Three-dimensional dosimetry for intralesional radionuclide therapy using mathematical modeling and multimodality imaging (original) (raw)
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Journal of Nuclear Medicine, 2007
Phantom-based and patient-specific imaging-based dosimetry methodologies have traditionally yielded mean organ-absorbed doses or spatial dose distributions over tumors and normal organs. In this work, radiobiologic modeling is introduced to convert the spatial distribution of absorbed dose into biologically effective dose and equivalent uniform dose parameters. The methodology is illustrated using data from a thyroid cancer patient treated with radioiodine. Methods: Three registered SPECT/CT scans were used to generate 3-dimensional images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT scan were provided as input into an EGSnrc-based Monte Carlo calculation: The cumulated activity image was used to define the distribution of decays, and an attenuation image derived from CT was used to define the corresponding spatial tissue density and composition distribution. The rate images were used to convert the spatial absorbed dose distribution to a biologically effective dose distribution, which was then used to estimate a single equivalent uniform dose for segmented volumes of interest. Equivalent uniform dose was also calculated from the absorbed dose distribution directly. Results: We validate the method using simple models; compare the dose-volume histogram with a previously analyzed clinical case; and give the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for the tumor were 57.7, 58.5, and 25.0 Gy, respectively. Corresponding values for normal lung tissue were 9.5, 9.8, and 8.3 Gy, respectively. Conclusion: The analysis demonstrates the impact of radiobiologic modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose nonuniformity in the tumor and a corresponding reduced likelihood of achieving a tumor response. Such analyses are expected to be useful in treatment planning for radionuclide therapy.
2007
Phantom-based and patient-specific imaging-based dosimetry methodologies have traditionally yielded mean organ absorbed doses or spatial dose distributions over tumors and normal organs. In this work, radiobiological modeling is introduced to convert the spatial distribution of absorbed dose into biologically effective dose and equivalent uniform dose parameters. The methodology is illustrated using data from a thyroid cancer patient treated with radioiodine. METHODS: Three registered SPECT/CT scans were used to generate 3-D images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT were provided as input into an EGSnrc-based Monte Carlo calculation; the cumulated activity image defined the distribution of decays while an attenuation image derived from CT was used to define the corresponding spatial tissue density and composition distribution. The rate images were used to convert the spatial absorbed dose distribution to a Biologically Effective Dose (BED) distribution which was then used to estimate a single Equivalent Uniform Dose (EUD) for segmented volumes of interest. EUD was also calculated from the absorbed dose distribution directly. RESULTS: Validation using simple models and also comparison of the dose-volume histogram to a previously analyzed clinical case is shown as well as the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative clinical case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean BED and EUD for tumor was 57.7, 58.5 and 25.0 Gy, respectively. Corresponding values for normal lung tissue were 9.5, 9.8 and 8.3 Gy, respectively. CONCLUSION The analysis demonstrates the impact of radiobiological modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose non-uniformity in the tumor and a corresponding reduced likelihood of achieving a tumor response. Such analyses are expected to be useful in treatment planning for radionuclide therapy.
Patient-specific dosimetry in radionuclide therapy
Radiation Protection Dosimetry, 2011
This study presents an attempt to compare individualised palliative treatment absorbed doses, by planar images data and Monte Carlo simulation, in two in vivo treatment cases, one of bone metastases and the other of liver lesions. Medical Internal Radiation Dose schema was employed to estimate the absorbed doses. Radiopharmaceutical volume distributions and absorbed doses in the lesions as well as in critical organs were also calculated by Monte Carlo simulation. Individualised planar data calculations remain the method of choice in internal dosimetry in nuclear medicine, but with the disadvantage of attenuation and scatter corrections lack and organ overlay. The overall error is about 7 % for planar data calculations compared with that using Monte Carlo simulation. Patient-specific three-dimensional dosimetric calculations using single-photon emission computed tomography with a parallel computed tomography study is proposed as an accurate internal dosimetry with the additional use of dose-volume histograms, which express dose distributions in cases with obvious inhomogeneity.
Journal of Nuclear Medicine, 2012
In internal radionuclide therapy, a growing interest in voxel-level estimates of tissue-absorbed dose has been driven by the desire to report radiobiologic quantities that account for the biologic consequences of both spatial and temporal nonuniformities in these dose estimates. This report presents an overview of 3-dimensional SPECT methods and requirements for internal dosimetry at both regional and voxel levels. Combined SPECT/CT image-based methods are emphasized, because the CT-derived anatomic information allows one to address multiple technical factors that affect SPECT quantification while facilitating the patient-specific voxel-level dosimetry calculation itself. SPECT imaging and reconstruction techniques for quantification in radionuclide therapy are not necessarily the same as those designed to optimize diagnostic imaging quality. The current overview is intended as an introduction to an upcoming series of MIRD pamphlets with detailed radionuclide-specific recommendations intended to provide best-practice SPECT quantification-based guidance for radionuclide dosimetry.
Radiotherapy and Oncology, 2009
Purpose: Retrospective study of 3D clinical treatment plans based on radiobiological considerations in the choice of the reference dose level from tumor dose-volume histograms. Methods and materials: When a radiation oncologist evaluates the 3D dose distribution calculated by a treatment planning system, a decision must be made on the percentage dose level at which the prescribed dose should be delivered. Much effort is dedicated to deliver a dose as uniform as possible to the tumor volume. However due to the presence of critical organs, the result may be a rather inhomogeneous dose distribution throughout the tumor volume. In this study we use a formulation of tumor control probability (TCP) based on the linear quadratic model and on a parameter, the F factor. The F factor allows one to write TCP, from the heterogeneous dose distribution (TCP{(e j ,D j )}), as a function of TCP under condition of homogeneous irradiation of tumor volume (V) with dose D (TCP(V,D)). We used the expression of the F factor to calculate the ''ideal" percentage dose level (iDL r ) to be used as reference level for the prescribed dose D delivery, so as to render TCP{(e j ,D j )} equal to TCP(V,D).Methods and materials: The 3D dose distributions of 53 clinical treatment plans were re-evaluated to derive the iDL r and to compare it with the one (D tp L) to which the dose was actually administered. Results: For the majority of prostate treatments, we observed a low overdosing following the choice of a D tp L lower than the iDL r. While for the breast and head-and-neck treatments, the method showed that in many cases we underdosed choosing a D tp L greater than the iDL r . The maximum difference between the iDL r and the D tp L was À3.24% for one of the head-and-neck treatments. Conclusions: Using the TCP model, the probability of tumor control is compromised following an incorrect choice of D tp L; so we conclude that the application of the F factor is an effective tool and clinical aid to derive the optimal reference dose level from the dose-volume histogram (DVH) of each treatment plan.
Three-Dimensional Imaging-Based Radiobiological Dosimetry
Seminars in Nuclear Medicine, 2008
Targeted radionuclide therapy holds promise as a new treatment against cancer. Advances in imaging are making it possible to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging such as combined SPECT/CT and PET/CT have also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithims, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods.
Journal of Nuclear Medicine, 2009
Dosimetric calculations are performed with an increasing frequency before or after treatment in targeted radionuclide therapy, as well as for radiation protection purposes in diagnostic nuclear medicine. According to the MIRD committee formalism, the mean absorbed dose to a target is given by the product of the cumulated activity and a dose-conversion factor, known as the S factor. Standard S factors have been published for mathematic phantoms and for unit-density spheres. The accuracy of the results from the use of these S factors is questionable, because patient morphology can vary significantly. The aim of this work was to investigate differences between patient-specific dosimetric results obtained using Monte Carlo methodology and results obtained using S factors calculated on standard models. Methods: The CT images of 9 patients, who ranged in size, were used. Patient-specific S factors for 131 I were calculated with the MCNPX2.5.0 Monte Carlo code using a tool for personalized internal dose assessment, OEDIPE; standard S factors from OLINDA/EXM were compared against the patient-specific S factors. Furthermore, realistic biodistributions and cumulated activities for normal organs and tumors were used, and mean organ-and tumor-absorbed doses calculated with OEDIPE and OLINDA/EXM were compared. Results: The ratio of the standard and the patient-specific S factors were between 0.49 and 1.84 for a target distant from the source for 4 organs and 2 tumors studied as source and targets. For the case of self-irradiation, the equivalent ratio ranged between 0.45 and 2.47 and between 1.00 and 1.06 when mass correction was applied. Differences in mean absorbed doses were as high as 140% when realistic cumulated activity values were used. These values decreased to less than 26% in all cases studied when mass correction was applied to the self-irradiation given by OLINDA/EXM. Conclusion: Standard S factors can yield mean absorbed doses for normal organs or tumors with a reasonable accuracy (26% for the cases studied) as compared with absorbed doses calculated with Monte Carlo, provided that they have been corrected for mass.
Journal of Nuclear …, 2010
A 3-dimensional (3D) imaging-based patient-specific dosimetry methodology incorporating antitumor biologic effects using biologically effective dose (BED) and equivalent uniform dose (EUD) was developed in this study. The methodology was applied to the dosimetry analysis of 6 non-Hodgkin lymphoma patients with a total of 10 tumors. Methods: Six registered SPECT/CT scans were obtained for each patient treated with 131 I-labeled antibody. Three scans were obtained after tracer administration and 3 after therapy administration. The SPECT/CT scans were used to generate 3D images of cumulated activity. The cumulated activity images and corresponding CT scans were used as input to Monte Carlo dose-rate calculations. The dose-rate distributions were integrated over time to obtain 3D absorbed dose distributions. The time-dependent 3D cumulative dose distributions were used to generate 3D BED distributions. Techniques to incorporate the effect of unlabeled antibody (cold protein) in the BED analysis were explored. Finally, BED distributions were used to estimate an EUD for each tumor volume. Model parameters were determined from optimal fits to tumor regression data. The efficiency of dose delivery to tumors-the ratio of EUD to cumulative dose-was extracted for each tumor and correlated with patient response parameters. Results: The model developed in this study was validated for dosimetry of non-Hodgkin lymphoma patients treated with 131 I-labeled antibody. Correlations between therapy efficiency generated from the model and tumor response were observed using averaged model parameters. Model parameter determination favored a threshold for the cold effect and typical magnitude for tumor radiosensitivity parameters. Conclusion: The inclusion of radiobiologic effects in the dosimetry modeling of internal emitter therapy provides a powerful platform to investigate correlations of patient outcome with planned therapy.