Prediction of therapy response of breast cancer patients with machine learning based on clinical data and imaging data derived from breast [18F]FDG-PET/MRI.

PURPOSE: To evaluate if a machine learning prediction model based on clinical and easily assessable imaging features derived from baseline breast [18F]FDG-PET/MRI staging can predict pathologic complete response (pCR) in patients with newly diagnosed breast cancer prior to neoadjuvant system therapy (NAST). METHODS: Altogether 143 women with newly diagnosed breast cancer (54 ± 12 years) were retrospectively enrolled. All women underwent a breast [18F]FDG-PET/MRI, a histopathological workup of their breast cancer lesions and evaluation of clinical data. Fifty-six features derived from positron emission tomography (PET), magnetic resonance imaging (MRI), sociodemographic / anthropometric, histopathologic as well as clinical data were generated and used as input for an extreme Gradient Boosting model (XGBoost) to predict pCR. The model was evaluated in a five-fold nested-cross-validation incorporating independent hyper-parameter tuning within the inner loops to reduce the risk of overoptimistic estimations. Diagnostic model-performance was assessed by determining the area under the curve of the receiver operating characteristics curve (ROC-AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. Furthermore, feature importances of the XGBoost model were evaluated to assess which features contributed most to distinguish between pCR and non-pCR. RESULTS: Nested-cross-validation yielded a mean ROC-AUC of 80.4 ± 6.0% for prediction of pCR. Mean sensitivity, specificity, PPV, and NPV of 54.5 ± 21.3%, 83.6 ± 4.2%, 63.6 ± 8.5%, and 77.6 ± 8.1% could be achieved. Histopathological data were the most important features for classification of the XGBoost model followed by PET, MRI, and sociodemographic/anthropometric features. CONCLUSION: The evaluated multi-source XGBoost model shows promising results for reliably predicting pathological complete response in breast cancer patients prior to NAST. However, yielded performance is yet insufficient to be implemented in the clinical decision-making process.

Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?

OBJECTIVES: This study investigates the influence of normal cohort (NC) size and the impact of different NCs on automated MRI-based brain atrophy estimation. METHODS: A pooled NC of 3945 subjects (NCpool) was retrospectively created from five publicly available cohorts. Voxel-wise gray matter volume atrophy maps were calculated for 48 Alzheimer's disease (AD) patients (55-82 years) using veganbagel and dynamic normal templates with an increasing number of healthy subjects randomly drawn from NCpool (initially three, and finally 100 subjects). Over 100 repeats of the process, the mean over a voxel-wise standard deviation of gray matter z-scores was established and plotted against the number of subjects in the templates. The knee point of these curves was defined as the minimum number of subjects required for consistent brain atrophy estimation. Atrophy maps were calculated using each NC for AD patients and matched healthy controls (HC). Two readers rated the extent of mesiotemporal atrophy to discriminate AD/HC. RESULTS: The maximum knee point was at 15 subjects. For 21 AD/21 HC, a sufficient number of subjects were available in each NC for validation. Readers agreed on the AD diagnosis in all cases (Kappa for the extent of atrophy, 0.98). No differences in diagnoses between NCs were observed (intraclass correlation coefficient, 0.91; Cochran's Q, p = 0.19). CONCLUSION: At least 15 subjects should be included in age- and sex-specific normal templates for consistent brain atrophy estimation. In the study's context, qualitative interpretation of regional atrophy allows reliable AD diagnosis with a high inter-reader agreement, irrespective of the NC used. CLINICAL RELEVANCE STATEMENT: The influence of normal cohorts (NCs) on automated brain atrophy estimation, typically comparing individual scans to NCs, remains largely unexplored. Our study establishes the minimum number of NC-subjects needed and demonstrates minimal impact of different NCs on regional atrophy estimation. KEY POINTS: • Software-based brain atrophy estimation often relies on normal cohorts for comparisons. • At least 15 subjects must be included in an age- and sex-specific normal cohort. • Using different normal cohorts does not influence regional atrophy estimation.

Surgical and endovascular cerebral revascularization for cerebral vasculitis with inflammatory vessel stenosis: a case series.

Autoimmune vasculitides affect the cerebral vasculature significantly in a considerable number of cases. When immunosuppressive treatments fail to prevent stenosis in cerebral vessels, treatment options for affected patients become limited. In this case series, we present four cases of pharmacoresistant vasculitis with recurrent transient ischemic attacks (TIAs) or stroke successfully treated with either extracranial-intracranial (EC-IC) bypass surgery or endovascular stenting. Both rescue treatments were effective and safe in the selected cases. Our experience suggests that cases of pharmacoresistant cerebral vasculitis with recurrent stroke may benefit from rescue revascularization in combination with maximum medical management.

Brain-age prediction: A systematic comparison of machine learning workflows.

The difference between age predicted using anatomical brain scans and chronological age, i.e., the brain-age delta, provides a proxy for atypical aging. Various data representations and machine learning (ML) algorithms have been used for brain-age estimation. However, how these choices compare on performance criteria important for real-world applications, such as; (1) within-dataset accuracy, (2) cross-dataset generalization, (3) test-retest reliability, and (4) longitudinal consistency, remains uncharacterized. We evaluated 128 workflows consisting of 16 feature representations derived from gray matter (GM) images and eight ML algorithms with diverse inductive biases. Using four large neuroimaging databases covering the adult lifespan (total N = 2953, 18-88 years), we followed a systematic model selection procedure by sequentially applying stringent criteria. The 128 workflows showed a within-dataset mean absolute error (MAE) between 4.73-8.38 years, from which 32 broadly sampled workflows showed a cross-dataset MAE between 5.23-8.98 years. The test-retest reliability and longitudinal consistency of the top 10 workflows were comparable. The choice of feature representation and the ML algorithm both affected the performance. Specifically, voxel-wise feature spaces (smoothed and resampled), with and without principal components analysis, with non-linear and kernel-based ML algorithms performed well. Strikingly, the correlation of brain-age delta with behavioral measures disagreed between within-dataset and cross-dataset predictions. Application of the best-performing workflow on the ADNI sample showed a significantly higher brain-age delta in Alzheimer's and mild cognitive impairment patients compared to healthy controls. However, in the presence of age bias, the delta estimates in the patients varied depending on the sample used for bias correction. Taken together, brain-age shows promise, but further evaluation and improvements are needed for its real-world application.

Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate.

A wide homology between human and macaque striatum is often assumed as in both the striatum is involved in cognition, emotion and executive functions. However, differences in functional and structural organization between human and macaque striatum may reveal evolutionary divergence and shed light on human vulnerability to neuropsychiatric diseases. For instance, dopaminergic dysfunction of the human striatum is considered to be a pathophysiological underpinning of different disorders, such as Parkinson's disease (PD) and schizophrenia (SCZ). Previous investigations have found a wide similarity in structural connectivity of the striatum between human and macaque, leaving the cross-species comparison of its functional organization unknown. In this study, resting-state functional connectivity (RSFC) derived striatal parcels were compared based on their homologous cortico-striatal connectivity. The goal here was to identify striatal parcels whose connectivity is human-specific compared to macaque parcels. Functional parcellation revealed that the human striatum was split into dorsal, dorsomedial, and rostral caudate and ventral, central, and caudal putamen, while the macaque striatum was divided into dorsal, and rostral caudate and rostral, and caudal putamen. Cross-species comparison indicated dissimilar cortico-striatal RSFC of the topographically similar dorsal caudate. We probed clinical relevance of the striatal clusters by examining differences in their cortico-striatal RSFC and gray matter (GM) volume between patients (with PD and SCZ) and healthy controls. We found abnormal RSFC not only between dorsal caudate, but also between rostral caudate, ventral, central and caudal putamen and widespread cortical regions for both PD and SCZ patients. Also, we observed significant structural atrophy in rostral caudate, ventral and central putamen for both PD and SCZ while atrophy in the dorsal caudate was specific to PD. Taken together, our cross-species comparative results revealed shared and human-specific RSFC of different striatal clusters reinforcing the complex organization and function of the striatum. In addition, we provided a testable hypothesis that abnormalities in a region with human-specific connectivity, i.e., dorsal caudate, might be associated with neuropsychiatric disorders.

Automated age- and sex-specific volumetric estimation of regional brain atrophy: workflow and feasibility.

OBJECTIVES: An automated workflow for age- and sex-specific estimation of regional brain volume changes from structural MRI relative to a standard population is presented and evaluated for feasibility. METHODS: T1w MRI scans are preprocessed in a standardized way comprising gray matter (GM) segmentation, normalization, modulation, and spatial smoothing. Resulting GM images are then compared to precomputed age- and sex-specific GM templates derived from the population-based Nathan Kline Institute Rockland Sample, and voxel-wise z-maps are compiled. z-maps are color-coded and fused with the subject's T1w images. The rate of technical success of the proposed workflow was evaluated in 1330 subjects of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Furthermore, medial temporal atrophy (MTA) was assessed using the color-coded maps and with the MTA visual rating scale in these subjects. Sensitivities and specificity of color-coded maps and MTA scale were compared using McNemar's test. RESULTS: One test dataset was excluded due to severe motion artifacts. Out of the remaining 1329 datasets, atrophy map generation was successful in 1323 ADNI subjects (99.5%). Sensitivity for AD diagnosis (71.4 % vs. 53.3%, p < 0.0001 for left; 70.4% vs. 55.3%, p < 0.0001 for right hemisphere) and for MCI (45.4% vs. 17.4, p < 0.0001 for left; 43.5% vs. 14.6%, p < 0.0001 for right hemisphere) based on medial temporal atrophy assessment in color-coded maps was significantly higher than for MTA visual rating scale, while specificity was lower (78.4% vs. 93.8%, p < 0.0001 for left; 79.4% vs. 95.8%, p < 0.0001 for right hemisphere). The workflow is named veganbagel and is published as open-source software with an integrated PACS interface. CONCLUSIONS: Automated brain volume change estimation with the proposed workflow is feasible and technically dependable. It provides high potential for radiologic assessment of brain volume changes and neurodegenerative diseases. KEY POINTS: • A workflow combining techniques from voxel-based morphometry and population-based neuroimaging data is feasible and technically highly dependable. • The workflow is provided as open-source software, named veganbagel. • Sensitivity of medial temporal atrophy assessment in atrophy maps from veganbagel exceeds the sensitivity of MTA visual rating scale for the diagnosis of Alzheimer's disease.

Within- and across-network alterations of the sensorimotor network in Parkinson's disease.

PURPOSE: Parkinson's disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. METHODS: Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. RESULTS: There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. CONCLUSION: PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

Functional Connectivity Changes of Key Regions for Motor Initiation in Parkinson's Disease.

Akinesia, a cardinal symptom of Parkinson's disease, has been linked to abnormal activation in putamen and posterior medial frontal cortex (pMFC). However, little is known whether clinical severity of akinesia is linked to dysfunctional connectivity of these regions. Using a seed-based approach, we here investigated resting-state functional connectivity (RSFC) of putamen, pMFC and primary motor cortex (M1) in 60 patients with Parkinson's disease on regular medication and 72 healthy controls. We found that in patients putamen featured decreases of connectivity for a number of cortical and subcortical areas engaged in sensorimotor and cognitive processing. In contrast, the pMFC showed reduced connectivity with a more focal cortical network involved in higher-level motor-cognition. Finally, M1 featured a selective disruption of connectivity in a network specifically connected with M1. Correlating clinical impairment with connectivity changes revealed a relationship between akinesia and reduced RSFC between pMFC and left intraparietal lobule (IPL). Together, the present study demonstrated RSFC decreases in networks for motor initiation and execution in Parkinson's disease. Moreover, results suggest a relationship between pMFC-IPL decoupling and the manifestation of akinetic symptoms.

Mechanical thrombectomy in acute middle cerebral artery M2 segment occlusion with regard to vessel involvement.

BACKGROUND: Endovascular treatment (EVT) is an established procedure in patients with acute ischemic stroke due to occlusion of the proximal M1-segment of middle cerebral artery. The assessment of distal thrombectomy in daily clinical routine has not yet been sufficiently evaluated. METHODS: Patients with M2-segment-occlusions treated by EVT in the local department (January 2012-December 2017) were included (n = 57, mean National-Institutes-of-Health-Stroke-Scale of 11, range 0-20). Patients were grouped according to localization of M2-occlusion (Cohort A (n = 14): central region only, B (n = 24): central region and involvement of frontal vessels, C (n = 19): parietal, occipital, and/or temporal vessels). Differences in proximal (M2-trunk, n = 34) and distal (M2-branches, n = 23) occlusions were also examined. Reperfusion (Thrombolysis-In-Cerebral-Infarction (TICI)), early clinical outcome at discharge (modified Rankin Scale (mRS)), and complications (hemorrhage, new emboli) were noted. RESULT: Successful reperfusion (TICI2b-3) was found in 49 patients (86.0%). Favorable early clinical outcome (mRS0-2) was achieved in n = 19 (37.7%). Compared to admission, mRS at discharge improved significantly (median (admission) 5 vs. median (discharge) 4, p < 0.001). Early clinical outcome was more favorable in patients with better reperfusion (TICI2b-3: mean mRS 3 ± 1.7 vs. TICI0-2a: mean mRS 4.4 ± 1.4, p = 0.037). Six (10.5%) patients suffered from symptomatic intracranial hemorrhage during treatment or hospitalization. Four patients died (7.0%). No significant differences in favorable clinical outcome (mRS ≤ 2: Cohort A 42.9%, B 50.0%, C 16.7%, p = 0.4; χ2-test) or periinterventional complications were found with regard to vessel involvement. CONCLUSION: EVT in patients with acute M2-occlusion is safe and leads to a significant clinical improvement at discharge. No significant differences in clinical outcome or complications were found with regard to the localization of the M2-occlusion.

Potential of a machine-learning model for dose optimization in CT quality assurance.

OBJECTIVES: To evaluate machine learning (ML) to detect chest CT examinations with dose optimization potential for quality assurance in a retrospective, cross-sectional study. METHODS: Three thousand one hundred ninety-nine CT chest examinations were used for training and testing of the feed-forward, single hidden layer neural network (January 2016-December 2017, 60% male, 62 ± 15 years, 80/20 split). The model was optimized and trained to predict the volumetric computed tomography dose index (CTDIvol) based on scan patient metrics (scanner, study description, protocol, patient age, sex, and water-equivalent diameter (DW)). The root mean-squared error (RMSE) was calculated as performance measurement. One hundred separate, consecutive chest CTs were used for validation (January 2018, 60% male, 63 ± 16 years), independently reviewed by two blinded radiologists with regard to dose optimization, and used to define an optimal cutoff for the model. RESULTS: RMSE was 1.71, 1.45, and 1.52 for the training, test, and validation dataset, respectively. The scanner and DW were the most important features. The radiologists found dose optimization potential in 7/100 of the validation cases. A percentage deviation of 18.3% between predicted and actual CTDIvol was found to be the optimal cutoff: 8/100 cases were flagged as suboptimal by the model (range 18.3-53.2%). All of the cases found by the radiologists were identified. One examination was flagged only by the model. CONCLUSIONS: ML can comprehensively detect CT examinations with dose optimization potential. It may be a helpful tool to simplify CT quality assurance. CT scanner and DW were most important. Final human review remains necessary. A threshold of 18.3% between the predicted and actual CTDIvol seems adequate for CT quality assurance. KEY POINTS: • Machine learning can be integrated into CT quality assurance to improve retrospective analysis of CT dose data. • Machine learning may help to comprehensively detect dose optimization potential in chest CT, but an individual review of the results by an experienced radiologist or radiation physicist is required to exclude false-positive findings.

One-year single-center experience with the Aperio thrombectomy device in large vessel occlusion in the anterior circulation: safety, efficacy, and clinical outcome.

BACKGROUND AND PURPOSE: The Aperio thrombectomy device (Aperio) is a stent retriever designed to achieve rapid and substantial flow restoration in acute ischemic stroke due to large-vessel occlusions (LVOs). We evaluated the safety and efficacy of the Aperio device and compared it with published data of established stent retrievers. METHODS: We retrospectively analyzed institutional data of consecutive stroke procedures in patients with LVO in the anterior circulation that were treated between January 2017 and December 2017 with the Aperio. Reperfusion rate regarding to the extended thrombolysis in cerebral infarction scale (eTICI), procedural times, early clinical outcome, and complications were documented. RESULTS: Eighty-two patients were treated by using the Aperio in LVO in the anterior circulation. Median age was 77 (± 12) years (w = 59.8%). Median Baseline National Institutes of Health Stroke Scale (NIHSS) score was 14. Fifty-three (64.6%) patients received intravenous thrombolysis. Successful recanalization (eTICI≥2b) was achieved in 85.3%. Mean time from groin puncture to final recanalization was 52.3 ± 34.8 min. Embolization to new territories occurred in one case. Symptomatic intracranial hemorrhage within 24 h was observed in six patients (7.3%). Twenty-eight (41.2%) out of 68 patients available for assessment of functional outcome at 3 months achieved favorable outcome (mRS 0-2). CONCLUSION: The Aperio stent retriever mechanical thrombectomy device demonstrated high rates of successful reperfusion and a good safety profile in patients with acute ischemic stroke due to LVO in the anterior circulation.

A Retrospective Single-Center Case Series of Direct Aspiration Thrombectomy as First-Line Approach in Ischemic Stroke and Review of the Literature.

INTRODUCTION: The benefit of the direct aspiration thrombectomy (ADAPT) technique for the treatment of ischemic stroke due to large vessel occlusion are challenged after publishing of the ASTER trial that failed to show superiority of ADAPT compared to stent retriever. Aim of the present single-center study was a retrospective evaluation of the ADAPT technique comparing our results with literature. MATERIAL/METHODS: We retrospectively analyzed institutional data of stroke procedures in patients with mainstem occlusion of the middle cerebral artery treated between November 2016 and December 2017 with an initial attempt of manual thrombaspiration. Reperfusion rate (thrombolysis in cerebral infarction), procedural times, early clinical outcome and complications were recorded. RESULTS: Forty patients were treated by using direct thrombaspiration in middle cerebral artery mainstem occlusion. Median age was 67.5 (±17.8) years (m = 27.5%). Median Baseline National Institutes of Health Stroke Scale score was 12 (IQR 7) preintervention and 3 (IQR 11) postintervention. Twenty-eight (70%) patients received intravenous thrombolysis. Successful recanalization (modified thrombolysis in cerebral infarction ≥ 2b) could be achieved in 85% with direct aspiration alone. Mean time from groin puncture to recanalization was 25.2 ± 14.3 minutes. Embolization to new territories occurred in 1 of 40 (2.5%) cases and symptomatic intracranial hemorrhage in 3 of 40 (7.5%). Nineteen of 40 (47.5%) patients achieved favorable outcome (modified Rankin scale 0-2) at discharge. CONCLUSIONS: The ADAPT technique presented as a safe and efficient first-line recanalization strategy with good clinical outcome for treatment of acute ischemic stroke resulting from large vessel occlusions in this single-center study and review of the literature. However, the concept of ADAPT as an equivalent first-line approach to stent retriever thrombectomy has to be proven by future randomized studies.

Prediction of outcome after aneurysmal subarachnoid haemorrhage using data from patient admission.

OBJECTIVES: The pathogenesis leading to poor functional outcome after aneurysmal subarachnoid haemorrhage (aSAH) is multifactorial and not fully understood. We evaluated a machine learning approach based on easily determinable clinical and CT perfusion (CTP) features in the course of patient admission to predict the functional outcome 6 months after ictus. METHODS: Out of 630 consecutive subarachnoid haemorrhage patients (2008-2015), 147 (mean age 54.3, 66.7% women) were retrospectively included (Inclusion: aSAH, admission within 24 h of ictus, CTP within 24 h of admission, documented modified Rankin scale (mRS) grades after 6 months. Exclusion: occlusive therapy before first CTP, previous aSAH, CTP not evaluable). A random forests model with conditional inference trees was optimised and trained on sex, age, World Federation of Neurosurgical Societies (WFNS) and modified Fisher grades, aneurysm in anterior vs. posterior circulation, early external ventricular drainage (EVD), as well as MTT and Tmax maximum, mean, standard deviation (SD), range, 75th quartile and interquartile range to predict dichotomised mRS (≤ 2; > 2). Performance was assessed using the balanced accuracy over the training and validation folds using 20 repeats of 10-fold cross-validation. RESULTS: In the final model, using 200 trees and the synthetic minority oversampling technique, median balanced accuracy was 84.4% (SD 0.7) over the training folds and 70.9% (SD 1.2) over the validation folds. The five most important features were the modified Fisher grade, age, MTT range, WFNS and early EVD. CONCLUSIONS: A random forests model trained on easily determinable features in the course of patient admission can predict the functional outcome 6 months after aSAH with considerable accuracy. KEY POINTS: • Features determinable in the course of admission of a patient with aneurysmal subarachnoid haemorrhage (aSAH) can predict the functional outcome 6 months after the occurrence of aSAH. • The top five predictive features were the modified Fisher grade, age, the mean transit time (MTT) range from computed tomography perfusion (CTP), the WFNS grade and the early necessity for an external ventricular drainage (EVD). • The range between the minimum and the maximum MTT may prove to be a valuable biomarker for detrimental functional outcome.

The Cytoarchitecture of Domain-specific Regions in Human High-level Visual Cortex.

A fundamental hypothesis in neuroscience proposes that underlying cellular architecture (cytoarchitecture) contributes to the functionality of a brain area. However, this hypothesis has not been tested in human ventral temporal cortex (VTC) that contains domain-specific regions causally involved in perception. To fill this gap in knowledge, we used cortex-based alignment to register functional regions from living participants to cytoarchitectonic areas in ex vivo brains. This novel approach reveals 3 findings. First, there is a consistent relationship between domain-specific regions and cytoarchitectonic areas: each functional region is largely restricted to 1 cytoarchitectonic area. Second, extracting cytoarchitectonic profiles from face- and place-selective regions after back-projecting each region to 20-µm thick histological sections indicates that cytoarchitectonic properties distinguish these regions from each other. Third, some cytoarchitectonic areas contain more than 1 domain-specific region. For example, face-, body-, and character-selective regions are located within the same cytoarchitectonic area. We summarize these findings with a parsimonious hypothesis incorporating how cellular properties may contribute to functional specialization in human VTC. Specifically, we link computational principles to correlated axes of functional and cytoarchitectonic segregation in human VTC, in which parallel processing across domains occurs along a lateral-medial axis while transformations of information within domain occur along an anterior-posterior axis.

Two New Cytoarchitectonic Areas on the Human Mid-Fusiform Gyrus.

Areas of the fusiform gyrus (FG) within human ventral temporal cortex (VTC) process high-level visual information associated with faces, limbs, words, and places. Since classical cytoarchitectonic maps do not adequately reflect the functional and structural heterogeneity of the VTC, we studied the cytoarchitectonic segregation in a region, which is rostral to the recently identified cytoarchitectonic areas FG1 and FG2. Using an observer-independent and statistically testable parcellation method, we identify 2 new areas, FG3 and FG4, in 10 human postmortem brains on the mid-FG. The mid-fusiform sulcus reliably identifies the cytoarchitectonic transition between FG3 and FG4. We registered these cytoarchitectonic areas to the common reference space of the single-subject Montreal Neurological Institute (MNI) template and generated probability maps, which reflect the intersubject variability of both areas. Future studies can relate in vivo neuroimaging data with these microscopically defined cortical areas to functional parcellations. We discuss these results in the context of both large-scale functional maps and fine-scale functional clusters that have been identified within the human VTC. We propose that our observer-independent cytoarchitectonic parcellation of the FG better explains the functional heterogeneity of the FG compared with the homogeneity of classic cytoarchitectonic maps.

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc.

Gadolinium Brain Deposition after Macrocyclic Gadolinium Administration: A Pediatric Case-Control Study.

Purpose To determine whether signal intensity (SI) in T1 sequences as a potential indicator of gadolinium deposition increases after repeated administration of the macrocyclic gadolinium-based contrast agents (GBCAs) gadoteridol and gadoterate meglumine in a pediatric cohort. Materials and Methods This retrospective case-control study of children with brain tumors who underwent nine or more contrast material-enhanced brain magnetic resonance (MR) imaging studies from 2008 to 2015 was approved by the local ethics board. Informed consent was obtained for MR imaging. Twenty-four case patients aged 5-18 years and appropriate control patients with nonpathologic MR neuroimaging findings (and no GBCA administration), matched for age and sex, were inculded. SI was measured on unenhanced T1-weighted MR images for the following five regions of interest (ROIs): the dentate nucleus (DN), pons, substantia nigra (SN), pulvinar thalami, and globus pallidus (GP). Paired t tests were used to compare SI and SI ratios (DN to pons, GP to thalamus) between case patients and control patients. Pearson correlations between relative signal changes and the number of GBCA administrations and total GBCA dose were calculated. Results The mean number of GBCA administrations was 14.2. No significant differences in mean SI for any ROI and no group differences were found when DN-to-pons and GP-to-pulvinar ratios were compared (DN-to-pons ratio in case patients: mean, 1.0083 ± 0.0373 [standard deviation]; DN-to-pons ratio in control patients: mean, 1.0183 ± 0.01917; P = .37; GP-to-pulvinar ratio in case patients: mean, 1.1335 ± 0.04528; and GP-to-pulvinar ratio in control patients: mean, 1.1141 ± 0.07058; P = .29). No correlation was found between the number of GBCA administrations or the total amount of GBCA administered and signal change for any ROI. (Number of GBCA applications: DN: r = -0.254, P = .31; pons: r = -0.097, P = .65; SN: r = -0.194, P = .38; GP: r = -0.175, P = .41; pulvinar: r = -0.067, P = .75; total amount of administered GBCA: DN: r = 0.091, P = .72; pons: r = 0.106, P = .62; SN: r = -0.165, P = .45; GP: r = 0.111, P = .61; pulvinar: r = 0.173, P = .42.) Conclusion Multiple intravenous administrations of these macrocyclic GBCAs in children were not associated with a measurable increase in SI in T1 sequences as an indicator of brain gadolinium deposition detectable by using MR imaging. Additional imaging and pathologic studies are needed to confirm these findings. © RSNA, 2017 Online supplemental material is available for this article.

Dynamics of cerebral perfusion deficits after aneurysmal SAH - predictive value of early MTT for subsequent MTT deterioration.

BACKGROUND AND PURPOSE: The pathogenesis of poor functional outcome after aneurysmal subarachnoid hemorrhage (aSAH) is not fully understood. Microcirculatory dysfunction, which can be indirectly measured by CT perfusion (CTP), is assumed to play a central role. We evaluated the predictive value of early changes in microcirculation for secondary critical perfusion changes. MATERIALS AND METHODS: Out of 351 consecutive aSAH patients, 166 patients with ≥1 CTP within 72h of ictus (early CTP) and ≥3 CTPs in total were included in the retrospective analysis (53.2±12.4years of age). Receiver-operating-characteristic (ROC) analysis was performed to identify the mean transit time (MTT) threshold in early CTP with the highest sensitivity and specificity for predicting secondary critical perfusion changes >72h after ictus. The odds ratio was calculated and the threshold for the highest odds ratio was determined. RESULTS: Secondary critical perfusion changes were observed in 67/166 patients (40.4%). An early MTT 1.3 times the mean normal MTT could predict those changes with an odds ratio of 2.67 (sensitivity 67.2%, specificity 56.6%). Shifting the threshold to 1.26 times the mean normal MTT resulted in an odds ratio of 3.56 (sensitivity 79.1%, specificity 48.5%). CONCLUSIONS: Early MTT is predictive of secondary critical perfusion changes, which could have applications for neuromonitoring and treatment.

Optimizing radiation exposure in screening of body packing: image quality and diagnostic acceptability of an 80 kVp protocol with automated tube current modulation.

The aim of this study was to evaluate the objective and subjective image quality of a novel computed tomography (CT) protocol with reduced radiation dose for body packing with 80 kVp and automated tube current modulation (ATCM) compared to a standard body packing CT protocol. 80 individuals who were examined between March 2012 and July 2015 in suspicion of ingested drug packets were retrospectively included in this study. Thirty-one CT examinations were performed using ATCM and a fixed tube voltage of 80 kVp (group A). Forty-nine CT examinations were performed using a standard protocol with a tube voltage of 120 kVp and a fixed tube current time product of 40 mAs (group B). Subjective and objective image quality and visibility of drug packets were assessed. Radiation exposure of both protocols was compared. Contrast-to-noise ratio (group A: 0.56 ± 0.36; group B: 1.13 ± 0.91) and Signal-to-noise ratio (group A: 3.69 ± 0.98; group B: 7.08 ± 2.67) were significantly lower for group A compared to group B (p < 0.001). Subjectively, image quality was decreased for group A compared to group B (2.5 ± 0.8 vs. 1.2 ± 0.4; p < 0.001). Attenuation of body packets was higher with the new protocol (group A: 362.2 ± 70.3 Hounsfield Units (HU); group B: 210.6 ± 60.2 HU; p = 0.005). Volumetric Computed Tomography Dose Index (CTDIvol) and Dose Length Product (DLP) were significantly lower in group A (CTDIvol 2.2 ± 0.9 mGy, DLP 105.7 ± 52.3 mGycm) as compared to group B (CTDIvol 2.7 ± 0.1 mGy, DLP 126.0 ± 9.7 mGycm, p = 0.002 and p = 0.01). The novel 80 kVp CT protocol with ATCM leads to a significant dose reduction compared to a standard CT body packing protocol. The novel protocol led to a diagnostic image quality and cocaine body packets were reliably detected due to the high attenuation.

Functional Connectivity Differences of the Subthalamic Nucleus Related to Parkinson's Disease.

A typical feature of Parkinson's disease (PD) is pathological activity in the subthalamic nucleus (STN). Here, we tested whether in patients with PD under dopaminergic treatment functional connectivity of the STN differs from healthy controls (HC) and whether some brain regions show (anti-) correlations between functional connectivity with STN and motor symptoms. We used functional magnetic resonance imaging to investigate whole-brain resting-state functional connectivity with STN in 54 patients with PD and 55 HC matched for age, gender, and within-scanner motion. Compared to HC, we found attenuated negative STN-coupling with Crus I of the right cerebellum and with right ventromedial prefrontal regions in patients with PD. Furthermore, we observed enhanced negative STN-coupling with bilateral intraparietal sulcus/superior parietal cortex, right sensorimotor, right premotor, and left visual cortex compared to HC. Finally, we found a decline in positive STN-coupling with the left insula related to severity of motor symptoms and a decline of inter-hemispheric functional connectivity between left and right STN with progression of PD-related motor symptoms. Motor symptom related uncoupling of the insula, a key region in the saliency network and for executive function, from the STN might be associated with well-known executive dysfunction in PD. Moreover, uncoupling between insula and STN might also induce an insufficient setting of thresholds for the discrimination between relevant and irrelevant salient environmental stimuli, explaining observations of disturbed response control in PD. In sum, motor symptoms in PD are associated with a reduced coupling between STN and a key region for executive function.