Canadian radiology: 2024 update.

Radiology in Canada is advancing through innovations in clinical practices and research methodologies. Recent developments focus on refining evidence-based practice guidelines, exploring innovative imaging techniques and enhancing diagnostic processes through artificial intelligence. Within the global radiology community, Canadian institutions play an important role by engaging in international collaborations, such as with the American College of Radiology to refine implementation of the Ovarian-Adnexal Reporting and Data System for ultrasound and magnetic resonance imaging.

Evaluation of a BERT Natural Language Processing Model for Automating CT and MRI Triage and Protocol Selection.

To evaluate the accuracy of a Bidirectional Encoder Representations for Transformers (BERT) Natural Language Processing (NLP) model for automating triage and protocol selection of cross-sectional image requisitions. A retrospective study was completed using 222 392 CT and MRI studies from a single Canadian university hospital database (January 2018-September 2022). Three hundred unique protocols (116 CT and 184 MRI) were included.

Applications of Artificial Intelligence in Acute Abdominal Imaging.

Artificial intelligence (AI) is a rapidly growing field with significant implications for radiology. Acute abdominal pain is a common clinical presentation that can range from benign conditions to life-threatening emergencies. The critical nature of these situations renders emergent abdominal imaging an ideal candidate for AI applications.

Machine and deep learning models for accurate detection of ischemia and scar with myocardial blood flow positron emission tomography imaging.

Background: Quantification of myocardial blood flow (MBF) is used for the noninvasive diagnosis of patients with coronary artery disease (CAD). This study compared traditional statistics, machine learning, and deep learning techniques in their ability to diagnose disease using only the rest and stress MBF values.

Methods: This study included 3245 rest and stress rubidium-82 positron emission tomography (PET) studies and matching diagnostic labels from perfusion reports.

Artificial Intelligence Chatbots' Understanding of the Risks and Benefits of Computed Tomography and Magnetic Resonance Imaging Scenarios.

Purpose: Patients may seek online information to better understand medical imaging procedures. The purpose of this study was to assess the accuracy of information provided by 2 popular artificial intelligence (AI) chatbots pertaining to common imaging scenarios' risks, benefits, and alternatives.

Methods: Fourteen imaging-related scenarios pertaining to computed tomography (CT) or magnetic resonance imaging (MRI) were used.

Quantum critical dynamics in a 5,000-qubit programmable spin glass.

Experiments on disordered alloys suggest that spin glasses can be brought into low-energy states faster by annealing quantum fluctuations than by conventional thermal annealing. Owing to the importance of spin glasses as a paradigmatic computational testbed, reproducing this phenomenon in a programmable system has remained a central challenge in quantum optimization. Here we achieve this goal by realizing quantum-critical spin-glass dynamics on thousands of qubits with a superconducting quantum annealer.

Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI.

Objective: To evaluate if deep learning is a feasible approach for automated detection of supraspinatus tears on MRI.

Materials And Methods: A total of 200 shoulder MRI studies performed between 2015 and 2019 were retrospectively obtained from our institutional database using a balanced random sampling of studies containing a full-thickness tear, partial-thickness tear, or intact supraspinatus tendon. A 3-stage pipeline was developed comprised of a slice selection network based on a pre-trained residual neural network (ResNet); a segmentation network based on an encoder-decoder network (U-Net); and a custom multi-input convolutional neural network (CNN) classifier.

Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets.

The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter systems. One important task is the simulation of geometrically frustrated magnets in which topological phenomena can emerge from competition between quantum and thermal fluctuations. Here we report on experimental observations of equilibration in such simulations, measured on up to 1440 qubits with microsecond resolution.

Internal validation of myocardial flow reserve PET imaging using stress/rest myocardial activity ratios with Rb-82 and N-13-ammonia.

Background: Myocardial flow reserve (MFR) measurement provides incremental diagnostic and prognostic information. The objective of the current study was to investigate the application of a simplified model for the estimation of MFR using only the stress/rest myocardial activity ratio (MAR) in patients undergoing rest-stress cardiac PET MPI.

Methods And Results: Rest and dipyridamole stress dynamic PET imaging was performed in consecutive patients using Rb or NH (n = 250 each).

Prognostic utility of longitudinal quantification of PET myocardial blood flow early post heart transplantation.

Background: Myocardial blood flow (MBF) quantification by Rubidium-82 positron emission tomography (PET) has shown promise for cardiac allograft vasculopathy (CAV) surveillance and risk stratification post heart transplantation. The objective was to determine the prognostic value of serial PET performed early post transplantation.

Methods And Result: Heart transplant (HT) recipients at the University of Ottawa Heart Institute with 2 PET examinations (PET1 = baseline, PET2 = follow-up) within 6 years of transplant were included in the study.

Publication bias in diagnostic imaging: conference abstracts with positive conclusions are more likely to be published.

Objective: To evaluate whether imaging diagnostic test accuracy conference abstracts with positive conclusions or titles are more likely to reach full-text publication than those with negative (or neutral) conclusions or titles.

Methods: Diagnostic accuracy research abstracts were included if they were presented at the 2011 or 2012 Radiological Society of North America conference. Full-text publication status at 5 years post conference abstract submission was determined.

Observation of topological phenomena in a programmable lattice of 1,800 qubits.

The work of Berezinskii, Kosterlitz and Thouless in the 1970s revealed exotic phases of matter governed by the topological properties of low-dimensional materials such as thin films of superfluids and superconductors. A hallmark of this phenomenon is the appearance and interaction of vortices and antivortices in an angular degree of freedom-typified by the classical XY model-owing to thermal fluctuations. In the two-dimensional Ising model this angular degree of freedom is absent in the classical case, but with the addition of a transverse field it can emerge from the interplay between frustration and quantum fluctuations.

RNA-MoIP: prediction of RNA secondary structure and local 3D motifs from sequence data.

RNA structures are hierarchically organized. The secondary structure is articulated around sophisticated local three-dimensional (3D) motifs shaping the full 3D architecture of the molecule. Recent contributions have identified and organized recurrent local 3D motifs, but applications of this knowledge for predictive purposes is still in its infancy.

Distinct cellular states determine calcium signaling response.

The heterogeneity in mammalian cells signaling response is largely a result of pre-existing cell-to-cell variability. It is unknown whether cell-to-cell variability rises from biochemical stochastic fluctuations or distinct cellular states. Here, we utilize calcium response to adenosine trisphosphate as a model for investigating the structure of heterogeneity within a population of cells and analyze whether distinct cellular response states coexist.

Signal Transduction at the Single-Cell Level: Approaches to Study the Dynamic Nature of Signaling Networks.

Signal transduction, or how cells interpret and react to external events, is a fundamental aspect of cellular function. Traditional study of signal transduction pathways involves mapping cellular signaling pathways at the population level. However, population-averaged readouts do not adequately illuminate the complex dynamics and heterogeneous responses found at the single-cell level.

Systems biology. Accurate information transmission through dynamic biochemical signaling networks.

Stochasticity inherent to biochemical reactions (intrinsic noise) and variability in cellular states (extrinsic noise) degrade information transmitted through signaling networks. We analyzed the ability of temporal signal modulation--that is, dynamics--to reduce noise-induced information loss. In the extracellular signal-regulated kinase (ERK), calcium (Ca(2+)), and nuclear factor kappa-B (NF-κB) pathways, response dynamics resulted in significantly greater information transmission capacities compared to nondynamic responses.