Evidence map›Paper›PMID 38502330›Full record

ArticleBrain structure & function2024

MRI atlas of the pituitary gland in young female adults.

Manel Merabet Zennadi, Maurice Ptito, Jérôme Redouté, Nicolas Costes, Claire Boutet, Natacha Germain, Bogdan Galusca, Fabien C Schneider

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Article in Brain structure & function, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Manel Merabet ZennadiUniversité Jean Monnet Saint Etienne, CHU de Saint Etienne, TAPE Research Unit EA 7423, F-42023, Saint Etienne, France.
Maurice PtitoÉcole d'Optométrie, Université de Montréal, Montréal, Québec, Canada.
Jérôme RedoutéCERMEP, Claude Bernard University Lyon 1, Villeurbanne, France.
Nicolas CostesCERMEP, Claude Bernard University Lyon 1, Villeurbanne, France.
Claire BoutetUniversité Jean Monnet Saint Etienne, CHU de Saint Etienne, TAPE Research Unit EA 7423, F-42023, Saint Etienne, France.
Natacha GermainUniversité Jean Monnet Saint Etienne, CHU de Saint Etienne, TAPE Research Unit EA 7423, F-42023, Saint Etienne, France.
Bogdan GaluscaUniversité Jean Monnet Saint Etienne, CHU de Saint Etienne, TAPE Research Unit EA 7423, F-42023, Saint Etienne, France.
Fabien C SchneiderUniversité Jean Monnet Saint Etienne, CHU de Saint Etienne, TAPE Research Unit EA 7423, F-42023, Saint Etienne, France. fabien.schneider@univ-st-etienne.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The probabilistic topography and inter-individual variability of the pituitary gland (PG) remain undetermined. The absence of a standardized reference atlas hinders research on PG volumetrics. In this study, we aimed at creating maximum probability maps for the anterior and posterior PG in young female adults. We manually delineated the anterior and posterior parts of the pituitary glands in 26 healthy subjects using high-resolution MRI T1 images. A three-step procedure and a cost function-masking approach were employed to optimize spatial normalization for the PG. We generated probabilistic atlases and maximum probability maps, which were subsequently coregistered back to the subjects' space and compared to manual delineations. Manual measurements led to a total pituitary volume of 705 ± 88 mm³, with the anterior and posterior volumes measuring 614 ± 82 mm³ and 91 ± 20 mm³, respectively. The mean relative volume difference between manual and atlas-based estimations was 1.3%. The global pituitary atlas exhibited an 80% (± 9%) overlap for the DICE index and 67% (± 11%) for the Jaccard index. Similarly, these values were 77% (± 13%) and 64% (± 14%) for the anterior pituitary atlas and 62% (± 21%) and 47% (± 17%) for the posterior PG atlas, respectively. We observed a substantial concordance and a significant correlation between the volume estimations of the manual and atlas-based methods for the global pituitary and anterior volumes. The maximum probability maps of the anterior and posterior PG lay the groundwork for automatic atlas-based segmentation methods and the standardized analysis of large PG datasets.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance ImagingAdultAlgorithmsFemaleHumansPituitary GlandAtlasAutomatic segmentationHuman brainMRIPituitary gland

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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.