{
  "abstract": "Purpose: To compare the image quality of diffusion-weighted imaging (DWI) between deep learning reconstruction (DLR)-applied Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) and MUltiplexed Sensitivity Encoding (MUSE) sequences in MRI of uterine malignancies.\n\nMaterials and methods: This retrospective study included 66 MRI examinations of 48 patients. The cohort consisted of cases with uterine malignancies (cervical cancer (n = 50), endometrial cancer (n = 15) and endometrial stromal sarcoma (n = 1)) at different clinical settings (initial staging, post-treatment, or recurrence). DWI was performed using both DLR-applied PROPELLER and MUSE sequences using b-values of 0 and 800 s/mm2. Two independent reviewers evaluated overall image quality, artifacts, sharpness, and lesion conspicuity using a 5-point Likert scale. Apparent diffusion coefficient (ADC), apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) were quantitatively measured in both sequences.\n\nResults: In the qualitative assessment, DLR-applied PROPELLER-DWI showed significantly fewer artifacts and better lesion conspicuity than MUSE-DWI. No significant difference was found in overall image quality or sharpness. Inter-reader agreement was slight to moderate, except for strong agreement on DLR-applied PROPELLER-DWI lesion conspicuity (κ = 0.696, good). Quantitatively, the mean ADC values were significantly higher with DLR-applied PROPELLER-DWI compared to MUSE-DWI for both readers (p < 0.001). Furthermore, both aSNR and aCNR were significantly higher with DLR-applied PROPELLER-DWI compared to MUSE-DWI.\n\nConclusions: DLR-applied PROPELLER-DWI demonstrated fewer artifacts and better lesion conspicuity than MUSE-DWI, with higher measured aSNR and aCNR. However, DLR-applied PROPELLER-DWI yielded significantly higher mean ADC values.\n\nSupplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s11604-026-02048-9.",
  "abstract_shown": true,
  "affiliations": [
    "Division of Radiology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, 36-1, Nishi-Cho, Yonago, Tottori, 683-8504 Japan",
    "Department of Clinical Radiology, Tottori University Hospital, Yonago, Japan"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Takuro Gonda",
      "orcid": "0009-0006-1456-0844"
    },
    {
      "affs": [
        0
      ],
      "name": "Ryoya Ochiai"
    },
    {
      "affs": [
        0
      ],
      "name": "Hiroto Yunaga"
    },
    {
      "affs": [
        1
      ],
      "name": "Kyohei Okuda"
    },
    {
      "affs": [
        1
      ],
      "name": "Yudai Ota"
    },
    {
      "affs": [
        0
      ],
      "name": "Shinya Fujii"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5wqzzmtyx6nmm.bib",
  "cited_by": 0,
  "doi": "10.1007/s11604-026-02048-9",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13722724/",
  "id": "5wqzzmtyx6nmm",
  "issns": [
    "1867-1071",
    "1867-108X"
  ],
  "landing_url": "https://doi.org/10.1007/s11604-026-02048-9",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Article"
    ],
    [
      "openalex",
      "2741|MRI in cancer diagnosis"
    ]
  ],
  "openalex": "W7167594148",
  "pdf_url": "https://link.springer.com/content/pdf/10.1007/s11604-026-02048-9.pdf",
  "pmcid": "PMC13722724",
  "pmid": "42412308",
  "published": "2026-07-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5wqzzmtyx6nmm.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:21:29Z",
      "native_id": "PMC13722724",
      "source": "pmc",
      "url": "https://doi.org/10.1007/s11604-026-02048-9"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|MRI in cancer diagnosis",
      "subfield": "imaging"
    }
  ],
  "title": "Deep learning reconstruction-applied PROPELLER diffusion-weighted imaging in uterine malignancies: a comparison study with MUSE",
  "title_text": "Deep learning reconstruction-applied PROPELLER diffusion-weighted imaging in uterine malignancies: a comparison study with MUSE",
  "type": "peer-reviewed",
  "updated_at": "2026-11-04T12:21:29Z",
  "url": "https://research.draconitic.com/paper/5wqzzmtyx6nmm",
  "venue": "Japanese Journal of Radiology",
  "versions": []
}