OBM Transplantation

(ISSN 2577-5820)

OBM Transplantation (ISSN 2577-5820) is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc., which covers all evidence-based scientific studies related to transplantation, including: transplantation procedures and the maintenance of transplanted tissues or organs; assimilation of grafted tissue and the reconstitution of removed organs or parts of organs; transplantation of heart, lung, kidney, liver, pancreatic islets and bone marrow, etc. Areas related to clinical and experimental transplantation are also of interest.

OBM Transplantation is committed to rapid review and publication, and we aim at serving the international transplant community with high accessibility as well as relevant and high quality content.

The journal publishes all types of articles in English. There is no restriction on the length of the papers. We encourage authors to be concise but present their results in as much detail as necessary, as reviewers are expected to emphasize scientific rigor and reproducibility.

 
 

Publication Speed (median values for papers published in 2024): Submission to First Decision: 6.7 weeks; Submission to Acceptance: 14.4 weeks; Acceptance to Publication: 4 days (1-2 days of FREE language polishing included)

 
 
Open Access Review

Machine Perfusion in DCD Lung Transplantation: Advances in Preservation and Donor Pool Expansion

Chawannuch Ruaengsri 1,*, Marc Leon 1, Miguel Alvarez-Cortes 1,2, Manuel Quiroz-Flores 1, Yasuhiro Shudo 1

  1. Division of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA

  2. University of Puerto Rico School of Medicine, San Juan, PR 00936, USA

Correspondence: Chawannuch Ruaengsri

Academic Editor: Chiara Lazzeri

Special Issue: Organ Preservation and Distribution

Received: June 30, 2025 | Accepted: January 08, 2026 | Published: January 21, 2026

OBM Transplantation 2026, Volume 10, Issue 1, doi:10.21926/obm.transplant.2601264

Recommended citation: Ruaengsri C, Leon M, Alvarez-Cortes M, Quiroz-Flores M, Shudo Y. Machine Perfusion in DCD Lung Transplantation: Advances in Preservation and Donor Pool Expansion. OBM Transplantation 2026; 10(1): 264; doi:10.21926/obm.transplant.2601264.

© 2026 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

Abstract

To address the pressing shortage of donor lungs, Donation after Circulatory Death (DCD) transplantation has become a vital strategy for expanding the donor pool. Minimizing warm ischemic injury is crucial for optimizing organ viability and function. This review synthesizes current evidence on Normothermic Regional Perfusion (NRP) and Ex-Vivo Lung Perfusion (EVLP) in DCD lung transplantation. Analysis reveals their growing efficacy in minimizing ischemic damage, facilitating organ assessment, and expanding the transplantable organ pool. Studies indicate comparable or improved recipient outcomes, including reduce primary graft dysfunction (PGD) and improved survival. However, challenges persist regarding protocol standardization, ethical considerations and long term outcome validation.

Keywords

Normothermic regional perfusion; donation after circulatory death; lung transplantation; lung preservation; ex-vivo lung perfusion

1. Introduction

Lung transplantation is considered the gold standard treatment for patients with end-stage lung disease. The limited availability of suitable donor lungs remains the primary barrier to increase the rate of lung transplantation. Currently, donation after brain death donors (DBD) continue to the majority source of lung allografts. However, less than 25% of DBD donors provide lungs that meet transplantation criteria [1]. To address this shortage, donation after circulatory death (DCD) has been proposed as a viable strategy to expand the donor organ pool. Ex-vivo lung perfusion (EVLP) has been employing to optimize marginal donor lungs [2].

Warm ischemic injury sustained during the hypotensive phase following withdraw life support and the subsequent cold ischemic period prior to reperfusion in the recipient reflected the unfavorable outcomes after transplant [3]. Recently, normothermic regional perfusion (NRP) has emerged as an innovative technique for procuring organs following circulatory death by using extracorporeal membrane oxygenation (ECMO) to restore oxygenated blood perfusion to allografts at normothermic state [4]. While NRP and EVLP offer significant promise in minimizing ischemia and enhancing organ quality, a comprehensive and critical synthesis of their integrated impact on DCD lung procurement, particularly in the context of multiorgan harvesting and evolving ethical considerations, remains crucial for optimizing their application and maximizing donor potential [5].

This review critically synthesizes current evidence on machine perfusion in DCD lung transplantation, focusing on their mechanisms for minimizing ischemic injury, evaluating outcomes and utilization, discussing technical strategies for multiorgan procurement, and highlighting ethical debates and future directions in clinical practice and research.

2. History of DCD Lung Transplant

The first-in-human lung transplant was conducted by Dr. Hardy in 1963, utilizing a lung procured after circulatory death, a method akin to current DCD practices [6]. Although the recipient survived only 18 days due to renal dysfunction, the lung graft itself functioned well, marking a significant milestone and establishing lung transplantation as a viable option [6].

In the subsequent decades, a considerable number of lung transplants from DCD donors were performed [7]. However, the long term success of these early transplants was significantly challenged by limitations in immunosuppressive therapy, as the crucial drug cyclosporine had not yet received FDA approval. This lack of effective immunosuppression, coupled with the introduction of the Uniform Determination of Death Act (UDDA) [8], which established brain death criteria, let to a decline in DCD utilization as donation after brain death (DBD) became the preferred and dominant pathway [9].

With advancements in medical care and the overall improvement in lung transplant patient outcomes, the critical scarcity of suitable organ reemerged as a primary limitation. This renewed imperative spurred a re-evaluation of CD. Which is broadly classified into two primary pathways: controlled DCD (cDCD) and uncontrolled DCD (uDCD), often categorized by the modified Maastricht classification (Table 1) [10]. In 1993, Love et al. achieved the first successful lung transplant from a donor following the elective withdrawal of life-sustaining therapy (WLST), a practice subsequently recognized as controlled DCD (cDCD) [11]. This cDCD pathway benefits from a planned and controlled environment, typically occurring in the operating room (OR), post-anesthesia care unit (PACU), or intensive care unit (ICU) [10]. Such settings allow for optimized donor management, a predicted and often shorter warm ischemic time (WIT), and coordinated surgical team efforts, resulting in lungs with less ischemic injury, often suitable for direct transplantation or with in-situ normothermic regional perfusion (NRP) to further minimize ischemia [12].

Table 1 "Organ Donor Classification After Circulatory Death: Modified Maastricht System" [13].

Conversely, uDCD occurs following an unanticipated cardiac arrest, generally outside the hospital or in an emergency unit, where WLST is not performed [12]. The unpredictable nature and potentially prolonged period of untreated warm ischemia in uDCD donors present significant challenges to organ viability. Lung procured from uDCD often incur more severe ischemic damage, necessitating advanced preservation techniques, such as ex-vivo lung perfusion (EVLP), for thorough assessment, reconditioning, and improved suitability before transplantation [10,12]. This historical trajectory underscores the challenges in donor organ availability and sets the stage for modern strategies, such as machine perfusion, aimed at minimizing ischemia and optimizing graft viability across the spectrum of DCD contexts.

This system groups organ donors based on when, where, and how circulatory death occurs. It separates uncontrolled deaths (like unexpected cardiac arrest) from controlled deaths (such as planned life support withdrawal). The classification helps assess donor eligibility and guide organ recovery [13,14].

3. Donation After Circulatory Death: Challenges and the Rationale for Machine Perfusion

Building on the historical context of DCD and its classification as detailed by Maastricht classification in Table 1. While cDCD is the most widely utilized approach due to planned withdrawal of support and optimized timing and logistics, the criteria for DCD donor lung selection typically mirror those for donation after brain death (DBD), involving bronchoscopy, chest X-ray, arterial blood gas analysis, and direct organ visualization. Early experimental studies, by Egan et al. [15], indicated that lung tissue could remain viable for up to an hour post cardiac arrest, suggesting a tolerable warm ischemic time (WIT) of 60-90 minutes [16,17]. However, these findings were often based on controlled arrest models (medication induced or electrical fibrillation), which frequently overlooked the complex and injurious physiological events occurring during the agonal phase of actual DCD donors.

The lung possesses unique anatomical and physiological characteristics that render it particularly vulnerable to ischemic-reperfusion injury [18]. Its high metabolic demand is coupled with a fragile vascular architecture, which can lead to significant oxidative stress and inflammatory responses when blood flow is restored after a period of ischemia. Unlike other solid organs, the lungs rely heavily on adequate oxygenation and clearance of inflammatory mediators, making them susceptible to damage during the reperfusion phase. Understanding these peculiarities is crucial for developing effective preservation strategies that aim to minimize injury and improve outcomes in lung transplantation [18,19].

The clinical reality of DCD procurement often involves dynamic physiological changes that significantly compromise graft quality. Pre-mortem hypotension and cardiopulmonary instability, as highlighted by Tremblay et al. [20], induce polymorphonuclear leukocyte activation and sequestration, leading to the release of damaging proinflammatory cytokines [20]. Furthermore, the sympathetic surge during the agonal phase can cause capillary damage and pulmonary edema, manifesting as acute respiratory distress syndrome (ARDS) like features upon reperfusion. Suboptimal graft quality has been observed in DCD lungs from hypoxic cardiac arrest models compared to more controlled scenarios, exacerbated by the risk of aspiration from unprotected airway [21].

Simultaneous thoracic and abdominal organ retrieval from DCD donors is globally standard practice [22,23]. Traditionally, this relies on rapid recovery with in-situ organ flush, a cost-effective method still preferred in some regions. However, this approach demands exceptionally high surgical skill to minimize the risk of organ injury or organ loss from technical errors, and critically, offers no opportunity for real time functional assessment or mitigation of prior ischemic damage [22].

These formidable challenges, particularly the unpredictable nature of WiT, the complex inflammatory cascade, and the limitations of cold static preservation in reversing ischemic injury or providing functional assessment, have provided the compelling rationale for the development and adoption of machine perfusion technologies like normothermic regional perfusion (NRP) and ex-vivo lung perfusion (EVLP). These techniques aim to counter these adverse effects, thereby enhancing graft viability and expanding the therapeutic window for DCD lungs [24,25].

4. Normothermic Regional Perfusion (NRP) in DCD Lung Procurement

Normothermic Regional Perfusion (NRP) has emerged as a revolutionary technique in the procurement of lungs from DCD donors, addressing the significant challenge posed by warm ischemic injury. This method employs Extracorporeal Membrane Oxygenation (ECMO) to restore and maintain oxygenated blood flow to the organs at physiologic temperature, thereby preserving metabolic function and enhancing graft viability [26].

4.1 Clinical Impact of NRP

NRP has been shown to facilitate better outcomes in DCD lung transplantation compared to traditional methods [26]. By actively perfusing organs post-mortem, NRP reduces the incidence of warm ischemia, consequently mitigating the risk of primary graft dysfunction (PGD). Studies indicate that lungs procured using NRP exhibit improved metrics in oxygenation, lung compliance, and long-term survival rates [27]. For instance, 1 year survival rates for DCD lungs utilizing NRP often surpass those of conventional cold static storage [26,28].

4.2 Comparative Effectiveness

While NRP demonstrates significant advantages in the recovery and preservation of DCD lungs, [26] it is crucial to understand its performance relative to other techniques, particularly Ex-vivo lung perfusion (EVLP). Both NRP and EVLP serve to optimize donor lung conditions post-mortem, but they are utilized in different clinical contexts based on specific factors.

NRP is primarily employed the ability to maintain organ perfusion at normothermic temperature, which enhance metabolic activity and facilitates the immediate assessment of organ viability in situ. By restoring oxygenated blood flow, NRP effectively mitigates warm ischemic injury. It is useful in scenarios where swift decision-making is required after withdrawal of life support, allowing for rapid organ procurement and intraoperative organ assessment [26,27,29].

In contrast, EVLP serves as a post retrieval assessment technique that enables prolonged evaluation and rehabilitation of donor lungs outside the body. It involves perfusing lungs under controlled conditions and can provide a detailed analysis of graft viability based on parameters such as gas exchange, lung compliance, and pulmonary edema. EVLP is highly beneficial for lungs that may be deemed marginal, allowing for potential therapeutic interventions to improve transplant outcomes [30].

The choice between NRP and EVLP depends on specific scenarios, such as donor lung condition, urgency of the transplant, and available resources. Centers with robust ECMO capabilities may favor NRP for its rapid implementation, while those with well established EVLP programs may opt for EVLP to maximize lung function before transplantation [31].

Moreover, the emergence of specialized third-party services that offer NRP [32] and EVLP as a hub for multiple hospitals can play a pivotal role in enhancing access to these techniques. Such centers provide expertise, advanced technology that can support smaller institutions lacking the resources or training needed for those procedures. However, the utilization of these centralized services may incur additional costs, including logistical fees, service charges for specialized personnel, and costs associated with the technology employed during NRP and EVLP [32,33].

Combining both techniques may also present a comprehensive strategy. NRP can be utilized for initial organ preservation and assessment, followed by EVLP to further optimize lung function before transplantation. This integrated approach enhances patient outcomes and maximizes the use of available donor organs [2,34].

5. Donor Cannulation in NRP

Donor cannulation for NRP is critical in facilitating optimal graft preservation while mitigating the risk of unintended reperfusion of the brain. Recent guidelines from the Organ Procurement and Transplantation Network (OPTN) [35] emphasize the importance of addressing the potential for unintended reperfusion due to collateral circulation, aberrant anatomy, or clamp failure. To reinforce patient safety, all stakeholders involved in the NRP process, including Organ Procurement Organization (OPO) staff, hospital teams, transplant centers, and third-party service providers, must review their practices to align with these updated recommendations [35].

The methodology for cannulation may differ based on national regulations and institutional protocols, which primarily dictate whether cannulation occurs pre or post-mortem. The legal frameworks surrounding DCD donor cannulation vary in different jurisdictions. In Spain and Belgium, pre-mortem cannulation is permitted, allowing for advanced preparation that can minimize warm ischemic time (WIT) [36]. In contrast, countries like France, Italy, and Norway utilize techniques for ante-mortem vessel identification, often using guidewire under the Seldinger technique. These procedures are accompanied by protocols to secure explicit consent from the donor’s next of kin before any pre-mortem interventions [12].

Ethical considerations play a significant role in the cannulation process. Adhering to established protocols not only respects the autonomy of the donor’s family but also fosters trust in the organ donation system. Transparency about practices and ensuring informed consent are crucial in maintaining ethical integrity and public confidence in the transplantation process [35].

Following the declaration of death due to loss of circulatory function, the cannulation process begins with the positioning of the donor and administering heparin to prevent clotting. For abdominal NRP (A-NRP) (Figure 1 and Figure 2), the aorta must be occluded above the level of the celiac origin, either just below or immediately above the diaphragm. It is essential that the proximal aorta is transected cephalad to this occlusion and allowed to drain to the atmosphere before initiating perfusion. Techniques such as vascular clamps or intra-aortic balloons may be employed for occlusion, and the approach used should be documented in the OPO donor record [35].

Click to view original image

Figure 1 This image demonstrates an in-situ inspection of the lungs, with lung recruitment and compliance testing conducted while Abdominal Normothermic Regional Perfusion (A-NRP) is actively in progress. Prior to initiation of NRP, the inferior vena cava (IVC) and thoracic aorta were clamped, ensuring optimal conditions for lung evaluation. This approach highlights the importance of thorough assessment and intervention in maximizing donor lung function prior to transplant [37,38].

Click to view original image

Figure 2 This image illustrates the implementation of Abdominal Normothermic Regional Perfusion (A-NRP) in conjunction with the rapid recovery of lungs from donors after circulatory death (DCD). In this set up, the inferior vena cava (IVC) and thoracic aorta are securely clamped within the chest, while the superior vena cava (SVC), neck vessels, and azygos vein are ligated, ensuring there is no bleeding present inside the chest cavity. Notably, this is accomplished while the A-NRP process continues uninterrupted, demonstrating that the integrity and functionality of the NRP circuit remain uncompromised throughout the operation [38].

In thoraco-abdominal NRP (TA-NRP), individual occlusion of the vessels arising from the aortic arch, namely the brachiocephalic, left common carotid, and left subclavian arteries, is required. Each artery should be transected and allowed to drain to the atmosphere prior to perfusion initiation, ensuring there is no cerebral reperfusion. As with A-NRP, appropriate techniques such as vascular clamps, ligation, or staplers should be employed, and this process must be thoroughly documented in the donor record.

It is vital for all team members to maintain open communication and coordination during the NRP procurement process. A pre-recovery time out should be conducted to review the plan for securing and transecting the appropriate vessels, including contingency plans to address potential complications such as inadequate occlusion or sustained back bleeding. Ensuring to these protocols not only enhances patient safety but also fosters trust in the organ donation and procurement process.

6. DCD Lung Donor Evaluation

The assessment of DCD lung donors is conducted similarly to that of other donors, with some important exceptions. Due to limitations in performing lung recruitment techniques prior to organ donation in DCD situations, a slightly lower threshold for the challenge gas of greater than 200 is permissible [39]. Appropriate donors should also exhibit strong urine output to help minimize anticipated pulmonary edema after the thoraco-abdominal NRP (TA-NRP) process [39].

Once the donor is prepared and the decision to initiate TA-NRP is made, the TA-NRP circuit is started. At this point, donor reintubation and bronchoscopy can be performed. For lung retrieval, a pulmonary artery (PA) vent is placed for decompression, with both cardiac and lung teams reconfirming the location to ensure that both receive sufficient margins (Figure 3) This PA vent cannula can be utilized for pulmoplegia flush when ready to proceed with procurement [40].

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Figure 3 This figure illustrates the thoracoabdominal NRP (TA-NRP) cannulation technique used during simultaneous DCD heart and lung procurement. A two-stage venous cannula is inserted via the right atrium, and a pulmonary artery (PA) vent is placed to reduce pulmonary blood flow to the lungs. The arterial cannula is positioned through the innominate artery to deliver perfusion to both thoracic and abdominal organs. Aortic root pressure monitoring line is placed to track central blood pressure and can also serve for cardioplegia delivery during cross clamping. All head vessels are clamped to prevent cerebral perfusion [41].

Protective lung ventilation is implemented with parameters including 4-8 mL/kg of ideal body weight, a respiratory rate of 10-15 breaths per minute, PEEP of 5, and 40% FiO2. Lung recruitment, potentially using a Valsava maneuver, may be necessary to address lung atelectasis. The TA-NRP flow rate should be maintained above 2.2 L/m/m2. The ideal duration of TA-NRP has yet to be established. However, extended donor organ dissection during TA-NRP can lead to a loss of reservoir volume, necessitating the transfusion of banked blood. It is essential for discussion among team members regarding the duration of TA-NRP to occur and be agreed upon prior to the procedure. When performing only thoracic organ recovery, it is advisable to limit TA-NRP to less than one hour [34,40].

The performance and quality of the lungs should undergo thorough evaluation once the donor has been discontinued from TA-NRP, ensuring that adequate ventilator support is in place. Systemic blood gas or pulmonary vein gas sampling can be conducted as deemed necessary [34].

When the team is ready, an aortic cross clamp is applied. Similar procedures followed for donations after brain death, both heart and lungs are vented for decompression. The procured lungs should be evaluated at the back table, packed, and stored in either cold storage or a temperature-controlled environment before being transported to the recipient center.

To effectively recover donor lungs and assess lung functions during TA-NRP, several protective strategies should be implemented. Aggressive diuresis should be performed at specific times to achieve a negative fluid balance [39,40]. It is essential to thoroughly drain all donor blood once the venous cannula is in place to reduce pressure inside the heart and alleviate congestion in the lungs and abdominal organs before initiating TA-NRP. Placement of the PA vent helps decrease hydrostatic pressure on the lung. Early reintubation should be followed by minimal lung recruitment or a Valsava maneuver along with lung protective ventilation parameters. Additionally, reducing the duration of TA-NRP is advisable to maintain optimal condition [34,39,40].

While direct lung recovery can be safely carried out during A-NRP, clinical experiences have shown positive transplant outcomes [42,43,44]. The debate continues regarding whether NRP contributes to lung injury. Recent findings indicate that outcomes are comparable to those of conventional DCD lungs [39,45,46,47,48,49]. However, the incidence of lung decline following TA-NRP remains unclear, and many centers have report unpredictable outcomes [34]. The inconsistency in TA-NRP practices, particularly regarding PA venting, may contribute to pulmonary edema. There is a pressing need for further long-term survival studies on the use of lung allografts following TA-NRP. Due to insufficient data comparing direct procurement and procurement with TA-NRP, the expert consensus is unable to recently endorse one technique over the other for lung recovery. More research is anticipated to provide clearer guidance [34].

7. Static Cold Storage (SCS)

Static cold storage has been the gold standard for lung preservation [34]. This method involves using a cold pulmoplegia solution to flush the lungs, which are then slightly inflated and stored on ice or within a temperature-controlled device. The cold environment significantly reduces the metabolic activity of the lungs, thereby prolonging their viability until transplantation.

7.1 Benefits of Static Cold Storage

One of the key advantages of static colds is its simplicity and the established nature of the technique. SCS is easy to implement in most transplant centers and does not require complex machinery, making it accessible for a wide range of clinical settings. Additionally, when performed correctly, static cold storage has been effective in yielding successful transplant outcomes, particularly for organs that meet standard criteria for donation [34].

7.2 Limitations of Static Cold Storage

Despite its benefits, static cold storage has notable limitations. The risk of cold ischemic injury is a significant concern, which can lead to primary graft dysfunction (PGD) following transplantation [34]. The preservation fluid must be managed carefully, as inadequate cooling or uneven temperature distribution can lead to further complications. Moreover, prolonged cold ischemic times may adversely affect graft quality, potentially impacting post-transplant outcomes.

Recent study has indicated that suboptimal storage temperature, particularly below 0 degree Celsius can result in freeze injuries to lung tissue [50]. This highlights the need for ongoing evaluation of optimal preservation conditions to maximize donor organ viability.

Recent advancements in lung preservation strategies have led to a reevaluation of static cold storage practices [50,51]. Study has shown improved mitochondrial functions and inflammatory responses in lung allografts stored at a slightly elevated temperature of 10 degrees celcius [51]. Motivated by this finding, a multicenter nonrandomized clinical trial demonstrated comparable outcomes in recipients who received lung allografts preserved at this temperature, with prolonged ischemic times up to 14 hours compared to those who received grafts stored on ice for up to 7 hours [52]. Indices such as PGD, perioperative mortality, and 1-year survival rates were favorably impacted [52].

Additionally, data from a multicenter registry indicate that lungs preserved using storage devices maintaining stable temperatures between 4-8 degrees celcius show a trend toward lower PGD rates at 72 hours postoperatively [53].

Several studies are exploring the optimal temperature of static cold storage and the deliberate extension of cold ischemic times for lung allografts [50,51,52]. In a study conducted by the Toronto team, 5 patients received lung transplants using lungs preserved at 10 degrees celcius, with cold ischemic times extended to as long as 16 hours, and no cases of grade 3 PGD were reported at 72 hours [51]. This research emphasizes the feasibility of intentionally extending cold ischemic time, challenging previous beliefs in the field. The results of ongoing randomized trials comparing preservation at 4 degrees celcius versus 10 degrees celcius are eagerly awaited, particularly as they assess the implications of extending cold ischemic time within 10 degrees celcius cohort [34].

8. Ex-Vivo Lung Perfusion (EVLP)

Static cold preservation has significant drawbacks, particularly its inability to adequately assess and improve the condition of the graft at low temperatures. Consequently, Ex-Vivo Lung Perfusion (EVLP) has emerged as a promising alternative, allowing for the perfusion and maintenance of lungs under physiological and normothermic conditions. This approach may significantly expand the donor pool, as only about 15-25% of donated lungs are typically deemed suitable for transplantation, with many others discarded or used for research [54,55]. Many institutions are now considering grafts from donors with expanded criteria that may require ex-vivo assessment [2,56]. Additionally, logistical challenges and conflicting clinical demands can lead to the discarding of potentially usable organs [56,57].

EVLP was first introduced clinically by Steen et al. [58], who successfully performed a lung transplant using a lung from an uncontrolled DCD donor following EVLP. This technique offers a way to improve lung evaluation, extend preservation time, and potentially restore donor lungs by maintaining their function through continuous perfusion and ventilation at normothermic levels, thus facilitating lung resuscitation and optimization of function [58,59].

The main indications for EVLP [2,60] include a low P/F ratio, where donor lungs showing a low P/F ratio of less than 300 mmHg indicate ineffective oxygen exchange. Evidence of pulmonary edema, characterized by fluid infiltration detectable via chest X-ray or clinical examination, allows for the evaluation of the severity of pulmonary edema and monitoring of its resolution. Additionally, EVLP is indicated for donors with a poor compliance profile and those with high-risk histories, such as significant transfusions before procurement or questionable airway aspiration histories. Furthermore, DCD donors, particularly those with an interval of more than one hour from WLST, benefit from EVLP as it provides extra time for assessment of lungs that may have experienced warm ischemic injury [60,61].

In the United States, there are currently two primary EVLP systems in clinical use: the XVIVO Perfusion System (XPS) and the Organ Care System (OCS, Transmedics) [60]. These systems differ in several key aspects, most notably the portability of the OCS compared to the stationary design of the XPS. Both systems utilize a ventilator connected to an endotracheal tube for ventilation, with perfusion fluid pumped through a circuit attached to the pulmonary artery (PA) for antegrade flow. The OCS features open pulmonary vein drainage, while the XPS employs a pulmonary venous cannula for a closed drainage circuit. Oxygenation is achieved through a gas exchanger, and normothermia is maintained with a heat exchanger [60].

9. The Organ Care System (OCS)

The Lung Organ Care System (OCS) (Figure 4) is a mobile unit specifically designed to reduce cold ischemic times during the transportation of donor lungs [62]. Its use is contraindicated in cases involving lung contusion or traumatic lung injuries. Donor lungs harvested for OCS are prepared in a manner similar to those for traditional static cold storage. It is essential that the pulmonary artery (PA) be of adequate length to facilitate successful cannulation with a PA cannula, ensuring equal perfusion to both the left and right lungs without preferential distribution. In instances where the pulmonary artery is short, particularly in donors from whom both the heart and lungs are being procured, reconstruction using a segment of the descending aorta via end-to-end anastomosis may be necessary to achieve sufficient arterial length [63].

Click to view original image

Figure 4 The Organ Care System (OCS) by Transmedics (Andover, MA) comprises a portable base unit (Left image) and a single-use, sterile disposable module (Right image). The disposable module includes essential components such as a pulsatile perfusion pump, perfusate reservoir, integrated ventilator, gas exchanger, tubing system, and a transparent sterile chamber that houses the donor lung. This figure has been reproduced by permission of TransMedics (Andover, MA).

The OCS (Figure 4) consists of a portable base unit and a single-use, sterile disposable module. This module incorporates vital components such as a pulsatile perfusion pump, a perfusate reservoir, an integrated ventilator, a gas exchanger, tubing system, and a transparent sterile chamber designed to house the donor lung [62]. This configuration facilitates effective monitoring and management during lung preservation.

The priming solution for the OCS is created by mixing three units of leukocyte-depleted packed red blood cells with two liters of OCS lung solution, further supplemented with sodium bicarbonate, insulin, milrinone, antibiotics, multivitamins, and various additives. Once the temperature of the perfusate reaches 32 degrees Celsius, the lungs begin to be perfused, with the temperature gradually increasing to 37 degrees Celsius. Ventilation commences once the system reaches 34 degrees Celsius, and the OCS is then transported to the recipient hospital for final evaluations [62,64].

To assess lung function, the protocol for measuring the PF (PaO2/FiO2) ratio involves several key steps. After procurement, the donor lungs are connected to the OCS, providing continuous perfusion and ventilation. Ventilatory settings are typically established to include a tidal volume of approximately 6-8 mL/kg of predicted body weight and a respiratory rate set between 10-15 breaths per minute. The fraction of inspired oxygen (FiO2) is adjusted as necessary, and arterial blood gases (ABG) are closely monitored to evaluate lung function.

The PF ratio is calculated by dividing the measured PaO2 (partial pressure of oxygen in arterial blood) by the FiO2. A PF ratio greater than 300 mmHg generally indicates acceptable lung function for transplantation, while lower ratios may suggest inadequate function, necessitating reevaluation of the donor lungs [62]. Continuous monitoring and documentation of the PF ratio and other relevant parameters are crucial for informed decision-making regarding lung transplantation. If the lungs are deemed acceptable for transplant, they are flushed with cold OCS solution [62].

The EXPAND trial [64] marked the first multicenter prospective international study to evaluate the Organ Care System (OCS) aimed at enhancing donations from extended criteria and DCD donors. This trial reported an impressive utilization rate of 87%, with 33% of the donors being DCD. Notably, the one-year survival rate for DCD donors was 100% [64].

Loor and colleagues assessed the short-term and long-term outcomes of the OCS lung system in the EXPAND trial and found a high utilization rate for both extended criteria donor lungs and DCD donor lungs, with post-transplant outcomes that were not inferior to those of standard donors [65].

10. The XVIVO Perfusion System (XPS)

The XVIVO Perfusion System (XPS) is designed as a stationary perfusion system for in-house lung assessment [2]. This device facilitates X-ray imaging, allowing for effective evaluation of lung edema, indicated by an increase in graft weight, as a measure for assessing fluid accumulation. XPS uses an acellular STEEN solution instead of a blood-based perfusate, mixed with heparin, steroids, and antibiotics. The system adheres closely to the Toronto protocol with two cannulas: one attached to the left atrium and another to the pulmonary artery. After the lungs are moved to the XPS chamber, the PA cannula is connected to the circuit, and the flow of the perfusate begins. The temperature is gradually raised to 37 degrees Celsius, with ventilation commencing at 34 degrees Celsius. Lung recruitment is performed hourly with a peak airway pressure of 25 cm H2O, accompanied by an oxygen challenge. Periodic bronchoscopy and X-ray evaluations are also conducted [2].

The NOVEL trial [25], a prospective, nonrandomized controlled study, included a total of 216 donor lungs that underwent EVLP, resulting in 110 successful transplants. The lungs assessed through EVLP exhibited similar rates of primary graft dysfunction (PGD) grade 3 at 72 hours and comparable one-year survival rates to 116 control lungs that did not undergo EVLP [25].

The NOVEL extension trial [24], conducted from July 2011 to January 2017, utilized the XVIVO Perfusion System for donor lungs after circulatory death (DCD), achieving a 51% utilization rate. Among 95 recipients, 71 were from donation after brain death (DBD) and 24 from DCD donors, with success rates of 55.5% for DBD and 40.7% for DCD. Notably, there were no statistically significant differences in primary graft dysfunction (PGD) rates between the two groups [24].

11. Financial Implications

The financial implications of using Ex-Vivo Lung Perfusion (EVLP) compared to the Organ Care System (OCS) can vary significantly, and it is essential for decision-makers to evaluate these costs when determining the most suitable approach for their institution (Table 2).

Table 2 Advantages and Key Considerations of Lung Preservation Methods.

In general, the OCS is often regarded as less expensive than EVLP. The OCS is designed for portability and ease of use, which can lead to lower operational costs associated with transport and implementation. Consumable costs for the OCS, such as perfusion solutions and sterile components, are typically standardized, but they still need to be factored into the overall budget.

Conversely, EVLP generally involves higher initial and ongoing costs due to the need for specialized equipment and the complexity of the procedure. The EVLP systems require skilled personnel who are trained to operate complex machinery, which can increase labor costs. Additionally, the expenses related to consumables and the potential for equipment maintenance also contribute to higher operational costs.

While the OCS may present a more cost-effective option in terms of initial expenses, the benefits of EVLP—such as its capability for thorough evaluation and rehabilitation of donor lungs may justify the higher costs in specific clinical scenarios. Ultimately, the decision between using OCS or EVLP will depend on individual center capabilities, patient needs, and the conditions of the donor lungs.

As research continues to evolve, further comparative studies will be essential to guide best practices and optimize resource allocation in lung transplantation.

This table provides a comparative overview of the 3 primary lung preservation techniques: Static Cold Storage (SCS), Ex-vivo Lung Perfusion (EVLP), and the Organ Care System (OCS). It highlights the advantages, limitations, preservation times, and costs associate with each method.

12. Future of Lung Transplantation: Artificial Intelligence (AI) and Research Innovations

The recent technological revolution has introduced artificial intelligence (AI) and machine learning (ML) as transformative forces capable of optimizing the entire transplantation lifecycle. By leveraging vast datasets comprising clinical, radiographic, and molecular information, AI facilitates a transition from subjective clinical assessment to objective, data-driven precision medicine [66,67,68]. Currently, the supply of viable donor lungs significantly lags global demand, resulting in high waitlist mortality [26,69]. Furthermore, the assessment of donor suitability remains subjective, with fewer than 30% of offered organs being accepted for transplantation [69,70]. Artificial intelligence addresses these inefficiencies through advanced predictive tools that forecast the viability of donors after circulatory death (DCD), provide high-resolution radiographic screening via ex vivo computed tomography (CT), and offer real-time autonomous monitoring during ex vivo lung perfusion (EVLP) [69,71]. These technologies expand the donor pool by rehabilitating marginal organs and refining the matching process to ensure optimal recipient compatibility [72]. The initial phase of lung transplantation involves organ procurement, which is characterized by significant logistical challenges. Identifying suitable donors is often complicated by physiological deterioration following brain death or circulatory arrest. Traditional selection relies on standard criteria such as age, smoking history, chest X-ray clarity, and gas exchange metrics. However, these metrics often lack precision [26,69,73]. AI-driven models now revolutionize this process by providing granular predictions and objective measurements that surpass human clinical judgment.

12.1 AI in DCD Lung Procurement Optimization

A significant barrier in organ procurement is the unpredictability of DCD donor outcomes. The interval between the withdrawal of life-sustaining treatment (WLST) and donor death is critical. If death does not occur within a strictly defined period, the procurement must be canceled [26,71]. Historically, clinicians cannot predict whether the donor will die within the time window after WLST, leading to high rates of futile procurements where surgical teams are mobilized for no organs [71]. Recent research from Stanford University introduced a machine learning model to predict death progression in DCD donors with high accuracy [71]. By analyzing neurological, respiratory, and circulatory data from over 2,000 donors, this AI tool reduced the rate of futile procurements by 60% [71]. This efficiency conserves hospital resources and increases the number of life-saving transplants by identifying viable donors previously bypassed due to uncertainty [66,71].

12.2 Radiographic Assessment and Donor-Lung Suitability

Radiographic evaluation is fundamental to donor assessment, yet conventional chest X-rays (CXR) are limited by two-dimensional perspectives and interpretation errors [73,74]. To overcome these limitations, researchers developed AI models to analyze CT scans of donor lungs both in vivo and ex vivo [69,70,73]. A breakthrough study utilized a supervised machine learning method known as dictionary learning to screen donor lungs ex vivo after procurement [5]. This algorithm focuses on unique image patterns pertaining to accepted versus declined lungs without prior knowledge of clinical variables [69]. The model effectively predicted long-term outcomes, noting that recipients of lungs the algorithm would have declined faced a 19-fold higher risk of Chronic Lung Allograft Dysfunction (CLAD) within two years and were 5.25 times more likely to experience severe Primary Graft Dysfunction (PGD) [69]. Furthermore, researchers are investigating lobar-level quantification through AI to identify salvageable tissue in marginal donors [70,73]. Instead of a binary approach, AI-enhanced CT scoring systems identify individual lung lobes healthy enough for transplantation even when the whole organ is considered suboptimal [73]. A 3D Res Net model integrated with clinical data predicted Grade 3 PGD with an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.74 [70].

12.3 The Intelligent Ex Vivo Platform

The preservation of pulmonary allografts has evolved from static cold storage (SCS) to sophisticated normothermic systems. While ice-box storage at 4°C slows metabolic rates, it precludes functional assessment or repair [26,59]. Ex vivo lung perfusion (EVLP) has revolutionized this phase by maintaining lungs in a physiological state (37°C) to allow for the assessment and reconditioning of marginal organs [2,59,75]. The voluminous data generated during EVLP is difficult for humans to interpret in real-time, making AI an essential decision-support tool. The InsighTx model (Table 3) represents an advanced application of machine learning within the EVLP platform [67,76]. Utilizing an eXtreme Gradient Boosting (XGBoost) algorithm, InsighTx was trained on 725 clinical human EVLP cases to predict post-transplant outcomes [67,76,77]. InsighTx provides a three-tiered clinical prediction:

  1. High Suitability: High likelihood of extubation in less than 72 hours [67,77].
  2. Prolonged Ventilation: Moderate likelihood of requiring extended postoperative support [67].
  3. Unsuitable: High risk of failure or poor quality [76,77].

Table 3 Diagnostic metrics analyzed by the InsighTx machine learning model during EVLP.

In a retrospective study, the use of InsighTx increased the odds of a favorable transplant decision by 13-fold for suitable lungs that might have been declined due to subjectivity [67,77]. Conversely, the model facilitated a 4% decrease in the decision to transplant unsuitable lungs, reducing the risk of graft failure [67]. The model's AUROC ranged from 0.75 to 0.85 across validation cohorts [67,77].

12.4 Biomarker Integration and Real-Time Metabolic Monitoring

The future of organ preservation involves real-time molecular diagnostics. During EVLP, the perfusate provides a non-invasive source for biological sampling [78]. AI models analyze inflammatory cytokines such as IL-6, IL-8, and soluble VCAM-1, which are linked to PGD development [67,78]. While traditional cytokine testing was previously too slow for clinical use, rapid platforms like TORdx LUNG now provide results in under 40 minutes [67]. InsighTx and similar systems ingest this data to create a digital twin of the lung, allowing clinicians to monitor the efficacy of therapeutic interventions such as gene therapy or antimicrobial treatments [2,78].

12.5 Strategic Donor-Recipient Matching and Allocation Models

Success in lung transplantation depends on morphological and immunological compatibility. Standard systems like the Lung Allocation Score (LAS) primarily balance urgency with expected survival [66]. AI-enhanced matching systems offer a multi-dimensional approach to this complex problem.

12.6 Automated Lung Sizing and Morphological Compatibility

Size mismatching causes significant postoperative complications. Oversized lungs may lead to impaired chest wall mechanics, while undersized lungs can result in persistent atelectasis [79,80,81]. Traditional size matching relies on predicted Total Lung Capacity (pTLC), which is often inaccurate for patients with end-stage lung disease [81]. AI systems using U-Net architectures now allow for automated lung sizing from radiographs with an error rate below 2.5% [79,82]. These systems identify anatomical landmarks to provide precise volumetric comparisons [79]. Furthermore, 3D point cloud analysis and K-Nearest Neighbors (K-NN) approaches help surgeons visualize the physical fit and potentially accept organs with significant size discrepancies if the AI predicts a proper anatomical fit [80,83].

12.7 Immunological Matching and Predictive Allocation

Immunological compatibility is a complex frontier. AI models now reveal that subtle HLA disparities at the epitope level significantly influence the development of donor-specific antibodies (DSA) and CLAD [66,84]. Using machine learning tools like HLA Matchmaker, researchers calculate compatibility scores for B-cell and T-cell epitopes [84]. These models demonstrate that HLA-DQB1 epitope scores are associated with worse survival and rapid rejection [84]. Additionally, AI analysis of UNOS database records has identified non-traditional risk factors like recipient serum albumin levels as critical predictors of mortality [68,85]. By integrating these variables, AI assists in risk-based matching to maximize the utility of limited resources [68,85].

12.8 Post-Transplant Monitoring and Predictive Analytics

AI utility extends into the post-transplant period to guide management. The primary challenges are PGD, occurring within 72 hours, and CLAD, which manifests after one year [66,68]. PGD is an acute lung injury with a multifactorial pathogenesis. AI models have been developed to forecast Grade 3 PGD:

  • Random Forest (RF) Models: In a study of 802 patients, an RF model achieved an AUROC of 0.82 in risk-stratifying patients for ECMO support and ICU stay [68].
  • K-Nearest Neighbor (KNN) Models: Research utilizing 100 features from transplant patients developed a KNN model that demonstrated high calibration for predicted probabilities [68].
  • Volatile Organic Compound (VOC) Analysis: VOCs from bronchial aspirates serve as biomarkers for PGD. AI algorithms, specifically support vector machines (SVM), perform high-dimensional data transformation to select key indicators. By narrowing 386 variables to 20 key VOC indicators, the model achieved an accuracy of 83% and an AUROC of 90% in predicting severe PGD within six hours post-transplant [68].

13. Conclusion

The advancement of Donation after Circulatory Death (DCD) lung transplantation marks a significant step forward in addressing the critical organ shortage faced globally. As traditional donor sources dwindle, DCD lungs present a viable and increasingly accepted alternative, with outcomes that are comparable to those from brain-dead donors. The application of advanced machine perfusion techniques, such as Normothermic Regional Perfusion (NRP) and Ex Vivo Lung Perfusion (EVLP), plays a pivotal role in mitigating the negative effects of warm ischemia and enhancing the preservation of lung function. By maintaining physiological conditions during the critical phases of organ procurement, these methods optimize metabolic activity and improve graft viability.

As we look to the future, the continued refinement of machine perfusion protocols, alongside the integration of innovative technologies and therapeutic strategies, will be essential in further enhancing the outcomes of DCD lung transplantation. Ongoing research should focus on developing personalized perfusion solutions, utilizing artificial intelligence for better decision-making during organ selection and assessment, and exploring gene therapies to enhance donor organ resilience. Additionally, studies examining the long-term impacts of these techniques on patient survival and graft function will provide valuable insights into best practices and establish new standards of care.

Author Contributions

Dr. Chawannuch Ruaengsri: Responsible for project development and the overall write-up of the content. Dr. Marc Leon: Contributed to the writing of the content, providing valuable insights and expertise that helped to shape the final document. Miguel Alvarez-Cortes: Assisted with picture editing, ensuring that all visual elements were accurately represented and aligned with the article's goals. Manuel Quiroz-Flores: Also contributed to picture editing, enhancing the visual presentation of the work. Yasuhiro Shudo: Supervised the project, overseeing the overall progress and ensuring that all aspects of the research were conducted effectively and efficiently.

Competing Interests

The authors declare that they have no conflicts of interest related to this study.

AI-Assisted Technologies Statement

Open AI’s ChatGPT, were used solely for basic grammar correction and language refinement in this manuscript. All scientific content, data interpretation, and conclusion were independently developed by the authors. The authors reviewed the AI-assisted text to ensure accuracy and accept full responsibility for the content.

References

  1. Valapour M, Lehr CJ, Skeans MA, Smith JM, Uccellini K, Lehman R, et al. OPTN/SRTR 2017 annual data report: Lung. Am J Transplant. 2019; 19: 404-484. [CrossRef] [Google scholar]
  2. Nakata K, Alderete IS, Hughes BA, Hartwig MG. Ex vivo lung perfusion: Recent advancements and future directions. Front Immunol. 2025; 16: 1513546. [CrossRef] [Google scholar]
  3. Tao JQ, Sorokina EM, Medina JV, Mishra MK, Yamada Y, Satalin J, et al. Onset of inflammation with ischemia: Implications for donor lung preservation and transplant survival. Am J Transplant. 2016; 16: 2598-2611. [CrossRef] [Google scholar]
  4. Vidgren M, Delorme C, Oniscu GC. Challenges and opportunities in organ donation after circulatory death. J Intern Med. 2025; 297: 124-140. [CrossRef] [Google scholar]
  5. Murphy NB, Slessarev M, Basmaji J, Blackstock L, Blaszak M, Brahmania M, et al. Ethical issues in normothermic regional perfusion in controlled organ donation after determination of death by circulatory criteria: A scoping review. Transplantation. 2025; 109: 597-609. [CrossRef] [Google scholar]
  6. Hardy JD, Webb WR, Dalton ML, Walker GR. Lung homotransplantation in man: Report of the initial case. JAMA. 1963; 186: 1065-1074. [CrossRef] [Google scholar]
  7. Egan TM, Kaiser LR, Cooper JD. Lung transplantation. Curr Probl Surg. 1989; 26: 673-751. [CrossRef] [Google scholar]
  8. Lewis A. The uniform determination of death act is being revised. Neurocrit Care. 2022; 36: 335-338. [CrossRef] [Google scholar]
  9. Sade RM. Brain death, cardiac death, and the dead donor rule. J S C Med Assoc. 2011; 107: 146-149. [Google scholar]
  10. Bello I, Palleschi A, Cypel M, Argudo E, Sandiumenge A. Unlocking the potential of uncontrolled dcd in lung transplantation: A review of two decades of experience. JHLT Open. 2025; 10: 100374. [CrossRef] [Google scholar]
  11. Love RB, D’Allesandro AM, Cornwell RA, Meyer KM. Ten-year experience with human lung transplantation from non-heart beating donors. J Heart Lung Transplant. 2003; 22: S87. [CrossRef] [Google scholar]
  12. Moreno P, González-García J, Ruíz-López E, Alvarez A. Lung transplantation in controlled donation after circulatory-determination-of-death using normothermic abdominal perfusion. Transpl Int. 2024; 37: 12659. [CrossRef] [Google scholar]
  13. Thuong M, Ruiz A, Evrard P, Kuiper M, Boffa C, Akhtar MZ, et al. New classification of donation after circulatory death donors definitions and terminology. Transpl Int. 2016; 29: 749-759. [CrossRef] [Google scholar]
  14. Morrison LJ, Sandroni C, Grunau B, Parr M, Macneil F, Perkins GD, et al. Organ donation after out-of-hospital cardiac arrest: A scientific statement from the international liaison committee on resuscitation. Circulation. 2023; 148: e120-e146. [CrossRef] [Google scholar]
  15. Egan TM, Lambert Jr CJ, Reddick R, Ulicny Jr KS, Keagy BA, Wilcox BR. A strategy to increase the donor pool: Use of cadaver lungs for transplantation. Ann Thorac Surg. 1991; 52: 1113-1121. [CrossRef] [Google scholar]
  16. Van Raemdonck DE, Jannis NC, De Leyn PR, Flameng WJ, Lerut TE. Warm ischemic tolerance in collapsed pulmonary grafts is limited to 1 hour. Ann Surg. 1998; 228: 788-796. [CrossRef] [Google scholar]
  17. Van Raemdonck DE, Jannis NC, Rega FR, De Leyn PR, Flameng WJ, Lerut TE. Extended preservation of ischemic pulmonary graft by postmortem alveolar expansion. Ann Thorac Surg. 1997; 64: 801-808. [CrossRef] [Google scholar]
  18. de Perrot M, Liu M, Waddell TK, Keshavjee S. Ischemia-reperfusion-induced lung injury. Am J Respir Crit Care Med. 2003; 167: 490-511. [CrossRef] [Google scholar]
  19. Chen-Yoshikawa TF. Ischemia-reperfusion injury in lung transplantation. Cells. 2021; 10: 1333. [CrossRef] [Google scholar]
  20. Tremblay LN, Yamashiro T, DeCampos KN, Mestrinho BV, Slutsky AS, Todd TR, et al. Effect of hypotension preceding death on the function of lungs from donors with nonbeating hearts. J Heart Lung Transplant. 1996; 15: 260-268. [Google scholar]
  21. Van De Wauwer C, Neyrinck AP, Geudens N, Rega FR, Verleden GM, Lerut TE, et al. The mode of death in the non-heart-beating donor has an impact on lung graft quality. Eur J Cardiothorac Surg. 2009; 36: 919-926. [CrossRef] [Google scholar]
  22. Thiessen C, Wisel SA, Roll GR. Simultaneous thoracic and abdominal donation after circulatory death organ recovery: The abdominal surgeon's perspective. Curr Opin Organ Transplant. 2023; 28: 139-144. [CrossRef] [Google scholar]
  23. Zanierato M, Dondossola D, Palleschi A, Zanella A. Donation after circulatory death: Possible strategies for in-situ organ preservation. Minerva Anestesiol. 2020; 86: 984-991. [CrossRef] [Google scholar]
  24. Whitson BA, Shukrallah B, Mulligan MS, D’Cunha J, Daneshmand M, Wozniak T, et al. Ex-vivo lung perfusion in donation after circulatory death lung transplantation increases donor utilization: Analysis of the NOVEL extension trial. J Heart Lung Transplant. 2018; 37: S147-S148. [CrossRef] [Google scholar]
  25. Sanchez PG, Chan EG, Davis RD, Hartwig M, Machuca T, Whitson B, et al. Normothermic ex vivo lung perfusion (novel) as an assessment of extended criteria donor lungs: A prospective multi-center clinical trial. J Heart Lung Transplant. 2022; 41: S40-S41. [CrossRef] [Google scholar]
  26. Gorton AJ, Mohammadi DK, Malik MJ, Keshavamurthy S. Normothermic regional perfusion for donation after circulatory death in lung transplantation. Front Cardiovasc Med. 2025; 12: 1716890. [CrossRef] [Google scholar]
  27. Chandra R, Hauptmann E, Keshavamurthy S. Lung transplantation in the era of normothermic regional perfusion in donation after cardiac death: A review. Curr Chall Thorac Surg. 2025; 7: 9. doi: 10.21037/ccts-24-42. [CrossRef] [Google scholar]
  28. Alderete IS, Pontula A, Halpern SE, Patel KJ, Klapper JA, Hartwig MG. Thoracoabdominal normothermic regional perfusion and donation after circulatory death lung use. JAMA Netw Open. 2025; 8: e2460033. [CrossRef] [Google scholar]
  29. Miñambres E, Royo-Villanova M, Domínguez-Gil B. Normothermic regional perfusion provides a great opportunity to maximize organ procurement in donation after the circulatory determination of death. Crit Care Med. 2022; 50: 1649-1653. [CrossRef] [Google scholar]
  30. Watanabe T, Cypel M, Keshavjee S. Ex vivo lung perfusion. J Thorac Dis. 2021; 13: 6602-6617. [CrossRef] [Google scholar]
  31. Mody S, Nadkarni S, Vats S, Kumar A, Nandavaram S, Keshavamurthy S. Lung donor selection and management: An updated review. OBM Transplant. 2023; 7: 203. [CrossRef] [Google scholar]
  32. Sellers MT, Strom C, Clapper DC, Hasz RD, Edwards JM. Organ procurement organization-based normothermic regional perfusion in the US: Current state and future direction. Curr Transpl Rep. 2025; 12: 14. [CrossRef] [Google scholar]
  33. Trindade AJ, Demarest CT, Stokes JW, Thomas M, Makey I, Bacchetta M, et al. Outcomes associated with remote, centralized ex vivo lung perfusion (rc-EVLP) for donor lungs in a real-world setting. JTCVS Open. 2025; 26: 292-298. [CrossRef] [Google scholar]
  34. Kukreja J, Van Raemdonck D, Cantu E, Date H, D’Ovidio F, Hartwig M, et al. The 2024 American association for thoracic surgery expert consensus document: Current standards in donor lung procurement and preservation. J Thorac Cardiovasc Surg. 2025; 169: 484-504. [CrossRef] [Google scholar]
  35. Magee JC. Ensuring Safety and Reliability in Normothermic Regional Perfusion Protocols – A Message to the OPTN Community [Internet]. Atlanta, GA: Organ Donation and Transplantation Alliance; 2025. Available from: https://www.organdonationalliance.org/article/ensuring-safety-and-reliability-in-normothermic-regional-perfusion-protocols/.
  36. Domínguez-Gil B, Ascher N, Capron AM, Gardiner D, Manara AR, Bernat JL, et al. Expanding controlled donation after the circulatory determination of death: Statement from an international collaborative. Intensive Care Med. 2021; 47: 265-281. [CrossRef] [Google scholar]
  37. Ruaengsri C. First En-Bloc Heart and Lung Rapid Recovery combined with Abdominal Normothermic Regional Perfusion Donation After Circulatory Death Procurement [Internet]. Fairfax, VA: The American Association for Thoracic Surgery; 2025. Available from: https://www.aats.org/resources/first-en-bloc-heart-and-lung-r-10903.
  38. Ruaengsri C, Leon M, Quiroz-Flores M. En Bloc Heart and Lung Rapid Recovery Combined with Abdominal Normothermic Regional Perfusion Donation After Circulatory Death [Internet]. Chicago, IL: CTSNet, Inc.; 2025. Available from: https://www.ctsnet.org/article/en-bloc-heart-and-lung-rapid-recovery-combined-abdominal-normothermic-regional-perfusion.
  39. Cain MT, Park SY, Schäfer M, Hay-Arthur E, Justison GA, Zhan QP, et al. Lung recovery utilizing thoracoabdominal normothermic regional perfusion during donation after circulatory death: The Colorado experience. JTCVS Tech. 2023; 22: 350-358. [CrossRef] [Google scholar]
  40. Hoffman JR, Hartwig MG, Cain MT, Rove JY, Siddique A, Urban M, et al. Consensus statement: Technical standards for thoracoabdominal normothermic regional perfusion. Ann Thorac Surg. 2024; 118: 778-791. [CrossRef] [Google scholar]
  41. Bashian EJ, Gergen AK, Park SY, Cain MT, Hoffman JR, Campbell D. A novel technique for innominate artery cannulation in thoracoabdominal normothermic regional perfusion. JTCVS Tech. 2025; 29: 94-96. [CrossRef] [Google scholar]
  42. Tanaka S, Luis Campo-Cañaveral de la Cruz J, Crowley Carrasco S, Romero Román A, Hoyos Mejía L, Manuel NaranjoGómez J, et al. Effect on the donor lungs of using abdominal normothermic regional perfusion in controlled donation after circulatory death. Eur J Cardiothorac Surg. 2020; ezaa398. doi: 10.1093/ejcts/ezaa398. [CrossRef] [Google scholar]
  43. Mora V, Ballesteros MA, Naranjo S, Sánchez L, Suberviola B, Iturbe D, et al. Lung transplantation from controlled donation after circulatory death using simultaneous abdominal normothermic regional perfusion: A single center experience. Am J Transplant. 2022; 22: 1852-1860. [CrossRef] [Google scholar]
  44. Campo-Cañaveral de la Cruz JL, Miñambres E, Coll E, Padilla M, Antolín GS, de la Rosa G, et al. Outcomes of lung and liver transplantation after simultaneous recovery using abdominal normothermic regional perfusion in donors after the circulatory determination of death versus donors after brain death. Am J Transplant. 2023; 23: 996-1008. [CrossRef] [Google scholar]
  45. Spencer PJ, Saddoughi SA, Choi K, Dickinson TA, Richman A, Reynolds FA, et al. Heart-lung transplantation from donation after circulatory death using mobile normothermic regional perfusion. ASAIO J. 2024; 70: e13-e15. [CrossRef] [Google scholar]
  46. Schwarz S, Gökler J, Moayedifar R, Atteneder C, Bocchialini G, Benazzo A, et al. Prioritizing direct heart procurement in organ donors after circulatory death does not jeopardize lung transplant outcomes. JTCVS Tech. 2022; 16: 182-195. [CrossRef] [Google scholar]
  47. Gao Q, Pontula A, Alderete IS, DeLaura I, Kahan R, Nakata K, et al. Impact of simultaneous heart procurement on outcomes of donation after circulatory death lung transplantation. Am J Transplant. 2024; 24: 79-88. [CrossRef] [Google scholar]
  48. Zhou AL, Ruck JM, Casillan AJ, Larson EL, Shou BL, Karius AK, et al. Early United States experience with lung donation after circulatory death using thoracoabdominal normothermic regional perfusion. J Heart Lung Transplant. 2023; 42: 693-696. [CrossRef] [Google scholar]
  49. Ribeiro RV, Reynolds FA, Sarrafian TL, Spadaccio C, Colby C, Richman A, et al. Impact of normothermic regional perfusion during DCD recovery on lung allograft function: A preclinical study. JHLT Open. 2023; 2: 100009. [CrossRef] [Google scholar]
  50. Cenik I, Van Slambrouck J, Provoost AL, Barbarossa A, Vanluyten C, Boelhouwer C, et al. Controlled hypothermic storage for lung preservation: Leaving the ice age behind. Transpl Int. 2024; 37: 12601. [CrossRef] [Google scholar]
  51. Ali A, Wang A, Ribeiro RV, Beroncal EL, Baciu C, Galasso M, et al. Static lung storage at 10°C maintains mitochondrial health and preserves donor organ function. Sci Transl Med. 2021; 13: eabf7601. [CrossRef] [Google scholar]
  52. Ali A, Hoetzenecker K, Luis Campo-Cañaveral de la Cruz J, Schwarz S, Barturen MG, Tomlinson G, et al. Extension of cold static donor lung preservation at 10°C. NEJM Evid. 2023; 2: EVIDoa2300008. [CrossRef] [Google scholar]
  53. Haney J, Hartwig M, Langer N, Sanchez P, Bush E. (68) Not too warm, not too cold: Real-world multi-center outcomes with elevated hypothermic preservation of donor lungs. J Heart Lung Transpl. 2023; 42: S39-S40. [CrossRef] [Google scholar]
  54. Bobba CM, Whitson BA, Henn MC, Mokadam NA, Keller BC, Rosenheck J, et al. Trends in donation after circulatory death in lung transplantation in the United States: Impact of era. Transpl Int. 2022; 35: 10172. [CrossRef] [Google scholar]
  55. Singh TP, Cherikh WS, Hsich E, Lewis A, Perch M, Kian S, et al. Graft survival in primary thoracic organ transplant recipients: A special report from the international thoracic organ transplant registry of the international society for heart and lung transplantation. J Heart Lung Transpl. 2023; 42: 1321-1333. [CrossRef] [Google scholar]
  56. Amarelli C, Bello I, Aigner C, Berman M, Boffini M, Clark S, et al. European society of organ transplantation (ESOT) consensus statement on machine perfusion in cardiothoracic transplant. Transpl Int. 2024; 37: 13112. [CrossRef] [Google scholar]
  57. Lepoittevin M, Giraud S, Kerforne T, Barrou B, Badet L, Bucur P, et al. Preservation of organs to be transplanted: An essential step in the transplant process. Int J Mol Sci. 2022; 23: 4989. [CrossRef] [Google scholar]
  58. Steen S, Ingemansson R, Eriksson L, Pierre L, Algotsson L, Wierup P, et al. First human transplantation of a nonacceptable donor lung after reconditioning ex vivo. Ann Thorac Surg. 2007; 83: 2191-2194. [CrossRef] [Google scholar]
  59. Ragheb DK, Elgharably H, Ayyat KS. A narrative review on ex vivo lung perfusion: Up-to-date role in lung transplantation. Curr Chall Thorac Surg. 2025; 7: 2. doi: 10.21037/ccts-24-34. [CrossRef] [Google scholar]
  60. Menander M, Attawar S, Mahesh BN, Tisekar O, Mohandas A. Ex vivo lung perfusion and the organ care system: A review. Clin Transpl Res. 2024; 38: 23-36. [CrossRef] [Google scholar]
  61. Machuca TN, Mercier O, Collaud S, Tikkanen J, Krueger T, Yeung JC, et al. Lung transplantation with donation after circulatory determination of death donors and the impact of ex vivo lung perfusion. Am J Transpl. 2015; 15: 993-1002. [CrossRef] [Google scholar]
  62. Lightle W, Daoud D, Loor G. Breathing lung transplantation with the Organ Care System (OCS) lung: Lessons learned and future implications. J Thorac Dis. 2019; 11: S1755-S1760. [CrossRef] [Google scholar]
  63. Sabashnikov A, Zeriouh M, Mohite PN, Patil NP, García-Sáez D, Schmack B, et al. Moving back to the future: Use of organ care system lung for lobectomy before lobar lung transplantation. Med Sci Monit Basic Res. 2016; 22: 70-74. [CrossRef] [Google scholar]
  64. Loor G, Warnecke G, Villavicencio MA, Smith MA, Kukreja J, Ardehali A, et al. Portable normothermic ex-vivo lung perfusion, ventilation, and functional assessment with the Organ Care System on donor lung use for transplantation from extended-criteria donors (EXPAND): A single-arm, pivotal trial. Lancet Respir Med. 2019; 7: 975-984. [CrossRef] [Google scholar]
  65. Loor G, Warnecke G, Villavicencio MA, Smith MA, Kukreja J, Ardehali A, et al. Long-term results of the OCS Lung EXPAND international trial using Organ Care System Lung Perfusion System (OCS) in extended-criteria donor (ECD) and donation after circulatory death (DCD) donor lungs. J Heart Lung Transplant. 2022; 41: S43. [CrossRef] [Google scholar]
  66. Liu X, Chen W, Du W, Li P, Wang X. Application of artificial intelligence and machine learning in lung transplantation: A comprehensive review. Front Digit Health. 2025; 7: 1583490. [CrossRef] [Google scholar]
  67. Sage AT, Donahoe LL, Shamandy AA, Mousavi SH, Chao BT, Zhou X, et al. A machine-learning approach to human ex vivo lung perfusion predicts transplantation outcomes and promotes organ utilization. Nat Commun. 2023; 14: 4810. [CrossRef] [Google scholar]
  68. Ronen L, Keshavjee S, Sage AT. Advancing lung transplantation through machine learning and artificial intelligence. Curr Opin Pulm Med. 2025; 31: 381-386. [CrossRef] [Google scholar]
  69. Ram S, Verleden SE, Kumar M, Bell AJ, Pal R, Ordies S, et al. CT-based machine learning for donor lung screening prior to transplantation. medRxiv. 2023. doi: 10.1101/2023.03.28.23287705. [CrossRef] [Google scholar]
  70. Ma W, Oh I, Luo Y, Kumar S, Gupta A, Lai AM, et al. Developing approaches to incorporate donor-lung computed tomography images into machine learning models to predict severe primary graft dysfunction after lung transplantation. Am J Transpl. 2025; 25: 1339-1349. [CrossRef] [Google scholar]
  71. Yanagawa R, Iwadoh K, Nakayama T, Firl DJ, Wehrle CJ, Bekki Y, et al. Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA: A multicentre study. Lancet Digit Health. 2025; 7: 100918. [CrossRef] [Google scholar]
  72. Duncheskie RP, Al Omari O, Anjum F. Role of artificial intelligence in lung transplantation: Current state, challenges, and future directions. Transplant Proc. 2025; 57: 1621-1626. [CrossRef] [Google scholar]
  73. Liu M, Xi L, Luo C, Li X, Yang C, Peng G, et al. Maximizing lung transplant donor utilization: Developing a lobar donor repository guided by chest computed tomography visual scoring. Interdiscip Cardiovasc Thorac Surg. 2025; ivaf300. doi: 10.1093/icvts/ivaf300. [CrossRef] [Google scholar]
  74. Magar BT, Rahman MA, Saha PK, Ahmad M, Rashid MA, Higa H. Development of a CNN-based decision support system for lung disease diagnosis using chest radiographs. AIP Adv. 2025; 15: 035052. [CrossRef] [Google scholar]
  75. Cypel M, Rubacha M, Yeung J, Hirayama S, Torbicki K, Madonik M, et al. Normothermic ex vivo perfusion prevents lung injury compared to extended cold preservation for transplantation. Am J Transplant. 2009; 9: 2262-2269. [CrossRef] [Google scholar]
  76. Sage A, Keshavjee S, Wang B. Increasing Transplant Rates with AI [Internet]. Toronto, ON: UHN Foundation; 2023. Available from: https://uhnfoundation.ca/stories/increasing-transplant-rates-with-ai/.
  77. Sage AT, Shamandy AA, Mousavi SH, Chao BT, Nitski O, Zhou X, et al. InsighTx: A machine-learning model that accurately predicts transplant outcomes during ex vivo lung perfusion. J Heart Lung Transplant. 2022; 41: S15. [CrossRef] [Google scholar]
  78. Wang A, Ali A, Keshavjee S, Liu M, Cypel M. Ex vivo lung perfusion for donor lung assessment and repair: A review of translational interspecies models. Am J Physiol Lung Cell Mol Physiol. 2020; 319: L932-L940. [CrossRef] [Google scholar]
  79. Sangeetha G, Vasan KJ, Subash M, Venu Krishnan S. AI-enhanced lung size matching and eligibility system. Int J Innov Sci Res Technol. 2025; 10: 530-535. [CrossRef] [Google scholar]
  80. Schinstock E, Deakyne A, Iles T, Shaffer A, Iaizzo PA. Lung allocation pipeline: Machine learning approach to optimized lung transplant. Proceedings of the 2020 Design of Medical Devices Conference; 2020 April 6-9; Minneapolis, MN, USA. New York, NY: ASME. [CrossRef] [Google scholar]
  81. Poo-Fernández C, Iturbe-Fernández D, Tello-Mena S, Izquierdo-Cuervo S, Sánchez-Moreno L, Murillo-Brito DA, et al. The impact of donor-recipient size mismatch on lung transplant outcomes. J Thorac Dis. 2025; 17: 4621-4632. [CrossRef] [Google scholar]
  82. Ismail MK, Araki T, Gefter WB, Suzuki Y, Raevsky A, Saleh A, et al. Artificial intelligence-driven automated lung sizing from chest radiographs. Am J Transplant. 2025; 25: 198-203. [CrossRef] [Google scholar]
  83. Mason DP, Batizy LH, Wu J, Nowicki ER, Murthy SC, McNeill AM, et al. Matching donor to recipient in lung transplantation: How much does size matter? J Thorac Cardiovasc Surg. 2009; 137: 1234-1240.e1. [CrossRef] [Google scholar]
  84. Daniëls L, Beeckmans H, Zajacova A, Kerckhof P, Bos S, Naesens M, et al. The clinical significance of HLA compatibility scores in lung transplantation. Transpl Int. 2025; 37: 13484. [CrossRef] [Google scholar]
  85. Gholamzadeh M, Abtahi H, Safdari R. Machine learning-based techniques to improve lung transplantation outcomes and complications: A systematic review. BMC Med Res Methodol. 2022; 22: 331. [CrossRef] [Google scholar]
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