Nuclear Imaging
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This project aims at developing advanced methods for robotic image acquisitions, enabling more flexible, patient- and process-specific functional and anatomical imaging with the operating theater. Using robotic manipulations, co-registered and dynamic imaging can be provided to the surgeon, allowing for optimal implementation of preoperative planning. In particular, this projects is the first one developing concepts for intraoperative SPECT-CT, and introduces intraoperative robotic Ultrasound imaging based on CT trajectory planning, enabling registration with angiographic data. With distinguished partners from Bavarian industry, this project has a fundamental contribution in developing safe, reliable, flexible, and multi-modal imaging technologies for the operating room of the future.
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Nuclear medicine imaging modalities assist commonly in surgical guidance given their functional nature. However, when used in the operating room they present limitations. Pre-operative tomographic 3D imaging can only serve as a vague guidance intra-operatively, due to movement, deformation and changes in anatomy since the time of imaging, while standard intra-operative nuclear measurements are limited to 1D or (in some cases) 2D images with no depth information. To resolve this problem we propose the synchronized acquisition of position, orientation and readings of gamma probes intra-operatively to reconstruct a 3D activity volume. In contrast to conventional emission tomography, here, in a first proof-of-concept, the reconstruction succeeds without requiring symmetry in the positions and angles of acquisition, which allows greater flexibility and thus opens doors towards 3D intra-operative nuclear imaging.
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The SFB824 (Sonderforschungsbereich 824: Central project for histopathology, immunohistochemistry and analytical microscopy) represents an interdisciplinary consortium which aims at the development of novel imaging technologies for the selection and monitoring of cancer therapy as an important support for personalized medicine. Z2, the central unit for comparative morphomolecular pathology and computational validation, provides integration, registration and quantification of data obtained from both macroscopic and (sub-)cellular in-vivo as well as ex-vivo imaging modalities with tissue-based morphomolecular readouts as the basis for the development and establishment of personalized medicine. In order to develop novel imaging technologies, co-annotation and validation of image data acquired by preclinical or diagnostic imaging platforms via tissue based quantitative morphomolecular methods is crucial. Light sheet microscopy will continue to close the gap between 3D data acquired by in-vivo imaging and 2D histological slices especially focusing on tumor vascularization. The Multimodal ImagiNg Data Flow StUdy Lab (MINDFUL) is a central system for data management in preclinical studies developed within SFB824. Continuing the close collaboration of pathology, computer sciences and basic as well as translational researchers from SFB824 will allow the Z2 to develop and subsequently provide a broad variety of registration and analysis tools for joint imaging and tissue based image standardization and quantification.
The goal of the BFS Project: ImmunoProfiling using Neuronal Networks (IPN2) is to develop a method based on neuronal networks and recent advances in Deep Learning to allow characterization of a patient's tumor as ″hot″ or ″cold″ tumor depending on the identified ImmunoProfile. Recent research has shown that many tumors are infiltrated by immuno-competent cells, as well as that the amount, type and location of the infiltrated lymph nodes in primary tumors provide valuable prognostic information. In contrast to a ″cold tumor″, a ″hot tumor″ is characterized by an active immune system which the tumor has identified as threat. This identification provides the basis for selecting the therapy best suitable for the individual patient.
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