Evidence map›Paper›PMID 39736638›Full record

ArticleFluids and barriers of the CNS2024

The utility of customised tissue probability maps and templates for patients with idiopathic normal pressure hydrocephalus: a computational anatomy toolbox (CAT12) study.

Shigenori Kanno, Junyan Liu, Ai Kawamura, Shoko Ota, Nobuko Kawakami, Chifumi Iseki, Kazuo Kakinuma, Shiho Matsubara, Kazuto Katsuse, Kazushi Sato and 10 more

Erratum issuedAbstract readValidation Study
In one paragraph

Article in Fluids and barriers of the CNS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors.

Shigenori KannoDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan. shigenori.kanno.b4@tohoku.ac.jp.
Junyan LiuDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Ai KawamuraDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Shoko OtaDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Nobuko KawakamiDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Chifumi IsekiDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Kazuo KakinumaDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Shiho MatsubaraDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Kazuto KatsuseDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Kazushi SatoDepartment of Radiological Technology, South Miyagi Medical Centre, Shibata, Japan.
Takashi TakeuchiDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Yoshitaka TanakaDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Hiroyasu KodamaDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Tatsuo NagasakaDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Masahiro SaiDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Hayato OdagiriDepartment of Diagnostic Image Analysis, Tohoku University Graduate School of Medicine, Sendai, Japan.
Mioko SaitoDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Kentaro TakanamiDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Shunji MugikuraDepartment of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan.
Kyoko SuzukiDepartment of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.

Funding

JSPS KAKENHI JP20K11202
6 · The paper itself

Abstract

backgroundDisproportionately enlarged subarachnoid space hydrocephalus (DESH) is one of the neuroradiological characteristics of idiopathic normal pressure hydrocephalus (iNPH), which makes statistical analyses of brain images difficult. This study aimed to develop and validate methods of accurate brain segmentation and spatial normalisation in patients with DESH by using the Computational Anatomy Toolbox (CAT12).

methodsTwo hundred ninety-eight iNPH patients with DESH and 25 healthy controls (HCs) who underwent cranial MRI were enrolled in this study. We selected the structural images of 169 patients to create customised tissue probability maps and diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) templates for patients with DESH (DESH-TPM and DESH-Template). The structural images of 38 other patients were used to evaluate the validity of the DESH-TPM and DESH-Template. DESH-TPM and DESH-Template were created using the 114 well-segmented images after the segmentation processing of CAT12. In the validation study, we compared the accuracy of brain segmentation and spatial normalisation among three conditions: customised condition, applying DESH-TPM and DESH-Template to CAT12 and patient images; standard condition, applying the default setting of CAT12 to patient images; and reference condition, applying the default setting of CAT12 to HC images.

resultsIn the validation study, we identified three error types during segmentation. (1) The proportions of misidentifying the dura and/or extradural structures as brain structures in the customised, standard, and reference conditions were 10.5%, 44.7%, and 13.6%, respectively; (2) the failure rates of white matter hypointensity (WMH) cancellation in the customised, standard, and reference conditions were 18.4%, 44.7%, and 0%, respectively; and (3) the proportions of cerebrospinal fluid (CSF)-image deficits in the customised, standard, and reference conditions were 97.4%, 84.2%, and 28%, respectively. The spatial normalisation accuracy of grey and white matter images in the customised condition was the highest among the three conditions, especially in terms of superior convexity.

conclusionsApplying the combination of the DESH-TPM and DESH-Template to CAT12 could improve the accuracy of grey and white matter segmentation and spatial normalisation in patients with DESH. However, this combination could not improve the CSF segmentation accuracy. Another approach is needed to overcome this challenge.

Indexed as

BrainHydrocephalus, Normal PressureMagnetic Resonance ImagingAgedAged, 80 and overFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedProbabilitySubarachnoid SpaceBrain tissue segmentationCAT12 = computational anatomy toolboxDESH = disproportionately enlarged subarachnoid space hydrocephalusINPH = idiopathic normal pressure hydrocephalusSpatial normalisationTemplate

Identifiers

PMID39736638
PMCPMC11687168

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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.