Prostate brachytherapyProstate post-implant dosimetry: Interobserver variability in seed localisation, contouring and fusion
Section snippets
Patients
Three patients treated with 125I seed implants at the University Hospital Gasthuisberg (Leuven) were selected. The pre-implant prostate volumes were 38, 21 and 42 cm3, implanted with 76, 62 and 87 seeds respectively. The dose prescription was 145 Gy to the prostate CTV.
Image acquisition
Post-implant CT, MRI and X-ray images (0° and 60°, for seed count) were acquired 28 days after implantation. CT images of 3 mm were acquired on a 4-slice spiral CT (Somatom, Siemens). MRI scans were performed on a 1.5 T scanner
Interobserver variability in contouring
Fig. 1 shows the results of the prostate delineation on CT and T2. Table 2 gives the calculated volumes. In general, the mean observer volumes corresponded quite well with the reference volumes (except for patient 2 on CT). In almost all cases the CT volumes were larger than the T2 volumes (ratio 1.20 ± 0.12). This finding corresponds with external beam literature [14], [15], [16].
Averaged over the patients, the interobserver variability in contoured prostate volume, expressed as SDref (1 SD with
Interobserver variability in contouring
Several studies have reported a large interobserver variability for CT based post-implant contouring [7], [8], [9]. It is not possible to compare SD data however due to the small number of observers in these studies. For MRI, data on post-implant prostate contouring are scarce and even contradictory. In a single-centre study it was found that the MRI prostate volume exceeded the CT volume on average by 9% [17]. Another study found slightly larger volumes for post-implant contouring on CT than
Conclusion
The dosimetric parameters for prostate post-implant evaluation showed large technique-dependent interobserver variabilities. Contouring and image fusion are the ‘weak links’ in the procedure. This can be approached by establishing widespread training across Europe. Image fusion uncertainties could additionally be tackled with automated fusion software.
Acknowledgements
The authors want to thank the BRAPHYQS and PROBATE members (Bashar Al-Qaisieh, Ann Henry, Christian Kirisits, Peter Niehoff, Alfredo Polo, Alex Rijnders, Carl Salembier, Marco Van Vulpen) and Tom Budiharto, Liesbeth De Wever, Gregor Goldner, Kenneth Poels, Marinus Moerland, Raymond Oyen, for their contribution.
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