X-ray Dark-Field Imaging Shows Potential for Diagnostic Assessment of Lungs


X-ray dark-field chest imaging may generate detailed imaging of lungs without interference from surrounding tissue or influence by characteristics such as age, gender or weight.

X-ray dark-field imaging has potential for diagnostic assessment of lungs, according to a recent study in Germany that described the qualitative and quantitative characteristics of the images in healthy patients.

The study, published in Radiology, describes the appearance and quantitative features of X-ray dark-field images in healthy humans. It included 40 participants, 26 men and 14 women, with an average age of 62 years, average weight of 172 pounds and average height of 5-foot, 6 inches.

“The research over the last years has now culminated in the construction of a human-size patient scanner for lung imaging,” Florian T. Gassert, MD, B.Sc., radiologist-in-training in the Department of Diagnostic and Interventional Radiology at the School of Medicine & Klinikum Rechts der Isar at Technical University of Munich, told Diagnostic Imaging. “The method allows the assessment of the alveolar structure of healthy patients. In our small cohort we did not find (significant) differences in dark-field signal for height, weight, sex and age.”

The experimental approach, introduced in 2008, takes advantage of wave properties of X-rays, creating an image contrast that is different from and complementary to traditional X-ray imaging.

Chest radiography is the most frequently ordered imaging test, Hiroto Hatabu, MD, PhD, professor of radiology at Harvard Medical School and medical director of the Center for Pulmonary Functional Imaging in the Radiology Department at Brigham and Women’s Hospital, and Bruno Madore, BSc, PhD, associate professor at Harvard Medical School, Brigham and Women’s Hospital, noted in a related editorial.

They said dark-field X-ray imaging “appears to be especially well-suited for chest applications. The alveolar structure of the lungs, with its multitude of water-air transitions, is a main contributor to the type of small-angle scattering effects detected with dark-field X-ray imaging.”

Gassert said, “X-ray dark-field imaging adds to the currently existing methods of lung imaging: it is a low-radiation functional imaging alternative to CT providing information on the ventilation situation of the lung.”

Because bone structures and soft tissue generate minimal dark-field signal, the method allows for detailed imaging of lung tissue without interference from surrounding material.

Gassert said the investigators were surprised by how well the scanner performed.

“Even in the human scale we found only very low artifacts from beam-hardening and breathing,” he said.

The study found that the average dark-field signal was 2.5 m−1 ± 0.4 of examined lung tissue. The quantitative X-ray dark-field coefficient based on the total dark-field signal and lung size is independent from the individual characteristics such as sex (P = .78), age (r = –0.18, P = .26), weight (r = 0.24, P = .13), and height (r = 0.01, P = .96). The study demonstrated that the dark-field signal is subject only to the patient’s lung condition, correlating with lung volume (r = 0.61, P < .001). Alveolar density can be estimated from dark-field images, with differences expected between health subjects and those with lung impairments.

“The technique needs to be further evaluated, both in larger cohorts of healthy humans, but also and especially in patients with pulmonary pathologies,” Gassert said. “In this respect, especially lung diseases interfering with the integrity of the alveolar structure are of interest, such as COPD and pneumonia but also tumors and pneumothorax.”

The study builds on previous research in animal models and ex vivo studies that have demonstrated benefits of X-ray dark-field imaging for diagnosis of such impairments as pulmonary fibrosis, acute lung inflammation, lung cancer in mice, radiation-induced lung damage and pulmonary emphysema.

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