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We have been considering the question of calculating, conveniently but with precision, significant basic image quality indicators for mammography. As a result of this work, a number of questions have been addressed regarding both the philosophy and the practicability of such calculations. One way to make a prediction is to define a phantom, determine a primary photon fluence, obtain the scatter fluence from empirical correlations, define a target of interest and make a straightforward calculation. The other extreme is to define a phantom and target and do a complete Monte-Carlo calculation. The first is too approximate for making close calls between various system configurations. The second, although it can be very useful, tends to gather in one place the weaknesses of both experiments and theory. On one hand the Monte-Carlo calculations are unwieldy like experiments; on the other, like any theory they can only represent the physics that is included. It is always necessary to verify the calculation by experiments. For example, scatter radiation in mammography has a simple energy dependency but its angular distribution is quite complicated due to interference phenomena and also quite important. The first approach mentioned above would certainly miss the complication, as experiments have in the past. The Monte-Carlo calculations also miss the complication because, for practical reasons, their angular resolution is generally too low and in addition the appropriate physics is not included. We will describe our approach to the modelling of mammography. It is a combination of prediction techniques, based on variables chosen to be convenient for describing the physics, and experiments to verify uncertainties in the modelling. We will also discuss the point of greatest vulnerability of either calculations or experiments - the phantom. Our thesis is that all possible phantoms and targets can and should be treated in generalized combinations, which can be used to raise the level of usefulness of either experiments or predictions.
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