Modelling DW-MRI data from primary and metastatic ovarian tumours

Winfield, Jessica M.; deSouza, Nandita M.; Priest, Andrew N.; Wakefield, Jennifer C.; Hodgkin, Charlotte; Freeman, Susan; Orton, Matthew; Collins, David J.

doi:10.1007/s00330-014-3573-3

Cited by 56 publications

(59 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The absence of a clear preference for a particular model within each grade and type of tumour indicates that the models assessed here are applicable across all tumours and the choice of model is not driven purely by characteristics of a particular tumour grade or type. The preference for a non-mono-exponential model fit for the data from these tumours is consistent with results from other studies: a study in squamous cell carcinoma of the head and neck demonstrated that the kurtosis model provided a better fit to DW-MRI data than the mono-exponential model in primary tumours and in metastatic lymph nodes [7] and a study in advanced ovarian cancer demonstrated a preference for the stretched exponential model over the mono-exponential model in the majority of primary and metastatic lesions in DW-MRI data both pre- and post-treatment [11]. Clinical studies comparing various models for DW-MRI data from prostate cancer have also demonstrated a better fit in malignant as well as benign regions using the bi-exponential model [6] or the kurtosis model [17] compared with the mono-exponential model.…”

Section: Discussionmentioning

confidence: 99%

“…The use of non-mono-exponential models provides a better description of the DW-MRI signal, and parameters derived from these models allow more detailed investigation of differences between tumour sub-types or inter-tumour heterogeneity [6–11] and may also provide an earlier indication of response to treatment [12, 13]. However, use of a model with a large number of additional parameters risks over-fitting the data and may be sensitive to noise characteristics of the system rather than structural properties of the tumour or normal tissue.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI

et al. 2016

Self Cite

View full text Add to dashboard Cite

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-2). 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.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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…Within different DWI models, the f and D * parameters from the IVIM model have a correlation of 0.65, which although not large indicates that they have an appreciable covariance and are difficult to confidently report (from this acquisition scheme). The very low correlation between α and DDC α in the stretched exponential model (0.083) suggests that these parameters are unique and identifiable parameters [28], associated with independent tissue properties, and thus provide more information than the simple ADC model [29]. The same is true of the pseudo-diffusion-related parameters in the IVIM model, and K in the kurtosis model, although the higher CVs observed for these may limit their utility.…”

Section: Discussionmentioning

confidence: 99%

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

et al. 2016

Self Cite

View full text Add to dashboard Cite

ObjectivesTo examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours.MethodsPaediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0–1000 mm−2 s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians.ResultsThe values for ADC, D, DDCα, α, and DDCK gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDCα, and DDCK were strongly correlated (ρ > 0.9), DDCα and α were not correlated (ρ = 0.083).ConclusionPerfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDCα and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data.Key Points • ADC has good repeatability as low 5th centile of the histogram distribution. • High CV was observed for all parameters at extremes of histogram. • Parameters from the stretched exponential model showed low coefficients of variation. • The median ADC, D, DDC α , and DDC K are highly correlated and repeatable. • Perfusion/kurtosis parameters showed high CV variations across their histogram distributions.

show abstract

“…Although, the choice of the mathematical model depends on the anatomical region in the study but it is imperative to have the flexibility of using different models as this could influence repeatability. In a recent study on primary and secondary ovarian cancer, a stretched exponential model showed better repeatability over mono-exponential and biexponential models [151] . Finally, in any DW-MRI study, system-induced variability must be established using a standardized phantom as was recommended in the 2009 meeting report [5] .…”

Section: Need For Validationmentioning

confidence: 99%

Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients,in-vitroandin-vivoreproducibility

Jafar

Parsaï

Miquel

2016

WJR

View full text Add to dashboard Cite

There is considerable disparity in the published apparent diffusion coefficient (ADC) values across different anatomies. Institutions are increasingly assessing repeatability and reproducibility of the derived ADC to determine its variation, which could potentially be used as an indicator in determining tumour aggressiveness or assessing tumour response. In this manuscript, a review of selected articles published to date in healthy extracranial body diffusion-weighted magnetic resonance imaging is presented, detailing reported ADC values and discussing their variation across different studies. In total 115 studies were selected including 28 for liver parenchyma, 15 for kidney (renal parenchyma), 14 for spleen, 13 for pancreatic body, 6 for gallbladder, 13 for prostate, 13 for uterus (endometrium, myometrium, cervix) In addition, six phantom studies and thirteen in vivo studies were summarized to compare repeatability and reproducibility of the measured ADC. All selected phantom studies demonstrated lower intra-scanner and inter-scanner variation compared to in vivo studies. Based on the findings of this manuscript, it is recommended that protocols need to be optimised for the body part studied and that system-induced variability must be established using a standardized phantom in any clinical study. Reproducibility of the measured ADC must also be assessed in a volunteer population, as variations are far more significant in vivo compared with phantom studies. Core tip: Diffusion-weighted magnetic resonance imaging was highlighted as a potential cancer imaging biomarker by a team of experts in a report published in 2009. We review the variability of published diffusion values in the major extra-cranial organs and focus on the validation literature, both in vivo and in vitro . A total of 115 studies were selected including for liver parenchyma, kidney, pancreatic body, spleen, gallbladder, prostate, uterus (endometrium, myometrium, cervix) and breast. We also look in detail at the published repeatability and reproducibility studies, both in vivo and in phantoms. A series of recommendations based on our findings are given at the end of this review.Jafar MM, Parsai A, Miquel ME. Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in vitro and in vivo reproducibility.

show abstract

Modelling DW-MRI data from primary and metastatic ovarian tumours

Cited by 56 publications

References 27 publications

Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI

Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients,in-vitroandin-vivoreproducibility

Contact Info

Product

Resources

About