ArticleFrontiers in neurology2025
Potential of transcranial ultrasound- and near-infrared spectroscopy-based acute stroke imaging for decision-making on intravenous thrombolysis treatment.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Mobile Stroke Units (MSU) shorten time to intravenous thrombolysis (IVT) and improve functional outcome, but they rely on computed tomography (CT) making them highly specialized and costly. Alternative technologies can potentially identify imaging-based IVT contraindications like intracranial hemorrhage (ICH) or malignancies (IM), e.g., by transcranial color-coded sonography (TCCS) and near-infrared spectroscopy (NIRS). Methods: Using a simulation approach, we analyzed magnetic resonance imaging (MRI) scans of stroke-suspected patients within 4.5 h of symptom onset to assess TCCS and NIRS for identifying imaging-based IVT contraindications. Our study included both primary and sensitivity analyses, each employing conservative and optimistic scenarios. The primary analysis integrated clinical information from the emergency department, while the sensitivity analysis evaluated overall performance across all patients, regardless of clinical information. The conservative scenario defined TCCS detecting acute deep-brain hemorrhages or tumors >20 mm from scalp surface or > 10 mL in volume or causing >4 mm midline-shift, while NIRS was defined detecting them <20 mm from scalp surface with a volume > 3.5 mL. The optimistic scenario defined TCCS detecting intracranial or subarachnoid acute/subacute hematoma or tumors >20 mm from scalp surface or > 5 mL in volume or causing >2 mm midline-shift, while NIRS was defined detecting them <35 mm from the scalp surface with volume > 3.5 mL. Results: We assessed 1,089 consecutive patients undergoing acute MRI, identifying 69 with imaging-based IVT contraindications, of which 40 had additional non-imaging contraindications. In the primary analysis, among those 29 patients without non-imaging-based contraindications, TCCS/NIRS would have detected 15 of 25 ICH and 3 of 4 malignant tumors in the conservative scenario. In the optimistic scenario, 18 of 25 ICH and all malignant tumors would have been detected. In the sensitivity analyses, the conservative scenario would have detected 30 of 52 ICH and 8 of 17 malignant tumors, while the optimistic scenario would have identified 37 of 52 ICH and 12 of 17 malignant tumors. Conclusion: While TCCS and NIRS technologies exhibit potential for identifying IVT contraindications in pre-hospital settings, comprehensive evaluation in real-world scenarios is imperative to ascertain their operational constraints.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.