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212 Microsphere deposition, dosimetry, radiobiology at the cell-scale
1
bed
NTCP
1
KF
d)
i
ii
()
toxicity observed in EBRT and that observed in
liver radioembolization. e two modalities are
characterized by a dierent dose rate: instantaneous 1.5–2 Gy doses spaced in time (>8 hours)
in EBRT and exponentially decreasing dose rate
in liver radioembolization (half-life = 2.7 days
for 90Y). e biological eective dose (BED) concept based on a linear-quadratic model (LQM)
has been introduced to account for the dose rate
(Fowler, 1989). is concept succeeded in unifying
the renal toxicity observed in EBRT and in peptide
receptor radionuclide therapy (PRRT) (Barone
et al., 2005; Wessels et al., 2008) and is now also
considered in liver radioembolization (Cremonesi
et al., 2008; Strigari et al., 2010). Regarding the
irradiation itself, both the photons used in EBRT
and the β-particles used in liver radioembolization are low linear energy transfer (LET) particles
and thus share the same radiobiology eectiveness
(RBE) (ICRP, 2007).
Partial liver irradiation in EBRT (Dawson et al.
2001) showed that NTCP = 0.5 is obtained by killing ≈40% of the liver volume or by irradiating 100%,
80%, or 66% of the liver volume with a BED of 77, 95,
or 115 Gy, respectively. ese results can be described
by the following the sigmoid curve for the lobule
nonrecovery probability (Walrand et al. 2014b):
e liver NTCP as a function of the killed lobule
fraction (KF) is (Dawson et al. 2001)
NR bed
1
KF
93.8
0.4
1
(9.9)
2.12
8.29
(9.10)
Equation 9.2 with the glass microsphere distribution obtained using the microsphere transport MC
simulations corresponding to dierent BED delivered to the liver parenchyma. e best agreement
with studies in glass and resin microsphere radioembolization (Chiesa et al., 2015; Strigari et al.,
2010, respectively) was obtained using the asymmetric probability of 69%–31% for the microsphere
bifurcation partition (Figure 9.11). is value is not
far from the 64% to 36% value giving the best agreement with the cluster size distribution observed
(Högberg, 2015). Note that a misunderstanding
occurred in Walrand et al. (2014b) where for the
MC simulations the median toxic dose (TD50)
was given in the targeted liver region as done in
EBRT, while clinical TD50 data observed in radioembolization were reported averaged on the whole
liver (Chiesa et al., 2015; Strigari et al., 2010). is
explains why 60%–40% was the previous optimal
microsphere partition probability.
An important benet of the MC simulation is
the prediction of the hepatic toxicity as a function of various parameters. Figure 9.12 shows the
WLTD50, i.e., the dose averaged over the whole
liver giving NTCP = 0.5, as a function of the
targeted liver fraction and of the microspherespecic activity (msA). For resin microspheres,
the WLTD50 is almost constant for a targeted liver
fraction larger than 65%, reducing the drawback of
mixing whole and right liver radioembolizations
in the same NTCP reporting (Strigari et al., 2010).
Note that Equations 9.9 and 9.10 derived from
EBRT involve that the WLTD50 become innite
when the targeted liver fraction is lower than 40%.
where KF can be computed using
ν
where ν(BEDi) is the fraction of lobules receiving a dose BEDi. Note that in EBRT, Equation 9.11
reduces to
where Vf is the irradiated liver fraction.
Walrand et al. (2014b) computed the ν(BEDi)
fractions by convolving the Russell dose kernel
=KF (bed)NR(be
∑
(9.11)
(9.12)
9.13 APPLICATION OF THE
HEPATIC TOXICITY MODEL
For convenient use, the WLTD(p,Vf,msA), i.e., the
whole-liver dose providing a NTCP = p when targeting a liver volume fraction Vf using 90Y loaded
microspheres of specic activity msA, is tted by
pF
0.869(msA)
=
(9.13)
Vf
F
WLTD ,,msA 47.1Gy
×
where the dimensionless scale factor F(msA) is
pVf
+
10.457 (msA)
()
−
Vf p
Kf()
()
1.2
(a)
SPECT–based VOI drawing method
NTCP
200
0
0.0 0.2 0.4 0.6 0.8 1.0
50 100
Liver BED (Gy)
(b)
150200
03555
Liver D (Gy)
Liver NTCP
72 87
MC simulation
Model
95% CI
Exp
0.8
0.6
9.13 Application of the hepatic toxicity model 213
1
0.4
0.2
0
–0.2
20 40 60 80 100
0
120 140 160 180
D [Gy]
MC simulation
NTCP (D)
FIT NTCP (D)
95% CI
Figure 9.11 NCTP comparison between clinical observations and prediction (squares) from Equations
9.9 and 9.10 using 69%–31% as the microsphere partition probability in the MC calculation of ν(BEDi).
(a) Glass microspheres in right liver radioembolizations (Vf ≈ 0.66) (With kind permission from
Springer Science + Business Media: Eur J Nucl Med Mol Imaging, Radioembolization of hepatocarcinoma with (90)Y glass microspheres: Development of an individualized treatment planning strategy
based on dosimetry and radiobiology, 42, 2015, 1718–1738, Chiesa et al.). (b) Resin microspheres in
mixed whole and right liver radioembolizations (Vf ≈ 0.80). (Reprinted from Strigari et al., J Nucl Med,
51, 1377–1385, 2010. With permission of the Nuclear Medicine Society). Squares were added by the
author. Doses are averaged over the whole liver parenchyma.
214 Microsphere deposition, dosimetry, radiobiology at the cell-scale
msA/0.0471kBq
3
F
()
()
=−
−
1
p
p
200
(a)
WLTD50 [Gy]
q: Strigari et al. 2010
120
(b)
WLTD50 [Gy]
Vf = 0.66
2.50
180
160
140
120
100
80
ms A
2.5 kBq
0.94 kBq
0.45 kBq
0.15 kBq
0.94 kBq: Chiesa et al. 2015
60
40
110
100
90
80
70
60
50
40
0.5
0.00
0.05 kBq
0.6 0.7
Targeted liver fraction
0.50 1.00
Microsphere specific activity (kBq)
0.05 kB
0.8 0.9 1
Vf = 0.8
Vf = 1.0
1.50 2.00
Figure 9.12 Circles: WLTD50 (i.e., dose averaged on the whole liver parenchyma giving NTCP = 0.5)
derived from Equations 9.9 and 9.10 using a 69%–31% microsphere partition probability in the MC
simulation of ν(BEDi). Straight lines: t with Equations 9.13 and 9.14. (a) WLTD50 as a function of the
targeted liver fraction for different microsphere-specic activities (msA). (b) WLTD50 as a function of
the msA for different targeted liver volume fractions (Vf).
msA1e
(9.14)
And Kf(p) is the inverse of the relation
(Equation 9.10), i.e.,
Note that, for a xed total radioembolization
0.4
p
=
activity, the cube root in F(msA) is a quantity
strongly proportional to the mean intermicrosphere distance in the liver.
()
8.29
(9.15)
−
References 215
MC
MC
)
fit −
MC
MC
)
fit −
limWLTD, ,msA 0
pVf
()
=
→
Kf(0.5) = 0.4 and Kf(0.05) = 0.28, which means
that ablating by irradiation 40% and 28% of the
liver induces a NTCP of 50% and 5%, respectively,
as observed in EBRT (Dawson et al., 2001).
In the tted domain {msA (0.05,0.15,
0.45,0.94,2.5) kBq, p (0.15,0.30,0.50), Vf
(0.55,0.66,0.80,1.00)} the mean absolute relative
deviation of the t versus MC simulations (i.e.,
was 2.9% with extreme relative devia-
tions (i.e.,
of –4.97% and 4.60%. It is
quite remarkable that such a simple expression of
F accurately takes into account the impact of mSA.
As the microspheres are localized in the por-
tal triads, the WLTD(p,Vf,msA) value when msA
vanishes does not approach that of EBRT. Indeed,
TD50 = 43 Gy is the dose of 90Y corresponding to
BED50 = 77 Gy observed in whole-liver EBRT. e
simulation in Table 9.1 shows that, in the case of trans-
lation invariant microsphere distribution (which is
expected when the microsphere number increases), 43
Gy in the triad arteries corresponds to a liver parenchyma dose of 40 × 43/118 = 15 Gy, i.e., BED = 19 Gy,
fourfold smaller than the 77 Gy observed in EBRT.
As there is no clinical study available in order to
validate the MC simulation for microsphere activity below 0.05 kBq, a conservative expression of
F(msA) was chosen such as
(9.16)
Equations 9.13 and 9.14 could be used to compute
the needed absorbed dose and also the activity in
order to achieve a desired NTCP = p as a function
of the targeted liver fraction volume and mSA. Note
that this set of equations was obtained by tuning
one parameter of the model (the microsphere partition probability at the arterial tree nodes) in order
to t the clinical hepatic toxicity observed in glass
(Chiesa et al., 2015) and in resin (Strigari et al., 2010)
radioembolization. us, the prediction accuracy of
Equations 9.13 and 9.14 does not only depend on the
goodness of the model but also on the goodness of
the observed clinical hepatic toxicity.
9.14 CONCLUSIONS
MC simulations, using a very simple model of the
hepatic arterial tree and microsphere transport,
reconcile the liver toxicities observed in EBRT
and in radioembolization using glass and resin
microspheres. More interestingly, these MC simulations can be tted with an analytical formula
(Equations 9.13 and 9.14) that allows performing
of individualized radioembolization planning as
a function of the liver fraction targeted and of the
mSA used.
is model contains an adjustable parameter, i.e., the microsphere partition probability
at the arterial nodes, which was tted in order to
reproduce the liver toxicities observed in clinical
radioembolization studies (Strigari et al., 2010;
Chiesa et al., 2015). However, the obtained partition probability 69%–31%: (1) is within the range of
probabilities predicted by microsphere transport
dynamic simulations (Kennedy et al., 2010), (2) is
close to the value 64%–36% tting the observed
microsphere cluster distribution (Högberg et al.,
2015), (3) ts both the hepatic toxicity reported in
glass and resin microsphere radioembolization,
and (4) unies hepatic toxicity observed in radioembolization and in EBRT. ese four facts support the coherence of the whole model and also of
the reported clinical hepatic toxicity as well.
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PART 4
Following Patients Treated
withRadioembolization
10 Postradioembolization imaging using bremsstrahlung 90Y SPECT/CT 221
S. Cheenu Kappadath
11 Quantitative postradioembolization imaging using PET/CT 229
Marco D’arienzo, Luca Filippi, and Oreste Bagni
12 Image-based three-dimensional dosimetry following radioembolization 251
Alexander S. Pasciak and S. Cheenu Kappadath
13 Diagnostic reporting using postradioembolization imaging 263
Yung Hsiang Kao
14 The use of postprocedural imaging in the medical management of patients 281
Austin C. Bourgeois, Marcelo S. Guimaraes, Yong C. Bradley,
Christopher Hannegan, and Alexander S. Pasciak
10
Postradioembolization imaging using
90
bremsstrahlung
S. CHEENU KAPPADATH
Y SPECT/CT
10.1 Background and rationale 221
10.2 Challenges associated with
90
YSPECTimaging 222
10.3 Approaches to
imaging 222
90
Y bremsstrahlung
10.1 BACKGROUND AND
RATIONALE
90
Y radioembolization is used in the management of
patients with unresectable primary and metastatic
liver cancers.
gated albumin (
used, at least in terms of patient safety, as a surrogate
radiopharmaceutical for treatment planning since
the inception of the therapy, as described in Chapter
4. Planar scintigraphy of
primarily to evaluate the lung shunt fraction and
estimate the mean absorbed dose to lung aer the
radioembolization treatment (Ho et al., 1997). MAA
uptake in the lung consequently aects the prescription of administered
vent radiation pneumonitis. MAA distribution in
vivo is also used to assess extrahepatic distribution
and judge the adequateness of tumor perfusion from
the catheter placement. It has been demonstrated
that the assessment of MAA distribution with singlephoton emission computed tomography/CT (SPECT/
CT) is superior compared with SPECT, which in turn
is superior to planar imaging (Ahmadzadehfar et al.,
99m
Technetium-labeled macroaggre-
99m
Tc MAA) has been successfully
99m
Tc MAA has been used
90
Y microsphere activity to pre-
90
Y
10.3.1 Planar imaging 222
10.3.2 SPECT and SPECT/CT imaging 223
10.4 Summary and conclusions 225
References 226
2010). Overall accuracies of 72%, 79%, and 96% for
planar, SPECT, and SPECT/CT, respectively, have
been reported (Hamami et al., 2009).
ere are a number of qualitative studies that
have suggested that MAA distributions observed
during planning oen match the
distributions aer therapy. Concordance between
MAA and
that increases in condence when selective segmental or lobar therapies are planned (Kao et al., 2013).
However, as reviewed in Chapter 4, several studies
have also shown that the distribution of MAA during treatment planning may not be a consistent and
reliable indicator of the distribution of the
spheres aer the administration of treatment (Ilhan
et al., 2015). Dierences of greater than 20% uptake
between
43% (97/225) of cases (Wondergem et al., 2013).
Furthermore, especially in the past decade, in
vivo
used in conjunction with dosimetry models such as
the medical internal radiation dose (MIRD) (Gulec
et al., 2006) or partition (Ho et al., 1996) models
to calculate the tumor and normal liver doses (see,
e.g., Chiesa et al., 2015; Garin et al., 2013).
90
Y has been reported (Chiesa et al., 2015)
99m
Tc MAA and 90Y have been reported in
99m
Tc MAA distributions have begun to be
90
Y microsphere
90
Y micro-
221
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