Quickstart: The first minimal treatment plan

Once pyRadPlan is installed (see Installation), a basic treatment plan can be generated with just a few lines of code — mirroring the experience of matRad’s matRad.m example script.

from pyRadPlan import (
    load_tg119,
    IonPlan,
    generate_stf,
    calc_dose_influence,
    fluence_optimization,
    plot_slice,
)

# 1. Load patient data from the bundled TG119 phantom
ct, cst = load_tg119()

# 2. Create a plan: proton therapy on the Generic machine
pln = IonPlan(radiation_mode="protons", machine="Generic")

# 3. Generate beam geometry (steering information)
stf = generate_stf(ct, cst, pln)

# 4. Compute the dose influence matrix
dij = calc_dose_influence(ct, cst, stf, pln)

# 5. Optimize beamlet fluences
fluence = fluence_optimization(ct, cst, stf, dij, pln)

# 6. Reconstruct dose on the CT grid
result = dij.compute_result_ct_grid(fluence)

# 7. Visualize
plot_slice(image_volume=ct, cst=cst, overlay=result["physical_dose"], overlay_unit="Gy")

Each step corresponds to a major concept described in Concepts. The following sections explain every object and function in detail.