Evidence map›Paper›PMID 41479607›Full record

ArticleFrontiers in neurology2025

Multi-center evaluation of Neurophet AQUA for brain MRI segmentation: T1 compared with FreeSurfer and T2-FLAIR compared with ground truth.

Hyunjae Yu, Hyunji Lee, Minho Lee, Donghyeon Kim, Lukas Pirpamer, Marco Duering, Sue Moy, Karl G Helmer, Regina E Y Kim, Alzheimer's Disease Neuroimaging Initiative

Abstract read
In one paragraph

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.

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

10 authors.

Hyunjae YuResearch Institute, Neurophet Inc., Seoul, Republic of Korea.
Hyunji LeeResearch Institute, Neurophet Inc., Seoul, Republic of Korea.
Minho LeeResearch Institute, Neurophet Inc., Seoul, Republic of Korea.
Donghyeon KimResearch Institute, Neurophet Inc., Seoul, Republic of Korea.
Lukas PirpamerMedical Image Analysis Center (MIAC), Basel, Switzerland.
Marco DueringMedical Image Analysis Center (MIAC), Basel, Switzerland.
Sue MoyDepartment of Radiology, Massachusetts General Hospital, Boston, MA, United States.
Karl G HelmerDepartment of Radiology, Massachusetts General Hospital, Boston, MA, United States.
Regina E Y KimResearch Institute, Neurophet Inc., Seoul, Republic of Korea.
Alzheimer's Disease Neuroimaging Initiative

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Accurate segmentation of brain regions in magnetic resonance imaging (MRI) is essential for diagnosing and managing neurological diseases. FreeSurfer is a widely used tool for brain MRI segmentation, but its limitations in speed and usability pose challenges in clinical practice. Neurophet AQUA, an advanced automated segmentation tool, aims to overcome these challenges by offering rapid and reliable segmentation. This study evaluates two segmentation pipelines: (1) a T1-based brain region segmentation pipeline, comparing the performance and reliability of Neurophet AQUA and FreeSurfer v7.3.2 using the standard recon-all pipeline in segmenting gray matter, white matter, and subcortical structures; and (2) a T2-FLAIR-based white matter lesion segmentation pipeline of Neurophet AQUA, assessing the detection of white matter hyperintensities (WMH). Methods: Four main datasets were used. For the T1-based segmentation pipeline, the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset was used to compare the segmentation results of Neurophet AQUA and FreeSurfer, with quality assessed by expert evaluation. The MarkVCID dataset was used to evaluate the scan-rescan repeatability and inter-scanner reproducibility of Neurophet AQUA. For the T2-FLAIR-based pipeline, WMH segmentation performance was assessed using 2D and 3D FLAIR sequences from the ADNI dataset by comparing the segmentations to ground truth (GT) labels and calculating Dice similarity coefficients (DSC). Results: Segmentation quality and reliability showed that Neurophet AQUA and FreeSurfer achieved comparable performance in most regions, with no significant differences. However, Neurophet AQUA had significantly faster processing time. In intracranial volume (ICV) measurements, Neurophet AQUA showed better repeatability than FreeSurfer in both rescans (ICC: 0.999 vs. 0.991) and inter-scanner settings (ICC: 0.983 vs. 0.866). AQUA also demonstrated consistent WMH segmentation across 2D and 3D FLAIR images. Conclusion: Neurophet AQUA demonstrated high segmentation accuracy and excellent repeatability in rescanned measurements, as well as exploratory evidence of inter-scanner reproducibility on T1-weighted MRI, showing comparable performance to established tools such as FreeSurfer. It also showed consistent WMH segmentation across FLAIR types. Neurophet AQUA is highly suitable for clinical applications that require accurate analysis, high repeatability and reproducibility, and rapid brain MRI processing, making it particularly well-suited for multicenter research studies.

Indexed as

automated segmentationbrain MRI segmentationinter-scanner reproducibilityscan-rescan repeatabilityT1-weighted MRIT2-FLAIRwhite matter hyperintensity

Identifiers

PMID41479607
PMCPMC12753458

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.