ArticleEuropean radiology2017
Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI.
Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed, 76 citations in OpenAlex.
- Development and evaluation of a cervical cancer-specific restriction spectrum imaging (RSI) model.Magnetic resonance imaging · 2026Article
- Advanced Diffusion MRI in Cervical Cancer: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Differentiation of cervical cancer subtypes using machine learning models on MRI images.Polish journal of radiology · 2026Article
- Interpretable ensemble learning model using intratumoral and peritumoral multi-sequence MR-radiomics predicts high-grade cervical cancer with lymphovascular space invasion.Frontiers in oncology · 2026Article
- MRI cytometry imaging for cervical cancer differential diagnosis: a preliminary study.BMC medical imaging · 2025Article
- Prospective comparison of synthetic high b-value field of view optimized and constrained undistorted multiplexed sensitivity encoding (FOCUS-MUSE) and FOCUS diffusion-weighted imaging in evaluating cervical cancer.Quantitative imaging in medicine and surgery · 2025Article
- Intra-voxel incoherent motion biomarker repeatability in healthy volunteers and sensitivity to chemoradiotherapy-induced changes in patients with uterine cervical cancer.Frontiers in oncology · 2025Article
- Whole-tumor histogram analysis of multiple non-Gaussian diffusion models at high b values for assessing cervical cancer.Abdominal radiology (New York) · 2024Article
- T1 mapping as a quantitative imaging biomarker for diagnosing cervical cancer: a comparison with diffusion kurtosis imaging.BMC medical imaging · 2024Article
- Radiomics-based machine learning models for differentiating pathological subtypes in cervical cancer: a multicenter study.Frontiers in oncology · 2024Article
- Added-value of 3D amide proton transfer MRI in assessing prognostic factors of cervical cancer: a comparative study with multiple model diffusion-weighted imaging.Quantitative imaging in medicine and surgery · 2023Article
- T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study.The British journal of radiology · 2023Article
- Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.Japanese journal of radiology · 2023Article
- Article
- Intravoxel Incoherent Motion (IVIM) MR Quantification in Locally Advanced Cervical Cancer (LACC): Preliminary Study on Assessment of Tumor Aggressiveness and Response to Neoadjuvant Chemotherapy.Journal of personalized medicine · 2022Article
- Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease.Brain imaging and behavior · 2022Article
- Native T1-mapping and diffusion-weighted imaging (DWI) can be used to identify lung cancer pathological types and their correlation with Ki-67 expression.Journal of thoracic disease · 2022Article
- Article
- Prediction of outcomes by diffusion kurtosis imaging in patients with large (≥5 cm) hepatocellular carcinoma after liver resection: A retrospective study.Frontiers in oncology · 2022Article
- A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma.Contrast media & molecular imaging · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesAssessment of empirical diffusion-weighted MRI (DW-MRI) models in cervical tumours to investigate whether fitted parameters distinguish between types and grades of tumours.
methodsForty-two patients (24 squamous cell carcinomas, 14 well/moderately differentiated, 10 poorly differentiated; 15 adenocarcinomas, 13 well/moderately differentiated, two poorly differentiated; three rare types) were imaged at 3 T using nine b-values (0 to 800 s mm
resultsNon-mono-exponential models were preferred by 83 % of tumours with bi-exponential and stretched exponential models preferred by the largest numbers of tumours. Apparent diffusion coefficient (ADC) and diffusion coefficients from non-mono-exponential models were significantly lower in poorly differentiated tumours than well/moderately differentiated tumours. α (stretched exponential), K (kurtosis), f and D* (bi-exponential) were significantly different between tumour types. Strong correlation was observed between ADC and diffusion coefficients from other models.
conclusionsNon-mono-exponential models were preferred to the mono-exponential model in DW-MRI data from cervical tumours. Parameters of non-mono-exponential models showed significant differences between types and grades of tumours. KEY POINTS: • Non-mono-exponential DW-MRI models are preferred in the majority of cervical tumours. • Poorly differentiated cervical tumours exhibit lower diffusion coefficients than well/moderately differentiated tumours. • Non-mono-exponential model parameters α, K, f, and D* differ between tumour types. • Micro-structural features are likely to affect parameters in non-mono-exponential models differently.
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