Koninklijke Bibliotheek, National Library of the Netherlands
IP1511433777920
Comparative study of the calculated risk of radiation-induced cancer after photon- and proton-beam based radiosurgery of liver metastases
Mondlane, Gracinda
Gubanski, Michael
Lind, Pehr A.
Ureba, Ana
Siegbahn, Albert
text
article
monographic
Physica medica
continuing
11201797
0000000012597
42
C
text
Born digital tijdschriften
KB collectiekavel
text
Elektronische Wetenschappelijke Tijdschriften
EWTIJ
10.1016/j.ejmp.2017.03.019
urn:nbn:nl:kb-1511433777664
Automatisch gegenereerd op basis van de EWTIJ XML in release 1.5 van het digitaal magazijn.
EJMP
936
S1120-1797(17)30078-9
10.1016/j.ejmp.2017.03.019
Associazione Italiana di Fisica Medica
Fig. 1
Dose distributions in two patients (left: patient 7; right: patient 3) planned with (a) fixed-field (3D-CRT) photon SBRT and (b) SBRT implemented with VMAT. The corresponding two-field IMPT plans for these patients are presented in (c) and (d), respectively.
Fig. 2
Calculated whole-body risks of fatal cancer induction (a) and total risks of cancer induction (b) for the SBRT-plans (photon-beam based) and IMPT-plans (proton-beam based), estimated using the Dasu-model.
Fig. 3
The relative risks of observing carcinomas (skin, lungs, healthy part of the liver, esophagus, spinal cord and other solid tissue) and sarcomas (bone), estimated using the Schneider-model.
Table 1
Patient setup and description of the photon-beam treatment.
Patient #
Modality (photon SBRT)
Fractionation
Abdominal pressure
PTV (cm3)
Target location
1
Static fields
15Gy x 3
Yes
59.6
Central-peripheral
2
Static fields
17Gy x 3
Yes
73.1
Superior
3
VMAT
8Gy x 7
No
332.3
Posterior/whole liver extent axially
4
Static fields
8Gy x 5
Yes
302.6
Central/whole liver extent axially
5
Static fields
7Gy x 8
No
66.4
Central-periphery
6
VMAT
7Gy x 8
No
294.1
Central-superior
7
Static fields
15Gy x 3
No
18.6
Central-periphery
8
VMAT
7Gy x 8
Yes
78.6
Superior
9
Static fields
17Gy x 3
No
30.2
Central
10
Static fields
15Gy x 3
No
72.3
Central
Table 2
Risk coefficients (
α
1
, second and third column) and the linear quadratic model parameter (last column) used for risk assessment for the different organs at risk. The risk coefficients were taken from ICRP 103 [25]. The linear LQ-model parameters were adapted from Schneider et al. [16], except the value for the spinal cord, which was taken from Kehwar [42].
Organ
α
1
(Gy−1) (fatal risk)
α
1
(Gy−1) (total risk)
α
2
(Gy−1)
Skin
0.0002
0.1000
0.047
Lung
0.0101
0.0144
0.129
Normal liver
0.0028
0.0030
0.487
Esophagus
0.0014
0.0015
0.274
Bone
0.0003
0.0007
0.033
Spinal cord
–
–
0.044
Other solid
0.0028
0.0144
0.080
Table 3
Median values (range) of the relative risks for observing carcinomas (skin, lung, normal liver, esophagus, spinal cord and other solid) and sarcomas (bone), assessed using the Schneider-model.
Organ
IMPT/SBRT relative risk of cancer
Linear
Linear-Exponential
Plateau
Carcinoma
Skin
0.3 (0.2–0.5)
0.2 (0.1–0.3)
0.2 (0.1–0.3)
Lung
0.2 (0.1–0.7)
0.2 (0.1–0.5)
0.2 (0.1–0.5)
Normal liver
0.6 (0.3–0.9)
0.4 (0.2–1.7)
0.4 (0.2–0.6)
Esophagus
0.1 (0.0–0.4)
0.3 (0.1–0.7)
0.2 (0.0–0.5)
Spinal cord
0.0 (0.0–0.2)
0.1 (0.0–0.2)
0.0 (0.0–0.2)
Other solid
0.3 (0.2–0.5)
0.2 (0.1–0.2)
0.2 (0.1–0.3)
Sarcoma
Bone
0.5 (0.2–0.7)
*
p
<0.05 in the comparisons of the risks determined pairwise for all the OARs with the SBRT and IMPT plans.
*
The result for sarcoma induction was calculated with a specific dose-response relationship for sarcomas.
Original paper
Comparative study of the calculated risk of radiation-induced cancer after photon- and proton-beam based radiosurgery of liver metastases
Gracinda
Mondlane
a
b
⁎
gracinda.mondlane@fysik.su.se
Michael
Gubanski
c
Pehr A.
Lind
c
d
Ana
Ureba
a
Albert
Siegbahn
a
a
Department of Physics – Medical Radiation Physics, Stockholm University, Stockholm, Sweden
Department of Physics – Medical Radiation Physics
Stockholm University
Stockholm
Sweden
b
Department of Physics, Universidade Eduardo Mondlane, Maputo, Mozambique
Department of Physics
Universidade Eduardo Mondlane
Maputo
Mozambique
c
Department of Oncology and Pathology, Karolinska University Hospital, Stockholm, Sweden
Department of Oncology and Pathology
Karolinska University Hospital
Stockholm
Sweden
d
Department of Oncology, Södersjukhuset, Stockholm, Sweden
Department of Oncology
Södersjukhuset
Stockholm
Sweden
⁎
Corresponding author at: Department of Medical Radiation Physics, Stockholm University, Box 260, 171 76 Stockholm, Sweden.
Department of Medical Radiation Physics
Stockholm University
Box 260
171 76 Stockholm
Sweden
Highlights
•
Comparison of risks for cancer induction after SBRT and IMPT of liver metastases.
•
With the Dasu-model, the highest risks were estimated for the skin.
•
With the Schneider-model, the highest risk-ratios were estimated for the liver.
•
Both the fatal- and total-cancer risks were lower when the IMPT method was used.
•
Both the carcinoma- and sarcoma risks were lower when the IMPT method was used.
Abstract
Introduction
The potential of proton therapy to improve the sparing of the healthy tissue has been demonstrated in several studies. However, even small doses delivered to the organs at risk (OAR) may induce long-term detriments after radiotherapy. In this study, we investigated the possibility to reduce the risk of radiation-induced secondary cancers with intensity modulated proton therapy (IMPT), when used for radiosurgery of liver metastases.
Material and methods
Ten patients, previously treated for liver metastases with photon-beam based stereotactic body radiation therapy (SBRT) were retrospectively planned for radiosurgery with IMPT. A treatment plan comparison was then performed in terms of calculated risk of radiation-induced secondary cancer. The risks were estimated using two distinct models (Dasu et al., 2005; Schneider et al., 2005, 2009). The plans were compared pairwise with a two-sided Wilcoxon signed-rank test with a significance level of 0.05.
Results
Reduced risks for induction of fatal and other types of cancers were estimated for the IMPT plans (p<0.05) with the Dasu et al. model. Using the Schneider et al. model, lower risks for carcinoma-induction with IMPT were estimated for the skin, lungs, healthy part of the liver, esophagus and the remaining part of the body (p<0.05). The risk of observing sarcomas in the bone was also reduced with IMPT (p<0.05).
Conclusion
The findings of this study indicate that the risks of radiation-induced secondary cancers after radiosurgery of liver metastases may be reduced, if IMPT is used instead of photon-beam based SBRT.
Keywords
Liver metastases
Secondary cancers
SBRT
IMPT
1
Introduction
Proton-beam therapy (PBT) is an emerging form of radiotherapy (RT) used for cancer treatment. A reduction in the number of observed long-term side effects can be expected after proton beam radiotherapy [1–4], due to the decreased integral doses delivered to the risk organs [5]. The reduced risks of inducing secondary malignancies have also been stated as a rationale for the implementation of proton beams in the clinic. This advantage has been emphasized mainly for the radiotherapy of paediatric patients [6–8]. However, in the last decades, advances in cancer diagnostics as well as in systemic treatment options, in combination with a variety of local treatment modalities, have led to increasing survival rates and life expectancy, even for patients receiving RT late in life. This makes the incidence of cancer induction after RT pertinent also for adult RT patients [9,10].
The frequency of radiation-induced cancer in human tissues, after total body exposures with low doses of ionizing radiation, has been determined in different epidemiological studies [11–14]. However, these studies involve doses (<100mSv) which are lower than those used in RT, for which the dose-response can be described with the linear non-threshold (LNT) model. It is well-known that the LNT model overestimates the risks for higher doses, as it does not account for cell kill which decreases the cancer risk [15,16]. Different dose-response models, valid for all doses, have been proposed [15–18]. These models predict a linear increase of risk with dose in the low dose region. At higher doses, some models predict an exponential decrease of the risk with increasing doses. Other models assume risk saturation at high doses. Due to the fact that the estimated cancer-risk depends on the dose heterogeneity across the irradiated organ and on the type of tissue irradiated, these factors should be included in the risk estimation.
A photon-based radiosurgery technique called stereotactic body radiation therapy (SBRT) has been developed, with which high lethal doses can be delivered to targets in the liver with low toxicity. It has been suggested that hypofractionated RT could reduce the frequency of radiation-induced secondary cancers, compared to conventionally fractionated RT [19]. The age at the time of treatment is in general high for patients receiving radiosurgery of liver metastases [20]. However, a large fraction of the patients treated have been found to be long-term survivors [20–22], which has made the late side effects more relevant.
Radiosurgery implemented with proton beams have been proposed for the treatment of liver metastases. Dosimetric studies, comparing photon- and proton-beam therapy for the treatment of oligo-metastases in the liver [22–24] have reported that the doses given to normal tissues can be reduced with PBT. This is in particular the case for the doses given to the normal part of the liver, the main OAR in radiation therapy of malignancies in the liver.
In a recent dosimetric study of radiosurgery of liver metastases, involving patients included in the present study [24], the OARs were found to be better spared from irradiation with low and intermediate doses with the intensity modulated proton therapy (IMPT) technique. However, stochastic effects which lead to cancer induction may occur at all dose levels [25]. Therefore, to be able to compare the risk of radiation-induced cancer, produced with different RT modalities, the risks need to be quantified with the suggested radiation-risk models. The aim of this study was to use radiobiological models to investigate the potential of IMPT to reduce the risk of inducing secondary malignancies after radiosurgery of liver metastases.
2
Material and methods
2.1
Patient selection and treatment planning
Ten patients diagnosed with liver metastases from primary colorectal cancer were included in this study (median age of 77years and range 66 – 89years). These patients were treated with photon-based SBRT at the Department of Oncology and Pathology at Karolinska University Hospital and were selected based on the tumour size and location within the liver (Table 1
), as representative cases for this patient group. A summary of the treatment characteristics is also shown in Table 1.
The planning computed tomography (CT) image sets consisted of 3.0mm thick slices. The dose calculations, carried out as part of the treatment planning, were based on patient-composition data from regular free-breathing CT studies. The ITV concept was used to take the target motion into consideration in the planning. The CTV to ITV expansion margins were determined using 4D-CT studies. The ITV to PTV margins were set to 5mm in the transversal direction and 10mm in the cranio-caudal direction. Two distinct SBRT treatment techniques were used to create the photon plans, the static-field three-dimensional conformal radiotherapy (3D-CRT) technique (7 patients) and the volumetric modulated arc therapy (VMAT) technique (3 patients). VMAT was used to treat the patients with large target volumes (patients 3 and 6) or when critical structures were located close to the target (patient 8), (Table 1). These photon plans, used for the actual treatments, were used as reference plans in the comparison with the prepared IMPT plans. The stereotactic frame, used for patient immobilization, was assigned the Hounsfield unit of air in the planning CT study used for the IMPT planning in order to avoid uncertainties specific for the proton dose calculation.
A two-field IMPT technique was used to retrospectively plan all the patients. The planning objective was set to achieve a similar PTV dose coverage as with the original photon plans. In these plans, the periphery of the PTV received 100% of the prescribed dose and in the center of the target volume, where presumably the more radio-resistant cells were located, doses in the range from 145% to 160% of the prescribed dose were allowed. The healthy part of the liver was identified as the most critical OAR. Other OARs considered were the skin, kidneys, lungs, esophagus, bone and spinal cord. Direct irradiations through the spinal cord and the right kidney were avoided in the IMPT planning. The assessment of risk for treatment-induced secondary malignancies was also performed for the remaining tissues (the part of the body encompassed by the CT study that was not delineated as OARs), referred to as “other-solid”.
The treatment planning was performed with the Eclipse treatment planning system (TPS) (Varian Medical Systems, Palo Alto, California, version 11.0.42). Photon beams of energy 6 MV, produced by a Varian (Varian Medical Systems, Palo Alto, California) linear accelerator, were used for the photon-beam therapy planning. The proton-beam data was taken from a facility with an IBA cyclotron (Ion Beam Applications S.A., Louvain-La-Neuve, Belgium) with initial proton energies varying between 60 and 230MeV. A generic relative biologic effectiveness (RBE) value of 1.1 was assumed for the proton beams.
2.2
Estimation of the risk for radiation-induced secondary cancer
The cancer-risk calculations were performed using data extracted from the dose-volume histograms (DVHs) generated in the treatment planning process. The estimation of the risk for radiation-induced secondary malignancies following radiotherapy was performed using two distinct calculation models. One of these models, the competition model (competition between mutation induction and cell kill), was first proposed by UNSCEAR [17] and later adapted by Dasu et al. [15] to account for both treatment dose fractionation and dose heterogeneity within the OARs. The other model, proposed by Schneider and co-authors [16,18], is based on a metric called the organ equivalent dose (OED) which can be determined with different dose-response relationships. In this model, besides mutation induction and cell kill, repopulation/repair can also be considered to estimate the risks for inducing carcinomas and sarcomas.
From here on, the competition model will be referred to as the Dasu-model and the model based on the OED will be referred to as the Schneider-model. A pairwise two-sided Wilcoxon signed-rank test, with a significance level of 0.05, was then performed of the results obtained with the Dasu- and with the Schneider-model.
2.3
The Dasu-model
The competition model is a linear-quadratic (LQ)-based model (Eq. (1)).
(1)
Total
risk
organ
=
1
∑
i
v
i
∑
i
v
i
×
α
1
D
i
+
β
1
D
i
2
n
×
exp
-
α
2
D
i
+
β
2
D
i
2
n
where
v
i
is the volume of tissue receiving a dose
D
i
and n is the number of fractions used. The parameters
α
1
and
β
1
describe the induction of carcinogenic mutations and
α
2
and
β
2
describe the cell survival in the irradiated organs. The parameters
α
1
and
α
2
are shown in Table 2
. The parameter
α
1
was calculated using the sex-averaged nominal risks coefficients for fatal- and total-risk of induction of cancers given by the ICRP Publication 103 [25] (see Table 2). For proton beams, a radiation weighting factor of 2 (wR as defined by ICRP 103) [25] was used in the conversion of the risk coefficients, to account for the difference in biological effectiveness compared to photon beams. The parameter
β
1
was calculated under the assumption that the probability of induction of mutations and the probability of cell kill are described by the same
α
/
β
parameter. A value of the
α
/
β
parameter of 3Gy was assumed for all the OARs (skin, lungs, healthy part of the liver, esophagus, bone and other-solid). The risk of observing cancer after radiotherapy in any part of the body was then calculated as the sum of the risks obtained for the individual organs and tissues encompassed by the planning CT image studies.
2.4
The Schneider-model
The risks for inducing carcinomas and sarcomas were also estimated using the model proposed by Schneider and co-authors, based on determination of the so-called OED [16] (Eq. (2)).
(2)
OED
=
1
∑
i
v
i
∑
i
v
i
×
RED
(
D
i
)
where
v
i
and
D
i
are defined as for Eq. (1) and
RED
(
D
i
)
is the selected dose-response relationship.
With this model, the risk of observing treatment-induced carcinomas was estimated with three distinct dose-response relationships: the linear, linear-exponential and plateau relationships. The linear relationship predicts a linear increase of the risk with increasing doses. With this model, the mean dose given to the whole organ can be used to calculate the risk. The linear-exponential and the plateau models were derived from a mechanistic equation which, besides the induction of mutations and cell kill also takes the repopulation/repair and treatment fractionation into account (Eq. (3)) [18].
(3)
RED
(
D
i
)
=
e
-
α
′
D
i
α
′
R
1
-
2
R
+
R
2
e
α
′
D
i
-
(
1
-
R
)
2
e
-
α
′
R
1
-
R
D
i
where, R describes the repopulation/repair of the irradiated cells between two dose fractions. It has a value of 0 if no repair occurs and 1 if full repair is observed. The parameter
α
′
is defined using the LQ model and it is proportional to the number of cells which are reduced by cell killing:
(4)
α
′
=
α
+
β
D
i
n
where n is the number of fractions used. The values of
α
in Eq. (4) are presented in the last column of Table 2 as
α
2
. The linear-exponential dose-response relationship is obtained from Eq. (3) by completely neglecting the repopulation/repair effect, i.e., in the limit of
R
→
0
. The plateau dose-response relationship is obtained from Eq. (3) by considering that complete repopulation/repair takes place, i.e., in the limit of
R
→
1
. The three equations describing the dose-response relationships for the linear, linear-exponential and the plateau models, respectively, are shown in Eq. (5).
(5)
RED
(
D
i
)
=
D
i
D
i
e
-
α
′
D
i
1
-
e
-
α
′
D
i
α
′
For the induction of sarcomas, a mechanistic dose-response relationship which takes cell kill and dose fractionation into account was used (Eq. (6)). A minimal repair/repopulation was considered by using a value for the parameter R of 0.1. This level of repair/repopulation was chosen for this work since the patients in our study received hypofractionated treatments.
(6)
RED
(
D
i
)
=
e
-
α
′
D
i
α
′
R
1
-
2
R
+
R
2
e
α
′
D
i
-
(
1
-
R
)
2
e
-
α
′
R
1
-
R
D
i
-
α
′
RD
i
The relative risks for inducing carcinomas and sarcomas were calculated as the ratio of the OEDs obtained for specific OARs in the two plans compared (the IMPT plan relative to the SBRT plan). The risk of observing carcinoma was calculated for the skin, the lungs, the normal liver, the esophagus, the spinal cord and “other-solid”, and the risk for observing sarcomas was estimated for bone. As for the Dasu-model, an
α
/
β
value of 3Gy was assumed for all the OARs in the calculation of risk for radiation-induced malignancies with the Schneider-model.
3
Results
Regarding the target dose-coverage, the treatment planning objectives were fulfilled in all IMPT plans. With these plans, the doses given to most of the OARs were reduced [24]. Calculated dose distributions in the axial plane for two patients planned for SBRT, implemented with fixed-field photon beams (3D-CRT) or with VMAT (representing one case with a small PTV (patient 3) and one case with a large PTV (patient 7)), are shown in Fig. 1
. The dose distributions calculated for the corresponding IMPT plans for these two patients, are also presented.
The risk for inducing fatal cancer and the total risk for observing any type of radiation-induced secondary cancer, estimated using the Dasu-model, are presented in Fig. 2
for each patient. The risk of fatal cancer decreased from a median value of 1% (0%–2%) in the SBRT plans to 0% (0%–1%) in the IMPT plans (p
<0.05) and the total risk for observing secondary neoplasms of any type after radiotherapy decreased from a median value of 14% (5%–41%) in the SBRT plans to 4% (3%–8%), in the IMPT plans (p
<0.05).
When using the Schneider-model for estimating the risk of inducing carcinomas and sarcomas, the ratios of the OED values obtained from the IMPT and SBRT plans were determined, which resulted in the relative risks presented in Table 3
. The ratios of the risks for carcinoma induction were below unity for the different OARs, showing that these risks were consistently lower for the IMPT plans (p<0.05), with only one exception. For patient 3, a relative risk of 1.7 was obtained for the healthy part of the liver with the linear-exponential dose-response relationship (p
<0.05). The risk of inducing sarcomas in the bone was also lower with the IMPT plans (Table 3). A summary of the calculated relative risks of carcinoma induction in the skin, lungs, normal liver, esophagus, spinal cord and other-solid is presented in Fig. 3
for the three distinct dose-response relationships. The calculated relative risks for inducing sarcoma (for bone) are also shown.
4
Discussion
In the present study, we performed a pairwise comparison of the estimated individual risks of radiation-induced secondary malignancies for liver metastases patients treated with photon-beam based SBRT and then later retrospectively planned for IMPT. We found that the calculated risks of radiation-induced secondary cancers were lower for IMPT-based radiosurgery, using both the Dasu- and Schneider-model for cancer-risk estimation.
With the Dasu-model, the risk of observing skin cancer (melanoma) gave the largest individual contribution to the total risk of cancer (between 72% and 94% of the total risk calculated for SBRT and between 75% and 88% of the total risk calculated for IMPT). On the other hand, in the risk assessment carried out with the Schneider-model, the highest values of the OED were registered for the healthy part of the liver for both the SBRT- and IMPT-plans. Relative risks closer to unity were calculated for this organ, indicating that the risk reduction achievable with IMPT was not large. Furthermore, an analysis of the results obtained with the Dasu-model showed that the highest cancer-induction risks were obtained for the patients with the largest PTV volumes, i.e., patients 3, 4 and 6 (Table 1). This is due to the fact that a larger target volume implies larger volumes of the healthy tissue irradiated.
Higher relative cancer-risks (Schneider-model) were calculated with the linear dose-risk relationship, except for the esophagus and spinal cord. For the former organ, the linear model predicted the lowest relative risk, while for the latter organ, comparable risk values were obtained with the three different dose-response relationships. The highest relative risk was determined for the normal liver tissue, with the linear dose-response relationship. With this model, the risk is proportional to the organ mean dose, which was highest for the liver.
The major contribution to the cancer-risks comes from the primary radiation [26]. However, to provide a complete description of the cancer-induction risks for a specific RT technique, the dose deposition produced by the different kinds of secondary radiation present during the treatment, which is considered to be of importance for cancer induction, e.g. neutrons, should also be taken into account [27]. We did not calculate the specific risk produced by secondary neutrons in this work. The standard TPS used clinically (also used for this work) does not perform neutron transport. The doses deposited by other types of scatter radiation, e.g. out-of-field stray photons in photon RT, are also normally not calculated accurately with standard TPSs. To accurately assess the doses deposited by scattered out-of-field radiation, direct phantom measurements and Monte Carlo calculations have been performed [3,26,28]. In one of these studies [28], a 40% reduction of the cancer-risk was calculated for passively-scattered proton beam treatments of hepatocellular carcinoma, compared to 6-MV IMRT treatments. In another study [26], involving 30 prostate-cancer patients, a reduction of the risk of secondary cancer of approximately 50% was obtained for PBS, compared to the photon beam treatment. The irradiation setup used for different treatments must be considered since it determines the tissue volume irradiated and which dose that is given to the surrounding healthy tissue. Despite the fact that these two studies report results for two different tumour sites, the reduction in cancer risk with PBS was large and partly connected to the reduced secondary-neutron doses in PBS, compared to passive-scattering proton beams.
It has been shown that the neutron dose-equivalent decreases rapidly with increasing distance from the beam [3,29]. Schneider et al. [29] reported that, for a medium-sized target volume, the maximum neutron dose-equivalent in the beam, found in the Bragg peak region (177-MeV PBS), is approximately 1% of the treatment dose and therefore practically irrelevant for cancer induction in those regions. The relative importance of the neutron dose increases with distance from the beam due to the long range of neutrons in tissue. For the healthy tissues located outside of the beam, typical equivalent neutron dose of a few mSv per treatment Gy have been determined for medium-size target volumes. Using phantom measurements, Yoon et al. [3] compared the out-of-field doses produced in head-and-neck and prostate cancer treatments after IMRT (scattered photons) and passive-scattered proton therapy (secondary neutrons). The cancer-risk arising from this out-of-field radiation was also estimated using the OED approach. For the prostate cancer patients, the secondary equivalent doses produced in the IMRT treatments were found to be one order of magnitude higher than those produced in the proton-beam treatments. The calculated risk of secondary cancer produced by the out-of-field doses were 5 times higher for the IMRT treatments for these patients, compared to the passive-scattered proton –beam treatments. For the head-and-neck patients, no significant differences in the equivalent doses were found. The lower neutron doses produced in PBS will most likely result in further decreases of the cancer-risk for the out-of-field organs.
RT delivered with conventional fractionation schemes has historically only had a limited role in the treatment of non-resectable primary or metastatic malignancies in the liver due to the risk of treatment induced toxicity [30]. The use of ablative doses to small target volumes, as in SBRT, has led to reduced levels of toxicity while providing effective local control, in the management of liver malignancies [31]. However, the delivery of high radiosurgery doses to targets in the liver requires high accuracy in patient positioning and motion management, especially when using PBS. Motion management for the patients included in this study was performed by using the ITV concept and in some cases abdominal compression was applied. The use of large margins around the CTV leads to increased risks of secondary malignancies due to larger volumes of the surrounding healthy tissue included in the PTV [32]. The implementation of image-guided radiation therapy (IGRT) [33,34] in treatments involving moving targets will enable a reduction of the margins added around the CTV, and thereby a reduction of the doses given to the OARs. There is also a slight increase in the radiation-induced cancer-risk associated with imaging which should not be neglected [35,36].
It has been suggested that radiosurgery could reduce the frequency of secondary cancers, compared to conventional fractionation. In a study performed by Murray et al. [37], hypofractionated RT of prostate cancer reduced the risks of radiation-induced cancers compared to conventional fractionation schemes. This was found to be the case irrespective of the OAR location in relation to the treated volume. In a study performed by Dasu and co-workers [32], hypofractionation resulted in slightly increased risks for bladder- and rectal-cancer. The increased cancer-risk was observed in the organs located closer to the irradiated tumour volumes. On the other hand, due to a reduced fluence of out-of-field radiation, hypofractionation produced decreased cancer-risks in the volumes located farther away from the target.
In our study, the demonstrated advantage of PBS, in terms of cancer-risk reduction, is related to the reduced integral doses given to the patients, compared to the corresponding photon plans. To minimize the irradiation of the healthy tissues in the proton plans, it was found advantageous to use as few beams as possible.
Clinical data regarding the long-term cancer incidence after proton RT is limited. Published short-term follow-up studies can be used for prospective evaluation of the treatment outcome in terms of secondary-cancer induction. In a short-term follow-up study, Chung et al. [38] compared the cancer incidence in a cohort of 558 adult patients (median age 59years) which received proton therapy with another 558 adult patients which received photon-beam RT. The proton beam treatments resulted in a lower frequency of secondary malignancies (5.2%) compared to the photon-beam treatments (7.5%). However, the secondary cancer incidence has, in a study performed by Brenner et al. [39], been shown to increase considerably with the follow-up time. In this long-term follow-up study, the cancer incidence in prostate-cancer patients, which received photon-beam RT, was compared to those prostate-cancer patients previously treated with surgery alone. A comparable level of the risk of secondary cancer was obtained for the bladder (15%) and lungs (11%), even though one of these patient-groups was not irradiated at all. Our results show a relative reduction in the organ-specific cancer risks with PBS, without necessarily providing the accurate absolute values of these cancer risks. The relative reduction of cancer-risk could be less important if the overall absolute risks are very low.
The patients included in this study were adult patients diagnosed with liver metastases late in life. Lower risks of secondary-cancer induction have been reported for elderly RT cancer patients [40], mostly due to the short life expectancy compared to the time required for the carcinogenesis process to take place. The results obtained for the patient group included in this study, can potentially serve as a guideline for ranking between the two RT modalities compared, taking into account the levels of cancer-induction which can be expected after completed RT.
The model parameters used in this work for the assessment of treatment-induced cancer risks were derived from epidemiological studies. Apart from the uncertainties in the epidemiological data [41], there are considerable uncertainties associated with the predictions of radiotherapy-induced cancers connected to other factors. For example, the inter-patient variation of the target size and location determines the irradiation configuration used for the photon- and proton-beam treatments. In this context, the use of ratios of risks in a pairwise comparison of different RT modalities may be useful for ranking RT modalities [41]. In this work, the risk of radiation induced-secondary cancers in different OARs after IMPT was studied using established model-parameters, obtained from the experience with photon-beam RT, assuming that the radiobiological effect of proton beams is similar to what it is for photon beams. The expected future increase in the clinical use of proton beams for cancer treatment will provide further information regarding the tissue response to proton-beam irradiation.
5
Conclusions
The results of this study indicate that, with IMPT-based radiosurgery of liver metastases, a reduction of the risks of radiation-induced secondary cancers can be achieved, compared to photon-beam based SBRT treatments. Despite the fact that the predicted cancer-risks were model-dependent, lower risks were obtained with IMPT, irrespective of the dose-response relationship used.
Funding
This study was financially supported by the Swedish International Development Cooperation Agency (SIDA) through the International Science Programme (ISP) and the Cancer Research Funds of Radiumhemmet at Karolinska Institute, Stockholm, Sweden.
Conflicts of interest
None.
Acknowledgements
The authors would like to acknowledge Maja Malmberg for the valuable comments and critical suggestions, which strongly contributed to this report.
References
[1]
R.
Miralbell
A.
Lomax
L.
Cella
U.
Schneider
Potential reduction of the incidence of radiation-induced second cancers by using proton beams in the treatment of pediatric tumors
Int J Radiat Oncol
54
2002
824
829
10.1016/S0360-3016(02)02982-6
[2]
T.I.
Yock
P.A.
Caruso
Risk of second cancers after photon and proton radiotherapy: a review of the data
Health Phys
103
2012
577
585
10.1097/HP.0b013e3182609ba4
[3]
M.
Yoon
S.H.
Ahn
J.
Kim
D.H.
Shin
S.Y.
Park
S.B.
Lee
Radiation-induced cancers from modern radiotherapy techniques: intensity-modulated radiotherapy versus proton therapy
Int J Radiat Oncol Biol Phys
77
2010
1477
1485
10.1016/j.ijrobp.2009.07.011
[4]
H.
Paganetti
B.S.
Athar
M.
Moteabbed
J.
Adams
U.
Schneider
T.
Yock
Assessment of radiation-induced second cancer risks in proton therapy and IMRT for organs inside the primary radiation field
Phys Med Biol
57
2012
6047
6061
10.1088/0031-9155/57/19/6047
[5]
H.
Paganetti
P.
van Luijk
Biological considerations when comparing proton therapy with photon therapy
Semin Radiat Oncol
2012
10.1016/j.semradonc.2012.11.002
[6]
C.
Greco
S.
Wolden
Current status of radiotherapy with proton and light ion beams
Cancer
109
2007
1227
[7]
T.
Björk-Eriksson
B.
Glimelius
The potential of proton beam therapy in paediatric cancer
Acta Oncol (Madr)
44
2005
871
875
10.1080/02841860500355959
[8]
P.
Hardy
P.
Bridge
What are the potential benefits and limitations of particle therapy in the treatment of paediatric malignancies?
J Radiother Pract
7
2008
9
18
10.1017/S1460396907006218
[9]
A.B.
de Gonzalez
R.E.
Curtis
S.F.
Kry
E.
Gilbert
S.
Lamart
C.D.
Berg
Proportion of second cancers attributable to radiotherapy treatment in adults: a cohort study in the US SEER cancer registries
Lancet Oncol
12
2011
353
360
10.1016/S1470-2045(11)70061-4
[10]
A.M.
Vanderwalde
A.
Hurria
Second malignancies among elderly survivors of cancer
Oncologist
16
2011
1572
1581
10.1634/theoncologist.2011-0214
[11]
D.L.
Preston
E.
Ron
S.
Tokuoka
S.
Funamoto
N.
Nishi
M.
Soda
Solid cancer incidence in atomic bomb survivors: 1958–1998
Radiat Res
168
2007
1
64
[12]
A.
Stewart
A-bomb data: detection of bias in the life span study cohort
Environ Health Perspect
105
1997
1519
1521
[13]
W.F.
Heidenreich
H.M.
Cullings
Use of the individual data of the a-bomb survivors for biologically based cancer models
Radiat Environ Biophys
49
2010
39
46
10.1007/s00411-009-0253-9
[14]
C.I.
Li
N.
Nishi
J.A.
McDougall
E.O.
Semmens
H.
Sugiyama
M.
Soda
Relationship between radiation exposure and risk of second primary cancers among atomic bomb survivors
Cancer Res
70
2010
7187
7198
10.1158/0008-5472.CAN-10-0276
[15]
A.
Daşu
I.
Toma-Daşu
J.
Olofsson
M.
Karlsson
The use of risk estimation models for the induction of secondary cancers following radiotherapy
Acta Oncol (Madr)
44
2005
339
347
10.1080/02841860510029833
[16]
U.
Schneider
D.
Zwahlen
D.
Ross
B.
Kaser-Hotz
Estimation of radiation-induced cancer from three-dimensional dose distributions: concept of organ equivalent dose
Int J Radiat Oncol Biol Phys
61
2005
1510
1515
10.1016/j.ijrobp.2004.12.040
[17]
UNSCEAR
Sources and Effects of Ionizing Radiation 1993 Report to the General Assembly with Scientific Annexes
New York
1993
[18]
U.
Schneider
Mechanistic model of radiation-induced cancer after fractionated radiotherapy using the linear-quadratic formula
Med Phys
36
2009
1138
1143
10.1118/1.3089792
[19]
U.
Schneider
J.
Besserer
M.
Hartmann
Hypofractionated radiotherapy has the potential for second cancer reduction
Strahlentherapie Und Onkol
189
2013
1078
[20]
E.
Liu
M.H.
Stenmark
M.J.
Schipper
J.M.
Balter
M.L.
Kessler
E.M.
Caoili
Stereotactic body radiation therapy for primary and metastatic liver tumors
Transl Oncol
6
2013
442
446
[21]
M.T.
Lee
J.J.
Kim
R.
Dinniwell
J.
Brierley
G.
Lockwood
R.
Wong
Phase I study of individualized stereotactic body radiotherapy of liver metastases
J Clin Oncol
27
2009
1585
1591
10.1200/JCO.2008.20.0600
[22]
N.
Fukumitsu
T.
Okumura
D.
Takizawa
H.
Makishima
H.
Numajiri
K.
Murofushi
Proton beam therapy for metastatic liver tumors
Radiother Oncol
117
2015
322
327
10.1016/j.radonc.2015.09.011
[23]
J.B.B.
Petersen
Y.
Lassen
A.T.
Hansen
L.P.
Muren
C.
Grau
M.
Hyer
Normal liver tissue sparing by intensity-modulated proton stereotactic body radiotherapy for solitary liver tumours
Acta Oncol
Vol 50
6
2011
823
828
doi:10.3109/0284186X.2011.590526
[24]
G.
Mondlane
M.
Gubanski
P.
Lind
T.
Henry
A.
Ureba
A.
Siegbahn
Dosimetric comparison of plans for photon- or proton-beam based radiosurgery of liver metastases
Int J Part Ther
3
2016
277
284
https://doi.org/10.14338/IJPT-16-00010.1
[25]
ICRP Publication 103. The 2007 Recommendations of the International Commission on Radiological Protection. 2007.
[26]
U.
Schneider
A.
Lomax
P.
Pemler
J.
Besserer
D.
Ross
N.
Lombriser
The impact of IMRT and proton radiotherapy on secondary cancer incidence
Strahlentherapie Und Onkol Organ Der Dtsch Rontgengesellschaft [et al.]
182
2006
647
652
10.1007/s00066-006-1534-8
[27]
U.
Schneider
R.
Hälg
The impact of neutrons in clinical proton therapy
Front Oncol
2015
5
doi:10.3389/fonc.2015.00235
[28]
P.J.
Taddei
R.M.
Howell
S.
Krishnan
S.B.
Scarboro
D.
Mirkovic
W.D.
Newhauser
Risk of second malignant neoplasm following proton versus intensity-modulated photon radiotherapies for hepatocellular carcinoma
Phys Med Biol
55
2010
7055
7065
10.1088/0031-9155/55/23/S07
[29]
U.
Schneider
S.
Agosteo
E.
Pedroni
J.
Besserer
Secondary neutron dose during proton therapy using spot scanning
Int J Radiat Oncol Biol Phys
53
2002
244
251
10.1016/S0360-3016(01)02826-7
[30]
L.A.
Dawson
R.K.
Ten Haken
Partial volume tolerance of the liver to radiation
Semin Radiat Oncol
15
2005
279
283
10.1016/j.semradonc.2005.04.005
[31]
V.J.
Nair
J.R.
Pantarotto
Treatment of metastatic liver tumors using stereotactic ablative radiotherapy
World J Radiol
6
2014
18
25
10.4329/wjr.v6.i2.18
[32]
A.
Daşu
I.
Toma-Daşu
L.
Franzén
A.
Widmark
P.
Nilsson
Secondary malignancies from prostate cancer radiation treatment: a risk analysis of the influence of target margins and fractionation patterns
Int J Radiat Oncol
79
2011
738
746
10.1016/j.ijrobp.2009.12.004
[33]
D.A.
Jaffray
Image-guided radiotherapy: from current concept to future perspectives
Nat Rev Clin Oncol
9
2012
688
699
[34]
S.
Shimizu
N.
Miyamoto
T.
Matsuura
Y.
Fujii
M.
Umezawa
K.
Umegaki
A proton beam therapy system dedicated to spot-scanning increases accuracy with moving tumors by real-time imaging and gating and reduces equipment size
(Report). PLoS One
2014
9
[35]
O.
Ardenfors
D.
Josefsson
A.
Dasu
Are IMRT treatments in the head and neck region increasing the risk of secondary cancers?
Acta Oncol (Madr)
53
2014
1041
1047
10.3109/0284186X.2014.925581
[36]
C.B.
Hess
H.M.
Thompson
S.H.
Benedict
J.A.
Seibert
K.
Wong
A.T.
Vaughan
Exposure risks among children undergoing radiation therapy: considerations in the era of image guided radiation therapy
Int J Radiat Oncol
94
2016
978
992
10.1016/j.ijrobp.2015.12.372
[37]
L.J.
Murray
C.M.
Thompson
J.
Lilley
V.
Cosgrove
K.
Franks
D.
Sebag-Montefiore
Radiation-induced second primary cancer risks from modern external beam radiotherapy for early prostate cancer: impact of stereotactic ablative radiotherapy (SABR), volumetric modulated arc therapy (VMAT) and flattening filter free (FFF) radiotherapy
Phys Med Biol
60
2015
1237
1257
10.1088/0031-9155/60/3/1237
[38]
C.S.
Chung
T.I.
Yock
K.
Nelson
Y.
Xu
N.L.
Keating
N.J.
Tarbell
Incidence of second malignancies among patients treated with proton versus photon radiation
Int J Radiat Oncol Biol Phys
87
2013
46
52
10.1016/j.ijrobp.2013.04.030
[39]
D.J.
Brenner
R.E.
Curtis
E.J.
Hall
E.
Ron
Second malignancies in prostate carcinoma patients after radiotherapy compared with surgery
Cancer
88
2000
398
406
10.1002/(SICI)1097-0142(20000115)88:2<398::AID-CNCR22>3.0.CO
[40]
J.
Fraumeni
R.
Curtis
B.
Edwards
M.
Tucker
Introduction
R.
Curtis
D.
Freedman
E.
Ron
L.
Ries
D.
Hacker
B.
Edwards
New Malig among cancer Surviv SEER cancer Regist 1973–2000
2006
National Cancer Institute Publ No 05-5302
Bethseda, USA
[41]
S.F.
Kry
D.
Followill
R.A.
White
M.
Stovall
D.A.
Kuban
M.
Salehpour
Uncertainty of calculated risk estimates for secondary malignancies after radiotherapy
Int J Radiat Oncol
68
2007
1265
1271
10.1016/j.ijrobp.2007.04.014
[42]
T.
Kehwar
Analytical approach to estimate normal tissue complication probability using best fit of normal tissue tolerance doses into the NTCP equation of the linear quadratic model
J Cancer Res Ther
1
2005
168
179
EJMP
936
S1120-1797(17)30078-9
10.1016/j.ejmp.2017.03.019
Associazione Italiana di Fisica Medica
Original paper
Comparative study of the calculated risk of radiation-induced cancer after photon- and proton-beam based radiosurgery of liver metastases
Gracinda
Mondlane
a
b
⁎
gracinda.mondlane@fysik.su.se
Michael
Gubanski
c
Pehr A.
Lind
c
d
Ana
Ureba
a
Albert
Siegbahn
a
a
Department of Physics – Medical Radiation Physics, Stockholm University, Stockholm, Sweden
Department of Physics – Medical Radiation Physics
Stockholm University
Stockholm
Sweden
b
Department of Physics, Universidade Eduardo Mondlane, Maputo, Mozambique
Department of Physics
Universidade Eduardo Mondlane
Maputo
Mozambique
c
Department of Oncology and Pathology, Karolinska University Hospital, Stockholm, Sweden
Department of Oncology and Pathology
Karolinska University Hospital
Stockholm
Sweden
d
Department of Oncology, Södersjukhuset, Stockholm, Sweden
Department of Oncology
Södersjukhuset
Stockholm
Sweden
⁎
Corresponding author at: Department of Medical Radiation Physics, Stockholm University, Box 260, 171 76 Stockholm, Sweden.
Department of Medical Radiation Physics
Stockholm University
Box 260
171 76 Stockholm
Sweden
Highlights
•
Comparison of risks for cancer induction after SBRT and IMPT of liver metastases.
•
With the Dasu-model, the highest risks were estimated for the skin.
•
With the Schneider-model, the highest risk-ratios were estimated for the liver.
•
Both the fatal- and total-cancer risks were lower when the IMPT method was used.
•
Both the carcinoma- and sarcoma risks were lower when the IMPT method was used.
Abstract
Introduction
The potential of proton therapy to improve the sparing of the healthy tissue has been demonstrated in several studies. However, even small doses delivered to the organs at risk (OAR) may induce long-term detriments after radiotherapy. In this study, we investigated the possibility to reduce the risk of radiation-induced secondary cancers with intensity modulated proton therapy (IMPT), when used for radiosurgery of liver metastases.
Material and methods
Ten patients, previously treated for liver metastases with photon-beam based stereotactic body radiation therapy (SBRT) were retrospectively planned for radiosurgery with IMPT. A treatment plan comparison was then performed in terms of calculated risk of radiation-induced secondary cancer. The risks were estimated using two distinct models (Dasu et al., 2005; Schneider et al., 2005, 2009). The plans were compared pairwise with a two-sided Wilcoxon signed-rank test with a significance level of 0.05.
Results
Reduced risks for induction of fatal and other types of cancers were estimated for the IMPT plans (p<0.05) with the Dasu et al. model. Using the Schneider et al. model, lower risks for carcinoma-induction with IMPT were estimated for the skin, lungs, healthy part of the liver, esophagus and the remaining part of the body (p<0.05). The risk of observing sarcomas in the bone was also reduced with IMPT (p<0.05).
Conclusion
The findings of this study indicate that the risks of radiation-induced secondary cancers after radiosurgery of liver metastases may be reduced, if IMPT is used instead of photon-beam based SBRT.
Keywords
Liver metastases
Secondary cancers
SBRT
IMPT
KBJ00000000007620
2017-11-22T18:49:33
S300.1
S300
S1120-1797(17)30078-9
10.1016/j.ejmp.2017.03.019
EJMP
1120-1797
936
FLA
NON-CRC
UNLIMITED
NONE
2017-03-31T02:32:00Z
11201797/v42sC/S1120179717300789/main.xml
103818
MAIN
JA 5.4.0 ARTICLE
FULL-TEXT
11201797/v42sC/S1120179717300789/main.assets/gr1.sml
16176
IMAGE-THUMBNAIL
11201797/v42sC/S1120179717300789/main.assets/gr2.sml
4223
IMAGE-THUMBNAIL
11201797/v42sC/S1120179717300789/main.assets/gr3.sml
5960
IMAGE-THUMBNAIL
11201797/v42sC/S1120179717300789/main.assets/gr1.jpg
88026
IMAGE-DOWNSAMPLED
11201797/v42sC/S1120179717300789/main.assets/gr2.jpg
25920
IMAGE-DOWNSAMPLED
11201797/v42sC/S1120179717300789/main.assets/gr3.jpg
93691
IMAGE-DOWNSAMPLED
11201797/v42sC/S1120179717300789/main.pdf
1334978
MAIN
1.7 6.5
DISTILLED OPTIMIZED BOOKMARKED
11201797/v42sC/S1120179717300789/main.raw
41027
S1120-1797(17)X0010-0
EJMP
1120-1797
42
C
201710
1
364
S1120-1797(17)30078-9
10.1016/j.ejmp.2017.03.019
263
270
main.pdf
PDF
1.7
local
1511433777664
collectiebehoudsniveau 1
2017-11-23T11:33:43.097+01:00
local
1511433778176
0
SHA-512
c0475f7fb9e8e7c9bab8e7a8c7851e341456875f420ec0f4c3c8b5ff318ff0326907a1440f053d22ccb67c40f6ae72e8f0a6fbd1a6bbc576b16d0b6dce3bcec8
java.security.MessageDigest
1334978
Adobe Acrobat Document
1.7
DIAS
62
DIAS tentative identification
main.pdf
local
1511433778177
0
SHA-512
a642569be09692bb8a8a6319dc2314f839f014728ceba2113d0793af4e0760b5d451a0a08bc329dd084c2224cfe6c233c92190dc820cc84277edae82e44b478c
java.security.MessageDigest
41027
not checked
main.raw
local
1511433778178
0
SHA-512
654113c050fd3a309a07b557a36de459e2b0f7413c176a218f9554949162d13d9f68225b07a65dbaddf75bb3f9769dfd5da9feb50b401c78a93e2d133a209d6f
java.security.MessageDigest
103818
not checked
main.xml
local
1511433778179
0
SHA-512
0f80b63fd9ba0b9c512db93f4782012fae6bf99597090fb06556482b7acf7679024140a79a9373ba495d08c35977d30fb0f6ccba61065dd8bb6dd892d642352b
java.security.MessageDigest
3487
not checked
si1.gif
local
1511433778180
0
SHA-512
82696fec8bd8d2040202cd346447719c32b79aa2df94b3d15af2f6a5b729a8e269ec08b9d835955a3e9da6f6d460f0cf5a7353693b454ac0207f116ce5de71ed
java.security.MessageDigest
313
not checked
si12.gif
local
1511433778181
0
SHA-512
51e0f33584d4a35b178e70c56b856c9f6a80f3e5ca57b67a9d545173f8a178c17e1623629f841eadbd6e066a6745a81345c6cc45c8386f96d0763bb422faeb74
java.security.MessageDigest
1304
not checked
si14.gif
local
1511433778182
0
SHA-512
7c52306aee68ee86fe97cb8d71e81059cd15d981d09fd57fe0a5f40f5af989bd67feed0cc0d3b0f488ffbd1c289933ed2febfff5f3052f4bff315b329b02774a
java.security.MessageDigest
464
not checked
si17.gif
local
1511433778183
0
SHA-512
5f058589aec6093aa1a24b77101ebdf996a449219c43db4791185273d3590f9043c978cfdb23053c5825bc0dbacffe169a04baaade1116a50a7ee0a9bd1bba56
java.security.MessageDigest
1884
not checked
si18.gif
local
1511433778184
0
SHA-512
54f7e7d2e025efcf82fc3e3b9ccd717a53f4623294b4114b6231e2ea8a03531a4297b60b61764701a94ce865fdc0b3a7201b24be2ad4230239a67bc1f996bc75
java.security.MessageDigest
215
not checked
si19.gif
local
1511433778185
0
SHA-512
ecd0d81d92b74ed4ad2c4e32d8f5c08328c912c650f2ecc00ff43056628986563eb5416e502bb5327674acaf7d47dcb593b0f2534447d73888648659aacc6b88
java.security.MessageDigest
211
not checked
si2.gif
local
1511433778186
0
SHA-512
cedbfc13a7ee2bebf355a595ddc9712df540c1ca0bca643935544f7fc0f57d1689009dfb66324176019eaf511eaf8bbea5bc9871045c043dcdd3076d286e90d9
java.security.MessageDigest
604
not checked
si20.gif
local
1511433778187
0
SHA-512
0dc989e48377fdce923621bd25dfbf035e86ebcc77d83fb4cde073bc839627a0ae66ed990201c148d96892504a0c3d77a74c524a90c88b14003c178c86d2b08b
java.security.MessageDigest
195
not checked
si21.gif
local
1511433778188
0
SHA-512
b7496e38edfc9a497e79f99780e90b54fe63e138d97ef3f05b24d5ba360cb450695869c83d868a32d4c206f02778db75597d56761ef16889bda80f48a80c0ac2
java.security.MessageDigest
306
not checked
si23.gif
local
1511433778189
0
SHA-512
e5685269a37d10d625570e017a15468ac458f1125f09ee4f5e709668a7604379566aa19aedfb51145078ff6bf435750382c6c9208343fb42fb7d196351bb2dc2
java.security.MessageDigest
272
not checked
si24.gif
local
1511433778190
0
SHA-512
32a013320568bc0196068d144b363258894c8b6f63b7d104ec4b4fe452696a3be87cb2815b2d7e24aee6fec3e6c19fa96ea911b1ec277c066b3ca4a878dd5ff8
java.security.MessageDigest
1269
not checked
si25.gif
local
1511433778191
0
SHA-512
bda58ae1eb1d896df40e4e9de55ff95b5c8a10e62452b92c636c27a6f5dcb01ef8d4c97485557d1c94ed4869f6e413108dfe154104ca0507b95725a2c95e354b
java.security.MessageDigest
2077
not checked
si26.gif
local
1511433778192
0
SHA-512
417914cba0c1129b3f9134a5f64386af523c793903dad7023ad0637d8e8c8a4518302f28122d0d8ce29d847d4ec1c1a79b68c7e4480ed8249c3ca6ec8dddf664
java.security.MessageDigest
228
not checked
si3.gif
local
1511433778193
0
SHA-512
836ca5e4d96098e78a3bf427867a67eecb3d0a02c3000404f9ab3f4e6eb23b12086648d3a2540c7c8e0870d3089c4ad7697d300a5c2ef7b6246b2aa1be8761bd
java.security.MessageDigest
215
not checked
si4.gif
local
1511433778194
0
SHA-512
1454314806ee61daccafca5a9ee64d7d0f8a327560f79df82b23ab26334d79becbf0acc506f0a53f1dcf694dae9bee59b73337407bd3973f3c55d474b0f8526a
java.security.MessageDigest
229
not checked
si5.gif
local
1511433778195
0
SHA-512
71a5d1b80ddf94dbc6f8b99ac2f4b6af2fad6469cd5a1cadc257a3489b516d0c5a14e2005dcfbef8e79f600d31de183a883ee8304cbba478091278de4c9f58e3
java.security.MessageDigest
226
not checked
si6.gif
local
1511433778196
0
SHA-512
0a97b5ba2ac07fa26f9cbfb792f26d01dabb0f679f0056e2b1376ec3670e2233dc49be1389152c8acf0371479a5f14ee7f96c756850df425c097d04814f5996b
java.security.MessageDigest
241
not checked
si7.gif
local
1511433778197
0
SHA-512
8b0f7f7e9a9ef670c8a6dedbe4b435cd53ae89a1a8799bcbd08c6f0e4f538fec70602b1aed05230cba105bdad370961835c12f802b5c597601ebc775fbf67c95
java.security.MessageDigest
88026
not checked
gr1.jpg
local
1511433778198
0
SHA-512
9c3adad9d0497d01273e7fbd74784b89a7c60e640d16a48a45d34d778c87b2c683aaf2d7a69a853a3643efcfd26ce2a1140ac61793b70d2bf543c7b97be8235b
java.security.MessageDigest
16176
not checked
gr1.sml
local
1511433778199
0
SHA-512
3bb0bff4cab296a751c5cfb8e8356f995b550ac31bdbab3f941e340ad715e7bb41486ca6a3ffb452fbfdf8c215a3e9adfbe9da1874095770bb3500d85658271f
java.security.MessageDigest
25920
not checked
gr2.jpg
local
1511433778200
0
SHA-512
f6a2e0590ad9efcd9b9288a0c3ad542879f820a39ee4e946e77b066fab8f94a651292ac9153305b90df6d34860b7ac9f7aa663de6ee8bf8d014104c1e67338a7
java.security.MessageDigest
4223
not checked
gr2.sml
local
1511433778201
0
SHA-512
d667ecd034cf22331eebc6d27e9d52d07381419f3fc28a55e3b0530c30b83479bf5bc12bd14ebc92fdb288dbfbe737b916e047fdc1f7472cfa142ab2e8e5defe
java.security.MessageDigest
93691
not checked
gr3.jpg
local
1511433778202
0
SHA-512
21eea8194cc4daf9631acc2c48e2117ab57a896cb9d558f6209677f0cb95451b015870db3ea7a941d10e1f0dd0ad4f4b983926b1cdaf88c0c1d24b135528a958
java.security.MessageDigest
5960
not checked
gr3.sml
local
1511433778203
0
SHA-512
3d9cbc932e02f767389d0f561868335caf6c32c452d8c83daf3042474a893049b7fc01e25f209d0e3160634a0d263473ba79838e5053278b5c4faa9dce29188f
java.security.MessageDigest
15664
not checked
metadata.xml
free
00001
Associazione Italiana di Fisica Medica
KB-agent-id
1
supplier
KB-owner-id
00001
KB-agent-id
1
Elsevier
organization
Associazione Italiana di Fisica Medica
ingestion
2017-11-23T11:33:43.097+01:00
Connector
software
Digitaal Magazijn release 1.5
ejournals_esp_1
streamprofile
ingestion2017-11-23T11:46:10.053+01:00Generic IngestsoftwareDigitaal Magazijn release 1.5