Pulmonary ventilation imaged by magnetic resonance: at the doorstep of clinical application
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past few years, magnetic resonance imaging (MRI) has emerged as an important instrument for functional ventilation imaging. The aim of this review is to summarize established clinical methods and emerging techniques for research and clinical arenas. Before the advent of MRI, chest radiography and computed tomography (CT) dominated morphological lung imaging, while functional ventilation imaging was accomplished with scintigraphy. Initially, MRI was not used for morphological lung imaging often, due to technical and physical limitations. However, recent developments have considerably improved anatomical MRI, as well as advanced new techniques in functional ventilation imaging, such as inhaled contrast aerosols, oxygen, hyperpolarized noble gases (Helium-3, Xenon-129), and fluorinated gases (sulphur-hexafluoride). Straightforward images demonstrating homogeneity of ventilation and determining ventilated lung volumes can be obtained. Furthermore, new image-derived functional parameters are measurable, such as airspace size, regional oxygen partial pressure, and analysis of ventilation distribution and ventilation/perfusion ratios. There are several advantages to using MRI: lack of radiation, high spatial and temporal resolution and a broad range of functional information. The MRI technique applied in patients with chronic obstructive pulmonary disease, emphysema, cystic fibrosis, asthma, and bronchiolitis obliterans, may yield a higher sensitivity in the detection of ventilation defects than ventilation scintigraphy, CT or standard pulmonary function tests. The next step will be to define the threshold between physiological variation and pathological defects. Using complementary strategies, radiologists will have the tools to characterize the impairment of lung function and to improve specificity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it