Though smartphone apps are technically not clinical laboratory tools, anatomic pathologists and medical laboratory scientists (MLSs) may be interested to learn how health information technology (HIT), machine learning, and smartphone apps are being used to assess different aspects of individuals’ health, independent of trained healthcare professionals.
The issue that the Cedars Sinai researchers were investigating is the accuracy of patient self-reporting. Because poop can be more complicated than meets the eye, when asked to describe their bowel movements patients often find it difficult to be specific. Thus, use of a smartphone app that enables patients to accurately assess their stools in cases where watching the function of their digestive tract is relevant to their diagnoses and treatment would be a boon to precision medicine treatments of gastroenterology diseases.
“This app takes out the guesswork by using AI—not patient input—to process the images (of bowel movements) taken by the smartphone,” said gastroenterologist Mark Pimentel, MD (above), Executive Director of Cedars-Sinai’s Medically Associated Science and Technology (MAST) program and principal investigator of the study, in a news release. “The mobile app produced more accurate and complete descriptions of constipation, diarrhea, and normal stools than a patient could, and was comparable to specimen evaluations by well-trained gastroenterologists in the study.” (Photo copyright: Cedars-Sinai.)
Pros and Cons of Bristol Stool Scale
In their paper, the scientists discussed the Bristol Stool Scale (BSS), a traditional diagnostic tool for identifying stool forms into seven categories. The seven types of stool are:
Type 1: Separate hard lumps, like nuts (difficult to pass).
Type 2: Sausage-shaped, but lumpy.
Type 3: Like a sausage, but with cracks on its surface.
Type 4: Like a sausage or snake, smooth and soft (average stool).
Type 5: Soft blobs with clear cut edges.
Type 6: Fluffy pieces with ragged edges, a mushy stool (diarrhea).
Type 7: Watery, no solid pieces, entirely liquid (diarrhea).
But even with the BSS, things can get murky for patients. Inaccurate self-reporting of stool forms by people with IBS and diarrhea can make proper diagnoses difficult.
“The problem is that whenever you have a patient reporting an outcome measure, it becomes subjective rather than objective. This can impact the placebo effect,” gastroenterologist Mark Pimentel, MD, Executive Director of Cedars-Sinai’s Medically Associated Science and Technology (MAST) program and principal investigator of the study, told Healio.
Thus, according to the researchers, AI algorithms can help with diagnosis by systematically doing the assessments for the patients, News Medical reported.
30,000 Stool Images Train New App
To conduct their study, the Cedars-Sinai researchers tested an AI smartphone app developed by Dieta Health. According to Health IT Analytics, employing AI trained on 30,000 annotated stool images, the app characterizes digital images of bowel movements using five parameters:
BSS,
Consistency,
Edge fuzziness,
Fragmentation, and
Volume.
“The app used AI to train the software to detect the consistency of the stool in the toilet based on the five parameters of stool form, We then compared that with doctors who know what they are looking at,” Pimentel told Healio.
AI Assessments Comparable to Doctors, Better than Patients
According to Health IT Analytics, the researchers found that:
AI assessed the stool comparable to gastroenterologists’ assessments on BSS, consistency, fragmentation, and edge fuzziness scores.
AI and gastroenterologists had moderate-to-good agreement on volume.
AI outperformed study participant self-reports based on the BSS with 95% accuracy, compared to patients’ 89% accuracy.
Additionally, the AI outperformed humans in specificity and sensitivity as well:
Specificity (ability to correctly report a negative result) was 27% higher.
Sensitivity (ability to correctly report a positive result) was 23% higher.
“A novel smartphone application can determine BSS and other visual stool characteristics with high accuracy compared with the two expert gastroenterologists. Moreover, trained AI was superior to subject self-reporting of BSS. AI assessments could provide more objective outcome measures for stool characterization in gastroenterology,” the Cedars-Sinai researchers wrote in their paper.
“In addition to improving a physician’s ability to assess their patients’ digestive health, this app could be advantageous for clinical trials by reducing the variability of stool outcome measures,” said gastroenterologist Ali Rezaie, MD, study co-author and Medical Director of Cedars-Sinai’s GI Motility Program in the news release.
The researchers plan to seek FDA review of the mobile app.
Opportunity for Clinical Laboratories
Anatomic pathologists and clinical laboratory leaders may want to reach out to referring gastroenterologists to find out how they can help to better serve gastro patients. As the Cedars-Sinai study suggests, AI smartphone apps can perform BSS assessments as good as or better than humans and may be useful tools in the pursuit of precision medicine treatments for patient suffering from painful gastrointestinal disorders.
Proteins in human saliva make up its proteome and may be the key to new, precision medicine diagnostics that would give clinical pathologists new capabilities to identify disease
Clinical pathologists may soon have an array of new precision medicine diagnostic tools based on peoples’ saliva. There are an increasing number of “–omes” that can be the source of useful diagnostic biomarkers for developing clinical laboratory tests. The latest is the world’s first saliva protein biome wiki.
Called the Human Salivary Proteome Wiki (HSP Wiki), the “public data platform,” which was created by researchers at the University of Buffalo, is the “first of its kind,” according to Labroots, and “contains data on the many thousands of proteins present in saliva.”
The HSP Wiki brings together data from independent studies on proteins present in human saliva. One of the researchers’ goals is to speed up the development of saliva-based diagnostics and personalized medicine tools.
In “The Human Salivary Proteome Wiki: A Community-Driven Research Platform,” published in the Journal of Dental Research, the researchers wrote, “Saliva has become an attractive body fluid for on-site, remote, and real-time monitoring of oral and systemic health. At the same time, the scientific community needs a saliva-centered information platform that keeps pace with the rapid accumulation of new data and knowledge by annotating, refining, and updating the salivary proteome catalog.
“We developed the Human Salivary Proteome (HSP) Wiki as a public data platform for researching and retrieving custom-curated data and knowledge on the saliva proteome. … The HSP Wiki will pave the way for harnessing the full potential of the salivary proteome for diagnosis, risk prediction, therapy of oral and systemic diseases, and preparedness for emerging infectious diseases,” they concluded.
“This community-based data and knowledge base will pave the way to harness the full potential of the salivary proteome for diagnosis, risk prediction, and therapy for oral and systemic diseases, and increase preparedness for future emerging diseases and pandemics,” Stefan Ruhl, DDS, PhD (above right, with Omer Gokcumen, PhD, Associate Professor of Biological Sciences on left), Professor, Department of Oral Biology, University of Buffalo, and lead researcher of the study, told Labroots. Development of precision medicine clinical laboratory diagnostics is part of their research goals. (Photo copyright: University of Buffalo.)
Where Does Saliva Come From?
Saliva is a complex biological fluid that has long been linked to oral health and the health of the upper gastrointestinal tract. Only recently, though, have scientists begun to understand from where in the body saliva proteins originate.
The authors wrote: “Salivary proteins are essential for maintaining health in the oral cavity and proximal digestive tract, and they serve as potential diagnostic markers for monitoring human health and disease. However, their precise organ origins remain unclear.
“Through transcriptomic analysis of major adult and fetal salivary glands and integration with the saliva proteome, the blood plasma proteome, and transcriptomes of 28+ organs, we link human saliva proteins to their source, identify salivary-gland-specific genes, and uncover fetal- and adult-specific gene repertoires,” they added.
“Our results pave the way for future investigations into glandular biology and pathology, as well as saliva’s use as a diagnostic fluid,” the researchers concluded.
Saliva plays a crucial role in digestion by breaking down starches. It also provides a protective barrier in the mouth. When salivary glands malfunction, patients can face serious health consequences. Although clinicians and scientists have long understood the importance of saliva to good health, the question now is whether it contains markers of specific diseases.
“The Human Salivary Proteome Wiki contains proteomic, genomic, transcriptomic data, as well as data on the glycome, sugar molecules present on salivary glycoproteins. New data goes through an interdisciplinary team of curators, which ensures that all input data is accurate and scientifically sound,” noted Labroots.
The graphic above “shows the interconnectedness of the thousands of salivary proteins originating from blood plasma, parotid glands, and submandibular and sublingual glands. The diagram is one of many tools available to researchers and clinicians through the Human Salivary Proteome Wiki,” noted a UBNow blog post. (Graphic copyright: University of Buffalo.)
Omics and Their Role in Clinical Laboratory Diagnostics
Proteomics is just one of several hotly-researched -omics that hold the potential to develop into important personalized medicine and diagnostics tools for pathologists. Genomics is a related area of research being studied for its potential to benefit precision medicine diagnostics.
However, unlike genomes, which do not change, proteomes change constantly. That is one of the main reasons studying the human salivary proteome could lead to valuable diagnostics tools.
Combining the study of the -omes with tools like mass spectrometry, a new era of pathology may be evolving. “With the rapid decrease in the costs of omics technologies over the past few years, whole-proteome profiling from tissue slides has become more accessible to diagnostic labs as a means of characterization of global protein expression patterns to evaluate the pathophysiology of diseases,” noted Pathology News.
Saliva and the Age of Precision Medicine
The study of the -omes may be an important element in the evolution of precision medicine, because of its ability to provide information about what is happening in patients’ bodies at the point of care.
Thus, a full understanding of the proteome of saliva and what causes it to change in response to different health conditions and diseases could open the door to an entirely new branch of diagnostics and laboratory medicine. It is easy and non-invasive to gather and, given that saliva contains so much information, it offers an avenue of study that may improve patients’ lives.
It also would bring us closer to the age of precision medicine where clinical laboratory scientists and pathologists can contribute even more value to referring physicians and their patients.
Pathologists may be interested to learn that everyone’s breath reveals a signature composition of metabolites that may reflect a lifetime of diet, state of health, illnesses, and exposure to chemicals
New research shows that a person’s “breathprint” is as unique as a fingerprint and may be as effective as bodily fluids in diagnosing diseases. That same research effort is showing that it is feasible to combine breath specimens and mass spectrometry to accurately identify disease. That could give clinical laboratories a new methodology to use when creating diagnostic assays.
Health insurers may be poised to leave hospitals and physicians out of their networks, thus potentially cutting out pathologists and clinical laboratories
Clinical laboratory companies that find themselves excluded from health insurers’ provider networks do not need to feel like they were singled out. That’s because health insurers are narrowing their networks by also excluding hospitals and physicians.
Years ago, the “narrow network” strategy was used by HMOs and health insurers to extract rock bottom prices from hospitals, physicians, and medical laboratories. Now this strategy is returning as health insurers develop what they call narrow networks. (more…)
Goal of unique collaboration is to give physicians a more accurate way to diagnose and treat many types of cancer
Two noteworthy healthcare organizations will collaborate with IBM (NYSE: IBM) to explore how IBM’s Watson can be used to help physicians deliver improved outcomes to patients. The collaboration involves one major health insurer and a prominent academic medical center in Los Angeles.
WellPoint, Inc. (NYSE: WLP) will interact with oncology experts at the Cedars-Sinai Cancer Institute in Los Angeles to “educate” and program Watson as a physician’s assistant. What makes this particularly interesting for anatomic pathologists is the potential of this project to marry advances in molecular diagnostics with artificial intelligence in ways that allow physicians to diagnose different cancers earlier and with greater accuracy.
The institute’s doctors will serve as advisers and lend expertise to help shape the initiative to develop effective ways to use Watson. “Cedars Sinai will provide the guidelines and insights to put into Watson,” stated Manoj Saxena, General Manager of IBM Watson Solutions, in a story published by Forbes Magazine.
Watson is IBM’s computing system that incorporates deep question answering technology that allows it to search quickly through vast amounts of data, then process it and analyze it in a way similar to that of the human brain. The Watson system is capable of processing the equivalent of about 200 million pages of data in about three seconds, Forbes reported.
