Canadian Society of Thoracic Radiology/Canadian Association of Radiologists Consensus Statement Regarding Chest Imaging in Suspected and Confirmed COVID-19
Bibliographic record
Abstract
On March 11, 2020, the World Health Organization declared infection related to a novel coronavirus (SARS-CoV-2) a pandemic. The role and impact of imaging predates this declaration and continues to change rapidly. This article is a consensus statement provided by the Canadian Society of Thoracic Radiology and the Canadian Association of Radiologists outlining the role of imaging in COVID-19 patients. The objectives are to answer key questions related to COVID-19 imaging of the chest and provide guidance for radiologists who are interpreting such studies during this pandemic. The role of chest radiography (CXR), computed tomography (CT), and lung ultrasound is discussed. This document attempts to answer key questions for the imager when dealing with this crisis, such as "When is CXR appropriate in patients with suspected or confirmed COVID-19 infection?" or "How should a radiologist deal with incidental findings of COVID-19 on CT of the chest done for other indications?" This article also provides recommended reporting structure for CXR and CT, breaking diagnostic possibilities for both CXR and CT into 3 categories: typical, nonspecific, and negative based on imaging findings with representative images provided. Proposed reporting language is also outlined based on this structure. As our understanding of this pandemic evolves, our appreciation for how imaging fits into the workup of patients during this unprecedented time evolves as well. Although this consensus statement was written using the most recent literature, it is important to maintain an open mind as new information continues to surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".