Microfluidic artificial lung devices seek to capitalize on the increased surface-area-to-volume ratio at the microscale to increase gas exchange efficiency, allowing for oxygenation of blood with smaller volumes and a smoother flow path. However, such small scales also lead to challenges, including coagulation, channel blockage, and difficulty in scaling up. This article presents the integration of active mixing into the blood-side channel via acoustic microstreaming by an oscillating membrane to enhance gas exchange across that membrane. Tests with fresh ovine blood show reduced biofouling by platelet deposition on the actuated membranes (up to 80% lower surface coverage), which may extend device lifetimes. Coagulation and channel blockage experiments demonstrate reduced coagulation and channel blockage in taller and actuated channels. O2 gas exchange into ovine blood is improved up to 2.6× compared to the non-actuated control, allowing blood pumped through the device to reach a 95% target for oxygen saturation with channel geometry and flow parameters, which would otherwise be unsuitable. Such a design allows for taller channel heights than those typically seen in microfluidic artificial lung devices while maintaining gas exchange efficiency, enabling the device to capitalize on the reduced coagulation associated with the taller, actuated channels, enabling easier fabrication by conventional machining, and allowing for larger throughput per channel branch.

Preterm neonates are susceptible to respiratory distress syndrome (RDS) due to their underdeveloped lungs and require mechanical ventilation. Microfluidic blood oxygenators (MBOs) are a suitable alternative due to their small priming volume and their potential to reduce iatrogenic effects of ventilation. Current MBOs use lithographic fabrication that limits their manufacturability due to scalability and integration issues. Additive-manufacturing has been recently explored to overcome fabrication challenges, but has its own limitations in realizing scalable thin-membrane devices with high degree of channel patency. This work presents a new hybrid additive-manufacturing strategy for artificial lungs, by combining extrusion printing of sacrificial isomalt scaffolds with spin-coating of thin polydimethylsiloxane membranes. It eliminates the use of synthetic polymers or toxic solvents, yielding complete channel patency and biocompatibility. Using this scalable process, oxygenators with 11 alternating blood/gas layers separated by thin (121 µm) membranes were manufactured, achieving complete channel patency and a 0% rejection rate. In vitro evaluation showed reduced form-factor while achieving a high oxygen-transfer efficiency of 184 mL O2 min−1 m−2. Furthermore, the performance metrics of the devices were evaluated against the clinical requirement, substantiating their ability to support a 1 kg neonate with RDS, achieving 1.73 mL O2 min−1 oxygen uptake at 30 mL min−1 blood flow rate, with 8.6 mL priming volume and offering pumpless operation.

To compare lung nodule volumetric accuracy and precision between photon-counting detector (PCD) computed tomography (CT) and energy-integrating detector (EID) CT using low-dose lung cancer screening protocols, and to optimize reconstruction parameters for lung nodule volumetry. An anthropomorphic chest phantom with 12 artificial lung nodules of varying size, shape, and radiodensity was scanned using EID-CT and PCD-CT with reference and optimized low-dose lung cancer screening protocols. PCD-CT reconstruction parameters (slice thickness, matrix size, kernel, iterative reconstruction, and virtual monoenergetic imaging energy) were varied. Each protocol was scanned 3 times with nodule repositioning. Nodule volumes were independently measured semiautomatically by 2 observers. Interobserver agreement and test-retest reliability were assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots. Volumetric accuracy and precision were calculated relative to ground-truth volumes. Volumetric accuracy was compared between PCD-CT and EID-CT using one-way analysis of variance, and across PCD-CT reconstructions using univariable linear regression. Volumetric precision was assessed based on the SD of mean volume differences. Noise was compared across scanners and reconstructions using one-way analysis of variance. A total of 1224 nodule measurements demonstrated excellent volumetric interobserver agreement (ICC: 0.99) and test-retest reliability (ICCs of 0.96 for both observers). Volumetric accuracy improved from -16.6% and -15.2% with the reference and optimized EID-CT protocols to -12.5% and -10.2% with the reference and optimized PCD-CT protocols (P < 0.05). Volumetric precision remained comparable between reference and optimized EID-CT (6.3 and 8.2mm3) and PCD-CT (6.4 and 6.2mm3) protocols. On PCD-CT, ultra-thin slices (0.2mm) and an ultra-sharp kernel (Qr76) worsened volumetric accuracy by 2.9% and 2.8%, respectively (P < 0.05). Image noise was lower on PCD-CT than on EID-CT (P < 0.05) and varied significantly across reconstruction settings on PCD-CT. PCD-CT improved lung nodule volumetric accuracy and reduced volume underestimation by up to 6% compared with EID-CT using low-dose screening protocols, while maintaining similar volumetric precision. Ultra-thin slices and an ultra-sharp kernel worsened volumetric accuracy. By reducing volume underestimation, PCD-CT may shift a larger proportion of nodules to higher baseline risk categories, potentially increasing the number of screening participants requiring clinical referral or short-term follow-up CT.

Clinical hollow fiber artificial lungs are prone to clotting, necessitating the use of systemic anticoagulation and thus increasing the risk of bleeding events. This study seeks to address these limitations by creating hemocompatible and biomimetic 3D printed artificial lungs. This study investigates the nonthrombogenic effects of imbuingpolydimethylsiloxane (PDMS or silicone elastomer) based 3D-printable resin with hydrophilic molecules with the goal of reducing the body’s natural coagulation response to foreign materials, increasing device lifetime, and reducing systemic anticoagulation, thereby coming closer to mimicking the native in vivo blood interface. First, contact angle (hydrophilicity) tests were done to narrow down the number of candidate modifications for the development of a high-resolution PDMS resin for vat photopolymerization (VPP). Then, dynamic blood flow through testing was performed using a high-resolution PDMS base resin modified by 1) adding 1% 2-Methacryloyloxyethyl phosphorylcholine (MPC) to the base resin; 2) adding 1.8% Poly(ethylene glycol) methacrylate (PEGMA) to the base resin; or 3) infusing the neat PDMS devices with 2% dimethylsiloxane-[60-70% ethylene oxide] (PEO-PDMS) in ethanol post-printing. Biomimetic microfluidic capillary devices designed in SOLIDWORKS were 3D printed via SLA, cleared of uncured resin, and tested for coagulation with freshly-drawn ovine whole blood. Devices (n ≥ 12 per group) were exposed to blood for 10 minutes at 0.8 mL/min and evaluated for clotting via fluorescent confocal microscopy, percent clotting area analyses, pressure logging data, and flow cytometry. The 1% MPC, 1.8% PEGMA, and 2% PEO-PDMS infusion resin groups demonstrated a significant decrease in clotting area and fluorescence intensity when compared to the unmodified base resin and a commercially-available resin (FTD Nano Clear). The top performing modification (PEO-PDMS infusion) decreased clotting area by 57.5 and 65.2% and fluorescence intensity by 84.6 and 88.3% relative to the unmodified base resin and FTD Nano Clear resin, respectively.

This paper presents the design and development of a portable, low-cost mechanical ventilator intended for emergency respiratory support in resource-constrained healthcare environments. The proposed system automates a conventional Bag Valve Mask (BVM) using a stepper motor– driven lead screw mechanism to deliver controlled ventilation. Key parameters such as tidal volume, respiratory rate, airway pressure, and inspiration–expiration ratio are regulated using a microcontroller-based control unit. Real-time feedback from an airway pressure sensor and a pulse oximeter ensures patient safety by preventing over-pressurization and maintaining adequate oxygenation. Experimental evaluation using an artificial lung model demonstrates stable and repeatable ventilation performance within clinically safe limits. Due to its low power consumption, portability, and affordability, the proposed ventilator is well suited for use in rural healthcare centers, ambulances, and emergency disaster-response situations. Keywords -Ventilator, Bag Valve Mask (BVM), Low-Cost, Low-Power, Portable, Automated Ventilation

BACKGROUNDPulmonary arteriovenous fistulas (PAVFs) are abnormal vascular communications between pulmonary arteries and veins that may cause hypoxemia and paradoxical embolism. Because many patients are asymptomatic, PAVFs are often detected incidentally on chest computed tomography (CT). Accurate identification of PAVFs is clinically important for appropriate management; however, small or atypical lesions may be overlooked during routine interpretation. Computer-aided detection (CAD) systems for pulmonary nodules are widely used in clinical practice, but their ability to detect PAVFs has not been systematically evaluated. We hypothesized that a lung nodule-based artificial intelligence (AI)-CAD system could detect PAVFs on chest CT.AIMTo evaluate the detectability of PAVFs on chest CT using an AI-based CAD system for lung nodules.METHODSThis retrospective observational study included 21 patients with 26 PAVFs identified at University of the Ryukyus Hospital between 2009 and 2021. Chest CT images, including non-contrast and contrast-enhanced scans, were analyzed using a commercially available AI-based lung nodule CAD system. Detection performance was classified as consistent, conditional, or failed detection, and lesion characteristics associated with successful detection were analyzed. Correlations between CAD-derived measurements and manual measurements were assessed using Pearson’s correlation coefficient.RESULTSAmong the 26 PAVFs, 15 lesions (58%) were consistently detected, 2 lesions (8%) were detected under certain imaging conditions, and 9 lesions (35%) were not detected, yielding an overall detection success rate of 65% (17/26). Detection rates did not differ significantly according to contrast phase (58% for non-contrast, 71% for pulmonary arterial phase, and 47% for parenchymal phase) or window setting (61% for lung window vs 58% for mediastinal window). Detection success was higher for complex-type lesions than for simple-type lesions (100% vs 59%, P = 0.26). CAD-derived maximum lesion length correlated strongly with manual measurements (r = 0.90, P < 0.001), as did CAD-derived lesion volume (r = 0.92, P < 0.001).CONCLUSIONA lung nodule-based AI-CAD system detected a substantial proportion of PAVFs on chest CT and provided reliable quantitative measurements, supporting its potential adjunctive role in PAVF detection and follow-up.

The objective was to evaluate the effectiveness of nitric oxide inhalation in correcting gas exchange disorders and clinical outcomes in patients with severe combined trauma complicated by ARDS. Materials and methods. An open prospective study included 47 patients with ARDS against the background of severe combined trauma. Patients were divided into two groups: the 1st group ( n = 24) patients who received standard therapy, the 2nd group ( n = 23) patients who received, in addition to standard therapy, inhalation therapy with nitrogen monoxide at a dose of 20-28 ppm. In both groups, the parameters of artificial lung ventilation, oxygen fraction in the inhaled mixture, positive end-expiratory pressure, saturation, oxygenation index, and compliance were evaluated on days 1, 3, and 5 after the injury. Results. In the group of patients who received inhalation therapy with nitrogen monoxide, compared to the control group, there was a decrease in ventilation parameters (PEEP and FiO 2 ) and an improvement in oxygenation parameters (SpO 2 and PaO 2 /FiO 2 ) on the first day ( p &lt; 0.05). It was found that the use of inhalation therapy with nitrogen monoxide leads to a stable increase in gas exchange parameters such as the oxygenation index and arterial blood oxygen saturation on the third day after the start of therapy. The achieved improvement in gas exchange parameters was maintained on day 5 after the start of therapy. Despite a significant improvement in respiratory function, no statistically significant differences in overall mortality were observed between the groups Conclusions . Nitric oxide inhalation therapy is an effective addition to the standard treatment of ARDS, allowing to optimize ventilation parameters and improve oxygenation in the shortest terms, thereby reducing the risk of ventilator-associated lung damage. Further research should focus on optimizing patient selection criteria and therapeutic protocols.

Lung ultrasound (LUS) is a sensitive, low-cost, and radiation-free modality for interstitial lung disease (ILD) detection. We previously developed and validated LUS interpretation criteria in systemic sclerosis (SSc) and idiopathic inflammatory myopathy (IIM) showing excellent diagnostic performance and correlations with ILD severity. In this study, we applied deep learning to evaluate whether convolutional neural networks (CNNs) can accurately detect ILD and its severity on LUS. Patients with SSc or IIM ± ILD and paired LUS and chest computed tomography (CT) were included. LUS images were labeled using CT results and human LUS-ILD 2024 (LUS-ILD-24) interpretation. Three pretrained CNN architectures (InceptionV3, ResNet-50, VGG-16) were fine-tuned via transfer learning, and a de novo lightweight architecture (LUS-Net) was developed. Model performance for ILD detection was assessed at image and patient levels using area under the curve (AUC), sensitivity, specificity, and agreement with expert interpretation. CNN outputs were correlated with pulmonary function tests (PFTs) and CT-based Computer-Aided Lung Informatics for Pathology Evaluation and Rating indices. Gradient-weighted Class Activation Mapping (Grad-CAM) visualized regions driving predictions. A total of 140 patients representing 3,920 LUS images were included and split into development (74) and independent test sets (66). VGG-16 achieved the best patient-level performance (AUC 0.972, sensitivity 97.4%, specificity 92.6%) showing strong correlations with PFTs and CT severity. Grad-CAM highlighted pleural features as the primary regions influencing model predictions. CNN performance matched or exceeded LUS-ILD-24 interpretation. Deep learning applied to LUS enables accurate ILD detection in connective tissue disease and can enhance expert interpretation. Explainable artificial intelligence suggests pleural features, even when B-lines are infrequent, are sufficient for reliable ILD recognition.

Automatic Breathing: Artificial lungs kept a patient alive for two days before transplant.

Extracorporeal membrane oxygenation (ECMO) systems for permanent respiratory support are currently under development as an alternative to lung transplantation. Direct oral anticoagulants are a promising alternative to heparin due to their oral administration and predictable pharmacology. The efficacy of rivaroxaban for artificial surface anticoagulation was evaluated using 3 studies that determined (1) the pharmacological behavior of 0.25, 0.5, and 1 mg/kg doses of rivaroxaban in sheep; (2) the artificial surface anticoagulation efficacy of these 3 doses compared with heparin in a short-term mini-ECMO model; and (3) the efficacy of the optimal dose from study 2 with simulated oral pharmacokinetics in an extended-duration mini-ECMO model. Study 1 found that sheep have a higher volume of distribution (2.2 ± 0.4 L/kg) and a shorter half-life (1.4 ± 0.1 h) for rivaroxaban than humans but a similar linear relationship between prothrombin time and rivaroxaban plasma concentration. In study 2, device survival time in the heparin group (57.5 ± 13.0 min) was most similar to the 0.5 mg/kg rivaroxaban group (51.3 ± 8.8 min; P = 0.287). This dose was selected for study 3, and no difference was found in device survival time between heparin (6.3 ± 1.3 h) and the 0.5 mg/kg rivaroxaban infusion (6.3 ± 1.6 h; P = 0.837). Furthermore, the calculated rivaroxaban exposure was similar to the clinically approved oral rivaroxaban doses (24-h area under the plasma concentration curve = 2074 µg h/L). These results demonstrate that rivaroxaban has artificial surface anticoagulation efficacy similar to that of heparin at dosages that are feasible for oral administration in humans. Future studies will evaluate rivaroxaban anticoagulation using a 10-d full-scale ovine ECMO model.

Background: The impact of artificial intelligence (AI) tools for lung nodule evaluation on low-dose CT (LDCT) have been evaluated primarily using experimental retrospective reader designs, outside of clinical practice. Objective: To compare interpretation times and lung nodule detection rates between real-world interpretations conducted with versus without an AI-based lung nodule evaluation tool for LDCT examinations in asymptomatic individuals. Methods: This prospective single-center, parallel, open-label clinical trial included consecutive individuals who underwent LDCT of the chest during a self-initiated general health checkup from May 19, 2025 to September 4, 2025. Individuals underwent 1:1 random allocation to an intervention (AI-assisted interpretation) or control (interpretation without AI) group. In the intervention group, a commercial AI tool automatically detected, classified, and measured nodules, and the results were displayed within PACS. Examinations were interpreted by one of ten thoracic radiologists, who reported nodules only when measuring ≥4 mm. The primary outcome was interpretation time per examination. Secondary outcomes included the detection rates (proportion of examinations reporting a finding) of Lung-RADS-positive (category 3 or 4) nodules and of all nodules and the frequency of recommendations for follow-up LDCT. Subsequent lung cancer diagnoses were recorded. Results: The final analysis included 911 individuals (517 men, 394 women; mean age, 62 years; 447 and 464 in the intervention and control groups, respectively). The intervention group, in comparison with the control group, showed no significant difference in interpretation time per examination (187 vs 172 seconds, respectively; P=.23), but a significantly higher detection rate of Lung-RADS-positive nodules (16.9% vs 10.3%, respectively; P=.03), detection rate of all nodules (52.9% vs 32.6%, respectively; P=.002), and frequency of follow-up LDCT recommendations (15.3% vs 7.4%, respectively; P=.04). No individual in either group was diagnosed with lung cancer (median follow-up of 215 and 216 days in intervention and control groups, respectively). Conclusion: Use of an AI-based nodule evaluation tool integrated into PACS during real-world clinical workflows was not associated with a significant difference in interpretation times. However, the tool was associated with significantly greater detection of clinically actionable nodules. Clinical Impact: This randomized clinical trial provides pragmatic evidence regarding the implications of AI-assisted LDCT interpretation.

Bridge to transplant using a flow-adaptive extracorporeal total artificial lung system following bilateral pneumonectomy.

To evaluate the effectiveness of the artificial intelligence-based qXR lung nodule malignancy score (qXR-LNMS) in detecting high-risk incidental pulmonary nodules (IPNs) on chest X-rays (CXRs). The CREATE (NCT05817110), a prospective, observational study for participants aged 35 years or older with IPN (size, ≥8 to ≤30 mm) on CXR, enrolled 712 participants (high-risk: 498 and low-risk: 214) between April 1, 2023, and December 31, 2024. Participants were flagged by the Food and Drug Administration-cleared qXR detection algorithm and confirmed by radiologists. Threshold for success was set at 20% for positive predictive value (PPV) and 70% for negative predictive value (NPV). The primary and secondary outcomes included PPV and NPV of qXR-LNMS against the risk of malignancy assessed by radiologists using low-dose computed tomography (LDCT) and binarized risk categories based on Lung-RADS score and Mayo Clinic model and PPVs and NPVs by clinicodemographic characteristics with 95% CIs using Wilson score method. Overall, the PPV and the NPV of qXR-LNMS risk prediction against radiologists' assessment on LDCT were 54.2% (95% CI, 49.8-58.5) and 93.5% (95% CI, 89.3-96.1), respectively. The agreement between Mayo Clinic model and qXR-LNMS was observed in 70.6% participants (Spearman correlation, 0.247). Results across key subgroups were consistent with all PPV and NPV point estimates crossing the prespecified threshold. The results demonstrate the potential of qXR-LNMS in predicting benign and malignant IPN on CXR, thereby supporting lung cancer screening, particularly in resource-limited settings, although further validation is needed. clinicaltrials.gov Identifier: NCT05817110.

Animal diaphragm-lung systems are soft organs that generate a controllable vacuum. Elephants, as rare land animals, can manipulate all three states of matter using their lung-generated vacuum. In soft robotics, however, current vacuum generation relies on rigid components, and no single soft device effectively handles all states of matter. Traditional soft pumps and grippers are limited in scope: soft pumps provide continuous liquid flow but cannot directly manipulate solids, while grippers manage solids but are ineffective with liquids and gases. Inspired by lung functionality, we present a soft pressure-to-vacuum converter that provides precise control over the suction, holding, and release of solids, liquids, and gases through a single entry and exit point based on negative pressure. Through the selection of appropriate material properties and design variations, our soft device achieves vacuum levels up to -18 kPa, enabling intermittent control and sequential handling of various media without the need for additional components. We demonstrate diverse applications of our soft device, including artificial lungs, liquid blending, vacuum gripping, coffee preparation, and liquid-gas vaporization. This bioinspired device not only provides a safe and adaptable solution for vacuum generation but also addresses a critical gap in soft robotics, offering a multifunctional system capable of manipulating all states of matter.

Lung cancer represents a primary global cause of cancer-related mortality, imposing substantial healthcare burdens on both patients and public health systems. Pulmonary nodules, as early-stage manifestations of lung cancer, exhibit considerable morphological heterogeneity. Consequently, precise identification and clinical management of these nodules are critical for effective lung cancer prevention. In recent years, artificial intelligence (AI) has emerged as a transformative component in modern oncology, providing advanced tools for end-to-end pulmonary nodule management. This review systematically analyzes existing literature through bibliometric assessment to synthesize AI applications across the pulmonary nodule care continuum. AI-powered clinical decision support systems and personalized treatment planning are reshaping precision oncology paradigms. Current research advancements and prevailing challenges are critically examined to identify potential future breakthroughs. The comprehensive synthesis presented herein aims to establish a foundational conceptual framework for researchers and clinicians, while facilitating efficient translation of AI technologies into clinical practice for pulmonary nodule diagnosis and therapy.

From 2016 to the present, hospital-acquired pneumonia has been the leading cause of healthcare-associated infections in the Russian Federation. Pneumonia associated with artificial lung ventilation is an independent risk factor for mortality, and the costs associated with its treatment range from $ 9,966 to EUR 20,965. A generalized strategy for the prevention of pneumonia associated with artificial lung ventilation is presented, which includes: ensuring the safety of the hospital environment, ensuring the safety of patient medical technologies, early detection of patients with signs of infectious diseases, and training of medical personnel. It is necessary to consolidate specialists from various fields to systematize best practices and develop guidelines at the national and regional levels.

Polyethersulfone (PES)-based materials have been increasingly applied in the area of blood purification because of their outstanding thermal, oxidative, and physical/chemical stability, excellent mechanical properties, mild sterilization conditions, and ease of processing. In addition, PES can easily form highly porous structures within the bulk by phase inversion between aqueous solutions and organic solvents. This pore-forming characteristic contributes to the application of PES-based materials for effective adsorption and separation in hemodialysis (HD), hemoperfusion (HP) and extracorporeal membrane oxygenation (ECMO). However, the intrinsic hydrophobic nature of PES, which leads to biofouling and relatively poor hemocompatibility, restricts its further practical use. This review outlines the concept of the heparin-like functionalization of PES, aiming to find an effective way to address the hemocompatibility issues. We discuss the fabrication strategy of functional PES-based materials and highlight the virtue of the proposed in situ crosslinking copolymerization method. We also review the fabricated multifunctional PES products, including membranes, microspheres and fibers, with not only anti-fouling, antibacterial, anticoagulant and antioxidant functions, but also stimulus-responsiveness under varied pH, salinity, anions, temperature, photoperiods and redox conditions. The integration of smart functions with novel structures, such as core-shell and bionic design enriches the variety of PES based materials and maximumly promoting the blood toxin adsorption and separation capacity. Thus, these materials are promising candidates for HD and HP applications in artificial kidneys, livers and lungs, aligning with current research developments. Finally, we summarize the perspectives and challenges of PES-based materials for blood purification and provide guidelines for the development of these materials, from functionalization and fabrication to biomedical engineering applications.

Blood oxygenation artificial lung membranes – three incremental modification strategies to improve hemocompatibility

Rationale:Early lung cancer diagnosis is crucial for prognosis, but elderly patients with comorbidities poorly tolerate invasive procedures. Conventional percutaneous biopsy for major vessel-adjacent high-risk nodules has a mere 60% to 70% success rate and high complications, while artificial pneumothorax boosts it to 85% to 90%. This case verifies the technique’s safety in this population.Patient concerns:A 72-year-old female had a 7-mm left lung ground-glass nodule (2021, no intervention). Follow-up computed tomography (CT) (November 2024) showed the nodule enlarged to 10 × 10 mm with a new 18 × 17 mm irregular consolidation. Empirical anti-infection failed; the lesion was adjacent to the aortic arch and heart, so artificial pneumothorax-assisted CT-guided biopsy was adopted.Diagnoses:Video-assisted thoracoscopic surgery confirmed stage IA1 (tumor, node, metastasis stage T1aN0M0) lung adenocarcinoma (lepidic-predominant + invasive mucinous subtypes), with negative margins and no vascular, nerve, or pleural invasion.Interventions:CT-guided artificial pneumothorax-assisted percutaneous lung biopsy, followed by video-assisted thoracoscopic surgery left upper lobectomy plus lymph node dissection.Outcomes:Vital signs were stable; drainage tube removed on day 4 post-biopsy. One-month follow-up: no hemoptysis, chest pain, or pneumothorax; CT showed no intrapulmonary exudation.Lessons:The technique is safe for lesions adjacent to the heart and major vessels. However, large-sample studies and artificial intelligence–based nodule analysis are needed to further verify its efficacy.

The article discusses medical devices registered on the domestic pharmaceutical market that are used in long-term home oxygen therapy for patients with chronic obstructive pulmonary disease (COPD). The aim of the study was to investigate portable oxygen sources used in patients with COPD at home. The methods of statistical, logical, comparative and content analysis were used in the study. The relevance of studying the portable oxygen sources market is due to an increase in the number of patients with chronic obstructive pulmonary disease who require long-term oxygen therapy at home. According to the nomenclature classification of medical devices and codes of types of medical devices, portable oxygen sources belong to the group of Anesthetic and respiratory medical devices. As a result of studying the technical characteristics of various medical devices, we proposed to classify them as portable oxygen sources: a portable liquid oxygen unit, a mobile/portable oxygen concentrator, artificial lung ventilation devices with the possibility of non-invasive administration, inhaler cans with a gas oxygen mixture. In the State Register of Medical Devices, electric ventilators, constant positive pressure ventilators for home use and mobile/portable oxygen concentrators are represented in the largest number of valid registration certificates. The most significant increase in registered medical devices used in home oxygen therapy was noted first in 2020 and then in 2024, which we attribute to the coronavirus pandemic and its consequences. Portable oxygen sources from foreign manufacturers prevail in the Russian pharmaceutical market (87%), China is the leader (18 manufacturers), followed by the USA and Germany (14 manufacturers each). In the Russian Federation, patients suffering from severe respiratory diseases have the right to receive medical devices and medical equipment free of charge as part of palliative care provided at home, including portable oxygen sources.