Patient Size-Dependent Dosimetry Methodology Applied to 18F-FDG Using New ICRP Mesh Phantoms.

Despite the known influence of anatomic variability on internal dosimetry, dosimetry for 18F-FDG and other diagnostic radiopharmaceuticals is routinely derived using reference phantoms, which embody population-averaged morphometry for a given age and sex. Moreover, phantom format affects dosimetry estimates to varying extent. Here, we applied newly developed mesh format reference phantoms and a patient-dependent phantom library to assess the impact of height, weight, and body contour variation on dosimetry of 18F-FDG. We compared the mesh reference phantom dosimetry estimates with corresponding estimates from common software to identify differences related to phantom format or software implementation. Our study serves as an example of how more precise patient size-dependent dosimetry methodology could be performed. Methods: Absorbed dose coefficients were computed for the adult mesh reference phantoms and derivative patient-dependent phantom series by Monte Carlo simulation using the PHITS radiation transport code within PARaDIM software. The dose coefficients were compared with reference absorbed dose coefficients obtained from ICRP Publication 128, or generated using software including OLINDA 2.1, OLINDA 1.1, and IDAC-dose 2.1. Results: Differences in dosimetry arising from anatomical variations were shown to be significant, with detriment-weighted dose coefficients for the percentile-specific phantoms varying by up to ±40% relative to the corresponding reference phantom effective dose coefficients, irrespective of phantom format. Similar variations were seen in the individual organ absorbed dose coefficients for the percentile-specific phantoms relative to the reference phantoms. The effective dose coefficient for the mesh reference adult was 0.017 mSv/MBq, which was 5% higher than estimated by a corresponding voxel phantom, and 10% lower than estimated by the stylized phantom format. Conclusion: We observed notable variability in 18F-FDG dosimetry across morphometrically different patients, supporting the use of patient-dependent phantoms for more accurate dosimetric estimations relative to standard reference dosimetry. These data may help in optimizing imaging protocols and research studies, in particular when longer-lived isotopes are employed.

The Impact of Positron Range on PET Resolution, Evaluated with Phantoms and PHITS Monte Carlo Simulations for Conventional and Non-conventional Radionuclides.

PURPOSE: The increasing interest and availability of non-standard positron-emitting radionuclides has heightened the relevance of radionuclide choice in the development and optimization of new positron emission tomography (PET) imaging procedures, both in preclinical research and clinical practice. Differences in achievable resolution arising from positron range can largely influence application suitability of each radionuclide, especially in small-ring preclinical PET where system blurring factors due to annihilation photon acollinearity and detector geometry are less significant. Some resolution degradation can be mitigated with appropriate range corrections implemented during image reconstruction, the quality of which is contingent on an accurate characterization of positron range. PROCEDURES: To address this need, we have characterized the positron range of several standard and non-standard PET radionuclides (As-72, F-18, Ga-68, Mn-52, Y-86, and Zr-89) through imaging of small-animal quality control phantoms on a benchmark preclinical PET scanner. Further, the Particle and Heavy Ion Transport code System (PHITS v3.02) code was utilized for Monte Carlo modeling of positron range-dependent blurring effects. RESULTS: Positron range kernels for each radionuclide were derived from simulation of point sources in ICRP reference tissues. PET resolution and quantitative accuracy afforded by various radionuclides in practicable imaging scenarios were characterized using a convolution-based method based on positron annihilation distributions obtained from PHITS. Our imaging and simulation results demonstrate the degradation of small animal PET resolution, and quantitative accuracy correlates with increasing positron energy; however, for a specific "benchmark" preclinical PET scanner and reconstruction workflow, these differences were observed to be minimal given radionuclides with average positron energies below ~ 400 keV. CONCLUSION: Our measurements and simulations of the influence of positron range on PET resolution compare well with previous efforts documented in the literature and provide new data for several radionuclides in increasing clinical and preclinical use. The results will support current and future improvements in methods for positron range corrections in PET imaging.

The IAEA Radiotracer Biodistribution Template - A community resource for supporting the standardization and reporting of radionuclide pre-dosimetry data.

Radionuclide absorbed-dose dosimetry is an active area of development and has the potential to positively impact molecular radiotherapies. At present, many of the operations required to perform dosimetry calculations are unstandardized and unestablished. While the current methodology allows reasonable dosimetry estimates to be derived and published, it can be difficult to understand, and reproduce, each others' work. To help alleviate this we have identified the collection of biodistribution information as a key step in all internal dosimetry calculations, and present a template that can be used to standardize its documentation and reporting. A generalized biodistribution template entitled the IAEA Radiotracer Biodistribution Template (IAEA RaBiT) has been built and distributed for users performing biodistribution measurements in the community. The template enables robust recording of dosimetry-relevant information through standardization of details and their format. It has been designed to be simple and easy to use, and establish a structured recording of a common reference point in dosimetry operations - biodistribution data documentation. Improved documentation procedures may benefit organization of in house data, or be used to disseminate details throughout the community - for example to supplement dosimetry related publications. The standard format information may also enable the creation of new dosimetry related tools and protocols and support robust population databases. As dosimetry in nuclear medicine becomes more routinely applied in clinical applications, we need to develop the infrastructure for robustly handling large amounts of these data. Our IAEA RaBiT can be used as a standard format structure for data collection, organization, and dissemination.

Validation of Software Gating: A Practical Technology for Respiratory Motion Correction in PET.

Purpose To assess the performance of hardware- and software-gating technologies in terms of qualitative and quantitative characteristics of respiratory motion in positron emission tomography (PET) imaging. Materials and Methods Between 2010 and 2013, 219 fluorine 18 fluorodeoxyglucose PET examinations were performed in 116 patients for assessment of pulmonary nodules. All patients provided informed consent in this institutional review board-approved study. Acquisitions were reconstructed as respiratory-gated images by using hardware-derived respiratory triggers and software-derived signal (via an automated postprocessing method). Asymmetry was evaluated in the joint distribution of reader preference, and linear mixed models were used to evaluate differences in outcomes according to gating type. Results In blind reviews of reconstructed gated images, software was selected as superior 16.9% of the time (111 of 657 image sets; 95% confidence interval [CI]: 14.0%, 19.8%), and hardware was selected as superior 6.2% of the time (41 of 657 image sets; 95% CI: 4.4%, 8.1%). Of the image sets, 76.9% (505 of 657; 95% CI: 73.6%, 80.1%) were judged as having indistinguishable motion quality. Quantitative analysis demonstrated that the two gating strategies exhibited similar performance, and the performance of both was significantly different from that of nongated images. The mean increase ± standard deviation in lesion maximum standardized uptake value was 42.2% ± 38.9 between nongated and software-gated images, and lesion full width at half maximum values decreased by 9.9% ± 9.6. Conclusion Compared with vendor-supplied respiratory-gating hardware methods, software gating performed favorably, both qualitatively and quantitatively. Fully automated gating is a feasible approach to motion correction of PET images. (©) RSNA, 2016 Online supplemental material is available for this article.

Gating, enhanced gating, and beyond: information utilization strategies for motion management, applied to preclinical PET.

BACKGROUND: Respiratory gating and gate optimization strategies present solutions for overcoming image degradation caused by respiratory motion in PET and traditionally utilize hardware systems and/or employ complex processing algorithms. In this work, we aimed to advance recently emerging data-driven gating methods and introduce a new strategy for optimizing the four-dimensional data based on information contained in that data. These algorithms are combined to form an automated motion correction workflow. METHODS: Software-based gating methods were applied to a nonspecific population of 84 small-animal rat PET scans to create respiratory gated images. The gated PET images were then optimized using an algorithm we introduce as 'gating+' to reduce noise and optimize signal; the technique was also tested using simulations. Gating+ is based on a principle of only using gated information if and where it adds a net benefit, as evaluated in temporal frequency space. Motion-corrected images were assessed quantitatively and qualitatively. RESULTS: Of the small-animal PET scans, 71% exhibited quantifiable motion after software gating. The mean liver displacement was 3.25 mm for gated and 3.04 mm for gating+ images. The (relative) mean percent standard deviations measured in background ROIs were 1.53, 1.05, and 1.00 for the gated, gating+, and ungated values, respectively. Simulations confirmed that gating+ image voxels had a higher probability of being accurate relative to the corresponding ungated values under varying noise and motion scenarios. Additionally, we found motion mapping and phase decoupling models that readily extend from gating+ processing. CONCLUSIONS: Raw PET data contain information about motion that is not currently utilized. In our work, we showed that through automated processing of standard (ungated) PET acquisitions, (motion-) information-rich images can be constructed with minimal risk of noise introduction. Such methods have the potential for implementation with current PET technology in a robust and reproducible way.

A new fast and fully automated software based algorithm for extracting respiratory signal from raw PET data and its comparison to other methods.

PURPOSE: Respiratory gating in PET is an approach used to minimize the negative effects of respiratory motion on spatial resolution. It is based on an initial determination of a patient's respiratory movements during a scan, typically using hardware based systems. In recent years, several fully automated databased algorithms have been presented for extracting a respiratory signal directly from PET data, providing a very practical strategy for implementing gating in the clinic. In this work, a new method is presented for extracting a respiratory signal from raw PET sinogram data and compared to previously presented automated techniques. METHODS: The acquisition of respiratory signal from PET data in the newly proposed method is based on rebinning the sinogram data into smaller data structures and then analyzing the time activity behavior in the elements of these structures. From this analysis, a 1D respiratory trace is produced, analogous to a hardware derived respiratory trace. To assess the accuracy of this fully automated method, respiratory signal was extracted from a collection of 22 clinical FDG-PET scans using this method, and compared to signal derived from several other software based methods as well as a signal derived from a hardware system. RESULTS: The method presented required approximately 9 min of processing time for each 10 min scan (using a single 2.67 GHz processor), which in theory can be accomplished while the scan is being acquired and therefore allowing a real-time respiratory signal acquisition. Using the mean correlation between the software based and hardware based respiratory traces, the optimal parameters were determined for the presented algorithm. The mean/median/range of correlations for the set of scans when using the optimal parameters was found to be 0.58/0.68/0.07-0.86. The speed of this method was within the range of real-time while the accuracy surpassed the most accurate of the previously presented algorithms. CONCLUSIONS: PET data inherently contains information about patient motion; information that is not currently being utilized. We have shown that a respiratory signal can be extracted from raw PET data in potentially real-time and in a fully automated manner. This signal correlates well with hardware based signal for a large percentage of scans, and avoids the efforts and complications associated with hardware. The proposed method to extract a respiratory signal can be implemented on existing scanners and, if properly integrated, can be applied without changes to routine clinical procedures.