Evidence map›Paper›PMID 37064182›Full record

ArticleFrontiers in neurology2023

Volumetric measurement of paranasal sinuses and its clinical significance in pituitary neuroendocrine tumors operated using an endoscopic endonasal approach.

Masato Nakaya, Ryota Tamura, Kento Takahara, Takumi Senuma, Keisuke Yoshida, Yohei Kitamura, Ryo Ueda, Masahiro Toda

Abstract read
In one paragraph

Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

Masato NakayaDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.
Ryota TamuraDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.
Kento TakaharaDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.
Takumi SenumaDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.
Keisuke YoshidaDepartment of Neurosurgery, Mihara Memorial Hospital, Isesaki-shi, Japan.
Yohei KitamuraDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.
Ryo UedaDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.
Masahiro TodaDepartment of Neurosurgery, Keio University School of Medicine, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Endoscopic endonasal surgery (EES) for deep intracranial lesions has gained popularity following recent developments in endoscopic technology. The operability of invasive pituitary neuroendocrine tumors (PitNETs) depends on the anatomy of the nasal cavity and paranasal sinus. This study aimed to establish a simple volume reconstruction algorithm of the nasal cavity and paranasal sinus. Additionally, this is the first study to demonstrate the relationship between the segmentation method and the clinical significance in patients with PitNET. Methods: Pre-and postoperative tumor volumes were analyzed in 106 patients with primary (new-onset) PitNETs (80 nonfunctioning and 26 functioning) who underwent EES. The efficiency and accuracy of the semiautomatic segmentation with manual adjustments (SSMA) method was compared with other established segmentation methods for volumetric analysis in the nasal cavity and paranasal sinuses. Correlations between the measured nasal cavity and paranasal sinus volumes and the extent of tumor removal were evaluated. Results: The SSMA method yielded accurate and time-saving results following the volumetric analyses of nasal cavity and paranasal sinuses with complex structures. Alternatively, the manual and semiautomatic segmentation methods proved time-consuming and inaccurate, respectively. The sphenoid sinus volume measured by SSMA was significantly correlated with the extent of tumor removal in patients with nonfunctioning Knosp grade 3 and 4 PitNET ( Conclusion: The volume of sphenoid sinus potentially could predict the extent of resection due to better visualization of the tumor for PitNETs with CS invasion.

Indexed as

endoscopic endonasal surgeryparanasal sinuspituitary neuroendocrine tumorsphenoid sinusvolumetric analysis

Identifiers

PMID37064182
PMCPMC10098075

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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.