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242 Quantitative postradioembolization imaging using PET/CT
homemade 2.5-mm-thick copper ring to reduce
bremsstrahlung radiation emerging from a patient
administered with 1.3 GBq of 90Y. Of note, typical administered activities may be in the order of
several GBq, therefore, possible detector saturation
may not be ignored a priori.
Other degrading factors that signicantly contribute randomly are (1) the detection of random
coincidences from two bremsstrahlung photons
emitted simultaneously; (2) detection of coincidences from an annihilation 511 keV photon
and a bremsstrahlung photon emitted simultaneously; and (3) the presence of the naturally occurring isotope
176
Lu within the detection crystals
(i.e., cerium-doped LYSO or cerium-doped LSO)
of PET imaging systems that may generate background count rates. ere is ample evidence in the
literature that bremsstrahlung radiation together
with the LSO background radiation greatly
increases the random fraction in quantitative 90Y
PET imaging.
Lutetium (Lu)-based scintillators such as LSO
and LYSO are widely used in current generation
PET detectors (especially in ToF scanners) due to
their relatively high stopping power for 511 keV
gamma rays, high light yield, and short decay
time. However, 2.6% of naturally occurring Lu is
the isotope
176
Lu (T
∼ 3.6 × 1010 year), a long-lived
1/2
radioactive element undergoing beta decay (maximum energy 596 keV) and three major simultaneous gamma decays at energies 88 keV (15%), 202
keV (78%), and 307 keV (94%) (Browne and Junde,
1998). While the presence of
176
Lu is generally not
an issue with traditional PET radionuclides due to
the high true coincidence count rate (e.g., 18F), this
phenomenon is likely to introduce nonnegligible
random events during 90Y PET acquisition, thereby
aecting system performance.
In a PET detector, the β particles emitted from
Lu-based crystals, given the short range, deliver
most of their energy in the same crystal. On the
other hand, γ-rays can be detected not only in the
same crystal where they are generated but also in
other detector elements. erefore, the background
radiation generated by the radionuclide
176
Lu can
contribute to the amount of random and true coincidences. e most likely event is the detection of
coincidences originating from the detection of the
β− in the crystal in which the
176
Lu decay occurred
and one of the prompt γ-rays in another detector
crystal (Goertzen et al., 2009). As a general rule, in
order to assess the impact of natural
176
Lu radioactivity on the image quality, long acquisition with
no radioactivity present in the eld of view is performed to determine the
176
Lu background count
rate.
One last confounding factor in 90Y PET quantitative imaging is attributable to scatter correction.
At very low counts, PET images are very noisy
and the resulting scatter correction might lead
to heavy under- or overestimation of the scatter
contribution.
To conclude, bremsstrahlung photons and
prompt gammas are likely to result in a very high
random fraction in imaging 90Y on the order of
80% (Willowson et al., 2015) or even higher (Carlier
et al., 2015) compared with a typical FDG scan of
30%–40%. e combination of high random fraction, extremely low true coincidences, and problematic scatter modeling for low counting statistics
results in very noisy true coincidence sinograms.
In addition, a well-known problem in PET imaging is the introduction of a positive bias aer correction for random events (Ahn and Fessler, 2004;
Rahmim et al., 2005; Li and Leahy, 2006). e most
common method of correcting for random coincidences is the real-time or oine subtraction of a
delayed coincidence time window from the prompt
signal. In a scenario with low true coincidences
and high random fraction (as in 90Y PET imaging),
negative sinogram ray-sum values can be produced. ese negative sinogram values are oen
truncated in commercial soware packages before
iterative reconstruction (i.e., become zeroed) thus
introducing a positive bias. is bias does not have
a signicant impact for clinical imaging with 18F,
but may become important in 90Y PET imaging.
is bias was observed by several authors (Tapp
et al., 2014; Carlier et al., 2015) and it is possibly
responsible for hot contrast recovery obtained with
90
Y being inferior to that obtained with 18F.
It is worth mentioning that presently a number
of literature studies provided ample evidence that
neither detector saturation (D’Arienzo et al., 2012;
Bagni et al., 2012; Carlier et al., 2013) nor intrinsic
natural
176
Lu (Carlier et al., 2013) radioactivity represents a major issue in 90Y PET quantication at
activity concentrations commonly encountered in
liver radioembolization. In particular, the presence
of natural
176
Lu radioactivity produces a measurable
but not limiting contribution. Carlier et al. (2013)
suggested that emissions from the radionuclide
11.5 Performance characteristics of PET scanners / 11.5.6 Image reconstruction 243
176
Lu may signicantly contribute to random coincidences when 90Y radioactivity concentration is
below 1 MBq mL−1 in the presence of high tumor to
background activity concentration ratios.
An extensive study on the limitations and
the accuracy achievable under conditions of low
counts and high random fraction can be found in
Carlier et al. (2015).
11.5.6 IMAGE RECONSTRUCTION
Iterative reconstruction has become the standard
for routine clinical PET imaging. However, iterative algorithms are resource intensive, especially
for ToF data, and OSEM algorithms are, therefore,
commonly used to accelerate reconstruction. As a
general rule, the image noise in the reconstructed
images increases as the number of iterations proceeds (Figure 11.6). On the other hand, image
quality is also degraded when OSEM is used with
a large number of subsets. As a consequence, there
is a tradeo between the number of iterations/subsets and reconstructed image quality.
e impact of image reconstruction on 90Y
PET quantication has been widely investigated
by a number of literature studies with varying
reported success. e general consensus is that
the best reconstruction technique will depend on
the scanner and the acquisition modality (ToF
or non-ToF). Both Willowson et al. (2012) and
Carlier et al. (2013) found that one iteration provided the most accurate quantication on a ToF
Siemens BioGraph mCT. On the other hand Bagni
et al. (2012) and D’Arienzo et al. (2012) performed
acquisitions on a BGO GE discovery ST scanner
using two and three iterations, respectively. In
another study van Elmbt et al. (2011) used three
iterations (eight substeps + Gaussian lter) both
on a Philips Gemini Power 16 and a Siemens
Ecat Exact HR, while Lhommel et al. (2009) and
Werner et al. (2010) used two iterations (33 substeps, ToF, RR) and eight iterations (16 substeps)
on a Philips Gemini TF and a Siemens BioGraph
Hi-Rez 16, respectively. A summary of the image
reconstruction parameters obtained in published
literature is given in Table 11.2.
1 iteration, 10 substeps2 iterations, 10 substeps 3 iterations, 10 substeps
4 iteration, 10 substeps5 iterations, 10 substeps 6 iterations, 10 substeps
Figure 11.6 Effect of number of iterations on the NEMA phantom with six llable spherical inserts.
Image noise in the reconstructed images increases as the number of iterations proceeds. Images were
obtained using a BGO GE Discovery ST PET scanner.
244 Quantitative postradioembolization imaging using PET/CT
e major outcome of the QUEST phantom
study is that 90Y imaging capability appears to be
optimal for Siemens systems using two iterations
and 21 subsets with ToF and resolution recovery
(RR) and an all-pass lter. For GE Healthcare
systems, the use of an all-pass lter in conjunction with RR and ToF (2 iterations and 24 substeps) provided the best quantication results.
Regarding non-ToF generation scanners, measures of background provided average deviations to within 1%, 5%, and 2% for GE Healthcare
(all-pass lter, RR + ToF), Philips (4i8s ToF), and
Siemens (2i21s all-pass lter, RR + ToF) ToF systems, respectively.
11.6 PREPARATION OF A
CALIBRATED PHANTOM
90
FOR
As previously mentioned, most qua ntitative imaging studies make use of phantoms and require
very accurate knowledge of both the activity and
the volume of liquid solution inserted into the
phantoms. e general purpose of quantitative
imaging studies with calibrated phantoms is (1)
to assess uncertainties in the imaging process;
(2) to quantify accuracy of correction factors and
reconstruction algorithms; and (3) to evaluate
scanner performance over time. A recent study
(Sunderland et al., 2015) demonstrated that technical error in phantom lling is one of the primary reasons for exclusion of PET/CT scanners
from clinical trials. Section 11.4 was dedicated to
the importance of accurate 90Y activity measurements. Here, we describe further issues that need
to be addressed for an optimal phantom preparation dedicated to quantitative analysis with 90Y
PET.
Adsorption of radionuclides on the inner walls
of plastic phantoms may lead to inhomogeneous
radionuclide distribution that can negatively
aect quantitative imaging studies (Park et al.,
2008). erefore, the preparation of a carrier
solution is recommended. e use of tap water
should be avoided as minerals and other chemical
impurities might stick to the phantom walls or
combine with the radiopharmaceutical changing
the radionuclide distribution. Carrier solutions
Y-PET STUDIES
should always be prepared using laboratory grade
chemicals and puried water. erefore, it is
important to ensure that a favorable chemistry
is used throughout the calibration procedure in
order to have a uniform and stable solution. For
90
Y PET studies, 90YCl3 in an aqueous solution of
0.1 mol dm-3 hydrochloric acid also containing
inactive yttrium at a concentration of about 50 µg
g-1 can be used as a carrier solution. Alternatively,
diethylenetriaminepentaacetic acid (DTPA) or
ethylenediaminetetraacetic acid (EDTA) at a concentration of about 50 µgg-1 can be used to prevent radioactive 90Y from sticking to the phantom
walls and to guarantee a homogeneous radionuclide solution.
It is recommended that all containers be prelled with carrier 12 hours prior to addition of
radioactive 90YCl3. is will help to “seal” the surface and reduce sticking or plating of activity. All
containers should be emptied, dried, and the used
carrier discarded before activity is added.
Activity concentration should be determined
using a radionuclide dose calibrator traceable to
a national standards laboratory for the geometry being measured, as previously discussed.
Uncertainty for a typical well-calibrated eld
instrument can be expected to be in the region of
~5% for low-energy gamma emitters (<100 keV)
and pure beta emitters, such as 90Y. It is worth
noting that if activity is determined by a national
laboratory then this uncertainty can be reduced
signicantly.
As a general rule, preparation of a stock solution is recommended. Radioactive 90Y provided
by a supplier should be diluted using the carrier
solution to desired volume and concentration.
Activity concentration should be determined
by measuring an aliquot of the stock solution in
terms of activity per unit mass (or volume). is
can then be used to determine the activity of all
subsequent sources produced from this stock
solution.
Filling of the phantoms should be performed
using a calibrated (preferably four decimal places)
analytic scientic scale and with routine double or
triple weighing of the sources. e overall uncertainty in the activity concentration determined
using this method is dependent on the precision
of the scale being used as well as the accuracy
of the method used to determine the activity
11.8 Conclusions 245
5
±×
−
concentration of the solution. Radioactivity should
be dispensed using calibrated pipette devices or
syringes and ensuring that no air bubbles remain
in the phantom. Either way, it is suggested to ush
the needle to remove all activity from the syringe
or the pipette. Again the uncertainty is dependent
on the precision of the volume measurement as
well as the activity determined.
If large background volumes are used for calibration purposes, the phantom can be lled with
nonradioactive water to measure the llable volume (and to conrm the phantom is watertight
with no leaks). When lling large phantom volumes, a funnel should be used. When the phantom is nearly full, the funnel can be removed and a
syringe used to complete the lling process thereby
preventing the spillage of radioactive water from
the background compartment.
11.7 DISCUSSION AND
SUMMARY
PET imaging of 90Y microspheres is a rapidly evolving eld whose features and attributes have not yet
been fully addressed. At present, the general consensus is that accurate quantication is possible on
a variety of PET scanner models, with or without
ToF, although ToF is likely to improve the accuracy at lower activity concentrations. Quantitative
accuracy has been investigated by a number of
authors using dierent phantoms with varying
reported success. Regardless of the scanner used,
partial volume eects play a major role in activity
quantication showing a steady decline for spheres
with diameter below 37 mm. It is expected that
quantication in small hot regions may be underestimated with all current generation scanners to a
consistent degree of 15%–20% for a 37-mm-diameter object (Willowson et al., 2015). Higher quantication accuracy can be achieved for large regions
uniformly lled with 90Y. Non-ToF generation GE
Healthcare and Siemens scanners are capable of
recovering activity concentrations on the order of
300 kBq/mL within 2% and 9% of true values, while
the deviation for ToF GE Healthcare and Siemens
scanners can be expected to be in the range 1%–5%
(Willowson et al., 2015). Furthermore, the recovery
of activity concentration in hot spheres is inferior
to that obtained with 18F, probably due to eects
of image noise on the OSEM reconstruction algorithms, which present an inherent nonnegativity
constraint. While the intrinsic radioactivity present in lutetium-based crystals is a potential limitation, it has been shown to have a negligible impact
at the high activity concentrations typically found
in 90Y radioembolization.
Regarding the acquisition time, a 40-minute
acquisition is recommended in a clinical scenario,
acquired as two bed positions, 20 minutes each.
Figure 11.7 shows dierent acquisitions performed
with a GE Discovery ST BGO scanner 2 hours aer
the microsphere administration (single bed acquisition, 20 minutes). An excellent match between
microsphere accumulation and tumor areas was
observed.
Last, the accuracy of quantitative 90Y PET/CT
imaging is strongly related to the measurement
precision of the internal pair production branching ratio. At present, the β+ emission probability of 90Y is known with an uncertainty around
1.5% (
; Selwyn et al., 2007). A
reduction of such uncertainty will lead to a reduction of the overall uncertainty in the activity quantication. is is especially important in light of
the current uncertainty in the clinical measurement of 90Y activity using a dose calibrator. In the
near future, new experimental measurements of
the internal pair production branching ratio are
desirable in order to achieve more accurate quantication in postradioembolization imaging using
PET/CT.
11.8 CONCLUSIONS
Currently, a number of clinics have developed their
own quantitative imaging procedures using 90Y PET/
CT. Very oen there is a lack of harmonization of
these procedures, most likely because quantitative
imaging with 90Y PET/CT is a relatively new imaging
strategy and further because imaging capabilities
are strongly related to PET scanner performance.
Ultimately, it is worth stressing that scanner performance is optimized for 18F imaging and dedicated
imaging protocols are required for accurate 90Y
PET/CT studies. Careful choice of reconstruction
246 Quantitative postradioembolization imaging using PET/CT
(a)
(b)
(c)
Figure 11.7 Clinical examples of postradioembolization imaging using 90Y-PET showing an excel-
lent match between microsphere accumulation on hepatic lesions. (Left) 90Y-PET fused with CT data.
(Central) CT of the liver parenchyma clearly showing tumor regions. (Right) 90Y-PET. Figure parts (a)
through (c) show different axial levels of the same patient.
parameters has the potential to increase the quantitative accuracy. However, the nal outcome will
depend on the scanner and reconstruction soware.
Comprehensive guidance has yet to be presented in this eld and there is no doubt that an
internationally endorsed protocol on the 90Y PET/
References 247
CT quantitative imaging would lead to further
advances in this area.
REFERENCES
AAPM Task Group 181. (2012). The selection, use,
calibration, and quality assurance of radionuclide calibrators used in nuclear medicine
report of AAPM Task Group 181. College
Park, MD: American Association of Physicists
in Medicine.
Ahn, S., Fessler, J.A. (2004). Emission image
reconstruction for randoms-precorrected PET
allowing negative sinogram values. IEEE Trans
Med Imaging 23:591– 601.
Attarwala, A. et al. (2014). Quantitative and
qualitative assessment of yttrium-90 PET/CT
imaging. PLoS One 9:e110401.
Bagni, O. et al. (2012). 90Y-PET for the assess-
ment of microsphere biodistribution after
selective internal radiotherapy. Nucl Med
Commun 33:198– 204.
Bé, M. et al. (2006). Table of radionuclides.
Monographie BIPM-5. Sèvres, Paris: Bureau
International des Poids et Mesures, ISBN
92-822-2218-7.
Browne, E., Junde H. (1998). Nuclear data
sheets for A = 176. Nucl Data Sheets
1998;84:337–486.
Carlier, T. et al. (2013). Assessment of acquisition
protocols for routine imaging of Y-90 using
PE T/CT. EJNMMI Res 3:11.
Carlier, T., Willowson, K., Fourkal, E., Bailey, D.,
Doss, M., Conti, M. (2015).
Exploring limitations and accuracy under
conditions of low counts and high random
fraction. Med Phys 42:4295–4309.
Cherry, S., Sorenson, J., Phelps, M. (2012).
Physics in Nuclear Medicine. Philadelphia, PA:
Elsevier/Saunders.
Conti, M. (2009). State of the art and challenges
of time-of-ight PET. Phys Med 25:1 –11.
Conti, M., Eriksson, L., Rothfuss, H., Melcher,
C. (2009). Comparison of fast scintillators
with TOF PET potential. IEEE Trans Nucl Sci
56:926–933.
D’Arienzo, M. (2013). Emission of β
internal pair production in the 0
90
tion of
Zr: Historical background and current
applications. Nucl Med Imaging Atoms 1:2–12.
90
Y-PET imaging:
+
particles via
+–0+
transi-
D’Arienzo, M. et al. (2012).
90
Y PET-based dosimetry after selective internal radiotherapy
treatments. Nucl Med Commun 33:633–640.
D’Arienzo, M. et al. (2013). Absorbed dose to
lesion and clinical outcome after liver radioembolization with 90Y microspheres: A case
report of PET-based dosimetry. Ann Nucl
Med 27:676–680.
Daube-Witherspoon, M.E. et al. (2002). PET
performance measures using the NEMA NU
2-2001 standard. J Nucl Med 43:1398–1409.
Dezarn, W. et al. (2011). Recommendations of
the American Association of Physicists in
Medicine on dosimetry, imaging, and quality
assurance procedures for
90
Y microsphere
brachytherapy in the treatment of hepatic
malignancies. Med Phys 38:4824–4845.
Dezarn, W., Kennedy, A. (2007a). SU-FF-T-380:
Signicant differences exist across institutions in 90Y activities compared to reference
standard. Med Phys 34:2489.
Dezarn, W., Kennedy, A. (2007b). Resin
90
Y
microsphere activity measurements for liver
brachytherapy. Med Phys 34:1896 –1900.
Elschot, M. et al. (2013). Quantitative compari-
son of PET and bremsstrahlung SPECT for
imaging the in vivo yttrium-90 microsphere
distribution after liver radioembolization.
PLoS One 8:e55742.
Fenwick, A., Baker, M., Ferreira, K., Keightley, J.
(2014). Comparison of Y-90 measurements
in UK hospitals. NPL Report IR 20. United
Kingdom: National Physics Laboratory.
Ferreira, K., Fenwick, A., Arinc, A., Johansson,
L. (2016). Standardisation of 90Y and determination of calibration factors for 90Y
microspheres (resin) for the NPL secondary
ionisation chamber and a Capintec CRC-25R.
Appl Radiat Isotopes 109:226–230.
Ford, K. (1955). Predicted 0
+
level of Zr90. Phys
Rev 98:1516–1517.
Fourkal, E. et al. (2013). 3D inpatient dose
reconstruction from the PET-CT imaging
90
of
Y microspheres for metastatic cancer
to the liver: Feasibility study. Med Phys
40:081702.
Fowler, K. et al. (2016). PET/MRI of hepatic 90Y
microsphere deposition determines individual tumor response. Cardiovasc Intervent
Radiol 39:855–864.
248 Quantitative postradioembolization imaging using PET/CT
Gadd, R. et al. (2006). Protocol for establishing
and maintaining the calibration of medical
radionuclide calibrators and their quality
control. Measurement Good Practice Guide
No. 93. Teddington, Middlesex, UK: National
Physical Laboratory.
Gates, V. et al. (2010). Internal pair production
90
of
Y permits hepatic localization of microspheres using routine PET: Proof of concept.
J Nucl Med 52:72–76.
Goertzen, A., Stout, D., Thompson, C. (2009). A
method for measuring the energy spectrum
of coincidence events in positron emission
tomography. Phys Med Biol 55:535–549.
Greenberg, J.S., Deutsch, M. (1956). Positrons
from the decay of P
32
and Y90. Phys Rev
102:415 – 421.
IAEA. (1996). International basic safety standards
for protection against ionizing radiation and for
the safety of radiation sources. International
Atomic Energy Agency, Vienna, Austria.
Johnson, O., Johnson, R., Langer, L. (1955).
Evidence for a 0
+
rst excited state in Zr90.
Phys Rev 98:1517–1518.
Kao, Y. et al. (2013). Post-radioembolization
yttrium-90 PET/CT—Part 2: Dose-response
and tumor predictive dosimetry for resin
microspheres. EJNMMI Res 3 :57.
Kao, Y. et al. (2012). Yttrium-90 internal pair
production imaging using rst generation
PET/CT provides high-resolution images for
qualitative diagnostic purposes. Br J Radiol
85:1018–1019.
Kossert, K. et al. (2016). Comparison of 90Y
activity measurements in nuclear medicine in
Germany. Appl Radiat Isot 109:247–249.
Langhoff, H., Hennies, H. (1961). Zum experimen-
tellen Nachweis von Zweiquantenzerfall beim
+–0+
0
Ubergang des Zr90. Z Phys 164:166–173.
Lewellen, T. (1998). Time-of-ight PET. Semin
Nucl Med 28:268–275.
Lhommel, R., Goffette, P., Van den Eynde, M.,
Jamar, F., Pauwels, S., Bilbao, J., Walrand,
S. (2009). Yttrium-90 TOF PET scan demonstrates high-resolution biodistribution
after liver SIRT. Eur J Nucl Med Mol Imaging
36:1696–1696.
Lhommel, R. et al. (2010). Feasibility of
90
YTOF
PET-based dosimetry in liver metastasis
therapy using SIR-spheres. Eur J Nucl Med
Mol Imaging 37:1654–1662.
Li, Q., Leahy, R.M. (2006). Statistical model-
ing and reconstruction of randoms precorrected PET data. IEEE Trans Med Imaging
25:1565 –1572.
Lourenço, V. et al. (2015). Primary standardization
of SIR-Spheres based on the dissolution of the
90Y-labeled resin microspheres. Appl Radiat
Isot 97:170–176.
Martí-Climent, J. et al. (2014). PET optimiza-
tion for improved assessment and accurate
quantication of
90
Y-microsphere biodistribution after radioembolization. Med Phys
41:092503.
Mo, L. et al. (2005). Development of activity
standard for 90Y microspheres. Appl Radiat
Isot 63:193–199.
National Electrical Manufacturers Association.
(2007). NEMA NU 2-2007 Performance
Measurements of Positron Emission
Tomographs Arlington, VA: NEMA.
Ng, S.C. et al. (2013). Patient dosimetry for
90
Y
selective internal radiation treatment based
on 90Y PET imaging. J Appl Clin Med Phys
14:212–221.
Nickles, R.J. et al. (2004). Assaying and PET
imaging of yttrium-90: 1>>34 ppm>0. IEEE
Nucl Sci Symp Rec 6:3412–3414.
Okuda, K. et al. (1985). Natural history of hepa-
tocellular carcinoma and prognosis in relation
to treatment study of 850 patients. Cancer
56:918–928.
Park, M., Mahmood, A., Zimmerman, R.,
Limpa-Amara, N., Makrigiorgos, G., Moore,
S. (2008). Adsorption of metallic radionuclides on plastic phantom walls. Med Phys
35:1606.
Pasciak, A., Bourgeois, A., Bradley, Y. (2014a).
A comparison of techniques for 90Y PET/CT
image-based dosimetry following radioembolization with resin microspheres. Front
Oncol 4:121.
Pasciak, A. et al. (2014b). Radioembolization and
the dynamic role of
90
Y PET/CT. Front Oncol
4:38.
Peller, P., Subramaniam, R., Guermazi, A. (2012).
PET-CT and PET-MRI in Oncology. Berlin:
Springer.
Rahmim, A. et al. (2005). Statistical dynamic
image reconstruction in state-of-the-art
high resolution PET. Phys Med Biol
50:4887– 4912.
References 249
Selwyn, R. et al. (2007). A new internal pair pro-
duction branching ratio of
ment of a non-destructive assay for
90
Sr. Appl Radiat Isot 65:318–327.
90
Y: The develop-
90
Y and
Stabin, M.G., Eckerman, K.F., Ryman, J.C.,
Williams, L.E. (1994). Bremsstrahlung radiation dose in yttrium-90 therapy applications.
J Nucl Med 35:1377–1380.
Sunderland, J., Christian, P., Kiss, T. (2015). PET/
CT scanner validation for clinical trials-reasons
for failure, recipes for success: The Clinical
Trials Network (CTN) experience. J Nucl Med
56(3 ):1737.
Surti, S. (2014). Update on time-of-ight PET
imaging. J Nucl Med 56:98–105.
Surti, S., Karp, J. (2016). Advances in time-of-
ight PET. Phys Med 32:12–22. doi: 10.1016/j.
ejmp. 2 015 .12.0 0 7.
Tapp, K. et al. (2014). The impact of image recon-
struction bias on PET/CT 90Y dosimetry after
radioembolization. J Nucl Med 55:1452–1458.
Thiam, C., Bobin, C., Lourenço, V., Chisté, V.,
Amiot, M., Mougeot, X., Lacour, D., Rigoulay,
F., Ferreux, L. (2016). Investigation of the
response variability of ionization chambers for
the standard transfer of SIR-Spheres®. Appl
Radiat Isotopes 109:231–235.
van Elmbt, L. et al. (2011). Comparison of
yttrium-90 quantitative imaging by TOF and
non-TOF PET in a phantom of liver selective internal radiotherapy. Phys Med Biol
56:6759–6777.
Walrand, S. et al. (2015). The impact of image
reconstruction bias on PET/CT
90
Y dosimetry after radioembolization. J Nucl Med
56:494–495.
Wissmeyer, M. et al. (2011).
90
Y time-of-ight
PET/MR on a hybrid scanner following liver
radioembolisation (SIRT). Eur J Nucl Med Mol
Imaging 38:1744 –1745.
Werner, M. et al. (2009). PET/CT for the assess-
ment and quantication of 90Y biodistribution
after selective internal radiotherapy (SIRT) of
liver metastases. Eur J Nucl Med Mol Imaging
37:407–408.
Werner, M. et al. (2010). PET/CT for the detection
and quantication of the β-emitting therapeutic radionuclide yttrium-90 after liver SIRT
[abstract]. J Nucl Med 51(Suppl 2):341.
Willowson, K. et al. (2012). Quantitative
90
Y
image reconstruction in PET. Med Phys
39:7153.
Willowson, K., Tapner, M., Bailey, D. (2015). A
multicentre comparison of quantitative 90Y
PET/CT for dosimetric purposes after radioembolization with resin microspheres. Eur J
Nucl Med Mol Imaging, 42:1202–1222.
Woods, M. et al. (1996). Calibration of the NPL
secondary standard radionuclide calibrator
for 32P, 89Sr and
90
Y. Nucl Instrum Methods
Phys Res A 369:698–702.
Zimmerman, B., Ratel, G. (2005). Report of
the CIPM key comparison CCRI(II)-K2Y-90.
Metrologia 42:06001.
12
Image-based three-dimensional
dosimetry following radioembolization
ALEXANDER S. PASCIAK AND S. CHEENU KAPPADATH
12.1 Introduction 251
12.2 Fully 3D Monte Carlo transport for
image-based hepatic dosimetry 252
12.3 Dose-point kernel convolution for
image-based hepatic dosimetry 253
12.4 The voxel S-value MIRD approach for
image-based hepatic dosimetry 254
12.1 INTRODUCTION
e general dosimetric principles of 90Y radioembolization have been discussed in detail
in several chapters in this book. For example,
Chapter 5 discusses a commonly used formula
that allows for the calculation of the absorbed
dose to a volume of tissue given a uniform distribution of 90Y activity. While this is useful for
determining the average absorbed dose to the
liver, lobe, or segment treated, it is of limited
use in the estimation of biological eect. More
accurate methods for determining absorbed dose
have been suggested such as the partition model,
discussed in Chapters 4 and 5. However, the partition model cannot account for inhomogeneity
of microsphere distribution in tumor or normal
liver. Determining the absorbed dose following
90
Y radioembolization in all areas of the tumor,
uninvolved liver, and extrahepatic tissues is a
critical future component of managing patient
12.5 LDM for image-based epatic dosimetry 255
12.5.1 Validation of the LDM 256
12.5.2 LDM and alternative
radionuclides 258
12.6 Instances where DPK convolution and
LDM may not be appropriate 259
12.7 Conclusion 260
References 260
follow-up. For example, if radiation dose and,
therefore, toxicity to normal or extrahepatic
tissues can be determined immediately following radioembolization, prompt administration
of prophylaxis can be considered which may
decrease the severity of side eects. Furthermore,
undertreated areas of tumor could be identied
and alternative or adjuvant therapies could be
prescribed, increasing the potential ecacy of
90
Y radioembolization in some patients.
e ability to utilize posttreatment dosimetry
in the aforementioned manner depends on the
availability of several important pieces of data.
First, one must understand the radiation biology
and dose–response properties of the normal liver
andthe tumor, which may vary substantially with
tumor size, type, and other factors. e radiation
biology of radioembolization at a macroscopic and
a microscopic level has been discussed in Chapters
8 and 9, respectively. However, there are still many
unknowns yet to be addressed. Once the radiation
biology is understood for a patient with a given
251
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