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  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>et al 2012 The DECIDE Science Gateway. Journal of Grid
Computing (2012)</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>A GEANT4 Web-based Application to Support Intra- Operative Electron Radio-Therapy using the European Grid Infrastructure</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>IBFM CNR - LATO Cefalù - Italy</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
          <xref ref-type="aff" rid="aff6">6</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Giovanni Borasi</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
          <xref ref-type="aff" rid="aff6">6</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Maria Carla Gilardi</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
          <xref ref-type="aff" rid="aff6">6</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Carlo Casarino</institution>
          ,
          <addr-line>Giorgio Russo</addr-line>
          ,
          <country>Giuliana Carmela Candiano</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Gianluca Passaro Consortium COMETA</institution>
          ,
          <addr-line>Catania</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Giuseppe La Rocca</institution>
          ,
          <addr-line>Roberto Barbera</addr-line>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>IBFM CNR - LATO Cefalù - Italy University of Milano Bicocca, Milan - Italy San Gerardo Hospital</institution>
          ,
          <addr-line>Monza -</addr-line>
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution>IBFM CNR - LATO Cefalù - Italy University of Milano Bicocca, Milan - Italy San Raffaele Scientific Institute</institution>
          ,
          <addr-line>Milan -</addr-line>
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff5">
          <label>5</label>
          <institution>Italian National Institute of Nuclear Physics, Division of Catania - Italy Department of Physics and Astronomy of the University of Catania -</institution>
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff6">
          <label>6</label>
          <institution>University of Milano Bicocca</institution>
          ,
          <addr-line>Milan -</addr-line>
          <country country="IT">Italy</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2012</year>
      </pub-date>
      <abstract>
        <p>- Radiotherapy techniques permit to deliver ionizing radiations (X-rays, photons, electrons, protons, etc) inside cancerous tissues to kill the abnormal-cells. Radiotherapy related activities, as the optimization of the therapeutic radiation dose to the patient, worker radioprotection, performance controls and technical innovations of linear accelerators, are strongly based on the ability to predict the dose distribution. Monte Carlo simulations are the most accurate tools in this field but, unfortunately, they require large computing power to achieve accurate results in reasonable times. In the last years, advanced cancer treatment clinical and research communities have adopted e-Infrastructures to reduce this gap. The present paper reports on the developments of a computing facility for helping physicians, radiotherapists and medical physical in using modern R&amp;E networking and distributed resources to address some technical and clinical Intra-Operative Electron Radio-Therapy (IOERT) needs (e.g. the design of the linear accelerator collimation system or the optimization of the patient therapeutic dose distribution).</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Keywords— IOERT, Monte Carlo simulation, GEANT4,
Distributed Computing Resources, Catania Science Gateway
framework.</p>
      <p>I.</p>
      <p>INTRODUCTION</p>
      <p>Radiotherapy is one of the most successful non-invasive
methodology for the treatment of different types of cancers.
This technique consists in delivering ionizing radiations
(Xrays, photons, electrons, protons, etc) inside cancerous tissues
to control or kill abnormal-cell growth. Radiation therapy
normally has also several applications in non-malignant
conditions, such as the treatment of trigeminal neuralgia,
acoustic neuromas, severe thyroid eye disease, the prevention
of keloid scar growth, vascular restenosis, and heterotopic
ossification. The use of radiation therapy in non-malignant
conditions is limited partly by worries about the risk of
radiation-induced cancers. In addition, radiation therapy can
also be used as part of curative therapy, to prevent tumor
recurrence after surgery to remove a primary malignant tumor
(for example, early stages of breast cancer).</p>
      <p>From the medical perspective, the radiation of the cancer
cell aim to damage its DNA content and leads rapidly to its
death since no mechanisms to auto-recover from a damage are
available in the cancer cells. Another important aspect which
has to take into account when we talk about radiotherapy is the
radio-protection of tissues not affected by the cancer. To spare
normal tissues, such as skin or organs, some different technics
are used such as: shape the beams during the irradiation,
consider many entrance points, fluence modulation, or, in the
intraoperative treatment, shift the normal tissue and irradiate
the tumor directly. Thanks to this different technics it is
possible to guarantee a much larger absorbed dose level in the
targeted tissues and protect the normal tissues.</p>
      <p>The rapid development and adoption of radiotherapy
techniques have been possible thanks to the introduction a new
generation of linear accelerators (often shorted to linac) that
greatly increases the velocity of charged subatomic particles or
ions by subjecting the charged particles to a series of
oscillating electric potentials along a linear beam-line. The
design of a linac depends on the type of particle that is being
accelerated: electrons, protons or ions. Linac range in size from
a cathode ray tube (which is a type of linac) to the 2-mile (3.2
km) long linac at the SLAC National Accelerator Laboratory in
Menlo Park, California.</p>
      <p>
        Computer simulation of radiation transport and subsequent
dose distribution estimate is of fundamental importance, both
in clinical and research activities. In the clinical perspective
some commercial software, such as Therapeutic Planning
Systems (TPS), are commonly in use to plan, approve and in
situ verify, patient radiotherapy sessions. TPS scope is to
optimize the dose distribution release in the treatment zone and
implement the healthy tissues protection. Unfortunately these
tools, often, offer unsatisfactory accuracy dose calculation
methods, especially in inhomogeneous regions as soft tissue –
bone boundaries [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. Moreover there are others clinical
activities, involving medical physicists, where simulations may
be a support in the development of procedures for the
verification of the linac specifications [2] or impractical
activities where the radiation transport simulations are
irreplaceable, as well adjustments in radiation shielding room
design [3], or even impossible, when direct measurements of
physical quantities are conceptually not executable as in the
case of energy of the particles escaped from the head
accelerators [4].
      </p>
      <p>
        In radiotherapy research, linac manufacturer designers and
medical physics study the best solution to generate and
collimate the radiation beam and/or to optimize the patient
radioprotection. In this context, Monte Carlo simulation
method offers the most exact software tool to calculate
radiation transport and energy deposition but, unfortunately,
require large computing power to achieve accurate results in
reasonable times [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. In fact, particles transports (histories) are
processed sequentially and to achieve a correct statistical
uncertainty in dose values (in most case within 2% the
experimental values) the number of histories may increase up
to 108. In these conditions, a single standard CPU (3 GHz) can
take even some months to complete a single simulation.
      </p>
      <p>On the other hand, useful (per simulation) times may vary
from few hours, as in the case of a TPS, to some days for
company and research requests.</p>
      <p>
        To improve simulation efficiency, in the last three decades,
the direct synergy between scientific-medical community and
linac manufacturers-commercial vendors has produced many
alternative no MC solutions, as convolution/superposition
methods or approximate, as MC simulation associated with
variance reduction techniques [
        <xref ref-type="bibr" rid="ref1">1,5</xref>
        ]. Another innovative and
promising expedient it is represented by Graphical Processing
Unit (GPU) implementation of MC methods. Using the Single
Instruction Multiple Data structure presents on the graphic
board, the same function may be execute many times
simultaneously allowing to process in parallel several histories
[6].
      </p>
      <p>However, the best reliable and tested solution is to use the
“raw” Monte Carlo method in distributed computing
environment. Parallelized computation, in fact, offers to serial
processing a natural and more appropriate practical support. A
time-heavy simulation (of N histories) may be splitted in N’
smaller simulations each one executed on different CPU. For
example, a Grid infrastructure offering 200 CPU core for user,
permits then to reduce computing-times of a factor of 200
(N/200=N’). To address the problematic described above and
support a new and advanced radiotherapy technique, the
iort_therapy application, has been developed.</p>
      <p>The outline of this paper is as follow: in section II we
provide IOERT. In section III we will introduce some
background information about the iort_therapy application
developed by researchers of the IBMF CNR-LATO [7,8]. In
Section IV an overview of the reference model used for
implementing a Science Gateway, which is now used by
physicians, radiotherapists and medical physical to address
some technical and clinical Intra-Operative Electron
RadioTherapy (IOERT) needs, will be described. Finally, we will
report about some outcomes and future prospective.</p>
      <p>II.</p>
      <p>THE INTRA-OPERATIVE ELECTRON RADIOTHERAPY
The Intra-Operative Electron Radiotherapy (IOERT) is a
technique that allows treatment of the cancerous cells directly
in the operating theatre after the surgeon have removed the
tumor tissues [9]. The high ionizing beam is delivered through
special cylindrical applicators positioned during the surgery.
The protection of internal normal tissue from radiation leakage
is a critical point [4]. In breast treatment, for example, it
involves the surgeon positioning a shielding metal disc
between the deep face of the patient’s residual breast and the
pectoral muscle.</p>
      <p>For IOERT dedicated and mobile accelerators, such as
NOVAC7 (NRT, Aprilia, Italy) [10], Liac (Sordina SpA, Italy)
[11], and Mobetron (IntraOp Medical, Inc. Santa Clara, CA)
[2], are employed . The main characteristics of these machines
relies on the capability to be placed near the patient’s bed, the
orientation of the beam in different directions, and the delivery
of very high dose rates compared to traditional linear
accelerators. With the availability of these mobile electron
linear accelerators, IOERT procedures have become
widespread, at least in major clinical centers, giving the
possibility that greater numbers of patients can be treated.
NOVAC7 produces electron beams of 4, 6, 8, and 10 MeV
nominal energies to perform treatments at different tissue
depths. Applicators (collimators) with different diameters from
3 to 10 cm are available. The field of radiation is collimated by
cylindrical perspex applicators with different diameters and tilt
angles. Applicators are available with diameters ranging from 3
to 10 cm and are either parallel (0°) or beveled (15°, 22.5°, 30°
and 45°). The collimation system is of a hard docking type: the
applicators are rigidly attached to the accelerator. Each
collimator is made up of two parts: the upper applicator, that is
fixed to the radiant head, and the lower applicator, that is
placed on the surface to radiate. To perform the treatment, the
radiant head is slowly moved to place the upper and lower part
of collimator in line; a ring allows the two parts to be coupled.
Each collimator corresponds to a Source Skin Distance (SSD)
of 80 cm except for the collimator of 10 cm of diameter that
corresponds to a SSD of 100 cm. In figure 1, the NOVAC7 is
shown in the surgery ready for operation. The collimation
system starts from the end of the accelerator head. The latter
acts as the primary collimation system. Connected to this is the
secondary collimator, consisting of a larger PMMA cylinder
that includes a fixed adaptor and a final collimator.</p>
      <p>To contribute to the study of intra-operative procedures and
to the optimization of the machine, we developed a specific
Monte Carlo (MC) application, “iort_therapy”, using the
GEANT4 toolkit [12]. Today it represents one of the advanced
examples of the official GEANT4 release (9.5 version) and it
can be freely downloaded [13].</p>
      <p>The application simulates the electron beam and the
collimation system of the NOVAC7 and addresses several
technical and clinical issues related to the IOERT technique
such as: the design and optimization of the collimation system;
the study of patient radio-protection aspects; the optimization
of the therapeutic dose distribution [4] and the development of
procedures for verification of the linac specifications [14].</p>
      <p>The application allows the calculation of dose distribution
in water or in other materials. Moreover, it gives the possibility
to choose between different clinical setups and to optimize
radio-protection of normal tissues. Using macro commands, the
user can easily select the appropriate collimator, the phantom
and detector characteristics, the configuration of the shielding
disc employed in breast treatments, the initial conditions of the
electron beam (in particular, position and angular
distributions), and the appropriate physics list, i.e., the
command list for the physical processes.</p>
      <p>In Fig. 2 are shown typical critical situations when the
shielding disc is incorrectly positioned (misaligned and tilted)
respect the collimation system, to reproduce potential
erroneous clinical set-up. In these situations the healthy tissues
are exposed to dangerous ionizing radiations.</p>
      <p>Figure 3 shows the Graphical User Interface (GUI) of
iort_therapy. The GUI is implemented with QT4 libraries. By
interactive windows (Help, Commands, Command outputs and
History) the geometric and physical characteristics of the
clinical setup are chosen and visualized. On the right side, the
smaller tube represents the accelerator head and includes the
exit window, the monitor chamber and the primary collimation
system. The larger and longer tube is the second collimation
system. The water phantom (simulating patient tissues) is
represented by the larger box. It includes a smaller box
representing the sensitive detector (70 mm depth x 150 mm x
150 mm surface). The shielding disc is positioned in the middle
of this structure. To provide a relative error comparable to that
obtained experimentally, 108 histories per simulation must be
generated.
From a technical point of view the application is
embarrassingly parallel and needs a prior-installation of Geant4
as well as some additional libraries. The typical output file
produced by the tool is a dose distribution in a volume
(sensitive detector) of 300 x 300 x 140 voxels. The size of
output files vary from few MBs to tens of GBs. The
application’s workflow is a highly computing demanding
problem. On a single CPU (with 3 GHz core) it would require
about 200 CPU days to produce the dose distribution with the
required precision. The same Monte Carlo computation must
also be repeated many times starting from the same input file
which contains the macro.</p>
      <p>IV.</p>
      <p>THE REFERENCE MODEL</p>
      <p>This section describes the present status of the IOERT
Science Gateway which has been developed by the INFN of
Catania for helping physicians, radiotherapists and medical
physical to use the pan-European GÉANT network, which
operates at speed of up 100 Gbps, and the computing facilities
of the COMETA Consortium[15] to optimize the patient’s
radioprotection and/or set up the best collimation system
configuration to deliver a high dose to the target tissues.</p>
      <p>The IOERT Science Gateway is based on the Catania
Science Gateway framework [16] which has been successfully
adopted in the context of several EU funded projects such as
DECIDE [17], EUMEDGRID-Support [18], GISELA [19],
CHAIN [20] and INDICATE [21]. In a nutshell, the Science
Gateway uses JSR 286 standards (also known as “portlet 2.0”)
to develop advanced tools that can be re-used and combined for
resolving different and complex problems and Liferay as a
portlets container. The access to the Science Gateway relies on
the use of Identity Federations based on the SAML 2.0
standard and on its implementation done by Shibboleth [22]
and SimpleSAMLphp [23]. A “catch-all” Identity Federation to
gather all the users who do not already belong to any
federations and a special IdP that allow people to get
authenticated with the same credentials they already have with
the most common and populated social networks (Facebook,
Google+, LinkedIn, Twitter, Windows Live and Yahoo!) are
also supported. The following authorization mechanism makes
possible to simplifying the access to the infrastructure and
widening its user base. The access to the underlying
computing infrastructure relies on the SAGA standard [24] and
on its JSAGA implementation. A specific JSAGA Adaptors is
used to run Monte Carlo simulations on the COMETA
computing facilities. For the authentication point of view, all
the grid transactions are secured using a robot certificate
installed on a eToken PRO 64KB USB smart card plugged on a
dedicated server which is in charge to generate, using
PKCS#11 and JAX-RS standards, proxy certificates for the
users. Last but not least, the IORT Science Gateway has been
implemented in order to be fully complaint with the strict rules
of the EGI VO Portal [25] and EGI Grid Security Traceability
and Logging Policy [26] policies. The reference model of the
IORT Science Gateway is shown in figure 4.</p>
      <p>The IOERT Science Gateway is an interdisciplinary work
that involves experts belonging to different scientific areas. The
main purpose of the Science Gateway is to build a unique entry
point for physicians, radiotherapists and medical physical
needing to optimize the patient’s radioprotection and/or set up
the best collimation system configuration to deliver a high dose
to the target tissues. When users register to the Science
Gateway, they are mapped to valid Grid users so that, through
a single sign-on mechanism, they can use the portal services
and the underlying computational and storage resources. In fig.
5 is shown a standard JSP page and the relative logic portlet
that has been implemented for collecting the input parameters
and send a bunch of Monte Carlo simulations on the computing
facilities.
The input page consists of several input fields with, at the
bottom, a link to start the running of the Monte Carlo
simulations. Once the simulations have been submitted, users
can follow its status and download its output at the end through
the links of the MyWorkspace portlet which appears on the left
side of the browser when users are signed in. The
MyWorkspace portlet aims to handle users’ jobs and data
through the respective and self-explaining functions MyJobs
and MyData. As an example, figure 6 shows a typical view of
MyJobs.</p>
      <p>Thanks to the advanced R&amp;E networking and the
computing facilities of the COMETA consortium, the
iort_therapy application produces several MB of compressed
data for each simulation reducing the consumed computing
time to 10 CPU hours per run. The raw data generated are then
refined offline using some MATLAB sub-routines. In figure 7
is shown the Wall Clock time consumed by the application
starting from Oct 2012 when the application started to run in
production.</p>
      <p>As it is shown by the figure the trend is increasing. With
this data rate the application is now able to address some of the
Companies and Research Community requirements. As a
future prospective, a new iort_therapy version is under
development for letting physicians to use this application in
hospitals.
[3] National Council on Radiation Protection and Measurement. Structural
Shielding Design and Evaluation for Medical Use of X-Rays and
Gamma-Rays up to 10 MeV (NCRP 49). Office of the Federal Register.</p>
      <p>U.S.A. 1976
[4] Russo G, Casarino C, Arnetta G, Candiano G, Stefano A, Alongi F,
Borasi G, Messa C, Gilardi MC. Dose distribution changes with
shielding disc misalignments and wrong orientations in breast IOERT: a
Monte Carlo - GEANT4 and experimental study. Journal of Applied
Clinical Medical Physics, 2012; 13(5):1526-9914
[5] P. Downes, G. Yaikhom, J.P. Giddy, D.W. Walker, E. Spezi and D.G.</p>
      <p>Lewis. High-performance computing for Monte Carlo radiotherapy
calculations. Phil. Trans. R. Soc. vol. 367, pp. 2607–2617, May 2009.
[6] L. Jahnke, J. Fleckenstein, F. Wenz and J. Hesser. GMC: a GPU
implementation of a Monte Carlo dose calculation based on Geant4.</p>
      <p>Phys. Med. Biol. vol.57, pp. 1217–1229, February 2012.
[7] CNR-IBMF. Available from: www.ibfm.cnr.it
[8] LATO HSR Giglio. Available from www.polooncologicocefalu.it/
[9] Veronesi et al 2001 A preliminary report of intraoperative radiotherapy
(IORT) in limited-stage breast cancers that are conservatively treated
Eur. J. Canc. 37 2178–2183.
[10] Pimpinella M, Mihailescu D, Guerra A S and Laitano R F 2007
Dosimetric characteristics of electron beams produced by a mobile
accelerator for IORT Phys. Med. Biol. 52 6197–6214.
[11] Soriani A, Felici G, Fantini M, Paolucci M, Borla O, Evangelisti G,
Benassi M and Strigari L 2010 Radiation protection measurements
around a 12 MeV mobile dedicated IORT accelerator Med. Phys. 37
995-1003.
[12] Allison J, Amako K, et al 2006 Geant4 Developments and Applications.</p>
      <p>IEEE Trans. Nuc.l Sci. 53 270-278.
[13] Geant4.9.5. Available from: http://geant4.web.cern.ch/geant4/
[14] Bjork P, Knoos T and Nilsson P 2004 Measurements of output factors
with different detectors types and Monte Carlo calculations of
stoppingpower ratios for degraded electron beams Phys. Med. Biol. 49:
44934506.
[15] The COMETA Consortium web site. Available from
www.consorziocometa.it
[17] The DECIDE Project web site. Available from www.eu-decide.eu
[18] The EUMEDGRID-Support Project</p>
      <p>www.eumedgrid.eu
[19] The GISELA Project web site. Available from www.gisela-grid.eu
[20] The CHAIN Project web site. Available from www.chain-project.eu
[21] The INDICATE Project web site. Avaialbe from
project.eu
www.indicateweb site.</p>
      <p>Available from
Project
web
site.</p>
      <p>Available
from
[22] The Shibboleth</p>
      <p>shibboleth.internet2.edu
[23] The SimpleSAMLPhp web site. Available from simplesamlphp.org
[24] SAGA Standard specifications.</p>
      <p>www.gridforum.org/documents/GDF.90.pdf
[25] https://documents.egi.eu/public/ShowDocument?docid=80
[26] https://documents.egi.eu/public/ShowDocument?docid=81
Available
from</p>
    </sec>
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