Photon contribution to tumor dose from considerations of 131I radiolabeled antibody uptake in liver, spleen, and whole body

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

PURPOSE

The authors' objective was to compare internal dose estimates obtained using the Organ Level Dose Assessment with Exponential Modeling (OLINDA/EXM) software, the voxel S value technique, and Monte Carlo simulation. Monte Carlo dose estimates were used as the reference standard to assess the impact of patient-specific anatomy on the final dose estimate.

METHODS

Six patients injected with 99mTc-hydrazinonicotinamide-Tyr3-octreotide were included in this study. A hybrid planar/SPECT imaging protocol was used to estimate 99mTc time-integrated activity coefficients (TIACs) for kidneys, liver, spleen, and tumors. Additionally, TIACs were predicted for 131I, 177Lu, and 90Y assuming the same biological half-lives as the 99mTc labeled tracer. The TIACs were used as input for OLINDA/EXM for organ-level dose calculation and voxel level dosimetry was performed using the voxel S value method and Monte Carlo simulation. Dose estimates for 99mTc, 131I, 177Lu, and 90Y distributions were evaluated by comparing (i) organ-level S values corresponding to each method, (ii) total tumor and organ doses, (iii) differences in right and left kidney doses, and (iv) voxelized dose distributions calculated by Monte Carlo and the voxel S value technique.

RESULTS

The S values for all investigated radionuclides used by OLINDA/EXM and the corresponding patient-specific S values calculated by Monte Carlo agreed within 2.3% on average for self-irradiation, and differed by as much as 105% for cross-organ irradiation. Total organ doses calculated by OLINDA/EXM and the voxel S value technique agreed with Monte Carlo results within approximately ±7%. Differences between right and left kidney doses determined by Monte Carlo were as high as 73%. Comparison of the Monte Carlo and voxel S value dose distributions showed that each method produced similar dose volume histograms with a minimum dose covering 90% of the volume (D90) agreeing within ±3%, on average.

CONCLUSIONS

Several aspects of OLINDA/EXM dose calculation were compared with patient-specific dose estimates obtained using Monte Carlo. Differences in patient anatomy led to large differences in cross-organ doses. However, total organ doses were still in good agreement since most of the deposited dose is due to self-irradiation. Comparison of voxelized doses calculated by Monte Carlo and the voxel S value technique showed that the 3D dose distributions produced by the respective methods are nearly identical.

Comparison of I-131 radioimmunotherapy tumor dosimetry: unit density sphere model versus patient-specific Monte Carlo calculations

High computational requirements restrict the use of Monte Carlo algorithms for dose estimation in a clinical setting, despite the fact that they are considered more accurate than traditional methods. The goal of this study was to compare mean tumor absorbed dose estimates using the unit density sphere model incorporated in OLINDA with previously reported dose estimates from Monte Carlo simulations using the dose planning method (DPMMC) particle transport algorithm. The dataset (57 tumors, 19 lymphoma patients who underwent SPECT/CT imaging during I-131 radioimmunotherapy) included tumors of varying size, shape, and contrast. OLINDA calculations were first carried out using the baseline tumor volume and residence time from SPECT/CT imaging during 6 days post-tracer and 8 days post-therapy. Next, the OLINDA calculation was split over multiple time periods and summed to get the total dose, which accounted for the changes in tumor size. Results from the second calculation were compared with results determined by coupling SPECT/CT images with DPM Monte Carlo algorithms. Results from the OLINDA calculation accounting for changes in tumor size were almost always higher (median 22%, range -1%-68%) than the results from OLINDA using the baseline tumor volume because of tumor shrinkage. There was good agreement (median -5%, range -13%-2%) between the OLINDA results and the self-dose component from Monte Carlo calculations, indicating that tumor shape effects are a minor source of error when using the sphere model. However, because the sphere model ignores cross-irradiation, the OLINDA calculation significantly underestimated (median 14%, range 2%-31%) the total tumor absorbed dose compared with Monte Carlo. These results show that when the quantity of interest is the mean tumor absorbed dose, the unit density sphere model is a practical alternative to Monte Carlo for some applications. For applications requiring higher accuracy, computer-intensive Monte Carlo calculation is needed.

Use of integrated SPECT/CT imaging for tumor dosimetry in I-131 radioimmunotherapy: a pilot patient study

Integrated systems combining functional (single-photon emission computed tomography; SPECT) imaging with anatomic (computed tomography; CT) imaging have the potential to greatly improve the accuracy of dose estimation in radionuclide therapy. In this article, we present the methodology for highly patient-specific tumor dosimetry by utilizing such a system and apply it to a pilot study of 4 follicular lymphoma patients treated with I-131 tositumomab. SPECT quantification included three-dimensional ordered-subset expectation-maximization reconstruction and CT-defined tumor outlines at each time point. SPECT/CT images from multiple time points were coupled to a Monte Carlo algorithm to calculate a mean tumor dose that incorporated measured changes in tumor volume. The tumor shrinkage, defined as the difference between volumes drawn on the first and last CT scan (a typical time period of 15 days) was in the range 5%-49%. The therapy-delivered mean tumor-absorbed dose was in the range 146-334 cGy. For comparison, the therapy dose was also calculated by assuming a static volume from the initial CT and was found to underestimate this dose by up to 47%. The agreement between tracer-predicted and therapy-delivered tumor-absorbed dose was in the range 7%-21%. In summary, malignant lymphomas can have dramatic tumor regression within days of treatment, and advanced imaging methods allow for a highly patient-specific tumor-dosimetry calculation that accounts for this regression.

MABDOSE. I: Characterization of a general purpose dose estimation code

The MABDOSE software represents a general tool to perform internal radiation dosimetry. It uses a three-dimensional lattice in which to conduct radiation transport, scoring energy deposition in discrete voxels. The dosimetry system currently relies on the same algorithm used by the MIRD committee for photon transport, and assumes local deposition of particulate energy. A mathematical description of the dosimetry system's implementation is given. Additionally, a characterization of the system with respect to memory requirements, data libraries used, and simulation timing benchmarks, is presented. Validation of the software is presented in a companion manuscript.

Relevance of accurate Monte Carlo modeling in nuclear medical imaging

Monte Carlo techniques have become popular in different areas of medical physics with advantage of powerful computing systems. In particular, they have been extensively applied to simulate processes involving random behavior and to quantify physical parameters that are difficult or even impossible to calculate by experimental measurements. Recent nuclear medical imaging innovations such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), and multiple emission tomography (MET) are ideal for Monte Carlo modeling techniques because of the stochastic nature of radiation emission, transport and detection processes. Factors which have contributed to the wider use include improved models of radiation transport processes, the practicality of application with the development of acceleration schemes and the improved speed of computers. In this paper we present a derivation and methodological basis for this approach and critically review their areas of application in nuclear imaging. An overview of existing simulation programs is provided and illustrated with examples of some useful features of such sophisticated tools in connection with common computing facilities and more powerful multiple-processor parallel processing systems. Current and future trends in the field are also discussed.

Monte Carlo-assisted voxel source kernel method (MAVSK) for internal beta dosimetry

A method is described for the determination of patient-specific organ beta doses given a known cumulated internal radioactivity distribution. A voxel source kernel for 90Y analogous to the point source function was simulated. Dose to each organ of interest could then be estimated by convolving the voxel source kernel with the patient's 3-D volume with known radioactivity assigned to each voxel. The dose calculation on eight organs took less than 1 min per patient using a Sun Sparc10 workstation.

Treatment planning for radio-immunotherapy

To foster the success of clinical trials in radio-immunotherapy (RIT), one needs to determine (i) the quantity and spatial distribution of the administered radionuclide carrier in the patient over time, (ii) the absorbed dose in the tumour sites and critical organs based on this distribution and (iii) the volume of tumour mass(es) and normal organs from computerized tomography or magnetic resonance imaging and appropriately correlated with nuclear medicine imaging techniques (such as planar, single-photon emission computerized tomography or positron-emission tomography). Treatment planning for RIT has become an important tool in predicting the relative benefit of therapy based on individualized dosimetry as derived from diagnostic, pre-therapy administration of the radiolabelled antibody. This allows the investigator to pre-select those patients who have 'favorable' dosimetry characteristics (high time-averaged target: non-target ratios) so that the chances for treatment success may be more accurately quantified before placing the patient at risk for treatment-related organ toxicities. The future prospects for RIT treatment planning may yield a more accurate correlation of response and critical organ toxicity with computed absorbed dose, and the compilation of dose-volume histogram information for tumour(s) and normal organ(s) such that computing tumour control probabilities and normal tissue complication probabilities becomes possible for heterogeneous distributions of the radiolabelled antibody. Additionally, radiobiological consequences of depositing absorbed doses from exponentially decaying sources must be factored into the interpretation when trying to compute the effects of standard external beam isodose display patterns combined with those associated with RIT.

A radioimmunoimaging and MIRD dosimetry treatment planning program for radioimmunotherapy

A treatment planning program for radioimmunotherapy employing quantitative Anger camera imaging and the MIRD formalism has been designed and implemented on a clinical nuclear medicine computer. Radionuclide residence times are calculated from linear, mono- and bi-exponential, and cubic spline fits to regional activity versus time curves, and radiation-absorbed dose estimates for all target organs for 131I, 67Cu, and 58 other radionuclides can be calculated. This software has been successfully applied to radioimmunotherapy of B-cell malignancies and breast adenocarcinomas.

Validation of a dose-point kernel convolution technique for internal dosimetry

The objective of this study was to validate a dose-point kernel convolution technique that provides a three-dimensional (3D) distribution of absorbed dose from a 3D distribution of the radionuclide 131I. A dose-point kernel for the penetrating radiations was calculated by a Monte Carlo simulation and cast in a 3D rectangular matrix. This matrix was convolved with the 3D activity map furnished by quantitative single-photon-emission computed tomography (SPECT) to provide a 3D distribution of absorbed dose. The convolution calculation was performed using a 3D fast Fourier transform (FFT) technique, which takes less than 40 s for a 128 x 128 x 16 matrix on an Intel 486 DX2 (66 MHz) personal computer. The calculated photon absorbed dose was compared with values measured by thermoluminescent dosimeters (TLDS) inserted along the diameter of a 22 cm diameter annular source of 131I. The mean and standard deviation of the percentage difference between the measurements and the calculations were equal to -1% and 3.6%, respectively. This convolution method was also used to calculate the 3D dose distribution in an Alderson abdominal phantom containing a liver, a spleen, and a spherical tumour volume loaded with various concentrations of 131I. By averaging the dose calculated throughout the liver, spleen, and tumour the dose-point kernel approach was compared with values derived using the MIRD formalism, and found to agree to better than 15%.