As the cancer registry expands it will increasing become more useful to anatomic pathologists, histopathologists, oncologists, and even clinical laboratories
Oncologists, histopathologists, anatomic pathologists, and other cancer physicians now have a powerful new Wikipedia-style tumor registry to help them with their diagnoses and in educating patients on their specific types of cancer. Clinical laboratory managers may find it useful to understand the value this searchable database, and it can help their staff pathologists as well.
Free to use by both physicians and patients the World Tumor Registry (WTR) is designed “to minimize diagnostic errors by giving doctors a searchable online database of cancers that have been collected and categorized with cellular images collected from around the world,” Pittsburg-Post Gazette reported.
Prompt, accurate cancer diagnoses offer cancer patients the best chance for optimal treatment outcomes. However, many medical professionals around the globe do not have the training and resources to offer superior cancer diagnoses. That deficiency can translate to inferior treatment options and lower survival rates among cancer patients.
To help improve cancer diagnoses, pathologist Yuri E. Nikiforov, MD, PhD, Division Director, Molecular and Genomic Pathology, Vice Chair of the Department of Pathology, and Professor of Pathology, University of Pittsburgh, developed the WTR to provide educational and practical resources for individuals and organizations involved in cancer research.
Officially announced at the United States and Canadian Academy of Pathology (USCAP) annual convention, the WTR is an open-access catalog of digital microscopic images of human cancer types and subtypes.
The lower cost of technology and improved speed of access via the internet are technologies enabling this effort.
“We are creating sort of a Wikipedia for cancer images,” said Alyaksandr V. Nikitski, MD, PhD (above), Research Assistant Professor of Pathology, Division of Molecular and Genomic Pathology at Pittsburg School of Medicine and Administrative Director of the WTR, in an exclusive interview with Dark Daily. “Anyone in the world, if they can access the internet, can look at the well-annotated, diagnostic digital slides of cancer,” said Nikitski. Clinical laboratories may also find this new pathology tool useful. (Photo copyright: Alyaksandr V. Nikitski)
Minimizing Diagnostic Errors
Based in Pittsburgh, the WTR is freely available to anyone for viewing digital pathology slides of known cancer tumors as well as borderline and questionable cases. On the website, individuals can search for pictures of tumors in the registry by diagnosis, specific cohorts, and by microscopic features. Individuals may search further by tumor type and subtype to receive a picture of related tumors.
According to the WTR website, the mission of the nonprofit “is to minimize diagnostic errors, eliminate inequality in cancer recognition, diagnosis, and treatment in diverse populations, and improve outcomes by increasing access to the diagnostic pathology expertise and knowledge of microscopic characteristics of cancers that occur in different geographic, environmental, and socio-economic settings.”
This new comprehensive initiative will eventually encompass cancer images from all over the world.
“Let’s assume that I am a pathologist or a trainee who has little experience, or I don’t have access to collections of atypical tumors,” Nikitski explained. “I can view tumor collections online [in the WTR database] and check how typical and rare tumors look in various geographic regions and environmental settings.”
Once an image of a slide is selected, users will then receive a brief case history of the tumor in addition to such data as the age of the patient, their geographic location, sex, family history of the disease, and the size and stage of the tumor.
Increasing Probability of Correct Diagnosis
Pathologists and clinicians may also predict the probability of a particular diagnosis by searching under the microscopic feature of the database. This feature utilizes an innovative classifier known as PathDxFinder, where users may compare a slide from their lab to slides in the database by certain criteria. This includes:
After completing the questions above, the user presses the “predict diagnosis” button to receive the probability of cancer and most likely diagnosis based on the answers provided in the questionnaire.
WTR Editorial Boards
The WTR represents collections for each type of cancer site, such as lung or breast. A chairperson and editorial board are responsible for reviewing submitted slides before they are placed online. The editorial boards include 20 pathologists who are experts in diagnosing cancer categories, Nikitski explained.
Thousands of identified microscopic whole slide images (WSI) representing various types of cancer are deposited by the editors and other contributors to the project. The editorial board then carefully analyzes and compiles the data before posting the images for public viewing.
The editorial boards are located in five world regions:
Africa and the Middle East
Asia and Oceania
Central and South America
North America and Europe
Northern Asia
Any physicians or pathologists can contribute images to the database, by “simply selecting the editor of their region on the website, writing their name, and asking if they can submit tumor cases,” Nikitski stated.
“We have established a platform that allows pathologists to contact editors who are in the same geographic region,” he added.
Helping Physicians Identify Cancer Types
In a YouTube video, Nikiforov states that the WTR is an “educational nonprofit organization rooted in [the] beliefs that every cancer patient deserves accurate and timely diagnosis as the first and essential step in better treatment and outcomes.”
“We believe this can be achieved only when modern diagnostic tools and technologies are freely available to every physician and pathologist. Only when we understand how microscopic features of cancer vary in different geographic, environmental and ethnic populations, and only by integrating histopathology with clinical immunohistochemical and molecular genetic information for every cancer type,” he stated.
Since patient privacy is important, the database contains only basic data about patients, and all patient information is protected.
Launched in March, there are currently more than 400 thyroid tumor slides available to view in the online database. At the time of the announcement, the WTR platform was planned to be implemented in three phases:
Thyroid cancer (released in March of this year).
Lung cancer and breast cancer (anticipated to be completed by the third quarter of 2026).
Remaining cancers, including brain, soft tissue and bone, colorectal, head and neck, hematolymphoid, female genital, liver, pancreatic, prostate and male genital, skin, urinary system, pediatric, other endocrine cancers, and rare cancers (anticipated to be completed by the end of 2029).
“We believe that this resource will help physicians and pathologists practicing in small or big or remote medical centers to learn how cancer looks under a microscope in their own communities,” Nikiforov said in the video. “We also see WTR as a platform that connects physicians and scientists from different parts of the world who can work together to better understand and treat cancer.”
Catalogs like the World Tumor Registry might potentially create a pool of information that that could be mined by analytical and artificial intelligence (AI) platforms to ferret out new ways to improve the diagnosis of certain types of cancer and even enable earlier diagnoses.
“It is an extremely useful resource,” Nikitski said.
Anatomic pathologists will certainly find it so. And clinical laboratory managers may find the information useful as well when interacting with histopathologists and oncologists.
The deal will enable Crosscope’s digital pathology platform to layer around Clarapath’s histology automation hardware, a combination that could improve quality and efficiencies in diagnostic services for future customers, according to a Clarapath press release.
Clarapath’s goal with its products is to automate certain manual processes in histology laboratories, while at the same time reducing variability in how specimens are processed and produced into glass slides. In an exclusive interview with Dark Daily, Eric Feinstein, CEO and President at Clarapath said he believes the resulting data about these activities can drive further changes.
“A histotechnologist turns a microtome wheel and makes decisions about a piece of tissue in real time,” noted Feinstein, who will speak at the Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management on April 25-26 in New Orleans. “All of that real-time data isn’t captured. Imagine if we could take all of that data from thousands of histotechnologists who are cutting every day and aggregate it. Then you could start drawing definitive conclusions about best practices.”
“Clarapath’s foundation is about creating consistency and standardizing steps in histology—and uncovering the data that you need in order to accomplish those goals as a whole system,” Eric Feinstein (above), CEO and President at Clarapath told Dark Daily. “A histology lab’s workflow—from when the tissue comes in to when the glass slide is produced—should all be connected.” Many processes in histology and anatomic pathology continue to be manual. Automated solutions can contribute to improved productivity and reducing variability in how individual specimens are processed. (Photo copyright: Clarapath.)
Details Behind Clarapath’s Deal to Acquire Crosscope
As part of its acquisition, Clarapath of Hawthorne, New York, has retained all of Crosscope’s employees, who are located in Mountain View, California, and Bombay, India. Financial terms of the deal were not disclosed.
Clarapath’s flagship histology automation product is SectionStar, a tissue sectioning and transfer system designed to automate inefficient and manual activities in slide processing. The device offers faster and more efficient sample processing while reducing human involvement. Clarapath expects SectionStar be on the market in 2023. The company is currently taking pre-orders.
Meanwhile, Crosscope developed Crosscope Dx, a turnkey digital pathology solution that provides workflow tools and slide management as well as AI and machine learning to assist pathologists with their medical decision-making and diagnoses.
Adoption of Digital Pathology and Automation Can Be Challenging
Digital pathology has experienced growing popularity in the post-COVID-19 pandemic world. This is not only because remote pathology case reviews have become increasingly acceptable to physicians but also because of the ongoing shortages in clinical laboratory staffing.
“A pain point today for clinicians and laboratories is labor. That’s across the board,” Feinstein said. “We can help solve that with SectionStar.”
Feinstein does not believe adoption of digital pathology and histology automation is proceeding slowly, but he does acknowledge barriers to healthcare organizations installing the technologies.
“There are lots of little things that—from a workflow perspective—people have outsized expectations about,” he explained. “Clinicians and administrators are not used to innovating in a product sense. They may be innovating on how they deliver care or treatment pathways, but they’re not used to developing an engineering product and going through alpha and beta stages. That makes adopting new technology challenging.”
Medical laboratory managers and pathologists interested in pursuing histology automation and digital pathology should first determine what processes are sub-optimal or would benefit from the standardization hardware and software can offer. Being able to articulate those gains can help build the case for a return on investment to decision-makers.
Another resource to consider: Feinstein will speak about innovations for remote histology laboratory workers at the upcoming Executive War College for Clinical Laboratory, Diagnostics, and Pathology Management on April 25-26 in New Orleans. His session is titled, “Re-engineering the Classic Histology Laboratory: Enabling the Remote Histotechnologist with New Tools That Improve Productivity, Automate Processes, and Protect Quality.”
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.
“The SDPR will consolidate geographically fragmented EMR, PAS, and LIMS systems to create a detailed lifelong patient record and deliver cost savings,” NSW Health said in a news release.
NSW Health is the largest public health system in Australia with more than 220 public hospitals, 16 Local Health Districts, and three Specialty Networks. NSW Health Pathology operates more than 60 pathology laboratories (clinical laboratories in the US) and has 150 patient service centers.
“While this initiative will provide untold benefits to all the patients of NSW, we are excited about its potential for improving the health outcomes of our regional patients,” said Andrew Montague (above), former Chief Executive, Central Coast Local Health District in a press release. “By enabling greater collaboration across all local health districts and specialty health networks, the Single Digital Patient Record will provide clinicians with even better tools to keep the patient at the center of everything we do.” This project is more market evidence of the trend to bring clinical laboratory test results from multiple lab sites into a single data repository. (Photo copyright: Coast Community News.)
Cloud-based Realtime Access to Patient Records
Australia has a population of about 26 million and New South Wales, a state on the east coast, is home to more than eight million people. Though the scale of healthcare in Australia is much smaller than in the US, this is still a major project to pull patient data together from all the NSW hospitals, physicians’ offices, and other healthcare providers such as clinical laboratories and pathology practices.
With the change, NSW clinicians will benefit from a cloud–based system offering up real-time access to patients’ medical records, NSW Health Pathology Chief Executive Tracey McCosker told ITnews.
“Patients and our busy staff will benefit from clinical insights gained from the capture of important new data. Our work in pathology is vital to the diagnostic process and developing a statewide laboratory information management system will ensure we provide the best possible services,” McCosker told ITnews.
The KLAS Research report, “US Hospital Market Share 2022,” states that Epic, located in Verona, Wisconsin, has the largest US electronic health record (EHR) market share, Healthgrades noted. According to KLAS:
NSW Health’s decision to engage Epic came after a process involving 350 clinicians, scientists, and technical experts, Zoran Bolevich, MD, Chief Executive of eHealth NSW and NSW Health’s Chief Information Officer, told ITnews.
NSW Health’s Goal for Statewide Digital Patient Record
It was in December 2020 when NSW Health announced its plan to create the SDPR.
“Our vision is to be able to provide a single, holistic, statewide view of every patient—and for that information to be readily accessible to anyone involved in the patient’s care,” Bolevich said in the news release.
The SDPR, according to NSW Health, will address the following:
Challenges:
Current systems not connected statewide.
Inaccessible patient data.
Duplicative data collection.
Gaps in decision-making.
Goals:
Improve health outcomes.
Create patient centricity.
Leverage insights.
NSW’s government has already invested more than $106 million in the SDPR, Healthcare IT News reported.
Other Large EHR Rollouts
NSW Health is not the only large organization to take on such an ambitious project of creating a large-scale digital patient record. And not always to a successful conclusion.
The US Department of Veterans Affairs (VA)—also intent on EHR modernization—recently announced it is suspending roll-out of the Oracle Cerner EHR at VA centers until June 2023 to address technical issues affecting appointments, referrals, and test results.
Four VA centers in Washington, Oregon, and Ohio already went live with the system in 2022.
“We are delaying all future deployments of the new EHR while we fully assess performance and address every concern. Veterans and clinicians deserve a seamless, modernized health record system, and we will not rest until they get it,” said Deputy Secretary of Veterans Affairs Donald Remy, JD, in a news release.
For its part, Oracle Cerner wrote federal lawmakers noting the importance of continuing the project, which will move the VA away from its former VistA health information system.
“Modernization requires change and some short-term pain for the long-term benefits of a modern technology infrastructure,” noted Oracle Cerner Executive Vice President Ken Glueck in the letter, Becker’s Health IT reported. “A modernization project of this scale and scope necessarily involves time to untangle the decades of customized processes established in support of VistA, which inevitably involves challenges.”
NSW Health’s goal is to build a single repository of health information—including lab test results from multiple clinical laboratory sites. When finished NSW Health expects that sharing patient data will contribute to producing better healthcare outcomes.
However, the VA’s experience—and several other similar attempts at large-scale electronic patient record installations—suggest the work ahead will not be easy. But for NSW Health, it may be worth the effort.
Platform could be next breakthrough in quest for painless technology to replace in-patient phlebotomy blood draws for many clinical laboratory tests
In a proof-of-concept study, scientists from Israel and China have developed a “smart” microneedle adhesive bandage that measures and monitors in real time three critical biomarkers that currently require invasive blood draws for medical laboratory tests commonly performed on patients in hospitals.
According to a Technion news release, the microneedles are short, thin, and relatively painless because they only extend through the outer layer of skin to reach the interstitial fluid underneath. The needle system attaches to the patient’s skin using an adhesive patch and transfers data wirelessly to both doctor and patient in real time through cloud and Internet of Things (IoT) technologies.
Such a novel technology that allows inpatients to be monitored for key biomarkers without the need for a phlebotomist to collect blood for testing will be attractive and would likely improve the patient’s experience.
It also could reduce the volume of specimen required, potentially eliminating the invasive specimen collection procedure altogether.
“To adapt the technology to daily life, we have developed a unique [adhesive bandage] made of a flexible and soft polymer that stretches and contracts along with the skin and therefore does not interfere with any action whatsoever,” said Hossam Haick, PhD (above), in a Technion news release. “Since it is important for us that the system is available to everyone, we made sure to use relatively inexpensive materials, so the final product will not be expensive. The technology we have developed represents a leap forward in diagnosing diseases and continuous physiological monitoring at home and in the clinic.” Such a real-time monitoring device could eliminate clinical laboratory testing for certain biomarkers that currently require invasive blood draws. (Photo copyright: Technion-Israel Institute of Technology.)
Leap Forward in Diagnostic Testing and Disease Monitoring
As pathologists and medical laboratory scientists are aware, sodium is a prominent prognostic biomarker for assessing certain blood conditions such as dysnatremia, the presence of too much or too little sodium. It’s an essential element found in blood cells and blood fluid that plays a vital role in transmitting signals to the nervous system, as well as in other biological functions.
Led by Hossam Haick, PhD, head of the LNDB (Laboratory for Nanomaterials-based Devices) group and Dean of Certification Studies at Technion, the team of scientists tested their device’s effectiveness at monitoring patients’ blood for both hypernatremia (high concentration of sodium in the blood) as well as hyponatremia (low concentration of sodium in the blood).
Both conditions can affect neurological function and lead to loss of consciousness and coma. Thus, early monitoring is critical.
“As of now, detection and monitoring of sodium levels in the human body is carried out by means of laborious and bulky laboratory equipment, or by offline analysis of various bodily fluids,” the study’s authors explained in the news release. Use of the smart microneedle patch, they added, allows the patient to continue about their day as normal, as well as gives their doctor time to attend to more patients.
The “innovative stretchable, skin-conformal and fast-response microneedle extended-gate FET (field-effect transistor) biosensor [integrated with] a wireless-data transmitter and the Internet-of-Things cloud for real-time monitoring and long-term analysis [could] eventually help [bring] unlimited possibilities for efficient medical care and accurate clinical decision-making,” noted the study’s authors in Advanced Materials.
More research will be needed to determine whether this latest medical technology breakthrough will lead to a viable minimally invasive method for measuring, diagnosing, and monitoring medical conditions, but Technion’s platform appears to be another step toward a long-sought alternative to painful blood draws.
Further, pathologists and clinical laboratory managers should expect more products to hit the market that are designed to collect a lab specimen without the need for a trained phlebotomist. Companies developing these products recognize that recruiting and retaining trained phlebotomist is an ongoing concern for medical labs. Thus, to have a method of collecting a lab specimen that is simple and can be done by anyone—including patients themselves—would be an important benefit.
The technology is similar to the concept of a liquid biopsy, which uses blood specimens to identify cancer by capturing tumor cells circulating in the blood.
According to the American Cancer Society, lung cancer is responsible for approximately 25% of cancer deaths in the US and is the leading cause of cancer deaths in both men and women. The ACS estimates there will be about 236,740 new cases of lung cancer diagnosed in the US this year, and about 130,180 deaths due to the disease.
Early-stage lung cancer is typically asymptomatic which leads to later stage diagnoses and lowers survival rates, largely due to a lack of early disease detection tools. The current method used to detect early lung cancer lesions is low-dose spiral CT imaging, which is costly and can be risky due to the radiation hazards of repeated screenings, the news release noted.
MGH’s newly developed diagnostic tool detects lung cancer from alterations in blood metabolites and may lead to clinical laboratory tests that could dramatically improve survival rates of the deadly disease, the MGH scientist noted in a news release.
“Our study demonstrates the potential for developing a sensitive screening tool for the early detection of lung cancer,” said Leo Cheng, PhD (above), in the news release. Cheng is Associate Professor of Radiology at Harvard Medical School and Associate Biophysicist in Radiology at Massachusetts General Hospital. “The predictive model we constructed can identify which people may be harboring lung cancer. Individuals with suspicious findings would then be referred for further evaluation by imaging tests, such as low-dose CT, for a definitive diagnosis,” he added. Oncologists may soon have a clinical laboratory test for screening patients with early-stage lung cancer. (Photo copyright: OCSMRM.)
Detecting Lung Cancer in Blood Metabolomic Profiles
The MGH scientists created their lung-cancer predictive model based on magnetic resonance spectroscopy which can detect the presence of lung cancer from alterations in blood metabolites.
The researchers screened tens of thousands of stored blood specimens and found 25 patients who had been diagnosed with non-small-cell lung carcinoma (NSCLC), and who had blood specimens collected both at the time of their diagnosis and at least six months prior to the diagnosis. They then matched these individuals with 25 healthy controls.
The scientists first trained their statistical model to recognize lung cancer by measuring metabolomic profiles in the blood samples obtained from the patients when they were first diagnosed with lung cancer. They then compared those samples to those of the healthy controls and validated their model by comparing the samples that had been obtained from the same patients prior to the lung cancer diagnosis.
The predictive model yielded values between the healthy controls and the patients at the time of their diagnoses.
“This was very encouraging, because screening for early disease should detect changes in blood metabolomic profiles that are intermediate between healthy and disease states,” Cheng noted.
The MGH scientists then tested their model with a different group of 54 patients who had been diagnosed with NSCLC using blood samples collected before their diagnosis. The second test confirmed the accuracy of their model.
Predicting Five-Year Survival Rates for Lung Cancer Patients
Values derived from the MGH predictive model measured from blood samples obtained prior to a lung cancer diagnosis also could enable oncologists to predict five-year survival rates for patients. This discovery could prove to be useful in determining clinical strategies and personalized treatment decisions.
The researchers plan to analyze the metabolomic profiles of the clinical characteristics of lung cancer to understand the entire metabolic spectrum of the disease. They hope to create similar models for other illnesses and have already created a model that can distinguish aggressive prostate cancer by measuring the metabolomics profiles of more than 400 patients with that disease.
In addition, they are working on a similar model to screen for Alzheimer’s disease using blood samples and cerebrospinal fluid.
More research and clinical studies are needed to validate the utilization of blood metabolomics models as early screening tools in clinical practice. However, this technology might provide pathologists and clinical laboratories with diagnostic tests for the screening of early-stage lung cancer that could save thousands of lives each year.
