Method for Fast CT/SPECT-Based 3D Monte Carlo Absorbed Dose Computations in Internal Emitter Therapy

PET/CT-Based Absorbed Dose Maps in 90Y Selective Internal Radiation Therapy Correlate with Spatial Changes in Liver Function Derived from Dynamic MRI

Functional liver parenchyma can be damaged from treatment of liver malignancies with 90Y selective internal radiation therapy (SIRT). Evaluating functional parenchymal changes and developing an absorbed dose (AD)-toxicity model can assist the clinical management of patients receiving SIRT. We aimed to determine whether there is a correlation between 90Y PET AD voxel maps and spatial changes in the nontumoral liver (NTL) function derived from dynamic gadoxetic acid-enhanced MRI before and after SIRT. Methods: Dynamic gadoxetic acid-enhanced MRI scans were acquired before and after treatment for 11 patients undergoing 90Y SIRT. Gadoxetic acid uptake rate (k1) maps that directly quantify spatial liver parenchymal function were generated from MRI data. Voxel-based AD maps, derived from the 90Y PET/CT scans, were binned according to AD. Pre- and post-SIRT k1 maps were coregistered to the AD map. Absolute and percentage k1 loss in each bin was calculated as a measure of loss of liver function, and Spearman correlation coefficients between k1 loss and AD were evaluated for each patient. Average k1 loss over the patients was fit to a 3-parameter logistic function based on AD. Patients were further stratified into subgroups based on lesion type, baseline albumin-bilirubin scores and alanine transaminase levels, dose-volume effect, and number of SIRT treatments. Results: Significant positive correlations (ρ = 0.53-0.99, P < 0.001) between both absolute and percentage k1 loss and AD were observed in most patients (8/11). The average k1 loss over 9 patients also exhibited a significant strong correlation with AD (ρ ≥ 0.92, P < 0.001). The average percentage k1 loss of patients across AD bins was 28%, with a logistic function model demonstrating about a 25% k1 loss at about 100 Gy. Analysis between patient subgroups demonstrated that k1 loss was greater among patients with hepatocellular carcinoma, higher alanine transaminase levels, larger fractional volumes of NTL receiving an AD of 70 Gy or more, and sequential SIRT treatments. Conclusion: Novel application of multimodality imaging demonstrated a correlation between 90Y SIRT AD and spatial functional liver parenchymal degradation, indicating that a higher AD is associated with a larger loss of local hepatocyte function. With the developed response models, PET-derived AD maps can potentially be used prospectively to identify localized damage in liver and to enhance treatment strategies.

SPECT/CT Image-Derived Absorbed Dose to Red Marrow Correlates with Hematologic Toxicity in Patients Treated with [177Lu]Lu-DOTATATE

Hematologic toxicity, although often transient, is the most common limiting adverse effect during somatostatin peptide receptor radionuclide therapy. This study investigated the association between Monte Carlo-derived absorbed dose to the red marrow (RM) and hematologic toxicity in patients being treated for their neuroendocrine tumors. Methods: Twenty patients each receiving 4 treatment cycles of [177Lu]Lu-DOTATATE were included. Multiple-time-point 177Lu SPECT/CT imaging-based RM dosimetry was performed using an artificial intelligence-driven workflow to segment vertebral spongiosa within the field of view (FOV). This workflow was coupled with an in-house macroscale/microscale Monte Carlo code that incorporates a spongiosa microstructure model. Absorbed dose estimates to RM in lumbar and thoracic vertebrae within the FOV, considered as representations of the whole-body RM absorbed dose, were correlated with hematologic toxicity markers at about 8 wk after each cycle and at 3- and 6-mo follow-up after completion of all cycles. Results: The median of absorbed dose to RM in lumbar and thoracic vertebrae within the FOV (D median,vertebrae) ranged from 0.019 to 0.11 Gy/GBq. The median of cumulative absorbed dose across all 4 cycles was 1.3 Gy (range, 0.6-2.5 Gy). Hematologic toxicity was generally mild, with no grade 2 or higher toxicity for platelets, neutrophils, or hemoglobin. However, there was a decline in blood counts over time, with a fractional value relative to baseline at 6 mo of 74%, 97%, 57%, and 97%, for platelets, neutrophils, lymphocytes, and hemoglobin, respectively. Statistically significant correlations were found between a subset of hematologic toxicity markers and RM absorbed doses, both during treatment and at 3- and 6-mo follow-up. This included a correlation between the platelet count relative to baseline at 6-mo follow up: D median,vertebrae (r = -0.64, P = 0.015), D median,lumbar (r = -0.72, P = 0.0038), D median,thoracic (r = -0.58, P = 0.029), and D average,vertebrae (r = -0.66, P = 0.010), where D median,lumbar and D median,thoracic are median absorbed dose to the RM in the lumbar and thoracic vertebrae, respectively, within the FOV and D average,vertebrae is the mass-weighted average absorbed dose of all vertebrae. Conclusion: This study found a significant correlation between image-derived absorbed dose to the RM and hematologic toxicity, including a relative reduction of platelets at 6-mo follow up. These findings indicate that absorbed dose to the RM can potentially be used to understand and manage hematologic toxicity in peptide receptor radionuclide therapy.

Linear Boltzmann equation solver for voxel-level dosimetry in radiopharmaceutical therapy: Comparison with Monte Carlo and kernel convolution

BACKGROUND

With recent interest in patient-specific dosimetry for radiopharmaceutical therapy (RPT) and selective internal radiation therapy (SIRT), an increasing number of voxel-based algorithms are being evaluated. Monte Carlo (MC) radiation transport, generally considered to be the most accurate among different methods for voxel-level absorbed dose estimation, can be computationally inefficient for routine clinical use.

PURPOSE

This work demonstrates a recently implemented grid-based linear Boltzmann transport equation (LBTE) solver for fast and accurate voxel-based dosimetry in RPT and SIRT and benchmarks it against MC.

METHODS

A deterministic LBTE solver (Acuros MRT) was implemented within a commercial RPT dosimetry package (Velocity 4.1). The LBTE is directly discretized using an adaptive mesh refined grid and then the coupled photon-electron radiation transport is iteratively solved inside specified volumes to estimate radiation doses from both photons and charged particles in heterogeneous media. To evaluate the performance of the LBTE solver for RPT and SIRT applications, 177 Lu SPECT/CT, 90 Y PET/CT, and 131 I SPECT/CT images of phantoms and patients were used. Multiple lesions (2-1052 mL) and normal organs were delineated for each study. Voxel dosimetry was performed with the LBTE solver, dose voxel kernel (DVK) convolution with density correction, and a validated in-house MC code using the same time-integrated activity and density maps as input to the different dose engines. The resulting dose maps, difference maps, and dose-volume-histogram (DVH) metrics were compared, to assess the voxel-level agreement. Evaluation of mean absorbed dose included comparison with structure-level estimates from OLINDA.

RESULTS

In the phantom inserts/compartments, the LBTE solver versus MC and DVK convolution demonstrated good agreement with mean absorbed dose and DVH metrics agreeing to within 5% except for the D90 and D70 metrics of a very low activity concentration insert of 90 Y where the agreement was within 15%. In the patient studies (five patients imaged after 177 Lu DOTATATE RPT, five after 90 Y SIRT, and two after 131 I radioimmunotherapy), in general, there was better agreement between the LBTE solver and MC than between LBTE solver and DVK convolution for mean absorbed dose and voxel-level evaluations. Across all patients for all three radionuclides, for soft tissue structures (kidney, liver, lesions), the mean absorbed dose estimates from the LBTE solver were in good agreement with those from MC (median difference < 1%, maximum 9%) and those from DVK (median difference < 5%, maximum 9%). The LBTE and OLINDA estimates for mean absorbed dose in kidneys and liver agreed to within 10%, but differences for lesions were larger with a maximum 14% for 177 Lu, 23% for 90 Y, and 26% for 131 I. For bone regions, the agreement in mean absorbed doses between LBTE and both MC and DVK were similar (median < 11%, max 11%) while for lung the agreement between LBTE and MC (median < 1%, max 8%) was substantially better than between LBTE and DVK (median < 16%, max 33%). Voxel level estimates for soft tissue structures also showed good agreement between the LBTE solver and both MC and DVK with a median difference < 5% (maximum < 13%) for the DVH metrics with all three radionuclides. The largest difference in DVH metrics was for the D90 and D70 metric in lung and bone where the uptake was low. Here, the difference between LBTE and MC had a median value < 14% (maximum 23%) for bone and < 4% (maximum 37%) for lung, while the corresponding differences between LBTE and DVK were < 23% (maximum 31%) and < 67% (maximum 313%), respectively. For a typical patient with a matrix size of 166 × 166 × 129 (voxel size 3 × 3 × 3 mm3 ), voxel dosimetry using the LBTE solver was as fast as ∼2 min on a desktop computer.

CONCLUSION

Having established good agreement between the LBTE solver and MC for RPT and SIRT applications, the LBTE solver is a viable option for voxel dosimetry that can be faster than MC. Further analysis is being performed to encompass the broad range of radionuclides and conditions encountered clinically.

90Y SPECT scatter estimation and voxel dosimetry in radioembolization using a unified deep learning framework

PURPOSE

90Y SPECT-based dosimetry following radioembolization (RE) in liver malignancies is challenging due to the inherent scatter and the poor spatial resolution of bremsstrahlung SPECT. This study explores a deep-learning-based absorbed dose-rate estimation method for 90Y that mitigates the impact of poor SPECT image quality on dosimetry and the accuracy-efficiency trade-off of Monte Carlo (MC)-based scatter estimation and voxel dosimetry methods.

METHODS

Our unified framework consists of three stages: convolutional neural network (CNN)-based bremsstrahlung scatter estimation, SPECT reconstruction with scatter correction (SC) and absorbed dose-rate map generation with a residual learning network (DblurDoseNet). The input to the framework is the measured SPECT projections and CT, and the output is the absorbed dose-rate map. For training and testing under realistic conditions, we generated a series of virtual patient phantom activity/density maps from post-therapy images of patients treated with 90Y-RE at our clinic. To train the scatter estimation network, we use the scatter projections for phantoms generated from MC simulation as the ground truth (GT). To train the dosimetry network, we use MC dose-rate maps generated directly from the activity/density maps of phantoms as the GT (Phantom + MC Dose). We compared performance of our framework (SPECT w/CNN SC + DblurDoseNet) and MC dosimetry (SPECT w/CNN SC + MC Dose) using normalized root mean square error (NRMSE) and normalized mean absolute error (NMAE) relative to GT.

RESULTS

When testing on virtual patient phantoms, our CNN predicted scatter projections had NRMSE of 4.0% ± 0.7% on average. For the SPECT reconstruction with CNN SC, we observed a significant improvement on NRMSE (9.2% ± 1.7%), compared to reconstructions with no SC (149.5% ± 31.2%). In terms of virtual patient dose-rate estimation, SPECT w/CNN SC + DblurDoseNet had a NMAE of 8.6% ± 5.7% and 5.4% ± 4.8% in lesions and healthy livers, respectively; compared to 24.0% ± 6.1% and 17.7% ± 2.1% for SPECT w/CNN SC + MC Dose. In patient dose-rate maps, though no GT was available, we observed sharper lesion boundaries and increased lesion-to-background ratios with our framework. For a typical patient data set, the trained networks took ~ 1 s to generate the scatter estimate and ~ 20 s to generate the dose-rate map (matrix size: 512 × 512 × 194) on a single GPU (NVIDIA V100).

CONCLUSION

Our deep learning framework, trained using true activity/density maps, has the potential to outperform non-learning voxel dosimetry methods such as MC that are dependent on SPECT image quality. Across comprehensive testing and evaluations on multiple targeted lesions and healthy livers in virtual patients, our proposed deep learning framework demonstrated higher (66% on average in terms of NMAE) estimation accuracy than the current "gold-standard" MC method. The enhanced computing speed with our framework without sacrificing accuracy is highly relevant for clinical dosimetry following 90Y-RE.

The predictive value of pretherapy [68Ga]Ga-DOTA-TATE PET and biomarkers in [177Lu]Lu-PRRT tumor dosimetry

PURPOSE

Metastatic neuroendocrine tumors (NETs) overexpressing type 2 somatostatin receptors are the target for peptide receptor radionuclide therapy (PRRT) through the theragnostic pair of 68Ga/177Lu-DOTATATE. The main purpose of this study was to develop machine learning models to predict therapeutic tumor dose using pre therapy 68Ga -PET and clinicopathological biomarkers.

METHODS

We retrospectively analyzed 90 segmented metastatic NETs from 25 patients (M14/F11, age 63.7 ± 9.5, range 38-76) treated by 177Lu-DOTATATE at our institute. Patients underwent both pretherapy [68Ga]Ga-DOTA-TATE PET/CT and four timepoints SPECT/CT at  ~ 4, 24, 96, and 168 h post-177Lu-DOTATATE infusion. Tumors were segmented by a radiologist on baseline CT or MRI and transferred to co-registered PET/CT and SPECT/CT, and normal organs were segmented by deep learning-based method on CT of the PET and SPECT. The SUV metrics and tumor-to-normal tissue SUV ratios (SUV_TNRs) were calculated from 68Ga -PET at the contour-level. Posttherapy dosimetry was performed based on the co-registration of SPECT/CTs to generate time-integrated-activity, followed by an in-house Monte Carlo-based absorbed dose estimation. The correlation between delivered 177Lu Tumor absorbed dose and PET-derived metrics along with baseline clinicopathological biomarkers (such as Creatinine, Chromogranin A and prior therapies) were evaluated. Multiple interpretable machine-learning algorithms were developed to predict tumor dose using these pretherapy information. Model performance on a nested tenfold cross-validation was evaluated in terms of coefficient of determination (R2), mean-absolute-error (MAE), and mean-relative-absolute-error (MRAE).

RESULTS

SUVmean showed a significant correlation (q-value < 0.05) with absorbed dose (Spearman ρ = 0.64), followed by TLSUVmean (SUVmean of total-lesion-burden) and SUVpeak (ρ = 0.45 and 0.41, respectively). The predictive value of PET-SUVmean in estimation of posttherapy absorbed dose was stronger compared to PET-SUVpeak, and SUV_TNRs in terms of univariate analysis (R2 = 0.28 vs. R2 ≤ 0.12). An optimal trivariate random forest model composed of SUVmean, TLSUVmean, and total liver SUVmean (normal and tumoral liver) provided the best performance in tumor dose prediction with R2 = 0.64, MAE = 0.73 Gy/GBq, and MRAE = 0.2.

CONCLUSION

Our preliminary results demonstrate the feasibility of using baseline PET images for prediction of absorbed dose prior to 177Lu-PRRT. Machine learning models combining multiple PET-based metrics performed better than using a single SUV value and using other investigated clinicopathological biomarkers. Developing such quantitative models forms the groundwork for the role of 68Ga -PET not only for the implementation of personalized treatment planning but also for patient stratification in the era of precision medicine.

Stereotactic body radiation therapy (SBRT) following Yttrium-90 (90Y) selective internal radiation therapy (SIRT): a feasibility planning study using90Y delivered dose

Objective.⁹⁰Y selective internal radiation therapy (SIRT) treatment of hepatocellular carcinoma (HCC) can potentially underdose lesions, as identified on post-therapy PET/CT imaging. This study introduces a methodology and explores the feasibility for selectively treating SIRT-underdosed HCC lesions, or lesion subvolumes, with stereotactic body radiation therapy (SBRT) following post-SIRT dosimetry.Approach. We retrospectively analyzed post-treatment PET/CT images of 20 HCC patients after⁹⁰Y SIRT. Predicted tumor response from SIRT was quantified based on personalized post-therapy dosimetry and corresponding response models. Predicted non-responding tumor regions were then targeted with a hypothetical SBRT boost plan using a framework for selecting eligible tumors and tumor subregions. SBRT boost plans were compared to SBRT plans targeting all tumors irrespective of SIRT dose with the same prescription and organ-at-risk (OAR) objectives. The potential benefit of SIRT followed by a SBRT was evaluated based on OAR dose and predicted toxicity compared to the independent SBRT treatment.Main results. Following SIRT, 14/20 patients had at least one predicted non-responding tumor considered eligible for a SBRT boost. When comparing SBRT plans, 10/14 (71%) SBRT_boostand 12/20 (60%) SBRT_aloneplans were within OAR dose constraints. For three patients, SBRT_boostplans were within OAR constraints while SBRT_aloneplans were not. Across the 14 eligible patients, SBRT_boostplans had significantly less dose to the healthy liver (decrease in mean dose was on average ± standard deviation, 2.09 Gy ± 1.99 Gy, ) and reduced the overall targeted PTV volume (39% ± 21%) compared with SBRT_alone.Significance. A clinical methodology for treating HCC using a synergized SIRT and SBRT approach is presented, demonstrating that it could reduce normal tissue toxicity risk in a majority of our retrospectively evaluated cases. Selectively targeting SIRT underdosed HCC lesions, or lesion subvolumes, with SBRT could improve tumor control and patient outcomes post-SIRT and allow SIRT to function as a target debulking tool for cases when SBRT is not independently feasible.

Experimental validation of Monte Carlo dosimetry for therapeutic beta emitters with radiochromic film in a 3D-printed phantom

PURPOSE

Validation of dosimetry software, such as Monte Carlo (MC) radiation transport codes used for patient-specific absorbed dose estimation, is critical prior to their use in clinical decision making. However, direct experimental validation in the clinic is generally not performed for low/medium-energy beta emitters used in radiopharmaceutical therapy (RPT) due to the challenges of measuring energy deposited by short-range particles. Our objective was to design a practical phantom geometry for radiochromic film (RF)-based absorbed dose measurements of beta-emitting radionuclides and perform experiments to directly validate our in-house developed Dose Planning Method (DPM) MC code dedicated to internal dosimetry.

METHODS

The experimental setup was designed for measuring absorbed dose from beta emitters that have a range sufficiently penetrating to ∼200 μm in water as well as to capture any photon contributions to absorbed dose. Assayed ¹⁷⁷ Lu and ⁹⁰ Y liquid sources, 13-450 MBq estimated to deliver 0.5-10 Gy to the sensitive layer of the RF, were injected into the cavity of two 3D-printed half-cylinders that had been sealed with 12.7 μm or 25.4 μm thick Kapton Tape. A 3.8 × 6 cm strip of GafChromic EBT3 RF was sandwiched between the two taped half-cylinders. After 2-48 h exposures, films were retrieved and wipe tested for contamination. Absorbed dose to the RF was measured using a commercial triple-channel dosimetry optimization method and a calibration generated via 6 MV photon beam. Profiles were analyzed across the central 1 cm² area of the RF for validation. Eleven experiments were completed with ¹⁷⁷ Lu and nine with ⁹⁰ Y both in saline and a bone equivalent solution. Depth dose curves were generated for ¹⁷⁷ Lu and ⁹⁰ Y stacking multiple RF strips between a single filled half-cylinder and an acrylic backing. All experiments were modeled in DPM to generate voxelized MC absorbed dose estimates. We extended our study to benchmark general purpose MC codes MCNP6 and EGSnrc against the experimental results as well.

RESULTS

A total of 20 experiments showed that both the 3D-printed phantoms and the final absorbed dose values were reproducible. The agreement between the absorbed dose estimates from the RF measurements and DPM was on average -4.0% (range -10.9% to 3.2%) for all single film ¹⁷⁷ Lu experiments and was on average -1.0% (range -2.7% to 0.7%) for all single film ⁹⁰ Y experiments. Absorbed depth dose estimates by DPM agreed with RF on average 1.2% (range -8.0% to 15.2%) across all depths for ¹⁷⁷ Lu and on average 4.0% (range -5.0% to 9.3%) across all depths for ⁹⁰ Y. DPM absorbed dose estimates agreed with estimates from EGSnrc and MCNP across the board, within 4.7% and within 3.4% for ¹⁷⁷ Lu and ⁹⁰ Y respectively, for all geometries and across all depths. MC showed that absorbed dose to RF from betas was greater than 92% of the total (betas + other radiations) for ¹⁷⁷ Lu, indicating measurement of dominant beta contribution with our design.

CONCLUSIONS

The reproducible results with a RF insert in a simple phantom designed for liquid sources demonstrate that this is a reliable setup for experimentally validating dosimetry algorithms used in therapies with beta-emitting unsealed sources. Absorbed doses estimated with the DPM MC code showed close agreement with RF measurement and with results from two general purpose MC codes, thereby validating the use of this algorithms for clinical RPT dosimetry.

DblurDoseNet: A deep residual learning network for voxel radionuclide dosimetry compensating for single-photon emission computerized tomography imaging resolution

PURPOSE

Current methods for patient-specific voxel-level dosimetry in radionuclide therapy suffer from a trade-off between accuracy and computational efficiency. Monte Carlo (MC) radiation transport algorithms are considered the gold standard for voxel-level dosimetry but can be computationally expensive, whereas faster dose voxel kernel (DVK) convolution can be suboptimal in the presence of tissue heterogeneities. Furthermore, the accuracies of both these methods are limited by the spatial resolution of the reconstructed emission image. To overcome these limitations, this paper considers a single deep convolutional neural network (CNN) with residual learning (named DblurDoseNet) that learns to produce dose-rate maps while compensating for the limited resolution of SPECT images.

METHODS

We trained our CNN using MC-generated dose-rate maps that directly corresponded to the true activity maps in virtual patient phantoms. Residual learning was applied such that our CNN learned only the difference between the true dose-rate map and DVK dose-rate map with density scaling. Our CNN consists of a 3D depth feature extractor followed by a 2D U-Net, where the input was 11 slices (3.3 cm) of a given Lu-177 SPECT/CT image and density map, and the output was the dose-rate map corresponding to the center slice. The CNN was trained with nine virtual patient phantoms and tested on five different phantoms plus 42 SPECT/CT scans of patients who underwent Lu-177 DOTATATE therapy.

RESULTS

When testing on virtual patient phantoms, the lesion/organ mean dose-rate error and the normalized root mean square error (NRMSE) relative to the ground truth of the CNN method was consistently lower than DVK and MC, when applied to SPECT images. Compared to DVK/MC, the average improvement for the CNN in mean dose-rate error was 55%/53% and 66%/56%; and in NRMSE was 18%/17% and 10%/11% for lesion and kidney regions, respectively. Line profiles and dose-volume histograms demonstrated compensation for SPECT resolution effects in the CNN-generated dose-rate maps. The ensemble noise standard deviation, determined from multiple Poisson realizations, was improved by 21%/27% compared to DVK/MC. In patients, potential improvements from CNN dose-rate maps compared to DVK/MC were illustrated qualitatively, due to the absence of ground truth. The trained residual CNN took about 30 s on a single GPU (Tesla V100) to generate a 512 × 512 × 130 dose-rate map for a patient.

CONCLUSION

The proposed residual CNN, trained using phantoms generated from patient images, has potential for real-time patient-specific dosimetry in clinical treatment planning due to its demonstrated improvement in accuracy, resolution, noise, and speed over the DVK/MC approaches.

Absorbed dose distributions from beta-decaying radionuclides: Experimental validation of Monte Carlo tools for radiopharmaceutical dosimetry

PURPOSE

This study aims to experimentally validate the Monte Carlo generated absorbed doses from the beta particles emitted by ⁹⁰ Y and ¹⁷⁷ Lu using radiochromic EBT3 film-based dosimetry.

METHODS

Line sources of ⁹⁰ Y and ¹⁷⁷ Lu were inserted longitudinally through blocks of low-density polyethylene and tissue-equivalent slabs of cortical bone and lung equivalent plastics. Radiochromic film (Gafchromic EBT3) was laser cut to accommodate orthogonal line sources of radioactivity, and the film was sandwiched intimately between the rectangular blocks to achieve charged particle equilibrium. Line sources consisted of plastic capillary tube of length (13 ± 0.1) cm, with 0.42-mm inner diameter and a wall thickness of 0.21 mm. ⁹⁰ Y line sources were prepared from a solution of dissolved ⁹⁰ Y resin microspheres. ¹⁷⁷ Lu line sources were prepared from an aliquot of ¹⁷⁷ Lu-DOTATATE. Film exposures were conducted for durations ranging from 10 min to 38 h. Radiochromic film calibration was performed by irradiation with 6-MV-bremsstrahlung x rays from a calibrated linear accelerator, in accordance with literature recommendations. Experimental geometries were precisely simulated within the GATE Monte Carlo toolkit, which has previously been used for the generation of dose point kernels.

RESULTS

The mean percentage difference between measured and simulated absorbed doses were 5.04% and 7.21% for ⁹⁰ Y and ¹⁷⁷ Lu beta absorbed dose in the range of (0.1-10) Gy. Additionally, 1D gamma analysis using a local 10%/1 mm gamma criterion was performed to compare the absorbed dose distributions. The percentage of measurement points passing the gamma criterion, averaged over all tests, was 93.5%.

CONCLUSIONS

We report the experimental validation of Monte Carlo derived beta absorbed dose distributions for ⁹⁰ Y and ¹⁷⁷ Lu, solidifying the validity of using Monte Carlo-based methods for estimating absorbed dose from beta emitters. Overall, excellent agreement was observed between the experimental beta absorbed doses in the linear region of the radiochromic film and the GATE Monte Carlo simulations demonstrating that radiochromic film dosimetry has sufficient sensitivity and spatial resolution to be used as a tool for measuring beta decay absorbed dose distributions.

Preclinical Voxel-Based Dosimetry in Theranostics: a Review

Due to the increasing use of preclinical targeted radionuclide therapy (TRT) studies for the development of novel theranostic agents, several studies have been performed to accurately estimate absorbed doses to mice at the voxel level using reference mouse phantoms and Monte Carlo (MC) simulations. Accurate dosimetry is important in preclinical theranostics to interpret radiobiological dose-response relationships and to translate results for clinical use. Direct MC (DMC) simulation is believed to produce more realistic voxel-level dose distribution with high precision because tissue heterogeneities and nonuniform source distributions in patients or animals are considered. Although MC simulation is considered to be an accurate method for voxel-based absorbed dose calculations, it is time-consuming, computationally demanding, and often impractical in daily practice. In this review, we focus on the current status of voxel-based dosimetry methods applied in preclinical theranostics and discuss the need for accurate and fast voxel-based dosimetry methods for pretherapy absorbed dose calculations to optimize the dose computation time in preclinical TRT.

Prediction of Tumor Control in 90Y Radioembolization by Logit Models with PET/CT-Based Dose Metrics

The aim of this work was to develop models for tumor control probability (TCP) in radioembolization with ⁹⁰Y PET/CT-derived radiobiologic dose metrics. Methods: Patients with primary liver cancer or liver metastases who underwent radioembolization with glass microspheres were imaged with ⁹⁰Y PET/CT for voxel-level dosimetry to determine lesion absorbed dose (AD) metrics, biological effective dose (BED) metrics, equivalent uniform dose, and equivalent uniform BED for 28 treatments (89 lesions). The lesion dose-shrinkage correlation was assessed on the basis of RECIST and, when available, modified RECIST (mRECIST) at first follow-up. For a subset with mRECIST, logit regression TCP models were fit via maximum likelihood to relate lesion-level binary response to the dose metrics. As an exploratory analysis, the nontumoral liver dose-toxicity relationship was also evaluated. Results: Lesion dose-shrinkage analysis showed that there were no significant differences between model parameters for primary and metastatic subgroups and that correlation coefficients were superior with mRECIST. Therefore, subsequent TCP analysis was performed for the combined group using mRECIST only. The overall lesion-level mRECIST response rate was 57%. The AD and BED metrics yielding 50% TCP were 292 and 441 Gy, respectively. All dose metrics considered for TCP modeling, including mean AD, were significantly associated with the probability of response, with high areas under the curve (0.87-0.90, P < 0.0001) and high sensitivity (>0.75) and specificity (>0.83) calculated using a threshold corresponding to 50% TCP. Because nonuniform AD deposition by microspheres cannot be determined by PET at a microscopic scale, radiosensitivity values extracted here by fitting models to clinical response data were substantially lower than reported for in vitro cell cultures or for external-beam radiotherapy clinical studies. There was no correlation between nontumoral liver AD and toxicity measures. Conclusion: Despite the heterogeneous patient cohort, logistic regression TCP models showed a strong association between various dose metrics and the probability of response. The performance of mean AD was comparable to that of radiobiologic dose metrics that involve more complex calculations. These results demonstrate the importance of considering TCP in treatment planning for radioembolization.

Impact of 90Y PET gradient-based tumor segmentation on voxel-level dosimetry in liver radioembolization

BACKGROUND

The purpose was to validate ⁹⁰Y PET gradient-based tumor segmentation in phantoms and to evaluate the impact of the segmentation method on reported tumor absorbed dose (AD) and biological effective dose (BED) in ⁹⁰Y microsphere radioembolization (RE) patients. A semi-automated gradient-based method was applied to phantoms and patient tumors on the ⁹⁰Y PET with the initial bounding volume for gradient detection determined from a registered diagnostic CT or MR; this PET-based segmentation (PS) was compared with radiologist-defined morphologic segmentation (MS) on CT or MRI. AD and BED volume histogram metrics (D90, D70, mean) were calculated using both segmentations and concordance/correlations were investigated. Spatial concordance was assessed using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). PS was repeated to assess intra-observer variability.

RESULTS

In phantoms, PS demonstrated high accuracy in lesion volumes (within 15%), AD metrics (within 11%), high spatial concordance relative to morphologic segmentation (DSC > 0.86 and MDA < 1.5 mm), and low intra-observer variability (DSC > 0.99, MDA < 0.2 mm, AD/BED metrics within 2%). For patients (58 lesions), spatial concordance between PS and MS was degraded compared to in-phantom (average DSC = 0.54, average MDA = 4.8 mm); the average mean tumor AD was 226 ± 153 and 197 ± 138 Gy, respectively for PS and MS. For patient AD metrics, the best Pearson correlation (r) and concordance correlation coefficient (ccc) between segmentation methods was found for mean AD (r = 0.94, ccc = 0.92), but worsened as the metric approached the minimum dose (for D90, r = 0.77, ccc = 0.69); BED metrics exhibited a similar trend. Patient PS showed low intra-observer variability (average DSC = 0.81, average MDA = 2.2 mm, average AD/BED metrics within 3.0%).

CONCLUSIONS

⁹⁰Y PET gradient-based segmentation led to accurate/robust results in phantoms, and showed high concordance with MS for reporting mean tumor AD/BED in patients. However, tumor coverage metrics such as D90 exhibited worse concordance between segmentation methods, highlighting the need to standardize segmentation methods when reporting AD/BED metrics from post-therapy ⁹⁰Y PET. Estimated differences in reported AD/BED metrics due to segmentation method will be useful for interpreting RE dosimetry results in the literature including tumor response data.

Beyond Dose: Using Pretherapy Biomarkers to Improve Dose Prediction of Outcomes for Radioimmunotherapy of Non-Hodgkin Lymphoma

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.

Three-Dimensional Dosimetry for Radiation Safety Estimates from Intrathecal Administration

Intrathecal administration is of growing interest for drug delivery, and its utility is being increasingly investigated through imaging. In this work, the 3-dimensional Voxel-Based Internal Dosimetry Application (VIDA) and 4D Extended Cardiac Torso Phantom (XCAT) were extended to provide radiation safety estimates specific to intrathecal administration. Methods: The 3-dimensional VIDA dosimetry application Monte Carlo simulation was run using a modified XCAT phantom with additional and edited cerebrospinal fluid (CSF) regions to produce voxel-level absorbed dose per unit cumulated activity maps for 9 selected source regions. Simulation validation was performed to compare absorbed dose estimates for common organs in a preexisting dosimetry tool (OLINDA/EXM). Dynamic planar imaging data were acquired in 6 healthy subjects using administered volumes of 5 or 15 mL (n = 3 each) of 185 MBq of ^99mTc-diethylenetriaminepentaacetic acid. Absorbed dose was estimated for each subject using the intrathecal-specific dosimetry application. Results: Simulation results were within 6% of OLINDA estimates for common organs. Absorbed dose estimates were highest (0.3-0.8 mGy/MBq) in the lumbar CSF space. A whole-body effective dose estimate of 0.003 mSv/MBq was observed. An administered volume dependency was observed with a 15-mL volume, resulting in lower absorbed dose estimates for several intrathecal and nonintrathecal regions. Conclusion: The intrathecal-specific VIDA implementation enables tailored dosimetry estimation for regions most relevant in intrathecal administration. Absorbed doses are highly localized to CSF and spinal regions and should be taken into consideration when designing intrathecal imaging studies. A potentially interesting relationship was observed between absorbed dose and administered volume, which merits further investigation.

A 3D Monte Carlo Method for Estimation of Patient-specific Internal Organs Absorbed Dose for (99m)Tc-hynic-Tyr(3)-octreotide Imaging

Single-photon emission computed tomography (SPECT)-based tracers are easily available and more widely used than positron emission tomography (PET)-based tracers, and SPECT imaging still remains the most prevalent nuclear medicine imaging modality worldwide. The aim of this study is to implement an image-based Monte Carlo method for patient-specific three-dimensional (3D) absorbed dose calculation in patients after injection of ^99mTc-hydrazinonicotinamide (hynic)-Tyr³-octreotide as a SPECT radiotracer. ^99mTc patient-specific S values and the absorbed doses were calculated with GATE code for each source-target organ pair in four patients who were imaged for suspected neuroendocrine tumors. Each patient underwent multiple whole-body planar scans as well as SPECT imaging over a period of 1-24 h after intravenous injection of ^99mhynic-Tyr³-octreotide. The patient-specific S values calculated by GATE Monte Carlo code and the corresponding S values obtained by MIRDOSE program differed within 4.3% on an average for self-irradiation, and differed within 69.6% on an average for cross-irradiation. However, the agreement between total organ doses calculated by GATE code and MIRDOSE program for all patients was reasonably well (percentage difference was about 4.6% on an average). Normal and tumor absorbed doses calculated with GATE were slightly higher than those calculated with MIRDOSE program. The average ratio of GATE absorbed doses to MIRDOSE was 1.07 ± 0.11 (ranging from 0.94 to 1.36). According to the results, it is proposed that when cross-organ irradiation is dominant, a comprehensive approach such as GATE Monte Carlo dosimetry be used since it provides more reliable dosimetric results.

VIDA: a voxel-based dosimetry method for targeted radionuclide therapy using Geant4

We have developed the Voxel-Based Internal Dosimetry Application (VIDA) to provide patient-specific dosimetry in targeted radionuclide therapy performing Monte Carlo simulations of radiation transport with the Geant4 toolkit. The code generates voxel-level dose rate maps using anatomical and physiological data taken from individual patients. Voxel level dose rate curves are then fit and integrated to yield a spatial map of radiation absorbed dose. In this article, we present validation studies using established dosimetry results, including self-dose factors (DFs) from the OLINDA/EXM program for uniform activity in unit density spheres and organ self- and cross-organ DFs in the Radiation Dose Assessment Resource (RADAR) reference adult phantom. The comparison with reference data demonstrated agreement within 5% for self-DFs to spheres and reference phantom source organs for four common radionuclides used in targeted therapy ((131)I, (90)Y, (111)In, (177)Lu). Agreement within 9% was achieved for cross-organ DFs. We also present dose estimates to normal tissues and tumors from studies of two non-Hodgkin Lymphoma patients treated by (131)I radioimmunotherapy, with comparison to results generated independently with another dosimetry code. A relative difference of 12% or less was found between methods for mean absorbed tumor doses accounting for tumor regression.

Tumor-Absorbed Dose Predicts Progression-Free Survival Following (131)I-Tositumomab Radioimmunotherapy

The study aimed at identifying patient-specific dosimetric and nondosimetric factors predicting outcome of non-Hodgkin lymphoma patients after (131)I-tositumomab radioimmunotherapy for potential use in treatment planning.

METHODS

Tumor-absorbed dose measures were estimated for 130 tumors in 39 relapsed or refractory non-Hodgkin lymphoma patients by coupling SPECT/CT imaging with the Dose Planning Method (DPM) Monte Carlo code. Equivalent biologic effect was calculated to assess the biologic effects of nonuniform absorbed dose including the effects of the unlabeled antibody. Evaluated nondosimetric covariates included histology, presence of bulky disease, and prior treatment history. Tumor level outcome was based on volume shrinkage assessed on follow-up CT. Patient level outcome measures were overall response (OR), complete response (CR), and progression-free survival (PFS), determined from clinical assessments that included PET/CT.

RESULTS

The estimated mean tumor-absorbed dose had a median value of 275 cGy (range, 94-711 cGy). A high correlation was observed between tracer-predicted and therapy-delivered mean tumor-absorbed doses (P < 0.001; r = 0.85). In univariate tumor-level analysis, tumor shrinkage correlated significantly with almost all of the evaluated dosimetric factors, including equivalent biologic effect. Regression analysis showed that OR, CR, and PFS were associated with the dosimetric factors and equivalent biologic effect. Both mean tumor-absorbed dose (P = 0.025) and equivalent biologic effect (P = 0.035) were significant predictors of PFS whereas none of the nondosimetric covariates were found to be statistically significant factors affecting PFS. The most important finding of the study was that in Kaplan-Meier curves stratified by mean dose, longer PFS was observed in patients receiving mean tumor-absorbed doses greater than 200 cGy than in those receiving 200 cGy or less (median PFS, 13.6 vs. 1.9 mo for the 2 dose groups; log-rank P < 0.0001).

CONCLUSION

A higher mean tumor-absorbed dose was significantly predictive of improved PFS after (131)I-tositumomab radioimmunotherapy. Hence tumor-absorbed dose, which can be estimated before therapy, can potentially be used to design radioimmunotherapy protocols to improve efficacy.

Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images

Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 10(8) primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3–4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image-based dosimetry in nuclear medicine.

MIRD pamphlet No. 24: Guidelines for quantitative 131I SPECT in dosimetry applications

The reliability of radiation dose estimates in internal radionuclide therapy is directly related to the accuracy of activity estimates obtained at each imaging time point. The recently published MIRD pamphlet no. 23 provided a general overview of quantitative SPECT imaging for dosimetry. The present document is the first in a series of isotope-specific guidelines that will follow MIRD 23 and focuses on one of the most commonly used therapeutic radionuclides, (131)I. The purpose of this document is to provide guidance on the development of protocols for quantitative (131)I SPECT in radionuclide therapy applications that require regional (normal organs, lesions) and 3-dimensional dosimetry.

Biological-effect modeling of radioimmunotherapy for non-hodgkins lymphoma: determination of model parameters

Treatment with Tositumomab and 131I tositumomab anti-CD20 radioimmunotherapy (Bexxar) yields a nonradioactive antibody antitumor response (the so-called cold effect) and a radiation response. Numerical parameter determination by least-squares (LS) fitting was implemented for more accurate parameter estimates in equivalent biological-effect calculations.

METHODS

One hundred thirty-two tumors in 37 patients were followed using five or six SPECT/CT studies per patient, three each (typical) post-tracer (0.2 GBq) and post-therapy (∼3 GBq) injections. The SPECT/CT data were used to calculate position- and time-dependent dose rates and antibody concentrations for each tumor. CT-defined tumor volumes were used to track tumor volume changes. Combined biological-effect and cell-clearance models were fit to tumor volume changes. Optimized parameter values determined using LS fitting were compared to previous fitted values that were determined by matching calculated to measured tumor volume changes using visual assessment. Absorbed dose sensitivity (α) and cold-effect sensitivity (λp) parameters were the primary fitted parameters, yielding equivalent biological-effect (E) values.

RESULTS

Individual parameter uncertainties were approximately 10% and 30% for α and λp, respectively. LS versus previously fit parameter values were highly correlated, although the averaged α value decreased and the averaged λp value increased for the LS fits compared to the previous fits. Correlation of E with 2-month tumor shrinkage data was similar for the two fitting techniques. The LS fitting yielded improved fit quality and likely improved parameter estimation.

Investigation of effect of variations in bone fraction and red marrow cellularity on bone marrow dosimetry in radio-immunotherapy

A method is described for computing patient-specific absorbed dose rates to active marrow which accounts for spatial variation in bone volume fraction and marrow cellularity. A module has been added to the 3D Monte Carlo dosimetry program DPM to treat energy deposition in the components of bone spongiosa distinctly. Homogeneous voxels in regions containing bone spongiosa (as defined on CT images) are assumed to be comprised only of bone, active (red) marrow and inactive (yellow) marrow. Cellularities are determined from biopsy, and bone volume fractions are computed from cellularities and CT-derived voxel densities. Electrons are assumed to deposit energy locally in the three constituent components in proportions determined by electron energy absorption fractions which depend on energy, cellularity, and bone volume fraction, and which are either taken from the literature or are derived from Monte Carlo simulations using EGS5. Separate algorithms are used to model primary β particles and secondary electrons generated after photon interactions. Treating energy deposition distinctly in bone spongiosa constituents leads to marrow dosimetry results which differ from homogeneous spongiosa dosimetry by up to 20%. Dose rates in active marrow regions with cellularities of 20, 50, and 80% can vary by up to 20%, and can differ by up to 10% as a function of bone volume fraction. Dose to bone marrow exhibits a strong dependence on marrow cellularity and a potentially significant dependence on bone volume fraction.

Prediction of therapy tumor-absorbed dose estimates in I-131 radioimmunotherapy using tracer data via a mixed-model fit to time activity

BACKGROUND

For individualized treatment planning in radioimmunotherapy (RIT), correlations must be established between tracer-predicted and therapy-delivered absorbed doses. The focus of this work was to investigate this correlation for tumors.

METHODS

The study analyzed 57 tumors in 19 follicular lymphoma patients treated with I-131 tositumomab and imaged with SPECT/CT multiple times after tracer and therapy administrations. Instead of the typical least-squares fit to a single tumor's measured time-activity data, estimation was accomplished via a biexponential mixed model in which the curves from multiple subjects were jointly estimated. The tumor-absorbed dose estimates were determined by patient-specific Monte Carlo calculation.

RESULTS

The mixed model gave realistic tumor time-activity fits that showed the expected uptake and clearance phases even with noisy data or missing time points. Correlation between tracer and therapy tumor-residence times (r=0.98; p<0.0001) and correlation between tracer-predicted and therapy-delivered mean tumor-absorbed doses (r=0.86; p<0.0001) were very high. The predicted and delivered absorbed doses were within ± 25% (or within ± 75 cGy) for 80% of tumors.

CONCLUSIONS

The mixed-model approach is feasible for fitting tumor time-activity data in RIT treatment planning when individual least-squares fitting is not possible due to inadequate sampling points. The good correlation between predicted and delivered tumor doses demonstrates the potential of using a pretherapy tracer study for tumor dosimetry-based treatment planning in RIT.

Development and validation of RAYDOSE: a Geant4-based application for molecular radiotherapy

We developed and validated a Monte-Carlo-based application (RAYDOSE) to generate patient-specific 3D dose maps on the basis of pre-treatment imaging studies. A CT DICOM image is used to model patient geometry, while repeated PET scans are employed to assess radionuclide kinetics and distribution at the voxel level. In this work, we describe the structure of this application and present the tests performed to validate it against reference data and experiments. We used the spheres of a NEMA phantom to calculate S values and total doses. The comparison with reference data from OLINDA/EXM showed an agreement within 2% for a sphere size above 2.8 cm diameter. A custom heterogeneous phantom composed of several layers of Perspex and lung equivalent material was used to compare TLD measurements of gamma radiation from (131)I to Monte Carlo simulations. An agreement within 5% was found. RAYDOSE has been validated against reference data and experimental measurements and can be a useful multi-modality platform for treatment planning and research in MRT.

Minor changes in effective half-life during fractionated 177Lu-octreotate therapy

AIMS

Fractionated (177)Lu-DOTA-octreotate therapy has been reported to be an effective treatment option for patients with generalized neuroendocrine tumors. In our clinic, full individual dosimetry is performed during the first therapy cycle, while dosimetry at later cycles is based on the 24 h uptake measurement assuming an unchanged effective half-life. Our aim was to evaluate this assumption and the variation in the 24 h uptake during therapy.

PATIENTS

Thirty patients, 13 women and 17 men, were included in the study.

METHODS

During the first therapy cycle the (177)Lu-concentration was measured with SPECT/CT over the abdomen at 24 h, 96 h and 168 h after infusion. The effective half-life was determined for the kidneys, liver and spleen. The procedure was repeated at cycle 4 or 5.

RESULTS

The median ratio between the effective half-lives of the latter and the first cycle was 0.97 and 1.01 for the right and left kidney, with a range of 0.89-1.01 (1st-3rd quartile) and 0.93-1.05, respectively.

DISCUSSION

The mean value of the ratios was slightly lower than one, indicating a tendency towards increased activity elimination during therapy. In individual patients, significant changes were found for all organs, often when a large tumor burden reduction occurred during treatment. Possible contributing factors appeared to be larger amounts of non-tumor bound tracer, improved organ function (kidneys), decrease of vessel obstruction (spleen), less scatter from large tumors and reduction of small metastases (liver and spleen).

CONCLUSION

With most patients it is safe to estimate absorbed doses to kidneys, liver and spleen from 24 h activity concentration assuming an unchanged effective half-life during therapy. Patients with risk factors for kidney dysfunction need to be monitored in more detail. Simplified dosimetry based on the assumption of unchanged effective half-life can function as guidance to the number of therapy cycles an individual patient can tolerate.

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.

Bio-effect model applied to 131I radioimmunotherapy of refractory non-Hodgkin's lymphoma

PURPOSE

Improved data collection methods have improved absorbed dose estimation by tracking activity distributions and tumor extent at multiple time points, allowing individualized absorbed dose estimation. Treatment with tositumomab and (131)I-tositumomab anti-CD20 radioimmunotherapy (BEXXAR) yields a cold antibody antitumor response (cold protein effect) and a radiation response. Biologically effective contributions, including the cold protein effect, are included in an equivalent biological effect model that was fit to patient data.

METHODS

Fifty-seven tumors in 19 patients were followed using 6 single proton emission computed tomography (SPECT)/CT studies, 3 each post tracer (5 mCi) and therapy (∼100 mCi) injections with tositumomab and (131)I-tositumomab. Both injections used identical antibody mass, a flood dose of 450 mg plus 35 mg of (131)I tagged antibody. The SPECT/CT data were used to calculate absorbed dose rate distributions and tumor and whole-body time-activity curves, yielding a space-time dependent absorbed dose rate description for each tumor. Tumor volume outlines on CT were used to derive the time dependence of tumor size for tracer and therapy time points. A combination of an equivalent biological effect model and an inactivated cell clearance model was used to fit absorbed dose sensitivity and cold effect sensitivity parameters to tumor shrinkage data, from which equivalent therapy values were calculated.

RESULTS

Patient responses were categorized into three groups: standard radiation sensitivity with no cold effect (7 patients), standard radiation sensitivity with cold effect (11 patients), and high radiation sensitivity with cold effect (1 patient).

CONCLUSION

Fit parameters can be used to categorize patient response, implying a potential predictive capability.

131I-tositumomab radioimmunotherapy: initial tumor dose-response results using 3-dimensional dosimetry including radiobiologic modeling

For optimal treatment planning in radionuclide therapy, robust tumor dose-response correlations must be established. Here, fully 3-dimensional (3D) dosimetry was performed coupling SPECT/CT at multiple time points with Monte Carlo-based voxel-by-voxel dosimetry to examine such correlations.

METHODS

Twenty patients undergoing (131)I-tositumomab for the treatment of refractory B-cell lymphoma volunteered for the study. Sixty tumors were imaged. Activity quantification and dosimetry were performed using previously developed 3D algorithms for SPECT reconstruction and absorbed dose estimation. Tumors were outlined on CT at multiple time points to obtain absorbed dose distributions in the presence of tumor deformation and regression. Equivalent uniform dose (EUD) was calculated to assess the biologic effects of the nonuniform absorbed dose, including the cold antibody effect. Response for correlation analysis was determined on the basis of the percentage reduction in the product of the largest perpendicular tumor diameters on CT at 2 mo. Overall response classification (as complete response, partial response, stable disease, or progressive disease) used for prediction analysis was based on criteria that included findings on PET.

RESULTS

Of the evaluated tumor-absorbed dose summary measures (mean absorbed dose, EUD, and other measures from dose-volume histogram analysis), a statistically significant correlation with response was seen only with EUD (r = 0.36 and P = 0.006 at the individual tumor level; r = 0.46 and P = 0.048 at the patient level). The median value of mean absorbed dose for stable disease, partial response, and complete response patients was 196, 346, and 342 cGy, respectively, whereas the median value of EUD for each of these categories was 170, 363, and 406 cGy, respectively. At a threshold of 200 cGy, both mean absorbed dose and EUD had a positive predictive value for responders (partial response + complete response) of 0.875 (14/16) and a negative predictive value of 1.0 (3/3).

CONCLUSION

Improved dose-response correlations were demonstrated when EUD incorporating the cold antibody effect was used instead of the conventionally used mean tumor-absorbed dose. This work demonstrates the importance of 3D calculation and radiobiologic modeling when estimating absorbed dose for correlation with outcome.

Methodology to incorporate biologically effective dose and equivalent uniform dose in patient-specific 3-dimensional dosimetry for non-Hodgkin lymphoma patients targeted with 131I-tositumomab therapy

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.

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.

Effect of voxel size and computation method on Tc-99m MAA SPECT/CT-based dose estimation for Y-90 microsphere therapy

The use of selective internal radiation therapy for treatment of hepatocellular carcinoma and liver metastases using Y-90 labeled microspheres has become an effective and widely used treatment regimen. However, dosimetric evaluations of this treatment are still primitive as uniform distribution models based only on injected activity are often used. This investigation attempts to quantify the effectiveness of several sophisticated patient-specific techniques which utilize the source distribution of Tc-99m MAA simulation studies to perform voxelized dosimetric computations. Among these techniques are complete Monte-Carlo radiation transport computation in patient-specific CT-based voxel phantoms, local energy deposition in patient specific phantoms and kernel transport techniques in water. Each technique was evaluated using three different phantom voxel dimensions and SPECT reconstruction matrix sizes. Dose evaluation results using all methods were compared to the exact solution, obtained using fully 3-D Monte-Carlo simulations with source distribution based not on SPECT data, but on the injected activity and exact boundaries of the anthropomorphic phantom used in the study. The results of this study show that at large voxel sizes and using SPECT reconstructions with a small matrix size (64 x 64), Monte-Carlo and local deposition methods are nearly equivalent. However, using a large SPECT reconstruction matrix (256 x 256) the local deposition method is significantly more accurate than full 3-D Monte-Carlo transport, and with a negligible computational burden.

Thyroid carcinoma metastasis to skull with infringement of brain: treatment with radioiodine

BACKGROUND

Infringement by differentiated thyroid carcinoma on the brain is rare but, when suspected, the patient deserves special attention. A patient with an enlarging metastasis of thyroid carcinoma to the skull that was impinging on the brain illustrates diagnostic and therapeutic strategies applicable to the treatment of metastatic carcinoma.

METHODS

A case study was performed. Computed tomography (CT) and magnetic resonance imaging (MRI) were done, serum thyroglobulin was measured, and tumor responses to thyroxine and (131)I treatments were monitored. Tumor dosimetry, enabled by scintigraphy with (131)I employing single photon emission tomography fused with CT (SPECT-CT), was performed.

RESULTS

The metastasis was from a follicular variant of papillary thyroid carcinoma. During thyrotropin stimulation the tumor enlarged. The tumor decreased in volume after each of two (131)I therapies. Dosimetry indicated delivery of 1970 and 2870 cGy to the tumor and 35 and 42 cGy to the brain, respectively, in the two treatments. The patient has survived for more than 11 years since diagnosis.

CONCLUSIONS

A metastasis from a follicular variant of papillary carcinoma increased in volume during hypothyroidism producing more infringement on the brain. Beyond the effects of thyroxine therapy, (131)I treatments induced recession of tumor volume. In patients with metastases that concentrate (131)I, dosimetry with SPECT-CT can predict absorbed doses of radiation to the tumor and to the adjacent organs and thus lay a basis for data-based decisions on (131)I therapies. Therapy may induce prolonged survival in patients with metastases infringing on the brain.