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 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 progress 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 tumor 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

Vergleich der verschiedenen Entsorgungsalternativen und Beurteilung ihrer Realisierbarkeit

SIGLEDEGerman

Micro-CT imaging of tumor angiogenesis: Quantitative measures describing micromorphology and vascularization

Angiogenesis is a hallmark of cancer, and its noninvasive visualization and quantification are key factors for facilitating translational anticancer research. Using four tumor models characterized by different degrees of aggressiveness and angiogenesis, we show that the combination of functional in vivo and anatomical ex vivo X-ray micro-computed tomography (μCT) allows highly accurate quantification of relative blood volume (rBV) and highly detailed three-dimensional analysis of the vascular network in tumors. Depending on the tumor model, rBV values determined using in vivo μCT ranged from 2.6% to 6.0%, and corresponds well with the values assessed using IHC. Using ultra–high-resolution ex vivo μCT, blood vessels as small as 3.4 μm and vessel branches up to the seventh order could be visualized, enabling a highly detailed and quantitative analysis of the three-dimensional micromorphology of tumor vessels. Microvascular parameters such as vessel size and vessel branching correlated very well with tumor aggressiveness and angiogenesis. In rapidly growing and highly angiogenic A431 tumors, the majority of vessels were small and branched only once or twice, whereas in slowly growing A549 tumors, the vessels were much larger and branched four to seven times. Thus, we consider that combining highly accurate functional with highly detailed anatomical μCT is a useful tool for facilitating high-throughput, quantitative, and translational (anti-) angiogenesis and antiangiogenesis research

Proceedings of the 2005 International Conference on Grid Computing and Applications, GCA'05: Foreword

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