Trial Report Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation, 2024, Eddy et al.

Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation
Rachel L Eddy; David Mummy; Shuo Zhang; Haoran Dai; Aryil Bechtel; Alexandra Schmidt; Bradie Frizzell; Firoozeh V Gerayeli; Jonathon A Leipsic; Janice M Leung; Bastiaan Driehuys; Loretta G Que; Mario Castro; Don D Sin; Peter J Niedbalski

BACKGROUND
Long COVID impacts ∼10% of people diagnosed with COVID-19, yet the pathophysiology driving ongoing symptoms is poorly understood. We hypothesised that 129Xe magnetic resonance imaging (MRI) could identify unique pulmonary phenotypic subgroups of long COVID, therefore we evaluated ventilation and gas exchange measurements with cluster analysis to generate imaging-based phenotypes.

METHODS
COVID-negative controls and participants who previously tested positive for COVID-19 underwent 129XeMRI ∼14-months post-acute infection across three centres. Long COVID was defined as persistent dyspnea, chest tightness, cough, fatigue, nausea and/or loss of taste/smell at MRI; participants reporting no symptoms were considered fully-recovered. 129XeMRI ventilation defect percent (VDP) and membrane (Mem)/Gas, red blood cell (RBC)/Mem and RBC/Gas ratios were used in k-means clustering for long COVID, and measurements were compared using ANOVA with post-hoc Bonferroni correction.

RESULTS
We evaluated 135 participants across three centres: 28 COVID-negative (40±16yrs), 34 fully-recovered (42±14yrs) and 73 long COVID (49±13yrs). RBC/Mem (p=0.03) and FEV1 (p=0.04) were different between long-and COVID-negative; FEV1 and all other pulmonary function tests (PFTs) were within normal ranges. Four unique long COVID clusters were identified compared with recovered and COVID-negative. Cluster1 was the youngest with normal MRI and mild gas-trapping; Cluster2 was the oldest, characterised by reduced RBC/Mem but normal PFTs; Cluster3 had mildly increased Mem/Gas with normal PFTs; and Cluster4 had markedly increased Mem/Gas with concomitant reduction in RBC/Mem and restrictive PFT pattern.

CONCLUSIONS
We identified four 129XeMRI long COVID phenotypes with distinct characteristics. 129XeMRI can dissect pathophysiologic heterogeneity of long COVID to enable personalised patient care.

TAKE HOME MESSAGE
Cluster analysis of 129 Xe MRI metrics identifies four phenotypes of long COVID with distinct functional MRI and clinical characteristics. MRI-based clusters can be used to dissect long COVID heterogeneity, enabling personalised clinical care and treatment.

Link | PDF (European Respiratory Journal)

 

Summary quotes from introduction —

 

Without detailing the technology, this section from the materials and methods sets the scene (split and emphasised for legibility) —

 

Summary quotes from discussion (my emphasis) —

RV is Residual Volume (Functional Residual Capacity = Expiratory Reserve Volume + Residual Volume)
TLC is Total Lung Capacity
See Wikipedia

 

Figure 5. Long COVID Cluster Summary.

(A) 129Xe MR gas, membrane and red blood cell (RBC) images for representative participants in COVID-negative participants, recovered participants, and resulting long COVID clusters. Site location for each participant embedded in images. (B) Qualitative cluster comparison for imaging measurements used to generate clusters and clinical characteristics.
D-defect (no signal); L=low-intensity signal; H=high-intensity signal; RBC-red blood cells; BMI-body mass index; CT=computed tomography; GGO-ground glass opacities; Ret-reticulation.