Smoke-measuring smart shirts, breath sound analyzing algorithms, and smart inhalers pave the way of pulmonology and respiratory care into the future. As the number of patients suffering from asthma, COPD, or lung cancer due to rising air pollution and steady smoker-levels will unfortunately not decrease any time soon, we looked around what technology can do to help both patients and caregivers. The results are breathtaking.
Attacks of breathlessness are too common
The diseases which pulmonologists and respiratory care specialists attempt to fight are among the most common conditions in the modern world – and the numbers of sufferers are just aggravating.According to WHO estimates, 235 million people suffer from asthma, the chronic disease characterized by recurrent attacks of breathlessness and wheezing. About 300,000 new patients are diagnosed with asthma annually, and nearly 250,000 people die prematurely each year due to the condition. For adults,this chronic disease is one of the top reasons for underperformance at work. Sufferers miss about14 million workdayseach year, and this equals about 2 billion dollars of indirect asthma costs.
Regarding the other widespread condition, chronic obstructive pulmonary disease (COPD),64 million people live with itglobally, but the WHO predicts that the illness will become the third leading cause of death worldwide by 2030 due to the rise of air pollution, and the persistent habit of smoking.
Other chronic diseases, such as chronic bronchitis, emphysema, or cystic fibrosis also embitter the life of thousands. Not to speak about pneumonia or lung cancer. In spite of the considerable progress in fighting childhood pneumonia, it still accounts for 16 percent of all deaths of children under five years old,according to WHO statistics. The case is not rosy either when it comes to lung cancer, what is more,theWorld Cancer Research Fund saysthat the condition is the most commonly occurring cancer in men and the third most commonly occurring one in women globally. There were 2 million new cases in 2018. Hungary, Serbia, New Caledonia (France), and Greece are the countries with the highest rate of lung cancer cases. However, the U.S. doesn’t fare better either. According to theAmerican Cancer Society, lung cancer is by far the leading cause of cancer death among both men and women in the States.
The situation might not get better soon with worsening air quality around the globe andthe persistence in tobacco use. While we would like to encourage smokers to give up on their habit entirely – as partial solutions, such asvaping could also lead to complications, apparently-, we also decided to look around and collect what technologies can do to aid respiratory care and make the future of pulmonology brighter.
Source: www.romper.com
Diagnostic algorithms aiding pulmonologists
Digital health technologies can effectively aid the diagnosis and management of chronic respiratory diseases in many cases. In the case of asthma,as the illness is still ratherit is widely accepted that current diagnostic tools should be greatly enhanced treated as one single disease instead of an umbrella term for many types of conditions.In the future, researchers will harness the power of artificial intelligence and create diagnostic algorithms that could transform the ability of non-specialist healthcare professionals to make an accurate diagnosis.Machine learning could be used forthe analysis of breath sounds obtained fromelectronic stethoscopes, or evenfrom smartphones, for the detection of wheezes and crackles, for the interpretation of pulmonary function test (PFT) scores, or for the analysis of bronchoscopy images, as well as X-rays and CT scans.
That’s already happening when it comes to lung cancer. Screening and early detection are one of the most important factors in connection with these ugly diseases, however,the current method of lung cancer detection has a 96 percent false-positive rate.Using machine learning for medical imaging, researchers at the University of Pittsburgh and UPMC Hillman Cancer Center have found a way to substantially reduce false positives without missing a single case of cancer. Astudy from Google and Northwestern Medicinealso showed that an algorithm was able to detect malignant lung nodules on low-dose chest computed tomography (LDCT) scans on par with or even better than radiologists, demonstrating how A.I. could enhance the accuracy of early lung cancer diagnosis in the future. In another, Europeanresearch, an algorithm for pattern recognition outperformed pulmonologists in the interpretation of PFTs. Plus,in yet another study, researchers created a machine learning algorithm to predict a patient’s risk for pulmonary embolism and may help improve the use of CT imaging for the condition.
Looking at all these studies, some might arrive at the conclusion that smart algorithms are not yet being used in clinical settings. But that’s not the case: GE Healthcare’s Critical Care Suite has recently gotFDA-clearanceand is ready to get into as many hospitals as demand requires. The algorithm automatically processes chest scans right on the X-ray machine and flags those where it detects potential signs of pneumothorax. The attending radiologist immediately gets a copy of the scan via the hospital’s PACS system and the technologist performing the scan is alerted as well, to help make sure that the patient is triaged properly.
In addition, companies such asFluiddahave been developing artificial intelligence tools to combine high-resolution CT scans with advanced Computational Fluid Dynamics (CFD) tools to help pulmonologists visualize both structural and functional parameters of the lungs, which can also aid the diagnostic process. Another example is the excellent smartphone app,ResApp, from Australia, which provides a reliable diagnostic test for respiratory diseases.
