Daily Respiratory Research Analysis

Based on a 3D pre-treatment magnetic resonance (MR) scan, we developed DREME-MR to jointly reconstruct the reference patient anatomy and solve a data-driven, patient-specific cardiorespiratory motion model. Via a motion encoder simultaneously learned during the reconstruction, DREME-MR further enables real-time volumetric MR imaging and cardiorespiratory motion tracking with minimal intra-treatment k-space data. Approach: DREME-MR integrates dynamic MRI reconstruction and real-time MR imaging into a unified, dual-task learning framework. From a 3D radial-spoke-based pre-treatment MR scan, DREME-MR uses spatiotemporal implicit-neural-representation (INR) to reconstruct pre-treatment dynamic volumetric MR images (learning task 1). The INR-based reconstruction takes a joint image reconstruction and deformable registration approach, yielding a reference anatomy and a corresponding cardiorespiratory motion model. The motion model adopts a low-rank, multi-resolution representation to approximate motion fields as products of motion coefficients and motion basis components (MBCs). Via a progressive, frequency-guided strategy, DREME-MR decouples cardiac MBCs from respiratory MBCs to resolve the two distinct motion modes. Simultaneously with the pre-treatment dynamic MRI reconstruction, DREME-MR also trains a multilayer perceptron (MLP)-based motion encoder to infer cardiorespiratory motion coefficients directly from the raw k-space data (learning task 2), allowing real-time, intra-treatment volumetric MR imaging and motion tracking with minimal k-space data (20-30 spokes) acquired after the pre-treatment MRI scan. Main results: Evaluated using data from a digital phantom (XCAT) and a human scan, DREME-MR solves real-time 3D cardiorespiratory motion with a latency of < 165 ms (= 150-ms data acquisition + 15-ms inference time), fulfilling the temporal constraint of real-time imaging. The XCAT study achieves mean(±S.D.) center-of-mass tracking errors of 0.73±0.38mm for a lung tumor and 1.69±1.12mm for the left ventricle. The human study shows good motion correlations (liver: 0.96; left ventricle: 0.65) between DREME-MR-solved motion and extracted surrogate signals. Significance: DREME-MR allows real-time 3D MRI and cardiorespiratory motion tracking with low latency, advancing intra-treatment MR-guided adaptive radiotherapy, including real-time multileaf collimator (MLC) tracking.

OBJECTIVES: We aimed to describe the incidence, presentation and clinical outcomes of RSV-associated acute respiratory infection (ARI) in older adults using a new national Hospital-based ARI Sentinel Surveillance (HARISS) system in England, prior to RSV vaccine introduction. METHODS: Adults aged ≥65 years from seven hospitals admitted for ≥24 hours with symptomatic ARI were included. We estimated the hospitalisation rate of RSV-associated ARI compared to influenza-associated ARI and assessed clinical outcomes using Poisson regression and mortality using Cox regression. RESULTS: This study included 2743 adults. During winter 2023/4 the hospitalisation rate for RSV-associated ARI was 58.3 per 100,000, compared to 114.6 per 100,000 for influenza-associated ARI. Hospitalisations increased with age. Exacerbation of chronic illness (lung disease, heart disease, frailty) was a common admission reason in RSV-associated ARI, with a combined incidence of 33.1 per 100,000. Most adults with RSV-associated ARI had at least one comorbidity (81%); a high proportion with immunosuppression (26%). Symptoms and clinical outcomes including mortality were similar between RSV- and influenza-associated ARI; 30-day mortality 10.6% vs 8.7% (adjusted hazard ratio 0.85, 95% confidence interval 0.6-1.2). CONCLUSIONS: In England, RSV infection is a common cause of hospitalisation in older adults. Symptoms and clinical outcomes, including mortality, are comparable to influenza.

OBJECTIVES: Pulse transit time (PTT) is used to assess vascular elasticity. We aim to investigate whether respiratory event-related PTT metrics can predict left ventricular (LV) impairment in obstructive sleep apnea (OSA). METHODS: This retrospective study included OSA patients without pre-existing LV impairment who underwent polysomnography from January 2014 to May 2017 at Affiliated Huai'an No.1 People's Hospital and The First Affiliated Hospital of Nanjing Medical University. LV impairment was assessed via echocardiography and blood tests from December 2023 to May 2024. Respiratory event-related PTT metrics (drop rate, magnitude, index, nadir, area) were measured using SOMNOscreen + polysomnographic system. Cox models estimated hazard ratios for LV impairment, and receiver operating characteristic (ROC) curves assessed the predictive value. RESULTS: The sample included 517 individuals (82.8 % male) with a median age of 53.0 years (IQR: 43.0-63.0). Over a median follow-up of 8.3 years, 112 patients (21.7 %) were diagnosed with LV hypertrophy (LVH) and 249 (48.2 %) with LV diastolic dysfunction (LVDD), none had systolic dysfunction. Patients in the fourth quartile of the PTT drop rate had adjusted hazard ratios of 2.49 [95 % CI, 1.38-4.49] for LVH and 3.84 [95 % CI, 2.49-5.92] for LVDD, and 0.53 ng/ml [95 % CI, 0.33-0.73] higher cardiac troponin T than those in the first quartile. No consistent associations were found with other PTT metrics. In ROC analysis, the PTT drop rate showed greater accuracy than traditional metrics in predicting LVDD. CONCLUSIONS: A high respiratory event-related PTT drop rate, reflecting vascular hyperactivity, may help stratify LV impairment risk in OSA.