“These findings highlight the value of the deep learning-based segmentation algorithm for improvement and automatization of clinical decision-making based on the volumetric evaluation of amino acid PET,” stated Lohmann. “The segmentation tool developed in our study could be an important platform to further promote amino acid PET and to strengthen its clinical value, which may give brain tumor patients access to important diagnostic information that was previously unavailable or difficult to obtain.”

To facilitate clinical implementation, the segmentation algorithm is freely available and can be executed on a conventional GPU-equipped computer in less than two minutes without preprocessing. “We hope to encourage and support treating physicians in neuro-oncology centers to consider amino acid PET for their patients, even if they have little or no prior experience,” said Lohmann. “Every patient with a brain tumor should have access to amino acid PET.”


The authors of “Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET” include Robin Gutsche, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany, and RWTH Aachen University, Aachen, Germany; Carsten Lowis and Philipp Lohmann, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany; Karl Ziemons, Medical Engineering and Technomathematics, FH Aachen University of Applied Sciences, Juelich, Germany; Martin Kocher, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany, and Department of Stereotaxy and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Garry Ceccon, Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Cláudia Régio Brambilla, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany, and JARA-BRAIN-Translational Medicine, Aachen, Germany; Nadim J. Shah, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany, JARA-BRAIN-Translational Medicine, Aachen, Germany, and Department of Neurology, University Hospital RWTH Aachen, Aachen, Germany; Karl-Josef Langen, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany, Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany, and Center for Integrated Oncology, Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany; Norbert Galldiks, Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany, Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, and Center for Integrated Oncology, Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany; and Fabian Isensee, Applied Computer Vision Lab, Helmholtz Imaging, Heidelberg, Germany, and Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany.

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