Imaging biomarker roadmap for cancer studies.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution

Computational modeling guides tissue-engineered heart valve design for long-term in vivo performance in a translational sheep model

\u3cp\u3eValvular heart disease is a major cause of morbidity and mortality worldwide. Current heart valve prostheses have considerable clinical limitations due to their artificial, nonliving nature without regenerative capacity. To overcome these limitations, heart valve tissue engineering (TE) aiming to develop living, native-like heart valves with self-repair, remodeling, and regeneration capacity has been suggested as next-generation technology. A major roadblock to clinically relevant, safe, and robust TE solutions has been the high complexity and variability inherent to bioengineering approaches that rely on cell-driven tissue remodeling. For heart valve TE, this has limited long-term performance in vivo because of uncontrolled tissue remodeling phenomena, such as valve leaflet shortening, which often translates into valve failure regardless of the bioengineering methodology used to develop the implant. We tested the hypothesis that integration of a computationally inspired heart valve design into our TE methodologies could guide tissue remodeling toward long-term functionality in tissue-engineered heart valves (TEHVs). In a clinically and regulatory relevant sheep model, TEHVs implanted as pulmonary valve replacements using minimally invasive techniques were monitored for 1 year via multimodal in vivo imaging and comprehensive tissue remodeling assessments. TEHVs exhibited good preserved long-term in vivo performance and remodeling comparable to native heart valves, as predicted by and consistent with computational modeling. TEHV failure could be predicted for nonphysiological pressure loading. Beyond previous studies, this work suggests the relevance of an integrated in silico, in vitro, and in vivo bioengineering approach as a basis for the safe and efficient clinical translation of TEHVs.\u3c/p\u3