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Clinical Laboratories and Pathology Groups

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Cedars-Sinai Researchers Determine Smartphone App Can Assess Stool Form as Well as Gastroenterologists and Better than IBS Patients

Artificial intelligence performs BSS assessments with higher sensitivity and specificity than human diagnosticians

In a recent study conducted by scientists at Cedars-Sinai Medical Center in Los Angeles, researchers evaluated a smartphone application (app) that uses artificial intelligence (AI) to assess and characterize digital images of stool samples. The app, it turns out, matched the accuracy of participating gastroenterologists and exceeded the accuracy of study patients’ self-reports of stool specimens, according to a news release.

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.

The scientists published their findings in the American Journal of Gastroenterology, titled, “A Smartphone Application Using Artificial Intelligence Is Superior to Subject Self-Reporting when Assessing Stool Form.”

Mark Pimentel, MD

“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). 

In an industry guidance report on irritable bowel syndrome (IBS)and associated drugs for treatment, the US Food and Drug Administration (FDA) said the BSS is “an appropriate instrument for capturing stool consistency in IBS.”

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.

—Donna Marie Pocius

Related Information:

Smartphone Application Using Artificial Intelligence is Superior to Subject Self-Reporting When Assessing Stool Form

Study: App More Accurate than Patient Evaluation of Stool Samples

Industry Guidance Report: Irritable Bowel Syndrome—Clinical Evaluation of Drugs

Artificial Intelligence-based Smartphone App for Characterizing Stool Form

AI Mobile App Improves on “Subjective” Patient-Reported Stool Assessment in IBS

Artificial Intelligence App Outperforms Patient-Reported Stool Assessments

Clinical Laboratories Could Soon Diagnose 17 Diseases with a Single Breath Analyzer Test from Israel’s Institute of Technology

The Technion breathalyzer would give pathology groups and medical laboratories unprecedented ability to support physicians in diagnosing and treating cancers, chronic diseases, and other illnesses

Readers of Dark Daily know that several pathology research teams in America and the UK are developing breath analyzer tests that can detect everything from lung cancer to early-stage infections. Clinical laboratories will soon have a plethora of breath-related tests from which to choose. Now there’s a new kid on the block. A breathalyzer test that can detect up to 17 distinct cancerous, inflammatory, and neurological diseases!

Assuming the cost per test was at a competitive level to existing technologies, what would give this new diagnostic system appeal to physicians and patients alike is that it would be a non-invasive way to diagnose disease. Only a sample of the patient’s breath would be needed to perform the assays.

Researchers at the Israel Institute of Technology, or Technion, published the results of their study in ACS Nano, a monthly journal of the American Chemical Society devoted to “nanoscience and nanotechnology research at the interfaces of chemistry, biology, materials science, physics, and engineering.” (more…)

Physicians May Soon Say Goodbye to the Stethoscope, as Digital Devices Take Over the Job of Monitoring Patient Bodily Functions

One device that uses computer algorithms to analyze bodily sounds has undergone clinical trials and is awaiting clearance by the FDA

Is technology poised to render the iconic stethoscope passé? For centuries, doctors have used stethoscopes for listening to functions in different parts of the body. However, new devices now exist that employ electronic biosensors to “listen” in on those same sounds and analyze them with computer algorithms. The devices then deliver assessments to attending physicians.

The concept remains the same. Place a device against the body, listen for sounds, and use those sounds to identify a patient’s symptoms. Since the goal is to monitor sounds, it is not likely that “digital stethoscopes” will impinge on the clinical laboratory testing services provided by pathologists and medical laboratory scientists. (more…)

Digital PCR Poised to Give Traditional Real-Time PCR a Run for Its Money in Gene Sequencing and Development of New Medical Laboratory Tests

Adoption of digital PCR is slow at this time, but pathologists may want to track how researchers use this technology in the new clinical laboratory assays they use

Molecular pathologists will be interested to learn that there is a new contender in the polymerase chain reaction (PCR) arena. It is digital PCR, and it has specific advantages over traditional real-time PCR methods.

For example, digital PCR can target specific DNA sequences in just one molecule of DNA. This new tool allows researchers to isolate rare genetic mutations too difficult to segregate with real-time PCR, noted a report from Insight Pharma Reports. (more…)

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