ABSTRACT
BACKGROUND: Brain bases and progression of methotrexate-associated neurotoxicity and cognitive disturbances remain unknown. We tested whether brain abnormalities worsen in proportion to intrathecal methotrexate(IT-MTX) doses. METHODS: In this prospective, longitudinal study, we recruited 19 patients with newly diagnosed acute lymphoblastic leukemia 4-to-20 years of age and 20 matched controls. We collected MRI and neuropsychological assessments at a pre-methotrexate baseline and at week 9, week 22, and year 1 during treatment. RESULTS: Patients had baseline abnormalities in cortical and subcortical gray matter(GM), white matter(WM) volumes and microstructure, regional cerebral blood flow, and neuronal density. Abnormalities of GM, blood flow, and metabolites worsened in direct proportions to IT-MTX doses. WM abnormalities persisted until week 22 but normalized by year 1. Brain injuries were localized to dorsal and ventral attentional and frontoparietal cognitive networks. Patients had cognitive deficits at baseline that persisted at 1-year follow-up. CONCLUSIONS: Baseline abnormalities are likely a consequence of neuroinflammation and oxidative stress. Baseline abnormalities in WM microstructure and volumes, and blood flow persisted until week 22 but normalized by year 1, likely due to treatment and its effects on reducing inflammation. The cytotoxic effects of IT-MTX, however, likely contributed to continued, progressive cortical thinning and reductions in neuronal density, thereby contributing to enduring cognitive deficits. IMPACT: Brain abnormalities at a pre-methotrexate baseline likely are due to acute illness. The cytotoxic effects of intrathecal MTX contribute to progressive cortical thinning, reductions in neuronal density, and enduring cognitive deficits. Baseline white matter abnormalities may have normalized via methotrexate treatment and decreasing neuroinflammation. Corticosteroid and leucovorin conferred neuroprotective effects. Our findings suggest that the administration of neuroprotective and anti-inflammatory agents should be considered even earlier than they are currently administered. The neuroprotective effects of leucovorin suggest that strategies may be developed that extend the duration of this intervention or adapt it for use in standard risk patients.
ABSTRACT
BACKGROUND: /Objective: Automatic apnea/hypopnea events classification, crucial for clinical applications, often faces challenges, particularly in hypopnea detection. This study aimed to evaluate the efficiency of a combined approach using nasal respiration flow (RF), peripheral oxygen saturation (SpO2), and ECG signals during polysomnography (PSG) for improved sleep apnea/hypopnea detection and obstructive sleep apnea (OSA) severity screening. METHODS: An Xception network was trained using main features from RF, SpO2, and ECG signals obtained during PSG. In addition, we incorporated demographic data for enhanced performance. The detection of apnea/hypopnea events was based on RF and SpO2 feature sets, while the screening and severity categorization of OSA utilized predicted apnea/hypopnea events in conjunction with demographic data. RESULTS: Using RF and SpO2 feature sets, our model achieved an accuracy of 94 % in detecting apnea/hypopnea events. For OSA screening, an exceptional accuracy of 99 % and an AUC of 0.99 were achieved. OSA severity categorization yielded an accuracy of 93 % and an AUC of 0.91, with no misclassification between normal and mild OSA versus moderate and severe OSA. However, classification errors predominantly arose in cases with hypopnea-prevalent participants. CONCLUSIONS: The proposed method offers a robust automatic detection system for apnea/hypopnea events, requiring fewer sensors than traditional PSG, and demonstrates exceptional performance. Additionally, the classification algorithms for OSA screening and severity categorization exhibit significant discriminatory capacity.
