Sepsis and delayed cerebral ischemia are associated and have a cumulative effect on poor functional outcome in aneurysmal subarachnoid hemorrhage.

Objective: Although sepsis and delayed cerebral ischemia (DCI) are severe complications in patients with aneurysmal subarachnoid hemorrhage (aSAH) and share pathophysiological features, their interrelation and additive effect on functional outcome is uncertain. We investigated the association between sepsis and DCI and their cumulative effect on functional outcome in patients with aSAH using current sepsis-3 definition.

Methods: Patients admitted to our hospital between 11/2014 and 11/2018 for aSAH were retrospectively analyzed.

Prediction of tissue outcome in acute ischemic stroke based on single-phase CT angiography at admission.

Introduction: In acute ischemic stroke, prediction of the tissue outcome after reperfusion can be used to identify patients that might benefit from mechanical thrombectomy (MT). The aim of this work was to develop a deep learning model that can predict the follow-up infarct location and extent exclusively based on acute single-phase computed tomography angiography (CTA) datasets. In comparison to CT perfusion (CTP), CTA imaging is more widely available, less prone to artifacts, and the established standard of care in acute stroke imaging protocols.

Association Between Recanalization Attempts and Functional Outcome After Thrombectomy for Large Ischemic Stroke.

Background: Recently, 3 randomized controlled trials provided high-level evidence that patients with large ischemic stroke achieved better functional outcomes after endovascular therapy than with medical care alone. We aimed to investigate whether the clinical benefit of endovascular therapy is associated with the number of recanalization attempts in extensive baseline infarction.

Methods: This retrospective multicenter study enrolled patients from the German Stroke Registry who underwent endovascular therapy for anterior circulation large vessel occlusion between 2015 and 2021.

The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms.

Individual glioblastoma cells harbor both proliferative and invasive capabilities during tumor progression.

Background: Glioblastomas are characterized by aggressive and infiltrative growth, and by striking heterogeneity. The aim of this study was to investigate whether tumor cell proliferation and invasion are interrelated, or rather distinct features of different cell populations.

Methods: Tumor cell invasion and proliferation were longitudinally determined in real-time using 3D in vivo 2-photon laser scanning microscopy over weeks.

Lightweight Visual Transformers Outperform Convolutional Neural Networks for Gram-Stained Image Classification: An Empirical Study.

We aimed to automate Gram-stain analysis to speed up the detection of bacterial strains in patients suffering from infections. We performed comparative analyses of visual transformers (VT) using various configurations including model size (small vs. large), training epochs (1 vs.

Myelofibrosis progression grading based on type I and type III collagen and fibrillin 1 expression boosted by whole slide image analysis.

Aims: The progression of primary myelofibrosis is characterised by ongoing extracellular matrix deposition graded based on 'reticulin' and 'collagen' fibrosis, as revealed by Gomori's silver impregnation. Here we studied the expression of the major extracellular matrix proteins of fibrosis in relation to diagnostic silver grading supported by image analysis.

Methods And Results: By using automated immunohistochemistry, in this study we demonstrate that the expression of both types I and III collagens and fibrillin 1 by bone marrow stromal cells can reveal the extracellular matrix scaffolding in line with myelofibrosis progression as classified by silver grading.

Rapid Convolutional Neural Networks for Gram-Stained Image Classification at Inference Time on Mobile Devices: Empirical Study from Transfer Learning to Optimization.

Despite the emergence of mobile health and the success of deep learning (DL), deploying production-ready DL models to resource-limited devices remains challenging. Especially, during inference time, the speed of DL models becomes relevant. We aimed to accelerate inference time for Gram-stained analysis, which is a tedious and manual task involving microorganism detection on whole slide images.

Influence of neurovascular anatomy on perforation site in different mouse strains using the filament perforation model for induction of subarachnoid hemorrhage.

Background: Filament perforation is a widely-used method to induce subarachnoid hemorrhage (SAH) in mice. Whereas the perforation site has been assumed to be in the branching of middle cerebral artery (MCA) and anterior cerebral artery (ACA), we recently observed more proximal perforations.

Methods: Filament perforation was performed in CD1- (n = 10) and C57Bl/6N-mice (n = 9) ex vivo.

Comparative Analyses of the Impact of Different Criteria for Sepsis Diagnosis on Outcome in Patients with Spontaneous Subarachnoid Hemorrhage.

Data on sepsis in patients with a subarachnoid hemorrhage (SAH) are scarce. We assessed the impact of different sepsis criteria on the outcome in an SAH cohort. Adult patients admitted to our ICU with a spontaneous SAH between 11/2014 and 11/2018 were retrospectively included.

Transfer learning for medical image classification: a literature review.

Background: Transfer learning (TL) with convolutional neural networks aims to improve performances on a new task by leveraging the knowledge of similar tasks learned in advance. It has made a major contribution to medical image analysis as it overcomes the data scarcity problem as well as it saves time and hardware resources. However, transfer learning has been arbitrarily configured in the majority of studies.

Correlations Between the Expression of Stromal Cell Activation Related Biomarkers, L-NGFR, Phospho-ERK1-2 and CXCL12, and Primary Myelofibrosis Progression.

In myelofibrosis, pathologically enhanced extracellular matrix production due to aberrant cytokine signalling and result() in impaired hemopoiesis. Disease progression is still determined by detecting reticulin and collagen fibrosis with Gomori's silver impregnation. Here, we tested whether the expression growth related biomarkers L-NGFR/CD271, phospho-ERK1-2 and CXCL12 can be linked to the functional activation of bone marrow stromal cells during primary myelofibrosis progression.

Number of Retrieval Attempts Rather Than Procedure Time Is Associated With Risk of Symptomatic Intracranial Hemorrhage.

Endovascular therapy is the standard of care in the treatment of acute ischemic stroke due to large-vessel occlusion. A direct association between the number of device passes and the occurrence of symptomatic intracranial hemorrhage (SICH) has been suggested. This study represents an in-depth investigation of the hypothesis that >3 retrieval attempts is associated with an increased rate of SICH in a large multicenter patient cohort.

Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings.

Computer-assisted reporting (CAR) tools were suggested to improve radiology report quality by context-sensitively recommending key imaging biomarkers. However, studies evaluating machine learning (ML) algorithms on cross-lingual ontological (RadLex) mappings for developing embedded CAR algorithms are lacking. Therefore, we compared ML algorithms developed on human expert-annotated features against those developed on fully automated cross-lingual (German to English) RadLex mappings using 206 CT reports of suspected stroke.

Good Clinical Outcome Decreases With Number of Retrieval Attempts in Stroke Thrombectomy: Beyond the First-Pass Effect.

Background And Purpose: Endovascular therapy is the standard of care in the treatment of acute ischemic stroke due to large-vessel occlusion. Often, more than one retrieval attempt is needed to achieve reperfusion. We aimed to quantify the influence of endovascular therapy on clinical outcome depending on the number of retrievals needed for successful reperfusion in a large multi-center cohort.

Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.

DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically highly multiclass classification tasks are still lacking. To support this choice, we evaluated well-established machine learning (ML) classifiers including random forests (RFs), elastic net (ELNET), support vector machines (SVMs) and boosted trees in combination with post-processing algorithms and developed ML workflows that allow for unbiased class probability (CP) estimation.

Longitudinal imaging and evaluation of SAH-associated cerebral large artery vasospasm in mice using micro-CT and angiography.

Longitudinal in vivo imaging studies characterizing subarachnoid hemorrhage (SAH)-induced large artery vasospasm (LAV) in mice are lacking. We developed a SAH-scoring system to assess SAH severity in mice using micro CT and longitudinally analysed LAV by intravenous digital subtraction angiography (i.v.

In situ cell cycle analysis in giant cell tumor of bone reveals patients with elevated risk of reduced progression-free survival.

Objective: Giant cell tumor of bone (GCTB) is a frequently recurring locally aggressive osteolytic lesion, where pathological osteoclastogenesis and bone destruction are driven by neoplastic stromal cells. Here, we studied if cell cycle fractions within the mononuclear cell compartment of GCTB can predict its progression-free survival (PFS).

Methods: 154 cases (100 primaries and 54 recurrent) from 139 patients of 40 progression events, was studied using tissue microarrays.

Longitudinal MRI findings in patients with newly diagnosed glioblastoma after intraoperative radiotherapy.

Background And Purpose: Post-radiation treatment effects (pseudoprogression/radionecrosis) may bias MRI-based tumor response evaluation. To understand these changes specifically after high doses of radiotherapy, we analyzed MRIs of patients enrolled in the INTRAGO study (NCT02104882), a phase I/II dose-escalation trial of intraoperative radiotherapy (20-40 Gy) in glioblastoma.

Methods: INTRAGO patients were evaluated and compared to control patients who received standard therapy with focus on contrast enhancement patterns/volume, T2 lesion volume, and mean rCBV.

Objective Comparison Using Guideline-based Query of Conventional Radiological Reports and Structured Reports.

Background: This feasibility study of text-mining-based scoring algorithm provides an objective comparison of structured reports (SR) and conventional free-text reports (cFTR) by means of guideline-based key terms. Furthermore, an open-source online version of this ranking algorithm was provided with multilingual text-retrieval pipeline, customizable query and real-time-scoring.

Materials And Methods: Twenty-five patients with suspected stroke and magnetic resonance imaging were re-assessed by two independent/blinded readers [inexperienced: 3 years; experienced >6 years/Board-certified).

Anatomical distribution of cerebral microbleeds and intracerebral hemorrhage in vertebrobasilar dolichoectasia.

Objectives: Vertebrobasilar dolichoectasia (VBD) is a dilatative arteriopathy associated with intracerebral hemorrhage. In the present study, we sought to evaluate the frequency and anatomical distribution of cerebral microbleeds (cMBs) and intracerebral hemorrhage (ICH) in VBD.

Methods: From a MRI database 94 VBD patients were identified and analyzed with special emphasis on cMBs and ICH on T2*-weighted gradient echo images (GRE) in relation to the established diagnostic MRI criteria of VBD (diameter, height, and lateral position).

Intra-individual diagnostic image quality and organ-specific-radiation dose comparison between spiral cCT with iterative image reconstruction and z-axis automated tube current modulation and sequential cCT.

Objectives: To prospectively evaluate image quality and organ-specific-radiation dose of spiral cranial CT (cCT) combined with automated tube current modulation (ATCM) and iterative image reconstruction (IR) in comparison to sequential tilted cCT reconstructed with filtered back projection (FBP) without ATCM.

Methods: 31 patients with a previous performed tilted non-contrast enhanced sequential cCT aquisition on a 4-slice CT system with only FBP reconstruction and no ATCM were prospectively enrolled in this study for a clinical indicated cCT scan. All spiral cCT examinations were performed on a 3rd generation dual-source CT system using ATCM in z-axis direction.