m2ABQ-a proposed refinement of the modified algorithm-based qualitative classification of osteoporotic vertebral fractures.

Currently, there is no reproducible, widely accepted gold standard to classify osteoporotic vertebral body fractures (OVFs). The purpose of this study is to refine a method with clear rules to classify OVFs for machine learning purposes. The method was found to have moderate interobserver agreement that improved with training. INTRODUCTION: The current methods to classify osteoporotic vertebral body fractures are considered ambiguous; there is no reproducible, accepted gold standard. The purpose of this study is to refine classification methodology by introducing clear, unambiguous rules and a refined flowchart to allow consistent classification of osteoporotic vertebral body fractures. METHODS: We developed a set of rules and refinements that we called m2ABQ to classify vertebrae into five categories. A fracture-enriched database of thoracic and lumbar spine radiographs of patients 65 years of age and older was retrospectively obtained from clinical institutional radiology records using natural language processing. Five raters independently classified each vertebral body using the m2ABQ system. After each annotation round, consensus sessions that included all raters were held to discuss and finalize a consensus annotation for each vertebral body where individual raters' evaluations differed. This process led to further refinement and development of the rules. RESULTS: Each annotation round showed increase in Fleiss kappa both for presence vs absence of fracture 0.62 (0.56-0.68) to 0.70 (0.65-0.75), as well as for the whole m2ABQ scale 0.29 (0.25-0.33) to 0.54 (0.51-0.58). CONCLUSION: The m2ABQ system demonstrates moderate interobserver agreement and practical feasibility for classifying osteoporotic vertebral body fractures. Future studies to compare the method to existing studies are warranted, as well as further development of its use in machine learning purposes.

Deposition of inhaled nanoparticles is reduced in subjects with COPD and correlates with the extent of emphysema: proof of concept for a novel diagnostic technique.

BACKGROUND: The diagnosis of chronic obstructive pulmonary disease (COPD) is often based on spirometry, which is not sensitive to early emphysema. We have recently described a method for assessing distal airspace dimensions by measuring recovery of nanoparticles in exhaled air after a single-breath inhalation followed by breath-hold. Recovery refers to the non-deposited particle fraction. The aim of this study was to explore differences in the recovery of exhaled nanoparticles in subjects with COPD and never-smoking controls. A secondary aim was to determine whether recovery correlates with the extent of emphysema. METHOD: A total of 19 patients with COPD and 19 controls underwent three repeats of single-breath nanoparticle inhalation followed by breath-hold. Particle concentrations in the inhaled aerosol, and in an alveolar sample exhaled after breath-hold, were measured to obtain recovery. FINDINGS: The patients with COPD had a significantly higher mean recovery than controls, 0·128 ± 0·063 versus 0·074 ± 0·058; P = 0·010. Also, recovery correlated significantly with computed tomography (CT) densitometry variables (P<0·01) and diffusing capacity for carbon monoxide (DL,CO ; P = 0·002). INTERPRETATION: Higher recovery for emphysema patients, relative to controls, is explained by larger diffusion distances in enlarged distal airspaces. The nanoparticle inhalation method shows potential to be developed towards a tool to diagnose emphysema.