Multimodal functional and anatomical imaging identifies preclinical microvascular abnormalities in type 1 diabetes mellitus

Structural and functional change in the microcirculation in type 1 diabetes mellitus predicts future end-organ damage and macrovascular events. We explored the utility of novel signal processing techniques to detect and track change in ocular hemodynamics in patients with this disease. 24 patients with uncomplicated type 1 diabetes mellitus, and 18 age-and-sex matched control subjects were studied. Doppler ultrasound was used to interrogate the carotid and ophthalmic arteries and digital photography to image the retinal vasculature. Frequency analysis algorithms were applied to quantify velocity waveform structure and retinal photographic data at baseline and following inhalation of 100% oxygen. Frequency data was compared between groups. No significant differences were found in the resistive index between groups at baseline or following inhaled oxygen. Frequency analysis of the Doppler flow velocity waveforms identified significant differences in bands 3-7 between patients and controls in data captured from the ophthalmic artery (p<0.01 for each band). In response to inhaled oxygen, changes in the frequency band amplitudes were significantly greater in control subjects compared with patients (p<0.05). Only control subjects demonstrated a positive correlation (R=0.61) between change in retinal vessel diameter and frequency band amplitudes derived from ophthalmic artery waveform data. The use of multimodal signal processing techniques applied to Doppler flow velocity waveforms and retinal photographic data identified preclinical change in the ocular microcirculation in patients with uncomplicated diabetes mellitus. An impaired autoregulatory response of the retinal microvasculature may contribute to the future development of retinopathy in such patients.

Prostate cancer radiotherapy: potential applications of metal nanoparticles for imaging and therapy

Prostate cancer (CaP) is the most commonly diagnosed cancer in males. There have been dramatic technical advances in radiotherapy delivery, enabling higher doses of radiotherapy to primary cancer, involved lymph nodes and oligometastases with acceptable normal tissue toxicity. Despite this, many patients relapse following primary radical therapy, and novel treatment approaches are required. Metal nanoparticles are agents that promise to improve diagnostic imaging and image-guided radiotherapy and to selectively enhance radiotherapy effectiveness in CaP. We summarize current radiotherapy treatment approaches for CaP and consider pre-clinical and clinical evidence for metal nanoparticles in this condition.

Prostate cancer (CaP) is the most commonly diagnosed cancer in males and is responsible for more than 10,000 deaths each year in the UK.1 Technical advances in radiotherapy delivery, including image-guided intensity-modulated radiotherapy (IG-IMRT), have enabled the delivery of higher radiation dose to the prostate, which has led to improved biochemical control. Further improvements in cancer imaging during radiotherapy are being developed with the advent of MRI simulators and MRI linear accelerators.2–4

Nanotechnology promises to deliver significant advancements across numerous disciplines.5 The widest scope of applications are from the biomedical field including exogenous gene/drug delivery systems, advanced biosensors, targeted contrast agents for diagnostic applications and as direct therapeutic agents used in combination with existing treatment modalities.6–11 This diversity of application is especially evident within cancer research, with a myriad of experimental anticancer strategies currently under investigation.

This review will focus specifically on the potential of metal-based nanoparticles to augment the efficacy of radiotherapy in CaP, a disease where radiotherapy constitutes a major curative treatment modality.12 Furthermore, we will also address the clinical state of the art for CaP radiotherapy and consider how these treatments could be best combined with nanotherapeutics to improve cancer outcomes.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.