideal therapist is a crucial component in the treatment of eating-disordered patients.

Caudate size in first-episode neuroleptic-naive schizophrenic patients measured using an artificial neural network.

BACKGROUND: Structural brain imaging studies have demonstrated an increase in caudate volume in schizophrenic patients medicated with typical neuroleptics and a volume decrease following treatment with atypical neuroleptics. The measurement of striatal volume in patients who have never been treated with neuroleptics may indicate whether these changes are superimposed on intrinsic basal ganglia pathology in schizophrenia or are solely neuroleptic-induced. METHODS: We studied 36 first-episode, neuroleptic-naive schizophrenic patients and 43 control subjects using an artificial neural network (ANN) to identify and measure the caudate nucleus. The resulting volumes were analyzed using an ANCOVA controlling for intracranial volume, age, gender, and socioeconomic status. RESULTS: The mean volume difference between the caudate nuclei of patients and control subjects was .297 mL, the caudate nuclei of the patients being smaller than those of controls. When we covaried for intracranial volume, this was a statistically significant difference in caudate volume (n = 79; df = 1,75; F = 4.18; p > .04). CONCLUSIONS: Caudate nuclei of neuroleptic naive schizophrenic patients are significantly smaller than those of controls. This suggests that patients suffering from schizophrenia may have intrinsic pathology of the caudate nucleus, in addition to the pathology observed as a consequence of chronic neuroleptic treatment.

Change in basal ganglia volume over 2 years in patients with schizophrenia: typical versus atypical neuroleptics.

OBJECTIVE: For many years, it has been assumed that medications affect brain chemistry and physiology but not structure. Recent reports suggest that neuroleptic medication changes basal ganglia volume. To explore this possibility, the authors assessed for basal ganglia volume change in individuals who had their basal ganglia structures delineated and measured on magnetic resonance scans at the beginning and end of a 2-year period and who received neuroleptic medication during this time. METHOD: The basal ganglia volumes of 23 male patients with schizophrenia spectrum disorders were measured from manual traces delineating the caudate and lenticular nucleus on magnetic resonance images at admission and 2 years later. Patients' neuroleptic exposure was calculated over the 2 years by using a dose-year formula. RESULTS: During the 2-year period, mean basal ganglia volume of patients receiving predominantly typical neuroleptics increased, while the opposite was observed for patients receiving mostly atypical neuroleptics. Correlation analysis for the entire group showed a positive relationship between the 2-year exposure to typical neuroleptic medication and change in basal ganglia volume and the reverse for exposure to atypical neuroleptics. CONCLUSIONS: In this group, basal ganglia volume increased following exposure to typical neuroleptics and decreased following exposure to atypical neuroleptics.

Measurement of brain structures with artificial neural networks: two- and three-dimensional applications.

PURPOSE: To evaluate the ability of an artificial neural network (ANN) to identify brain structures. This ANN was applied to postprocessed magnetic resonance (MR) images to segment various brain structures in both two- and three-dimensional applications. MATERIALS AND METHODS: An ANN was designed that learned from experience to define the corpus callosum, whole brain, caudate, and putamen. Manual segmentation was used as a training set for the ANN. The ANN was trained on two-thirds of the manually segmented images and was tested on the remaining one-third. The reliability of the ANN was compared against manual segmentations by two technicians. RESULTS: The ANN was able to identify the brain structures as readily and as well as did the two technicians. Reliability of the ANN compared with the technicians was 0.96 for the corpus callosum, 0.95 for the whole brain, 0.86 (right) and 0.93 (left) for the caudate, and 0.71 (right) and 0.88 (left) for the putamen. CONCLUSION: The ANN was able to identify the structures used in this study as well as did the two technicians. The ANN could do this much more rapidly and without rater drift. Several other cortical and subcortical structures could also be readily identified with this method.