Posts Tagged ‘lung’

35472460 - digital illustration of human lungs in colour background

Artificial intelligence (AI) can be an invaluable aid to help lung doctors interpret respiratory symptoms accurately and make a correct diagnosis, according to new research presented yesterday (Wednesday) at the European Respiratory Society International Congress.

Dr Marko Topalovic (PhD), a postdoctoral researcher at the Laboratory for Respiratory Diseases, Catholic University of Leuven (KU Leuven), Belgium, told the meeting that after training an AI computer algorithm using good quality data, it proved to be more consistent and accurate in interpreting respiratory test results and suggesting diagnoses than lung specialists.

“Pulmonary function tests provide an extensive series of numerical outputs and their patterns can be hard for the human eye to perceive and recognise; however, it is easy for computers to manage large quantities of data like these and so we thought AI could be useful for pulmonologists. We explored if this was true with 120 pulmonologists from 16 hospitals. We found that diagnosis by AI was more accurate in twice as many cases as diagnosis by pulmonologists. These results show how AI can serve as a second opinion for pulmonologists when they are assessing and diagnosing their patients,” he said.

Pulmonary function tests (PFT) include: spirometry, which involves the patient breathing through a mouthpiece to measure the amount of air inhaled and exhaled; a body box or plethysmography test, which enables doctors to assess lung volume by measuring the pressure in a booth in which the patient is sitting and breathing through a mouthpiece; and a diffusion capacity test, which tests how well a patient’s lungs are able to transfer oxygen and carbon dioxide to and from the bloodstream by testing the efficiency of the alveoli (small air sacks in the lungs). Results from these tests give doctors important information about the functioning of the lungs, but do not tell them what is wrong with the patient. This requires interpretation of the results in order to reach a diagnosis.

In this study, the researchers used historical data from 1430 patients from 33 Belgian hospitals. The data were assessed by an expert panel of pulmonologists and interpretations were measured against gold standard guidelines from the European Respiratory Society and the American Thoracic Society. The expert panel considered patients’ medical histories, results of all PFTs and any additional tests, before agreeing on the correct interpretation and diagnosis for each patient.

“When training the AI algorithm, the use of good quality data is of utmost importance,” explained Dr Topalovic. “An expert panel examined all the results from the pulmonary function tests, and the other tests and medical information as well. They used these to reach agreement on final diagnoses that the experts were confident were correct. These were then used to develop an algorithm to train the AI, before validating it by incorporating it into real clinical practice at the University Hospital Leuven. The challenging part was making sure the algorithm recognised patterns of up to nine different diseases.”

Then, 120 pulmonologists from 16 European hospitals (from Belgium, France, The Netherlands, Germany and Luxembourg) made 6000 interpretations of PFT data from 50 randomly selected patients. The AI also examined the same data. The results from both were measured against the gold standard guidelines in the same way as during development of the algorithm.

The researchers found that the interpretation of the PFTs by the pulmonologists matched the guidelines in 74% of cases (with a range of 56-88%), but the AI-based software interpretations perfectly matched the guidelines (100%). The doctors were able to correctly diagnose the primary disease in 45% of cases (with a range of 24-62%), while the AI gave a correct diagnosis in 82% of cases.

Dr Topalovic said: “We found that the interpretation of pulmonary function tests and the diagnosis of respiratory disease by pulmonologists is not an easy task. It takes more information and further tests to reach a satisfactory level of accuracy. On the other hand, the AI-based software has superior performance and therefore can provide a powerful decision support tool to improve current clinical practice. Feedback from doctors is very positive, particularly as it helps them to identify difficult patterns of rare diseases.”

Two large Belgian hospitals are already using the AI-based software to improve interpretations and diagnoses. “We firmly believe that we can empower doctors to make their interpretations and diagnoses easier, faster and better. AI will not replace doctors, that is certain, because doctors are able to see a broader perspective than that presented by pulmonary function tests alone. This enables them to make decisions based on a combination of many different factors. However, it is evident that AI will augment our abilities to accomplish more and decrease chances for errors and redundant work. The AI-based software has superior performance and therefore may provide a powerful decision support tool to improve current clinical practice.

“Nowadays, we trust computers to fly our planes, to drive our cars and to survey our security. We can also have confidence in computers to label medical conditions based on specific data. The beauty is that, independent of location or medical coverage, AI can provide the highest standards of PFT interpretation and patients can have the best and affordable diagnostic experience. Whether it will be widely used in future clinical applications is just a matter of time, but will be driven by the acceptance of the medical community,” said Dr Topalovic.

He said the next step would be to get more hospitals to use this technology and investigate transferring the AI technology to primary care, where the data would be captured by general practitioners (GPs) to help them make correct diagnoses and referrals.

Professor Mina Gaga is President of the European Respiratory Society, and Medical Director and Head of the Respiratory Department of Athens Chest Hospital, Greece, and was not involved in the study. She said: “This work shows the exciting possibilities that artificial intelligence offers to doctors to help them provide a better, quicker service to their patients. Over the past 20 to 30 years, the evolution in technology has led to better diagnosis and treatments: a revolution in imaging techniques, in molecular testing and in targeted treatments have make medicine easier and more effective. AI is the new addition! I think it will be invaluable in helping doctors and patients and will be an important aid to their decision-making.”

[1] Abstract no: PA5290, “Artificial intelligence improves experts in reading pulmonary function tests”, by M. Topalovic et al; Poster Discussion “The importance of the pulmonary function test in different clinical settings”, 08.30-10.30 hrs CEST, Wednesday 19 September, Room 7.2D.

The research was funded by Vlaams Agentschap Innoveren & Ondernemen – VLAIO (Belgian government body: Agency for Innovation and Entrepreneurship – VLAIO)

http://www.europeanlung.org/en/news-and-events/media-centre/press-releases/artificial-intelligence-improves-doctors%E2%80%99-ability-to-correctly-interpret-tests-and-diagnose-lung-disease

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Lung cancer seen on chest X ray.

Researchers have identified a gene that when inhibited or reduced, in turn, reduced or prevented human non-small cell lung cancer tumors from growing.

When mice were injected with non-small cell lung cancer cells that contained the gene NOVA1, three of four mice formed tumors. When the mice were injected with cancer cells without NOVA1, three of four mice remained tumor-free.

The fourth developed a tumor, but it was very small compared to the mice with the NOVA1 tumor cells, said Andrew Ludlow, first author on the study and assistant professor at the University of Michigan School of Kinesiology.

The research appears online today in Nature Communications. Ludlow did the work while a postdoctoral fellow at the University of Texas Southwestern Medical Center, in the shared lab of Woodring Wright, professor of cell biology and internal medicine, and Jerry Shay, professor of cell biology.

The study found that in cancer cells, the NOVA1 gene is thought to activate telomerase, the enzyme that maintains telomeres—the protective caps on the ends of chromosomes that preserve genetic information during cell division (think of the plastic aglets that prevent shoelace ends from fraying).

Telomerase isn’t active in healthy adult tissues, so telomeres degrade and shorten as we age. When they get too short, the body knows to remove those damaged or dead cells.

In most cancers, telomerase is reactivated and telomeres are maintained, thus preserving the genetic material, and these are the cells that mutate and become immortal.

Telomerase is present in most cancer types, and it’s an attractive therapeutic target for cancer. However, scientists haven’t had much luck inhibiting telomerase activity in cancer, Ludlow said.

Ludlow’s group wanted to try a new approach, so they screened lung cancer cell lines for splicing genes (genes that modify RNA) that might regulate telomerase in cancer, and identified NOVA1.

They found that reducing the NOVA1 gene reduced telomerase activity, which led to shorter telomeres, and cancer cells couldn’t survive and divide.

Researchers only looked at non-small cell lung cancers, and NOVA1 was present in about 70 percent of them.

“Non-small cell lung cancer is the most prevalent form of age-related cancer, and 80 to 85 percent of all lung cancers are non-small cell,” Ludlow said. “But there really aren’t that many treatments for it.”

According to the American Cancer Society, lung cancer causes the most cancer deaths among men and women, and is the second most common cancer, aside from skin cancer.

Before researchers can target NOVA1 or telomerase splicing as a serious potential therapy for non-small cell lung cancer, they must gain a much better understanding of how telomerase is regulated. This research is a step in that direction.

Ludlow’s group is also looking at ways to directly impact telomerase splicing, in addition to reducing NOVA1.

Explore further: Blocking two enzymes could make cancer cells mortal

More information: Andrew T. Ludlow et al, NOVA1 regulates hTERT splicing and cell growth in non-small cell lung cancer, Nature Communications (2018). DOI: 10.1038/s41467-018-05582-x

https://medicalxpress.com/news/2018-08-nova1-gene-tumor-growth-common.html


Ionocytes (orange) extend through neighboring epithelial cells (nuclei, cyan) to the surface of the respiratory epithelial lining. This newly identified cell type expresses high levels of CFTR, a gene that is associated with cystic fibrosis when mutated.

by ABBY OLENA

Two independent research teams have used single-cell RNA sequencing to generate detailed molecular atlases of mouse and human airway cells. The findings, reported in two studies today (August 1) in Nature, reveal the gene-expression patterns of thousands of lung cells, as well as the existence of a previously unknown cell type that expresses high levels of the gene mutated in cystic fibrosis, the cystic fibrosis transmembrane conductance regulator (CFTR).

“These papers are extremely exciting,” says Amy Ryan, a lung biologist at the University of Southern California who was not involved in either study. “They’ve interrogated the cellular composition and the cellular hierarchy of the airways by using a single-cell RNA-sequencing technique. That kind of information is going to have a significant impact on advancing the research that we can do, and hopefully the derivation of new therapeutic approaches for any number of airway diseases.”

Jayaraj Rajagopal, a pulmonary physician at Massachusetts General Hospital and Harvard University and coauthor of one of the studies, had been studying lung regeneration and wanted to use single-cell sequencing to look at differences in the lungs’ stem-cell populations. He and his colleagues teamed up with Aviv Regev, a computational biologist at the Broad Institute of MIT and Harvard University, and together, the two groups characterized the transcriptomes of thousands of epithelial cells from the adult mouse trachea.

Rajagopal, Regev, and colleagues uncovered previously unknown differences in gene expression in several groups of airway cells; identified novel structures in the lung; and found new paths of cellular differentiation. They also described several new cell types, including one that the team has named the pulmonary ionocyte, after salt-regulating cells in fish and amphibian skin. These lung cells express similar genes as fish and amphibian ionocytes, the team found, including a gene coding for the transcription factor Foxi1, which regulates genes that play a role in ion transport.

The team also showed that pulmonary ionocytes highly express CFTR, and are in fact the primary source of its product, CFTR—a membrane protein that helps regulate fluid transport and the consistency of mucus—in both mouse and human lungs, suggesting that the cells might play a role in cystic fibrosis.

“So much that we found rewrites the way we think about lung biology and lung cells,” says Rajagopal. “I think the entire community of pulmonologists and lung biologists will have to take a step back and think about their problems with respect to all these new cell types.”

For the other study, Aron Jaffe, a biologist at Novartis who studies how different airway cell types are made, combined forces with Harvard systems biologist Allon Klein and his team. Klein’s group had previously developed a single-cell RNA-sequencing method that Jaffe describes as “the perfect technology to take a big picture view and really define the full repertoire of epithelial cell types in the airway.”

Jaffe, Klein, and colleagues sequenced RNA from thousands of single human bronchial epithelial and mouse tracheal epithelial cells. The atlas generated by their sequencing analysis revealed pulmonary ionocytes, as well as new gene-expression patterns in familiar cells. The team examined the expression of CFTR in human and mouse ionocytes in order to better understand the possible role for the cells in cystic fibrosis. Consistent with the findings of the other study, the researchers showed that pulmonary ionocytes make the majority of CFTR protein in the airways of humans and mice.

“Finding this new rare cell type that accounts for the majority of CFTR activity in the airway epithelium was really the biggest surprise,” Jaffe tells The Scientist. “CFTR has been studied for a long time, and it was thought that the gene was broadly expressed in many cells in the airway. It turns out that the epithelium is more complicated than previously appreciated.”

These studies are “very exciting work [and] a wonderful example of how new technologies that have come online in the last few years—in this case single-cell RNA sequencing—have made a very dramatic advance in our understanding of aspects of biology,” says Ann Harris, a geneticist at Case Western Reserve University who did not participate in either study.

In terms of future directions, the authors “have shown that transcription factor [Foxi1] is central to the transcriptional program of these ionocytes,” says Harris. One of the next questions is, “does it directly interact with the CFTR gene or is it working through other transcription factors or other proteins that regulate CFTR gene expression?”

According to Jennifer Alexander-Brett, a pulmonary physician and researcher at Washington University School of Medicine in St. Louis who was not involved in the studies, the possibility that a rare cell type could be playing a part in regulating airway physiology is “captivating.”

Apart from investigating the potential role for ionocytes in lung function, Alexander-Brett says that researchers can likely make broad use of the data from the studies—particularly details on the expression of genes coding for transcription factors and cell-surface markers. “One area that we really struggle with in airway biology . . . is [that] we just don’t have good markers” to differentiate cell types, she explains. But these papers are “very comprehensive. There’s a ton of data here.”

D.T. Montoro et al., “A revised airway epithelial hierarchy includes CFTR-expressing ionocytes,” Nature, doi:10.1038/s41586-018-0393-7, 2018.

L.W. Plasschaert et al., “A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte,” Nature, doi:10.1038/s41586-018-0394-6, 2018.

https://www.the-scientist.com/news-opinion/new-lung-cell-identified-64594?utm_campaign=TS_DAILY%20NEWSLETTER_2018&utm_source=hs_email&utm_medium=email&utm_content=64924537&_hsenc=p2ANqtz-_M5n43mM_3CJb8-lIkjE6yt4ij2HduxgVeZi_X5bG7ATrAOGkvtsg4DpCbuAc0NAG8lx4myMxN3kiH4C1qc9OdlQkAGg&_hsmi=64924537