{
  "abstract": "Noninvasive live-cell imaging in deep human tissues is crucial for exploring the cellular biological and pathogenic processes, but remains a significant unmet challenge. Diffusion magnetic resonance imaging (dMRI) promises to narrow this gap by noninvasively providing cellular-level microstructural information. Within a single crowded voxel containing millions of living cells, the intricate cellular-level microstructures create numerous microcompartments, each characterized by a specific diffusivity. However, conventional dMRI methods relying on voxel-averaged macroscopic parameters, merely reflect aggregate microstructural properties and fail to quantify this distribution of microcompartment-specific diffusivity within a voxel, thereby obscuring microstructural details. Here, we propose an intravoxel diffusivity probability distribution (IDPD) model to resolve a wealth of essential microstructural information via quantifying microcompartment-specific diffusivity distribution, thereby enabling direct cellular-level characterization. This exceptional capability is realized through a multi-tiered analytical workflow spanning targeted single-voxel or region of interest (ROI) analysis to global visualization using dynamic videos and statistic parametric maps. Ultimately, the IDPD model enables noninvasive cellular-level microstructure imaging, offering a promising avenue to evaluate living cell functions in vivo.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2608.30430",
  "author_total": 7,
  "authors": [
    {
      "name": "Xiaodong Li"
    },
    {
      "name": "Jing Zhao"
    },
    {
      "name": "Baolan Lu"
    },
    {
      "name": "Jinzhu Wang"
    },
    {
      "name": "Xinhua Wei"
    },
    {
      "name": "Qingxian Yang"
    },
    {
      "name": "Xuegang Xin"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4sdnxn2dseztr.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2608.30430",
  "fulltext_url": null,
  "id": "4sdnxn2dseztr",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2608.30430",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.bio-ph"
    ],
    [
      "arxiv",
      "physics.med-ph"
    ],
    [
      "openalex",
      "2741|Advanced Neuroimaging Techniques and Applications"
    ]
  ],
  "openalex": "W7204963538",
  "pdf_url": "https://arxiv.org/pdf/2608.30430",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-31",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4sdnxn2dseztr.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:41Z",
      "native_id": "2608.30430",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2608.30430"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.bio-ph",
      "subfield": "biological-medical"
    }
  ],
  "title": "Imaging cellular-level brain microstructure with diffusion MRI",
  "title_text": "Imaging cellular-level brain microstructure with diffusion MRI",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:41Z",
  "url": "https://research.draconitic.com/paper/4sdnxn2dseztr",
  "venue": "arXiv",
  "versions": []
}