Posters
« Back
Computer Aided-Detection of sacroiliitis on MRI with Dynamika: pilot study
EP23282
Computer Aided-Detection of sacroiliitis on MRI with Dynamika: pilot study
Submitted on 14 Aug 2015

Strouhal P1, Roettger D2, Hagoug R2, Kubassova O2
1. Royal Wolverhampton NHS Trust 2. Image Analysis Ltd
This poster was presented at UKRC 2015
Poster Views: 1,846
View poster »
Poster Abstract
Aims:
Sacroiliitis is difficult to diagnose and harder still to quantify or monitor response. Dynamika is a stand-alone, cloud-based software using complex algorithms to allow real-time, user-defined analysis of regions of interest (ROI)in 3D and allows quantification of signal intensity (and/or contrast enhancement) within these ROIs on scans. The ROI evaluation technique in simplest guise was used to evaluate isotope imaging as proof of principle but we aim to show similar/better success with this software on STIR MR images.

Content:
50 MRI and 30 bone scans were analysed to evaluate initial validity of Dynamika software, including some follow-up imaging - giving insight into how disease monitoring could be undertaken. This analysis was benchmarked against scintigraphy standard peak-trough algorithm analysis.

Impact:
Potential to diagnose and grade disease and also monitor response with MRI, as well as show its superiority compared with bone scanning - though show utility of the software with bone scans also.

Outcomes:
Positive Negative Total
Bone scan 5 25 30
MRI scan (visual) 13 37 50
MRI (+Dynamika) 21 29 50
Clinical picture 19 31 50


Quantitative assessment:
“Positivity” of result: visual v ‘score’
Score rating Mild/ Moderate/ Severe
MRI result 11 mild; 1 moderate; 1 severe
MRI Dynamika outcome 7 mild; 7 moderate, 7 severe
Dynamika clinical correlation 2 false positive, no false negative:
100% sens; 94% spec; NPV 100%

Patients can be quantitatively graded into mild, moderate or severe sacroiliitis with greatest reliability using MRI +Dynamika.


Discussion:
Needs validating in bigger studies but initial results of Dynamika software are promising and simple to reproduce in evaluating sacroiliitis, with some correlation between results and the clinical scenario in a way not applicable to bone scintigraphy without the penalty of ionising radiation or contract administration.

1. Bozkurt MF and Kiratli P. Quantitative sacroiliac scintigraphy for pediatric patients: comparison of two methods. Ann Nucl Med. 2014 Apr;28(3):227-31;
2. Tiwari BP and Basu S. Estimation of sacroiliac joint index in normal subjects of various age groups... Nucl Med Rev Cent East Eur. 2013;16(1):26 30;
3. Kubassova O, et al. A computer-aided detection system for rheumatoid arthritis MRI data interpretation and quantification of synovial activity. Eur J Radiol. 2010 Jun;74(3):e67-72;
4. Althoff CE et al. Magnetic resonance imaging of active sacroiliitis: do we really need gadolinium? Eur J Radiol. 2009 Aug;71(2):232-6
Report abuse »
Questions
Ask the author a question about this poster.
Ask a Question »

Creative Commons

Related Posters


A Novel Method For Discovery of Peripheral Blood Biomarkers in Idiopathic Pulmonary Fibrosis Using Extensive Depletion and TMTcalibratorTM Tissue-Enhanced Plasma Proteomics
I. Pike1, M. Bremang1, P.J. Wolters 2, R. Gaster3, S. Turner3, M. Decaris3

Strategies for High-Titer Protein Expression Using the ExpiCHO and Expi293 Transient Expression Systems
Chao Yan Liu, Jian Liu, Wanhua Yan, Kyle Williston, Katy Irvin, Henry Chou, Jonathan Zmuda

A Chemically-Defined Baculovirus-Based Expression System for Enhanced Protein Production in Sf9 Cells
Maya Yovcheva, Sara Barnes, Kenneth Thompson, Melissa Cross, Katy Irvin, Mintu Desai, Natasha Lucki, Henry Chiou, Jonathan Zmuda

Addressing Technical, Legal and Diplomatic Obstacles To Combatting Human Trafficking Using DNA Databases Across National Boundaries
Michael J. Hennesseya, Jon Krollb, Jose A. Lorentec and Howard D. Cashb*

The EurOPDX EDIReX project: towards a European Research Infrastructure on patient-derived cancer models
E. Vinolo 1, J.P. Morris 1, D.G. Alférez 2, J. Arribas 3,4,5, C. Bernadó 3,4,5, A. Bertotti 6, A. Bruna 7, A.T. Byrne 8, C. Caldas 7, R.B. Clarke 2, N. Conte 9, R. Corsi 10, S. Corso 6, M. Crespo 3, A. Dahmani 11, V. Dangles-Marie 11, D. Decaudin 11, Z. Dudová 12, A. Fiori 6, S. Giordano 6, M. Hauptsmann 13, M. Hidalgo 14, C. Isella 6, S. de Jong 15, J. Jonkers 13, A. Křenek 12, O. Krijgsman 13, D. Kouřil 12, J.C. Lacal 14, L. Lanfrancone 16, E. Leucci 17, G.M. Mælandsmo 18, E. Marangoni 11, J. Mason 9, M.Th. Mayrhofer 19, A. Mazzocca 6, T.S. Meehan 9, E. Montaudon 11, F. Nem