Deep learning-assistance significantly increases the detection sensitivity of neurosurgery residents for intracranial aneurysms in subarachnoid hemorrhage.

Objective: The purpose of this study was to evaluate the effectiveness of a deep learning model (DLM) in improving the sensitivity of neurosurgery residents to detect intracranial aneurysms on CT angiography (CTA) in patients with aneurysmal subarachnoid hemorrhage (aSAH).

Methods: In this diagnostic accuracy study, a set of 104 CTA scans of aSAH patients containing a total of 126 aneurysms were presented to three blinded neurosurgery residents (a first-year, third-year, and fifth-year resident), who individually assessed them for aneurysms. After the initial reading, the residents were given the predictions of a dedicated DLM previously established for automated detection and segmentation of intracranial aneurysms.

Immediate angiographic control after intra-arterial nimodipine administration underestimates the vasodilatory effect.

Intra-arterial nimodipine administration is a widely used rescue therapy for cerebral vasospasm. Although it is known that its effect sets in with delay, there is little evidence in current literature. Our aim was to prove that the maximal vasodilatory effect is underestimated in direct angiographic controls.

Safety and efficacy of the fourth-generation Acandis Acclino flex plus stent for the treatment of complex intracranial aneurysms.

Objective: The low-profile Acandis Acclino flex plus (AFP) is a fourth-generation laser-cut microstent with a flexible structure designed for the treatment of a wide variety of aneurysms. We report our single-center experience with this device in the treatment of complex aneurysms.

Methods: Twenty-eight patients were treated with the Acclino flex plus for 28 aneurysms.

Metal artifact reduction in patients with total hip replacements: evaluation of clinical photon counting CT using virtual monoenergetic images.

Objectives: To investigate photon-counting CT (PCCT)-derived virtual monoenergetic images (VMI) for artifact reduction in patients with unilateral total hip replacements (THR).

Methods: Forty-two patients with THR and portal-venous phase PCCT of the abdomen and pelvis were retrospectively included. For the quantitative analysis, region of interest (ROI)-based measurements of hypodense and hyperdense artifacts, as well as of artifact-impaired bone and the urinary bladder, were conducted, and corrected attenuation and image noise were calculated as the difference of attenuation and noise between artifact-impaired and normal tissue.

Virtual non-contrast reconstructions improve differentiation between vascular enhancement and calcifications in stereotactic planning CT scans of cystic intracranial tumors.

Purpose: To assess the diagnostic value of spectral-detector CT (SDCT) derived virtual non-contrast images (VNC) for differentiation between vascular enhancement and wall calcifications of cystic intracranial tumors in contrast-enhanced stereotactic planning examinations.

Method: 48 patients with cystic intracranial tumors who underwent stereotactic SDCT examinations between 02/2017 and 02/2020 were retrospectively included. In each patient, two separate hyperattenuating structures along the cyst wall were defined as either enhancement or calcification, respectively, using reference MRI examinations.

Differentiation of Intracerebral Tumor Entities with Quantitative Contrast Attenuation and Iodine Mapping in Dual-Layer Computed Tomography.

Purpose: To investigate if quantitative contrast enhancement and iodine mapping of common brain tumor (BT) entities may correctly differentiate between tumor etiologies in standardized stereotactic CT protocols. Material and Methods: A retrospective monocentric study of 139 consecutive standardized dual-layer dual-energy CT (dlDECT) scans conducted prior to the stereotactic needle biopsy of untreated primary brain tumor lesions. Attenuation of contrast-enhancing BT was derived from polyenergetic images as well as spectral iodine density maps (IDM) and their contrast-to-noise-ratios (CNR) were determined using ROI measures in contrast-enhancing BT and healthy contralateral white matter.

MRI correlates of motoneuron loss in SMA.

Background: Magnetic resonance imaging (MRI) is currently explored as supplemental tool to monitor disease progression and treatment response in various neuromuscular disorders. We here assessed the utility of a multi-parametric magnetic resonance imaging (MRI) protocol including quantitative water T mapping, Dixon-based proton density fat fraction (PDFF) estimation and diffusion tensor imaging (DTI) to detect loss of spinal motor neurons and subsequent muscle damage in adult SMA patients.

Methods: Sixteen SMA patients and 13 age-matched controls were enrolled in this prospective, longitudinal study.

Metal implants on abdominal CT: does split-filter dual-energy CT provide additional value over iterative metal artifact reduction?

Purpose: To assess image quality and metal artifact reduction in split-filter dual-energy CT (sfDECT) of the abdomen with hip or spinal implants using virtual monoenergetic images (VMI) and iterative metal artifact reduction algorithm (iMAR).

Methods: 102 portal-venous abdominal sfDECTs of patients with hip (n = 71) or spinal implants (n = 31) were included in this study. Images were reconstructed as 120kVp-equivalent images (Mixed) and VMI (40-190 keV), with and without iMAR.

Imaging of the extracranial internal carotid artery in acute ischemic stroke: assessment of stenosis, plaques, and image quality using relaxation-enhanced angiography without contrast and triggering (REACT).

Background: In stroke magnetic resonance imaging (MRI), contrast-enhanced magnetic resonance angiography (CE-MRA) is the clinical standard to depict extracranial arteries but native MRA techniques are of increased interest to facilitate clinical practice. The purpose of this study was to assess the detection of extracranial internal carotid artery (ICA) stenosis and plaques as well as the image quality of cervical carotid arteries between a novel flow-independent relaxation-enhanced angiography without contrast and triggering (REACT) sequence and CE-MRA in acute ischemic stroke (AIS).

Methods: In this retrospective, single-center study, 105 consecutive patients (65.

Imaging of the Left Atrial Appendage Before Occluder Device Placement: Evaluation of Virtual Monoenergetic Images in a Single-Bolus Dual-Phase Protocol.

Purpose: Preimplantation cardiac computed tomography (CT) for assessment of the left atrial appendage (LAA) enables correct sizing of the device and the detection of contraindications, such as thrombi. In the arterial phase, distinction between false filling defects and true thrombi can be hampered by insufficient contrast medium distribution. A delayed scan can be used to further differentiate both conditions, but contrast in these acquisitions is relatively lower.

Virtual versus true non-contrast images of the brain from spectral detector CT: comparison of attenuation values and image quality.

Background: Prior studies focused on utilization of dual-energy computed tomography (DECT) to better detect intracranial pathology and to reduce artifacts. It is still unclear whether virtual non-contrast (VNC) images of DECT can replace true non-contrast (TNC) images.

Purpose: To compare attenuation values and image quality of VNC images to TNC images of the brain, obtained using spectral detector CT (SDCT).

Virtual Non-Contrast versus True Non-Contrast Computed Tomography: Initial Experiences with a Photon Counting Scanner Approved for Clinical Use.

The present study evaluates the diagnostic reliability of virtual non-contrast (VNC) images acquired with the first photon counting CT scanner that is approved for clinical use by comparing quantitative image properties of VNC and true non-contrast (TNC) images. Seventy-two patients were retrospectively enrolled in this study. VNC images reconstructed from the arterial (VNCa) and the portalvenous (VNCv) phase were compared to TNC images.

Clinical Characteristics and Magnetic Resonance Imaging-Based Prediction of the KLF4 Mutation in Meningioma.

Background: Meningioma is the most common primary brain tumor in adults. In recent years, several non-neurofibromin 2 mutations, i.e.

Generally applicable window settings of low-keV virtual monoenergetic reconstructions in dual-layer CT-angiography of the head and neck.

Background: Increased vessel contrast in low-keV virtual monoenergetic images (VMI) in spectral detector CT angiography of the head and neck requires adaption of window settings. Aim of this study was to define generally applicable window settings of low-keV VMI.

Methods: Two radiologists determined ideal subjective window settings for VMI in 54 patients.

Contrast-Enhanced Black Blood MRI Sequence Is Superior to Conventional T1 Sequence in Automated Detection of Brain Metastases by Convolutional Neural Networks.

Background: in magnetic resonance imaging (MRI), automated detection of brain metastases with convolutional neural networks (CNN) represents an extraordinary challenge due to small lesions sometimes posing as brain vessels as well as other confounders. Literature reporting high false positive rates when using conventional contrast enhanced (CE) T1 sequences questions their usefulness in clinical routine. CE black blood (BB) sequences may overcome these limitations by suppressing contrast-enhanced structures, thus facilitating lesion detection.

Impact of aneurysm morphology on aneurysmal subarachnoid hemorrhage severity, cerebral infarction and functional outcome.

Objective: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with high morbidity. The objective was to evaluate, whether specific morphological aneurysm characteristics could serve as predictive values for aSAH severity, disease-related complications and clinical outcome.

Methods: A total of 453 aSAH patients (mean age: 54.

Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning.

Background: Non-small cell lung cancer (NSCLC) is the most common tumor entity spreading to the brain and up to 50% of patients develop brain metastases (BMs). Detection of BMs on MRI is challenging with an inherent risk of missed diagnosis.

Purpose: To train and evaluate a deep learning model (DLM) for fully automated detection and 3D segmentation of BMs in NSCLC on clinical routine MRI.

Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

Purpose: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).

Methods: Three different DLMs were trained on CTA datasets of 68 aSAH patients with 79 aneurysms with their outputs being combined applying ensemble learning (DLM-Ens). The DLM-Ens was evaluated on an independent test set of 104 aSAH patients with 126 aneuryms (mean volume 129.

Abdominal vessel depiction on virtual triphasic spectral detector CT: initial clinical experience.

Purpose: To evaluate vessel assessment in virtual monoenergetic images (VMI) and virtual-non-contrast images (VNC) derived from venous phase spectral detector computed tomography (SDCT) acquisitions in comparison to arterial phase and true non-contrast (TNC) images.

Methods: Triphasic abdominal SDCT was performed in 25 patients including TNC, arterial and venous phase. VMI and VNC were reconstructed from the venous phase and compared to conventional arterial-phase images (CI), TNC and conventional venous-phase images (CI).

Reduction of CT artifacts from cardiac implantable electronic devices using a combination of virtual monoenergetic images and post-processing algorithms.

Objectives: To evaluate the reduction of artifacts from cardiac implantable electronic devices (CIEDs) by virtual monoenergetic images (VMI), metal artifact reduction (MAR) algorithms, and their combination (VMI) derived from spectral detector CT (SDCT) of the chest compared to conventional CT images (CI).

Methods: In this retrospective study, we included 34 patients (mean age 74.6 ± 8.

Dual energy imaging in cardiothoracic pathologies: A primer for radiologists and clinicians.

Recent advances in dual-energy imaging techniques, dual-energy subtraction radiography (DESR) and dual-energy CT (DECT), offer new and useful additional information to conventional imaging, thus improving assessment of cardiothoracic abnormalities. DESR facilitates detection and characterization of pulmonary nodules. Other advantages of DESR include better depiction of pleural, lung parenchymal, airway and chest wall abnormalities, detection of foreign bodies and indwelling devices, improved visualization of cardiac and coronary artery calcifications helping in risk stratification of coronary artery disease, and diagnosing conditions like constrictive pericarditis and valvular stenosis.

Trends in imaging utilization for small cell lung cancer: a decision tree analysis of the NCCN guidelines.

Purpose: To investigate the differences in small cell lung cancer (SCLC) diagnostic imaging utilization relative to National Comprehensive Cancer Network (NCCN) guidelines.

Methods: We retrospectively reviewed SCLC records at our institution between January 1, 2003 and August 1, 2019 (n = 529). Patients were grouped by extensive-stage versus limited-stage and diagnosis date.

Impact of the weekend effect on outcome after microsurgical clipping of ruptured intracranial aneurysms.

Background: The "weekend effect" describes the assumption that weekend and/or on-call duty admission of emergency patients is associated with increased morbidity and mortality rates. For aneurysmal subarachnoid hemorrhage, we investigated, whether presentation out of regular working hours and microsurgical clipping at nighttime correlates with worse patient outcome.

Methods: This is a retrospective review of consecutive patients that underwent microsurgical clipping of an acutely ruptured aneurysm at our institution between 2010 and 2019.