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Intraoperative computed tomography imaging for dose calculation in intraoperative electron radiation therapy: Initial clinical observations


Autoři: Verónica García-Vázquez aff001;  Felipe A. Calvo aff001;  María J. Ledesma-Carbayo aff005;  Claudio V. Sole aff001;  José Calvo-Haro aff001;  Manuel Desco aff001;  Javier Pascau aff001
Působiště autorů: Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Comunidad de Madrid, Spain aff001;  Departamento de Oncología, Hospital General Universitario Gregorio Marañón, Madrid, Comunidad de Madrid, Spain aff002;  Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid, Spain aff003;  Clínica Universidad de Navarra, Madrid, Comunidad de Madrid, Spain aff004;  Biomedical Image Technologies Laboratory (BIT), Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Comunidad de Madrid, Spain aff005;  CIBER-BBN, Madrid, Comunidad de Madrid, Spain aff006;  Department of Radiation Oncology, Instituto de Radiomedicina, Santiago, Región Metropolitana de Santiago, Chile aff007;  Servicio de Cirugía Ortopédica y Traumatología, Hospital General Universitario Gregorio Marañón, Madrid, Comunidad de Madrid, Spain aff008;  Departamento de Cirugía, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid, Spain aff009;  Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Comunidad de Madrid, Spain aff010;  Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Comunidad de Madrid, Spain aff011;  Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Comunidad de Madrid, Spain aff012
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0227155

Souhrn

In intraoperative electron radiation therapy (IOERT) the energy of the electron beam is selected under the conventional assumption of water-equivalent tissues at the applicator end. However, the treatment field can deviate from the theoretic flat irradiation surface, thus altering dose profiles. This patient-based study explored the feasibility of acquiring intraoperative computed tomography (CT) studies for calculating three-dimensional dose distributions with two factors not included in the conventional assumption, namely the air gap from the applicator end to the irradiation surface and tissue heterogeneity. In addition, dose distributions under the conventional assumption and from preoperative CT studies (both also updated with intraoperative data) were calculated to explore whether there are other alternatives to intraoperative CT studies that can provide similar dose distributions. The IOERT protocol was modified to incorporate the acquisition of intraoperative CT studies before radiation delivery in six patients. Three studies were not valid to calculate dose distributions due to the presence of metal artefacts. For the remaining three cases, the average gamma pass rates between the doses calculated from intraoperative CT studies and those obtained assuming water-equivalent tissues or from preoperative CT studies were 73.4% and 74.0% respectively. The agreement increased when the air gap was included in the conventional assumption (98.1%) or in the preoperative CT images (98.4%). Therefore, this factor was the one mostly influencing the dose distributions of this study. Our experience has shown that intraoperative CT studies are not recommended when the procedure includes the use of shielding discs or surgical retractors unless metal artefacts are removed. IOERT dose distributions calculated under the conventional assumption or from preoperative CT studies may be inaccurate unless the air gap (which depends on the surface irregularities of the irradiated volume and on the applicator pose) is included in the calculations.

Klíčová slova:

Cancer treatment – Surgical and invasive medical procedures – Computed axial tomography – Radiation therapy – Surgical oncology – Image processing – Breast cancer – Tissue distribution


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