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Purpose: To investigate the relationship between extramural venous invasion (EMVI) detected at T2-weighted MRI and nodal disease rectal cancer compared with histopathology. Materials and Methods:The MR imaging of 79 consecutive patients with rectal cancer who underwent primary rectal surgery without neoadjuvant treatment were reviewed. MR images were scored by an expert radiologist for the presence and degree of EMVI using a fi ve point scale blinded to pathological fi ndings. Receiver operating characteristic curve analyses were performed to determine the sensitivity and specifi city of MRI scoring in predicting EMVI and nodal disease at histopathology. Results:Compared with histology, an MR score of Ͼ2 was found to have 100% sensitivity (95% CI: 77%-100%) and 89% specifi city (95% CI: 79%-96%) in identifying EMVI involving veins Ͼ3 mm in diameter. An EMVI score of Ͼ2 was had a sensitivity of 56% (95% CI: 30%-80%) and specifi city of 81% (95% CI: 69%-90%) for identifying patients with stage N2 disease.Conclusions: EMVI score of Ͼ2 on T2-weighted MR imaging has a high sensitivity and specifi city for histopathologically proven extramural venous invasion involving venules Ն3 mm in diameter. However, EMVI scores have only moderate sensitivity in the predicting nodal involvement.

DCE MR imaging may be used to monitor the effects of peptide receptor radiolabeled targeted therapy in patients with neuroendocrine tumors liver metastases; a lower pretreatment distribution volume and high arterial flow fraction was associated with a better response to treatment.

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SummaryThe National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for accelerated translation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools and ongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification using multicentre clinical studies.

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Purpose: XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies of the type that are essential to validate quantitative imaging biomarkers. XNAT provides import, archiving, processing and secure distribution facilities for image and related study data. Until recently, however, modern data visualisation and annotation tools were lacking on the XNAT platform. We describe the background to, and implementation of, an integration of the Open Health Imaging Foundation (OHIF) Viewer into the XNAT environment. We explain the challenges overcome and discuss future prospects for quantitative imaging studies. Materials and methods: The OHIF Viewer adopts an approach based on the DICOM web protocol. To allow operation in an XNAT environment, a data-routing methodology was developed to overcome the mismatch between the DICOM and XNAT information models and a custom viewer panel created to allow navigation within the viewer between different XNAT projects, subjects and imaging sessions. Modifications to the development environment were made to allow developers to test new code more easily against a live XNAT instance. Major new developments focused on the creation and storage of regions-of-interest (ROIs) and included: ROI creation and editing tools for both contour- and mask-based regions; a “smart CT” paintbrush tool; the integration of NVIDIA’s Artificial Intelligence Assisted Annotation (AIAA); the ability to view surface meshes, fractional segmentation maps and image overlays; and a rapid image reader tool aimed at radiologists. We have incorporated the OHIF microscopy extension and, in parallel, introduced support for microscopy session types within XNAT for the first time. Results: Integration of the OHIF Viewer within XNAT has been highly successful and numerous additional and enhanced tools have been created in a programme started in 2017 that is still ongoing. The software has been downloaded more than 3700 times during the course of the development work reported here, demonstrating the impact of the work. Conclusions: The OHIF open-source, zero-footprint web viewer has been incorporated into the XNAT platform and is now used at many institutions worldwide. Further innovations are envisaged in the near future.