Multicenter Experience with Good Manufacturing Practice Production of [11C]PiB for Amyloid Positron Emission Tomography Imaging.

Alzheimer's disease (AD) is a neurodegenerative disorder with increasing global prevalence and accounts for over half of all dementia cases. Early diagnosis is paramount for not only the management of the disease, but also for the development of new AD treatments. The current golden standard for diagnosis is performed by positron emission tomography (PET) scans with the tracer [11C]Pittsburg Compound B ([11C]PiB), which targets amyloid beta protein (Aß) that builds up as plaques in the brain of AD patients. The increasing demand for AD diagnostics is in turn expected to drive an increase in [11C]PiB-PET scans and the setup of new [11C]PiB production lines at PET centers globally. Here, we present the [11C]PiB production setups, experiences, and use from four Danish PET facilities and discuss the challenges and potential pitfalls of [11C]PiB production. We report on the [11C]PiB production performed with the 6-OH-BTA-0 precursor dissolved in either dry acetone or 2-butanone and by using either [11C]CO2 or [11C]CH4 as 11C- precursors on three different commercial synthesis modules: TracerLab FX C Pro, ScanSys, or TracerMaker. It was found that the [11C]CO2 method gives the highest radioactive yield (1.5 to 3.2 GBq vs. 0.8 ± 0.3 GBq), while the highest molar activity (98.0 ± 61.4 GBq/µmol vs. 21.2 to 95.6 GBq/µmol) was achieved using [11C]CH4. [11C]PiB production with [11C]CO2 on a TracerLab FX C Pro offered the most desirable results, with the highest yield of 3.17 ± 1.20 GBq and good molar activity of 95.6 ± 44.2 GBq/µmol. Moreover, all reported methods produced [11C]PiB in quantities suitable for clinical applications, thus providing a foundation for other PET facilities seeking to establish their own [11C]PiB production.

Pancreatic Cyst Size Measurement on Magnetic Resonance Imaging Compared to Pathology.

BACKGROUND: While multiple cyst features are evaluated for stratifying pancreatic intraductal papillary mucinous neoplasms (IPMN), cyst size is an important factor that can influence treatment strategies. When magnetic resonance imaging (MRI) is used to evaluate IPMNs, no universally accepted sequence provides optimal size measurements. T2-weighted coronal/axial have been suggested as primary measurement sequences; however, it remains unknown how well these and maximum all-sequence diameter measurements correlate with pathology size. This study aims to compare agreement and bias between IPMN long-axis measurements on seven commonly obtained MRI sequences with pathologic size measurements. METHODS: This retrospective cohort included surgically resected IPMN cases with preoperative MRI exams. Long-axis diameter tumor measurements and the presence of worrisome features and/orhigh-risk stigmata were noted on all seven MRI sequences. MRI size and pathology agreement and MRI inter-observer agreement involved concordance correlation coefficient (CCC) and intraclass correlation coefficient (ICC), respectively. The presence of worrisome features and high-risk stigmata were compared to the tumor grade using kappa analysis. The Bland-Altman analysis assessed the systematic bias between MRI-size and pathology. RESULTS: In 52 patients (age 68 ± 13 years, 22 males), MRI sequences produced mean long-axis tumor measurements from 2.45-2.65 cm. The maximum MRI lesion size had a strong agreement with pathology (CCC = 0.82 (95% CI: 0.71-0.89)). The maximum IPMN size was typically observed on the axial T1 arterial post-contrast and MRCP coronal series and overestimated size versus pathology with bias +0.34 cm. The radiologist interobserver agreement reached ICCs 0.74 to 0.91 on the MRI sequences. CONCLUSION: The maximum MRI IPMN size strongly correlated with but tended to overestimate the length compared to the pathology, potentially related to formalin tissue shrinkage during tissue processing.

Laparoscopic cholecystectomy induce tension pneumocephalus in a patient with ventriculoperitoneal shunt: A case report and literature review.

INTRODUCTION AND PATIENT CONCERNS: We report on a 45-year-old woman who has a ventriculoperitoneal shunt (VPS), experienced drowsy mental status, with hypesthesia and hemiplegia on the left side. Ten days ago she underwent laparoscopic cholecystectomy (LC). Computed tomography revealed tension pneumocephalus, with severe compression on the right side of the brain. INTERVENTIONS AND DIAGNOSIS: She underwent 2 surgeries, the first surgery was to place a subdural drainage catheter, however, the pneumocephalus relapsed after withdrawing the catheter, and the later surgery was to replace the new VPS. OUTCOMES: After replacing the VPS, the patient recovers completely after 10 weeks of follow-up. CONCLUSION: To our knowledge, this is the first report of LC-induced tension pneumocephalus in a patient with VPS. The purpose of this study is to share our experience, with the hypothesized mechanism being the retrograde air through the VPS valve because of high abdominal pressurization. We recommend noting the existence of the VPS when the LC or any abdominal laparoscopy is performed. The VPS should be clamped during any laparoscopic procedure until complete depressurization. Furthermore, all patients with VPS who have neurological deterioration after abdominal laparoscopy should be treated as having the diagnosis of a tension pneumocephalus. These patients need emergency surgery to replace VPS and set the valve for high-pressure, which can result in a quick and complete recovery.

Epidemiological and genetic characterization of porcine epidemic diarrhea virus in the Mekong Delta, Vietnam, from 2015 to 2017.

Porcine epidemic diarrhea (PED) virus (PEDV) is a highly contagious virus. PED was first identified in 2008 and has greatly affected the Vietnamese pig production economy. The aim of this study was to investigate the epidemiological and genetic characteristics of PEDV in piglet herds in the Mekong Delta, Vietnam. Diarrheal stool and intestinal samples from 2262 piglets from 191 herds in five provinces were collected to test for the presence of PEDV. Ten PEDV strains were randomly selected for sequencing, and four genes encoding PEDV structural proteins were analyzed. The rates of herds and samples positive for PEDV were 27.23% and 27.72%, respectively. In positive herds, the morbidity and mortality of PEDV-positive piglets were 97.97% and 79.06%, respectively, with most of the infected piglets under 7 days of age. Phylogenetic analysis showed that the 10 PEDV strains from this study clustered with genotype G2 strains from Vietnam and neighboring countries. Many amino acid substitutions were identified in important antigenic regions in the spike protein of the 10 strains when compared to four PEDV vaccine strains. This study provides novel insights into the epidemiology and genetic diversity of circulating PEDV strains, which could facilitate the development of an appropriate and proactive strategy for controlling PED.

Radical resection of trigeminal schwannoma at the cerebellopontine angle with support of the digital robotic exoscope Synaptive Modus V system: A case report and literature review.

RATIONALE AND PATIENT CONCERNS: We report on a 67-year-old woman who experienced drowsy mental status, facial numbness, and hearing loss on the right side; the symptom gradually worsened over the last 4 years. Brain magnetic resonance imaging revealed a 4.8 × 1.8 × 2.6 cm lesion located in the right cerebellopontine angle. INTERVENTIONS: She underwent surgery with the retrosigmoid suboccipital approach and support from the digital robotic exoscope Synaptive Modus V system. To the best of our knowledge, this is the first reported case that used the robotic exoscope system in Vietnam, and also in Asia. DIAGNOSIS: We performed radical resection of the tumor, the surgery position and the pathology result concluded the diagnosis was trigeminal schwannoma. OUTCOMES: After 30 months of follow-up, she fully recovered and the magnetic resonance imaging showed radical resection of the tumor. LESSONS: The aim of this study is to share our experience with the robotic exoscope system, which can improve optical field and image resolution, hence creating an opportunity for surgery that otherwise is impossible. The application of this robotic exoscope system is a breakthrough in neurosurgery in developing countries, such as Vietnam.

Investigation of a river-tunnel effect on PM2.5 concentrations in New York City subway stations.

It is well-documented that subway stations exhibit high fine particulate matter (PM2.5) concentrations. Little is known about the potential of river-tunnels to increase PM2.5 concentrations in subways. We hypothesized a "river-tunnel" effect exists: Stations adjacent to poorly ventilated tunnels that travel beneath rivers exhibit higher PM2.5 concentrations than more distant stations. Accordingly, the PM2.5 concentrations were monitored at stations adjacent to and two- and three-stations distant from the river-tunnel. Multivariate linear regression analysis was conducted to disentangle how proximity to a river-tunnel and other factors (e.g., depth) influence concentrations. Stations adjacent to a river-tunnel had 80-130% higher PM2.5 concentrations than more distant stations. Moreover, distance from a river-tunnel was the strongest PM2.5-influencing factor This distance effect was not observed at underground stations adjacent to a river-bridge. The "river-tunnel" effect explains some of the inter-station variability in subway PM2.5 concentrations. These results support the need for improving ventilation systems in subways.

Application of Machine Learning in Epileptic Seizure Detection.

Epileptic seizure is a neurological condition caused by short and unexpectedly occurring electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide have had an epileptic seizure. Experiencing an epileptic seizure can have serious consequences for the patient. Automatic seizure detection on electroencephalogram (EEG) recordings is essential due to the irregular and unpredictable nature of seizures. By thoroughly analyzing EEG records, neurophysiologists can discover important information and patterns, and proper and timely treatments can be provided for the patients. This research presents a novel machine learning-based approach for detecting epileptic seizures in EEG signals. A public EEG dataset from the University of Bonn was used to validate the approach. Meaningful statistical features were extracted from the original data using discrete wavelet transform analysis, then the relevant features were selected using feature selection based on the binary particle swarm optimizer. This facilitated the reduction of 75% data dimensionality and 47% computational time, which eventually sped up the classification process. After having been selected, relevant features were used to train different machine learning models, then hyperparameter optimization was utilized to further enhance the models' performance. The results achieved up to 98.4% accuracy and showed that the proposed method was very effective and practical in detecting seizure presence in EEG signals. In clinical applications, this method could help relieve the suffering of epilepsy patients and alleviate the workload of neurologists.

An Analysis of Vocal Features for Parkinson's Disease Classification Using Evolutionary Algorithms.

Parkinson's Disease (PD) is a brain disorder that causes uncontrollable movements. According to estimation, roughly ten million individuals worldwide have had or are developing PD. This disorder can have severe consequences that affect the patient's daily life. Therefore, several previous works have worked on PD detection. Automatic Parkinson's Disease detection in voice recordings can be an innovation compared to other costly methods of ruling out examinations since the nature of this disease is unpredictable and non-curable. Analyzing the collected vocal records will detect essential patterns, and timely recommendations on appropriate treatments will be extremely helpful. This research proposed a machine learning-based approach for classifying healthy people from people with the disease utilizing Grey Wolf Optimization (GWO) for feature selection, along with Light Gradient Boosted Machine (LGBM) to optimize the model performance. The proposed method shows highly competitive results and has the ability to be developed further and implemented in a real-world setting.

Evidence-based Shared-Decision-Making Assistant (SDM-assistant) for choosing antipsychotics: protocol of a cluster-randomized trial in hospitalized patients with schizophrenia.

BACKGROUND: Choosing an antipsychotic medication is an important medical decision in the treatment of schizophrenia. This decision requires risk-benefit assessments of antipsychotics, and thus, shared-decision making between physician and patients is strongly encouraged. Although the efficacy and side-effect profiles of antipsychotics are well-established, there is no clear framework for the communication of the evidence between physicians and patients. For this reason, we developed an evidence-based shared-decision making assistant (SDM-assistant) that presents high-quality evidence from network meta-analysis on the efficacy and side-effect profile of antipsychotics and can be used as a basis for shared-decision making between physicians and patients when selecting antipsychotic medications. METHODS: The planned matched-pair cluster-randomised trial will be conducted in acute psychiatric wards (n = 14 wards planned) and will include adult inpatients with schizophrenia or schizophrenia-like disorders (N = 252 participants planned). On the intervention wards, patients and their treating physicians will use the SDM-assistant, whenever a decision on choosing an antipsychotic is warranted. On the control wards, antipsychotics will be chosen according to treatment-as-usual. The primary outcome will be patients' perceived involvement in the decision-making during the inpatient stay as measured with the SDM-Q-9. We will also assess therapeutic alliance, symptom severity, side-effects, treatment satisfaction, adherence, quality of life, functioning and rehospitalizations as secondary outcomes. Outcomes could be analysed at discharge and at follow-up after three months from discharge. The analysis will be conducted per-protocol using mixed-effects linear regression models for continuous outcomes and logistic regression models using generalised estimating equations for dichotomous outcomes. Barriers and facilitators in the implementation of the intervention will also be examined using a qualitative content analysis. DISCUSSION: This is the first trial to examine a decision assistant specifically designed to facilitate shared-decision making for choosing antipsychotic medications, i.e., SDM-assistant, in acutely ill inpatients with schizophrenia. If the intervention can be successfully implemented, SDM-assistant could advance evidence-based medicine in schizophrenia by putting medical evidence on antipsychotics into the context of patient preferences and values. This could subsequently lead to a higher involvement of the patients in decision-making and better therapy decisions. TRIAL REGISTRATION: German Clinical Trials Register (ID: DRKS00027316 , registration date 26.01.2022).

Semi-supervised learning for medical image classification using imbalanced training data.

BACKGROUND AND OBJECTIVE: Medical image classification is often challenging for two reasons: a lack of labelled examples due to expensive and time-consuming annotation protocols, and imbalanced class labels due to the relative scarcity of disease-positive individuals in the wider population. Semi-supervised learning methods exist for dealing with a lack of labels, but they generally do not address the problem of class imbalance. Hence, the purpose of this study is to explore a new approach to perturbation-based semi-supervised learning which tackles the problem of applying semi-supervised learning to medical image classification with imbalanced training data. METHODS: In this study we propose Adaptive Blended Consistency Loss (ABCL), a simple yet effective drop-in replacement for consistency loss in perturbation-based semi-supervised learning methods. ABCL counteracts data skew by adaptively mixing the target class distribution of the consistency loss in accordance with class frequency. Our proposed method is evaluated and compared with existing methods on two different imbalanced medical image classification datasets. An ablation study is also provided to analyse the properties and effectiveness of our proposed method. RESULTS: Our experiments with ABCL reveal improvements to unweighted average recall (UAR) when compared with existing consistency losses that are not designed to counteract class imbalance and other existing methods. Our proposed ABCL method is able to improve the performance of the baseline consistency loss approach from 0.59 to 0.67 UAR and outperforms methods that address the class imbalance problem for labelled data (between 0.51 and 0.59 UAR) and for unlabelled data (0.61 UAR) on the imbalanced skin cancer dataset. On the imbalanced retinal fundus glaucoma dataset, ABCL (combined with Weighted Cross Entropy loss) achieves 0.67 UAR, which is an improvement over the best existing approach (0.57 UAR). CONCLUSIONS: Overall the results show the effectiveness of ABCL to alleviate the class imbalance problem for semi-supervised classification for medical images.

GMP production of 6-[18F]Fluoro-L-DOPA for PET/CT imaging by different synthetic routes: a three center experience.

BACKGROUND: The radiofluorinated levodopa analogue 6-[18F]F-L-DOPA (3,4-dihydroxy-6-18F-L-phenylalanine) is a commonly employed radiotracer for PET/CT imaging of multiple oncological and neurological indications. An unusually large number of different radiosyntheses have been published to the point where two different Ph. Eur. monographs exist depending on whether the chemistry relies on electrophilic or nucleophilic radiosubstitution of appropriate chemical precursors. For new PET imaging sites wishing to adopt [18F]FDOPA into clinical practice, selecting the appropriate production process may be difficult and dependent on the clinical needs of the site. METHODS: Data from four years of [18F]FDOPA production at three different clinical sites are collected and compared. These three sites, Aarhus University Hospital (AUH), Odense University Hospital (OUH), and Herlev University Hospital (HUH), produce the radiotracer by different radiosynthetic routes with AUH adopting an electrophilic strategy, while OUH and HUH employ two different nucleophilic approaches. Production failure rates, radiochemical yields, and molar activities are compared across sites and time. Additionally, the clinical use of the radiotracer over the time period considered at the different sites are presented and discussed. RESULTS: The electrophilic substitution route suffers from being demanding in terms of cyclotron operation and maintenance. This challenge, however, was found to be compensated by a production failure rate significantly below that of both nucleophilic approaches; a result of simpler chemistry. The five-step nucleophilic approach employed at HUH produces superior radiochemical yields compared to the three-step approach adopted at OUH but suffers from the need for more comprehensive synthesis equipment given the multi-step nature of the procedure, including HPLC purification. While the procedure at OUH furnishes the lowest radiochemical yield of the synthetic routes considered, it produces the highest molar activity. This is of importance across the clinical applications of the tracer discussed here, including dopamine synthesis in striatum of subjects with schizophrenia and congenital hyperinsulinism in infants. CONCLUSION: For most sites either of the two nucleophilic substitution strategies should be favored. However, which of the two will depend on whether a given site wishes to optimize the radiochemical yield or the ease of the use.

Real-Time Size and Mass Estimation of Slender Axi-Symmetric Fruit/Vegetable Using a Single Top View Image.

Among the physical attributes of agricultural materials, mass, volume, and sizes have always been important quality parameters. Previous research focused mostly on volume estimation using stereo-based approaches, which rely on manual intervention or require a multiple-cameras set up or multiple-frames captures from different viewing angles to reconstruct the three-dimensional point-cloud information. These approaches are tedious and not suitable for practical machine vision systems. In this work, we only use a single camera mounted on the ceiling of the imaging chamber, which is directly above the fruit/vegetable to capture its top-view, two-dimensional image. We developed a method to estimate the mass/volume of agricultural products with axi-symmetrical shapes such as a carrot or a cucumber. The mass/volume is estimated as the sum of smaller standard blocks, such as chopped pyramids, an elliptical cone, or a conical cone. The computed mass/volume showed good agreement with analytical and experimental results. The weight estimation error is 95% for the case of the carrot and 96.7% for the cucumber. The method proved to be sufficiently accurate, easy to use, and rotationally invariant.

Automated synthesis of 68 Ga/177 Lu-PSMA on the Trasis miniAllinOne.

Prostate-specific membrane antigen (PSMA)-based radioligands for positron emission tomography (PET)/computed tomography (CT) studies represent the gold standard for detection of recurrent prostate cancer (PCa). [68 Ga]PSMA-HBED-CC is a PET radiotracer suitable for detection of PCa, and its clinical use has become widespread over the last few years. In this contribution, we detail our GMP-compliant production of [68 Ga]PSMA-HBED-CC using the Trasis miniAllinOne radiosynthesizer and report synthetic and clinical data for the first 100 productions of 2019. Additionally, we detail our efforts towards a GMP-compliant production of the radiotherapeutic [177 Lu]PSMA-I&T using the same synthesis module. PSMA-based radioligand therapy (RLT) offers a possible future treatment in cases of metastatic castration-resistant PCa, and GMP-compliant routine production methods are therefore called for. This report highlights how PSMA-based agents for theranostic purposes can be conveniently produced at a single radiochemistry Good Manufacturing Practice (GMP) site, thereby facilitating optimized detection and treatment of PCa.

Comparison of imaging modalities for measuring the diameter of intraductal papillary mucinous neoplasms of the pancreas.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are pre-malignant pancreatic cysts detected by imaging. Cyst size is one of many features evaluated on computed tomography (CT), magnetic resonance imaging (MRI), or endoscopic ultrasonography (EUS) to help guide IPMN management. Our objective was to determine which imaging modality best predicts pathological cyst size. METHODS: We analyzed records for 57 IPMN cases surgically treated at Moffitt Cancer Center from 2008 to 2016 for whom pre-operative CT, MRI, and EUS IPMN cyst size and post-operative pathological cyst size values were available. Long axis cyst diameter measurements were compared to each other and corresponding pathological cyst measurements using within-subjects ANOVA, Bland-Altman analysis, and linear regression. Consensus measurements were also performed on CT and MRI images. RESULTS: Cyst size measured via CT and MRI overestimated pathological size by 0.33 cm and 0.27 cm, respectively, whereas EUS underestimated pathological size by 0.05 cm and had the narrowest 95% limit of agreement (LOA). Among pathologically-confirmed cysts <3 cm, MRI overestimated pathological size by 0.30 cm (P = 0.049) and had the widest LOA, followed by EUS and CT. Among cysts ≥3 cm, EUS underestimated pathological size by 0.35 cm (P = 0.059) and MRI and CT overestimated pathological size by 0.23 cm and 0.51 cm, respectively. CONCLUSIONS: In this small retrospective study, EUS cyst size measurements correlated best with pathologic specimens compared to CT and MRI, especially for cysts < 3 cm. Larger prospective studies are needed to determine which imaging modalities are best to risk-stratify IPMNs and guide surgical versus. Non-surgical management.

Superior vestibular neuritis: improved detection using FLAIR sequence with delayed enhancement (1 h).

INTRODUCTION: Vestibular neuritis is the second cause of vertigo and new imaging protocols using delayed FLAIR with double-dose of gadolinium are proposed for its diagnosis. Our aim is to demonstrate that a single dose of gadolinium is sufficient. METHODS: Thirty-three patients with a unilateral vestibular neuritis are compared to a control group. All patients underwent a FLAIR sequence, 1 hour after intravenous injection of a single dose of gadolinium, on a 1.5 Tesla MRI. Two radiologists analyzed the enhancement intensity of the superior (sup VN) and inferior vestibular nerve (inf VN) and ratios to the signal of the cerebellum were calculated (supVN/C). The statistics were performed using Bayesian analysis. RESULTS: A strong enhancement of the sup VN was observed on the pathological side in 85% of patients with vestibular neuritis. The average signal intensity of the pathological sup VN (139 units ± 44) was more than two times the average intensity in the control group (58.5 units ± 5). The average ratios supVN/C were significantly different between the pathological side in vestibular neuritis (2.43 units ± 0.63) and the control group [1.16 ± 0.14 (Pr(diff > 0) = 1)]. A delayed enhancement > 71.5 units had a sensitivity of 96% and a specificity of 100% for the diagnosis of superior vestibular neuritis. CONCLUSION: A delayed FLAIR sequence, acquired 1 hour after a single dose of gadolinium injection, is a useful method for the diagnosis of vestibular neuritis. An enhancement of the sup VN > 71.5 units was in favor of the diagnosis.

Racial and ethnic disparities in a state-wide registry of patients with pancreatic cancer and an exploratory investigation of cancer cachexia as a contributor to observed inequities.

Pancreatic cancer (PC) is characterized by racial/ethnic disparities and the debilitating muscle-wasting condition, cancer cachexia. Florida ranks second in the number of PC deaths and has a large and understudied minority population. We examined the primary hypothesis that PC incidence and mortality rates may be highest among Black Floridians and the secondary hypothesis that biological correlates of cancer cachexia may underlie disparities. PC incidence and mortality rates were estimated by race/ethnicity, gender, and county using publicly available state-wide cancer registry data that included approximately 2700 Black, 25 200 Non-Hispanic White (NHW), and 3300 Hispanic/Latino (H/L) Floridians diagnosed between 2004 and 2014. Blacks within Florida experienced a significantly (P < 0.05) higher incidence (12.5/100 000) and mortality (10.97/100 000) compared to NHW (incidence = 11.2/100 000; mortality = 10.3/100 000) and H/L (incidence = 9.6/100 000; mortality = 8.7/100 000), especially in rural counties. To investigate radiologic and blood-based correlates of cachexia, we leveraged data from a subset of patients evaluated at two geographically distinct Florida Cancer Centers. In Blacks compared to NHW matched on stage, markers of PC-induced cachexia were more frequent and included greater decreases in core musculature compared to corresponding healthy control patients (25.0% vs 10.1% lower), greater decreases in psoas musculature over time (10.5% vs 4.8% loss), lower baseline serum albumin levels (3.8 vs 4.0 gm/dL), and higher platelet counts (332.8 vs 268.7 k/UL). Together, these findings suggest for the first time that PC and cachexia may affect Blacks disproportionately. Given its nearly universal contribution to illness and PC-related deaths, the early diagnosis and treatment of cachexia may represent an avenue to improve health equity, quality of life, and survival.

68Ga-PSMA-PET/CT in comparison with 18F-fluoride-PET/CT and whole-body MRI for the detection of bone metastases in patients with prostate cancer: a prospective diagnostic accuracy study.

OBJECTIVES: To determine the diagnostic accuracy of 68gallium prostate-specific membrane antigen (PSMA)-based positron emission tomography/computed tomography (PET/CT) in comparison with 18F-fluoride-based PET/CT (NaF-PET/CT) and whole-body magnetic resonance imaging (WB-MRI) for the detection of bone metastases in patients with prostate cancer. METHODS: Sixty patients with prostate cancer were included in the period May 2016 to June 2017. The participants underwent three scans (index tests) within 30 days: a NaF-PET/CT, a WB-MRI and a PSMA-PET/CT. Experienced specialists assessed the scans. In the absence of a histological reference standard, the final diagnosis was determined as a panel diagnosis. Measures of the diagnostic performances of the index tests were calculated from patient-based dichotomous outcomes (0 or ≥ 1 bone metastasis) and pairwise compared (McNemar test). For each index test, the agreement with the final diagnosis with regard to the number of bone metastases detected (0, 1-5, > 5) and the inter-reader agreement was calculated (kappa coefficients). RESULTS: Fifty-five patients constituted the final study population; 20 patients (36%) were classified as having bone metastatic disease as their final diagnosis. The patient-based diagnostic performances were (sensitivity, specificity, overall accuracy) PSMA-PET/CT (100%, 100%, 100%), NaF-PET/CT (95%, 97%, 96%) and WB-MRI (80%, 83%, 82%). The overall accuracy of PSMA-PET/CT was significantly more favourable compared to WB-MRI (p = 0.004), but not to NaF-PET/CT (p = 0.48). PSMA-PET/CT classified the number of bone metastases reliably compared to the final diagnosis (kappa coefficient 0.97) and with an "almost perfect" inter-reader agreement (kappa coefficient 0.93). CONCLUSIONS: The overall accuracy of PSMA-PET/CT was significantly more advantageous compared to WB-MRI, but not to NaF-PET/CT. KEY POINTS: • PSMA-PET/CT assessed the presence of bone metastases correctly in all 55 patients • PSMA-PET/CT was more advantageous compared to WB-MRI • No difference was found between PSMA-PET/CT and NaF-PET/CT.

Characteristics and Clinical Outcomes of Individuals at High Risk for Pancreatic Cancer: A Descriptive Analysis from a Comprehensive Cancer Center.

Pancreatic cancer (PC), a leading cause of cancer-related deaths in the United States, is typically diagnosed at an advanced stage. To improve survival, there is an unmet need to detect pre-malignant lesions and early invasive disease. Prime populations to study for early detection efforts include cohorts of high risk individuals (HRI): those with increased risk to develop pre-malignant pancreatic cysts and PC because of a familial or hereditary predisposition to the disease and those in the general population of sporadic cases who are incidentally found to harbor a pre-malignant pancreatic cyst. The objective of this study was to describe the characteristics and clinical outcomes of cohorts of HRI identified at Moffitt Cancer Center. We set out to determine the uptake of screening, the prevalence and characteristics of solid and cystic pancreatic lesions detected via screening or as incidental findings, and the age at which lesions were detected. Of a total of 329 HRI, roughly one-third were found to have pancreatic lesions, most of which constituted pre-malignant cysts known as intraductal papillary mucinous neoplasms. Individuals with the highest genetic risk for PC were found to have smaller cysts at a much earlier age than sporadic cases with incidental findings; however, many individuals at high genetic risk did not have abdominal imaging reports on file. We also identified a subset of HRI at moderate genetic risk for PC that were found to have cystic and solid pancreatic lesions as part of a diagnostic work-up rather than a screening protocol. These findings suggest the pancreatic research community should consider expanding criteria for who should be offered screening. We also emphasize the importance of continuity of care between cancer genetics and gastrointestinal oncology clinics so that HRI are made aware of the opportunities related to genetic counseling, genetic testing, and screening.

The hourglass sign.

The Hourglass sign is a useful imaging clue for diagnosing diaphragmatic ruptures with viscera herniation on multidetector CT, with a sensitivity ranging from 16% to 63% and a specificity around 98%-100%. This sign is also commonly found in the literature under the name "Collar sign," first described in 1995 by Worthy et al. It refers to the waistlike constriction of the herniated structure at the site of the diaphragmatic rupture.