Evidence map›Paper›PMID 41367747›Full record

ArticleQuantitative imaging in medicine and surgery2025

Creation of structural MRI brain templates for middle to late adulthood in the Thai population using single and multi-scanner data.

Kanokporn Pinyopornpanish, Uten Yarach, Chaisiri Angkurawaranon, Atiwat Soontornpun, Orasa Chawalparit, Chanon Ngamsombat, Ratthaporn Boonsuth, Atita Suwannasak, Yudthaphon Vichianin, Weerasak Muangpaisan and 2 more

Abstract read
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Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Kanokporn Pinyopornpanish *Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Uten Yarach *Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Chaisiri AngkurawaranonDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Atiwat SoontornpunDivision of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Orasa ChawalparitDepartment of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Chanon NgamsombatDepartment of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Ratthaporn BoonsuthDepartment of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Atita SuwannasakDepartment of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Yudthaphon VichianinDepartment of Radiological Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand.
Weerasak MuangpaisanDepartment of Preventive and Social Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Chaisak DumrikarnlertNeuroscience Center, Bangkok International Hospital, Bangkok, Thailand.
Salita AngkurawaranonGlobal Health and Chronic Conditions Research Group, Chiang Mai University, Chiang Mai, Thailand.ORCID https://orcid.org/0000-0001-6211-5717

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The global increase in elderly populations, particularly in low- and middle-income countries, underscores the rising prevalence of age-related conditions, such as Alzheimer's disease. Structural magnetic resonance imaging (MRI) plays a crucial role in Alzheimer's disease research and early diagnosis; however, manual brain segmentation is labor-intensive, time-consuming, and prone to inter-rater variability. Automated segmentation using existing brain templates from Mongoloid, Caucasoid, and Negroid populations may not be suitable for Thai individuals due to anatomical differences, emphasizing the need for population-specific templates. This study aimed to develop structural MRI brain templates tailored for cognitively normal Thai adults aged 50-70 years, using both single- and multi-scanner data. Methods: This study developed structural brain templates tailored for cognitively normal Thai adults aged 50-70 years. Participants underwent 3D T1-weighted MRI scans across three scanners. The image processing pipeline included bias field correction, rigid registration to standard space, and iterative non-rigid registration to ensure anatomical consistency. Two templates were created: TH150, based on data from a single scanner site, and TH240, constructed from multi-site data collected across three scanners. Results: Two templates were created: TH150 and TH240, which exhibited nearly identical brain spatial dimensions (width, length, and height). These features closely align with those obtained from individual brains through manual measurement, confirming the reliability of the template construction pipeline. Compared to CN200 and US200, the Thai templates showed 16-22% less gray matter, 2-9% less white matter, and 27-68% more cerebrospinal fluid. These differences likely reflect age-related changes, as the Thai templates were constructed from individuals aged 50-70 years, whereas the CN200 and US200 templates represent younger populations. Conclusions: These Thai adults aged 50-70 years population-specific templates reveal morphological differences from Chinese and Western templates. The high consistency between TH150 and TH240 supports methodological robustness, providing a foundation for future neuroimaging research and applications.

Indexed as

Brain templatesmiddle to late adulthoodstructural magnetic resonance imaging brain (structural MRI brain)Thai population

Identifiers

PMID41367747
PMCPMC12682506

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