Clinical potential of automated convolutional neural network-based hematoma volumetry after aneurysmal subarachnoid hemorrhage.

Objectives: Cerebrospinal fluid hemoglobin has been positioned as a potential biomarker and drug target for aneurysmal subarachnoid hemorrhage-related secondary brain injury (SAH-SBI). The maximum amount of hemoglobin, which may be released into the cerebrospinal fluid, is defined by the initial subarachnoid hematoma volume (ISHV). In patients without external ventricular or lumbar drain, there remains an unmet clinical need to predict the risk for SAH-SBI.

Spatial transcriptome data from coronal mouse brain sections after striatal injection of heme and heme-hemopexin.

Hemorrhagic stroke is a major cause of morbidity and mortality worldwide. Secondary mechanisms of brain injury adversely affect functional outcome in patients after intracranial hemorrhage. Potential drivers of intracranial hemorrhage-related secondary brain injury are hemoglobin and its downstream degradation products released from lysed red blood cells, such as free heme.

Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain.

After intracranial hemorrhage, heme is released from cell-free hemoglobin. This red blood cell component may drive secondary brain injury at the hematoma‒brain interface. This study aimed to generate a spatially resolved map of transcriptome-wide gene expression changes in the heme-exposed brain and to define the potential therapeutic activity of the heme-binding protein, hemopexin.

Optimizing Deep Learning Algorithms for Segmentation of Acute Infarcts on Non-Contrast Material-enhanced CT Scans of the Brain Using Simulated Lesions.

Purpose: To test the efficacy of lesion segmentation using a deep learning algorithm on non-contrast material-enhanced CT (NCCT) images with synthetic lesions resembling acute infarcts.

Materials And Methods: In this retrospective study, 40 diffusion-weighted imaging (DWI) lesions in patients with acute stroke (median age, 69 years; range, 62-76 years; 17 women; screened between 2011 and 2017) were coregistered to 40 normal NCCT scans (median age, 70 years; range, 55-76 years; 25 women; screened between 2008 and 2011), which produced 640 combinations of DWI-NCCT with and without lesions for training ( = 420), validation ( = 110), and testing ( = 110). The signal intensity on the NCCT scans was depressed by 4 HU (a 13% drop) in the region of the diffusion-weighted lesion.

Modular Platform for the Development of Recombinant Hemoglobin Scavenger Biotherapeutics.

Cell-free hemoglobin (Hb) is a driver of disease progression in conditions with intravascular or localized hemolysis. Genetic and acquired anemias or emergency medical conditions such as aneurysmal subarachnoid hemorrhage involve tissue Hb exposure. Haptoglobin (Hp) captures Hb in an irreversible protein complex and prevents its pathophysiological contributions to vascular nitric oxide depletion and tissue oxidation.

Realistic generation of diffusion-weighted magnetic resonance brain images with deep generative models.

We study two state of the art deep generative networks, the Introspective Variational Autoencoder and the Style-Based Generative Adversarial Network, for the generation of new diffusion-weighted magnetic resonance images. We show that high quality, diverse and realistic-looking images, as evaluated by external neuroradiologists blinded to the whole study, can be synthesized using these deep generative models. We evaluate diverse metrics with respect to quality and diversity of the generated synthetic brain images.

Cerebrospinal fluid hemoglobin drives subarachnoid hemorrhage-related secondary brain injury.

Secondary brain injury after aneurysmal subarachnoid hemorrhage (SAH-SBI) contributes to poor outcomes in patients after rupture of an intracranial aneurysm. The lack of diagnostic biomarkers and novel drug targets represent an unmet need. The aim of this study was to investigate the clinical and pathophysiological association between cerebrospinal fluid hemoglobin (CSF-Hb) and SAH-SBI.

Improved Segmentation and Detection Sensitivity of Diffusion-weighted Stroke Lesions with Synthetically Enhanced Deep Learning.

Purpose: To compare the segmentation and detection performance of a deep learning model trained on a database of human-labeled clinical stroke lesions on diffusion-weighted (DW) images to a model trained on the same database enhanced with synthetic stroke lesions.

Materials And Methods: In this institutional review board-approved study, a stroke database of 962 cases (mean patient age ± standard deviation, 65 years ± 17; 255 male patients; 449 scans with DW positive stroke lesions) and a normal database of 2027 patients (mean age, 38 years ± 24; 1088 female patients) were used. Brain volumes with synthetic stroke lesions on DW images were produced by warping the relative signal increase of real strokes to normal brain volumes.

Demonstration of asymmetric muscle perfusion of the back after exercise in patients with adolescent idiopathic scoliosis using intravoxel incoherent motion (IVIM) MRI.

The purpose of this work was to quantify muscular perfusion patterns of back muscles after exercise in patients with adolescent idiopathic scoliosis (AIS) using intravoxel incoherent motion (IVIM) MR perfusion imaging. The paraspinal muscles of eight patients with AIS (Cobb angle 35 ± 10°, range [25-47°]) and nine healthy volunteers were scanned with a 1.5 T MRI, at rest and after performing a symmetric back muscle exercise on a Roman chair.

Characterization of lower limb muscle activation patterns during walking and running with Intravoxel Incoherent Motion (IVIM) MR perfusion imaging.

Background: The distribution of energy use among different lower limb muscles during walking and running is not well understood. Local blood flow within skeletal muscle tissue depends on its metabolic activity during activation. The non-invasive magnetic resonance microvascular perfusion method Intravoxel Incoherent Motion (IVIM) is able to quantify muscle activation.