Publications by authors named "Helge C Kniep"

Article Synopsis
  • The study investigates factors leading to early stopping during mechanical thrombectomy (MT) in acute ischemic stroke patients, focusing on those that do not achieve a successful recanalization score (mTICI ≥2b).
  • An analysis of 2,977 patients revealed that factors such as higher age, worse pre-stroke conditions, and certain complications during the procedure were linked to early stopping without successful recanalization.
  • The findings suggest that decisions to stop the procedure often correspond to the patient's overall prognosis, indicating that both favorable and unfavorable conditions can influence the likelihood of early intervention cessation.
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Background: There is yet no randomized controlled evidence that mechanical thrombectomy (MT) is superior to best medical treatment in patients with large vessel occlusion but minor stroke symptoms (National Institutes of Health Stroke Scale (NIHSS) <6). Prior studies of patients with admission NIHSS scores 6 observed unfavorable functional outcomes despite successful recanalization, commonly termed as futile recanalization (FR), in up to 50% of cases.

Aim: The aim of this study is to determine the prevalence of FR in patients with minor stroke and identify associated patient-specific risk factors.

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Article Synopsis
  • The study investigates the impact of mechanical thrombectomy (MT) on patients with ischemic stroke who do not have salvageable brain tissue identified by computed tomography perfusion (CTP) imaging.
  • Out of 724 patients analyzed, 110 had no CTP mismatch, with successful recanalization in 66% of these cases, which was linked to improved functional independence after 90 days.
  • Results show that MT is particularly effective for patients under 70 years old and those with moderate brain injury (measured by the Alberta Stroke Program Early Computed Tomography Score).
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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.

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Article Synopsis
  • - The study explores how imaging techniques, specifically "tissue clock" indicators like CT perfusion and net water uptake, can better predict early neurologic improvement in stroke patients receiving intravenous thrombolysis (IVT) than traditional time-based criteria.
  • - Four hundred nine patients with strokes caused by proximal vessel occlusion were analyzed, revealing that IVT significantly improved early neurologic outcomes in those with low NWU or CTP mismatch, independent of the time since symptom onset.
  • - The findings suggest that using CT-based "tissue clock" measures could more accurately identify patients who would benefit from IVT, potentially changing treatment approaches for stroke patients within extended time frames.
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  • Discordance between receptor expressions in metastatic brain lesions and primary tumors in breast cancer patients shows the need for personalized therapy through constant monitoring of these expressions.
  • This study investigates using machine learning on MR imaging features to predict receptor status in brain metastases, analyzing 412 samples from 106 patients over a 14-year period.
  • Results reveal that MR image features can accurately predict the receptor status (ER+, PR+, HER2+) with high discriminatory accuracy, suggesting a valuable tool for individualized treatment planning.
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Background And Purpose: Mechanical thrombectomy (MT) has proven to be the standard of care for patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). However, high revascularization rates do not necessarily result in favorable functional outcomes. We aimed to investigate imaging biomarkers associated with futile recanalization, defined as unfavorable functional outcome despite successful recanalization in AIS-LVO patients.

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Purpose: Whether patients presenting with mild stroke (NIHSS at admission < 6) should be treated with mechanical thrombectomy (MT) is the subject of an ongoing debate. This retrospective study based on large-scale clinical data aims to identify factors associated with favorable outcome (FO) in patients with mild stroke.

Methods: A total of 761 patients with mild stroke enrolled between 1 January 2020 and 31 December 2020 in the Quality Registry of the German Society for Neuroradiology were analyzed.

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Article Synopsis
  • The study investigates the role of mechanical thrombectomy (MT) in patients with ischemic stroke and low Alberta Stroke Program Early CT Score (ASPECTS), focusing on how early lesion water uptake (NWU) affects functional outcomes.
  • Researchers analyzed 254 patients, finding that those with low NWU had a significantly higher rate of favorable outcomes post-MT compared to those with high NWU.
  • The results suggest that NWU could be a valuable imaging biomarker for predicting the success of MT in low ASPECTS patients, indicating that certain patients may not benefit from the procedure.
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Background And Purpose: We developed a machine learning model to allow early functional outcome prediction for patients presenting with posterior circulation (pc)-stroke based on CT-imaging and clinical data at admission. The proposed algorithm utilizes quantitative information from automated multidimensional assessments of posterior circulation Acute Stroke Prognosis Early CT-Score (pc-ASPECTS) regions. Discriminatory power was compared to predictions based on conventional pc-ASPECTS ratings.

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Objective: Thrombus microfragmentation causing peripheral emboli (PE) during mechanical thrombectomy (MT) may modulate treatment effects, even in cases with successful reperfusion. This study aims to investigate whether intravenous alteplase is of potential benefit in reducing PE after successful MT.

Methods: Patients from a prospective study treated at a tertiary care stroke center between 08/2017 and 12/2019 were analyzed.

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Thrombus fragmentation causing distal emboli is a feared complication during mechanical thrombectomy (MT). We aimed to investigate the impact of procedural parameters and thrombus properties on the incidence of peripheral emboli after MT for large vessel occlusions (LVO). We performed a prospective analysis of patients with LVO stroke successfully treated with MT, defined as a score of 2b, 2c, or 3 on the thrombolysis in cerebral infarction (TICI) scale.

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Objectives: Triage of patients with basilar artery occlusion for additional imaging diagnostics, therapy planning, and initial outcome prediction requires assessment of early ischemic changes in early hyperacute non-contrast computed tomography (NCCT) scans. However, accuracy of visual evaluation is impaired by inter- and intra-reader variability, artifacts in the posterior fossa and limited sensitivity for subtle density shifts. We propose a machine learning approach for detecting early ischemic changes in pc-ASPECTS regions (Posterior circulation Alberta Stroke Program Early CT Score) based on admission NCCTs.

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Background And Aim: To analyze the incidence of peripheral emboli after successful mechanical thrombectomy (MT) of intracranial large vessel occlusions (LVO).

Methods: We performed a prospective analysis of patients with intracranial LVO who underwent successful MT and received a 1.5 T MRI including diffusion-weighted imaging (DWI) in standard- and high-resolution as well as susceptibility-weighted imaging (SWI) on the day following the intervention.

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To date, imaging studies quantifying the amount of vasogenic edema reduction (VE) in patients with brain metastases (BM) treated with glucocorticoids (GC) have included a very limited number of patients and showed ambiguous results. Here, we aim to determine the radiological effect of GC on VE in BM patients in a large cohort with multiple primary tumor entities in a cross-sectional approach. This monocentric retrospective study includes 299 patients first-ever diagnosed with 2,759 intra-axial BM on the respective MRI.

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In multiple sclerosis (MS) patients, Double Inversion Recovery (DIR) magnetic resonance imaging (MRI) can be used to detect cortical lesions (CL). While the quantity and distribution of CLs seems to be associated with patients' disease course, literature lacks frequent assessments of CL volumes (CL-V) in this context. We investigated the reliability of DIR for the longitudinal assessment of CL-V development with frequent follow-up MRIs and examined the course of CL-V progressions in relation to white-matter lesions (WML), contrast enhancing lesions (CEL) and clinical parameters in patients with Relapsing-Remitting Multiple Sclerosis (RRMS).

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Purpose To investigate the feasibility of tumor type prediction with MRI radiomic image features of different brain metastases in a multiclass machine learning approach for patients with unknown primary lesion at the time of diagnosis. Materials and methods This single-center retrospective analysis included radiomic features of 658 brain metastases from T1-weighted contrast material-enhanced, T1-weighted nonenhanced, and fluid-attenuated inversion recovery (FLAIR) images in 189 patients (101 women, 88 men; mean age, 61 years; age range, 32-85 years). Images were acquired over a 9-year period (from September 2007 through December 2016) with different MRI units, reflecting heterogeneous image data.

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