Publications by authors named "A Pella"

Article Synopsis
  • Image-guided treatment adaptation using CycleGAN for synthetic CT generation is a significant advancement in particle therapy for young cancer patients.
  • The study involved processing CBCT scans from 15 pelvic patients to create synthetic CT images, which were evaluated against verification CT scans for quality.
  • Results showed that despite some limitations, the CycleGAN method produced satisfactory synthetic CT images that could improve treatment efficacy in pediatric oncology.
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Background: Currently, 13 Asian and European facilities deliver carbon ion radiotherapy (CIRT) for preclinical and clinical activity, and, to date, 55 clinical studies including CIRT for adult and paediatric solid neoplasms have been registered. The National Center for Oncological Hadrontherapy (CNAO) is the only Italian facility able to accelerate both protons and carbon ions for oncological treatment and research.

Methods: To summarise and critically evaluate state-of-the-art knowledge on the application of carbon ion radiotherapy in oncological settings, the authors conducted a literature search till December 2022 in the following electronic databases: PubMed, Web of Science, MEDLINE, Google Scholar, and Cochrane.

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This paper describes the design, installation, and commissioning of an in-room imaging device developed at the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy). The system is an upgraded version of the one previously installed in 2014, and its design accounted for the experience gained in a decade of clinical practice of patient setup verification and correction through robotic-supported, off-isocenter in-room image guidance. The system's basic feature consists of image-based setup correction through 2D/3D and 3D/3D registration through a dedicated HW/SW platform.

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. Respiration negatively affects the outcome of a radiation therapy treatment, with potentially severe effects especially in particle therapy (PT). If compensation strategies are not applied, accuracy cannot be achieved.

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The generation of synthetic CT for carbon ion radiotherapy (CIRT) applications is challenging, since high accuracy is required in treatment planning and delivery, especially in an anatomical site as complex as the abdomen. Thirty-nine abdominal MRI-CT volume pairs were collected and a three-channel cGAN (accounting for air, bones, soft tissues) was used to generate sCTs. The network was tested on five held-out MRI volumes for two scenarios: (i) a CT-based segmentation of the MRI channels, to assess the quality of sCTs and (ii) an MRI manual segmentation, to simulate an MRI-only treatment scenario.

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