Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_3618_Библиотеки_им_академика_М_И_Перельмана
.pdf
92 Treatment planning part III
(c)
by Campbell et al. (2000, 2001), light microscopy was
90
used to evaluate the distribution of
Y microspheres
directly from microscopic analysis of tissue samples
taken from a patient postradioembolization. is
patient received 3 GBq of 32-µm resin microspheres
to treat an 8-cm metastatic liver tumor. Campbell’s
analysis noted that the microspheres were highly
concentrated in the periphery of the tumor, creating
very large absorbed doses ranging from 200 to 600
Gy. However, the average absorbed dose in the center
of the tumor was only 6.8 Gy. Dose distribution was
equally inhomogeneous in uninvolved hepatic tissue
with an average dose of 8.9 Gy with approximately
1% of normal liver receiving more than 30 Gy.
e dose heterogeneity determined by microscopic analysis of Campbell’s biopsy samples has
been conrmed on a larger scale with a similar
analysis of whole livers (Kennedy et al., 2004) aer
radioembolization. Large tumor dose heterogeneity ranging between 100 and 3000 Gy was found
in patients with both primary and metastatic liver
cancer treated with glass and resin microspheres,
respectively (Kennedy et al., 2004). Owing to the
dierent specic microsphere activity in the glass
and resin products, livers treated with resin radioembolization had more microspheres per cluster
within the vessels (Kennedy et al., 2004).
Evaluation of intratumoral dose heterogeneity has also been performed noninvasively, using
various imaging modalities and methods. reedimensional dose distributions can be inferred
from
99m
Tc macroaggregated albumin (
99m
Tc-MAA)
single-photon emission computed tomography
(SPECT)/CT as also demonstrated by Kennedy
etal. (2011). In addition, the dose distribution can
90
be determined directly from posttreatment
Y
(a)
Figure 5.4 (a) Pretreatment contrast-enhanced CT of a patient with cholangiocarcinoma. Left lobe
tumor demonstrates hypodense necrotic core with enhancing peripheral areas of active tumor (b).
Correlating pretreatment 18FDG-PET/CT shows hypermetabolic activity along the peripheral tumor
margin. The necrotic, low attenuating tumor component manifests relatively little FDG avidity. (c) 90Y
PET/CT imaging following embolization of this patient’s left lobe with 821 MBq (22.2 mCi) of resin
microspheres. The low absorbed dose in the center of the necrotic region is plainly visible on posttreatment 90Y PET/CT.
(b)
5.5 Calculating the absorbed dose / 5.2.3 Effective dose 93
()
⋅⋅
()
⋅⋅
GBq 49.98(J s)
A
bremsstrahlung SPECT or 90Y positron emission
tomography/computed tomography (PET/CT), as
described in detail in Chapters 10 and 11. Figure 5.4a
illustrates the pretreatment contrast-enhanced CT
in a patient with cholangiocarcinoma. Figure 5.4b
demonstrates the correlating 2-deoxy-2-(18F) uoroD-glucose (FDG)-PET/CT of the same patient, with
hypermetabolic activity along the peripheral tumor
margin. e necrotic, low attenuating tumor component manifests relatively little FDG avidity. Figure
5.4c shows 90Y PET/CT imaging following emboli-
zation of this patient’s le lobe with 821 MBq (22.2
mCi) of resin microspheres. e low-absorbed dose
in the center of the necrotic region is plainly visible
on posttreatment 90Y PET/CT. Quantication of the
PET data in Figure 5.4c using methods described in
Chapters 11 and 12 yields a maximum tumor dose
of 440 Gy with a minimum dose of just 4.6 Gy at the
necrotic center of the tumor.
5.5 CALCULATING THE
ABSORBED DOSE
Yttrium-90 is one of a handful of radionuclides that
is considered to be a pure β-emitter, emitting no
gamma rays at any appreciable yield following decay.
Although several rare decay pathways of 90Y are discussed in the following chapters, 90Y is considered a
pure β-emitter for all practical purposes related to
dosimetry. 90Y releases a higher energy electron than
other pure β-emitters that have been used in internal radionuclide therapies, with a maximum and
average energy of 2.28 and 0.935 MeV, respectively.
e range of the maximum energy 90Y β-particle is
11 mm in tissue, while its average energy β particle
has a range slightly less than 4 mm. e penetration depth of the high-energy 90Y β-particle is a key
component of this radionuclide’s success in radioembolization, allowing for high dose deposition into
the tissues between embolized capillaries. However,
when the absorbed dose of 90Y therapy is considered
for a tumor or nontarget site, an important simplifying assumption can be made: β-radiation released
from microspheres within a given organ will be fully
absorbed by that organ. is assumption is easy to
justify based on the average 4-mm 90Y β range in
tissue. However, this does not account for secondary radiation, which may extend beyond the 11 mm
range of a 90Y β-particle. As discussed in Chapter
1, high-energy 90Y β-radiation will create second-
ary X-rays in the form of bremsstrahlung and characteristic emissions. ese photons will penetrate
through the liver and contribute to dose in extrahepatic tissues and even to individuals in close proximity to the patient. However, as discussed by Stabin et
al. (1994), this will have little eect on the absorbed
dose in the organ treated with radioembolization. A
second assumption that becomes important is the
permanence of 90Y radioembolization—neither glass
nor resin microspheres are biodegradable, and once
infused, both products form a permanent implant.
Combining these two assumptions allows for easy
calculation of average absorbed dose to an organ of
interest on a macroscopic scale.
is calculation is derived in Equations 5.1
through 5.3:
∞
=ϕ =
d0.935MeV
EEEE
avg
=⋅
==
J d 1.498 10
EAEet
()
tot0avg
GBq 49.86(J s)
A
=⋅⋅
D
where E
avg
is the average energy released per decay
avg
()
∫
0
1.498 10 J
()
0
Gy
()
−
13
∞
−λ −
t
∫
0
0
=
M
A
λ
liver
0
(kg)
13
(5.3)
(5.1)
(5.2)
of 90Y based on the probability density function
(E) for emission (Eckerman et al., 1994), and λ is
the Y90 decay constant based on a half-life of 64.24
hours. A0 is the 90Y activity present in the organ or
organ segment of interest in GBq, and E
is the total
tot
energy released by A0 from the time that it is infused
until it has fully decayed. e absorbed dose (D) is
expressed in Gy and can be obtained by dividing E
by the mass of the treated liver, M
. Alternatively,
liver
tot
the volume of the tissue can be obtained from tomographic imaging and multiplied by established tissue
densities (International Commission on Radiation
Units and Measurements [ICRU], 1992). It must
be reiterated that the absorbed dose calculation in
Equation 5.3 is only valid for 90Y radioembolization
and only representative of average absorbed dose in
an organ. Equation 5.3 cannot be used for absorbed
94 Treatment planning part III
dose calculation for radioembolization using radioisotopes other than 90Y such as
with the emission of a prompt gamma ray and a
β-particle, thus violating the assumption that all
energy emitted during decay is absorbed by the
organ of interest.
166
Ho, which decays
5.6 TUMOR AND NORMAL LIVER
ENDPOINTS
Careful consideration of tumor and nontarget tissue
endpoints is paramount to hepatic treatment planning for radioembolization. In addition to nontarget
hepatic dose deposition, radiation exposure to extrahepatic tissues, including the lungs and tissues in the
GI tract, are of concern. Consideration of lung dose,
from arteriovenous shunting as well as managing
patients with extrahepatic nontarget embolization,
is covered in detail elsewhere in this book. As such,
this section will emphasize dosimetry endpoints in
tumor and uninvolved liver tissue.
5.6.1 NORMAL LIVER ENDPOINTS
Radiation-induced liver disease (RILD) is a term
that is commonly referenced in the literature as 90Y
radioembolization has gained traction as a standard-of-care treatment for primary and metastatic
liver cancer. However, the meaning and context of
RILD are oen ambiguous and inconsistent. We
dene RILD in patients following radioembolization as clinically signicant manifestations of
hepatic insuciency such as weight gain, ascites,
anicteric hepatomegaly, and/or pain in the right
upper quadrant within 90 days of treatment (Guha
and Kavanagh, 2011). In patients without underlying cirrhosis, these symptoms may be accompanied by serologic evidence of hepatic toxicity,
manifested by rising alkaline phosphatase and
glutamyl transpeptidase (Sangro et al., 2008). It is
important to note that RILD represents a spectrum
of clinical and serologic manifestation of acute
hepatic injury. RILD is oen self-limited, although
in its most severe form can result in hepatic vascular endothelial damage leading to a fatal condition
resembling veno-occlusive disease (VOD). On the
other end of the spectrum, it should be emphasized that Grades 1 and 2 mild liver toxicity is very
common following radioembolization (Goin et al.,
2005; Gulec et al., 2007; Kennedy et al., 2009) and
does not t into the common denition of RILD.
Normal liver tissue has a relatively low tolerance
to radiation (Dawson and Guha, 2008). Data from
EBRT suggest that the threshold for RILD following whole-liver irradiation is between 30 and 40 Gy
(Emami et al., 1991; Lau et al., 1994; Cremonesi et
al., 2008). Specic cases have demonstrated that liver
failure can occur from VOD in the setting of EBRT
at doses as low as 35 Gy (Sempoux et al., 1997). It is
important to consider that the toxicity thresholds
from EBRT can only be applied to radioembolization
in a very limited fashion. In fact, the liver can tolerate higher absorbed doses from radioembolization
than it can from fractionated EBRT. is phenomenon may be explained by dierences between the
dose rate of fractionated EBRT and radioembolization, extent of nontumor involved liver, as well as the
degree of hypoxia created by capillary occlusion in
radioembolization. In addition, the heterogeneity of
absorbed dose at a microscopic scale also contributes
to the decreased hepatic toxicity per gray of radioembolization compared with EBRT due to microscopic
sparing of normal tissue. e importance of microscopic dosimetry is discussed in detail in Chapter 9.
e dose threshold for hepatic toxicity is variable among patients and reects hepatic functional
reserve, liver volume, concomitant diseases and
medications, tumor volume, and other patientspecic factors. e most widely supported upper
absorbed dose toxicity limit to normal liver from
radioembolization is 70–80 Gy (Fox et al., 1991;
Lau et al., 1994; Campbell et al., 2001; Salem and
urston, 2006). Because underlying cirrhosis
decreases the tolerance of the liver to radiation
(Dawson and Guha, 2008), 70 Gy should be considered the maximum in cirrhotic patients. However,
there have been published cases where the absorbed
dose to normal liver has safely exceeded these
thresholds, approaching 100 Gy (Gulec et al., 2007).
Further, treatment planning models for the glass
radioembolization product support average doses
of up to 150 Gy in treated tissue (Lewandowski
etal., 2005; Salem and urston, 2006).
Cirrhosis and other underlying chronic liver
disease such as viral hepatitis are not the only conditions that could decrease the tolerance of the
liver to radiation. It has been shown that previous
chemotherapy can increase the occurrence of VOD
5.7 Tumor-to-normal uptake ratio / 5.6.2 Tumor endpoints 95
T:
/
/
90 ,Normal normal
AV
AV
Y
following radioembolization (Sangro et al., 2008)
by contributing to intrahepatic vascular endothelial damage. Previous research has demonstrated
that patients with metastatic liver disease receive
a higher average dose to nontarget liver even when
the same dosage of radioembolization is delivered
(Sangro et al., 2008). erefore, one must carefully
consider prior chemotherapy in the treatment
planning process of patients undergoing radioembolization for metastatic disease, just as the
severity of cirrhosis aects treatment planning in
hepatocellular carcinoma (HCC) patients.
5.6.2 TUMOR ENDPOINTS
Tumoricidal endpoints in theory depend on
many radiobiologic factors, including tumor type,
absorbed dose, heterogeneity of absorbed dose,
and prior radiological or chemotherapeutic treatments. Because the number of infused microspheres and the activity per microsphere also vary
widely between glass and resin microspheres,
dose–response data of one product cannot necessarily be applied to the other.
e largest cohort of published data describing
tumoricidal endpoints is for hepatocellular carcinoma. When treating HCC, 120 Gy should be considered to be a reasonable minimum tumor target
dose (Yoo et al., 1989; Lau et al., 1994; Ho et al., 1997;
Kennedy et al., 2004; Strigari et al., 2010). Eorts to
achieve this absorbed dose in the tumor can be made
using the methods described in the following sections, provided the maximum tolerable dose to normal liver and extrahepatic tissues is not exceeded.
Because of the histologic and biologic variability of metastatic liver tumors, dose–response
data are less certain. However, worldwide clinical
trials are currently underway to use advanced
quantitative imaging to identify dose–response
thresholds for metastatic disease. While published data in the literature is widely varying, it
is likely that neuroendocrine metastases to the
liver or neuroendocrine tumor (NET) are likely
to show a strong response to radioembolization
at a lower absorbed dose than HCC. On the other
hand, metastatic colorectal cancer (mCRC) may
require an absorbed dose equal to or higher than
HCC (Gulec et al., 2007) to achieve the desired
therapeutic response.
5.7 TUMOR-TO-NORMAL
UPTAKE RATIO
e tumor-to-normal uptake ratio (T:N) is an
important quantity in radioembolization with
glass and resin 90Y microspheres as well as
radioembolization. is quantity has a substantial role in treatment planning and can impact the
tumor-absorbed dose, liver dose, and the toxicity or ecacy of the treatment. T:N is dened in
Equation 5.4:
90 ,Tumortumor
where A
N
is the 90Y activity (MBq) deposited
90 Y,Tum or
in the tumor and A
=
90 Y,Nor mal
Y
in uninvolved liver tissue. V
is the activity deposited
normal
(5.4)
and V
respective volumes of each. Table 5.2 lists a range
of measured T:N for dierent tumor types from
several publications in the literature.
While Table 5.2 shows just a few examples from
the literature, one thing is immediately clear: T:N
tumor
166
Ho
are the
Table 5.2 T:N from published sources
Disease
HCC 11.5:1 7:1–16:1 2 Pathologic Kennedy et al. (2004)
HCC 7.0:1 3.9:1–9.2:1 5
HCC 3.5:1 1:10–13.5:1 27
mCRC 6.8:1 2.9:1–15.4:1 15
mCRC — 2:5–2:1 2 Pathologic Kennedy et al. (2004)
NET 5.9:1 3.5:1–11.1:1 20
T:N
median/
mean T:N range
Number of
patients or
tumors
Measurement
method Reference
99m
Tc-MAA Gulec et al. (2007)
99m
Tc-MAA Lau et al. (1994)
99m
Tc-MAA Gulec et al. (2007)
99m
Tc-MAA Gulec et al. (2007)
96 Treatment planning part III
varies signicantly even in cases of the same
tumor type. Tumor size, percentage inltration,
presence of centralized necrosis, and the technique used to measure T:N all contribute to these
variations.
as a valid surrogate for 90Y microspheres. There
are many reasons why this may be untrue, several of which are outlined in Table 5.3.
Many authors have evaluated the validity of
MAA as a radioembolization surrogate, with
no clear consensus (Knesaurek et al., 2010; Kao
5.7.1 USING MAA AS AN
ESTIMATION TOOL
et al., 2012; Lam and Smits, 2013; Lam et al., 2013;
Wondergem et al., 2013; Garin et al., 2014; Lam
and Sze, 2014). e position of the catheter tip
Before reviewing how T:N can be used in radioembolization treatment planning, it is important to understand methods that can be used to
quantify it. The most widely used established
method for pretreatment estimation of T:N is
MAA SPECT/CT. This technique is convenient
since it is simply an extrapolation of the data
acquired in the pretreatment lung-shunt study.
This method assumes the validity of
Table 5.3 Potential sources of error when using MAA as a microsphere surrogate
Issue Comments Impact Amelioration
Specic gravity
differences between
macroaggregated
albumin (MAA) and
microspheres
Particle size and shape MAA particles generally
99m
Free
Embolic differences Stasis may be reached in
Catheter position and
Tc May not signicantly
centering
Signicant difference in
Catheter positioning
99m
Tc-MAA
the case of glass
microspheres
have a wider size range
compared to either
resin or glass
microspheres
affect T:N
measurements but
could obscure
detection of gastric
nontarget embolization
(NTE)
some tumors treated
with resin microspheres
but not MAA
differences between
MAA and
can drastically effect
deposition
90
Y infusions
during both infusion of MAA and radioembolization is among the most critical factors to the prognostic utility of T:N measurements made from
99m
Tc-MAA SPECT/CT. Positioning of the catheter
tip becomes especially critical when it is near a
bifurcation or when it is positioned in a tortuous
vessel (Jiang et al., 2012; Wondergem et al., 2013).
However, in spite of variable correlation between
MAA and 90Y microspheres in the literature, the
Moderate N/A
Moderate N/A
Moderate Prophylactic oral
administration of 500
mg perchlorate
(Ahmadzadehfar et al.,
2010); use MAA right
after preparation
High Understand the conditions
under which MAA is
likely to act as a good
surrogate based on
tumor type and size
High Conrm catheter
positioning
5.8 Treatment planning strategies / 5.8.1 The empiric model for resin microsphere 97
wholeliver
AA
V
V
=⋅
majority of authors agree that MAA is an excellent option for treatment planning and predictive dosimetry. Substantial additional discussion
related to the use of MAA as a radioembolization
surrogate is presented in Chapter 4.
5.7.2 OTHER TOOLS?
Cone-beam CT (CBCT) is a promising method
of dening three-dimensional vascular anatomy
and elucidating sources of nontarget embolization
(NTE). Louie et al. (2009) evaluated the utility of
CBCT as a tool to augment 99Tc-MAA for the identication of both extrahepatic NTE and poor T:N.
In this study, CBCT was used to identify areas of
extrahepatic localization in 22 out of 42 patients
using CBCT. Perhaps most signicantly, CBCT
identied incomplete tumor visualization in 8 out
of 42 patients, indicating a secondary vascular supply to the tumor (Louie et al., 2009). Cases such as
these are oen a result of so-called “parasitization”
of vascularity, in which the angiogenic factors produced by hypervascular tumors recruit ow from
otherwise insignicant vessels. is phenomenon is
common following one or more chemoembolization
treatments, which preferentially depend on small
vessel embolization to achieve treatment ecacy. If
identied during pretreatment angiography, collateral vessels may be prophylactically embolized, thus
redirecting more vascular ow to the treated vessel
and increasing the likelihood of technical success.
In extreme cases, extrahepatic collateral vessels
may provide the majority of a tumor’s blood supply,
and standard delivery of 90Y microspheres via the
hepatic arteries can result in a T:N less than 1. In
situations such as these, CBCT can be a powerful
tool in treatment planning and delivery.
CBCT has also been investigated as a potential tool in quantifying T:N. A study by Jones and
Mahvash (2012) used gelatin phantoms injected
with dierent concentrations of iodinated contrast
to show that CBCT is able to quantify relative contrast enhancement. Since T:N is a ratio, absolute
quantication is not necessary for its calculation.
In other words, relative densities in tumor and
normal liver in pre- and postcontrast CBCT can
be eectively used to estimate T:N. In this manner, CBCT can be used as an excellent way to aug-
99m
ment
T:N for use in partition model treatment planning.
One must be careful to dierentiate this method
Tc-MAA scintigraphy in the estimation of
from those that allow absolute quantication, such
as 90Y PET/CT. In 90Y PET/CT, following image
acquisition, a region-of-interest drawn in the
tumor will report a value that is directly representative of the activity of 90Y in that region (Pasciak
et al., 2014). ese distinctions are explained in
detail in Chapter 11.
5.8 TREATMENT PLANNING
STRATEGIES
5.8.1 THE EMPIRIC MODEL FOR
RESIN MICROSPHERE
TREATMENT PLANNING
e simplest model for radioembolization treatment planning with resin microspheres is the
empiric model. e empiric model can be used to
determine treatment dosages for whole-liver radioembolization based purely on the percent hepatic
tumor involvement. is model has fallen out of
favor and its clinical use has been largely replaced
by preferred methods such as the body surface area
(BSA) methods and partition models, discussed
in the following sections. However, it should be
noted that the empiric model is still included on
the SIRTeX SIR-Sphere package insert (SIRTeX
Technology Pty, Lane Cove, NSW, Australia). In
addition, the empiric model was the treatment
strategy used during the initial SIRTeX SIR-Sphere
clinical trials.
In the largest single cohort of retrospective data
of patients who underwent radioembolization using
resin microspheres, 28 expired with a cause of death
attributable to complications related to liver toxicity.
Of these deaths, 21 were from a single center that
used the empiric model exclusively for treatment
planning (Kennedy et al., 2009). is does not suggest that the empiric model is unsafe; however; it is
imperative that the model be used correctly.
When using the empiric model, it is critical
to understand that its denition in Table 5.4 is
for whole-liver radioembolization. For lobar or
segmental therapy, one must modify the recommended dosage (A
Equation 5.5:
GBq GBq
() ()
) in Table 5.4 according to
emp
emp
treated
(5.5)
98 Treatment planning part III
20
()
tumornormal
A
VV
+
=⋅
()
49.98(J s)
gl
Table 5.4 Description of the empiric model used
90
for
Y radioembolization with resin
microspheres
The percentage of tumor
involvement in the liver
More than 50% 3.0 GBq
25%–50% 2.5 GBq
Less than 25% 2.0 GBq
where A
is the recommended dosage from the
emp
empiric model as dened in Table 5.4. V
V
are the volumes of the portion of the liver
whole liver
Recommended
dosage, A
emp
treated
(GBq)
and
to be treated and entire liver volume, respectively.
5.8.2 THE BSA MODEL FOR RESIN
MICROSPHERE TREATMENT
PLANNING
e most widely used treatment planning technique for radioembolization with resin microspheres is the BSA method. is method may have
some familiarity to many clinicians since BSAbased calculations are widely used in medicine for
determining dosages for medications such as chemotherapy. Treatment dosage using the BSA model
is strongly dependent on the patient’s height and
weight and moderately dependent on the percent
tumor inltration. Equations 5.6 and 5.7 describe
the BSA treatment planning method:
patients treated with resin microspheres (Kennedy
et al., 2009).
When using the BSA model, it is critical to
understand that its denition in Equations 5.6 and
5.7 is for whole-liver radioembolization. For lobar
or segmental therapy, one must modify the recommended dosage, A
, in Equation 5.7 according to
BSA
Equation 5.8:
V
where A
GBq GBq
AA
() ()
is the recommended dosage from the
BSA
BSA
V
treated
wholeliver
(5.8)
BSA model as dened in Equations 5.6 and 5.7.
V
treated
and V
are the volumes of the portion
whole liver
of the liver to be treated and entire liver volume,
respectively.
5.8.3 GLASS MICROSPHERE
TREATMENT PLANNING
Standard treatment planning for radioembolization using glass microspheres is a relatively
cians signicant latitude to consider patientspecic factors. e foundational principle is
based on Equation 5.3, which describes the
average dose in a tissue volume as a function
of 90Y dosage. Equation 5.3 can be rewritten to
solve for the treatment dosage, Ao, as shown in
Equation5.9:
.725
⋅
Gy (kg)
o
DM
av
=
GBq
A
()
(5.6)
where D
V
tumor
(5.7)
tion of the liver to be treated and M
treated liver tissue. Liver mass is extrapolated from
is the target-absorbed dose in the por-
avg
iver
⋅
is the mass of
liver
(5.9)
BSA(m )0.2025 height m
GBq BSA 0.2
()
BSA
=⋅
0.425
weight (kg)
⋅
=−+
volumetric analysis performed on pretreatment
V
tumor
and V
are the respective volumes of
normal
tumor and uninvolved liver tissue in the portion
of the liver to be treated. e BSA model assumes
a relationship between the physical size of the
patient and ability to tolerate increasing dosage.
e concept that larger patients (not necessarily
with larger livers) are more tolerant to increased
dosages of 90Y has been shown in the literature
(Sangro et al., 2008). e BSA model was also
found to have a lower risk of liver toxicity than the
empiric model in the aforementioned cohort of 680
CT data for planning lobar therapy. In the setting
of radiation segmentectomy, segmental volume
may be calculated by preprocedural cross-sectional
imaging or from CBCT during the pretreatment
mapping procedure, discussed in additional detail
in Chapter 6. Once hepatic volume is obtained, a
conversion factor of 1.05 kg/L is used to convert
hepatic tissue volume to mass (ICRU, 1992).
e average dose endpoint (D
) used in treat-
avg
ment planning is recommended to be in the
range between 80 and 150 Gy as specied in the
5.8 Treatment planning strategies / 5.8.5 Comparing treatment planning models 99
T:N
tumornormal
V
VV
T:N
T:N
tumornormal
V
VV
⋅
()
0n
()
⋅⋅
GBq 49.98 FU
0t
A
() ()
yk
49.98 FU
tumor
DM
erasphere package insert (BTG International
Ltd., London, UK). e endpoint used should be
selected based on tumor burden, health of uninvolved liver tissue, previous therapy, and other
clinical factors that may aect toxicity and/or
response.
Finally, it should be mentioned that Equation
5.9 does not account for lung shunting or residual
activity remaining in the delivery system, both of
which will decrease the dosage of radioactivity
deposited in the liver, Ao, and therefore D
avg
.
5.8.4 THE PARTITION MODEL
e partition model for radioembolization (Ho
et al., 1996, 1997), also referred to as the medical internal radiation dose (MIRD) model (Gulec
et al., 2006), is a three-compartment model that
takes into account patient-specic data to tailor
the desired dosimetric endpoints in the tumor,
normal liver, and lungs. Unlike the previously
discussed models that are specic to resin or glass
microspheres, the partition model can potentially be used for either product. However, one
must always keep in mind that tumor and normal liver dose–response relationships are likely
to vary between resin and glass products due to
variable-specic activity, sphere number/density,
and sphere composition.
e lung SF is an important input into the parti-
tion model that is used along with T:N, tumor volume (V
determine the fractional uptake (FU) into a compartment. Equations 5.10 and 5.11 are the equations for the calculation of FU in the uninvolved
liver and tumor:
e FU can be used to determine the average
absorbed dose in both tumor and normal liver compartments according to Equations 5.12 and 5.13:
), and nontarget liver volume (V
tumor
(1 SF)
=−
normal
(1 SF)
=−
tumor
DGy
()
normal
A
=
normal
⋅+
⋅+
⋅⋅
GBq 49.98 FU
M
normal
tumor
(kg)
normal
(5.10)
(5.11)
ormal
(5.1 2)
) to
D
where A
tumor
is the activity of 90Y to be infused into
o
M
tumor
=
Gy
()
(kg)
umor
(5.13)
the liver. us, Equation 5.13 can be rearranged to
derive the prescribed 90Y dosage in Equation 5.14:
0
G
tumortumor
=
GBq
A
()
⋅
⋅
g
(5.14)
e partition model equation uses patientspecic tumor and liver volumes, along with predetermined T:N from pretreatment
99m
Tc-MAA
SPECT/CT and/or CBCT. us, this method
represents the most tailored treatment planning
algorithm, allowing for accurate estimation of
absorbed dose to tumor, nontarget liver tissue, and
lungs. Prior research has shown that treatment
planning with the partition model based on
99m
TcMAA SPECT/CT can improve clinical outcomes
(Gulec etal.,2006).
As discussed in a previous sec tion, when treating
an HCC patient with radioembolization, one may
wish to set D
to a minimum of 120 Gy. Solving
tumor
for Ao, however, is not the only necessary step in
the treatment plan. A0 must be back-substituted
into Equation 5.11 to ensure that the absorbed dose
to normal liver tissue is below suggested limits.
In addition, the dosimetric techniques described
in chapter 4 should also be applied to ensure an
acceptable lung dose.
It is critical to note that the partition model can be
eectively used for any radioembolization product
including resin or glass 90Y microspheres and
166
Ho
radioembolization. However, tumor and uninvolved
liver ecacy and safety endpoints are likely to dier
between radioembolization products.
5.8.5 COMPARING TREATMENT
PLANNING MODELS
In the previous sections, four treatment planning
models have been introduced for radioembolization
using resin microspheres, glass microspheres, or
both. However, it is dicult to understand simply by
examining the equations how the treatment activity prescribed using these models diers in patients
of varying size, tumor burden, and T:N. Figure 5.5a
compares the recommended dosage of resin microspheres based on the empiric, BSA, and partition
100 Treatment planning part III
4
Dosage (GBq)
4
(a) (b)
3.5
2.5
1.5
0.5
3
2
1
0
0
SIRSphere empirical model
SIRSphere BSA model, female in 10
SIRSphere BSA model, female in 50
SIRSphere BSA model, male in 50
SIRSphere BSA model, male in 90
Partition model, 2:1 T:N, 150 Gy tumor dose
Partition model, 5:1 T:N, 150 Gy tumor dose
10 20 30 40
Percentage tumor burden (%)
th
percentile of height/weight
th
percentile of height/weight
th
percentile of height/weight
th
percentile of height/weight
50 60 70 0
3.5
3
2.5
2
Dosage (GBq)
1.5
1
erasphere 80 Gy treatment endpoint
0.5
0
erasphere 120 Gy treatment endpoint
erasphere 150 Gy treatment endpoint
Partition model, 2:1 T:N, 150 Gy tumor dose
Partition model, 5:1 T:N, 150 Gy tumor dose
10 20 30 40
Percentage tumor burden (%)
50 60 70
Figure 5.5 Prescribed dosage recommendation for (a) resin microspheres and (b) glass microspheres
as a function of patient size, tumor burden, and T:N. Data are presented for a 1300 mL liver. Patient
size data are from published U.S. census demographic information 2007–2008.
models as a function of patient size, tumor burden,
and T:N. One can immediately see that the empiric
model yields a dosage that is higher than most of
than the other since toxicity and ecacy endpoints
dier between the two products. Chapter 9 will
explain this phenomenon at a microscopic level.
the other models, and it does this regardless of circumstance (i.e., varying patient size or liver size).
On the other hand,patient size (height+weight)
has a large impact on the BSA treatment planning
5.9 CONTOURING LIVER AND
TUMOR VOLUMES
model. A female in the 10th percentile of height
and weight will be treated with about half the dosage as a male in the 90th percentile of height and
weight. e partition model with a T:N of 5:1 yields
the lowest dosage at a low percentage tumor inltration but rises steeply as the tumor burden increases.
Use of the partition model with a low T:N (2:1 or
less) can result in a large dosage and the potential
for high absorbed doses to uninvolved liver. Figure
5.5b describes the dosage recommended for glass
treatment planning at 80, 120, and 150 Gy absorbeddose endpoints. Comparing Figure 5.5a with 5.5b,
it is quickly apparent that larger dosages are used
for radioembolization with glass microspheres than
resin microspheres. However, this does not suggest
that one product carries less toxicity or more ecacy
Each of the treatment planning methodologies presented in the previous section require
measurement of tissue volume through some form
of volumetry based on CT, MR, or hybrid (e.g., PET/
CT) tomographic imaging. e empiric and BSA
models are reliant on measurement of the percent
tumor inltration and also the percentage of treated
liver tissue relative to total liver volume. Treatment
planning for glass microspheres depends strongly
on the total volume of liver tissue being treated,
while the partition model relies on both volume of
tumor and uninvolved liver tissue. ese volumes
can be determined using automatic, semiautomatic,
or manual techniques as described in Sections 5.9.1
and 5.9.2.
5.9 Contouring liver and tumor volumes / 5.9.2 Manual segmentation 101
5.9.1 AUTOMATIC AND
SEMIAUTOMATIC
SEGMENTATION
Automatic and semiautomatic organ and tumor
segmentation have been widely used in areas of
health physics, radiation therapy, radiology, surgery,
and other facets of medicine for years with dierent
levels of accuracy and required human input (van
Ginneken and Haar Romeny, 2000; Ghanei et al.,
2001; Marroquín et al., 2002; Caon, 2004; François
et al., 2004; Buie et al., 2007; Fripp et al., 2007; Klein
et al., 2008; Metzger et al., 2013; Kockelkorn et al.,
2014). Techniques such as thresholding and region
growing (El-Baz et al., 2011) can be quite eective
in high-contrast anatomical areas that are clearly
demarcated. ese techniques have even been used
successfully in the semiautomatic segmentation of
the liver based on CT imaging (Foruzan et al., 2009).
In the context of radioembolization treatment
planning, available segmentation tools will dictate
the degree of automation that can be achieved in the
clinical workow. However, some automation can be
achieved in almost every clinical environment without specialized tools. For example, consider patients
with metastatic liver disease who have received a
pretreatment
these patients, manually contouring multiple liver
lesions to determine the percent tumor involvement
can be a time-consuming task. However, determining the tumor burden is a necessary component of
treatment planning for radioembolization using
resin microspheres. Automated 3D thresholding
tools available on basic radiology reading stations
can be used in conjunction with 18FDG-PET/CT to
delineate hypermetabolic tumor boundaries. e
threshold can be adjusted on a per-patient basis or
set quantitatively as a function of maximum standardized uptake value (SUV
is useful for many patients with FDG-avid metastatic liver tumors treated with radioembolization.
An example of thresholding at 40% of whole-liver
SUV
max
If automated segmentation tools are available, atlas-based segmentation (Ghanei et al., 2001;
Bondiau et al., 2005; Zhang et al., 2006; Reed et
al., 2009; Linguraru et al., 2010; El-Baz et al., 2011;
Park et al., 2014) is a method that has the potential
for more accurate organ segmentation and may
require less user input compared to alternatives such
as thresholding and region growing. e degree of
18
FDG-PET/CT exam. In many of
is shown in Figure 5.8b.
). is technique
max
automation of atlas-based segmentation is greater, in
part, because it is reliant on a standard atlas of reference segmented organ contours. ese contours are
predened and validated by radiologists or anatomists. e atlas is then matched to the dataset of
interest using deformable registration. To improve
the accuracy of the process and account for variant
anatomy, multiatlas-based segmentation is oen
employed. In this technique, many deformable registrations are performed with atlases that feature varying anatomy and those producing the best match
are combined or fused together to produce a nal
optimal segmentation. Several fusion methods are
employed with the simplest a majority vote fusion to
more complex techniques that incorporate statistical
models into the fusion process (Wareld et al., 2004).
In the context of radioembolization treatment
planning, automated delineation of lobar or segmental liver volumes can signicantly speed the
planning process. While atlas-based segmentation
usually requires some postsegmentation manual
correction (Figure 5.6), this task can be accomplished much faster than manual segmentation
alone. Small inaccuracies in the measured liver lobe
volume, segment volume, or tumor volume should
be considered in the context of the sensitivity of the
treatment planning model to volume changes discussed in Section 5.8.5 (Figure 5.5).
5.9.2 MANUAL SEGMENTATION
At institutions where radioembolization treatment
planning is not assisted by a radiation oncology
department, sophisticated thresholding and segmentation tools may be unavailable. In these cases, manual seg mentation may be the only option. e authors
of this chapter have found that DICOM viewers that
feature spline-based regions of interest (ROIs) combined with interpolative volumetry can signicantly
reduce the time required for manual liver and tumor
delineation since ROIs need not be drawn on every
slice. e three-dimensional liver volume rendered
in Figure 5.7 was generated with contours on only six
axial CT slices using the free DICOM viewer OsiriX
5.8.2 (Osirix Foundation, Geneva, Switzerland).
Once again, errors in either tumor or lobe delineation resulting from manual contouring with or
without interslice interpolation should be weighed
against the sensitivity of the treatment planning
model as discussed in a Section 5.8.5 (Figure 5.5).
Соседние файлы в папке Библиотека им академика М.И. Перельмана