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X-ray Dark-Field Chest Imaging: Qualitative and Quantitative Results in Healthy Humans
Florian T Gassert1, Theresa Urban1, Manuela Frank1
1From the Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum Rechts der Isar, Technical University of Munich, Ismaningerstr 22, 81675 Munich, Germany (F.T.G., A.A.F., A.P.S., M.R.M., D.P., F.P.); Department of Physics and Munich School of BioEngineering, Technical University of Munich, Garching, Germany (T.U., M.F., K.W., W.N., P.B., R.S., F.P.); and Philips Research, Hamburg, Germany (T.K., J.v.B.).
X-ray dark-field imaging reveals high signal in healthy lungs due to air-tissue interfaces. This quantitative method shows potential for lung diagnostics, independent of demographic factors.
Area of Science:
- Medical Imaging
- Radiography
- Pulmonology
Background:
- X-ray dark-field radiography leverages X-ray wave properties.
- High signal is observed in lung alveoli due to numerous air-tissue interfaces.
Purpose of the Study:
- To characterize X-ray dark-field images qualitatively and quantitatively in healthy individuals.
- Establish baseline values for X-ray dark-field imaging in pulmonary assessment.
Main Methods:
- Utilized a clinical X-ray dark-field prototype to acquire simultaneous attenuation-based and dark-field thorax radiographs.
- Correlated total dark-field signal with lung volume and the dark-field coefficient with demographic parameters (age, sex, weight, height).
- Included 40 healthy adult subjects with normal chest CT scans.
Main Results:
- Normal lungs exhibit a high dark-field signal (average 2.5 m-1 ± 0.4), while surrounding tissues show minimal to no signal.
- A significant correlation was found between total dark-field signal and lung volume (r = 0.61, P < .001).
- The dark-field coefficient was independent of sex, age, weight, and height.
Conclusions:
- This study provides normative qualitative and quantitative data for X-ray dark-field imaging in healthy lungs.
- The dark-field coefficient's independence from demographic factors highlights its diagnostic potential for lung conditions.
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