Toward Foundation Models in Radiology? Quantitative Assessment of GPT-4V's Multimodal and Multianatomic Region Capabilities.

Background Large language models have already demonstrated potential in medical text processing. GPT-4V, a large vision-language model from OpenAI, has shown potential for medical imaging, yet a quantitative analysis is lacking. Purpose To quantitatively assess the performance of GPT-4V in interpreting radiologic images using unseen data.

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).

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.

Application of A U-Net for Map-like Segmentation and Classification of Discontinuous Fibrosis Distribution in Gd-EOB-DTPA-Enhanced Liver MRI.

We aimed to evaluate whether U-shaped convolutional neuronal networks can be used to segment liver parenchyma and indicate the degree of liver fibrosis/cirrhosis at the voxel level using contrast-enhanced magnetic resonance imaging. This retrospective study included 112 examinations with histologically determined liver fibrosis/cirrhosis grade (Ishak score) as the ground truth. The T1-weighted volume-interpolated breath-hold examination sequences of native, arterial, late arterial, portal venous, and hepatobiliary phases were semi-automatically segmented and co-registered.

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

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.

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.