Deep brain stimulation: Connectivity profile for bradykinesia alleviation.

OBJECTIVE: Subthalamic deep brain stimulation may alleviate bradykinesia in Parkinson patients. Research suggests that this stimulation effect may be mediated by brain networks like the corticocerebellar loop. This study investigated the connectivity between stimulation sites and cortical and subcortical structures to identify connections for effective stimulation. METHODS: We retrospectively investigated 21 patients with Parkinson disease with bilateral subthalamic deep brain stimulation. Stimulation effectiveness in reducing bradykinesia, tremor, and rigidity was evaluated for each electrode contact in brain hemispheres contralateral to the affected hemibody. Dysarthric side effects were also examined. Probabilistic tractography based on diffusion-weighted imaging was performed in individual patient-specific brains using electrode contacts as seeds. Connectivity profiles of contacts with effective and noneffective stimulation were compared. RESULTS: Connectivity profiles of effective and noneffective contacts differed. Moreover, the connectivity profile for bradykinesia differed from that for rigidity, tremor, or dysarthria. Regarding bradykinesia, effective contacts were significantly more often connected with the ipsilateral superior cerebellar peduncle and the ipsilateral dentate nucleus, which correspond to the ipsilateral portion of the cerebellothalamocortical pathway. Rigidity was mitigated by stimulation of ascending brainstem and intralaminar thalamic connections. Tremor alleviation was related to connections with the internal capsule (anterior limb) and the pallidum. Dysarthric side effects were associated with connections to the supplementary motor area and the decussating cerebellothalamocortical pathway. INTERPRETATION: Whereas bradykinesia seems to be mitigated by stimulation of the ascending, ipsilateral cerebellothalamocortical pathway, stimulation of the descending corticopontocerebellar pathway may be ineffective. Rigidity, tremor, and dysarthric side effects seem to be influenced by different neural networks. ANN NEUROL 2019;85:852-864.

Limited capability of MRI radiomics to predict primary tumor histology of brain metastases in external validation.

Background: Growing research demonstrates the ability to predict histology or genetic information of various malignancies using radiomic features extracted from imaging data. This study aimed to investigate MRI-based radiomics in predicting the primary tumor of brain metastases through internal and external validation, using oversampling techniques to address the class imbalance. Methods: This IRB-approved retrospective multicenter study included brain metastases from lung cancer, melanoma, breast cancer, colorectal cancer, and a combined heterogenous group of other primary entities (5-class classification). Local data were acquired between 2003 and 2021 from 231 patients (545 metastases). External validation was performed with 82 patients (280 metastases) and 258 patients (809 metastases) from the publicly available Stanford BrainMetShare and the University of California San Francisco Brain Metastases Stereotactic Radiosurgery datasets, respectively. Preprocessing included brain extraction, bias correction, coregistration, intensity normalization, and semi-manual binary tumor segmentation. Two-thousand five hundred and twenty-eight radiomic features were extracted from T1w (±â€…contrast), fluid-attenuated inversion recovery (FLAIR), and wavelet transforms for each sequence (8 decompositions). Random forest classifiers were trained with selected features on original and oversampled data (5-fold cross-validation) and evaluated on internal/external holdout test sets using accuracy, precision, recall, F1 score, and area under the receiver-operating characteristic curve (AUC). Results: Oversampling did not improve the overall unsatisfactory performance on the internal and external test sets. Incorrect data partitioning (oversampling before train/validation/test split) leads to a massive overestimation of model performance. Conclusions: Radiomics models' capability to predict histologic or genomic data from imaging should be critically assessed; external validation is essential.

Head-to-Head Comparison of Dual-Source and Split-Beam Filter Multi-Energy CT versus SPECT/CT for Assessing Lobar Lung Perfusion in Emphysema.

Purpose: To evaluate dual-source and split-beam filter multi-energy chest CT in assessing pulmonary perfusion on a lobar level in patients with lung emphysema, using perfusion SPECT as the reference standard. Materials and Methods: Patients with emphysema evaluated for lung volume reduction therapy between May 2016 and February 2021 were retrospectively included. All patients underwent SPECT and either dual-source or split-beam filter (SBF) multi-energy CT. To calculate the fractional lobar lung perfusion (FLLP), SPECT acquisitions were co-registered with chest CT scans (hereafter, SPECT/CT) and semi-manually segmented. For multi-energy CT scans, lung lobes were automatically segmented using a U-Net model. Segmentations were manually verified. The FLLP was derived from iodine maps computed from the multi-energy data. Statistical analysis included Pearson and intraclass correlation coefficients and Bland-Altman analysis. Results: Fifty-nine patients (30 male, 29 female; 31 underwent dual-source CT, 28 underwent SBF CT; mean age for all patients, 67 years ± 8 [SD]) were included. Both multi-energy methods significantly correlated with the SPECT/CT acquisitions for all individual lobes (P < .001). Pearson correlation concerning all lobes combined was significantly better for dual-source (r = 0.88) than for SBF multi-energy CT (r = 0.78; P = .006). On the level of single lobes, Pearson correlation coefficient differed for the right upper lobe only (dual-source CT, r = 0.88; SBF CT, r = 0.58; P = .008). Conclusion: Dual-source and SBF multi-energy CT accurately assessed lung perfusion on a lobar level in patients with emphysema compared with SPECT/CT. The overall correlation was higher for dual-source multi-energy CT.Keywords: Chronic Obstructive Pulmonary Disease, Comparative Studies, Computer Applications, CT Spectral Imaging, Image Postprocessing, Lung, Pulmonary Perfusion© RSNA, 2023.

Structural Connectivity Patterns of Side Effects Induced by Subthalamic Deep Brain Stimulation for Parkinson's Disease.

Background: Tractography based on diffusion-weighted magnetic resonance imaging (DWI) models the structural connectivity of the human brain. Deep brain stimulation (DBS) targeting the subthalamic nucleus is an effective treatment for advanced Parkinson's disease, but may induce adverse effects. This study investigated the relationship between structural connectivity patterns of DBS electrodes and stimulation-induced side effects. Materials and Methods: Twenty-one patients with Parkinson's disease treated with bilateral subthalamic DBS were examined. Overall, 168 electrode contacts were categorized as inducing or noninducing depending on their capability for inducing side effects such as motor effects, paresthesia, dysarthria, oculomotor effects, hyperkinesia, and other complications as assessed during the initial programming session. Furthermore, the connectivity of each contact with target regions was evaluated by probabilistic tractography based on DWI. Finally, stimulation sites and structural connectivity patterns of inducing and noninducing contacts were compared. Results: Inducing contacts differed across the various side effects and from those mitigating Parkinson's symptoms. Although contacts showed a largely overlapping spatial distribution within the subthalamic region, they could be distinguished by their connectivity patterns. In particular, inducing contacts were more likely connected with supplementary motor areas (hyperkinesia, dysarthria), frontal cortex (oculomotor), fibers of the internal capsule (paresthesia), and the basal ganglia-thalamo-cortical circuitry (dysarthria). Discussion: Side effects induced by DBS seem to be associated with distinct connectivity patterns. Cerebellar connections are hardly associated with side effects, although they seem relevant for mitigating motor symptoms in Parkinson's disease. A symptom-specific, connectivity-based approach for target planning in DBS may enhance treatment outcomes and reduce adverse effects. Impact statement Tractography based on diffusion-weighted magnetic resonance imaging has become a prominent technique for investigating the connectivity of human brain networks in vivo. However, the relationship between structural connections and brain function is still hardly known. The present study examined the relationship between adverse behavioral effects induced by deep brain stimulation (DBS) and tractography patterns in individual brains. The results suggest that DBS-based side effects depend on the structural connections of electrode contacts rather than their location. Network-based target planning in DBS may improve treatment by avoiding side effects. Moreover, the adopted approach may serve as a paragon for investigating structure/function relationships.