Evidence map›Paper›PMID 38637466›Full record

SynthesisNeurosurgical review2024

Volumetric segmentation in the context of posterior fossa-related pathologies: a systematic review.

Andrew J Kobets, Seyed Ahmad Naseri Alavi, Samuel Jack Ahmad, Ashley Castillo, Dejauwne Young, Aurelia Minuti, David J Altschul, Michael Zhu, Rick Abbott

Abstract readSystematic Review
In one paragraph

Synthesis in Neurosurgical review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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

9 authors.

Andrew J KobetsDepartment of Neurological Surgery, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY, 10467, USA.
Seyed Ahmad Naseri AlaviDepartment of Neurological Surgery, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY, 10467, USA. dr.arsalan2010@gmail.com.
Samuel Jack AhmadAlbert Einstein College of Medicine, New York City, USA.
Ashley CastilloAlbert Einstein College of Medicine, New York City, USA.
Dejauwne YoungAlbert Einstein College of Medicine, New York City, USA.
Aurelia MinutiAlbert Einstein College of Medicine, New York City, USA.
David J AltschulDepartment of Neurological Surgery, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY, 10467, USA.
Michael ZhuAlbert Einstein College of Medicine, New York City, USA.
Rick AbbottDepartment of Neurological Surgery, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY, 10467, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSegmentation tools continue to advance, evolving from manual contouring to deep learning. Researchers have utilized segmentation to study a myriad of posterior fossa-related conditions, such as Chiari malformation, trigeminal neuralgia, post-operative pediatric cerebellar mutism syndrome, and Crouzon syndrome. Herein, we present a summary of the current literature on segmentation of the posterior fossa. The review highlights the various segmentation techniques, and their respective strengths and weaknesses, employed along with objectives and outcomes of the various studies reported in the literature.

methodsA literature search was conducted in PubMed, Embase, Cochrane, and Web of Science up to November 2023 for articles on segmentation techniques of posterior fossa. The two senior authors searched through databases based on the keywords of the article separately and then enrolled joint articles that met the inclusion and exclusion criteria.

resultsThe initial search identified 2205 articles. After applying inclusion and exclusion criteria, 77 articles were selected for full-text review after screening of titles/abstracts. 52 articles were ultimately included in the review. Segmentation techniques included manual, semi-automated, and fully automated (atlas-based, convolutional neural networks). The most common pathology investigated was Chiari malformation.

conclusionsVarious forms of segmentation techniques have been used to assess posterior fossa volumes/pathologies and each has its advantages and disadvantages. We discuss these nuances and summarize the current state of literature in the context of posterior fossa-associated pathologies.

Indexed as

Arnold-Chiari MalformationCranial Fossa, PosteriorHumansMagnetic Resonance ImagingChiari malformationPosterior fossaPosterior fossa volumeSegmentation

Identifiers

PMID38637466
PMCPMC11026186

What OpenQuestion holds

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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.