{'fraction_non_alphanumeric': 0.01757631822386679, 'fraction_numerical': 0.0037002775208140612, 'mean_word_length': 5.032078103207811, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Prostate fiducials and margins

The paper by Greer et al. in the current issue of the Journal compares daily online imaging using implanted fiducials against traditional offline bony landmark positioning. The study material is of interest and the topic timely, as several departments in Australasia are currently starting to use fiducial markers for prostate cancer set-up for radiation therapy. It is clear that daily online imaging based on fiducials is superior to offline imaging with bony anatomy and interest in this process can be expected to grow as daily image guidance, such as using fiducial markers is now standard of care in international prostate cancer radiation therapy trials, for example, the ‘PROFIT’ trial, which will open in Australasia with the Trans-Tasman Radiation Oncology Group in 2008. Van Herk et al. calculated that to ensure a minimum dose to the clinical target volume (CTV) of 95 for 90% of the patients, the margin around the CTV should be the sum of 2.5 times the standard deviation of the overall systematic error and 0.7 times the standard deviation of the overall random error. Online imaging, that is imaging and position adjustment before treatment can correct for both random and systematic movement whereas offline imaging that can only compensate for systematic movements. As the major contributor to margin size, however, systematic error is the component that most needs to be managed. This is because the blurring effect of random errors will result in a small decrease of dose at the edge of the highdose region that will moderately affect all patients. In contrast, a systematic error has the potential to move the clinical target volume outside the high-dose region. Many margin ‘recipes’ have been put forward. Van Herk’s formula is the most commonly used margin recipe. Such recipes are very valuable and are attractive because they sum up a complex modelling process into a neat and understandable formula. However, there are many underlying assumptions in the formula, including assuming that all patients have equal expected treatment error, assuming that patient motion is normally distributed in all three axes and modelling a rounded organ as having a straight boundary. It is important that clinicians are aware that there are other errors in the radiation treatment delivery process, such as the uncertainty in target delineation, often due to partial voluming effects in image data, intraobserver and interobserver variation, and limitations in CT planning compared with MRI. These delineation errors are systematic errors as they will affect all treatment fractions through the treatment course regardless of whether online fiducial-based verification or offline bony verification is used. There is little in the published work about observer errors in daily online image guidance with fiducials; however, there is probably a small error in this process even using kV imaging, and larger errors with the poorer electronic portal imaging MV images. There may also be small errors in the planning systems, as well as linear accelerator tolerances. And, of course, wemust remember that organmovement during treatment is not compensated for by any set-up correction technique. As technological progress gives us easier and more immediate access to accurate patient set-up data, it is natural that we should want to move closer to the goal of individualized margins. It is tempting to apply margin recipes to individuals without realizing that these formulas have been derived for group data. The path towards individualized margins will not be quite that simple. Numbers of patients may not be sufficient in many small institutional studies to accurately determine set-up error, margins and so on. To get the uncertainty in a calculated margin below 1 mm (2 standard deviations) requires a sample size of approximately 50 patients. Greer et al. indicate that their sample size was not based on statistical sample size determination. They showed that treatment with bony set-up results in large systematic errors, at least in comparison with online imaging with implanted fiducials. They should be commended on their careful logical work. However, the risk is that in some departments, clinicians may use margin formulas without taking into account limitations of such