Libertario Demi – libertario.demi@unitn.it
Department of Information Engineering and Computer Science
University of Trento, Italy
Popular version of paper 1pBA4
Presented Monday morning, May 13, 2019
177th ASA Meeting, Louisville, KY
Lung diseases have a large impact worldwide. Chronic Obstructive Pulmonary Diseases (COPD) and lower respiratory infections are respectively the third and fourth leading cause of death in the world, and are responsible for six million deaths per year [1]. Pneumonia, an inflammatory condition of the lung, is the leading cause of death in children under five years of age and responsible for approximately 1 million deaths per year. The economical burden is also significant. Considering only COPD, in the United States of America, the sum of indirect and direct healthcare costs is estimated to be in the order of 50 billion dollars [2].
Cost effective and largely available solutions for the diagnosis and monitoring of lung diseases would be of tremendous help, and this is exactly the role that could be played by ultrasound (US) technologies.
Compared to the current standard, i.e., X-ray based imaging technologies like a CT-scan, US tech is in fact safe, transportable, and cost-effective. Firstly, being an ionizing-radiation-free modality, US is a diagnostic option especially relevant to children, pregnant women and patients subjected to repeated investigations. Secondly, US devices are easily transportable to patient’s site, also in remote and rural areas, and developing countries. Thirdly, devices and examinations are significantly cheaper as compared to CT or MRI, making US tech accessible to a much broader range of facilities, thus reaching more patients.
However, this large potential is today underused. The examination of the lung is in fact performed with US equipment conceptually unsuitable to this task. Standard US scanners and probes have been designed to visualize body parts (hart, liver, mother’s womb, the abdomen) for which the speed of sound can be assumed to be constant. This is clearly not the case for the lung, due to presence of air. As a consequence, it is impossible to correctly visualize the anatomy of the lung beyond its surface and, in most conditions, the only usable products of standard US equipment are images that display “signs”.
These signs are called imaging artifacts, i.e., objects that are present in the image but which are not physically present in the lung (see example in the Figures). These artifacts, for most of which we still do not know why exactly they appear in the images, carry diagnostic information and are currently used in the clinics, but can obviously only lead to qualitative and subjective analysis.
Example of standard ultrasound images with different artifacts: A-line artifacts, left, are generally associated with a healthy lung, while B-lines, on the right, correlate with different pathological conditions of the lung. The arrows on top indicate the location of the lung surface in the image, visualized as a bright horizontal line. Beyond this depth the capability of these images to provide an anatomical description of the lung is lost.
Moreover, their appearance in the image largely depends on the user and on the equipment. Clearly, there is much more that we can do. Can we correctly (see) visualize what we (hear) receive from the lung after insonification? Can we re-conceive US tech in order to adapt it to the specific properties of the lung?
Can we develop an ultrasound-based method which can support, in real time, the clinician in the diagnosis of the many different pathologies affecting the lung? In this talk, trying to answer to these questions, recently developed imaging modalities and signal processing techniques dedicated to the analysis of the lung response to ultrasound will be introduced and discussed. In particular, in-vitro and clinical data will be presented which show how the study of the ultrasound spectral features [3] could lead to a quantitative ultrasound method dedicated to the lung.
[1] Global Health Estimates 2016: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2016. Geneva, World Health Organization; 2018.
[2] The clinical and economic burden of chronic obstructive pulmonary disease in the USA, A.J. Guarascio et al. Clinicoecon Outcomes Res, 2013.
[3] Determination of a potential quantitative measure of the state of the lung using lung ultrasound spectroscopy. L. Demi et al. Scientific Reports, 2017.