Computed tomographic simulation in palliative radiotherapy: the Princess Margaret Hospital experience

Clin Oncol (R Coll Radiol). 2004 Sep;16(6):425-8. doi: 10.1016/j.clon.2004.01.014.

Abstract

Aim: To examine the pattern of palliative radiation planning and the use of computed tomographic simulation (CTSIM) for this purpose.

Materials and methods: We reviewed our department's external radiotherapy database for all courses of treatment with a palliative intent during the period of April to June 2002. Patient characteristics and treatment details were compared based on whether CTSIM had been used or not.

Results: During the above period, 593 courses of external radiation treatment were delivered with palliative intent in our department. Of these, 100 treatments (17%) were planned with the help of CTSIM. The mean age of patients with CTSIM (62.9 years) was not significantly different with the patients planned without CTSIM (63.6 years). CTSIM use varied by treatment location, being highest in mediastinum/oesophagus (48%) and pancreas/stomach (47%) treatments, and lowest in spine (6%), lung (3%) and long bones (4%) (P < 0.01). Only 3% of palliative treatments without CTSIM were prescribed using multiple/complex fields (all field arrangements more complex than a single field or two opposed parallel fields). Although significantly higher (P < 0.001), this proportion was also only 24% in the cases planned with CTSIM. Only 12% of treatments without CTSIM were prescribed with more than 5 fractions, whereas 32% of CT-simulated treatments included more than 5 fractions (P < 0.001).

Conclusion: CTSIM was used much less frequently in our department's palliative radiotherapy compared with its use in radical treatments. The relatively low rate of multiple/complex fields planned in CT-simulated cases suggested that CTSIM was mostly used to improve tumour localisation. The optimal role of CTSIM in palliative radiotherapy will most probably evolve, based on an enhanced understanding of the implications from improved localisation and optimal planning techniques on clinical outcomes, patient convenience and resource accessibility.

MeSH terms

  • Aged
  • Brain / diagnostic imaging
  • Breast Neoplasms / radiotherapy
  • Humans
  • Lung Neoplasms / radiotherapy
  • Middle Aged
  • Palliative Care / methods*
  • Pelvis / diagnostic imaging
  • Radiotherapy Dosage
  • Radiotherapy, Adjuvant / instrumentation*
  • Radiotherapy, Adjuvant / statistics & numerical data
  • Radiotherapy, Computer-Assisted / methods*
  • Radiotherapy, Computer-Assisted / statistics & numerical data
  • Spine / diagnostic imaging
  • Tomography, X-Ray Computed