63 / 1082
S50
ESTRO 36 2017
_______________________________________________________________________________________________
In this image a dominant intra-prostatic lesion (DIL) in the
right posterolateral peripheral zone has been defined on
both anatomical MRI sequences (top left) and on the
diffusion weighted ADC map (top right). A dose-painting
by contour method has been used to define the region for
dose escalation. Treatment was performed using
interstitial high dose-rate brachytherapy with 5mm
catheter placement in the boost volume and 1cm spacing
elsewhere (bottom left). The final dose distribution
provides highly conformal dose escalation to the high risk
region whilst delivering a standard dose to the remaining
gland. In this plan, the dose escalation was designed to
deliver 21 Gy to at least 95% of the boost PTV and 15 Gy
to at least 95% of the remaining low-risk PTV.
OC-0102 MRI assisted focal boost integrated with HDR
monotherapy for low/intermediate risk prostate cancer
L. Dalimonte
1
, J. Helou
2
, G. Morton
2
, H. Chung
2
, M.
McGuffin
1
, A. Ravi
3
, A. Loblaw
2
1
Sunnybrook Health Sciences Centre University of
Toronto, Radiation Therapy, Toronto, Canada
2
Sunnybrook Health Sciences Centre University of
Toronto, Radiation Oncology, Toronto, Canada
3
Sunnybrook Health Sciences Centre University of
Toronto, Medical Physics, Toronto, Canada
Purpose or Objective
There is growing evidence for the use of High Dose Rate
(HDR) brachytherapy as monotherapy for the treated of
low and intermediate risk prostate cancer patients. With
the increasing availability of magnetic resonance imaging
(MRI) there is an opportunity to further escalate dose to
the dominant intraprostatic lesion (DIL). We report acute
toxicity of this prospective Phase I/II trial.
Material and Methods
Eligible patients had low- and intermediate risk prostate
cancer, IPSS < 16, were medically operable for HDR
brachytherapy treatment and had an identified DIL on
multiparametric MRI (mpMRI) prior to brachytherapy
treatment. Patients were treated with 19 Gy delivered in
one fraction to the whole prostate. A 0-5mm expansion
was applied to the DIL to define the PTV DIL, with a DIL
PTV D90 to receive > 23Gy based on previous experience.
Toxicity was assessed using CTCAE v.4.0 at baseline, 6
weeks 3, 6, 9 and 12 months post brachytherapy.
Results
A total of 34 patients have undergone HDR monotherapy
treatment with an integrated DIL boost with a median
follow up of 6 months. The median age was 67 years
(range 46-80). At presentation, median PSA was 6.1 ng/mL
(2.5-16.4). Three, 26, and 6 patients had low, low
intermediate and high intermediate risk disease. Baseline
characteristics were PIRAD 5 (n=21) and PIRAD 4 (n=13),
mean prostate volume was 37.9 cc (range 18-54). No
patients experienced acute or late Grade 2+ GI
toxicity. The percentage of acute Grade 2 GU toxicity
were as follows; retention 62%, frequency 18%, urinary
tract pain 6%. One patient required catheterization (acute
G3) for one day post treatment and has been catheter-free
since. Urinary retention is the only late Grade 2 GU
toxicity that has been reported (n=6).
Conclusion
The use of mpMRI to define and further escalate dose to
the DIL using HDR monotherapy is achievable with minimal
acute toxicities. Further long term follow is required to
determine efficacy of treatment, and impact on quality of
life and late toxicities.
SP-0103 The challenges of targeting tumour
heterogeneity in the field of radiation oncology
P. Lambin
1
, L. Dubois
2
, A. Yaromina
2
1
MAASTRO Clinic, Maastricht, The Netherlands
2
Maastricht University, Radiotherapy, Maastricht, The
Netherlands
There is no doubt that tumours are heterogeneous at
genetic, biological and pathophysiological level. Intra- and
intertumoural heterogeneity, on one hand, can facilitate
the development of new anti-cancer therapies such as
immunotherapies (1), radiation dose-painting strategies
(2), and can also have great implications for biomarker
discovery. On the other hand, it can hinder anti-cancer
therapy success due to the presence of a resistant clone.
Overall tumour heterogeneity quantified at the genetic
level, tissue level or imaging level (e.g. imaging of tumour
hypoxia, or radiomics), is a negative prognostic factor
(3,4,5). Tumour heterogeneity creates several challenges
that need to be overcome to achieve disease cure. It is
unlikely that a single anti-cancer therapy will work alone
for several reasons. First, the target is likely
heterogeneously expressed throughout a tumour and
primarily (intrinsically) resistant (radio- , chemo- or
immuno-resistant) tumour cells are likely to be present
within a tumour cell population. One example is
heterogeneous expression of epidermal growth factor
receptor targeted to monoclonal antibody cetuximab. In
addition heterogeneous distribution of functional blood
vessels may hamper uniform drug delivery. Secondly,
changes of molecular profile of cancer cells as a
consequence of tumour progression and therapy mediated
selection pressure may lead to acquired resistance and
activation of counteracting mechanisms by cancer cells.
Up-regulation of immune checkpoints or exhaustion
markers is an example of acquired resistance to
immunotherapies. Thirdly, therapy becomes ineffective if
a target gradually disappears while therapy progresses
such as tumour hypoxia during fractionated irradiation due
to tumour reoxygenation. These barriers also emphasize
the need for the development of clinical tools for patient
selection and for novel preferentially non-invasive
(imaging) or minimally invasive (blood based) biomarkers
for tumour monitoring during therapy to enable treatment
modification or adaptation. We believe that there is room
for new treatment options exploiting tumour
heterogeneity.
References:
1. Zegers CM et al. P. Radiotherapy combined with the
immunocytokine (L19-IL2) provides long-lasting anti-
tumor effects. Clin Cancer Res. 2015, 21(5):1151-60.
2. Trani D et al.Preclinical Assessment of Efficacy of
Radiation Dose Painting Based on Intratumoral FDG-PET
Uptake. Clin Cancer Res. 2015, 21(24):5511-8.
3. Lambin et al. Predicting outcomes in radiation
oncology-multifactorial decision support systems. Nature
Rev Clin Oncology. 2013;10(1):27-40.
4. Lambin et al. Radiomics: Extracting more information
from medical images using advanced feature analysis. Eur
J Cancer. 2012;48(4):441-6.