A multiparametric alternative to short inversion-time inversion recovery for imaging inflammation: T2water and fat fraction measurement using chemical shift–encoded turbo spin-echo MRI

Purpose: Short-inversion-time inversion-recovery MRI is used widely for imaging bone and soft-tissue inflammation in rheumatic inflammatory diseases, but there is no widely available quantitative equivalent of this sequence. This limits our ability to objectively assess inflammation and distinguish it from other processes. To address this, we investigate the use of the widely available Dixon turbo spin echo (TSE Dixon) sequence as a practical approach to simultaneous water-specific T2 (T2water) and fat fraction (FF) measurement.// Methods: We use a series of TSE Dixon acquisitions with varying effective TEs (TEeff) to quantify T2water and FF. The validity of this approach is assessed in a series of phantom and in vivo experiments, with reference values provided by Carr-Purcell-Meiboom-Gill acquisitions, MRS, and phantoms. The effect of inflammation on parameter values is evaluated in patients with spondyloarthritis.// Results: The T2water estimates obtained from TSE Dixon were accurate compared with the reference values from Carr-Purcell-Meiboom-Gill and spectroscopy in both fat-free environments and in the presence of fat. FF measurements with T2water correction from TSE Dixon were accurate from 0% to 60% FF and were not confounded by T2water variations. In vivo imaging produced good quality images that were artifact free, produced plausible T2 values, separating and quantifying the effect of inflammation on T2water and FF.// Conclusion: The T2water and FF measurements based on TSE Dixon with effective TE increments are accurate over a range of T2 and FF values and could provide a widely available quantitative alternative to the short-inversion-time inversion-recovery sequence for imaging inflamed tissue

Volume of hyperintense inflammation (VHI): A quantitative imaging biomarker of inflammation load in spondyloarthritis, enabled by human-machine cooperation

Qualitative visual assessment of MRI scans is a key mechanism by which inflammation is assessed in clinical practice. For example, in axial spondyloarthritis (axSpA), visual assessment focuses on the identification of regions with increased signal in the bone marrow, known as bone marrow oedema (BMO), on water-sensitive images. The identification of BMO has an important role in the diagnosis, quantification and monitoring of disease in axSpA. However, BMO evaluation depends heavily on the experience and expertise of the image reader, creating substantial imprecision. Deep learning-based segmentation is a natural approach to addressing this imprecision, but purely automated solutions require large training sets that are not currently available, and deep learning solutions with limited data may not be sufficiently trustworthy for use in clinical practice. To address this, we propose a workflow for inflammation segmentation incorporating both deep learning and human input. With this ‘human-machine cooperation’ workflow, a preliminary segmentation is generated automatically by deep learning; a human reader then ‘cleans’ the segmentation by removing extraneous segmented voxels. The final cleaned segmentation defines the volume of hyperintense inflammation (VHI), which is proposed as a quantitative imaging biomarker (QIB) of inflammation load in axSpA. We implemented and evaluated the proposed human-machine workflow in a cohort of 29 patients with axSpA who had undergone prospective MRI scans before and after starting biologic therapy. The performance of the workflow was compared against purely visual assessment in terms of inter-observer/inter-method segmentation overlap, inter-observer agreement and assessment of response to biologic therapy. The human-machine workflow showed superior inter-observer segmentation overlap than purely manual segmentation (Dice score 0.84 versus 0.56). VHI measurements produced by the workflow showed similar or better inter-observer agreement than visual scoring, with similar response assessments. We conclude that the proposed human-machine workflow offers a mechanism to improve the consistency of inflammation assessment, and that VHI could be a valuable QIB of inflammation load in axSpA, as well as offering an exemplar of human-machine cooperation more broadly

Quantitative magnetic resonance imaging (qMRI) in Axial Spondyloarthritis

Imaging, and particularly magnetic resonance imaging (MRI), plays a crucial role in the assessment of inflammation in rheumatic disease, and forms a core component of the diagnostic pathway in axial spondyloarthritis (axSpA). However, conventional imaging techniques are limited by image contrast being non-specific to inflammation and a reliance on subjective, qualitative reader interpretation. Quantitative MRI (qMRI) methods offer scope to address these limitations and improve our ability to accurately and precisely detect and characterise inflammation, potentially facilitating a more personalised approach to management. Here, we review qMRI methods and emerging quantitative imaging biomarkers (QIBs) for imaging inflammation in axSpA. We discuss the potential benefits as well as the practical considerations that must be addressed in the movement toward clinical translation of QIBs

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival