PET-scan premature evaluation after hypofractionated thoracic radiotherapy

2013 
It is currently agreed upon that PET-scan is an efficient tool to assess bronchial cancer expansion and to give predictive SUV values. The aim of this study is to judge the utility and ability of PET-scans for evaluating the premature response of lungs cancers to hypofractionated radiotherapy. Material and methods 10 patients were taken in charge between August and December 2012 (9 with primitive bronchial cancer and 1 with a secondary lung location). All were treated with high-dose hypofractionated radiotherapy, using either tomotherapy or conformational radiotherapy. They all have an histologic proof of diagnostic. Automatic and/or manual repositioning was ensured before each treatment using CBCT imagery. ITVs were determined thanks to MIP reconstructions (Maximum Intensity Projection) made from several tomodensitometric acquisitions. The median dose delivered to patients was 48 Gy in 6 fractions of 8 Gy (ext. 36–48) and the median duration of 10 days (ext. 8–15). Lung lesions had an average size of 21.8 mm and CTV's and PTV's mean volumes were respectively of 16.9 (ext. 5–39) and 50.1 cc (ext. 17–78.5). All patients did PET-scan exams 1 to 2 months before the treatment and did the same exam 2 month after the end of the therapy. Results While before treatments the median SUVmax was of 10.6 (ext. 4–30), a significant drop was observed for all patients during the PET-scan made 2 months after treatments, leading to a median SUVmax of 1.2 (ext. 0.8–4.3). A complete metabolic response was noted for 7 patients and a partial one for 3 others. Conclusion According to PET-scan results, the metabolic response after high-doses hypofractionated radiotherapy seems to be fast. The predictive nature of this response on the local control of the cancer is still to demonstrate, hopefully thanks to future PET-scan exams.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    0
    Citations
    NaN
    KQI
    []