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There has been significant recent interest in understanding both the frequency of nuclear medicine injection infiltration and the potential for negative impact, including skin injury. However, no large-scale study has yet correlated visualized injection site activity with actual activity measurement of an infiltrate. Additionally, current skin dosimetry approaches lack sufficient detail to account for critical factors that impact the dose to the radiosensitive epidermis. Methods: From 10 imaging sites, 1,000 PET/CT patient studies were retrospectively collected. At each site, consecutive patients with the injection site in the field of view were used. The radiopharmaceutical, injected activity, time of injection and imaging, injection site, and injection method were recorded. Net injection site activity was calculated from volumes of interest. Monte Carlo image-based absorbed dose calculations were performed using the actual geometry from a patient with a minor infiltration. The simulation model used an activity distribution in the skin microanatomy based on known properties of subcutaneous fat, dermis, and epidermis. Simulations using several subcutaneous fat-to-dermis concentration ratios were performed. Absorbed dose to the epidermis, dermis, and fat were calculated along with relative γ- and β-contributions, and these findings were extrapolated to a hypothetical worst-case (470 MBq) full-injection infiltration. Results: Only 6 of 1,000 patients had activity at the injection site in excess of 370 kBq (10 μCi), with no activities greater than 1.7 MBq (45 μCi). In 460 of 1,000 patients, activity at the injection site was clearly visualized. However, quantitative assessment of activities averaged only 34 kBq (0.9 μCi), representing 0.008% of the injected activity. Calculations for the extrapolated 470-MBq infiltration resulted in a hypothetical absorbed dose to the epidermis of below 1 Gy, a factor of 2 lower than what is required for deterministic skin reactions. Analysis of the dose distribution demonstrates that the dermis acts as a β-shield for the radiation-sensitive epidermis. Dermal shielding is highly effective for low-energy 18 F positrons but less so with the higher-energy positrons of 68 Ga. Conclusion: When quantitative activity measurement criteria are used rather than visual, the frequency of PET infiltration appears substantially below frequencies previously published. Shallow doses to the epidermis from infiltration events are also likely substantially lower than previously reported because of absorption of β-particles in the dermis., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Molecular tumor volume (MTV) is a parameter of interest in prostate cancer for assessing total disease burden on prostate-specific membrane antigen (PSMA) PET. Although software segmentation tools can delineate whole-body MTV, a necessary step toward meaningful monitoring of total tumor burden and treatment response through PET is establishing the repeatability of these metrics. The present study assessed the repeatability of total MTV and related metrics for 68 Ga-PSMA-HBED-CC in prostate cancer. Methods: Eighteen patients from a prior repeatability study who underwent 2 test-retest PSMA PET/CT scans within a mean interval of 5 d were reanalyzed. Within-subject coefficient of variation and repeatability coefficients (RCs) were analyzed on a per-lesion and per-patient basis. For the per-lesion analysis, individual lesions were segmented for analysis by a single reader. For the per-patient analysis, subgroups of up to 10 lesions (single reader) and the total tumor volume per patient were segmented (independently by 2 readers). Image parameters were MTV, SUV max , SUV peak , SUV mean , total lesion PSMA, and the related metric PSMA quotient (which integrates lesion volume and PSMA avidity). Results: In total, 192 segmentations were analyzed for the per-lesion analysis and 1,662 segmentations for the per-patient analysis (combining the 2 readers and 2 scans). The RC of the MTV of single lesions was 77% (95% CI, 63%-96%). The RC improved to 33% after aggregation of up to 10 manually selected lesions into subgroups assessed per patient (95% CI, 25%-46%). The RC of the semiautomatic MTV total (the sum of all voxels in the whole-body total tumor segmentation per patient) was 35% (95% CI, 25%-50%), the Bland-Altman bias was -6.70 (95% CI, -14.32-0.93). Alternating readers between scans led to a comparable RC of 37% (95% CI, 28%-49%) for MTV total , meaning that the metric is robust between scanning sessions and between readers. Conclusion: 68 Ga-PSMA-HBED-CC PET-derived semiautomatic MTV total is repeatable and reader-independent, with a change of ±35% representing a true change in tumor volume. Volumetry of single manually selected lesions has considerably lower repeatability, and volumetry based on subgroups of these lesions, although showing acceptable repeatability, is less systematic. The semiautomatic analysis of MTV total used in this study offers an efficient and robust means of assessing response to therapy., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: The purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation in computed tomography (CT) scans to enable the quantification of active pelvic bone marrow by means of Fluorothymidine F-18 (FLT) tracer uptake measurement in positron emission tomography (PET) scans. This quantification is a critical step in calculating bone marrow dose for radiopharmaceutical therapy clinical applications as well as external beam radiation doses., Methods: An approach for the combined localization and segmentation of the pelvis in CT volumes of varying sizes, ranging from full-body to pelvis CT scans, was developed that utilizes a novel CNN architecture in combination with a random sampling strategy. The method was validated on 34 planning CT scans and 106 full-body FLT PET-CT scans using a cross-validation strategy. Specifically, two different training and CNN application options were studied, quantitatively assessed, and statistically compared., Results: The proposed method was able to successfully locate and segment the pelvis in all test cases. On all data sets, an average Dice coefficient of 0.9396 ± $\pm$ 0.0182 or better was achieved. The relative tracer uptake measurement error ranged between 0.065% and 0.204%. The proposed approach is time-efficient and shows a reduction in runtime of up to 95% compared to a standard U-Net-based approach without a localization component., Conclusions: The proposed method enables the efficient calculation of FLT uptake in the pelvis. Thus, it represents a valuable tool to facilitate bone marrow preserving adaptive radiation therapy and radiopharmaceutical dose calculation. Furthermore, the method can be adapted to process other bone structures as well as organs., (© 2022 American Association of Physicists in Medicine.)

The PET radiotracer 68 Ga-PSMA (prostate-specific membrane antigen)-HBED-CC ( N,N '-bis [2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine- N,N '-diacetic acid) shows potential as an imaging biomarker for recurrent and metastatic prostate cancer. The purpose of this study was to determine the repeatability of 68 Ga-PSMA-HBED-CC in a test-retest trial in subjects with metastatic prostate adenocarcinoma. Methods: Subjects with metastatic prostate cancer underwent 2 PET/CT scans with 68 Ga-PSMA-HBED-CC within 14 d (mean, 6 ± 4 d). Lesions in bone, nodes, prostate/bed, and visceral organs, as well as representative normal tissues (salivary glands and spleen), were segmented separately by 2 readers. Absolute and percentage differences in SUV max and SUV mean were calculated for all test-retest regions. Repeatability was assessed using percentage difference, within-subject coefficient of variation (wCV), repeatability coefficient (RC), and Bland-Altman analysis. Results: Eighteen subjects were evaluated, 16 of whom demonstrated local or metastatic disease on 68 Ga-PSMA-HBED-CC PET/CT. In total, 136 lesions were segmented in bone ( n = 99), nodes ( n = 27), prostate/bed ( n = 7), and viscera ( n = 3). The wCV for SUV max was 11.7% for bone lesions and 13.7% for nodes. The RC was ±32.5% SUV max for bone lesions and ±37.9% SUV max for nodal lesions, meaning 95% of the normal variability between 2 measurements will be within these numbers, so larger differences are likely attributable to true biologic changes in tumor rather than normal physiologic or measurement variability. wCV in the salivary glands and spleen was 8.9% and 10.7% SUV mean , respectively. Conclusion: Repeatability measurements for PET/CT test-retests with 68 Ga-PSMA-HBED-CC showed a wCV of 12%-14% SUV max and an RC of ±33%-38% SUV max in bone and nodal lesions. These estimates are an important aspect of 68 Ga-PSMA-HBED-CC as a quantitative imaging biomarker. These estimates are similar to those reported for 18 F-FDG, suggesting that 68 Ga-PSMA-HBED-CC PET/CT may be useful in monitoring response to therapy., (© 2020 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: The purpose of this work was to assess the potential of deep convolutional neural networks in automated measurement of cerebellum tracer uptake in F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) scans., Methods: Three different three-dimensional (3D) convolutional neural network architectures (U-Net, V-Net, and modified U-Net) were implemented and compared regarding their performance in 3D cerebellum segmentation in FDG PET scans. For network training and testing, 134 PET scans with corresponding manual volumetric segmentations were utilized. For segmentation performance assessment, a fivefold cross-validation was used, and the Dice coefficient as well as signed and unsigned distance errors were calculated. In addition, standardized uptake value (SUV) uptake measurement performance was assessed by means of a statistical comparison to an independent reference standard. Furthermore, a comparison to a previously reported active-shape-model-based approach was performed., Results: Out of the three convolutional neural networks investigated, the modified U-Net showed significantly better segmentation performance. It achieved a Dice coefficient of 0.911 ± 0.026, a signed distance error of 0.220 ± 0.103 mm, and an unsigned distance error of 1.048 ± 0.340 mm. When compared to the independent reference standard, SUV uptake measurements produced with the modified U-Net showed no significant error in slope and intercept. The estimated reduction in total SUV measurement error was 95.1%., Conclusions: The presented work demonstrates the potential of deep convolutional neural networks in automated SUV measurement of reference regions. While it focuses on the cerebellum, utilized methods can be generalized to other reference regions like the liver or aortic arch. Future work will focus on combining lesion and reference region analysis into one approach., (© 2019 American Association of Physicists in Medicine.)

The Quantitative Imaging Biomarkers Alliance (QIBA) Profile for fluorodeoxyglucose (FDG) PET/CT imaging was created by QIBA to both characterize and reduce the variability of standardized uptake values (SUVs). The Profile provides two complementary claims on the precision of SUV measurements. First, tumor glycolytic activity as reflected by the maximum SUV (SUV max ) is measurable from FDG PET/CT with a within-subject coefficient of variation of 10%-12%. Second, a measured increase in SUV max of 39% or more, or a decrease of 28% or more, indicates that a true change has occurred with 95% confidence. Two applicable use cases are clinical trials and following individual patients in clinical practice. Other components of the Profile address the protocols and conformance standards considered necessary to achieve the performance claim. The Profile is intended for use by a broad audience; applications can range from discovery science through clinical trials to clinical practice. The goal of this report is to provide a rationale and overview of the FDG PET/CT Profile claims as well as its context, and to outline future needs and potential developments., (© RSNA, 2020 See also the editorial by Ulaner in this issue.)

The use of computed tomography (CT) images to correct for photon attenuation in positron emission tomography (PET) produces unbiased patient images, but it is not optimal for synthetic materials. For test objects made from epoxy, image bias and artifacts have been observed in well-calibrated PET/CT scanners. An epoxy used in commercially available sources was infused with long-lived 68 Ge/ 68 Ga nuclide and measured on several PET/CT scanners as well as on older PET scanners that measured attenuation with 511-keV photons. Bias in attenuation maps and PET images of phantoms was measured as imaging parameters and methods varied. Changes were made to the PET reconstruction to show the influence of CT-based attenuation correction. Additional attenuation measurements were made with a new epoxy intended for use in radiology and radiation treatment whose photonic properties mimic water. PET images of solid phantoms were biased by between 3% and 24% across variations in CT X-ray energy and scanner manufacturer. Modification of the reconstruction software reduced bias, but object-dependent changes were required to generate accurate attenuation maps. The water-mimicking epoxy formulation showed behavior similar to water in limited testing. For some solid phantoms, transformation of CT data to attenuation maps is a major source of PET image bias. The transformation can be modified to accommodate synthetic materials, but our data suggest that the problem may also be addressed by using epoxy formulations that are more compatible with PET/CT imaging.

Purpose: Quality control plays an increasingly important role in quantitative PET imaging and is typically performed using phantoms. The purpose of this work was to develop and validate a fully automated analysis method for two common PET/CT quality assurance phantoms: the NEMA NU-2 IQ and SNMMI/CTN oncology phantom. The algorithm was designed to only utilize the PET scan to enable the analysis of phantoms with thin-walled inserts., Methods: We introduce a model-based method for automated analysis of phantoms with spherical inserts. Models are first constructed for each type of phantom to be analyzed. A robust insert detection algorithm uses the model to locate all inserts inside the phantom. First, candidates for inserts are detected using a scale-space detection approach. Second, candidates are given an initial label using a score-based optimization algorithm. Third, a robust model fitting step aligns the phantom model to the initial labeling and fixes incorrect labels. Finally, the detected insert locations are refined and measurements are taken for each insert and several background regions. In addition, an approach for automated selection of NEMA and CTN phantom models is presented. The method was evaluated on a diverse set of 15 NEMA and 20 CTN phantom PET/CT scans. NEMA phantoms were filled with radioactive tracer solution at 9.7:1 activity ratio over background, and CTN phantoms were filled with 4:1 and 2:1 activity ratio over background. For quantitative evaluation, an independent reference standard was generated by two experts using PET/CT scans of the phantoms. In addition, the automated approach was compared against manual analysis, which represents the current clinical standard approach, of the PET phantom scans by four experts., Results: The automated analysis method successfully detected and measured all inserts in all test phantom scans. It is a deterministic algorithm (zero variability), and the insert detection RMS error (i.e., bias) was 0.97, 1.12, and 1.48 mm for phantom activity ratios 9.7:1, 4:1, and 2:1, respectively. For all phantoms and at all contrast ratios, the average RMS error was found to be significantly lower for the proposed automated method compared to the manual analysis of the phantom scans. The uptake measurements produced by the automated method showed high correlation with the independent reference standard (R 2 ≥ 0.9987). In addition, the average computing time for the automated method was 30.6 s and was found to be significantly lower (P ≪ 0.001) compared to manual analysis (mean: 247.8 s)., Conclusions: The proposed automated approach was found to have less error when measured against the independent reference than the manual approach. It can be easily adapted to other phantoms with spherical inserts. In addition, it eliminates inter- and intraoperator variability in PET phantom analysis and is significantly more time efficient, and therefore, represents a promising approach to facilitate and simplify PET standardization and harmonization efforts., (© 2017 American Association of Physicists in Medicine.)

Localization of the site of the unknown primary tumor is critical for surgical treatment of patients presenting with neuroendocrine tumor (NET) with metastases. Methods: Forty patients with metastatic NET and unknown primary site underwent 68 Ga-DOTATOC PET/CT in a single-site prospective study. The 68 Ga-DOTATOC PET/CT was considered true-positive if the positive primary site was confirmed by histology or follow-up imaging. The scan was considered false-positive if no primary lesion was found corresponding to the 68 Ga-DOTATOC-positive site. All negative scans for primary tumor were considered false-negative. A scan was classified unconfirmed if 68 Ga-DOTATOC PET/CT suggested a primary, however, no histology was obtained and imaging follow-up was not confirmatory. Results: The true-positive, false-positive, false-negative, and unconfirmed rates for unknown primary tumor were 38%, 7%, 50%, and 5%, respectively. Conclusion: 68 Ga-DOTATOC PET/CT is an effective modality in the localization of unknown primary in patients with metastatic NET., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

Human brown adipose tissue (BAT) presence, metabolic activity, and estimated mass are typically measured by imaging [18F]fluorodeoxyglucose (FDG) uptake in response to cold exposure in regions of the body expected to contain BAT, using positron emission tomography combined with X-ray computed tomography (FDG-PET/CT). Efforts to describe the epidemiology and biology of human BAT are hampered by diverse experimental practices, making it difficult to directly compare results among laboratories. An expert panel was assembled by the National Institute of Diabetes and Digestive and Kidney Diseases on November 4, 2014 to discuss minimal requirements for conducting FDG-PET/CT experiments of human BAT, data analysis, and publication of results. This resulted in Brown Adipose Reporting Criteria in Imaging STudies (BARCIST 1.0). Since there are no fully validated best practices at this time, panel recommendations are meant to enhance comparability across experiments, but not to constrain experimental design or the questions that can be asked., (Published by Elsevier Inc.)