Claire-Anne Reidel, Enrico Pierobon, Felix Horst, Lévana Gesson, Athena Paz, Christian Graeff, Timo Steinsberger, Klemens Zink, Matthias Witt, Yannick Senger, Christian Finck, Marie Vanstalle, Chiara La Tessa, Marco Durante, Uli Weber, Christoph Schuy
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引用次数: 0
Abstract
Tumor motion is a major challenge for scanned ion-beam therapy. In the case of lung tumors, strong under- and overdosage can be induced due to the high density gradients between the tumor- and bone tissues compared to lung tissues. This work proposes a non-invasive concept for 4D monitoring of high density gradients in carbon ion beam therapy, by detecting charged fragments. The method implements CMOS particle trackers that are used to reconstruct the fragment vertices, which define the emission points of nuclear interactions between the primary carbon ions and the patient tissues. A 3D treatment plan was optimized to deliver 2 Gy to a static spherical target volume. The goodness of the method was assessed by comparing reconstructed vertices measured in two static cases to the ones in a non-compensated moving case with an amplitude of 20 mm. The measurements, performed at the Marburg Ion-Beam Therapy Center (MIT), showed promising results to assess the conformity of the delivered dose. In particular to measure overshoots induced by high density gradients due to motion with 83.0 ± 1.5% and 92.0 ± 1.5% reliability based on the ground truth provided by the time-resolved motor position and depending on the considered volume and the iso-energy layers.
期刊介绍:
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.