- Original research
- Open Access
Yttrium-90-labeled microsphere tracking during liver selective internal radiotherapy by bremsstrahlung pinhole SPECT: feasibility study and evaluation in an abdominal phantom
- Stephan Walrand^{1}Email author,
- Michel Hesse^{2},
- Georges Demonceau^{2},
- Stanislas Pauwels^{1} and
- François Jamar^{1}
https://doi.org/10.1186/2191-219X-1-32
© Walrand et al; licensee Springer. 2011
- Received: 31 August 2011
- Accepted: 2 December 2011
- Published: 2 December 2011
Abstract
Background
The purpose of the study is to evaluate whether a pinhole collimator is better adapted to bremsstrahlung single photon emission computed tomography [SPECT] than parallel-hole collimators and in the affirmative, to evaluate whether pinhole bremsstrahlung SPECT, including a simple model of the scatter inside the patient, could provide a fast dosimetry assessment in liver selective internal radiotherapy [SIRT].
Materials and methods
Bremsstrahlung SPECT of an abdominal-shaped phantom including one cold and five hot spheres was performed using two long-bore parallel-hole collimators: a medium-energy general-purpose [MEGP] and a high-energy general-purpose [HEGP], and also using a medium-energy pinhole [MEPH] collimator. In addition, ten helical MEPH SPECTs (acquisition time 3.6 min) of a realistic liver-SIRT phantom were also acquired.
Results
Without scatter correction for SPECT, MEPH SPECT provided a significantly better contrast recovery coefficient [CRC] than MEGP and HEGP SPECTs. The CRCs obtained with MEPH SPECT were still improved with the scatter correction and became comparable to those obtained with positron-emission tomography [PET] for the 36-, 30- (cold), 28-, and 24-mm-diameter spheres: CRC = 1.09, 0.59, 0.91, and 0.69, respectively, for SPECT and CRC = 1.07, 0.56, 0.84, and 0.63, respectively, for PET. However, MEPH SPECT gave the best CRC for the 19-mm-diameter sphere: CRC = 0.56 for SPECT and CRC = 0.01 for PET. The 3.6-min helical MEPH SPECT provided accurate and reproducible activity estimation for the liver-SIRT phantom: relative deviation = 10 ± 1%.
Conclusion
Bremsstrahlung SPECT using a pinhole collimator provided a better CRC than those obtained with parallel-hole collimators. The different designs and the better attenuating material used for the collimation (tungsten instead of lead) explain this result. Further, the addition of an analytical modeling of the scattering inside the phantom resulted in an almost fully recovered contrast. This fills the gap between the performance of^{90}Y-PET and bremsstrahlung pinhole SPECT which is a more affordable technique and could even be used during the catheterization procedure in order to optimize the^{90}Y activity to inject.
Keywords
- bremsstrahlung
- pinhole
- SPECT
- SIRT
- yttrium-90
- microsphere
- dosimetry
Background
A selective internal radiation therapy [SIRT] using^{90}Y-labeled microspheres is a rapidly emerging treatment of unresectable, chemorefractory primary and metastatic liver tumors. The success of such therapeutic approach depends on (1) the expertise of the interventional radiologist to selectively catheterize the appropriate branch of artery, (2) the selection of patients with limited tumor burden, and (3) the determination of the maximal activity which can be safely injected to the patient. This determination is not achievable by angiography and is usually performed using empirical formulas, such as the partition model [1]. Pre-therapy single photon emission computed tomography [SPECT] using^{99m}Tc-labeled macroaggregates [^{99m}Tc-MAA] is mainly intended to rule out patients who display a liver-to-lung shunt in excess of 20% [1, 2]. Even if^{99m}Tc-MAA SPECT shows some usefulness in simulating the liver-SIRT procedure [3–5],^{90}Y-microspheres differ from^{99m}Tc-MAA by the higher number of particles injected during the therapeutic procedure, which could lead to a more pronounced embolic effect [6]. Imaging the actual^{90}Y-microsphere deposition during the liver SIRT appears thus preferable.
Gupta et al. [7] showed the feasibility of iron-labeled microsphere tracking during transcatheter delivery in rabbit liver by magnetic resonance [MR] imaging. In this paper, cosigned by R. Salem, the authors concluded: 'Although quantitative in vivo estimation of microsphere biodistribution may prove technically challenging, the clinical effect could be enormous, thus permitting dose optimization to maximize tumor kill while limiting toxic effects on normal liver tissues.' However, human liver SIRT appears quite incompatible with MR: the X-ray angiographic imager will difficultly be implemented around the MR table, and the long duration of liver SIRT, which can take hours when the arterial tree is challenging, can unlikely be fitted into clinical MR agenda.
Several methods are already clinically used to assess the microsphere deposition after SIRT and check that the procedure has been performed as expected. Conventional bremsstrahlung imaging is already widely used in order to qualitatively assess biodistribution after^{90}Y liver SIRT [8–17]. However, in the absence of a photopeak, SPECT imaging of^{90}Y is dependent on the continuous bremsstrahlung X-rays. Although numerous correction methods have been proposed for parallel-hole collimator bremsstrahlung SPECT, the reached accuracy is still insufficient to safely determine the maximal activity to inject in each patient (see Walrand et al. [18] for an extensive review of the correction methods and applications).
More recently, the development of^{90}Y-positron-emission tomography [PET] imaging [19–23] offers the unique opportunity to easily assess the actual absorbed dose delivered in^{90}Y SIRT. Early human data have already provided a promising relationship between tumor dose and cell survival fraction [18, 22]. However, the very low positron abundance (32 out of a million decays) required the use of long acquisition times (> 30 min).
To the best of our knowledge, bremsstrahlung SPECT using a pinhole collimator was never investigated for a human-directed application. This likely results from the fact that a pinhole collimator has a small field of view [FOV] and thus, for the imaging of large organs, results in lower SPECT performances compared with those obtained using parallel-hole collimators. However, in bremsstrahlung SPECT, the different designs (the pinhole collimator is almost an empty volume where high-energy X-rays cannot scatter down into the acquisition energy window) and the better attenuating material used for the collimation (tungsten rather than lead) could result in better bremsstrahlung SPECT performances using the pinhole collimator.
The purpose of the study is to evaluate whether a pinhole collimator is better adapted to bremsstrahlung SPECT than parallel-hole collimators and in the affirmative, to evaluate whether pinhole bremsstrahlung SPECT, including a simple previously published model of the scatter inside the patient [24, 25], could provide a fast dosimetry assessment in liver SIRT. For comparison, a^{90}Y time-of-flight [TOF]-PET acquisition was also acquired.
Materials and methods
Sphere phantom acquisitions
Collimator comparison
Pinhole SPECT with scatter modeling
To assess the 'intrinsic' CRC that can be reached by pinhole SPECT, i.e., not corrupted by the physical effects occurring in the emission medium, the continuous energy X-ray scattering in the phantom was modeled using an adapted version of a previously proposed analytical model [24, 25].
where $\oint $ is the linear integration of the effective attenuation coefficient $\stackrel{\wedge}{\mu}\left(\overrightarrow{y}\right)$ along the straight line from the point $\overrightarrow{X}$ to the scattering point $\overrightarrow{x}$, and $\rho \left(\overrightarrow{x}\right)$ is the density at the point $\overrightarrow{x}$ (zero in air). In liver SIRT, the attenuation is almost homogeneous, and the linear integration $\oint $ in Equation 1 reduces to $\stackrel{\wedge}{\mu}\mid \overrightarrow{x}-\overrightarrow{X}\mid $. Using fast Fourier transform, the additional convolution in Equation 1 did not increase the computation time per iteration.
The effective attenuation coefficient $\stackrel{\wedge}{\mu}$ was obtained by fitting the scatter profile along a tank filled with water and placed on a MEGP collimator, with a^{90}Y point source placed on one side of the tank (see Appendix 1). The scatter fraction α was obtained from a pinhole SPECT of a 20-cm-diameter Perspex cylinder (Philips Medical Systems) centered in the FOV, filled with water and containing an off-centered^{90}Y point source. The scatter fraction α was fitted to obtain the best agreement between the computed projections of this cylindrical phantom using Equation 1 and the measured planar views. As the scattering is now accounted for, the attenuation coefficient μ in Equation 1 is now the total attenuation coefficient and was set to the water attenuation coefficient at the middle of the energy acquisition window (μ = 0.17 cm^{-1}), both in the scatter modeling procedure and in the phantom pinhole SPECT reconstruction. The projection used in the collimator comparison corresponds to Equation 1 with α = 0 and μ = 0.13 cm^{-1}.
Quantitative assessment
where C^{meas} and C^{true} are the measured and true spheres to background specific activity ratios, respectively. The measured specific activity of a sphere was the mean specific activity obtained in a spherical volume of interest [VOI] centered on the sphere and having the actual diameter of the sphere. The background specific activity was the mean specific activity in the phantom voxels outside these sphere VOIs. The CRC is equal to 1 for an ideal reconstruction for both cold and hot spheres.
Liver-SIRT phantom acquisition
Abdominal phantom compartment activities assessed by the MEPH with scatter correction [MEPH-SCAT] SPECT
True | 3.6-min Acquisition time | 1-min Acquisition time | |||||
---|---|---|---|---|---|---|---|
Volume (ml) | RSA | % of 1.4 GBq | % of 1.4 GBq | RD (%) | % of 1.4 GBq | RD (%) | |
Core | 13 | 0 | 0 | 1.14 ± 0.13 | NA | 1.20 ± 0.17 | NA |
Shell | 52 | 4 | 27.31 | 20.79 ± 0.35 | -24 | 20.42 ± 0.59 | -25 |
Isolated tumor | 13 | 4 | 5.46 | 4.34 ± 0.10 | -21 | 4.32 ± 0.27 | -21 |
Healthy liver 1 | 34 | 1 | 3.73 | 3.22 ± 0.15 | -14 | 3.26 ± 0.18 | -13 |
Healthy liver 2 | 58 | 0.25 | 1.60 | 2.46 ± 0.59 | 54 | 2.12 ± 0.20 | 32 |
Healthy liver 3 | 58 | 0.5 | 3.20 | 4.03 ± 0.26 | 26 | 4.11 ± 0.31 | 28 |
Healthy liver 4 | 58 | 0.5 | 3.20 | 4.25 ± 0.59 | 33 | 4.33 ± 0.40 | 35 |
Total healthy liver | 709 | NA | 67.23 | 73.73 ± 0.41 | 10 | 74.06 ± 0.57 | 10 |
The 3.6-min helical SPECTs were reconstructed with OSEM (70 iterations × 8 subsets) including the analytical scatter model. The tumor and liver VOIs were drawn on a CT scan of the phantom, and the position of the set of VOIs was afterward tuned on the SPECT images (Figure 5). In liver SIRT, it can be approximated that the whole injected activity indefinitely remains in the liver and lungs and thus can be entirely imaged. As a result, the percentage of activity taken up by the different compartments was obtained by computing the ratio of the counts in the compartment VOI with the total count in the image. After time integration of the physical decay and summation-multiplication by the S factors between the different compartments, this determines the tissue dosimetry expressed in milligrays per megabecquerel [mGy/MBq] [30]. These S factors can be computed for each target ← source compartment by convolving a three-dimensional [3-D] mask of the source compartment VOI with a dose deposition kernel [31]. After analyzing the data, it was noted that the reproducibility of the 3.6-min acquisition time helical pinhole SPECTs was sufficiently good to expect useable results using shorter acquisition times, so we decided to generate pseudo 1-min helical SPECTs by keeping only the odd pixel in the two directions of the acquisition matrix (one pixel on four).
Results
Collimator comparison
CRC of the hot and cold sphere phantoms
Diameter (mm) (act sph/bg) | 30 (0) | 19 (3.5) | 24 (3.5) | 28 (3.5) | 36 (3.5) | 36 (7) |
---|---|---|---|---|---|---|
TOF-PET^{a} | 0.56 | 0.01 | 0.63 | 0.84 | 1.10 | 1.07 |
MEPH-SCAT SPECT^{a} | 0.59 | 0.56 | 0.69 | 0.91 | 1.03 | 1.09 |
MEPH-SPECT^{a} | 0.32 | 0.33 | 0.39 | 0.52 | 0.60 | 0.60 |
HEGP-SPECT^{a} | 0.01 | 0.13 | 0.06 | 0.23 | 0.38 | 0.39 |
MEGP-SPECT^{a} | 0.01 | 0.12 | 0.06 | 0.22 | 0.36 | 0.37 |
Pinhole SPECT with scatter modeling
The values obtained for the scattering modeling in Equation 1 were α = 1.97 × 10^{-4} and $\stackrel{\wedge}{\mu}$ = 0.0697 cm^{-1}. Using the scattering analytical model, MEPH provided similar results as those of the TOF-PET (Table 2), but with the need to perform significantly more iterations (see Appendix 2 about the CRC convergence rate). Table 1 and Figure 5 show the results obtained with the helical MEPH SPECT for the liver-SIRT phantom reconstructed with 70 iterations (eight subsets).
Discussion
This study demonstrates the better hardware properties of a pinhole collimation (MEPH) for bremsstrahlung SPECT imaging. Further, the adaptation of a previously described analytical modeling of the scattering inside the patient leads to contrast recovery very close to those obtained with^{90}Y-PET.
The better CRC obtained by MEPH compared with MEGP or HEGP collimators resulted from the reduced high-energy X-ray penetration in the tungsten insert of the pinhole compared to that of the lead septa of the parallel-hole collimators. Also, the pinhole collimator is almost an empty volume reducing the amount of high-energy X-rays scattering down into the acquisition energy window (Figure 3B) compared to parallel-hole collimators (Figure 3A). These features made the improvement especially noticeable for the cold sphere and the three smallest hot spheres (Table 2, Figure 2).
Using a simple analytical scatter model in the phantom, MEPH SPECT provides similar results than those of TOF-PET (Table 2, Figure 2), although TOF-PET is free of these collimator penetration-scatter and also of camera backscatter drawbacks. The results are even better for the smallest sphere that is hampered by the higher noise obtained in PET reconstruction as shown in Figure 1.
The analytical modeling of the scatter was derived from phantoms having different geometries, sizes, and distribution activities than those of the spheres and of the liver-SIRT phantom. This assures that the model can be applied to various patient corpulences. Also, the fact that the cold sphere CRC at the end converged to the same value than that of the hot sphere having the same diameter (see Appendix 2) proved that the background activity is well reproduced and that the analytical model does not underestimate or overestimate the scatter contribution. Furthermore, this model does not increase the computation time per iteration. Nevertheless, as the goal is to determine which maximal activity is still safe for the liver during the liver SIRT within a few minutes, it is of prime importance to further validate in patients the proposed method before its utilization in optimizing the injected activity. This validation could be performed by comparing the results with those obtained using a long-acquisition time PET (preferably TOF-PET) soon performed after the radioembolization.
The pinhole collimator used in our study was not designed for bremsstrahlung SPECT, and several features can still be improved. A gold or iridium insert and thicker pinhole lead walls can still reduce the contamination due to the penetration of the high-energy X-rays. The design of the collimator housing itself can be improved. Indeed, in conical housing pinhole, there is a possibility for the high-energy X-rays to pass through the aperture or through the nose of the aperture and then, to scatter on the pinhole inner lead walls down to an energy inside the acquisition energy window (Figure 3B, 4). Contrary to the parallel-hole collimator, these scatterings mainly occur from X-rays emitted in areas not geometrically seen by the crystal. Making the collimator housing cylindrical rather than conical, the insert will be inside a thick lead plate parallel to the crystal, and the scattering by the inner wall will be removed (Figure 3C). This housing shape will also have the benefit of removing the risk of hurting the patient.
Besides the optimization for bremsstrahlung imaging, the pinhole collimator should also be optimized to large-organ SPECT. This can be done by decreasing the focal length in order to increase the transverse FOV at a short distance to the aperture using the whole crystal surface (the MEPH collimator of the present study used only three-fourths of the crystal diameter). Multiple pinhole collimators should also be better adapted. Lastly, the aperture size and energy window should be optimized in relation with collimator effects modeling in the reconstruction process.
However, even with this suboptimal pinhole collimator, the results obtained for the liver-SIRT phantom showed that a 3.6-min helical MEPH SPECT with 70 iterations (eight subsets) is sufficient to obtain an accurate (relative deviation 10%) and reproducible (standard deviation [SD]/mean < 1%) estimation of the healthy liver activity that determines the maximal safe activity which can be injected (Table 1). The percentage of uptake in the different compartments was estimated versus the whole activity measured in the reconstruction. Thus, the computation of the compartment absorbed doses will require an accurate measure of the total delivered activity. Especially, the catheter and microsphere vial will have to be imaged or counted after the radioembolization.
Rather than to estimate the mean liver absorbed dose by multiplying the percentage taken up by the liver region reached by the microspheres with the S factor of this region, a voxel-based dosimetry could be obtained by convolving the reconstructed^{90}Y distribution with a dose deposition kernel [18, 20]. This will allow computation of the normal tissue complication probability using the equivalent uniform dose in order to take into account the liver irradiation heterogeneity. This can be done using Niemerko's model [32] and the normal tissue tolerance determined by Emami et al. [33]. The software performing this computation is already available [34], and recently, an improvement of Niemerko's model was proposed [35].
Using four commercial 4 × 8-core Xeon (Intel Corporation, Santa Clara, CA, USA) or 4 × 12-core Opteron (AMD, Sunnyvale, CA, USA) computers in a cluster, accurate results could be obtained in a 30-s computation time (see Appendix 2). The results obtained with the pseudo 1-min-helical acquisition (Table 2) supports that using an optimal pinhole collimator, it could be possible to reduce the acquisition time to 1 min. Although the small SDs obtained show that the statistic is sufficient, the reconstructed image is corrupted by more artifacts than for the sphere phantom where all the spheres were just in front of the collimator aperture. This likely resulted from the high pitch used (5.4 cm per half rotation). Ideally, the pitch should not be larger than the targeted final resolution (1 cm), requiring an acquisition software allowing automated helical SPECT that is not yet available on a commercial camera.
Additional file 1: SPECT animation. An example of a multi-pinhole SPECT implementation in a catheterization room using a six-axis arm robot. (MPEG 16 MB)
Conclusion
The use of pinhole SPECT reduces the disturbing interactions of the high-energy X-rays with the collimator. This would allow implementing a dosimetry assessment during the liver-SIRT procedure without displacing the catheter and at the end, injecting the optimal activity that provides the highest absorbed dose to the tumors still safe to the liver. This may definitely improve the patient outcome.
Appendix 1
Scatter model
where 511 (keV) is the energy of the electron at rest.
where S(E _{0} ) is the bremsstrahlung X-ray yield at energy E _{0} reaching the scattering point; note that due to the attenuation, there is a hardening of the X-ray beam when the distance between the emission and scattering points increases. Due to the continuous energy spectrum up to 2.27 MeV of the^{90}Y bremsstrahlung X-rays, all the scattering domain (0°, 180°) × (50, 150 keV) is targeted. The computation of Equation 5 using S(E _{0} ) obtained from Monte Carlo simulations [22] is given in Figure 7 and shows that contrary to^{99m}Tc, the first scattering emission can be reasonably considered as isotropic for^{90}Y. Successive scatterings will not fundamentally change this feature. As a result, while the high-energy continuous spectrum of^{90}Y bremsstrahlung X-rays increases the contamination level of the scattering compared to^{99m}Tc, it also simplifies the analytical model to approximate the scattering in the patient and its implementation in the iterative reconstruction that is now a simple additional convolution term.
Effective attenuation coefficient fitting
Appendix 2
Convergence rate
Declarations
Authors’ Affiliations
References
- Kennedy A, Nag S, Salem R, Murthy R, McEwan AJ, Nutting C, Benson A, Espat J, Bilbao JI, Sharma RA, Thomas JP, Coldwell D: Recommendations for radioembolization of hepatic malignancies using yttrium-90 microsphere brachytherapy: a consensus panel report from the radioembolization brachytherapy oncology consortium. Int J Radiat Oncol Biol Phys 2007, 68: 13–23. 10.1016/j.ijrobp.2006.11.060PubMedView ArticleGoogle Scholar
- Lambert B, Mertens J, Sturm EJ, Stienaers S, Defreyne L, D'Asseler Y: 99mTc-labelled macroaggregated albumin (MAA) scintigraphy for planning treatment with 90Y microspheres. Eur J Nucl Med Mol Imaging 2010, 37: 2328–2333. 10.1007/s00259-010-1566-2PubMedView ArticleGoogle Scholar
- Ahmadzadehfar H, Sabet A, Biermann K, Muckle M, Brockmann H, Kuhl C, Wilhelm K, Biersack HJ, Ezziddin S: The significance of 99mTc-MAA SPECT/CT liver perfusion imaging in treatment planning for 90Y-microsphere selective internal radiation treatment. J Nucl Med 2010, 51: 1206–1212. 10.2967/jnumed.109.074559PubMedView ArticleGoogle Scholar
- Garin E, Rolland Y, Lenoir L, Pracht M, Mesbah H, Porée P, Laffont S, Clement B, Raoul JL, Boucher E: Utility of quantitative Tc-MAA SPECT/CT for yttrium-labelled microsphere treatment planning: calculating vascularized hepatic volume and dosimetric approach. Int J Mol Imaging 2011, 2011: 398051.PubMed CentralPubMedView ArticleGoogle Scholar
- Flamen P, Vanderlinden B, Delatte P, Ghanem G, Ameye L, Van Den Eynde M, Hendlisz A: Multimodality imaging can predict the metabolic response of unresectable colorectal liver metastases to radioembolization therapy with yttrium-90 labeled resin microspheres. Phys Med Biol 2008, 53: 6591–5603. 10.1088/0031-9155/53/22/019PubMedView ArticleGoogle Scholar
- Bilbao JI, Reiser MF: Liver Radioembolization with 90Y Microspheres. Berlin Heidelberg: Springer-Verlag; 2008.View ArticleGoogle Scholar
- Gupta T, Virmani S, Neidt TM, Szolc-Kowalska B, Sato KT, Ryu RK, Lewandowski RJ, Gates VL, Woloschak GE, Salem R, Omary RA, Larson AC: MR tracking of iron-labeled glass radioembolization microsphres during transcatheter delivery to rabbit VX2 livers tumors: feasibility study. Radiology 2008, 249: 845–854. 10.1148/radiol.2491072027PubMedView ArticleGoogle Scholar
- Sebastian AJ, Szyszko T, Al-Nahhas A, Nijran K, Tait NP: Evaluation of hepatic angiography procedures and bremsstrahlung imaging in selective internal radiation therapy: a two-year single-center experience. Cardiovasc Intervent Radiol 2008, 31: 643–649. 10.1007/s00270-008-9298-4PubMedView ArticleGoogle Scholar
- Mansberg R, Sorensen N, Mansberg V, Van der Wall H: Yttrium 90 bremsstrahlung SPECT/CT scan demonstrating areas of tracer/tumour uptake. Eur J Nucl Med Mol Imaging 2007, 34: 1887. 10.1007/s00259-007-0536-9PubMedView ArticleGoogle Scholar
- Machac J, Weintraub J, Nowakowski F, Mobley D, Zhang Z, Warner R: Variations in liver perfusion patterns in patients with liver tumors undergoing therapy with yttrium-90 microspheres, studied with SPECT/CT. J Nucl Med 2007, 48: 396P.Google Scholar
- Knesaurek K, Muzinic M, Zhang Z, DaCosta M, Machac J: Comparison of visual and computer calculated coregistration of Y-90 and Tc-99m MAA SPECT/CT images in treatment of liver cancer. J Nucl Med 2008, 49: 112P.Google Scholar
- Knesaurek K, Machac J, Muzinic M, DaCosta M, Zhang Z, Heiba S: Quantitative comparison of yttrium-90 (90Y)-microspheres and technetium-99m (99mTc)-macroaggregated albumin SPECT images for planning 90Y therapy of liver cancer. Technol Cancer Res Treat 2010, 9: 253–262.PubMedView ArticleGoogle Scholar
- Moore S, Park M, Mueller S: Activity estimation performance in Y-90 microsphere bremsstrahlung SPECT. J Nucl Med 2009, 50: 1433.Google Scholar
- Tehranipour N, AL-Nahhas A, Canelo R, Stamp G, Woo K, Tait P, Gishen P: Concordant F-18 FDG PET and Y-90 bremsstrahlung scans depict selective delivery of Y-90-microspheres to liver tumors: confirmation with histopathology. Clin Nucl Med 2007, 32: 371–374. 10.1097/01.rlu.0000259568.54976.bdPubMedView ArticleGoogle Scholar
- Simon N, Feitelberg S: Scanning bremsstrahlung of yttrium-90 microspheres injected intra-arterially. Radiology 1967, 88: 719–724.PubMedView ArticleGoogle Scholar
- Gnanasegaran G, Buscombe JR, O'Rourke E, Caplin ME, Purfield D, Hilson AJW: Bremsstrahlung imaging after intra-arterial 90Y lanreotide radionuclide therapy for carcinoid liver metastases. Nucl Med Commun 2005, 26: 284–285.Google Scholar
- Luo J, Rao P, Zimmer M, Polis M, Mistretta M, Spies S: Imaging technique in estimating lung shunting of yttrium-90 microspheres. Med Phys 2005, 32: 1913.Google Scholar
- Walrand S, Flux GD, Konijnenberg MW, Valkema R, Krenning EP, Lhommel R, Pauwels S, Jamar F: Dosimetry of yttrium-labeled radiopharmaceutical for internal therapy: yttrium-86 or -90 imaging? Eur J Nucl Med Mol Imaging 2011.Google Scholar
- Lhommel R, Goffette P, Van den Eynde M, Jamar F, Pauwels S, Bilbao JI, Walrand S: Yttrium-90 TOF PET scan demonstrates high-resolution biodistribution after liver SIRT. Eur J Nucl Med Mol Imaging 2009.Google Scholar
- Lhommel R, van Elmbt L, Goffette P, Van den Eynde M, Jamar F, Pauwels S, Walrand S: Feasibility of yttrium-90 TOF-PET based dosimetry in liver metastasis therapy using SIR-spheres. Eur J Nucl Med Mol Imaging 2010.Google Scholar
- Werner MK, Brechtel K, Beyer T, Dittmann K, Pfannenberg C, Kupferschläger J: PET/CT for the assessment and quantification of 90Y biodistribution after selective internal radiotherapy (SIRT) of liver metastases. Eur J Nucl Med Mol Imaging 2009.Google Scholar
- Lhommel R, Walrand S, van Elmbt L, Pauwels S, Jamar F: Dose-response relationship in liver-SIRT: Y90 TOF-PET versus Tc99m-MAA SPECT based dosimetry. Eur J Nucl Med Mol Imaging 2010, 37: S201. 10.1007/s00259-009-1319-2View ArticleGoogle Scholar
- Gates VL, Esmail AAH, Marshall K, Spies S, Salem R: Internal pair production of 90Y permits hepatic localization of microspheres using routine pet: proof of concept. J Nucl Med 2010, 52: 72–76.PubMedView ArticleGoogle Scholar
- Walrand SH, van Elmbt LR, Pauwels S: Quantitation in SPECT using an effective model of the scattering. Phys Med Biol 1994, 39: 719–734. 10.1088/0031-9155/39/4/005PubMedView ArticleGoogle Scholar
- Cao ZJ, Frey EC, Tsui BMW: A scatter model for parallel and converging beam SPECT based on the Klein-Nishina formula. IEEE Trans Nucl Sci 1994, 41: 1594–1600. 10.1109/23.322954View ArticleGoogle Scholar
- Rault E, Staelens S, Van Holen R, De Beenhouwer J, Vandenberghe S: Accurate Monte Carlo modelling of the back compartments of SPECT cameras. Phys Med Biol 2011, 56: 87–104. 10.1088/0031-9155/56/1/006PubMedView ArticleGoogle Scholar
- Surti S, Kuhn A, Werner ME, Perkins AE, Kolthammer J, Karp JS: Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities. J Nucl Med 2007, 48: 471–480.PubMedGoogle Scholar
- Vanhove C, Andreyev A, Defrise M, Nuyts J, Bossuyt A: Resolution recovery in pinhole SPECT based on multi-ray projections: a phantom study. Eur J Nucl Med Mol Imaging 2007, 34: 170–180. 10.1007/s00259-006-0225-0PubMedView ArticleGoogle Scholar
- Shen S, DeNardo GL, DeNardo SJ: Quantitative bremsstrahlung imaging of yttrium-90 using a Wiener filter. Med Phys 1994, 21: 1409–1417. 10.1118/1.597198PubMedView ArticleGoogle Scholar
- Stabin MG: Fundamentals of Nuclear Medicine Dosimetry. New York: Springer; 2008.Google Scholar
- Walrand S, Jamar F, van Elmbt L, Lhommel R, Bekonde EB, Pauwels S: 4-Step renal dosimetry dependent on cortex geometry applied to 90Y peptide receptor radiotherapy: evaluation using a fillable kidney phantom imaged by 90Y PET. J Nucl Med 2010, 51: 1969–1973. 10.2967/jnumed.110.080093PubMedView ArticleGoogle Scholar
- Niemierko A: A unified model of tissue response to radiation. In Proceedings of the 41st AAPM Annual Meeting: July 25–29 1999; Nashville, Tennessee Edited by: William Hendee: AAPM. 1999, 1100.Google Scholar
- Emami B, Lyman J, Brown A, Coia L, Goitein M, Munzenrider JE, Shank B, Solin LJ, Wesson M: Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991, 21: 109–122.PubMedView ArticleGoogle Scholar
- Gay HA, Niemierko A: A free program for calculating EUD-based NTCP and TCP in external beam radiotherapy. Physica Medica 2007, 23: 115–125. 10.1016/j.ejmp.2007.07.001PubMedView ArticleGoogle Scholar
- Luxton G, Keall PJ, King CR: A new formula for normal tissue complication probability (NTCP) as a function of equivalent uniform dose (EUD). Phys Med Biol 2008, 53: 23–36. 10.1088/0031-9155/53/1/002PubMedView ArticleGoogle Scholar
- KUKA [http://www.kuka-robotics.com/en/products/industrial_robots]
- Kraus-Tiefenbacher U, Scheda A, Steil V, Hermann B, Kehrer T, Bauer L, Melchert F, Wenz F: Intraoperative radiotherapy (IORT) for breast cancer using the intrabeam™ system. Tumori 2005, 91: 339–345.PubMedGoogle Scholar
- Bjorken JD, Drell SD: Relativistic Quantum Mechanics. New York: McGraw-Hill Inc.; 1964.Google Scholar
- Kamphuis C, Beekman FJ, van Rijk PP, Viergever MA: Dual matrix ordered subsets reconstruction for accelerated 3D scatter compensation in single-photon emission tomography. Eur J Nucl Med 1997, 25: 8–18. 10.1007/s002590050188View ArticleGoogle Scholar
Copyright
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.