BJRD14065 1..15

Tumour heterogeneity has, in recent times, come to play a vital role in how we understand and treat cancers; however, the clinical translation of this has lagged behind advances in research. Although significant advancements in oncological management have been made, personalized care remains an elusive goal. Interand intratumour heterogeneity, particularly in the clinical setting, has been difficult to quantify and therefore to treat. The histological quantification of heterogeneity of tumours can be a logistical and clinical challenge. The ability to examine not just the whole tumour but also all the molecular variations of metastatic disease in a patient is obviously difficult with current histological techniques. Advances in imaging techniques and novel applications, alongside our understanding of tumour heterogeneity, have opened up a plethora of non-invasive biomarker potential to examine tumours, their heterogeneity and the clinical translation. This review will focus on how various imaging methods that allow for quantification of metastatic tumour heterogeneity, along with the potential of developing imaging, integrated with other in vitro diagnostic approaches such as genomics and exosome analyses, have the potential role as a non-invasive biomarker for guiding the treatment algorithm. Although continual improvements in diagnosis, surgical techniques and radiation oncology have together provided improved survival for many forms of human cancers, a majority of deaths from cancer are caused by the development and continuous growth of metastases that are resistant to conventional therapies. Similarly, although the use of systemic non-targeted and targeted adjuvant therapies has helped to prevent the spread of tumour cells from the primary site and is now a standard practice for many tumour types, the emergence of resistant disease continues to be a significant cause of patient mortality. These features provide an insight into the dynamic nature of the signalling network within the tumour cells, and human cancers are now being increasingly recognized as heterogeneous, characterized by distinct pathological, genomic, clinical and therapeutic features. Nearly 150 years after the original theory of tumours originating from immature cells by Virchow, innovative technological approaches unequivocally demonstrate the cellular heterogeneity of tumours, composed of distinct subpopulations of cancer cells within (“intra”) and between (“inter”) tumours of individual patients. These subpopulations are characterized by specific genetic and morphological profiles, representing the clonal selection and evolution of that tumour. This heterogeneity provides a powerful internal mechanism through which tumour cells can ultimately escape environmental stresses, including oncological therapies, posing a considerable challenge for translational researchers. There is considerable evidence that the tumour microenvironment actively contributes to tumour heterogeneity. Arguably the best example of this is the “pre-metastatic niche”, defined as the creation of an ideal thriving environment for the primary tumour to “seed” to. Through the secretion of cytokines, chemokines and growth factors, the primary tumour “primes” a distal site to become an ideal niche/target organ, favourable for future metastatic colonization. Although in some cases the target organ is already primed for metastatic spread and many organs may have “seeding” of cells, only a few will take “root”. Increasing understanding of tumour heterogeneity demands an effort from researchers to establish and understand pre-metastatic changes within distant organs and their major drivers. This new paradigm of cancer heterogeneity has yet to be fully assimilated into everyday patient management. It has been well documented with certain cancers that imaging signals can show phenotypic tumour heterogeneity and have clinical implications; for example, in radio-iodine imaging of metastatic thyroid cancer, somemetastatic lesionsmay not take up radio-iodine and therefore will be unaffected by radio-iodine therapy. However, for the majority of tumours, biopsies remain the standard of care for assessing tumour biology but cannot be expected to represent the entirety of a tumour in this tumour heterogenic era. Many physicians advocate the re-biopsy of metastatic disease at re-presentation for histological analysis and comparison with the primary, in an attempt to improve the choice of therapy upon relapse, having taken into account, for instance, intertumoral heterogeneity between the primary and metastatic disease. Repeated biopsy of tumour tissue is invasive, may be practically difficult, has resource implications and is clearly confounded by intratumoral heterogeneity. These shortcomings give huge potential to the recent advances in molecular imaging, which have the ability to visualize and quantify heterogeneity of tumour receptor expression, metabolism, apoptosis, blood flow or structure, non-invasively over time, i.e. at baseline and to assess response to treatment. Owing to space constraints, we can only select a subset of imaging techniques for illustration purposes; a more comprehensive précis of the different image modalities has been reviewed elsewhere. VARIOUS IMAGING MODALITIES AND METHODS THAT CAN HELP TO MAP THE HETEROGENEITY IN TUMOUR METASTASIS The development of metastasis is multifactorial and is dependent on the complex interaction between host factors and the tumour biology. This process is highly selective, and the metastatic lesion represents the end point of many sequential events that only a few cells can survive. Recent advances in next generation sequencing (NGS) have increased the understanding of (1) the clonal heterogeneity between primary and metastatic tumours and (2) the degree of genetic heterogeneity of metastatic tumours. For example, a study comparing sequences of primary tumours and metastases in lobular breast cancers revealed multiple mutations present only in metastases and several other mutations with increased frequency in metastatic sites. Similarly, a number of studies report on the discordance in oestrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 (HER2) expression between different metastatic sites. As pointed out, histological analyses with repeated invasive biopsies have limitations. For instance, when different metastatic deposits are heterogeneous with respect to receptor expression and/or cellularity and are not all subjected to biopsy, then a clinical decision based on in vitro analysis of the biopsied material may be prone to undersampling error. However, recent advances in imaging techniques, image acquisition and image analysis have been used to measure quantitative imaging biomarkers that may be able to address the complexities of tumour heterogeneity better than a standard histological biopsy. Here, we critically appraise these strategies specifically in the context of heterogeneous metastatic disease. F-fludeoxyglucose–positron emission tomography/CT Although CT is the imaging modality most widely used for tumour assessment, it provides very little in the way of distinct tumour activity information. The addition of positron emission tomography (PET) to CT can add such further information, and F-fludeoxyglucose (F-FDG) is the most commonly used PET radiotracer, although there are many other radiotracers that examine different aspects of tumour biology. The ability of F-FDG-PET to detect cancer is based on elevated aerobic glycolysis in the malignant tissue in comparison with the normal tissue—also known as the Warburg effect. Although primarily reporting on tumour cell activity, F-FDG-PET has been shown to also inform on tumour heterogeneity. A retrospective study using F-FDG-PET/CT to monitor response among lesions in patients with bone-dominant metastatic breast cancer treated with systemic therapies reported that lesions showed heterogeneous metabolic response amongst responding and nonresponding bony and non-bony lesions. Novel utilization of F-FDG-PET/CT in recent years, such as texture analysis on CT imaging, has been shown to reflect tumour heterogeneity and associated prognosis. This has been examined in multiple tumour types, including lung, colorectal and oesophageal cancers. There are a number of ways to extract texture elements in images. One such CT textural analysis methodology utilizes a two-step filtration–histogram technique. The first stage uses a Laplacian of gaussian spatial band-pass filter to selectively extract and enhance features of different sizes corresponding to fine, medium and coarse texture scales, allowing detection of spatial differences within a tissue (arising from the different band of spatial frequencies employed). The Laplacian detects intensity changes (or edges) within an image, which have been first smoothened by the gaussian distribution, based on the spatial scale filter (SSF) value. A lower SSF value (e.g. 2mm) extracts and enhances features of a “finer” texture scale, whereas an BJR R Chowdhury et al 2 of 15 birpublications.org/bjr Br J Radiol;87:20140065 SSF value of 3, 4 or 5mm extracts and enhances features of a “medium” texture scale and a higher SSF value (e.g. 6mm) extracts and enhances features of a “coarser” texture scale, as shown in Figures 1 and 2. These novel texture analyses have also been applied to other imaging modalities, e.g. MRI, and will be discussed later (section on Simultaneous positron emission tomography/MR and textural analysis). Generation of these texture parameters provides vital information on the image features themselves (reviewed in Miles et al). Standard deviation (SD) increases approximately in proportion to the square root of the number of features highlighted and their mean intensity difference comparedwith background (i.e. dark and bright features are both positive). Skewness is related to the average brightne