What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.

This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.

Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.

mRECIST for HCC: Performance and novel refinements

In 2010, modified RECIST (mRECIST) criteria were proposed as a way of adapting the RECIST criteria to the particularities of hepatocellular carcinoma (HCC). We intended to overcome some limitations of RECIST in measuring tumour shrinkage with local and systemic therapies, and also to refine the assessment of progression that could be misinterpreted with conventional RECIST 1.1, due to clinical events related to the natural progression of chronic liver disease (development of ascites, enlargement of lymph nodes, etc.). mRECIST has served its purpose since being adopted or included in clinical practice guidelines (European, American and Asian) for the management of HCC; it has also been instrumental for assessing response and time-to-event endpoints in several phase II and III investigations. Nowadays, mRECIST has become the standard tool for measurement of radiological endpoints at early/intermediate stages of HCC. At advanced stages, guidelines recommend both methods. mRECIST has been proven to capture higher objective response rates in tumours treated with molecular therapies and those responses have shown to be independently associated with better survival. With the advent of novel treatment approaches (i.e. immunotherapy) and combination therapies there is a need to further refine and clarify some concepts around the performance of mRECIST. Similarly, changes in the landscape of standard of care at advanced stages of the disease are pointing towards progression-free survival as a potential primary endpoint in some phase III investigations, as effective therapies applied beyond progression might mask overall survival results. Strict recommendations for adopting this endpoint have been reported. Overall, we review the performance of mRECIST during the last decade, incorporating novel clarifications and refinements in light of emerging challenges in the study and management of HCC.