Classification of small lesions on dynamic breast MRI: Integrating dimension reduction and out-of-sample extension into CADx methodology.

OBJECTIVE: While dimension reduction has been previously explored in computer aided diagnosis (CADx) as an alternative to feature selection, previous implementations of its integration into CADx do not ensure strict separation between training and test data required for the machine learning task. This compromises the integrity of the independent test set, which serves as the basis for evaluating classifier performance. METHODS AND MATERIALS: We propose, implement and evaluate an improved CADx methodology where strict separation is maintained. This is achieved by subjecting the training data alone to dimension reduction; the test data is subsequently processed with out-of-sample extension methods. Our approach is demonstrated in the research context of classifying small diagnostically challenging lesions annotated on dynamic breast magnetic resonance imaging (MRI) studies. The lesions were dynamically characterized through topological feature vectors derived from Minkowski functionals. These feature vectors were then subject to dimension reduction with different linear and non-linear algorithms applied in conjunction with out-of-sample extension techniques. This was followed by classification through supervised learning with support vector regression. Area under the receiver-operating characteristic curve (AUC) was evaluated as the metric of classifier performance. RESULTS: Of the feature vectors investigated, the best performance was observed with Minkowski functional 'perimeter' while comparable performance was observed with 'area'. Of the dimension reduction algorithms tested with 'perimeter', the best performance was observed with Sammon's mapping (0.84±0.10) while comparable performance was achieved with exploratory observation machine (0.82±0.09) and principal component analysis (0.80±0.10). CONCLUSIONS: The results reported in this study with the proposed CADx methodology present a significant improvement over previous results reported with such small lesions on dynamic breast MRI. In particular, non-linear algorithms for dimension reduction exhibited better classification performance than linear approaches, when integrated into our CADx methodology. We also note that while dimension reduction techniques may not necessarily provide an improvement in classification performance over feature selection, they do allow for a higher degree of feature compaction.

Classification of small lesions in dynamic breast MRI: Eliminating the need for precise lesion segmentation through spatio-temporal analysis of contrast enhancement over time.

Characterizing the dignity of breast lesions as benign or malignant is specifically difficult for small lesions; they don't exhibit typical characteristics of malignancy and are harder to segment since margins are harder to visualize. Previous attempts at using dynamic or morphologic criteria to classify small lesions (mean lesion diameter of about 1 cm) have not yielded satisfactory results. The goal of this work was to improve the classification performance in such small diagnostically challenging lesions while concurrently eliminating the need for precise lesion segmentation. To this end, we introduce a method for topological characterization of lesion enhancement patterns over time. Three Minkowski Functionals were extracted from all five post-contrast images of sixty annotated lesions on dynamic breast MRI exams. For each Minkowski Functional, topological features extracted from each post-contrast image of the lesions were combined into a high-dimensional texture feature vector. These feature vectors were classified in a machine learning task with support vector regression. For comparison, conventional Haralick texture features derived from gray-level co-occurrence matrices (GLCM) were also used. A new method for extracting thresholded GLCM features was also introduced and investigated here. The best classification performance was observed with Minkowski Functionals area and perimeter, thresholded GLCM features f8 and f9, and conventional GLCM features f4 and f6. However, both Minkowski Functionals and thresholded GLCM achieved such results without lesion segmentation while the performance of GLCM features significantly deteriorated when lesions were not segmented (p < 0.05). This suggests that such advanced spatio-temporal characterization can improve the classification performance achieved in such small lesions, while simultaneously eliminating the need for precise segmentation.

Classification of Small Lesions in Breast MRI: Evaluating The Role of Dynamically Extracted Texture Features Through Feature Selection.

Dynamic texture quantification, i.e., extracting texture features from the lesion enhancement pattern in all available post-contrast images, has not been evaluated in terms of its ability to classify small lesions. This study investigates the classification performance achieved with texture features extracted from all five post-contrast images of lesions (mean lesion diameter of 1.1 cm) annotated in dynamic breast magnetic resonance imaging exams. Sixty lesions are characterized dynamically using Haralick texture features. The texture features are then used in a classification task with support vector regression and a fuzzy k-nearest neighbor classifier; free parameters of these classifiers are optimized using random sub-sampling cross-validation. Classifier performance is determined through receiver-operator characteristic (ROC) analysis, specifically through computation of the area under the ROC curve (AUC). Mutual information is used to evaluate the contribution of texture features extracted from different post-contrast stages to classifier performance. Significant improvements (p < 0.05) are observed for six of the thirteen texture features when the lesion enhancement pattern is quantified using the proposed approach of dynamic texture quantification. The highest AUC value observed (0.82) is achieved with texture features responsible for capturing aspects of lesion heterogeneity. Mutual information analysis reveals that texture features extracted from the third and fourth post-contrast images contributed most to the observed improvement in classifier performance. These results show that the performance of automated character classification with small lesions can be significantly improved through dynamic texture quantification of the lesion enhancement pattern.

Performance of topological texture features to classify fibrotic interstitial lung disease patterns.

PURPOSE: Topological texture features were compared in their ability to classify "honeycombing," a morphological pattern that is considered indicative for the presence of fibrotic interstitial lung disease in high-resolution computed tomography (HRCT) images. METHODS: For 14 patients with known occurrence of honeycombing, a stack of 70 axial, lung kernel reconstructed images was acquired from HRCT chest exams. A set of 964 regions of interest of both healthy and pathological (356) lung tissue was identified by an experienced radiologist. Texture features were extracted using statistical features (Stat), six properties calculated from gray-level co-occurrence matrices (GLCMs), Minkowski dimensions (MDs), and three Minkowski functionals (MFs) (e.g., MF.Euler). A naïve Bayes (NB) and k-nearest-neighbor (k-NN) classifier, a multilayer radial basis functions network (RBFN), and a support vector machine with a radial basis function (SVMrbf) kernel were optimized in a tenfold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions and the significance thresholds were adjusted for multiple comparisons by the Bonferroni correction. RESULTS: The best classification results were obtained by the MF features, which performed significantly better than all the standard Stat, GLCM, and MD features (p < 0.001) for both classifiers. The highest accuracies were found for MF.Euler (93.6%, 94.9%, 94.2%, and 95.0% for NB, k-NN, RBFN, and SVMrbf, respectively). The best groups of standard texture features were a Stat and GLCM ("homogeneity") feature set (up to 91.8%). CONCLUSIONS: The results indicate that advanced topological texture features derived from MFs can provide superior classification performance in computer-assisted diagnosis of fibrotic interstitial lung disease patterns when compared to standard texture analysis methods.

Human vocal tract analysis by in vivo 3D MRI during phonation: a complete system for imaging, quantitative modeling, and speech synthesis.

We present a complete system for image-based 3D vocal tract analysis ranging from MR image acquisition during phonation, semi-automatic image processing, quantitative modeling including model-based speech synthesis, to quantitative model evaluation by comparison between recorded and synthesized phoneme sounds. For this purpose, six professionally trained speakers, age 22-34y, were examined using a standardized MRI protocol (1.5 T, T1w FLASH, ST 4mm, 23 slices, acq. time 21s). The volunteers performed a prolonged (> or = 21s) emission of sounds of the German phonemic inventory. Simultaneous audio tape recording was obtained to control correct utterance. Scans were made in axial, coronal, and sagittal planes each. Computer-aided quantitative 3D evaluation included (i) automated registration of the phoneme-specific data acquired in different slice orientations, (ii) semi-automated segmentation of oropharyngeal structures, (iii) computation of a curvilinear vocal tract midline in 3D by nonlinear PCA, (iv) computation of cross-sectional areas of the vocal tract perpendicular to this midline. For the vowels /a/,/e/,/i/,/o/,/ø/,/u/,/y/, the extracted area functions were used to synthesize phoneme sounds based on an articulatory-acoustic model. For quantitative analysis, recorded and synthesized phonemes were compared, where area functions extracted from 2D midsagittal slices were used as a reference. All vowels could be identified correctly based on the synthesized phoneme sounds. The comparison between synthesized and recorded vowel phonemes revealed that the quality of phoneme sound synthesis was improved for phonemes /a/, /o/, and /y/, if 3D instead of 2D data were used, as measured by the average relative frequency shift between recorded and synthesized vowel formants (p < 0.05, one-sided Wilcoxon rank sum test). In summary, the combination of fast MRI followed by subsequent 3D segmentation and analysis is a novel approach to examine human phonation in vivo. It unveils functional anatomical findings that may be essential for realistic modelling of the human vocal tract during speech production.

Functional abnormalities of the visual processing system in subjects with mild cognitive impairment: an fMRI study.

Subjects with mild cognitive impairment (MCI) have a higher risk of developing Alzheimer's disease compared with healthy controls (HC). Sensory impairment can contribute to the severity of cognitive impairment. We measured the activation changes in the visual system between MCI and HC subjects. There were 16 MCI subjects with either amnestic MCI or multiple-domain+amnestic MCI and an HC group of 19 subjects. There were two tasks: (a) a face matching and (b) a location matching task. Brain activation was measured using functional magnetic resonance imaging. There were no differences in task performance. The HC group selectively activated the ventral and dorsal pathways during the face and location matching tasks, respectively, while the MCI group did not. The MCI group had greater activation than the HC group in the left frontal lobe during the location matching task. There were no areas of increased activation in the HC group compared with the MCI group. The MCI group, as a compensatory mechanism, activated both visual pathways and increased activation in the left frontal lobe during the location matching task compared with the healthy controls. To our knowledge, this is the first study that has examined visual processing in MCI.

White matter alterations in schizophrenic patients with pronounced negative symptomatology and with positive family history for schizophrenia.

BACKGROUND: In recent years, in vivo and post-mortem studies detected structural brain changes in schizophrenia. The aim of our analysis was to investigate potential changes of white matter in schizophrenic patients compared to controls, and the relationship to clinical characteristics. METHODS: Fifty male, right-handed schizophrenic patients who met DSM-IV criteria for schizophrenia were recruited. Fifty right-handed, age- and sex-matched subjects without a psychiatric disorder were enrolled as controls. Volumes of white matter in several brain regions were measured by 1.5 T MRI using a volumetry and segmentation software (BRAINS). Regions of interest including frontal, temporal, parietal, occipital and subcortical areas were determined using Talairach spaces. RESULTS: No significant differences in white matter volumes of total brain tissue and regions of interest were detected between patients and controls. A significant reduction of white matter in parietal cortex of right hemisphere was found in a subgroup of patients with pronounced negative symptoms. Furthermore, patients with first-grade relatives suffering from schizophrenia showed a reduction of subcortical white matter in the right hemisphere. CONCLUSIONS: Our results indicate that subgroups of schizophrenic patients show alterations of white matter in distinct brain regions, including the right parietal lobe.

Anterior cingulate cortex does not differ between patients with major depression and healthy controls, but relatively large anterior cingulate cortex predicts a good clinical course.

The anterior cingulate cortex (ACC) is involved in the regulation of emotion processing, and its volume has been found to be reduced in patients with major depression. Furthermore, larger ACC volumes have been associated with faster symptom improvement under therapy. The aims of the study were to examine whether volumes of the anterior cingulate cortex are altered and are related to the clinical course of major depression. Subjects comprised 78 inpatients with major depression and 78 age-, gender- and handedness- matched healthy volunteers, who were investigated with structural magnetic resonance imaging (MRI). The ACC was subdivided into the subgenual, pre-callosal, rostral-anterior and caudal-anterior ACC. No significant differences were observed for ACC volumes between patients and healthy controls. Left ACC volumes showed a significant negative correlation with the number of hospitalizations. These findings suggest that ACC volumes are not altered in patients with major depression, but that patients with larger ACC have a better clinical outcome than patients with smaller ACC.

Classification of small contrast enhancing breast lesions in dynamic magnetic resonance imaging using a combination of morphological criteria and dynamic analysis based on unsupervised vector-quantization.

PURPOSE: To evaluate the diagnostic value of breast magnetic resonance imaging (MRI) in small focal lesions using dynamic analysis based on unsupervised vector quantization in combination with a score for morphologic criteria. MATERIALS AND METHODS: We examined 85 mammographically indetermintate lesions (BIRADS 3-4; 47 malignant, mean lesion size 1.2 cm; 38 benign, mean lesion size 1.1 cm). MRI was performed with a dynamic T1-weighted gradient echo sequence (1 precontrast and 5 postcontrast series). Lesions with an initial contrast enhancement >/=50% were selected with semiautomatic segmentation. For conventional dynamic analysis, we calculated the mean initial signal increase and postinitial course of all voxels included in a lesion. Secondly, all voxels within the lesions were assigned to 4 clusters using minimal-free-energy vector quantization. Dynamic and morphologic criteria were summarized in a diagnostic score and evaluated by receiver operating characteristic analysis. RESULTS: In the present collection of small lesions, morphologic criteria [area under the curve (AUC) = 0.610] were inferior to dynamic criteria in the detection of breast cancer. Dynamic analysis with vector quantization (AUC = 0.760) presented slightly better results compared with standard dynamic analysis (AUC = 0.693). There was no benefit for combined morphologic and dynamic analysis. CONCLUSION: In small MR-mammographic lesions, dynamic analysis with vector quantization alone tends to result in a higher diagnostic accuracy compared with combined morphologic and dynamic analysis.

Hippocampal volume reduction and history of aggressive behaviour in patients with borderline personality disorder.

Disturbances of aggression and impulse control are important symptoms of borderline personality disorder (BPD). The hippocampus is part of the limbic system, which is involved in the control of these types of behaviour. The aim of our study was to investigate potential structural changes of the hippocampal formation in BPD and to evaluate if these are related to aggressive and impulsive behaviour. Twenty-five female and right-handed BPD patients (DSM-IV) and 25 healthy control subjects matched according to sex, age, handedness and educational status were examined. Magnetic resonance imaging (MRI) was performed using a 1.5-T Magnetom Vision system. The software program "BRAINS" was employed for segmentation and volumetry of the hippocampal formation. German versions of instruments were used to evaluate impulsive and aggressive behaviour. Hippocampal grey matter volume was significantly decreased in BPD patients: the reduction was more pronounced in patients with multiple hospitalizations. Hippocampal volume of the left hemisphere was inversely correlated with lifetime history of aggressive behaviour. However, no significant relationship was found between hippocampal volume and impulsive behaviour. Our study confirms previous results indicating a volume reduction of the hippocampal formation in BPD patients. Furthermore, this structural change might facilitate aggressive behaviour. Subsequent studies are required to clarify whether the reduction of hippocampal volume is a trait and risk factor for increased aggression.

Reduced hippocampal volume correlates with executive dysfunctioning in major depression.

OBJECTIVE: Dysfunction of neuronal plasticity or remodelling seems to contribute to the pathopysiology of major depression and may cause the well-documented hippocampal changes in depression. We aimed to investigate whether reduced hippocampal volumes correlate with executive dysfunctioning or memory dysfunctioning or with depression severity. METHODS: We recruited 34 inpatients with a previous or current episode of major depression from the department of psychiatry at the Ludwig-Maximilians University of Munich, Germany. We examined the 34 patients and 34 healthy control subjects with structural high resolution MRI. We assessed cognitive functions with the Wisconsin Card Sorting Test (WCST) and the Rey Auditory Verbal Learning Test (RAVLT) and severity of depression with the Hamilton Depression Rating Scale. RESULTS: Hippocampal volumes and frontal lobe volumes were significantly smaller in patients, compared with healthy control subjects. Furthermore, lower hippocampal volumes were correlated with poorer performance in the WCST. No significant correlations were found between hippocampal volumes and RAVLT performance or severity of depression. CONCLUSIONS: The present findings emphasize that patients with reduced hippocampal volumes show more executive dysfunctions than their counterparts. Thus, the mechanisms resulting in reduced hippocampal volumes seem to be related to the development of major depression.

Amygdala volume and depressive symptoms in patients with borderline personality disorder.

BACKGROUND: Borderline personality disorder (BPD) is characterized by a high prevalence of comorbid psychiatric disorders, including major depression (MD). The aim of this study was to examine whether a co-occurrence of MD is associated with structural changes in the amygdala of BPD patients. METHODS: Twenty-five right-handed, female patients with BPD and 25 matched healthy control subjects were examined. Diagnoses of BPD and MD were made according to DSM IV. Depressive symptomatology was determined with the Hamilton Depression Scale (HAMD). Magnetic resonance imaging scans were performed with 1.5 T Magnetom Vision (Siemens, Erlangen, Germany). The software program "BRAINS" was applied for brain volumetry and segmentation. The amygdala was delineated as "region of interest." RESULTS: Comparison of amygdala volumes between the whole group of BPD patients and control subjects revealed no significant difference. Amygdala volumes in both hemispheres were significantly larger in BPD patients with MD compared with those without MD. There was a significant correlation in BPD patients between left amygdala volume and depressive symptoms as measured by HAMD. CONCLUSIONS: Correlation of amygdala volume with depression in BPD patients might indicate a causal relationship. Future studies should clarify whether amygdala enlargement is a risk factor for MD in BPD patients or a consequence of the affective disorder.

Cluster analysis of signal-intensity time course in dynamic breast MRI: does unsupervised vector quantization help to evaluate small mammographic lesions?

We examined whether neural network clustering could support the characterization of diagnostically challenging breast lesions in dynamic magnetic resonance imaging (MRI). We examined 88 patients with 92 breast lesions (51 malignant, 41 benign). Lesions were detected by mammography and classified Breast Imaging and Reporting Data System (BIRADS) III (median diameter 14 mm). MRI was performed with a dynamic T1-weighted gradient echo sequence (one precontrast and five postcontrast series). Lesions with an initial contrast enhancement >or=50% were selected with semiautomatic segmentation. For conventional analysis, we calculated the mean initial signal increase and postinitial course of all voxels included in a lesion. Secondly, all voxels within the lesions were divided into four clusters using minimal-free-energy vector quantization (VQ). With conventional analysis, maximum accuracy in detecting breast cancer was 71%. With VQ, a maximum accuracy of 75% was observed. The slight improvement using VQ was mainly achieved by an increase of sensitivity, especially in invasive lobular carcinoma and ductal carcinoma in situ (DCIS). For lesion size, a high correlation between different observers was found (R(2) = 0.98). VQ slightly improved the discrimination between malignant and benign indeterminate lesions (BIRADS III) in comparison with a standard evaluation method.

Correlation of cerebrospinal fluid levels of tau protein phosphorylated at threonine 231 with rates of hippocampal atrophy in Alzheimer disease.

BACKGROUND: The microtubule-associated tau protein abnormally phosphorylated at threonine 231 (p-tau231) has been investigated as a potential marker of Alzheimer disease. Levels of cerebrospinal fluid (CSF) p-tau231 vary across patients with Alzheimer disease. We hypothesized that these variations partially reflect differences in the degree of neuronal damage and therefore may be used to predict structural disease progression. OBJECTIVE: To investigate whether CSF p-tau231 levels correlate with rates of hippocampal atrophy as an in vivo marker of regional neuronal loss. DESIGN AND PATIENTS: We measured hippocampal volumes on the basis of serial magnetic resonance image examinations in 22 patients with Alzheimer disease. In addition, we determined CSF p-tau231 levels at baseline. RESULTS: Levels of CSF p-tau231 were significantly correlated with baseline hippocampal volumes (P<.001) and rates of hippocampal atrophy (left hippocampus, P<.001; right hippocampus, P = .02), independent of disease duration and severity. CONCLUSION: These findings suggest that variations in p-tau231 levels may be used to predict progression of brain atrophy in patients with Alzheimer disease.

Reliable manual segmentation of the frontal, parietal, temporal, and occipital lobes on magnetic resonance images of healthy subjects.

BACKGROUND: It is a challenge to reliably measure the lobar volumes from magnetic resonance imaging (MRI) data. OBJECTIVE: Description of a landmark-based method for volumetric segmentation of the brain into the four cerebral lobes from MR images. METHOD: The segmentation method relies on a combination of anatomical landmarks and geometrical definitions. The first step, described previously, is a segmentation of the four lobes on the surface of the brain. The internal borders between the lobes are defined on the axial slices of the brain. The intra- and inter- rater reliability was determined from the MRI scans of a group of 10 healthy control subjects measured by 2 independent raters. RESULTS: The intra-rater relative error (and intra-class correlation coefficient) of the lobar volume measures ranged from 0.81% to 3.85% (from 0.97 to 0.99). The inter-rater relative error (and intra-class correlation coefficient) ranged from 0.55% to 3.09% (from 0.94 to 0.99). CONCLUSION: This technique has been shown to have high intra- and inter-rater reliability. The current method provides a method to obtain volumetric estimates of the 4 cerebral lobes.

The septum pellucidum and its variants. An MRI study.

PURPOSE: Increased prevalence of cavum septi pellucidi (CSP) in schizophrenic patients in comparison to healthy subjects was reported previously. Our purpose was to evaluate the prevalence of variants of the septum pellucidum in healthy subjects in three different age groups. METHODS: 151 healthy subjects, including 46 children (age 6 +/- 4 years), 72 young adults (age 31 +/- 8 years) and 33 elderly adults (age 59 +/- 7 years) were examined with high-resolution MRI. Three observers analysed the images using a standardised protocol. We evaluated the incidences of CSP, cavum vergae (CV) and their length. RESULTS: CSP was detected in 80% of the cases in the paediatric group and 68% of young adults and in 72% of the elderly adults. A cavum vergae (CV) was noted in 22% of the children, in 39% of the young adults and in 36% of the elderly subjects. There was no significant difference between the age-related groups. CONCLUSION: We detected a high prevalence of cavum septi pellucidi without a significant age dependence. Enlarged cava septi pellucidi are rare in healthy subjects.

The long-term outcome of anti-Jo-1-positive inflammatory myopathies.

OBJECTIVE: To determine the response to treatment and the long-term outcome of patients with the antisynthetase syndrome associated with anti-Jo-1-antibodies. PATIENTS AND METHODS: A total of 12 patients with histologically proven myositis and anti-Jo-1-autoantibodies were evaluated over a mean follow-up period of 66.4 months. In all patients neuromuscular function tests, electromyographic examinations, pulmonary function tests and high-resolution-computed tomography of the lungs were performed regularly. RESULTS: Muscle function improved in all patients with treatment, and a complete clinical response was achieved in 5 patients. Pulmonary function worsened in 1 patient, who died from respiratory failure, but normalised in 4 patients. Arthropathy progressed despite improvement of myositis and pulmonary status in 2 patients. Discontinuation of treatment was facilitated in 1 patient, although long-term therapy was required in 10 patients. In 2 patients with refractory disease, treatment with intravenous immunoglobulins was successful. Severe side effects of treatment occurred in 7 patients and overall mortality rate was one of 12 (8 %). CONCLUSION: The antisynthetase syndrome associated with anti-Jo-1-antibodies requires long-term immunosuppressive therapy in most patients. Whereas a complete clinical response of muscular symptoms is frequent, continued deterioration of the pulmonary system may occur despite immunosuppressive treatment, and may lead to fatal outcome. An interdisciplinary therapeutic approach is necessary for best possible results in these patients.

Hippocampal and amygdala changes in patients with major depressive disorder and healthy controls during a 1-year follow-up.

BACKGROUND: Although the hippocampus has been found to be smaller in patients with depression, prospective longitudinal in vivo studies are necessary to investigate whether depression can result in a further diminution of hippocampal volumes or whether a smaller hippocampal volume predisposes an individual to the development of depression. METHOD: Thirty patients with DSM-IV major depressive disorder as well as 30 healthy control subjects matched for age, gender, and handedness were examined at admission to the hospital and 1 year later using a documentation of the medical history and high-resolution magnetic resonance imaging (MRI) for the presence of depression and to determine changes in hippocampal as well as amygdala volumes. Patients were enrolled from March 2000 to August 2002. RESULTS: No significant hippocampal and amygdala volume changes were observed in patients or controls between baseline and 1-year follow-up investigations. However, the subgroup of patients who were nonremitted at the time of the follow-up investigation showed significantly reduced left and right hippocampal volumes at both baseline and the 1-year follow-up compared with remitted patients. Moreover, the right hippocampal volumes of nonremitted patients were significantly smaller compared with matched healthy controls. CONCLUSION: These results do not support the hypothesis that hippocampal volumes diminish during the 1-year follow-up period. However, smaller hippocampal volumes may be related to a poor clinical outcome after 1 year.

Reduced hippocampal volumes associated with the long variant of the serotonin transporter polymorphism in major depression.

BACKGROUND: Substantial evidence supports a role for dysfunction of the serotonin transporter in the pathogenesis of major depression. Several studies have found reciprocal interactions between the serotonergic system and both brain-derived neurotrophic factor and glutamate, which are known to modulate or affect hippocampal morphologic characteristics. OBJECTIVE: To examine the influence of a polymorphism (5-HTTLPR) in the promoter region of the serotonin transporter gene on hippocampal volumes in patients with major depression and healthy controls. DESIGN: Baseline investigation of a prospective magnetic resonance imaging study with a 4-year follow-up period. PATIENTS: We examined 40 inpatients with major depression as well as 40 healthy controls matched for age, sex, and handedness. MAIN OUTCOME MEASURES: Subjects underwent high-resolution magnetic resonance imaging. Furthermore, genotyping for the 5-HTTLPR biallelic polymorphism was performed, which consists of a 44-base pair insertion (L allele) or deletion (S allele). RESULTS: Patients with the L/L homozygous genotype had significantly smaller hippocampal gray matter (left hemisphere: P=.003; right hemisphere: P=.01) and white matter volumes (left hemisphere: P=.001; right hemisphere: P=.002) than controls with this genotype. No significant differences were found between patients and controls with the L/S or S/S genotype. Moreover, patients with the L/L genotype had significantly smaller hippocampal white matter volumes than those with the L/S or S/S genotype (P=.03). CONCLUSIONS: These findings suggest that homozygosity for the L allele is associated with decreased hippocampal volumes in patients with major depression but not in healthy controls. A possible explanation is that the interaction between the serotonergic system and neurotrophic factors as well as excitatory amino acid neurotransmission may affect hippocampal morphologic characteristics.

Integrated imaging using MRI and 123I metaiodobenzylguanidine scintigraphy to improve sensitivity and specificity in the diagnosis of pediatric neuroblastoma.

OBJECTIVE: The objectives of this study were to compare MRI and iodine-123 ((123)I) metaiodobenzylguanidine (MIBG) scintigraphy in the detection of neuroblastoma lesions in pediatric patients and to assess the additional value of combined imaging. MATERIALS AND METHODS: Fifty MRI and 50 (123)I MIBG examinations (mean interval, 6.4 days) were analyzed retrospectively with regard to suspected or proven neuroblastoma lesions (n = 193) in 28 patients. MRI and MIBG scans were reviewed by two independent observers each. Separate and combined analyses of MRI and MIBG scintigraphy were compared with clinical and histologic findings. RESULTS: With regard to the diagnosis of neuroblastoma lesion, MIBG scintigraphy, MRI, and combined analysis showed a sensitivity of 69%, 86%, and 99% and a specificity of 85%, 77%, and 95%, respectively. On MRI, 15 false-positive findings were recorded: posttherapeutic reactive changes (n = 10), benign adrenal tumors (n = 3), and enlarged lymph nodes (n = 2). On MIBG scintigraphy, 10 false-positive findings occurred: ganglioneuromas (n = 2), benign liver tumors (n = 2), and physiologic uptake (n = 6). Thirteen neuroblastoma metastases and two residual masses under treatment with chemotherapy were judged to be false-negative findings on MRI. Two primary or residual neuroblastomas and one orbital metastasis were misinterpreted as Wilms' tumor, reactive changes after surgery, and rhabdomyosarcoma on MRI. Thirty-two bone metastases, six other neuroblastoma metastases, and one adrenal neuroblastoma showed no MIBG uptake. On combined imaging, one false-negative (bone metastasis) and three false-positive (two ganglioneuromas and one pheochromocytoma) findings remained. CONCLUSION: In the assessment of neuroblastoma lesions in pediatric patients, MRI showed a higher sensitivity and MIBG scintigraphy a higher specificity. However, integrated imaging showed an increase in both sensitivity and specificity.