Chung, C.

Coolens, C.

Driscoll, B.

Foltz, W.

Pellow, C.

Elsevier - Publisher Connector 

56 Comparison of Arterial Input Functions by Magnitude and Phase Signal Measurement in DCE MRI of brain cancer patients 

ICTR-PHE 2016  S27 
 
55 
The International Cancer Expert Corps (ICEC): 
Implementing a global force to address the catastrophic 
rise in cancer in the developing world. 
C. N. Coleman 1, S. C. Formenti2,N. Chao3, S. Grover4; D. 
Rodin5; D. G. Petereit6; B. Vikram7; D. A. Pistenmaa1; M. 
Mohiuddin8; T. R. Williams9. 
1 International Cancer Expert Corps, New York, NY  
2 Cornell University Medical School, New York, NY 
3 Duke Cancer Institute, Durham, NC 
4 University of Pennsylvania, Philadelphia, PA 
5 University of Toronto, Toronto, Canada 
6 American Indian "Walking Forward" Program, Rapid City, SD  
7 National Cancer Institute, Bethesda, MD 
8 Radiation Oncology Consultants, Ltd., Park Ridge, IL, USA. 
9 Lynn Cancer Institute at Boca Raton Regional Hospital, Boca 
Raton, FL , USA. 
 
Purpose: The growing burden of cancer and non-
communicable diseases in the developing world is well 
recognized by the WHO and IAEA culminating in a declaration 
of the need to address them by the UN General Assembly in 
2011. It is projected that ~75% of cancer cases will be in Low 
& Lower-Middle Income Countries (LMIC) by 2025. Effective 
solutions require technological and logistical approaches and 
sufficient expertise to establish sustainable capacity and 
capability in country. 
Materials/methods: Recognizing that the essential 
component for any solution requires expertise, the ICEC (1,2) 
was established in 2013 as a not-for-profit non-government 
organization to address the human resources shortage. An 
extensive analysis by the Global Task Force for Radiation for 
Cancer Control under the auspices of the Union for 
International Cancer Control indicates that a solution is both 
possible and economically feasible (3).  
Results: There is a confluence of forces and opportunities 
that makes the solution to what appears to be an 
overwhelming problem one that can and must be addressed. 
This includes: 
a) the necessity for collaboration among existing programs, 
allowing for individual recognition and approaches while 
minimizing competition that can dissuade investment 
b) a cohort of early stage career cancer experts committed 
to global health 
c) participation of the private sector in global cancer 
education and training 
d) success in addressing health disparities in indigenous 
populations in resource-rich countries that is part of global 
cancer care  
e) an influx of retirees seeking opportunities to use their 
skills 
f)  interest in eliminating dangerous nuclear material 
especially in unstable countries 
The ICEC mentorship model is in active organizational and 
funding development. Essential features and challenges are: 
a) establishing a career path with metrics for academic 
advancement so that time, effort and contributions become 
an integral component of a medical career and not an 
extracurricular activity 
b) supporting time and effort in both resource-rich and –poor 
countries 
c) conducting guideline/protocol-based multi-modality 
cancer care at international standards so that LMICs can 
participate fully in research and training 
d) being multi-national from the outset, capitalizing on 
existing twinning programs 
e) creating an essential role for radiation therapy. 
f) incorporating innovations in physics, information 
technology and telecommunications 
Conclusions: The need, opportunity and a path forward for 
reducing the global burden of cancer are in hand. A 
concerted effort and sustainable investment by a broad range 
of partners are essential. The ICEC addresses the sustainable 
human resources problem with catalytic and disruptive 
innovation in cancer care delivery including a career path, 
economics, technology, public-private partnerships as well as 
visionary leaders and investors.  
 
Key words: Global health, health disparities, disruptive 
innovation 
 
References: 
[1] Coleman CN et al Sci Transl Med. 2014 Oct 22;6(259):259 
[2] Coleman CN et al, Front Oncol. 2014 Nov 19;4:33 
[3] Atun R, et al. Lancet Oncol. 2015 Sep;16(10):1153-86 
[4] Olson AC et al. Int J Radiat Oncol Biol Phys. 2015 Nov 
1;93(3):493-6. 
 
56 
Comparison of Arterial Input Functions by Magnitude and 
Phase Signal Measurement in DCE MRI of brain cancer 
patients  
C. Coolens1,2,3, W. Foltz1,2, B. Driscoll1, C. Pellow1, C. Chung1,2 
1 Radiation Medicine Program, Princess Margaret Cancer 
Centre, Toronto, Canada 
2 Department of Radiation Oncology, University of Toronto, 
Toronto, Canada.   
3 Institute of Biomaterials and Biomedical Engineering, 
Toronto, Canada 
 
Purpose: The aim of this work is to (1) investigate the 
accuracy and robustness of magnitude and phase-derived 
arterial input functions (AIF) as compared to “gold standard” 
volumetric DCE-CT; and (2) evaluate the impact of 
individualized magnitude and phase signal AIF measurements 
on resulting perfusion parameter maps using a common 4D 
temporal dynamic analysis (TDA) method in metastatic brain 
cancer patients treated with stereotactic radiosurgery. 
Methods: We evaluated 14 brain metastases imaged with 
volumetric DCE-CT (Toshiba, Aquilion ONE) and DCE-MRI 
(IMRIS 3T Verio) at baseline then 7 and 21 days post-
radiosurgery.  Both variable-flip-angle (VFA) T1 
measurements and dynamic imaging used 3D-FLASH with 
matched TE/TR of 1.8/4.8ms, with 1x1x5 mm voxels. Voxel-
based whole brain TDA was performed on all data using in-
house software to: (1) compare the AIF curve from DCE-CT 
using the internal carotid artery (AIF) and sagittal sinus (VIF) 
curve from the DCE-CT against DCE-MRI [magnitude (VIFmag) 
and phase-based (VIFph)] (2) compare kinetic parameters 
area under the curve (AUC) and Ktrans, assuming the Modified 
Tofts model when using individual CT AIF, MRI Magnitude and 
Phase-based VIF (Sagittal Sinus) and population-based AIF as 
well as individual voxel-based T10 maps versus assumed T10= 
2400 msec.  
Results: The AUC of individual AIF and VIF on DCE-CT were 
similar and resulting median Ktrans (0.048 +/- 0.03 s-1) was also 
similar. For DCE-MRI, using measured voxel-based T10 maps, 
the resulting Ktrans was higher than for CT using individual 
VIFmag (0.181 +/- 0.11 s-1) or VIFph (0.121 +/- 0.099 s-1). This 
is likely resulting from the smaller AIF peak since the 
population AIF (which more closely resembles CT) correlates 
better to DCE-CT metrics. The measured median T10 value 
was 1572 +/- 594 (n=41) and using the assuming T10=2400 ms 
resulted in significantly higher Ktrans (0.3 +/- 0.14 s-1) and AUC 
(p<0.0006). Voxel-wise correlation between Ktrans values than 
from CT and MRIpopAIF,T10 resulted in high R2 values (~0.5, 
p<0.05) for all imaging days and showed good 
interchangeability (see Bland-Altman plot in Figure 1). 
Conclusion: This preliminary data highlights the stability of 
DCE-CT calculations as well as susceptibility of DCE-MRI Ktrans 
measurements to various imaging factors, including AIF 
selection and T10 values used in the model.  Using the same 
voxel-based analysis platform for both DCE-CT and MR 
significantly improved correlation values confirming the need 
to take into account tumor heterogeneity when assessing 
functional data. 
 
Keywords: Brain metastases, biomarker, perfusion imaging  
 
S28  ICTR-PHE 2016 
 
 
 
57 
Focal adhesion signaling and therapy resistance in cancer 
N. Cordes1-5 
1 OncoRay – National Center for Radiation Research in 
Oncology, Faculty of Medicine and University Hospital Carl 
Gustav Carus, Technische Universität Dresden, Germany and 
Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany  
2 Department of Radiation Oncology, University Hospital Carl 
Gustav Carus, Technische Universität Dresden, Germany  
3 Helmholtz-Zentrum Dresden - Rossendorf, Institute of 
Radiooncology, Dresden, Germany 
4 German Cancer Consortium (DKTK), Dresden, Germany 
5 German Cancer Research Center (DKFZ), Heidelberg, 
Germany 
 
Purpose: Intrinsic and acquired resistance of tumor cells to 
therapy originates from multiple avenues. One avenue 
includes extracellular matrix (ECM) and proteins that 
facilitate cell interaction with ECM. These focal adhesion 
(FA) proteins coalesce at specific membrane sites as large 
multiprotein complexes functioning as signaling hubs and 
structural nexus. Molecular targeting of various FA proteins 
has shown promising preclinical data. Even more interesting 
are rather recent findings about activation of prosurvival 
bypass signaling under specific inhibition of integrins and 
their dependence on ECM stiffness. 
Materials/methods: Different tumor models were 
investigated such as head and neck, pancreatic ductal 
carcinoma, glioblastoma. We performed a systematic 
targeting of FA proteins using siRNA or antibodies where 
applicable. In-vitro and in-vivo survival assays and a variety 
of mechanistic studies were conducted. 
Results: To date, integrins turned out as most promising 
druggable candidates. Most interesting, molecular targeting 
generally showed to prominently induce unfavorable 
prosurvival signaling. Multitargeting strategies were 
successful to abrogate this bypass signaling and optimize 
radiochemosensitization. 
Conclusions: Integrins and other FA proteins are promising 
cancer targets. Identification of underlying mechanisms is 
still the needle eye. From our data, multitargeting 
approaches on top of conventional radiochemotherapy look 
beneficial as specific tumor cell functions can be inhibited. 
 
Keywords: 
Focal adhesions, resistance, bypass signaling 
 
References: 
[1] Eke I, Deuse Y, Hehlgans S, Gurtner K, Krause M, Baumann 
M, Shevchenko A, Sandfort V, Cordes N. β1 
integrin/FAK/Cortactin signaling is essential for human head 
and neck cancer resistance to radiotherapy. J Clin Invest, 
2012, 122(4):1529-40 
[2] Eke I, Schneider L, Förster C, Zips D, Kunz-Schughart LA, 
Cordes N. EGFR/JIP-4/JNK2 signaling attenuates Cetuximab-
mediated radiosensitization of squamous cell carcinoma 
cells. Cancer Res, 2013, Jan 1;73(1):297-306. 
[3] Vehlow A, Cordes N. Invasion as target for therapy of 
glioblastoma multiforme. Biochim Biophys Acta, 2013 Jul 24. 
doi:pii: S0304-419X(13)00038-3. 
10.1016/j.bbcan.2013.07.001. [Epub ahead of print] 
[4] Eke I, Zscheppang K, Dickreuter E, Hickmann L, Mazzeo E, 
Unger K, Krause M, Cordes N. Simultaneous β1 integrin-EGFR 
targeting and radiosensitization of human head and neck 
cancer. J Natl Cancer Inst, 2015 Feb 5;107(2) 
[5] Steglich A, Vehlow A, Eke I, Cordes N. α integrin targeting 
for radiosensitization of three-dimensionally grown human 
head and neck squamous cell carcinoma cells. Cancer Lett, 
2015 Feb 28;357(2):542-8 
[6] Dickreuter E, Eke I, Krause M, Borgmann K, van Vugt MA, 
Cordes N. Targeting of beta1 integrins impairs DNA repair for 
radiosensitization of head and neck cancer cells. Oncogene, 
2015 Jun 15. doi: 10.1038/onc.2015.212. [Epub ahead of 
print] 
 
58 
Evaluation study of in-beam PET performances with a 
Carbon ion linac (CABOTO) 
C. Cuccagna1,2, R. S. Augusto3,4, W. Kozlowska3,5, P. G. Ortega 
3, V. Vlachoudis3 , A. Ferrari3 , U. Amaldi1 
1 Tera Foundation 
2 University of Geneva 
3 CERN 
4 LMU Munich 
5 Medical University of Vienna 
 
Purpose: In-Beam PET is a well-established method for dose 
monitoring in hadrontherapy, but its effectiveness is still 
limited by the accelerator duty cycle [1]. CABOTO [2, 3], 
CArbon BOoster for Therapy in Oncology, is an innovative 
development project of an efficient high-frequency linac for 
hadrontherapy that can accelerate 12C ions and H2 molecules 
up to 430 MeV/u, bunched in pulses of the order of 2-5 µs 
with a repetition rate of 360 Hz. 
Thanks to its low duty cycle (less than 0.1%), CABOTO allows 
the γ-pair acquisition with PET during 99.9% of the treatment 
time. The main goal of this research is to describe how the 
CABOTO time-structure influences the in-beam PET images, 
reconstructed by acquiring the γ-coincidences during the 
irradiation time as well as in a period following it. 
Methods and Materials: The study has been carried out 
performing several simulations with the FLUKA Monte Carlo 
code [4, 5] together with MATLAB routines written to take 
into account analytically the CABOTO time structure. 
In a first set of simulations, the β+ emitter isotopes, 
produced by the interaction of a pencil beam (protons and 
12C-ions) with a water phantom, are identified. Due to the 
special time structure, the PET detector is sensitive also to 
γ-pair produced in the β+-decays of isotopes having half-lives 
(T1/2) in the ms range; the most relevant ones are 13O 
(T1/2=8.6 ms), 12N (T1/2=11 ms), 9C (T1/2=126.5 ms), 8B 
(T1/2=770 ms). Considering the CABOTO time structure and 
the acquisition time window as defined before, the β+ 
activity versus time has been extrapolated for all β+ emitters. 
A second set of simulations including a PET detector has been 
carried out, using a modified version of the routines 
originally developed in Fluka for conventional PET [6]. Arrival 
times of gamma pair coincidences on the PET detector have 
been scored and analysed in order to verify their 
correspondence to the beam irradiation profile. The history 
of each coincidence has been traced in order to identify the 
parent isotope, which helps to discriminate and evaluate the 
true signal versus the background noise. Based on this 
information, the PET images could be reconstructed from the 
true coincidences from both the online and offline signal, and 
quantify the differences. 
Results & Conclusions: This work describes the results 
obtained in the study of the influence of CABOTO time 
structure on the PET scanner reconstruction. The β+ activity 
collected during the irradiation with a single pencil beam has 
been computed together with the estimated background 
during the irradiation. The effect of the very short half-life 
β+ emitters, which produce positrons of longer ranges, has 
been studied. Preliminary results obtained in a simulation on 
a real patient case, with all the beam spots delivered with 
the correct time structure, are also presented. 
 
Keywords: in-beam PET, hadrontherapy, Monte Carlo 
 
References: 


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56 Comparison of Arterial Input Functions by Magnitude and Phase Signal Measurement in DCE MRI of brain cancer patients

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