9 Abstracts Accepted for Presentation in Rheumatology and Oncology Upcoming Meetings

Nine IAG’s abstracts, reflecting clinical research innovations of the past year, were accepted for presentation in the industry’s leading #rheumatology and #oncology scientific meetings.

In the next 3 months, IAG’s scientific team will present our scientific work in inflammatory arthritis, osteoarthritis, degenerative and genetic muscle diseases, scleroderma, rare musculoskeletal diseases at European League Against Rheumatism (#EULAR2018), 13-16 June 2018, Amsterdam, Netherlands and World Congress Osteoarthritis (#OARSI2018), 26-29 April 2018, Liverpool, UK. 

4 abstracts focused on the strategic use of imaging in clinical research in oncology, including immuno-oncology, neuro-oncology, renal cancer and solid tumours will be presented at American Society of Clinical Oncology (#ASCO2018), June 1-5, 2018 Chicago, USA.

The works selected for publication are based on the results of innovative clinical research studies, which involve state-of-the-art and cutting-edge advanced imaging techniques, quantitative methodologies for assessment of treatment efficacy, including some that are based on machine learning and AI concepts. We warmly thank our collaborators, scientific advisors and biotechnology and pharmaceutical partners for their contributions and delighted to share the details of the abstracts below.

Please contact the team to schedule meetings: contact@ia-grp.com

ABSTRACTS:

CHANGE IN MUSCLE VOLUME AND MUSCLE FAT FRACTION AS POTENTIAL NON-INVASIVE BIOMARKERS OF DISEASE PROGRESSION: MACHINE LEARNING FRAMEWORK FOR QUANTITATIVE ANALYSIS OF MRI DATA, D. Fischer, P. Hafner, S. Schmidt, M. Hinton, J. Gonzalez, O. Kubassova, European League Against Rheumatism (EULAR), 2018.

In this study, we present a novel machine learning approach to segmentation of thigh muscles from MRI and the subsequent calculation of fat fraction from DIXON images to assess the quality of the muscle and its perfusion. We confirmed correlation between the manual and automated approaches to be 0.9396. Details of the method and discussion on measuring the treatment efficacy through the imaging biomarkers will be presented at EULAR, Poster session II – 15.06.2018 from 11:45 to 13:30 – Poster area ‘Diagnostics and imaging procedures

DYNAMIC CONTRAST ENHANCED (DCE)-MRI IN RELATION TO INFLAMMATORY MARKERS IN SERUM AND JOINT FLUID: INITIAL DATA AND VALIDATION IN FOUR MOST COMMON KNEE ARTHRITIC DISEASES, M. Boesen, O. Kubassova, A. Taylor, R. Riis, L. Hornum, H. Bliddal, C. Ballegaard, E. M. Bartels, European League Against Rheumatism (EULAR), 2018

In this study, we linked quantitative imaging and blood biomarkers of inflammation in the four most common knee arthritic diseases, RF + Rheumatoid Arthritis, RF- Rheumatoid Arthritis, Psoriatic Arthritis and Osteoarthritis, showing how imaging may have specific utility in differentiating these conditions, especially when multi-biomarker assays lacked complete sensitivity and specificity.

Poster session II – 15.06.2018 from 11:45 to 13:30 – Poster area ‘Diagnostics and imaging procedures’ 

DIGITAL ARTERY VOLUME INDEX: THE FIRST OBJECTIVE, NON INVASIVE IMAGING DIAGNOSTIC OF MACROVASCULAR INVOLVEMENT IN SCLERODERMA (SSC), Lettieri G, Abignano G, Bagnato G, Eng S, Ridgway JP, Kaftan J, Hinton M, Kubassova A, Buch M, Emery P, O’Connor P, Del Galdo F, European League Against Rheumatism (EULAR), 2018.

This study presents the first objective, non-invasive imaging diagnostic of macrovascular involvement in Scleroderma and assess its sensitivity to change in SSc patients. Its potential utility as an early diagnostic of neointima proliferation in SSc will be presented in Poster session II – 15.06.2018 from 11:45 to 13:30 – Poster area ‘Diagnostics and imaging procedures

QUANTITATIVE MRI OF SINGLE VS. MULTIPLE JOINTS IN JUVENILE IDIOPATHIC ARTHRITIS AS PREDICTIVE MEASURE OF CLINICAL OUTCOMES, Tzaribachev, O. Kubassova, M. Hinton, M. Boesen, European League Against Rheumatism (EULAR), 2018.

In this study, we return to inflammatory disease assessment in patients with juvenile rheumatoid arthritis and provide consistent validation of Dynamic Enhanced MRI scores (DEMRIQ) against clinical examination, showing that DEMRIQ-V and DEMRIQ-ME scores, which either followed clinical response (DEMRIQ-ME) or predicted clinical outcomes at 6 months (DEMRIQ-V) in most patients can support early clinical and research decisions.

Poster session II – 15.06.2018 from 11:45 to 13:30 – Poster area ‘Diagnostics and imaging procedures’ 

COMBINING FRACTAL- AND ENTROPY-BASED BONE TEXTURE ANALYSIS FOR THE PREDICTION OF OSTEOARTHRITIS: DATA FROM THE MULTICENTER OSTEOARTHRITIS STUDY, R.Ljuhar, et. all European League Against Rheumatism (EULAR), 2018.

Poster session II – 15.06.2018 from 11:45 to 13:30 – Poster area ‘Diagnostics and imaging procedures’

DELAYED GADOLINIUM ENHANCED MRI OF MENISCI AND CARTILAGE (DGEMRIM/DGEMRIC) IN OVERWEIGHT PATIENTS WITH KNEE OSTEOARTHRITIS, Stine Hangaard, Henrik Gudbergsen, Cecilie L . Daugaard, Henning Bliddal, Janus Damm Nybing, Miika T. Nieminen, Victor Casula, Carl-Johan Tiderius, Mikael Boesen, World Congress Osteoarthritis (OARSI), 2018

This paper examines the relationship between i.a. dGEMRIC and delayed Gadolinium enhanced MRI of menisci (dGEMRIM) in a cohort of 85 osteoarthritis patients and investigates if the approach can be used to assess the morphological degeneration of menisci. The details of the techniques will be presented as a poster at OARSI poster sessions

ASSESSING DCE-MRI AND DWI AS TREATMENT RESPONSE BIOMARKERS AFTER SABR FOR PRIMARY RENAL CELL CARCINOMA, Hayley Reynolds, Bimal Parameswaran, Mary Finnegan, Diana Roettger, Eddie Lau, Tomas Kron, Mark Shaw, Sarat Chander, and Shankar Siva, American Society of Clinical Oncology (ASCO), 2018

Assessment of treatment response for renal cell carcinoma (RCC) is typically carried out using anatomical CT sized-based RECIST 1.1 criteria. Recently, our group completed a prospective trial delivering stereotactic ablative body radiotherapy (SABR) to patients with, while assessing treatment efficacy using advanced MRI techniques and novel early treatment response biomarkers. The details will be presented at ASCO.

NON-INVASIVE IN VIVO PREDICTION OF TUMOUR GRADE AND IDH MUTATION STATUS IN GLIOMAS USING DYNAMIC SUSCEPTIBILITY CONTRAST (DSC) PERFUSION- AND DIFFUSION-WEIGHTED MRI. Sotirios Bisdas, Cristiana Tisca, Carole Sudre, Eser Sanverdi, Diana Roettger, Jorge M Cardoso, American Society of Clinical Oncology (ASCO), 2018

In this study, we investigated the relevance of texture and statistical features extracted from perfusion and diffusion MRI parametric maps (PMs) to discriminate between WHO grades and IDH mutation status in gliomas to determine if such novel assessment may enhance tumour grading, improving patient selection for specific treatment options.

THE ROLE OF DIFFUSION TENSOR IMAGING FOR NON-INVASIVE IDH PHENOTYPING IN GLIOMAS, Diana Roettger, Jialin Yuan, Laura Mancini, Steffi Thust, Sebastian Brandner, Jeremy Rees, Andrew McEvoy, Sotirios Bisdas, American Society of Clinical Oncology (ASCO), 2018

This study explores whether diffusion tensor imaging (DTI) metrics can differentiate IDH mutation status in gliomas using 76 IDH mutant type and 27 IDH wild-type gliomas histopathologically verified with pre-treatment DTI. The details how the integration of the DTI metrics with demographic information may help to provide a non-invasive molecular stratification of the gliomas will be presented at ASCO.

THE ROLE OF DYNAMIC SUSCEPTIBILITY CONTRAST PERFUSION- WEIGHTED MRI IN THE ESTIMATION OF IDH MUTATION IN GLIOMAS, Sotirios Bisdas, Eser Sanverdi, Carole Sudre, Diana Roettger, Sebastian Brandner, Vasileios Katsaros, American Society of Clinical Oncology (ASCO), 2018

Dynamic Susceptibility Contrast Perfusion- Weighted Imaging (DSC – PWI) is a relatively recently established technique for gliomas staging and its diagnostic accuracy may benefit when using sophisticated image analysis algorithms. In this study, we aimed to investigate whether DSC – PWI, enhanced by texture analysis and machine learning, can stratify gliomas according to their IDH mutation status using a cohort of 208 patients. The details will be presented at ASCO.

Please contact the team to schedule meetings: contact@ia-grp.com