Three-dimensional radiobiological dosimetry of kidneys for treatment planning in peptide receptor radionuclide therapy
Institute of Radiation Physics, Lausanne University Hospital, 1007 Lausanne, Switzerland. Medical Physics
(Impact Factor: 2.64).
10/2012; 39(10):6118-6128. DOI: 10.1118/1.4752213
Peptide receptor radionuclide therapy (PRRT) delivers high absorbed doses to kidneys and may lead to permanent nephropathy. Reliable dosimetry of kidneys is thus critical for safe and effective PRRT. The aim of this work was to assess the feasibility of planning PRRT based on 3D radiobiological dosimetry (3D-RD) in order to optimize both the amount of activity to administer and the fractionation scheme, while limiting the absorbed dose and the biological effective dose (BED) to the renal cortex.
Planar and SPECT data were available for a patient examined with (111)In-DTPA-octreotide at 0.5 (planar only), 4, 24, and 48 h post-injection. Absorbed dose and BED distributions were calculated for common therapeutic radionuclides, i.e., (111)In, (90)Y and (177)Lu, using the 3D-RD methodology. Dose-volume histograms were computed and mean absorbed doses to kidneys, renal cortices, and medullae were compared with results obtained using the MIRD schema (S-values) with the multiregion kidney dosimetry model. Two different treatment planning approaches based on (1) the fixed absorbed dose to the cortex and (2) the fixed BED to the cortex were then considered to optimize the activity to administer by varying the number of fractions.
Mean absorbed doses calculated with 3D-RD were in good agreement with those obtained with S-value-based SPECT dosimetry for (90)Y and (177)Lu. Nevertheless, for (111)In, differences of 14% and 22% were found for the whole kidneys and the cortex, respectively. Moreover, the authors found that planar-based dosimetry systematically underestimates the absorbed dose in comparison with SPECT-based methods, up to 32%. Regarding the 3D-RD-based treatment planning using a fixed BED constraint to the renal cortex, the optimal number of fractions was found to be 3 or 4, depending on the radionuclide administered and the value of the fixed BED. Cumulative activities obtained using the proposed simulated treatment planning are compatible with real activities administered to patients in PRRT.
The 3D-RD treatment planning approach based on the fixed BED was found to be the method of choice for clinical implementation in PRRT by providing realistic activity to administer and number of cycles. While dividing the activity in several cycles is important to reduce renal toxicity, the clinical outcome of fractionated PRRT should be investigated in the future.
Available from: Annibale Versari
- "When 90 Y is the radiopharmaceutical, either 111 In-or 86 Y-labeled peptides are used as a surrogate and 2 to 5 scans are collected up to 2-3 days p.i. . These activity data are usually fitted by means of monoexponential functions   , biexponential , or trapezoids . The great value of dosimetry is an established tenet, nonetheless each experimental point requires time-consuming acquisitions. "
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ABSTRACT: Kidney dosimetry in 177Lu and 90Y PRRT requires 3 to 6 whole-body/SPECT scans to extrapolate the peptide kinetics, and it is considered time and resource consuming. We investigated the most adequate timing for imaging and time-activity interpolating curve, as well as the performance of a simplified dosimetry, by means of just 1-2 scans. Finally the influence of risk factors and of the peptide (DOTATOC versus DOTATATE) is considered. 28 patients treated at first cycle with 177Lu DOTATATE and 30 with 177Lu DOTATOC underwent SPECT scans at 2 and 6 hours, 1, 2, and 3 days after the radiopharmaceutical injection. Dose was calculated with our simplified method, as well as the ones most used in the clinic, that is, trapezoids, monoexponential, and biexponential functions. The same was done skipping the 6 h and the 3 d points. We found that data should be collected until 100 h for 177Lu therapy and 70 h for 90Y therapy, otherwise the dose calculation is strongly influenced by the curve interpolating the data and should be carefully chosen.
Risk factors (hypertension, diabetes) cause a rather statistically significant 20% increase in dose (t-test, P < 0.10), with DOTATATE affecting an increase of 25% compared to DOTATOC (t-test, P < 0.05).
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ABSTRACT: In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator-detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.
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The main objective of this work was to design a comprehensive dosimetry package that would keep all aspects of internal dose calculation within the framework of a single software environment and that would be applicable for a variety of dose calculation approaches.
Our MATLAB-based graphical user interface (GUI) can be used for processing data obtained using pure planar, pure SPECT, or hybrid planar/SPECT imaging. Time-activity data for source regions are obtained using a set of tools that allow the user to reconstruct SPECT images, load images, coregister a series of planar images, and to perform two-dimensional and three-dimensional image segmentation. Curve fits are applied to the acquired time-activity data to construct time-activity curves, which are then integrated to obtain time-integrated activity coefficients. Subsequently, dose estimates are made using one of three methods.
The organ level dose calculation subGUI calculates mean organ doses that are equivalent to dose assessment performed by OLINDA/EXM. Voxelized dose calculation options, which include the voxel S value approach and Monte Carlo simulation using the EGSnrc user code DOSXYZnrc, are available within the process 3D image data subGUI.
The developed internal dosimetry software package provides an assortment of tools for every step in the dose calculation process, eliminating the need for manual data transfer between programs. This saves times and minimizes user errors, while offering a versatility that can be used to efficiently perform patient-specific internal dose calculations in a variety of clinical situations.
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