# Treatment Planning System Basics

## What is a treatment planning system?

A Treatment Planning System (TPS) is a computer system used to determine optimal beam arrangements, energies, field sizes, and ultimately fluence pattern to produce a safe and effective dose distribution.

Moder treatment planning systems are divided into three main components:

Beam model

The beam model is a computerized representation of a beam, defined by energy distribution, machine specific geometry, and beam modifiers such as MLC, flattening filters, and wedges.

Dose Calculation Engine

The dose calculation engine is responsible for applying the beam model to a given patient/phantom geometry and accurately calculating dose.

Beam models range from extremely simple representations to full simulations of individual particles traveling from the treatment head to the region of interest. Selection of calculation engine is often a trade-off between increased accuracy and increased computation time.

Optimization Engine

The optimization engine is determine the optimal arrangement of fields and field modifiers to produce the treatment plan.

In classical 3D treatment planning, the human treatment planner serves as the optimization engine manually manipulating variables to achieve a reasonable plan. IMRT (intensity modulated radiotherapy) and VMAT (volumetrically modulated arc therapy) use a computerized optimization engine and inverse planning to produce complex field arrangements.

## Calculating Dose to Medium

Absorbed dose calculation depends upon the material the radiation is incident upon and the material between the source and the region of interest.  There are 3 common dose calculations:

Dose-to-water with radiation transport in water ()

Historically, most dose computations algorithms (pencil beam, collapsed cone, etc) have computed as this is the dose directly measuring during TPS commissioning and treatment machine calibration.

Dose-to-medium with radiation transport in medium ()

This is inherently the most accurate dose calculation option but is difficult to implement without Monte Carlo.

Dose-to-water with radiation transport in medium ()

Monte Carlo calculations, which typically compute , can be converted to a dose to water, by multiplication with the ratio of unrestricted mass collision stopping power between the medium and water.

is often reported in Monte Carlo simulations because dose to water has been the historical unit used in evaluating treatment efficacy.

#### Can we trust Dose-to-Water with radiation transport in medium?

All three dose calculation methods yield similar calculation in soft tissue but for bone, significant dose differences are found.

There is some evidence that may actually be closer to than . For this reason, and because has been used in determining historical tissue tolerances, AAPM MGGP5.a recommends  over .

Reference: Ma, C-M and Li J, Dose specification of radiation therapy: dose to water or dose to medium? Phys. Med. Biol. 56 (2011) 9073-3089.

Comparison of collapsed cone (CC) dose to water with water radiation transport with Monte Carlo (MC) dose to medium with medium radiation transport and dose to water with medium transport. Note that CC dose to water is closer than MC dose to water to MC dose to medium. Image credit: RayStation.

#### Which dose to use?

In soft tissue targets, the dose differences are small (1-2%).
In bone, however, calculation methods may vary by as much as 12-15%.

Key Point: Today, essentially all clinical implementations calculate dose-to-water both because it is directly traceable to calibration (TG-51) but also because the majority of radiation oncology efficacy data has been gathered using this convention.

• Most clinical experience has historically used dose-to-water.
• Treatment units are calibrated using water, providing a direct link between calibration and calculation.
• Clinical QA is performed in phantoms which are water like (e.g. acrylic, solid water)
• Even for tumor cells in bone, the cells may be chemically more similar to water than to bone.

• is the most accurate representation of absorbed dose to the tissue of interest.
• For Monte Carlo, converting to may introduce additional error.
• Most treatment sites are in soft tissue, where the difference between  and is small (1-2%). Therefore, historical clinical experience may remain useful.

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