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TAU PET HARMONIZATION VIA SURFACE-BASED DIFFUSION MODEL
Jiaxin Yue, Jianwei Zhang, Lujia Zhong, Yonggang Shi. Proceedings. IEEE International Symposium on Biomedical Imaging, 2025-05-12
Topic: Plasma and spinal-fluid biomarkers
The heterogeneity inherent in tau positron emission tomography (PET) imaging data across different tracers challenges the integration of multi-site tau PET data, thereby necessitating the trustful harmonization technique for a better utilization of the emerging large-scale datasets. Unlike other imaging modalities, the harmonization among multi-site tau PET data involves more than intensity mapping but contains intricate pattern alterations attributed to tracer binding properties, which makes the existing statistical methods inadequate. Meanwhile, the effective data preprocessing is required to eliminate the artifacts caused by off-target binding and partial volume effect for meaningful comparison and harmonization. In this paper, we propose a systematic tau PET harmonization framework that involves the surface-based data preprocessing and diffusion model for generating the vertex-wise mapping between multi-site tau standardized uptake value ratio (SUVR) on the cortical surface. In the experiments, using large-scale Alzheimer's Disease Neuroimaging Initiative (ADNI) and Health and Aging Brain Study-Health Disparities (HABS-HD) data with different tracers, we demonstrate our method can successfully achieve harmonization by generating the SUVR maps with consistent pattern distributions and persevering the individual variability.
Key findings
- The heterogeneity inherent in tau positron emission tomography (PET) imaging data across different tracers challenges the integration of multi-site tau PET data, thereby necessitating the trustful harmonization technique for a better utilization of the emerging large-scale datasets.
- Unlike other imaging modalities, the harmonization among multi-site tau PET data involves more than intensity mapping but contains intricate pattern alterations attributed to tracer binding properties, which makes the existing statistical methods inadequate.
- Meanwhile, the effective data preprocessing is required to eliminate the artifacts caused by off-target binding and partial volume effect for meaningful comparison and harmonization.
- In this paper, we propose a systematic tau PET harmonization framework that involves the surface-based data preprocessing and diffusion model for generating the vertex-wise mapping between multi-site tau standardized uptake value ratio (SUVR) on the cortical surface.
- In the experiments, using large-scale Alzheimer's Disease Neuroimaging Initiative (ADNI) and Health and Aging Brain Study-Health Disparities (HABS-HD) data with different tracers, we demonstrate our method can successfully achieve harmonization by generating the SUVR maps with consistent pattern distributions and persevering the individual variability.
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Study details
- Evidence strengthLow
How this study scored 43/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record, multi-centre collaboration and free to read, so those were left out: it earned 24 of the 56 points we could judge it on, which is 43 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Proceedings. IEEE International Symposium on Biomedical Imaging) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40881622) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 24 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 24 of the 56 points we could judge it on is 43 out of 100. |
| Total | 43 / 100 | — |
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APA 7th
Yue, J., Zhang, J., Zhong, L., & Shi, Y. (2025). TAU PET HARMONIZATION VIA SURFACE-BASED DIFFUSION MODEL. Proceedings. IEEE International Symposium on Biomedical Imaging. https://doi.org/10.1109/isbi60581.2025.10981166
Vancouver
Yue J, Zhang J, Zhong L, Shi Y. TAU PET HARMONIZATION VIA SURFACE-BASED DIFFUSION MODEL. Proceedings. IEEE International Symposium on Biomedical Imaging. 2025. doi:10.1109/isbi60581.2025.10981166. PMID: 40881622.
BibTeX
@article{yue2025-40881622,
author = {Yue, Jiaxin and Zhang, Jianwei and Zhong, Lujia and Shi, Yonggang},
title = {{TAU PET HARMONIZATION VIA SURFACE-BASED DIFFUSION MODEL}},
journal = {Proceedings. IEEE International Symposium on Biomedical Imaging},
year = {2025},
doi = {10.1109/isbi60581.2025.10981166},
pmid = {40881622},
url = {https://doi.org/10.1109/isbi60581.2025.10981166}
}