Lesion-Specific Language Network Alterations in Temporal Lobe Epilepsy.

BACKGROUND AND PURPOSE: Temporal lobe epilepsy, structural or nonlesional, may negatively affect language function. However, little is known about the lesion-specific influence on language networks. We hypothesized that different epileptogenic lesions are related to distinct alterations in the functional language connectome detected by fMRI. MATERIALS AND METHODS: One hundred one patients with epilepsy due to mesiotemporal sclerosis (21 left, 22 right), low-grade mesiotemporal tumors (12 left), or nonlesional temporal lobe epilepsy (22 left, 24 right) and 22 healthy subjects performed 3T task-based language fMRI. Task-based activation maps (laterality indices) and functional connectivity analysis (global and connectivity strengths between language areas) were correlated with language scores. RESULTS: Laterality indices based on fMRI activation maps failed to discriminate among patient groups. Functional connectivity analysis revealed the most extended language network alterations in left mesiotemporal sclerosis (involving the left temporal pole, left inferior frontal gyrus, and bilateral premotor areas). The other patient groups showed less extended but also predominantly ipsilesional network changes compared with healthy controls. Left-to-right hippocampal connectivity strength correlated positively with naming function (P = .01), and connectivity strength between the left Wernicke area and the left hippocampus was linked to verbal fluency scores (P = .01) across all groups. CONCLUSIONS: Different pathologies underlying temporal lobe epilepsy are related to distinct alterations of the functional language connectome visualized by fMRI functional connectivity analysis. Network analysis allows new insights into language organization and provides possible imaging biomarkers for language function. These imaging findings emphasize the importance of a personalized treatment strategy in patients with epilepsy.

[Artificial intelligence in lung imaging]. / Künstliche Intelligenz in der Bildgebung der Lunge.

CLINICAL/METHODICAL ISSUE: Artificial intelligence (AI) has the potential to improve diagnostic accuracy and management in patients with lung disease through automated detection, quantification, classification, and prediction of disease progression. STANDARD RADIOLOGICAL METHODS: Owing to unspecific symptoms, few well-defined CT disease patterns, and varying prognosis, interstitial lungs disease represents a focus of AI-based research. METHODICAL INNOVATIONS: Supervised and unsupervised machine learning can identify CT disease patterns using features which may allow the analysis of associations with specific diseases and outcomes. PERFORMANCE: Machine learning on the one hand improves computer-aided detection of pulmonary nodules. On the other hand it enables further characterization of pulmonary nodules, which may improve resource effectiveness regarding lung cancer screening programs. ACHIEVEMENTS: There are several challenges regarding AI-based CT data analysis. Besides the need for powerful algorithms, expert annotations and extensive training data sets that reflect physiologic and pathologic variability are required for effective machine learning. Comparability and reproducibility of AI research deserve consideration due to a lack of standardization in this emerging field. PRACTICAL RECOMMENDATIONS: This review article presents the state of the art and the challenges concerning AI in lung imaging with special consideration of interstitial lung disease, and detection and consideration of pulmonary nodules.

Three-dimensional reconstruction of defects in congenital diaphragmatic hernia: a fetal MRI study.

OBJECTIVE: To assess the clinical feasibility and validity of fetal magnetic resonance imaging (MRI)-based three-dimensional (3D) reconstruction to locate, classify and quantify diaphragmatic defects in congenital diaphragmatic hernia (CDH). METHODS: This retrospective study included 46 cases of CDH which underwent a total of 69 fetal MRI scans (65 in-vivo and four postmortem) at the Medical University of Vienna during the period 1 January 2002 to 1 January 2017. Scans were performed between 16 and 38 gestational weeks using steady-state free precession, T2-weighted and T1-weighted sequences. MRI data were retrieved from the hospital database and manual segmentation of the diaphragm was performed with the open-source software, ITK-SNAP. The resulting 3D models of the fetal diaphragm and its defect(s) were validated by postmortem MRI segmentation and/or comparison of 3D model-based classification of the defect with a reference classification based on autopsy and/or surgery reports. Surface areas of the intact diaphragm and of the defect were measured and used to calculate defect-diaphragmatic ratios (DDR). The need for prosthetic patch repair and, in cases with repeated in-vivo fetal MRI scans, diaphragm growth dynamics, were analyzed based on DDR. RESULTS: Fetal MRI-based manual segmentation of the diaphragm in CDH was feasible for all 65 (100%) of the in-vivo fetal MRI scans. Based on the 3D diaphragmatic models, one bilateral and 45 unilateral defects (n = 47) were further classified as posterolateral (23/47, 48.9%), lateral (7/47, 14.9%) or hemidiaphragmatic (17/47, 36.2%) defects, and none (0%) was classified as anterolateral. This classification of defect location was correct in all 37 (100%) of the cases in which this information could be verified. Nineteen cases had a follow-up fetal MRI scan; in five (26.3%) of these, the initial CDH classification was altered by the results of the second scan. Thirty-three fetuses underwent postnatal diaphragmatic surgical repair; 20 fetuses (all of those with DDR ≥ 54 and 88% of those with DDR > 30) received a diaphragmatic patch, while the other 13 underwent primary surgical repair. Individual DDRs at initial and at follow-up in-vivo fetal MRI correlated significantly (P < 0.001). CONCLUSIONS: MRI-based 3D reconstruction of the fetal diaphragm in CDH has been validated to visualize, locate, classify and quantify the defect. Planning of postnatal surgery may be optimized by MRI-based prediction of the necessity for patch placement and the ability to personalize patch design based on 3D-printable templates. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Machine learning: from radiomics to discovery and routine.

Machine learning is rapidly gaining importance in radiology. It allows for the exploitation of patterns in imaging data and in patient records for a more accurate and precise quantification, diagnosis, and prognosis. Here, we outline the basics of machine learning relevant for radiology, and review the current state of the art, the limitations, and the challenges faced as these techniques become an important building block of precision medicine. Furthermore, we discuss the roles machine learning can play in clinical routine and research and predict how it might change the field of radiology.

Prenatal assessment of cerebellar vermian lobulation: fetal MRI with 3-Tesla postmortem validation.

OBJECTIVES: To optimize the imaging assessment of fetal hindbrain malformations, this observational magnetic resonance imaging (MRI) study aimed to assess whether fetal vermian lobulation can be quantified accurately and whether the relative growth of vermian lobules is uniform. METHODS: This retrospective study included singleton fetuses which underwent T2-weighted MRI in vivo with a 1.5-Tesla (T) scanner or within 24 h postmortem with a 3-T scanner between January 2007 and November 2016 at the Medical University of Vienna. We included only those showing normal structural brain development on ultrasound and MRI and which had image quality appropriate for quantitative analysis, i.e. good image quality and a precise midsagittal slice. Fetal brains were segmented and, for all discernible vermian lobules, we determined the mean relative area contribution (MRAC, the proportion of the lobule relative to the total vermian area, in terms of number of voxels). Inter- and intrarater measurement variability of a representative selection (21 cases) was determined by intraclass correlation coefficient (ICC) for voxel-based differences. A linear regression model was used to assess the correlation between the relative size of each vermian lobule (i.e. MRAC) and gestational age. RESULTS: A total of 78 fetuses scanned in vivo aged 18-32 gestational weeks and seven fetuses scanned postmortem aged 16-30 weeks had a precise midsagittal slice and image quality sufficient for quantitative analysis. After 22 weeks of gestation, seven of the nine known vermian lobules could be discriminated reliably. The MRAC showed a mean ± SD difference of only 2.89 ± 3.01% between in-vivo and postmortem measurements. The ICC of voxel-based interrater differences was mean ± SD, 0.91 ± 0.05 and the intrarater ICC was 0.95 ± 0.03. Growth of cerebellar lobules was non-uniform: the MRAC of culmen and DFT (declive + folium + tuber) increased with gestational age, whereas that of lingula, centralis, pyramis and nodulus decreased. The growth of the uvula showed no significant correlation with gestational age. CONCLUSIONS: Fetal vermian lobulation can be assessed accurately and reliably after 22 weeks on precise midsagittal sequences with 1.5-T T2-weighted MRI. Fetal vermian lobules show non-uniform growth, with expansion of DFT and culmen at the expense of the other vermian lobules. Evaluation and elucidation of vermian lobulation in normal fetuses should enable better characterization of fetuses with hindbrain malformations. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Keypoint Transfer Segmentation.

We present an image segmentation method that transfers label maps of entire organs from the training images to the novel image to be segmented. The transfer is based on sparse correspondences between keypoints that represent automatically identified distinctive image locations. Our segmentation algorithm consists of three steps: (i) keypoint matching, (ii) voting-based keypoint labeling, and (iii) keypoint-based probabilistic transfer of organ label maps. We introduce generative models for the inference of keypoint labels and for image segmentation, where keypoint matches are treated as a latent random variable and are marginalized out as part of the algorithm. We report segmentation results for abdominal organs in whole-body CT and in contrast-enhanced CT images. The accuracy of our method compares favorably to common multi-atlas segmentation while offering a speed-up of about three orders of magnitude. Furthermore, keypoint transfer requires no training phase or registration to an atlas. The algorithm's robustness enables the segmentation of scans with highly variable field-of-view.

Stent graft surface movement after infrarenal abdominal aortic aneurysm repair: comparison of patients with and without a type 2 endoleak.

OBJECTIVES: The aim was to compare multidirectional stent graft movement in patients with and without a type 2 endoleak. METHODS: This was a retrospective case control study of patients being followed up after elective endovascular aneurysm repair of abdominal aortic aneurysms. The post-procedural and final follow up multislice computed tomography (MSCT) of 69 patients with and 74 without a type 2 endoleak were analyzed. Three dimensional (3D) surface models of the stent graft, delimited by landmarks using custom built software, were derived from these MSCT data. The stent graft was segmented in different zones, and the proportion of the total stent graft surface moving >9 mm between the post-procedural and the final follow up MSCT was calculated, given in percentages, and compared between groups. Changes of infrarenal neck, renal artery to stent graft distance, and freedom from stent graft related endoleaks were evaluated. RESULTS: Overall surface movement was higher in the no endoleak (18.8%, IQR 0.1-45.1%) than in the type 2 endoleak group (5.3%, IQR 0-29.7%; p = .06). Furthermore, significantly higher surface movement in the no endoleak group was found in the proximal anchoring zone (p = .04) and the distal left limb (p = .01), which was the modular limb in 81.1% (p < .01). Neck diameter increase (1.0 mm, IQR 0-3.0 mm; p < .01) and renal artery to stent graft distance difference (0 mm, IQR 0-3.3 mm; p < .01) were significantly higher in the no endoleak group. Five patients in the no endoleak and one patient in the type 2 endoleak group suffered from a stent graft related endoleak (p = .27). CONCLUSIONS: The presence of a type 2 endoleak is associated with decreased surface movement of the proximal anchoring zone and the distal modular limb of bifurcated stent grafts.

A survey on visual information search behavior and requirements of radiologists.

OBJECTIVES: The main objective of this study is to learn more on the image use and search requirements of radiologists. These requirements will then be taken into account to develop a new search system for images and associated meta data search in the Khresmoi project. METHODS: Observations of the radiology workflow, case discussions and a literature review were performed to construct a survey form that was given online and in paper form to radiologists. Eye tracking was performed on a radiology viewing station to analyze typical tasks and to complement the survey. RESULTS: In total 34 radiologists answered the survey online or on paper. Image search was mentioned as a frequent and common task, particularly for finding cases of interest for differential diagnosis. Sources of information besides the Internet are books and discussions with colleagues. Search for images is unsuccessful in around 25% of the cases, stopping the search after around 10 minutes. The most common reason for failure is that target images are considered rare. Important additions for search requested in the survey are filtering by pathology and modality, as well as search for visually similar images and cases. Few radiologists are familiar with visual retrieval but they desire the option to upload images for searching similar ones. CONCLUSIONS: Image search is common in radiology but few radiologists are fully aware of visual information retrieval. Taking into account the many unsuccessful searches and time spent for this, a good image search could improve the situation and help in clinical practice.

Computational radiology in skeletal radiography.

Recent years have brought rapid developments in computational image analysis in musculo-skeletal radiology. Meanwhile the algorithms have reached a maturity that makes initial clinical use feasible. Applications range from joint space measurement to erosion quantification, and from fracture detection to the assessment of alignment angles. Current results of computational image analysis in radiography are very promising, but some fundamental issues remain to be clarified, among which the definition of the optimal trade off between automatization and operator-dependency, the integration of these tools into clinical work flow and last not least the proof of incremental clinical benefit of these methods.

[Measurement instead of scoring in rheumatology: new quantitative imaging and processing methods in radiology]. / Messen statt scoren in der Rheumatologie : Neue quantitative Bildgebungs- und -verarbeitungsmethoden der Radiologie.

Many radiological methods to statistically evaluate progression of rheumatic diseases have been presented in recent years. This review article explains their basics as well as the background to the development of "imaging biomarkers" and their potential application in rheumatology.

[Computer assisted radiological diagnostics of arthritic joint alterations]. / Computerassistierte radiologische Diagnostik arthritischer Gelenkveränderungen.

Computer assisted diagnosis (CAD) schemes are currently used in the field of musculoskeletal diseases to quantitatively assess vertebral fractures, joint space narrowing, andr erosion. Most systems work semi-automatically, i.e. they are operator dependent in the selection of anatomical landmarks. Fully automatic programs are currently under development. Some CAD products have already been successfully used in clinical trials.

[Quantitative imaging in rheumatoid arthritis: from scoring to measurement]. / Quantitative Bildgebung bei rheumatoider Arthritis: Vom Scoring zur Messung.

The need of clinical sciences to measure therapy effects on chronic illness led to development, evaluation, and publication of several radiological methods to monitor disease progression of rheumatic diseases. This review article explains the basics and background of scoring and measurement. The radiologist thus learns to report more compactly and to communicate the results more specifically.

Incidence of obsessive-compulsive phenomena in the course of acute schizophrenia and schizoaffective disorder.

Studies examining OC phenomena in schizophrenic and schizoaffective disorders have shown a prevalence of such phenomena in 1 to 60% of schizophrenic or schizoaffective patients. In this prospective study, about 10% of 150 male patients suffering from acute psychotic disorders (fulfilling DSM-IV criteria for Schizophrenia or Schizoaffective Disorder) were found to have OC symptoms. These symptoms showed no correlation to the type and severity of psychosis. As only 19% of the patients with obsessions and compulsions during acute psychosis showed an obsessive-compulsive personality disorder prior to their psychotic episodes, it may be concluded that there is no clear linkage between intrapsychotic OC phenomena and premorbid anancastic personality traits.

Basic symptoms and their contribution to the differential typology of acute schizophrenic and schizoaffective disorders.

One hundred and fifty male inpatients - 128 patients with DSM-IV schizophrenia and 22 patients with DSM-IV schizoaffective disorder - were investigated, over the course of their acute psychosis, on whether there were differences in the extent of basic symptoms (measured by the Bonn Scale for the Assessment of Basic Symptoms) according to their diagnostic subtype. Another aim was to find out if the diagnostic subtypes could be discriminated by means of basic symptoms and if clusters gained from basic symptoms were in accordance with the diagnostic subtypes. Differences in basic symptoms were found between the subtypes, but a clear discrimination of diagnostic subtypes by means of basic symptoms could not be achieved. There was indication that patients with prominent delusions or auditory hallucinations reported more basic symptoms than patients with exclusively prominent disorganization.

A case of comorbidity between panic disorder and photosensitive epilepsy.

Panic disorder and epilepsy usually are distinct entities which require different and specific therapeutic strategies. While anticonvulsant medication is the treatment of choice for seizure disorders, behavioral methods have proven to be effective in panic disorder. We here report a case of comorbidity between panic disorder and photosensitive epilepsy. Special attention is given to the different symptomatic presentations of the disorders, because a thorough knowledge of both disorders may save unnecessary diagnostic procedures. Therefore, the necessity of taking a careful patient's history is underlined. Furthermore the different possible relationship between panic disorder and epilepsy are discussed.

The development of agoraphobia in panic disorder: a predictable process?

BACKGROUND: Panic attacks are conceptualized to be the central feature of both panic disorder without (PDU) and with agoraphobia (PDA). As a sizeable percentage of panic patients do not develop avoidance behavior, other factors than 'panic attacks', in general, must influence the different courses of the disorder. METHOD: We studied 84 outpatients suffering from PDU or PDA concerning different factors which were hypothesized to influence the development of agoraphobia. RESULTS: 'Earlier age of onset', 'fear of losing control' and 'chills or hot flushes' turned out to correlate statistically significantly with PDA, while 'chest pain or discomfort' occurred more often in PDU. LIMITATIONS: The present study used retrospective data. CONCLUSIONS: The results of this study suggest that the development of agoraphobia in panic disorder is influenced by specific variables and is not a purely coincidental process.

[Frequency of immunologic disorders in acute schizophrenia]. / Zur Häufigkeit immunologischer Auffälligkeiten bei akuten Schizophrenien.

Immunological examinations in schizophrenic patients have shown that there are many alterations in both arms of the immune system, i.e. cellular and humoral activities. The results are quite heterogeneous, as not even all schizophrenics show these pathological changes. Immunological findings are assumed to be etiopathogenetically related to the disease process or to be an epiphenomenon. The present study supposes that immunological alterations as they can be found during the course of schizophrenia may be an indicator for somatic vulnerability or an epiphenomenon. 60 male inpatients, fulfilling DSM-IV criteria of schizophrenia where examined during their acute phases of psychosis and during their phases of clinical improvement, by means of a serological profile including cellular and humoral parameters. The control group consisted of 42 healthy male volunteers. It was the aim of this study to find out if there were (a) overall differences in the immune profiles between patients and control group and (b) differences between different categories of schizophrenic disorder. During the acute phase nearly half of the schizophrenic patients showed pathologic immunological parameters, whereas none of the controls did. During the phase of clinical improvement the number of patients with normal immunological findings predominated. Furthermore there was a difference between the Paranoid and the Disorganized Subtype, the latter showing more immunological abnormalities. The results of this study give further support to the hypothesis that immunological aberrations should not be seen as closely etiopathogenetically related to schizophrenic disorders, but rather as an epiphenomenon (e.g. as a stress marker) and/or as indicators for somatic vulnerability.