An MRI technique that needs no contrast and no radiation is proving able to reveal disrupted blood flow in the lungs across a wide range of respiratory diseases. The finding comes from a new study reinforcing the potential of functional lung MRI as a sensitive, noninvasive tool for assessing how the organ works.
What the study found
Led by Tao Ouyang, MD, PhD, of Capital Medical University in Beijing, the research was published on June 4 in Radiology: Cardiothoracic Imaging. The work assessed 287 patients who underwent spirometry — the standard test for measuring lung function — between March 2023 and July 2024.
The core finding: impaired lung function is independently associated with an increase in perfusion defects detected by MRI. In other words, the worse the lung function, the higher the proportion of regions with deficient blood flow. Airflow obstruction — a hallmark of diseases such as COPD and asthma — carried the greatest weight, though the abnormalities also appeared in other types of impairment.
In practice, PREFUL translates these findings into objective indices, such as the perfusion defect percentage and the ventilation defect percentage — essentially the fraction of the lung where blood or air fail to reach properly. These numbers make it possible to compare exams over time and to quantify disease progression or response to treatment.
How the PREFUL technique works
PREFUL stands for phase-resolved functional lung MRI. Unlike ventilation-perfusion scintigraphy, which uses radiotracers, or gadolinium-based perfusion imaging, PREFUL uses neither contrast nor ionizing radiation.
The technique acquires fast lung images while the patient breathes normally — with no need to hold their breath. From the small, periodic signal changes caused by the respiratory cycle and cardiac pulsation, algorithms reconstruct regional maps of ventilation and perfusion. The result is a kind of functional V/Q map obtained from water protons alone, in a free-breathing exam.
Conceptually, PREFUL builds on Fourier-decomposition methods: by tracking how the MR signal in each voxel rises and falls with breathing and the heartbeat, software separates the ventilation component from the perfusion component. No breath-holding is required, which is a major advantage for sick or pediatric patients who struggle to hold still or to suspend respiration on command.
Why it matters in clinical practice
The big draw is combining functional information with the absence of contrast and radiation. That makes PREFUL especially appealing for the longitudinal follow-up of chronic diseases, where patients must repeat exams many times over years — patients with COPD, asthma, cystic fibrosis or interstitial disease, plus post-lung-transplant monitoring.
It is worth comparing with current alternatives. V/Q scintigraphy exposes the patient to radiotracers and has limited spatial resolution; CT or gadolinium-enhanced MRI perfusion requires contrast, which is not always advisable in patients with impaired kidney function. PREFUL sidesteps both obstacles, which is particularly valuable in children, pregnant patients and those who need frequent reassessment throughout treatment.
Regional assessment is another advantage. While spirometry delivers a single global number for the whole lung, functional MRI shows where the impaired regions are, which can guide management and the interpretation of other imaging studies. It is no accident that chest imaging keeps gaining layers of sophistication, as we discussed when covering AI analysis of chest X-rays.
Limitations and caveats
Like any study, this one comes with caveats. It is single-center research, with a design that establishes associations rather than direct cause and effect. The results need confirmation in larger, more diverse populations, with protocols standardized across sites. The robustness of the reconstruction algorithms itself depends on acquisition quality and on patients able to cooperate at least minimally with the exam.
Even so, the study adds to a growing body of evidence that PREFUL may have a meaningful role in pulmonary assessment. Earlier research has already explored the technique in monitoring cystic fibrosis, COPD and even post-COVID sequelae, pointing to a path of clinical maturation.
Availability is another practical consideration. PREFUL runs on standard MRI hardware and does not require specialized hyperpolarized gases, but it does demand dedicated post-processing software and expertise that not every center has today. Wider adoption will hinge on vendor support, reproducibility across scanners and clear evidence that the functional information actually changes patient management.
Outlook and context
For radiology, functional lung MRI is an expanding frontier. The lung has always been a difficult organ for MRI, because it contains little proton signal and a great deal of air — hence the historical dominance of computed tomography in the chest. Techniques like PREFUL help turn that around, adding functional information without adding radiation dose to the patient. As artificial intelligence becomes embedded in chest-imaging workflows — a trend also visible in AI-supported lung cancer screening — functional maps like PREFUL’s are likely to increasingly complement anatomy, offering a fuller portrait of respiratory health.
Source: AuntMinnie
