Multimodal Imaging Techniques for the Extraction of Detailed Geometrical and Physiological Information for Use in Multi‐Scale Models of Colorectal Cancer and Treatment of Individual Patients

Abstract

A vast array of mathematical models have been proposed for all stages of cancer formation across a wide range of spatio -temporal scales. Attention is now turning to coupling these models across scales and building models of "virtual tumours" for use in in silico testing of novel drugs and treatment regimes. This leads naturally to the requirement for detailed knowledge of the underlying geometry and physiological properties of individual tumours for use in: (i) multi-scale mathematical models of in vivo tumour growth and development; (ii) fusion of multi-scale, multimodal medical imaging techniques to improve the diagnosis and treatment of individual patients; and (iii) training of cancer specialists and surgeons.

Towards a multiscale model of colorectal cancer

“…Hence, modern imaging techniques make it possible to detect and stage the primary tumour and to identify the presence of early metastases, thereby facilitating patient management decisions [52] . Furthermore, a number of mathematical models have been developed to investigate tumour invasion [53,54] and metastasis [55,56] .…”

“…Such models could, in principle, be adapted to evaluate the aggressiveness of colorectal neoplasms. Finally, we anticipate that in silico studies will be exploited to predict a patient's prognosis following cancer therapy and/or surgery [23,52,57] . In summary, we believe that mathematical modeling has an important role to play in advancing our understanding of CRC.…”

GIMI: the past, the present and the future

“…(The high-level architecture of Power et al (2005), whereby external services (E) mediate access according to local policies (P 1 and P 2 ) is illustrated in figure 1.) While early versions of what was to become SIF underpinned the MRC-funded NeuroGrid project (Geddes et al 2005) and a prototype demonstrator for the National Cancer Research Institute Informatics Initiative (Pitt-Francis et al 2006), it is through GIMI that the fundamental ideas described of Power et al (2005) have been realized.…”

A Proposed Decision-Support System for (Renal) Cancer Imaging

“…Three-dimensional visualisation techniques have proved useful here to show how scan layers can be built up into a three-dimensional model [9]. Finally, graphics hardware and three-dimensional algorithms have proved invaluable in allowing the resultant three-dimensional datasets to be moved, sliced, and/or the outermost layers made translucent [15,14,18,19].…”