ESTRO 36 Abstract Book

S852

ESTRO 36 2017

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Purpose or Objective

Radiomics aims to extract features from medical images

that are prognostic for outcome and may help optimize

treatment. As far as the tumour is concerned, most work

has focused on pixel values

inside

the gross tumour volume

(GTV). The aim of this work is to develop a generic

methodology to also sample pixels

outside

a tumour

volume, assuming that these may carry information about

microscopic tumour spread and therefore might predict

outcome.

Material and Methods

We analysed data from a cohort of 1101 non-small cell lung

cancer patients treated with IMRT to 55 Gy in 20 fractions.

To evaluate the CT pixel values at various distances inside

and outside the GTV, we calculated a signed distance

transform of the GTV, which was subsequently used to

efficiently collect cross-histograms of the CT density

versus distance from the GTV edge. Based on these cross-

histograms various pixel statistics were determined as

function of the GTV distance, here we report only on the

mean pixel value, giving a curve of mean CT value versus

distance. The mean of these curves was calculated for

patients that were alive (652) and dead (449) at 12 months

after start of therapy, censored for follow-up. Significance

of the difference was tested by permuting the dead/alive

labels 1000 times to create mock differences and counting

how often the true difference exceeded the mock

difference. Significant regions were defined and the mean

pixel value from those regions used as variable in a cox

proportional hazard model, splitting the patients on the

median of the mean region density, while correcting for

age and tumour size. As the outside of the tumour can also

include chest wall and mediastinum, we repeated the

analysis only analysing pixels inside the lungs.

Results

There was a significant different average pixel value in the

region 0-1 cm outside the GTV for dead and alive patients

(fig. 1) that translated to a hazard ratio (HR) of 1.4, p<10

(corrected for tumour size and age), survival curves split

at median density value (fig. 2A). However when only

pixels inside the lungs were analysed, the HR reduced to

1.1, p=0.15; i.e. no longer significant (fig. 2B). This finding

indicates that the mean pixel values represent mediastinal

attachment rather than microscopic disease. Not

correcting for tumour size, both signals incorrectly predict

outcome significantly (e.g. fig. 2C for lung pixels only).

Conclusion

Proper analysis of pixel-based data mining showed that

lung pixel density outside the GTV did not predict for

survival. The method we proposed allows pixel-based data

mining based on distance to an organ. For such analysis,

one should be well aware of confounding variables such as

tumour size and mediastinal attachment.

EP-1602 Treatment planning individualisation based on

18F-HX4 PET hypoxic subvolumes in NSCLC patients

E. Lindblom

, A. Dasu

, J. Uhrdin

, A. Even

, W. Van

Elmpt

, P. Lambin

, I. Toma-Dasu

Stockholm University, Medical Radiation Physics-

Department of Physics, Stockholm, Sweden

The Skandion Clinic, The Skandion Clinic, Uppsala,

Sweden

RaySearch Laboratories AB, RaySearch Laboratories AB,

Stockholm, Sweden

Maastricht University Medical Center, Department of

Radiation Oncology- GROW-School for Oncology and

Developmental Biology, Maastricht, The Netherlands

Stockholm University and Karolinska Institutet, Medical

Radiation Physics- Department of Physics and

Department of Oncology and Pathology, Stockholm,

Sweden

Purpose or Objective

Pre-treatment functional imaging of tumour hypoxia

enables the identification of patients at greater risk of

treatment

failure,

and,

potentially,

allows

individualisation of treatment to overcome the increased

radioresistance of hypoxic tumours. Treatment

individualisation based on tumour hypoxia aims at

identifying and prescribing higher doses to radioresistant

hypoxic subvolumes based on the relative uptake of

hypoxia-specific tracers. This study aimed to perform

hypoxic target volume delineation and dose-prescription

calculation for non-small cell lung cancer (NSCLC) patients

using a novel hypoxic PET tracer,

F-HX4.

Material and Methods

Six non-small cell lung cancer (NSCLC) patients imaged

with

F-HX4 PET/CT were included in the study. The

hypoxic target volumes (HTV) were determined based on

a non-linear conversion between tracer uptake and pO2,