Wednesday 12 September Advanced imaging science to practice 14:30 14:55. Recent advances in computed tomography (CT) technology

Transcription

1 14:30 14:55 Recent advances in computed tomography (CT) technology Dr Gareth Iball, Leeds Teaching Hospitals NHS Trust All modern CT systems incorporate iterative reconstruction (IR) techniques. Their basic functionality and uses will be presented along with the differences between manufacturers systems and potential pitfalls which need to be avoided. Although dual-energy CT scanners have been available for over a decade, new techniques for dual and multi-energy (spectral) scanning are still being developed and as a result new clinical applications are now available. The functionality and pros and cons of these systems will be presented. A further look at emerging and in-development technologies will cover ultra-high resolution scanning, cinematic rendering and photon counting technologies. McCollough CH, Leng S, Yu L, Flethcer JG. Dual- and multi-energy CT: principles, technical approaches and clinical applications. Radiology 2015; 276(3): Geyer LL, Schoepf UJ, Meinel FG, Nance Jr JW, Bastarrika G, Leipsi JA et al. State of the Art: Iterative CT Reconstruction Techniques. Radiology 2015; 276(2): Eid M, De Cecco CN, Nance Jr. JW et al. Cinematic rendering in CT: a novel, lifelike 3D visualization technique. AJR 2017; 209:

2 14:55 15:20 Incorporating advanced computed tomography (CT) applications into routine clinical practice Dr Damian Tolan, Leeds Teaching Hospitals NHS Trust New CT applications are moving beyond standard high-resolution morphological assessment of CT datasets to a more interactive assessment of organs and abnormalities. This is particularly true for multi-energy CT and radiologists need to be familiar with the techniques, the clinical applications and image post-processing to maximise the diagnostic benefits of this technology. There are also challenges in creating protocols and harmonising image quality across different CT scanners and manufacturers. This is particularly true for comparison of quantitative analysis related to multi-energy CT assessments on different machines. Determining the added value and cost of these assessments remains challenging. However there is growing evidence of the benefits of multi-energy CT imaging for a range of tumour types, body areas and conditions and it seems probable that this will become a mainstream technology in the coming years. Several authors have described potential benefits from cutting down unnecessary additional examinations for common clinical problems such as characterising abnormalities such as adrenal nodules and renal cystic lesions. Integration of multi-energy CT into routine reporting workflow will be critical to allow interpretation as part of routine work and maximise uptake of this technology. While routine post-processing can assist, radiologists are likely to need their own advanced postprocessing skills in image manipulation for problem solving challenging cases. Radiology departments will also need to define which patients are likely to benefit from multienergy CT procotols, as access is likely to be limited for the foreseeable future due to the constraints of scanner replacement programmes and limited access. McCollough CH, Leng S, Yu L, Fletcher JG. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology 2015; 276(3): Mileto A, Barina A, Marin D et al. Virtual monochromatic images from dual-energy multidetector CT: variance in CT numbers from the same lesion between single-source projection-based and dual-source image-based implementations. Radiology 2016; 279(1): Böning G, Feldhaus F, Adelt S et al. Clinical routine use of virtual monochromatic datasets based on spectral CT in patients with hypervascularized abdominal tumors evaluation of

3 effectiveness and efficiency. Acta Radiol 2018; doi: / [Epub ahead of print]

4 16:30 16:55 Textural analysis of computed tomography (CT) and magnetic resnonance (MR) data ready for routine clinical use? Dr Balaji Ganeshan, University College London Hospitals NHS Foundation Trust How does texture analysis of routinely acquired diagnostic images (for example, CT, MRI) quantify tissue/tumour heterogeneity which is key component of malignancy What does texture analysis actually measure/mean? What are various steps undertaken in qualifying texture analysis as an imaging biomarker? o Biological correlate o Clinical applications lesion classification/prognosis/treatment response, prediction o Technical validation o Clinical utility and cost-effectiveness What are barriers in the clinical adoption/implementation of texture analysis in routine practice? How easy is it to undertake texture analysis and statistical analysis which can be an integral part of data-mining and machine learning/artificial intelligence? Ganeshan B et al. Quantifying tumour heterogeneity with CT. Cancer Imaging 2013; 13: Miles KA et al. CT texture analysis using the filtration-histogram method: what do the Ganeshan B et al. Non-small cell lung cancer: histopathologic correlates for texture parameters at CT. Radiology 2013; 266(1): Weiss GJ et al. Noninvasive image texture analysis differentiates K-ras mutation from panwildtype NSCLC and is prognostic. PloS one 2014; 9(7): e Win T et al. Tumor heterogeneity and permeability as measured on the CT component of PET/CT predict survival in patients with non-small cell lung cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2013; 19(13): Ganeshan B et al. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. European Radiology 2012; 22(4): Miles KA. How to use CT texture analysis for prognostication of non-small cell lung cancer. Cancer Imaging BioMed Central 2016: 16(1): 10.

5 Craigie M, Squires J, Miles K. Can CT measures of tumour heterogeneity stratify risk for nodal metastasis in patients with non-small cell lung cancer? Clinical Radiology 2017; 72(10): 899. Miles KA et al. (2012). Selection of patients for advanced non-small cell lung cancer for chemotherapy: potential cost-effectiveness of CT texture analysis. European Society of Radiology 2012; doi: /ecr2012/C Miles KA, Squires J and Murphy M. Radiologist engagement as a potential barrier to the clinical translation of quantitative imaging for the assessment of tumor heterogeneity. Academic Radiology 2018: doi: /J.ACRA