Improving treatment planning

Different aspects of treatment planning are under study, the aim being to improve its accuracy [McGowan et al.,2013]. The LET, for example, needs to be considered in order to take full advantage of the properties of protons and heavier ions. The definition of the PTV by simply adding margins to the CTV is being questioned by the optimization robustness to the range uncertainty of treatment plans. In order to address the problem of range uncertainty, different possibilities of imaging, image treatment and conversion to RSP are being studied: improving the accuracy of CT images, improving the conversion,

(a) (b)

Figure 1.10: (a)Lateral scaling factors and (b) angular scaling factors as a function of the CT Hounsfield units, for the tissues tabulated by White et al (1987), Woodard and White (1986) and the mixtures lung-air and lung-blood. Figure from [Szymanowski and Oelfke,2003].

developing models for biological treatment planning or using charged particles to obtain the RSP image directly.

1.2.4.1 Taking full advantage of the LET

As the LET of the particles impacts greatly the biological effects of the treatment, it was proposed to use high-LET radiation as a boost in a precise region of the irradiation, and to optimize not only the dose distribution but the LET distribution in the volume to irradiate, in order to take full advantage of the properties of the particles used [Bassler et al., 2010]. The local increase in the LET at the end of the range of the protons, for example, can be considered during treatment planning. The fact that plans with identical dose conformation can lead to different repartitions of the LET is particularly important with active scanning [Grassberger and Paganetti,2011]. Thus, there is a need to consider a LET-dependent RBE [Tilly et al., 2005]. Recently, a LET-guided plan optimization (with both dose and LET objectives) was proposed, in order to maximize the dose average LET in the tumour and minimize it in normal tissues [Giantsoudi et al., 2013].

1.2.4.2 PTV definition and treatment plan optimization

As mentioned previously, the planning target volume is usually defined - for photon therapy as well as particle beam therapy - as the clinical target volume to which margins are added to take into account the uncertainties of treatment delivery. However, this definition used for conventional radiotherapy is not quite appropriate for particle beam therapy. It has been shown that, should the range uncertainty not be taken into account, the margins between PTV and CTV can be reduced from photon to proton therapy [Thomas, 2006]. However, when considering the range uncertainty, margins is not the answer to improve treatment plan robustness for highly modulated IMPT (though it

1.2. TREATMENT PLANNING AND UNCERTAINTIES IN PARTICLE BEAM THERAPY

was found satisfying for other deliveries of protons such as single-field uniform dose and low modulation of IMPT) [Albertini et al., 2011]. This is because the degradation of dose uniformity inside the target has some importance in IMPT. Heuristic approaches such as choosing beam angles with the less inhomogeneities in the beam path, or placing no organ at risk just behind the distal edge of the peak have been applied. It was also proposed to define a beam-specific PTV [Park et al.,2012], taking into account the range uncertainty and setup errors independently for each beam angle.

Rather than the re-definition of a more appropriate planning target volume, some efforts are also put towards the inclusion of the uncertainties directly into the planning system in order to determine the most robust solution [McGowan et al.,2013]. Different methods have been proposed, such as a probabilistic approach [Unkelbach et al.,2007], a robust formulation [Unkelbach et al., 2007] or a worst-case optimization [Pflugfelder et al.,2008]. More recently, the inclusion of robustness to range uncertainty in a multi-criteria objective framework was implemented [Chen et al., 2012]. These approaches have been tested, and showed less sensitivity to range and setup errors that traditional margins, assuring a better coverage of the clinical target volume.

1.2.4.3 Improving CT images

The improvement of the CT image quality, mainly the reduction of beam hardening and metal artefacts, leads to a more accurate range prediction. Different methods for image artefact correction have been proposed.

Beam hardening correction

Three kinds of methods for beam-hardening correction exist. The first is filtering: the beam is hardened so that the measured spectrum tends towards a monochromatic one [Paiva et al., 1998; Krimmel et al., 2005]. The second way to proceed is linearisation [Herman,1979;Hammersberg and M˚ang˚ard,1998;Kachelrieß et al.,2006]: the acquired projections are corrected to mimic monochromatic data. The third kind of method is post-reconstruction [Nalcioglu and Lou, 1979; Olson et al., 1981], for which a first reconstructed image of the object is used in order to estimate the distribution of the different materials, and their effect on the energy spectrum.

Metal artefacts correction

Metal artefact reduction techniques are either based on the completion of missing data using synthetic data, or on the modification of the reconstruction algorithm to ignore the missing data [Man et al.,2000;Abdoli et al.,2012]. Another possibility is the registration of kilo-voltage (kV) and mega-voltage (MV) CT images [Newhauser et al.,2008]. It has been shown that correcting for metal artefacts improves significantly the quality of the treatment plan [Wei et al.,2006] and diminishes the risk of potentially dramatic errors.

1.2.4.4 Improving the conversion to RSP with DECT

Dual-energy X-ray CT (DECT) acquisition has been put forward as a possible tool to improve treatment planning and reduce the range uncertainty. MV-CT has been put forward as a mean to overcome the problem of metal artefacts in kV-CT [Newhauser et al.,2008]. In the aforementioned paper, the use of an hybrid approach using registered kV- and MV-CT images has been proposed. This makes it possible to keep the better sensitivity and contrast of kV-CT. DECT can be even more interesting, in that it makes it possible to access more information on the materials.

Principle of DECT

DECT is a technique that has been first proposed in the late seventies [Alvarez and Macovski, 1976]. The attenuation coefficient of a material (Equation 1.8) can be re-written to take into account a continuous spectrum of energyj:

µ_j =n_e^X

i

w_ij^hZ⁴F(E_ij, Z) +G(E_ij, Z)ⁱ (1.12) withn_ethe electron density of the material,w_ithe fraction by weight of elementiserving as the weighting factor for the energy E_ij, andZ the effective atomic number [Johns, 1983] defined as: withZ_i the atomic number of the elementi.

A CT acquisition with two different energy spectra gives access to two linear attenuation coefficients. Thereby, two different evaluations of Equation1.12are available that can be solved iteratively forZ which makes it possible, in turn, to calculate n_e. Application to treatment planning

DECT gives access to the electron density of the materials, which is a great part of the relative stopping power. An electron density image obtained from kV-kV DECT used for the conversion to Water-Equivalent Path Length (WEPL, projection of the RSP, detailed in Section 2.3.1) makes it possible to reduce the range uncertainty, and the image shows less noise than single energy CT [H¨unemohr et al., 2013]. The other component of the stopping power depends on the ionization potential of the material.

An empirical relationship between the logarithm of this ionization potential and the effective atomic number has been put forward [Yang et al., 2010]. It was shown that kV-MV DECT gives better results than kV-kV or MV-MV DECT [Yang et al.,2011].

Nevertheless, performing DECT is not so trivial, as it either requires the registration of two CT images, or a simultaneous acquisition with two sources. Moreover, while DECT involving MV-CT shows great results, the image is still affected by beam hardening and the trade-off between the image quality and the dose needs to be carefully considered.

1.2. TREATMENT PLANNING AND UNCERTAINTIES IN PARTICLE BEAM THERAPY

1.2.4.5 Upcoming possibilities for X-ray CT imaging?

Other modalities of X-ray CT imaging exist, that have not been investigated in the context of treatment planning for particle beam therapy, but could be of interest.

Spectral CT

Spectral CT consists in detecting and exploiting the energy distribution of the transmitted photons [Giersch et al., 2005]. The principle is similar to that of DECT, except that spectral CT only uses one source but employs energy thresholds in the detector.

The advantage over DECT is that it does not require image registration, nor multiple sources. It could moreover bring more information in the sense that it is not limited to two energies. However, challenges in the covering of large areas, high resolution, uniform performance and long duration operation remain [Shikhaliev and Fritz,2011;Xu et al., 2012].

Phase contrast CT

Phase contrast CT [Momose et al.,1996] is a technique that makes it possible to access the two informations of DECT, namely the electron density and effective atomic number, with only one CT acquisition, thus only one dataset [Qi et al.,2010]. The electron density can be determined from refractive index decrement through a linear relationship. The effective atomic number can be explicitly derived from the ratio of the linear attenuation to refractive index decrement using a power function plus a constant. If proven efficient, this method could have the advantage over DECT due to the lower dose (only one CT acquisition) and because there is no need for registration nor for two sources and detectors.

Neither spectral CT nor phase contrast CT have been considered yet for improving treatment planning – as both are in rather early developmental stages and challenges remain to their spread in clinical setting [Xu et al., 2012; Bravin et al., 2013].

Nevertheless, they may one day become potential solutions.