Introduction: Non-Hodgkin Lymphoma patients respond differently to therapy according to inherent biological variations. Pretherapy biomarkers may improve dose-response prediction. Materials and Methods: Hybrid single-photon emission computed tomography (SPECT)/computed tomography (CT) three-dimensional imaging at multiple time points plus follow-up positron emission tomography (PET)/CT or CT at 2 and 6 months post therapy were used to fit tumor response to combined biological effect and cell clearance models from which three biological effect response parameters (radiosensitivity, cold effect sensitivity, and proliferation potential) were determined per patient. A correlation of biological effect parameters and pretherapy biomarker data (ki67, p53, and phospho-histone H3) allowed a dose-based equivalent biological effect (EBE) to be calculated for each patient. Results: Significant correlations were found between biological effect parameters and pretherapy biomarkers. Optimum correlations were found by splitting the patient data according to p53 status. Response correlation of progression free survival (PFS) and EBE were significantly improved compared with PFS and absorbed dose alone. Conclusions: It is possible and desirable to use pretherapy biomarkers to enhance the predictive potential of dose calculations for patient-specific treatment planning.

The DPM (Dose Planning Method) Monte Carlo electron and photon transport program, designed for fast computation of radiation absorbed dose in external beam radiotherapy, has been adapted to the calculation of absorbed dose in patient-specific internal emitter therapy. Because both its photon and electron transport mechanics algorithms have been optimized for fast computation in 3D voxelized geometries (in particular, those derived from CT scans), DPM is perfectly suited for performing patient-specific absorbed dose calculations in internal emitter therapy. In the updated version of DPM developed for the current work, the necessary inputs are a patient CT image, a registered SPECT image, and any number of registered masks defining regions of interest. DPM has been benchmarked for internal emitter therapy applications by comparing computed absorption fractions for a variety of organs using a Zubal phantom with reference results from the Medical Internal Radionuclide Dose (MIRD) Committee standards. In addition, the β decay source algorithm and the photon tracking algorithm of DPM have been further benchmarked by comparison to experimental data. This paper presents a description of the program, the results of the benchmark studies, and some sample computations using patient data from radioimmunotherapy studies using (131)I.

Accurate tumor dosimetry in internal emitter therapy requires modeling both the spatial and temporal variation of absorbed dose rates in tumor volumes. Generally, 3D absorbed dose distributions can be computed only under the approximation that the time dependence of tumor activity is spatially uniform, since 3D, time-varying patient measurement data is not available. However, in a pilot study at our clinic involving follicular lymphoma patients being treated with 131I tositumomab, registered SPECT and CT images are acquired with an integrated scanner at multiple times after both tracer and therapy administration, thus providing the extensive data required for detailed absorbed dose computations. In a previous work we described a method for the Monte Carlo computation of 3D absorbed dose distributions with spatially varying time-activity distributions in tumors. Multiple time point CT images were registered to a reference CT image which was used to define a fixed patient geometry, and voxel-based time-activity curves were derived from the registered SPECT images and numerically integrated to yield a 3D integrated activity map. Because this method relies on a single CT image to define the patient, it is not applicable for regressing, proliferating, or deforming tumor volumes. In the current work, we present results using a new method for computing absorbed dose that accounts for tumor deformation. Absorbed dose rate maps are calculated via Monte Carlo at each time point using the registered SPECT images to describe the activity distribution and the CT images to define the patient volume. These time-dependent 3D absorbed dose rate maps are then registered using transformation variables determined by a mutual information registration computation applied to the CT images. Time-integrated absorbed dose distributions are then computed by modeling the time dependence of dose rate between time steps and the tumor volume in the presence of deformation.

Accurate tumor dosimetry in internal emitter therapy requires modeling both the spatial and temporal variation of absorbed dose rates in tumor volumes. Generally, 3D absorbed dose distributions can be computed only under the approximation that the time dependence of tumor activity is spatially uniform, since 3D, time-varying patient measurement data is not available. However, in a pilot study at our clinic involving follicular lymphoma patients being treated with I-131 tositumomab, registered SPECT and CT images are acquired with an integrated scanner at multiple times after both tracer and therapy administration, thus providing the extensive data required for detailed absorbed dose computations. In a previous work we described a method for the Monte Carlo computation of 3D absorbed dose distributions with spatially varying time-activity distributions in tumors. Multiple time point CT images were registered to a reference CT image which was used to define a fixed patient geometry, and voxel-based time-activity curves were derived from the registered SPECT images and numerically integrated to yield a 3D integrated activity map. Because this method relies on a single CT image to define the patient, it is not applicable for regressmig, proliferating, or deforming tumor volumes. In the current work, we present results using a new method for computing absorbed dose that accounts for tumor deformation. Absorbed dose rate maps are calculated via Monte Carlo at each time point using the registered SPECT images to describe the activity distribution and the CT images to define the patient volume. These time-dependent 3D absorbed dose rate maps are then registered using transformation variables determined by a mutual information registration computation applied to the CT images. Time-integrated absorbed dose distributions are then computed by modeling the time dependence of dose rate between time steps and the tumor volume in the presence of deformation.

443 Objectives: For effective individualized treatment planning in radioimmunotherapy it is imperative that methods be established for accurate bone marrow dosimetry. In malignancies such as non-Hodgkin’s lymphoma (NHL) where marrow uptake is likely, image-based dose assessment is potentially more accurate than conventional blood-based estimates, which are valid only if the marrow is devoid of any specific uptake. Our objective was to carry out image-based bone marrow dosimetry using data from a SPECT/CT integrated system where more reliable delineation of the marrow regions and uptake quantification is achievable than with planar imaging. Methods: In this pilot study, four NHL patients treated with I-131 tositumomab were imaged multiple times with a Siemens SPECT/CT system. At each time point two marrow-rich regions (sacrum and lumbar vertebrae) were defined on the CT and were mapped to the corresponding quantitative SPECT to generate time-activity curves for each region. These results were combined with MIRD S-factors to obtain the self-absorbed dose in red marrow using published values for the fraction of the total adult red marrow that is present in each region. The contribution to marrow dose from activity in the rest of the body was determined based on whole body imaging data. For comparison, the red marrow dose was also calculated by the blood method. Results: For the 4 patients, the lumbar to rest of the body activity concentration ratio ranged from 2.0 to 3.0 and the sacrum to rest of the body activity concentration ratio ranged from 1.5 to 2.6. The absorbed dose to red marrow was 0.8 to 1.0 rad/mCi based on lumbar imaging, 0.9 to 1.4 rad/mCi based on sacrum imaging and 1.0 to 1.4 rad/mCi based on blood. Conclusions: There is variability in the image-based red marrow dose estimate depending on the marrow region imaged, which suggests that an average dose should be calculated based on analyzing multiple regions. To make the calculation more patient specific without relying on S-factors we are investigating coupling SPECT/CT data with a previously developed Monte Carlo dosimetry algorithm. Research Support (if any): National Institutes of Health R01 EB001994

UNLABELLED:(131)I radionuclide therapy studies have not shown a strong relationship between tumor absorbed dose and response, possibly due to inaccuracies in activity quantification and dose estimation. The goal of this work was to establish the accuracy of (131)I activity quantification and absorbed dose estimation when patient-specific, 3-dimensional (3D) methods are used for SPECT reconstruction and for absorbed dose calculation. METHODS:Clinically realistic voxel-phantom simulations were used in the evaluation of activity quantification and dosimetry. SPECT reconstruction was performed using an ordered-subsets expectation maximization (OSEM) algorithm with compensation for scatter, attenuation, and 3D detector response. Based on the SPECT image and a patient-specific density map derived from CT, 3D dosimetry was performed using a newly implemented Monte Carlo code. Dosimetry was evaluated by comparing mean absorbed dose estimates calculated directly from the defined phantom activity map with those calculated from the SPECT image of the phantom. Finally, the 3D methods were applied to a radioimmunotherapy patient, and the mean tumor absorbed dose from the new calculation was compared with that from conventional dosimetry obtained from conjugate-view imaging. RESULTS:Overall, the accuracy of the SPECT-based absorbed dose estimates in the phantom was >12% for targets down to 16 mL and up to 35% for the smallest 7-mL tumor. To improve accuracy in the smallest tumor, more OSEM iterations may be needed. The relative SD from multiple realizations was <3% for all targets except for the smallest tumor. For the patient, the mean tumor absorbed dose estimate from the new Monte Carlo calculation was 7% higher than that from conventional dosimetry. CONCLUSION:For target sizes down to 16 mL, highly accurate and precise dosimetry can be obtained with 3D methods for SPECT reconstruction and absorbed dose estimation. In the future, these methods can be applied to patients to potentially establish correlations between tumor regression and the absorbed dose statistics from 3D dosimetry.