Patterns of response and progression in bone and soft tissue during and after treatment with radium-223 for metastatic castrate-resistant prostate cancer.

BACKGROUND: Radium-223 improves survival and time to first symptomatic skeletal event in symptomatic bone predominant metastatic castrate-resistant prostate cancer (mCRPC). The imaging response to radium-223 has not been well characterized. METHODS: To describe patterns of response and progression with radium-223, we performed a retrospective review of all mCPRC patients who received radium-223 at Duke from 1 June 2013 to 1 June 2015. Radionuclide bone scans obtained at baseline, during, and after treatment were reviewed by two radiologists. The automated bone scan index (aBSI) was generated at each time point using EXINI boneBSI version 2.4. Computed tomography (CT) and magnetic resonance imaging (MRI) clinical radiology reports were reviewed to evaluate for soft tissue, visceral, epidural, and bone progression. Clinical data were abstracted from the electronic health record. RESULTS: We identified 61 men who received at least one dose of radium-223 at Duke during the study period (median, 5 doses; range, 1-6). Among men with imaging during treatment, 2 of 14 (14.3%) had resolution of greater than or equal to 1 lesion on bone scan, 4 of 14 (28.6%) had zero new bone lesions, 10 of 14 (71.4%) had greater than or equal to 1 new bone lesion, 14 of 26 (53.9%) progressed on CT. After radium-223, 6 of 39 (15.4%) had resolution of 1 to 4 bone lesions, 15 of 39 (38.5%) demonstrated zero new bone lesions, 24 of 39 (61.5%) progressed on bone scan, 15 of 37 (40.5%) progressed on CT, and 10 of 34 (29.4%) progressed on both bone scan and CT. No men with zero new bone lesions after radium-223 ultimately progressed in bone alone and only 3 of 15 eventually demonstrated any progression in the bone. aBSI decreased significantly from baseline to after radium-223 among men with zero new bone lesions (median change in aBSI -0.23 [IQR, -1.5, 0.02]) and increased significantly for men with greater than or equal to 1 new postradium bone lesions (median change in aBSI 1.41 [IQR, -0.05, 3.63] [P = 0.018]). CONCLUSIONS: Bone and soft tissue progression during and following radium-223 is common in heavily pretreated men with mCRPC. However, stable disease and responses were observed in a subset of patients and may be associated with durable treatment response in the bone. Prospective studies are needed to further investigate the change in aBSI as a biomarker of bone scan response/stabilization and progression following treatment with radium-223.

Non-invasive sensitive brain tumor detection using dual-modality bioimaging nanoprobe.

Despite decades of efforts, non-invasive sensitive detection of small malignant brain tumors still remains challenging. Here we report a dual-modality 124I-labeled gold nanostar (124I-GNS) probe for sensitive brain tumor imaging with positron emission tomography (PET) and subcellular tracking with two-photon photoluminescence (TPL) and electron microscopy (EM). Experiment results showed that the developed nanoprobe has potential to reach sub-millimeter intracranial brain tumor detection using PET scan, which is superior to any currently available non-invasive imaging modality. Microscopic examination using TPL and EM further confirmed that GNS nanoparticles permeated the brain tumor leaky vasculature and accumulated inside brain tumor cells following systemic administration. Selective brain tumor targeting by enhanced permeability and retention effect and ultrasensitive imaging render 124I-GNS nanoprobe promise for future brain tumor-related preclinical and translational applications.

Incidental Thyroid Nodules at Non-FDG PET Nuclear Medicine Imaging: Evaluation of Prevalence and Malignancy Rate.

OBJECTIVE: The purpose of this study was to estimate the prevalence of thyroid nodules detected incidentally on non-FDG PET nuclear medicine imaging studies, the malignancy rate, and predictors of malignancy. MATERIALS AND METHODS: A retrospective review of more than 10 years of patient records at an academic medical center identified the cases of 31 patients with incidental focal radiotracer-avid thyroid findings on non-FDG PET nuclear medicine studies who underwent biopsy or surgical excision. Statistical analysis of patient and imaging features was performed to identify features predictive of malignancy. Society of Radiologists in Ultrasound and American Thyroid Association biopsy criteria were applied to patients who had ultrasound images for review. RESULTS: Thirty-one patients had incidental thyroid findings on (99m)Tc-sestamibi parathyroid scans (80.6%), (111)In-pentetreotide scans (16.1%), and (99m)Tc-tetrofosmin cardiac scans (3.2%). These three types of scans accounted for 21,402 total examinations in the study period. Thus, the prevalence of incidental thyroid findings on non-PET nuclear medicine studies that were evaluated by pathologic examination was 0.14%. The malignancy rate was 16.1% (5/31). No clinical or imaging features were identified as predictive of malignancy. Society of Radiologists in Ultrasound and American Thyroid Association criteria were applied to 23 thyroid nodules with available ultrasound images. According to both sets of criteria, biopsy was recommended for 19 of 23 (82.6%) nodules, and one of three (33.3%) cases of thyroid cancer was missed. CONCLUSION: Most thyroid nodules incidentally detected on non-FDG PET nuclear medicine studies are detected on (99m)Tc-sestamibi parathyroid scans and (111)In-pentetreotide scans. Because these nodules are extremely rare and the malignancy rate is high, further evaluation of incidental focal radiotracer-avid thyroid findings with ultrasound is an appropriate recommendation.

Lifetime Attributable Risk of Cancer From Radiation Exposure During Parathyroid Imaging: Comparison of 4D CT and Parathyroid Scintigraphy.

OBJECTIVE: The purpose of this study is to measure the organ doses and effective dose (ED) for parathyroid 4D CT and scintigraphy and to estimate the lifetime attributable risk of cancer incidence associated with imaging. MATERIALS AND METHODS: Organ radiation doses for 4D CT and scintigraphy were measured on the basis of imaging with our institution's protocols. An anthropomorphic phantom with metal oxide semiconductor field effect transistor detectors was scanned to measure CT organ dose. Organ doses from the radionuclide were based on International Commission for Radiological Protection report 80. ED was calculated for 4D CT and scintigraphy and was used to estimate the lifetime attributable risk of cancer incidence for patients differing in age and sex with the approach established by the Biologic Effects of Ionizing Radiation VII report. A 55-year-old woman was selected as the standard patient according to the demographics of patients with primary hyperparathyroidism. RESULTS: Organs receiving the highest radiation dose from 4D CT were the thyroid (150.6 mGy) and salivary glands (137.8 mGy). For scintigraphy, the highest organ doses were to the colon (41.5 mGy), gallbladder (39.8 mGy), and kidneys (32.3 mGy). The ED was 28 mSv for 4D CT, compared with 12 mSv for scintigraphy. In the exposed standard patient, the lifetime attributable risk for cancer incidence was 193 cancers/100,000 patients for 4D CT and 68 cancers/100,000 patients for scintigraphy. Given a baseline lifetime incidence of cancer of 46,300 cancers/100,000 patients, imaging results in an increase in lifetime incidence of cancer over baseline of 0.52% for 4D CT and 0.19% for scintigraphy. CONCLUSION: The ED of 4D CT is more than double that of scintigraphy, but both studies cause negligible increases in lifetime risk of cancer. Clinicians should not allow concern for radiation-induced cancer to influence decisions regarding workup in older patients.

Location-Aware Encoding for Lesion Detection in 68Ga-DOTATATE Positron Emission Tomography Images.

OBJECTIVE: Lesion detection with positron emission tomography (PET) imaging is critical for tumor staging, treatment planning, and advancing novel therapies to improve patient outcomes, especially for neuroendocrine tumors (NETs). Current lesion detection methods often require manual cropping of regions/volumes of interest (ROIs/VOIs) a priori, or rely on multi-stage, cascaded models, or use multi-modality imaging to detect lesions in PET images. This leads to significant inefficiency, high variability and/or potential accumulative errors in lesion quantification. To tackle this issue, we propose a novel single-stage lesion detection method using only PET images. METHODS: We design and incorporate a new, plug-and-play codebook learning module into a U-Net-like neural network and promote lesion location-specific feature learning at multiple scales. We explicitly regularize the codebook learning with direct supervision at the network's multi-level hidden layers and enforce the network to learn multi-scale discriminative features with respect to predicting lesion positions. The network automatically combines the predictions from the codebook learning module and other layers via a learnable fusion layer. RESULTS: We evaluate the proposed method on a real-world clinical 68Ga-DOTATATE PET image dataset, and our method produces significantly better lesion detection performance than recent state-of-the-art approaches. CONCLUSION: We present a novel deep learning method for single-stage lesion detection in PET imaging data, with no ROI/VOI cropping in advance, no multi-stage modeling and no multi-modality data. SIGNIFICANCE: This study provides a new perspective for effective and efficient lesion identification in PET, potentially accelerating novel therapeutic regimen development for NETs and ultimately improving patient outcomes including survival.

Learning Without Real Data Annotations to Detect Hepatic Lesions in PET Images.

OBJECTIVE: Deep neural networks have been recently applied to lesion identification in fluorodeoxyglucose (FDG) positron emission tomography (PET) images, but they typically rely on a large amount of well-annotated data for model training. This is extremely difficult to achieve for neuroendocrine tumors (NETs), because of low incidence of NETs and expensive lesion annotation in PET images. The objective of this study is to design a novel, adaptable deep learning method, which uses no real lesion annotations but instead low-cost, list mode-simulated data, for hepatic lesion detection in real-world clinical NET PET images. METHODS: We first propose a region-guided generative adversarial network (RG-GAN) for lesion-preserved image-to-image translation. Then, we design a specific data augmentation module for our list-mode simulated data and incorporate this module into the RG-GAN to improve model training. Finally, we combine the RG-GAN, the data augmentation module and a lesion detection neural network into a unified framework for joint-task learning to adaptatively identify lesions in real-world PET data. RESULTS: The proposed method outperforms recent state-of-the-art lesion detection methods in real clinical 68Ga-DOTATATE PET images, and produces very competitive performance with the target model that is trained with real lesion annotations. CONCLUSION: With RG-GAN modeling and specific data augmentation, we can obtain good lesion detection performance without using any real data annotations. SIGNIFICANCE: This study introduces an adaptable deep learning method for hepatic lesion identification in NETs, which can significantly reduce human effort for data annotation and improve model generalizability for lesion detection with PET imaging.

Improving Generalizability of PET DL Algorithms: List-Mode Reconstructions Improve DOTATATE PET Hepatic Lesion Detection Performance.

Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n = 83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n = 123 subjects). Set1, the data set from Scanner1, was reconstructed with standard clinical parameters (5 min; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-min). Set2, data from Scanner2 representing out-of-domain clinical scans, used standard iterative reconstruction (5 min; OSEM). A deep neural network was trained with each dataset: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50% and 75%) of Set1 for training. Scanner1, list-mode 2-min reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1 = 0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1 = 0.755; p-value = 0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1 = 0.478) to 100% training data (F1 = 0.713; p < 0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability.

Attenuated kidney oxidative metabolism in young adults with type 1 diabetes.

BACKGROUND: In type 1 diabetes (T1D), impaired insulin sensitivity may contribute to the development of diabetic kidney disease (DKD) through alterations in kidney oxidative metabolism. METHODS: Young adults with T1D (n = 30) and healthy controls (HC, n = 20) underwent hyperinsulinemic-euglycemic clamp studies, MRI, 11C-acetate PET, kidney biopsies, single-cell RNA sequencing, and spatial metabolomics to assess this relationship. RESULTS: Participants with T1D had significantly higher glomerular basement membrane thickness compared to HC. T1D participants exhibited lower insulin sensitivity and cortical oxidative metabolism, correlating with higher insulin sensitivity. Proximal tubular transcripts of TCA cycle and oxidative phosphorylation enzymes were lower in T1D. Spatial metabolomics showed reductions in tubular TCA cycle intermediates, indicating mitochondrial dysfunction. The Slingshot algorithm identified a lineage of proximal tubular cells progressing from stable to adaptive/maladaptive subtypes, using pseudotime trajectory analysis, which computationally orders cells along a continuum of states. This analysis revealed distinct distribution patterns between T1D and HC, with attenuated oxidative metabolism in T1D attributed to a greater proportion of adaptive/maladaptive subtypes with low expression of TCA cycle and oxidative phosphorylation transcripts. Pseudotime progression associated with higher HbA1c, BMI, GBM, and lower insulin sensitivity and cortical oxidative metabolism. CONCLUSION: These early structural and metabolic changes in T1D kidneys may precede clinical DKD. CLINICALTRIALS: gov NCT04074668.

Modeling contrast-to-noise ratio from list mode reconstructions of 68Ga DOTATATE PET/CT: predicting detectability of hepatic metastases in shorter acquisition PET reconstructions.

BACKGROUND: Deep learning (DL) algorithms have shown promise in identifying and quantifying lesions in PET/CT. However, the accuracy and generalizability of these algorithms relies on large, diverse datasets which are time and labor intensive to curate. Modern PET/CT scanners may acquire data in list mode, allowing for multiple reconstructions of the same datasets with different parameters and imaging times. These reconstructions may provide a wide range of image characteristics to increase the size and diversity of datasets. Training algorithms with shorter imaging times and higher noise properties requires that lesions remain detectable. The purpose of this study is to model and predict the contrast-to-noise ratio (CNR) for shorter imaging times based on CNR from longer duration, lower noise images for 68Ga DOTATATE PET hepatic lesions and identify a threshold above which lesions remain detectable. METHODS: 68Ga DOTATATE subjects (n=20) with hepatic lesions were divided into two subgroups. The "Model" group (n=4 subjects; n=9 lesions; n=36 datapoints) was used to identify the relationship between CNR and imaging time. The "Test" group (n=16 subjects; n=44 lesions; n=176 datapoints) was used to evaluate the prediction provided by the model. RESULTS: CNR plotted as a function of imaging time for a subset of identified subjects was very well fit with a quadratic model. For the remaining subjects, the measured CNR showed a very high linear correlation with the predicted CNR for these lesions (R2 > 0.97) for all imaging durations. From the model, a threshold CNR=6.9 at 5-minutes predicted CNR > 5 at 2-minutes. Visual inspection of lesions in 2-minute images with CNR above the threshold in 5-minute images were assessed and rated as a 4 or 5 (probably positive or definitely positive) confirming 100% lesion detectability on the shorter 2-minute PET images. CONCLUSIONS: CNR for shorter DOTATATE PET imaging times may be accurately predicted using list mode reconstructions of longer acquisitions. A threshold CNR may be applied to longer duration images to ensure lesion detectability of shorter duration reconstructions. This method can aid in the selection of lesions to include in novel data augmentation techniques for deep learning.

Biomarker response to high-specific-activity I-131 meta-iodobenzylguanidine in pheochromocytoma/paraganglioma.

The objective of this study is to present the complete biomarker response dataset from a pivotal trial evaluating the efficacy and safety of high-specific-activity I-131 meta-iodobenzylguanidine in patients with advanced pheochromocytoma or paraganglioma. Biomarker status was assessed and post-treatment responses were analyzed for catecholamines, metanephrines, and serum chromogranin A. Complete biomarker response (normalization) or partial response, defined as at least 50% reduction from baseline if above the normal range, was evaluated at specified time points over a 12-month period. These results were correlated with two other study objectives: blood pressure control and objective tumor response as per RECIST 1.0. In this open-label, single-arm study, 68 patients received at least one therapeutic dose (~18.5 GBq (~500 mCi)) of high-specific-activity I-131 meta-iodobenzylguanidine. Of the patients, 79% and 72% had tumors associated with elevated total plasma free metanephrines and serum chromogranin A levels, respectively. Best overall biomarker responses (complete or partial response) for total plasma free metanephrines and chromogranin A were observed in 69% (37/54) and 80% (39/49) of patients, respectively. The best response for individual biomarkers was observed 6-12 months following the first administration of high-specific-activity I-131 meta-iodobenzylguanidine. Biochemical tumor marker response was significantly associated with both reduction in antihypertensive medication use (correlation coefficient 0.35; P = 0.006) as well as objective tumor response (correlation coefficient 0.36; P = 0.007). Treatment with high-specific-activity I-131 meta-iodobenzylguanidine resulted in long-lasting biomarker responses in patients with advanced pheochromocytoma or paraganglioma that correlated with blood pressure control and objective response rate. ClinicalTrials.gov number: NCT00874614.

Current status and future of targeted peptide receptor radionuclide positron emission tomography imaging and therapy of gastroenteropancreatic-neuroendocrine tumors.

Theranostics is the highly targeted molecular imaging and therapy of tumors. Targeted peptide receptor radionuclide therapy has taken the lead in demonstrating the safety and effectiveness of this molecular approach to treating cancers. Metastatic, well-differentiated gastroenteropancreatic neuroendocrine tumors may be most effectively imaged and treated with DOTATATE ligands. We review the current practice, safety, advantages, and limitations of DOTATATE based theranostics. Finally, we briefly describe the exciting new areas of development and future directions of gastroenteropancreatic neuroendocrine tumor theranostics.

Head and Neck Paragangliomas: An Update on the Molecular Classification, State-of-the-Art Imaging, and Management Recommendations.

Paragangliomas are neuroendocrine tumors that derive from paraganglia of the autonomic nervous system, with the majority of parasympathetic paragangliomas arising in the head and neck. More than one-third of all paragangliomas are hereditary, reflecting the strong genetic predisposition of these tumors. The molecular basis of paragangliomas has been investigated extensively in the past couple of decades, leading to the discovery of several molecular clusters and more than 20 well-characterized driver genes (somatic and hereditary), which are more than are known for any other endocrine tumor. Head and neck paragangliomas are largely related to the pseudohypoxia cluster and have been previously excluded from most molecular profiling studies. This review article introduces the molecular classification of paragangliomas, with a focus on head and neck paragangliomas, and discusses its impact on the management of these tumors. Genetic testing is now recommended for all patients with paragangliomas to provide screening and surveillance recommendations for patients and relatives. While CT and MRI provide excellent anatomic characterization of paragangliomas, gallium 68 tetraazacyclododecane tetraacetic acid-octreotate (ie, 68Ga-DOTATATE) has superior sensitivity and is recommended as first-line imaging in patients with head and neck paragangliomas with concern for multifocal and metastatic disease, patients with known multifocal and metastatic disease, and in candidates for targeted peptide-receptor therapy. Keywords: Molecular Imaging, MR Perfusion, MR Spectroscopy, Neuro-Oncology, PET/CT, SPECT/CT, Head/Neck, Genetic Defects © RSNA, 2022.

177Lu-PSMA Therapy.

Radiopharmaceutical therapy using 177Lu-prostate-specific membrane antigen (PSMA) is an effective prostate cancer treatment that was recently approved by the U.S. Food and Drug Administration. This method leverages the success of PSMA-targeted PET imaging, enabling delivery of targeted radiopharmaceutical therapy; has demonstrated a clear benefit in large prospective clinical trials; and promises to become part of the standard armamentarium of treatment for patients with prostate cancer. This review highlights the evidence supporting the use of this agent, along with important areas under investigation. Practical information on technology aspects, dose administration, nursing, and the role of the treating physician is highlighted. Overall, 177Lu-PSMA treatment requires close collaboration among referring physicians, nuclear medicine technologists, radiopharmacists, and nurses to streamline patient care.

Small target repeatability of 68Ga and 18F: effects of target concentration and imaging time on SUV measurements in clinically relevant phantoms.

Quantification of tumor uptake using PET imaging is important for the evaluation of therapy response. For 18F FDG PET scans, a change in uptake of 25% is commonly considered significant. For scans using novel radiopharmaceuticals, the threshold of significance is unclear. Factors including imaging time, tumor size, activity concentration, and radiopharmaceutical may affect the repeatablity of uptake metrics. This work evaluates the effect of these parameters on the repeatablity of maximum SUV (SUVmax) and mean SUV (SUVmean) in phantoms using 18F and 68Ga. An Esser PET phantom (Data Spectrum, Durham NC) was scanned on a Biograph Horizon PET/CT scanner (Siemens Medical Solutions, Malvern PA) using 18F and 68Ga. Data were acquired for 5 minutes with reconstructions between 0.5-5 minutes. The background activity mimicked clinical scans with target-to-background (T/B) ratios from 1.7-19.8. The SUVmax and SUVmean were measured for 5 slices. The mean, standard deviation, and coefficient of variation (COV) were calculated. The effects of radionuclide, imaging time, activity concentration, and target size on COV were evaluated using multivariate gamma regressions. COV for 68Ga was 40% higher and 54% higher on average than for 18F for SUVmax and SUVmean, respectively. Decreased lesion size, imaging time, and activity concentration were significantly associated with increased COV for both metrics (P < 0.001). COV was substantially reduced at high T/B for 68Ga. At the highest T/B the COV for SUVmax and SUVmean was within the typical range seen for 18F. COV is relatively high for small targets (8 mm) but is dramatically reduced with high radiotracer uptake.

Automated liver lesion detection in 68Ga DOTATATE PET/CT using a deep fully convolutional neural network.

BACKGROUND: Gastroenteropancreatic neuroendocrine tumors most commonly metastasize to the liver; however, high normal background 68Ga-DOTATATE activity and high image noise make metastatic lesions difficult to detect. The purpose of this study is to develop a rapid, automated and highly specific method to identify 68Ga-DOTATATE PET/CT hepatic lesions using a 2D U-Net convolutional neural network. METHODS: A retrospective study of 68Ga-DOTATATE PET/CT patient studies (n = 125; 57 with 68Ga-DOTATATE hepatic lesions and 68 without) was evaluated. The dataset was randomly divided into 75 studies for the training set (36 abnormal, 39 normal), 25 for the validation set (11 abnormal, 14 normal) and 25 for the testing set (11 abnormal, 14 normal). Hepatic lesions were physician annotated using a modified PERCIST threshold, and boundary definition by gradient edge detection. The 2D U-Net was trained independently five times for 100,000 iterations using a linear combination of binary cross-entropy and dice losses with a stochastic gradient descent algorithm. Performance metrics included: positive predictive value (PPV), sensitivity, F1 score and area under the precision-recall curve (PR-AUC). Five different pixel area thresholds were used to filter noisy predictions. RESULTS: A total of 233 lesions were annotated with each abnormal study containing a mean of 4 ± 2.75 lesions. A pixel filter of 20 produced the highest mean PPV 0.94 ± 0.01. A pixel filter of 5 produced the highest mean sensitivity 0.74 ± 0.02. The highest mean F1 score 0.79 ± 0.01 was produced with a 20 pixel filter. The highest mean PR-AUC 0.73 ± 0.03 was produced with a 15 pixel filter. CONCLUSION: Deep neural networks can automatically detect hepatic lesions in 68Ga-DOTATATE PET. Ongoing improvements in data annotation methods, increasing sample sizes and training methods are anticipated to further improve detection performance.

Physical characteristics of 68Ga DOTATATE PET/CT affecting small lesion detectability.

BACKGROUND AND PURPOSE: 68Ga DOTATATE PET/CT protocols are similar to 18F FDG protocols despite differences in physical properties, biodistribution, and tumor uptake. The purpose of this study is to evaluate the impact of scan time (counts), and target activity on signal-to-noise ratio (SNR) in various sized targets, or lesions. To evaluate this, phantom experiments and analysis of clinical 68Ga DOTATATE PET/CT studies were performed. MATERIALS AND METHODS: 68Ga was first compared to 18F in phantom studies to evaluate recovery coefficients and SNR. 68Ga phantom studies were also acquired in list mode, and at varying target activities to evaluate the effects of acquisition time and high target concentrations on SNR in clinically relevant small (8 mm) and larger targets (≥ 12 mm). Clinical studies (n = 50) were analyzed to determine if phantom target concentrations and SNR are present in clinical 68Ga DOTATATE studies at similarly very high tumor activity concentrations (n = 159). RESULTS: In phantoms, recovery coefficient and SUVmax for 68Ga were ~87% of 18F. SNR for 68Ga was ~65% of 18F. For the 68Ga small target (8 mm) at standard T/B = 2.4, increasing scan time from 5 to 15 minutes increased SNR from < 1 to 1.6, and did not result in target identification. Increasing T/B from 2.4 to 10.9, however, dramatically increased SNR from < 1 to 22.3. Increased T/B resulted in clear visibility of the 8 mm target, even for 1-minute scans. In patients, high hepatic tumor SUVmax (27.3±29.6), resulted in high SNR (12.5±9.8). For extrahepatic tumors, high SUVmax (41.6±42.8), resulted in high SNR (43.8±49.9). CONCLUSION: Very high target or T/B, even in small targets, can offset the physical limitations of 68Ga. High target uptake and high T/B are primary factors influencing small lesion detectability.

Increasing uptake time in FDG-PET: standardized uptake values in normal tissues at 1 versus 3 h.

OBJECTIVE: Positron emission tomography (PET) imaging at more than 1 h after 2-deoxy-2-[(18)F]fluoro-D: -glucose (FDG) administration may result in less blood pool activity and possibly decreased normal FDG uptake in tissues such as liver. Lower normal background activity could be an important component of improved image contrast on delayed imaging. Increasing FDG uptake in normal organs, however, may mitigate the beneficial effects of blood pool clearance. The purpose of this study is to determine the normal tissue and blood pool FDG uptake at 1 and 3 h after injection. SUBJECTS AND METHODS: Ninety-nine patients with known or suspected malignancy referred for FDG-PET-computed tomography (CT) were retrospectively evaluated. PET imaging was performed at either 1 h (60 +/- 15 min; n = 50) or at 3 h (180 +/- 15 min; n = 49) after FDG administration. Normal tissue FDG uptake without involvement by malignancy or influenced by artifact (misregistration, "brown fat," focal muscle uptake, focal atherosclerotic disease) was confirmed by inspection of both the PET and CT scans. Aortic blood pool, adipose tissue, bone marrow, cerebellum, liver, lungs, muscle, and spleen were quantitatively evaluated by CT-guided region of interest analysis in three contiguous slices. Mean standardized uptake values (SUVs) were analyzed using one-way analysis of variance. RESULTS: Mean SUVs on the 3- versus 1-h images were significantly lower for aortic blood pool 13% (p < 0.0001) and adipose tissue 20% (p < 0.008). FDG uptake showed significant increases at 3 h compared to 1-h imaging in the cerebellum 40% (p < 0.0001), bone marrow 25% (p = 0.003), muscle 21% (p = 0.0004), and spleen 13% (p = 0.01). The liver and lung showed no significant differences (1%, p = 0.85; -2%, p = 0.62, respectively). CONCLUSIONS: On FDG imaging at 3 h compared to 1 h, significant changes were apparent, but the magnitude of changes was modest overall. Three-hour delayed imaging demonstrated significantly lower aortic blood pool and adipose tissue activity and significantly higher cerebellum, muscle, spleen, and bone marrow activity. Hepatic and lung activities were not significantly different. These results suggest that previously reported improvements in tumor image contrast with delayed imaging may be primarily due to cumulative FDG uptake within the tumor rather than reduction in normal background activity.

Feasibility of rapid integrated radiation therapy planning with follow-up FDG PET/CT to improve overall treatment assessment in head and neck cancer.

Inflammatory changes and residual disease are difficult to distinguish after high dose, definitive radiotherapy of head and neck malignancies. FDG uptake located within a high dose field may more likely represent inflammatory changes, and FDG uptake outside of the radiation field could represent unsuspected and under treated disease. In situ knowledge of the precise radiotherapy fields, therefore, may be useful in distinguishing these etiologies. This study aimed to evaluate the clinical feasibility of rapid integration of radiation treatment field images during follow-up FDG PET/CT imaging. Twenty head and neck cancer patients who underwent radiation therapy were identified. A MIM based workflow was created which fused the radiation treatment CT, including the planning volumes and isodose curves, into the follow-up imaging. Two board certified physicians, blinded to treatment outcome, reviewed the follow-up exams, half with the treatment information and half without. Each exam was scored for recurrent or residual disease, confidence of the read and a qualitative assessment to the overall usefulness of the treatment plan. Interpretation accuracy improved from 80 to 90% with integration of the treatment plan. Similarly, the sensitivity improved from 71% to 86%, while the specificity increased from 85% to 92%. Confidence also increased by 0.7 on a 5 point scale for both readers. Data demonstrate the clinical feasibility of rapidly incorporating radiation treatment dosimetry into follow-up FDG PET/CT exams in patients with head and neck cancer. Preliminary results demonstrated a simple, efficient method which improved accuracy of interpretation and overall reader confidence.

Neuroendocrine prostate cancer or prostatitis? An unusual false positive on gallium-68 DOTA-Tyr3-octreotate positron emission tomography/computed tomography in a patient with known metastatic neuroendocrine tumor.

The importance of gallium-68 DOTA-Tyr3-octreotate (68Ga DOTATATE) positron emission tomography/computed tomography (PET/CT) in the imaging of neuroendocrine tumors (NETs) has grown substantially over the past decade and is becoming markedly more common. We present the case of a male with known metastatic NET who underwent 68Ga DOTATATE PET/CT for restaging, incidentally revealing intense uptake of the prostate with a maximum standard uptake value of 17.4. Due to the patient's medical history, this finding was concerning for neuroendocrine prostate cancer. However, core biopsies of the prostate were negative for malignancy and positive for chronic inflammation. Chronic prostatitis is a very common condition in adult males and is often asymptomatic. Inflammatory conditions, including prostatitis, are important causes of false-positive findings on 68Ga DOTATATE PET/CT and should be considered as part of the differential diagnosis, even in an asymptomatic patient.