Salvage Therapies After 18F-Fluciclovine Detected Prostate Cancer Recurrences.

Background: F-Fluciclovine is the most recent prostate cancer (PCa)-directed PET radiotracer approved by the US Food and Drug Administration for detection of recurrent PCa. We report the treatments and outcomes of patients at our institution with PCa recurrences detected on F-fluciclovine PET/CT.

Methods: We identified men with recurrent PCa detected on F-fluciclovine PET/CT performed between 2017 and 2018 who were previously treated definitively and analyzed their patterns of care and cancer-specific outcomes.

18F-Fluciclovine PET/CT Detection of Recurrent Prostate Carcinoma in Patients With Serum PSA ≤ 1 ng/mL After Definitive Primary Treatment.

Purpose: The aims of this study were to report on our initial experience using F-fluciclovine PET/CT to detect recurrent prostate carcinoma in patients with low serum prostate-specific antigen (PSA) after definitive treatment of primary disease and to conduct a preliminary investigation for factors associated with positive scan findings.

Patients And Methods: In this retrospective study, F-fluciclovine PET/CT scans from 28 men with suspected recurrence of prostate carcinoma and PSA values of 1 ng/mL or less were examined to identify the site(s) of disease recurrence. Differences in detection rate for Gleason scores of 7 and greater than 7, T2 and T3 disease, negative and positive surgical margins, and negative and positive seminal vesicle invasion were compared using the Fisher exact test.

Artificial Intelligence for Medical Image Analysis: A Guide for Authors and Reviewers.

Objective: The purpose of this article is to highlight best practices for writing and reviewing articles on artificial intelligence for medical image analysis.

Conclusion: Artificial intelligence is in the early phases of application to medical imaging, and patient safety demands a commitment to sound methods and avoidance of rhetorical and overly optimistic claims. Adherence to best practices should elevate the quality of articles submitted to and published by clinical journals.

Detection of Traumatic Pediatric Elbow Joint Effusion Using a Deep Convolutional Neural Network.

Objective: The purpose of this study is to determine whether a deep convolutional neural network (DCNN) trained on a dataset of limited size can accurately diagnose traumatic pediatric elbow effusion on lateral radiographs.

Materials And Methods: A total of 901 lateral elbow radiographs from 882 pediatric patients who presented to the emergency department with upper extremity trauma were divided into a training set (657 images), a validation set (115 images), and an independent test set (129 images). The training set was used to train DCNNs of varying depth, architecture, and parameter initialization, some trained from randomly initialized parameter weights and others trained using parameter weights derived from pretraining on an ImageNet dataset.

The Value of Needle-Guidance Technology in Ultrasound-Guided Percutaneous Procedures Performed by Radiology Residents: A Comparison of Freehand, In-Plane, Fixed-Angle, and Electromagnetic Needle Tracking Techniques.

Objectives: Radiology residents typically learn ultrasound-guided procedures by performing supervised procedures on patients who may experience longer procedure times and higher complication rates. The purpose of this study was to determine if existing technologies, such as in-plane, fixed-angle guidance (IPFA) and electromagnetic needle tracking (ENT), can improve resident procedure time and accuracy.

Methods: Radiology residents (18 total) were randomized to 1 of 3 ultrasound-guidance technique groups-freehand, IPFA, or ENT-and instructed to place a needle into 4 liver lesions in a humanoid phantom, each increasing in difficulty.

Automated Reporting of DXA Studies Using a Custom-Built Computer Program.

Dual-energy x-ray absorptiometry (DXA) scans are a critical population health tool and relatively simple to interpret but can be time consuming to report, often requiring manual transfer of bone mineral density and associated statistics into commercially available dictation systems. We describe here a custom-built computer program for automated reporting of DXA scans using Pydicom, an open-source package built in the Python computer language, and regular expressions to mine DICOM tags for patient information and bone mineral density statistics. This program, easy to emulate by any novice computer programmer, has doubled our efficiency at reporting DXA scans and has eliminated dictation errors.

Structure of RCC1 chromatin factor bound to the nucleosome core particle.

The small GTPase Ran enzyme regulates critical eukaryotic cellular functions including nuclear transport and mitosis through the creation of a RanGTP gradient around the chromosomes. This concentration gradient is created by the chromatin-bound RCC1 (regulator of chromosome condensation) protein, which recruits Ran to nucleosomes and activates Ran's nucleotide exchange activity. Although RCC1 has been shown to bind directly with the nucleosome, the molecular details of this interaction were not known.

RCC1 uses a conformationally diverse loop region to interact with the nucleosome: a model for the RCC1-nucleosome complex.

The binding of RCC1 (regulator of chromosome condensation 1) to chromatin is critical for cellular processes such as mitosis, nucleocytoplasmic transport, and nuclear envelope formation because RCC1 recruits the small GTPase Ran (Ras-related nuclear protein) to chromatin and sets up a Ran-GTP gradient around the chromosomes. However, the molecular mechanism by which RCC1 binds to nucleosomes, the repeating unit of chromatin, is not known. We have used biochemical approaches to test structural models for how the RCC1 beta-propeller protein could bind to the nucleosome.