Citations

Abstract Background Neuropathologic evaluation is essential for diagnosing and treating dementia, but definitive diagnoses is only available after post‐mortem brain autopsy. Positron emission tomography (PET) offers a potential in vivo proxy for predicting neuropathology. This study proposes a semi‐supervised learning (SSL) model using a single FDG‐PET image to predict underlying neuropathology. Method The SSL model leverages a self‐organized graph structure based on a patient similarity network (PSN) created from 1,495 FDG‐PET images across the aging and neurodegenerative spectrum. Each patient is represented by a node, with edges indicating image similarity derived from principal component analysis features and cosine similarity weights. The PSN structure connects 20 nearest neighbors. Neuropathologic labels were available for 204 autopsied patients. The Poisson Learning Method was employed to propagate labels from these annotated nodes to unlabeled nodes, guided by the PSN structure. FDG‐PET images were collected from clinical and research participants at the Mayo Clinic and processed using an MRI‐free pipeline. Neuropathologic labels were assigned based on widely accepted diagnostic criteria. Leave‐one‐out cross‐validation (LOOCV) was used to assess model performance. Results The confusion matrix demonstrated high accuracy in predicting Alzheimer's disease, frontotemporal lobar degeneration with tau inclusions, and Lewy body disease pathology. A Sankey diagram and label distribution analysis revealed strong correlations between clinical and predicted neuropathologic labels. Conclusion This study highlights the potential of a graph‐based SSL pipeline to predict neuropathological changes using FDG‐PET imaging data, despite limited pathology labels. The findings underscore the value of SSL in bridging the gap between abundant neuroimaging data and scarce neuropathologic labels, contributing to improved dementia diagnosis and understanding.

Positron emission tomography (PET) imaging in prostate cancer has advanced significantly in the past decade with prostate cancer targeted radiopharmaceuticals now playing a growing role in diagnosis, staging, and treatment. This narrative review focuses on the most commonly used PET radiopharmaceuticals in the USA: prostate-specific membrane antigen (PSMA), fluciclovine, and choline. 18F-fluorodeoxyglucose (FDG) is used in many other malignancies, but rarely in prostate cancer. Previous literature is discussed regarding each radiopharmaceutical’s utility in the settings of screening/diagnosis, initial staging, biochemical recurrence, advanced disease, and evaluation prior to targeted radiopharmaceutical therapy and radiation therapy. PET imaging has demonstrated utility over traditional imaging in various scenarios; however, there are few head-to-head studies comparing PET radiopharmaceuticals. PSMA radiopharmaceuticals are the newest tracers developed and have unique properties and uses, especially at low prostate-specific antigen (PSA) levels. However, each PET radiopharmaceutical has different properties which can affect image interpretation. Choline and fluciclovine have minimal urinary activity, whereas PSMA agents can have high urinary activity which may affect locoregional disease evaluation. Of the three radiopharmaceuticals, only PSMA is approved for both diagnostic and therapeutic indications with 177 Lu-PSMA. A variety of diagnostic PET radiotracers for prostate cancer allows for increased flexibility, especially in the setting of supply chain and medication shortages. For the time being, keeping a diverse group of PET radiopharmaceuticals for prostate cancer is justifiable.

Abstract Ewing sarcoma is the second most common primary bone tumor in children. Typical Ewing sarcoma most frequently occurs in long bones and within the pelvis. ALES (adamantinoma-like Ewing sarcoma) is a rare subtype of Ewing sarcoma that is characterized by epithelial differentiation in addition to small round blue cells. Unlike typical Ewing sarcoma, ALES has been described in several cases in the head and neck. Herein, we describe a case of a 9-year-old boy with ALES of the mandible evaluated on 18F-FDG PET/CT with correlative MRI scans.

Abstract Background Strategies to optimize antibiotic prescribing at discharge are not well understood. Methods In fall 2019, we surveyed 39 Michigan hospitals on their antibiotic stewardship strategies. The association of reported strategies with discharge antibiotic overuse (unnecessary, excess, suboptimal fluoroquinolones) for community-acquired pneumonia (CAP) and urinary tract infection (UTI) was evaluated in 2 ways: (1) all strategies assumed equal weight and (2) strategies were weighted based on the ROAD (Reducing Overuse of Antibiotics at Discharge) Home Framework (ie, Tier 1—Critical infrastructure, Tier 2—Broad inpatient interventions, Tier 3—Discharge-specific strategies) with Tier 3 strategies receiving the highest weight. Results Between 1 July 2017 and 30 July 2019, 39 hospitals with 20 444 patients (56.5% CAP; 43.5% UTI) were included. Survey response was 100%. Hospitals reported a median (interquartile range [IQR]) 12 (9–14) of 34 possible stewardship strategies. On analyses of individual stewardship strategies, the Tier 3 intervention, review of antibiotics prior to discharge, was the only strategy consistently associated with lower antibiotic overuse at discharge (adjusted incident rate ratio [aIRR] 0.543, 95% confidence interval [CI]: .335–.878). On multivariable analysis, weighting by ROAD Home tier predicted antibiotic overuse at discharge for both CAP and UTI. For diseases combined, having more weighted strategies was associated with lower antibiotic overuse at discharge (aIRR 0.957, 95% CI: .927–.987, per weighted intervention); discharge-specific stewardship strategies were associated with a 12.4% relative decrease in antibiotic overuse days at discharge. Conclusions The more stewardship strategies a hospital reported, the lower its antibiotic overuse at discharge. However, Tier 3, or discharge-specific strategies, appeared to have the largest effect on antibiotic prescribing at discharge.