Three-dimensional Monte Carlo-based voxel-wise tumor dosimetry in patients with neuroendocrine tumors who underwent 177Lu-DOTATOC therapy.

BACKGROUND: Patients with advanced neuroendocrine tumors (NETs) of the midgut are suitable candidates for 177Lu-DOTATOC therapy. Integrated SPECT/CT systems have the potential to help improve the accuracy of patient-specific tumor dosimetry. Dose estimations to target organs are generally performed using the Medical Internal Radiation Dose scheme. We present a novel Monte Carlo-based voxel-wise dosimetry approach to determine organ- and tumor-specific total tumor doses (TTD). METHODS: A cohort of 14 patients with histologically confirmed metastasized NETs of the midgut (11 men, 3 women, 62.3 ± 11.0 years of age) underwent a total of 39 cycles of 177Lu-DOTATOC therapy (mean 2.8 cycles, SD ± 1 cycle). After the first cycle of therapy, regions of interest were defined manually on the SPECT/CT images for the kidneys, the spleen, and all 198 tracer-positive tumor lesions in the field of view. Four SPECT images, taken at 4 h, 24 h, 48 h and 72 h after injection of the radiopharmaceutical, were used to determine their effective half-lives in the structures of interest. The absorbed doses were calculated by a three-dimensional dosimetry method based on Monte Carlo simulations. TTD was calculated as the sum of all products of single tumor doses with single tumor volumes divided by the sum of all tumor volumes. RESULTS: The average dose values per cycle were 3.41 ± 1.28 Gy (1.91-6.22 Gy) for the kidneys, 4.40 ± 2.90 Gy (1.14-11.22 Gy) for the spleen, and 9.70 ± 8.96 Gy (1.47-39.49 Gy) for all 177Lu-DOTATOC-positive tumor lesions. Low- and intermediate-grade tumors (G 1-2) absorbed a higher TTD compared to high-grade tumors (G 3) (signed-rank test, p = < 0.05). The pre-therapeutic chromogranin A (CgA) value and the TTD correlated significantly (Pearson correlation: = 0.67, p = 0.01). Higher TTD resulted in a significant decrease of CgA after therapy. CONCLUSION: These results suggest that Monte Carlo-based voxel-wise dosimetry is a very promising tool for predicting the absorbed TTD based on histological and clinical parameters.

A comparison of methods for adapting [Formula: see text] dose-voxel-kernels to tissue inhomogeneities.

In [Formula: see text] radionuclide therapies, dosimetry is used for determining patient-individual dose burden. Standard approaches provide whole organ doses only. For assessing dose heterogeneity inside organs, voxel-wise dosimetry based on 3D SPECT/CT imaging could be applied. Often, this is achieved by convolving voxel-wise time-activity-curves with appropriate dose-voxel-kernels (DVK). The DVKs are meant to model dose deposition, and can be more accurate if modelled for the specific tissue type under consideration. In literature, DVKs are often not adapted to these inhomogeneities, or simple approximation schemes are applied. For 26 patients, which had previously undergone a [Formula: see text] -PSMA or -DOTATOC therapy, decay maps, mass-density maps as well as tissue-type maps were derived from SPECT/CT acquisitions. These were used for a voxel-based dosimetry based on convolution with DVKs (each of size [Formula: see text]) obtained by four different DVK methods proposed in literature. The simplest only considers a spatially constant soft-tissue DVK (herein named 'constant'), while others either take into account only the local density of the center voxel of the DVK (herein named 'center-voxel') or scale each voxel linearly according to the proper mass density deduced from the CT image (herein named 'density') or considered both the local mass density as well as the direct path between the center voxel and any voxel in its surrounding (herein named 'percentage'). Deviations between resulting dose values and those from full Monte-Carlo simulations (MC simulations) were compared for selected organs and tissue-types. For each DVK method, inter-patient variability was considerable showing both under- and over-estimation of energy dose compared to the MC result for all tissue densities higher than soft tissue. In kidneys and spleen, 'constant' and 'density'-scaled DVKs achieved estimated doses with smallest deviations to the full MC gold standard (∼[Formula: see text] underestimation). For low and high density tissue types such as lung and adipose or bone tissue, alternative DVK methods like 'center-voxel'- and 'percentage'- scaled achieved superior results, respectively. Concerning computational load, dose estimation with the DVK method 'constant' needs about 1.1 s per patient, center-voxel scaling amounts to 1.2 s, density scaling needs 1.4 s while percentage scaling consumes 860.3 s per patient. In this study encompassing a large patient cohort and four different DVK estimation methods, no single DVK-adaption method was consistently better than any other in case of soft tissue kernels. Hence in such cases the simplest DVK method, labeled 'constant', suffices. In case of tumors, often located in tissues of low (lung) or high (bone) density, more sophisticated DVK methods excel. The high inter-patient variability indicates that for evaluating new algorithms, a sufficiently large patient cohort needs to be involved.

Factors affecting accuracy of S values and determination of time-integrated activity in clinical Lu-177 dosimetry.

INTRODUCTION: In any radiotherapy, the absorbed dose needs to be estimated based on two factors, the time-integrated activity of the administered radiopharmaceutical and the patient-specific dose kernel. In this study, we consider the uncertainty with which such absorbed dose estimation can be achieved in a clinical environment. METHODS: To calculate the total error of dose estimation we considered the following aspects: The error resulting from computing the time-integrated activity, the difference between the S-value and the patient specific full Monte Carlo simulation, the error from segmenting the volume-of-interest (kidney) and the intrinsic error of the activimeter. RESULTS: The total relative error in dose estimation can amount to 25.0% and is composed of the error of the time-integrated activity 17.1%, the error of the S-value 16.7%, the segmentation error 5.4% and the activimeter accuracy 5.0%. CONCLUSION: Errors from estimating the time-integrated activity and approximations applied to dose kernel computations contribute about equally and represent the dominant contributions far exceeding the contributions from VOI segmentation and activimeter accuracy.

GATE Monte Carlo simulations for variations of an integrated PET/MR hybrid imaging system based on the Biograph mMR model.

A simulation toolkit, GATE (Geant4 Application for Tomographic Emission), was used to develop an accurate Monte Carlo (MC) simulation of a fully integrated 3T PET/MR hybrid imaging system (Siemens Biograph mMR). The PET/MR components of the Biograph mMR were simulated in order to allow a detailed study of variations of the system design on the PET performance, which are not easy to access and measure on a real PET/MR system. The 3T static magnetic field of the MR system was taken into account in all Monte Carlo simulations. The validation of the MC model was carried out against actual measurements performed on the PET/MR system by following the NEMA (National Electrical Manufacturers Association) NU 2-2007 standard. The comparison of simulated and experimental performance measurements included spatial resolution, sensitivity, scatter fraction, and count rate capability. The validated system model was then used for two different applications. The first application focused on investigating the effect of an extension of the PET field-of-view on the PET performance of the PET/MR system. The second application deals with simulating a modified system timing resolution and coincidence time window of the PET detector electronics in order to simulate time-of-flight (TOF) PET detection. A dedicated phantom was modeled to investigate the impact of TOF on overall PET image quality. Simulation results showed that the overall divergence between simulated and measured data was found to be less than 10%. Varying the detector geometry showed that the system sensitivity and noise equivalent count rate of the PET/MR system increased progressively with an increasing number of axial detector block rings, as to be expected. TOF-based PET reconstructions of the modeled phantom showed an improvement in signal-to-noise ratio and image contrast to the conventional non-TOF PET reconstructions. In conclusion, the validated MC simulation model of an integrated PET/MR system with an overall accuracy error of less than 10% can now be used for further MC simulation applications such as development of hardware components as well as for testing of new PET/MR software algorithms, such as assessment of point-spread function-based reconstruction algorithms.

Quantitative SPECT/CT Imaging of (177)Lu with In Vivo Validation in Patients Undergoing Peptide Receptor Radionuclide Therapy.

PURPOSE: The purpose of this study is to extend an established SPECT/CT quantitation protocol to (177)Lu and validate it in vivo using urine samples, thus providing a basis for 3D dosimetry of (177)Lu radiotherapy and improvement over current planar methods which improperly account for anatomical variations, attenuation, and overlapping organs. PROCEDURES: In our quantitation protocol, counts in images reconstructed using an ordered subset-expectation maximization algorithm are converted to kilobecquerels per milliliter using a calibration factor derived from a phantom experiment. While varying reconstruction parameters, we tracked the ratio of image to true activity concentration (recovery coefficient, RC) in hot spheres and a noise measure in a homogeneous region. The optimal parameter set was selected as the point where recovery in the largest three spheres (16, 8, and 4 ml) stagnated, while the noise continued to increase. Urine samples were collected following 12 SPECT/CT acquisitions of patients undergoing [(177)Lu]DOTATATE therapy, and activity concentrations were measured in a well counter. Data was reconstructed using parameters chosen in the phantom experiment, and estimated activity concentration from the images was compared to the urine values to derive RCs. RESULTS: In phantom data, our chosen parameter set yielded RCs in 16, 8, and 4 ml spheres of 80.0, 74.1, and 64.5 %, respectively. For patients, the mean bladder RC was 96.1 ± 13.2% (range, 80.6-122.4 %), with a 95 % confidence interval between 88.6 and 103.6 %. The mean error of SPECT/CT concentrations was 10.1 ± 8.3% (range, -19.4-22.4 %). CONCLUSIONS: Our results show that quantitative (177)Lu SPECT/CT in vivo is feasible but could benefit from improved reconstruction methods. Quantifying bladder activity is analogous to determining the amount of activity in the kidneys, an important task in dosimetry, and our results provide a useful benchmark for future efforts.

Multimodality approach in cryptogenic epilepsy with focus on morphometric 3T MRI.

PURPOSE: This study aimed to investigate the potential contribution of morphometric MRI analysis in comparison to other modalities, such as MEG, SPECT and PET, in identifying the epileptogenic focus in patients with cryptogenic epilepsy. PATIENTS AND METHODS: Study inclusion was limited to epilepsy patients with a monolobar focus hypothesis, as concluded from EEG/seizure semiology and the best individual concordance rate. Feature maps, generated by the MATLAB(®) "morphometric analysis program" (MAP), were evaluated by a neuroradiologist blinded to conventional MRI and the focus hypothesis (MAP(1)). In addition, the feature maps were also interpreted by simultaneous matching conventional MRI but, again, with the reader having no knowledge of the focus hypothesis (MAP(2)). RESULTS: In 12 out of 51 patients, true-positive findings were achieved (MAP(1): sensitivity 24%; specificity 96%). The sensitivity of the MAP(1) results was superior extratemporally. After matching conventional MRI, FCD was traced in six of the 12 patients (MAP(2): sensitivity 12%; specificity 100%). MEG sensitivity was 62%. Sensitivity of interictal and ictal SPECT was 20% and 50%, respectively. PET was not as sensitive extratemporally (19%) as temporally (82%). The greatest correspondence with the best individual concordance rate was noted with PET (14/16; 88%) and MEG (8/10; 80%), followed by interictal (5/8; 63%) and ictal (9/15; 60%) SPECT. Results for MAP(1) were 53% (10/19), and 100% for MAP(2) (6/6). CONCLUSION: Although MAP sensitivity and specificity results are lower in comparison to other modalities, implementation of the technique should be considered first, before arranging any further investigations. The present study results offer guidelines for the implementation, interpretation and concordance of diagnostic procedures.

Anatomical accuracy of abdominal lesion localization. Retrospective automatic rigid image registration between FDG-PET and MRI.

UNLABELLED: Software-based image registration can improve the diagnostic value of imaging procedures and is an alternative to hybrid scanners. The aim of this study was to evaluate the anatomical accuracy of automatic rigid image registration of independently acquired datasets of positron emission tomography with 18F-deoxyglucose and abdominal magnetic resonance imaging. PATIENTS, METHODS: Analyses were performed on 28 abdominal lesions from 20 patients. The PET data were obtained using a stand-alone PET camera in 14 cases and a hybrid PET/CT scanner in 9 cases. The abdominal T1- and T2-weighted MRI scans were acquired on 1.5 T MRI scanners. The mean time interval between MRI and PET was 7.3 days (0-28 days). Automatic rigid registration was carried out using a self-developed registration tool integrated into commercial available software (InSpace for Siemens Syngo). Distances between the centres of gravity of 28 manually delineated neoplastic lesions represented in PET and MRI were measured in X-, Y-, and Z-direction. The intra- (intraclass correlation 0.94) and inter- (intraclass correlation 0.86) observer repeatability were high. RESULTS: The average distance in all MRI sequences was 5.2±7.6 mm in X-direction, 4.0±3.7 mm in Y-direction and 6.1±5.1 mm in Z-direction. There was a significantly higher misalignment in Z-direction (p<0.05). The misalignment was not significantly different for the registration of T1- and T2- weighted sequences (p=0.7). CONCLUSION: The misalignment between FDG-PET and abdominal MRI registered using an automated rigid registration tool was comparable to data reported for software-based fusion between PET and CT. Although this imprecision may not affect diagnostic accuracy, it is not sufficient to allow for pixel-wise integration of MRI and PET information.