TCP predictions of an automated dose painting strategy based on FDG and FMISO PET imaging
OC-0627
Abstract
TCP predictions of an automated dose painting strategy based on FDG and FMISO PET imaging
Authors: Marta Lazzeroni1,2, Ana Ureba3,2, Nils H. Nicolay4, Alexander Ruehle4, Benedikt Thomann4, Dimos Baltas4, Michael Mix5, Iuliana Toma-Dasu6,2, Anca L. Grosu4
1Stockhoolm University, Department of Physics, Stockholm, Sweden; 2Karolinska Institutet, Department of Oncology and Pathology, Stockholm, Sweden; 3Stockholm University , Department of Physics, Stockholm , Sweden; 4Medical Center, Medical Faculty Freiburg, German Cancer Consortium (DKTK) Partner Site Freiburg, Department of Radiation Oncology, Freiburg, Germany; 5University Medical Center, Department of Nuclear Medicine, Freiburg, Germany; 6Stockholm University, Department of Physics, Stockholm, Sweden
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Purpose or Objective
Aim of this study was to assess the Tumour Control Probability (TCP) of a
personalized Dose Painting By Contour (DPBC) strategy based on the synergistic
exploitation of the tumour clonogenic cell information derived from FDG PET
images and the tumour oxygen distribution derived from FMISO PET images.
Material and Methods
Thirty H&N cancer patients
imaged with FDG and FMISO PET/CT before radiochemotherapy were analysed. FMISO
PET images were converted into maps of oxygen partial pressure (pO2)
using a non-linear conversion function of radiotracer uptake previously
derived. A dose
distribution at voxel level considering the heterogeneity in
radiosensitivity related to the oxygenation and an heterogenous distribution of
clonogenic cells in the CTV was determined. The tumour clonogens information
was retrieved from
FDG PET images by applying a linear conversion of the radiotracer uptake, having
as an anchor point the tumour cell density carrying capacity set to correspond
to the maximum uptake level retrieved from the patient dataset. The CTV was
segmented into hypoxic target volume (HTV), GTV-HTV and CTV-GTV. A dose
escalation strategy consisting of uniform doses applied to the segmented targets
(dose painting by contour, DPBC) aiming at 95% of TCP in the CTV was employed.
Automated photon treatment plans were made in RayStation
(v10, RaySearchLaboratories)
with ±3mm setup errors (7 scenarios) for minimax robust optimization. The
unsupervised planning strategy used the same objective functions for the whole patient
population and a total dose delivered in 35 fractions with an integrated boost. A dosimetric
evaluation of the treatment plans, accounting for target coverage and
constraints for the organs at risk, was followed by an assessment of the TCP in
the targets accounting for the dose distribution in the nominal plan and the
radiosensitivity maps derived from combined FMISO and FDG PET information
(Figure 1).
Results
Prescribed doses expressed as equivalent doses in 2 Gy per fraction
(EQD2) for D50% were 82±4 Gy in the HTV, 72±3 Gy in GTV-HTV, and 68±2 Gy
in CTV-GTV. 97% of the plans were clinically feasible considering brain stem, spinal
cord, and mandible constraints. Parotids could be spared in only 57% of the
cases, since they were inside the PTV, and target coverage was prioritized. The
TCP accounting for
the planned dose distribution and image-derived radiosensitivity maps was
higher than 95% control for the nominal plan in all the targets for 87% of the
cases (Figure 2). For four remaining cases lower TCP values, seemingly attributable
to voxels receiving low doses at the target periphery, were however observed
requiring further investigation and potential a posteriori adjustment.
Conclusion
Automated treatment planning with integrated boost targeting hypoxia and considering
a heterogeneous density of clonogens in the tumour based on functional imaging has
shown clinical feasibility and high tumour control prediction.