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Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI.
- Source :
-
European radiology [Eur Radiol] 2017 Feb; Vol. 27 (2), pp. 627-636. Date of Electronic Publication: 2016 May 24. - Publication Year :
- 2017
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Abstract
- Objectives: Assessment of empirical diffusion-weighted MRI (DW-MRI) models in cervical tumours to investigate whether fitted parameters distinguish between types and grades of tumours.<br />Methods: Forty-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 <superscript>-2</superscript> ). Mono-exponential, stretched exponential, kurtosis, statistical, and bi-exponential models were fitted. Model preference was assessed using Bayesian Information Criterion analysis. Differences in fitted parameters between tumour types/grades and correlation between fitted parameters were assessed using two-way analysis of variance and Pearson's linear correlation coefficient, respectively.<br />Results: Non-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.<br />Conclusions: Non-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.<br />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.
- Subjects :
- Bayes Theorem
Carcinoma, Squamous Cell pathology
Cervix Uteri diagnostic imaging
Cervix Uteri pathology
Female
Humans
Male
Models, Theoretical
Neoplasm Grading
Prospective Studies
Adenocarcinoma diagnostic imaging
Carcinoma, Squamous Cell diagnostic imaging
Diffusion Magnetic Resonance Imaging methods
Uterine Cervical Neoplasms diagnostic imaging
Uterine Cervical Neoplasms pathology
Subjects
Details
- Language :
- English
- ISSN :
- 1432-1084
- Volume :
- 27
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- European radiology
- Publication Type :
- Academic Journal
- Accession number :
- 27221560
- Full Text :
- https://doi.org/10.1007/s00330-016-4417-0