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.

First detection of Omicron variant BA.4.1 lineage in dogs, Chile.

SARS-CoV-2's rapid global spread caused the declaration of COVID-19 as a pandemic in March 2020. Alongside humans, domestic dogs and cats are also susceptible to infection. However, limited reports on pet infections in Chile prompted a comprehensive study to address this knowledge gap. Between March 2021 and March 2023, the study assessed 65 pets (26 dogs and 39 cats) from 33 COVID-19+ households alongside 700 nasal swabs from animals in households with unknown COVID-19 status. Using RT-PCR, nasal, fecal, and environmental samples were analyzed for the virus. In COVID-19+ households, 6.06% tested positive for SARS-CoV-2, belonging to 3 dogs, indicating human-to-pet transmission. Pets from households with unknown COVID-19 status tested negative for the virus. We obtained 2 SARS-CoV-2 genomes from animals, that belonged to Omicron BA.4.1 variant, marking the first report of pets infected with this lineage globally. Phylogenetic analysis showed these sequences clustered with human sequences collected in Chile during the same period when the BA.4.1 variant was prevalent in the country. The prevalence of SARS-CoV-2 in Chilean pets was relatively low, likely due to the country's high human vaccination rate. Our study highlights the importance of upholding and strengthening human vaccination strategies to mitigate the risk of interspecies transmission. It underscores the critical role of the One Health approach in addressing emerging zoonotic diseases, calling for further research on infection dynamics and risk factors for a comprehensive understanding.

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.

Preparing future STEM faculty through flexible teaching professional development.

We have prepared thousands of future STEM faculty around the world to adopt evidence-based instructional practices through their participation in two massive open online courses (MOOCs) and facilitated in-person learning communities. Our novel combination of asynchronous online and coordinated, structured face-to-face learning community experiences provides flexible options for STEM graduate students and postdoctoral fellows to pursue teaching professional development. A total of 14,977 participants enrolled in seven offerings of the introductory course held 2014-2018, with 1,725 participants (11.5% of enrolled) completing the course. Our results of high levels of engagement and learning suggest that leveraging the affordances of educational technologies and the geographically clustered nature of this learner demographic in combination with online flexible learning could be a sustainable model for large scale professional development in higher education. The preparation of future STEM faculty makes an important difference in establishing high-quality instruction that meets the diverse needs of all undergraduate students, and the initiative described here can serve as a model for increasing access to such preparation.

A national professional development program fills mentoring gaps for postdoctoral researchers.

The Postdoc Academy: Succeeding as a Postdoc was designed to build postdocs' skills in career transition, career planning, collaborative research, resilience, and self-reflection. This study examined self-reported changes in five skills as learners progressed through the course. Data were collected from participants who responded to both pre- and post-surveys and engaged with the course learning activities. Results from repeated measures multivariate analysis of variance revealed that all of the self-reported perceptions of skills improved significantly upon completion of the course. Hierarchical regressions revealed that underrepresented minority learners had greater gains in their development of skills in career planning, resilience, and self-reflection. Qualitative analysis of learners' responses to learning activities found that postdocs perceived networking and mentor support as contributing factors to their skill advancement while tensions among multiple obligations and concerns of uncertainties were significant challenges to applying those skills.

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.

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.

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.

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.

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.

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.

Genetic associations of fatigue and other symptoms following breast cancer treatment: A prospective study.

BACKGROUND: Cancer-related fatigue, mood disturbances, pain and cognitive disturbance are common after adjuvant cancer therapy, but vary considerably between individuals despite common disease features and treatment exposures. A genetic basis for this variability was explored in a prospective cohort. METHODS: Physical and psychological health of women were assessed prospectively following therapy for early stage breast cancer with self-report questionnaires. Participation in a genetic association sub-study was offered. Indices for the key symptom domains of fatigue, pain, depression, anxiety, and neurocognitive difficulties were empirically derived by principal components analysis from end-treatment questionnaires, and then applied longitudinally. Genetic associations were sought with functional single nucleotide polymorphisms (SNPs) in pro- and anti-inflammatory cytokine genes - tumour necrosis factor (TNF)-α (-308 â€‹GG), interferon (IFN)-É£ (+874 â€‹TA), interleukin (IL)-10 (1082 â€‹GA and -592 CA), IL-6 (-174 â€‹GC), IL-1ß (-511 â€‹GA). RESULTS: Questionnaire data was available for 210 participants, of whom 111 participated in the genetic sub-study. As expected, symptom domain scores generally improved over several months following treatment completion. Tumour and adjuvant treatment related factors were unassociated with either severity or duration of the individual symptom domains, but severity of symptoms at end-treatment was strongly associated with duration for each domain (all p â€‹< â€‹0.05). In multivariable analyses, risk genotypes were independently associated with: fatigue with IL-6 -174 â€‹GG/GC and IL-10 -1082 GG; depression and anxiety with IL-10 -1082 AA; neurocognitive disturbance: TNF-α -308 GG; depression IL-1ß (all p â€‹< â€‹0.05). The identified SNPs also had cumulative effects in prolonging the time to recovery from the associated symptom domain. CONCLUSIONS: Genetic factors contribute to the severity and duration of common symptom domains after cancer therapy.

Bacterial Quorum-Sensing Regulation Induces Morphological Change in a Key Host Tissue during the Euprymna scolopes-Vibrio fischeri Symbiosis.

Microbes colonize the apical surfaces of polarized epithelia in nearly all animal taxa. In one example, the luminous bacterium Vibrio fischeri enters, grows to a dense population within, and persists for months inside, the light-emitting organ of the squid Euprymna scolopes. Crucial to the symbiont's success after entry is the ability to trigger the constriction of a host tissue region (the "bottleneck") at the entrance to the colonization site. Bottleneck constriction begins at about the same time as bioluminescence, which is induced in V. fischeri through an autoinduction process called quorum sensing. Here, we asked the following questions: (i) Are the quorum signals that induce symbiont bioluminescence also involved in triggering the constriction? (ii) Does improper signaling of constriction affect the normal maintenance of the symbiont population? We manipulated the presence of three factors, the two V. fischeri quorum signal synthases, AinS and LuxI, the transcriptional regulator LuxR, and light emission itself, and found that the major factor triggering and maintaining bottleneck constriction is an as yet unknown effector(s) regulated by LuxIR. Treating the animal with chemical inhibitors of actin polymerization reopened the bottlenecks, recapitulating the host's response to quorum-sensing defective symbionts, as well as suggesting that actin polymerization is the primary mechanism underlying constriction. Finally, we found that these host responses to the presence of symbionts changed as a function of tissue maturation. Taken together, this work broadens our concept of how quorum sensing can regulate host development, thereby allowing bacteria to maintain long-term tissue associations. IMPORTANCE Interbacterial signaling within a host-associated population can have profound effects on the behavior of the bacteria, for instance, in their production of virulence/colonization factors; in addition, such signaling can dictate the nature of the outcome for the host, in both pathogenic and beneficial associations. Using the monospecific squid-vibrio model of symbiosis, we examined how quorum-sensing regulation by the Vibrio fischeri population induces a biogeographic tissue phenotype that promotes the retention of this extracellular symbiont within the light organ of its host, Euprymna scolopes. Understanding the influence of bacterial symbionts on key sites of tissue architecture has implications for all horizontally transmitted symbioses, especially those that colonize an epithelial surface within the host.

Theory of change models deepen online learning evaluation.

Massive Open Online Courses (MOOCs) have gained traction as resources for professional development. This article presents the method that we used to evaluate a professional development MOOC for postdoctoral trainees that was created by a university consortium in the US. Most approaches to evaluating MOOCs focus on analysis of participation, outcomes from course assignments, self-reported learning outcomes, course completion and user pathways through the online content or clickstream data. Few published evaluations describe in detail how learning happens within online courses and the anticipated medium and longer term cognitive and behavioral outcomes on participants. This work aims to guide those who are designing, implementing and evaluating MOOCs through applying theories of change to focus evaluation on the process of learning. This approach can be used as a complement to traditional approaches for evaluating MOOCs. We described how we worked with the MOOC team building the content to develop a theory of change for each module (or lesson) within the MOOC and used the theory of change to guide evaluation of short and medium term participant cognitive, affective and attitudinal, and behavioral outcomes. Finally, we share lessons learned and suggestions for implementing theories of change in both the design and evaluation phases of MOOC development.

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.

Short bowel syndrome and the impact on patients and their families: a qualitative study.

BACKGROUND: Short bowel syndrome (SBS) is a malabsorptive condition that can result in intestinal failure (SBS-IF). Many patients with SBS-IF require home parenteral nutrition (PN) for survival. However, PN has profound effects on patients and their family members. The present study aimed to understand the lived experience of SBS-IF for patients and their families. METHODS: In-depth semi-structured qualitative interviews were conducted with 15 patients with SBS-IF and five adult family members living with someone with SBS-IF. A patient-centric approach was taken, with a patient steering group providing input and guidance to develop the interview guide. Key concepts were identified using thematic analysis of interview transcripts. RESULTS: Patients' lives were dominated by having SBS-IF. They described physical impacts that included patient-reported signs and symptoms and physical restrictions comprising of restrictions on daily life, actives of daily living and physical functioning. In addition, they encountered emotional impacts with a plethora of negative feelings and social impacts, such as difficulties socialising and maintaining relationships. Patients coped by adapting their life around SBS-IF, having support and adopting an attitude of gratitude and acceptance. Family members were also affected and, along with patients, appreciated the respite of a night off from infusions. CONCLUSIONS: Patients and families face many difficulties with SBS-IF. Healthcare professionals can support patients by facilitating them explore what others have found beneficial; adapting their life around PN, viewing PN with acceptance and trying to cultivate gratitude. Further research into the support required for families may be beneficial.

A Case Series of X-Linked Deafness-2 with Sensorineural Hearing Loss, Stapes Fixation, and Perilymphatic Gusher: MR Imaging and Clinical Features of Hypothalamic Malformations.

X-linked deafness-2 (DFNX2) is an X-linked recessive disorder characterized by profound sensorineural hearing loss and a pathognomonic temporal bone deformity. Because hypothalamic malformations associated with DFNX2 have been rarely described, we aimed to further describe these lesions and compare them with features of a nonaffected population. All patients diagnosed with DFNX2 between 2006 and 2019 were included and compared with age-matched patients with normal MR imaging findings and without hypothalamic dysfunction. MR imaging features differing between groups were selected to help identify DFNX2. Sensitivity and specificity were calculated for these features. Agreement among 3 radiologists was quantified using the index κ. Information on the presence or absence of gelastic seizures, precocious puberty, or delayed puberty was also gathered. We selected distinctive MR imaging features of hypothalamic malformations in DFNX2. The feature selected on axial T2 images was the folded appearance of the ventromedial hypothalamus (sensitivity, 100%; specificity, 95.8%) characterized by an abnormal internal/external cleft (sensitivity, 100%; specificity, 95.7%). On coronal T2, the first distinctive feature was a concave morphology of the medial eminence (sensitivity, 100%; specificity, 97.1%), the second feature was at least 1 hypothalamic-septum angle ≥90° (sensitivity, 90%; specificity, 72.5%), and the third feature was a forebrain-hypothalamic craniocaudal length of ≥6 mm (sensitivity, 70%; specificity, 79.7%). Clinical features were also distinctive because 9 patients with DFNX2 did not present with gelastic seizures or precocious puberty. One patient had delayed puberty. The κ index and intraclass correlation coefficient ranged between 0.78 and 0.95. Imaging and clinical features of the hypothalamus suggest that there is a hypothalamic malformation associated with DFNX2. Early assessment for pubertal delay is proposed.

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.