Evidence map›Paper›PMID 41871391›Full record

ArticleJournal of neurosurgery. Case lessons2026

Targeted repair of a refractory ventral cerebrospinal fluid leak identified by dynamic computed tomography myelography: illustrative case.

Amelia Stepniak, Samuel Adida, Sharath Kumar Anand, Vikas Agarwal, Peter C Gerszten

Abstract read
In one paragraph

Article in Journal of neurosurgery. Case lessons, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Amelia StepniakDepartment of Neurological Surgery and.
Samuel AdidaDepartment of Neurological Surgery and.ORCID 0000-0002-1258-8601
Sharath Kumar AnandDepartment of Neurological Surgery and.
Vikas AgarwalDepartment of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
Peter C GersztenDepartment of Neurological Surgery and.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpontaneous spinal CSF leaks can be difficult to diagnose, particularly with large or multiple dural tears. Although conventional CT myelography (CTM) is the standard imaging modality, it may fail to localize elusive leaks. Dynamic CTM (dCTM) enables real-time contrast tracking and improves localization, particularly for type 1 (ventral dural tear) and type 2 (lateral dural tear) leaks, to support targeted intervention. OBSERVATIONS: A 36-year-old woman with Birt-Hogg-Dubé syndrome and recurrent spontaneous CSF leaks previously treated with multiple epidural blood patches presented with worsening positional headaches. Brain MRI demonstrated features of intracranial hypotension, and total spine MRI raised concern for extradural fluid collection. Conventional CTM demonstrated a ventral extradural collection extending between T4 and T11 without a definitive source. Dynamic CTM successfully localized a ventral dural defect at T10-11. The patient underwent a posterior T10-11 laminectomy with dural reinforcement via a transpedicular approach using a TachoSil patch with DuraSeal. Her headaches resolved immediately, and she remained asymptomatic at the 6-month follow-up. LESSONS: Dynamic CTM is a valuable tool for localizing ventral and lateral spinal CSF leaks when standard imaging is inconclusive. Early application of dCTM may reduce unnecessary interventions, shorten treatment delays, and optimize surgical planning. https://thejns.org/doi/10.3171/CASE25700.

Indexed as

cerebrospinal fluid leakmyelographyventral dural tear

Identifiers

PMID41871391
PMCPMC13007649

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Registered trials

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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.