All Outputs (4)

Imaging Pain Relief in Osteoarthritis (IPRO): protocol of a double-blind randomised controlled mechanistic study assessing pain relief and prediction of duloxetine treatment outcome (2017)
Journal Article
Reckziegel, D., Bailey, H., Cottam, W. J., Tench, C. R., Mahajan, R. P., Walsh, D. A., …Auer, D. P. (in press). Imaging Pain Relief in Osteoarthritis (IPRO): protocol of a double-blind randomised controlled mechanistic study assessing pain relief and prediction of duloxetine treatment outcome. BMJ Open, 7(6), Article e014013. https://doi.org/10.1136/bmjopen-2016-014013

Introduction: Osteoarthritis (OA) pain is a major cause of long-term disability and chronic pain in the adult population. One in five patients does not receive satisfactory pain relief, which reflects the complexity of chronic pain and the current la... Read More about Imaging Pain Relief in Osteoarthritis (IPRO): protocol of a double-blind randomised controlled mechanistic study assessing pain relief and prediction of duloxetine treatment outcome.

The association between human endogenous retroviruses and multiple sclerosis: a systematic review and meta-analysis (2017)
Journal Article
Morandi, E., Tanasescu, R., Tarlinton, R. E., Constantinescu, C. S., Zhang, W., Tench, C. R., & Gran, B. (2017). The association between human endogenous retroviruses and multiple sclerosis: a systematic review and meta-analysis. PLoS ONE, 12(2), Article e0172415. https://doi.org/10.1371/journal.pone.0172415

Background: The interaction between genetic and environmental factors is crucial to multiple sclerosis (MS) pathogenesis. Human Endogenous Retroviruses (HERVs) are endogenous viral elements of the human genome whose expression is associated with MS.... Read More about The association between human endogenous retroviruses and multiple sclerosis: a systematic review and meta-analysis.

Potential pitfalls when denoising resting state fMRI data using nuisance regression (2016)
Journal Article
Bright, M. G., Tench, C. R., & Murphy, K. (2017). Potential pitfalls when denoising resting state fMRI data using nuisance regression. NeuroImage, 154, 159-168. https://doi.org/10.1016/j.neuroimage.2016.12.027

In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through n... Read More about Potential pitfalls when denoising resting state fMRI data using nuisance regression.

Denoising of optical coherence tomography using second order total generalized variation decomposition (2015)
Journal Article
Duan, J., Lu, W., Tench, C., Gottlob, I., Proudlock, F., Nilesh Samani, N., & Bai, L. (2016). Denoising of optical coherence tomography using second order total generalized variation decomposition. Biomedical Signal Processing and Control, 24, 120-127. doi:10.1016/j.bspc.2015.09.012