Alexander, DC

Atkinson, D

Bonet-Carne, E

Daducci, A

Johnston, E

Panagiotaki, E

Punwani, S

UCL Discovery

PROSENSE Conference on Prostate Cancer Diagnosis Bath, 12-13 September 2016  Please email the abstract to: prosense-conference@bath.ac.uk    Preference: Oral X  Topic: Prostate cancer biomarkers X  Poster    Probe characterisation   Either    Sensor technologies       System integration and validation   Non-invasive quantification of prostate cancer with VERDICT MRI: A repeatability study Elisenda Bonet-Carne1,2, Edward Johnston2, Alessandro Daducci3,4, Alexandra  Saborowska2, David Atkinson2, Shonit Punwani2, Daniel C. Alexander1, Eleftheria Panagiotaki1 1Centre for Medical Image Computing - UCL, UK; 2UCL Centre for Medical Imaging, UK; 3LTS5, École Polytechnique Fédérale de Lausanne, Switzerland, ; 4CHUV and UNIL, Switzerland  *Elisenda Bonet-Carne (e.bonet-carne@ucl.ac.uk) Diffusion-weighted MRI (DW-MRI) is becoming increasingly important in the assessment and characterisation of malignant tumours in the prostate1. However most DW-MRI studies use only the apparent diffusion coefficient (ADC) for cancer assessment, which lacks specificity and fails to associate contrast changes to particular microstructure features. Model-based quantitative imaging techniques can ameliorate problems associated with simplistic diffusion-based indices. One such example is VERDICT MRI2, a model-based DW-MRI technique that has been used to estimate microstructural differences between prostate tumours and normal tissue2,3. The aim of this study is to evaluate the VERDICT method in combination with an ultrafast fitting algorithm called AMICO4 for microstructural prostate tissue characterisation in a test-retest experiment. Six subjects underwent VERDICT DW-MRI using a 3T scanner (b-values range 90-3000 s/mm)5. The scan was repeated after a 2-minute interval. The VERDICT model was fitted to the data with the AMICO framework4 and microstructural parameter maps were computed. For each subject a board certified radiologist (EJ) contoured two regions of interest in the VERDICT fIC (Intracellular fraction) map: a region corresponding to a cancerous lesion and a region for normal tissue on the same slice and their median values were calculated. Bland-Altman plots were used to analyse the agreement between the maps from the two different acquisitions. The rest of the VERDICT parametric maps (fIC, fEES - extracellular extravascular fraction and cellularity) were also computed. All the VERDICT maps were repeatable and maximised lesion conspicuity. Quantitatively, Pearson r2 coefficients for the 3 maps were 0.929, 0.934, 0.896, respectively. See figure for fIC maps for both acquisitions (one patient) and the corresponding Bland-Altman plots. To conclude, VERDICT MRI can characterise microstructural differences between lesion and normal prostate tissue in a clinically practical time and a repeatable manner. This represents a significant step towards technical validation of the VERDICT estimates as imaging biomarkers. The method should be further evaluated in larger cohorts and the imaging parameters should be histologically validated. References and Acknowledgements: 1Padhani et al., 2009 Neoplasia, 2Panagiotaki et al, 2015, Invest Radiol, 3Bonet-Carne et al, 2016, ISMRM. 4Daducci et al, 2015, NeuroImage, 5Panagiotaki et al, 2015, ISMRM, PCUK: PG14-018-TR2, CCIC: 515729 GMAJB & BRC: 510419 GMAHD, EP/H046410/01, EP/G007748, EP/K020439/1, EP/M020533/1, EP/N018702/1, EP/N021967/1.  

Non-invasive quantification of prostate cancer with VERDICT MRI: A repeatability study

http://discovery.ucl.ac.uk/1513940/1/Bonet-Carne_PROSENSE_2016_bonetcarne_Final.pdf

Non-invasive quantification of prostate cancer with VERDICT MRI: A repeatability study

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