Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

Background: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduced radiation doses. This is essential in the context of low-dose CT lung cancer screening where accurate volumetry and characterization of pulmonary nodules in repeated CT scanning are indispensable.

Materials And Methods: A standardized CT dataset was established using an anthropomorphic chest phantom (Lungman, Kyoto Kaguku Inc.

Can angiographic Flat Detector Computed Tomography blood volume measurement be used to predict final infarct size in acute ischemic stroke?

Introduction And Purpose: Flat detector computed tomography (FD-CT) technology is becoming more widely available in the angiography suites of comprehensive stroke centers. In patients with acute ischemic stroke (AIS), who are referred for endovascular therapy (EVT), FD-CT generates cerebral pooled blood volume (PBV) maps, which might help in predicting the final infarct area. We retrospectively analyzed pre- and post-recanalization therapy quantitative PBV measurements in both the infarcted and hypoperfused brain areas of AIS patients referred for EVT.

Flat Detector CT with Cerebral Pooled Blood Volume Perfusion in the Angiography Suite: From Diagnostics to Treatment Monitoring.

C-arm flat-panel detector computed tomographic (CT) imaging in the angiography suite increasingly plays an important part during interventional neuroradiological procedures. In addition to conventional angiographic imaging of blood vessels, flat detector CT (FD CT) imaging allows simultaneous 3D visualization of parenchymal and vascular structures of the brain. Next to imaging of anatomical structures, it is also possible to perform FD CT perfusion imaging of the brain by means of cerebral blood volume (CBV) or pooled blood volume (PBV) mapping during steady state contrast administration.

Fluorescence-Guided Thoracic Duct Dissection in Robotic en Bloc Esophagectomy.

En bloc resection of the thoracic duct compartment enhances adequate lymph node removal and may improve oncologic outcomes in esophagectomy for malignant esophageal diseases. However, it also increases the risk of postoperative chylothorax, with a reported incidence of 5% to 20%. This report describes a technique that facilitates intraoperative identification of the thoracic duct, as well as proximal and distal ligation, during robot-assisted esophagectomy by lymphangiography-guided injection of indocyanine green in the right groin in a patient in the left lateral position.

Liver segmentation and metastases detection in MR images using convolutional neural networks.

Primary tumors have a high likelihood of developing metastases in the liver, and early detection of these metastases is crucial for patient outcome. We propose a method based on convolutional neural networks to detect liver metastases. First, the liver is automatically segmented using the six phases of abdominal dynamic contrast-enhanced (DCE) MR images.