Artificial intelligence tools for radiology, clinical laboratory, and pathology diagnostics continue to advance and improve
Researchers in Germany have developed a fully automated, artificial intelligence (AI) tool that improves the diagnosis of prostate cancer. Developed by mediaire, a company that creates AI-based tools for radiologists, the software reduces clinical workloads and could be beneficial in counteracting issues associated with variability in magnetic resonance imaging (MRI) reporting. This is another example of AI’s growth in the clinical diagnostic industry, including clinical laboratory and pathology medicine.
The software, called mdprostate, has received the mandatory certification mark (CE or European Conformity) for products sold within the European Economic Area (EEA). It is now commercially available in those countries and was recently incorporated into the picture archiving and communications system (PACS) of some healthcare organizations and applied to a group of patients who had undergone a multiparametric prostate MRI (mpMRI).
The goal was to compare the overall performance of mdprostate against radiologists who executed the initial interpretations of the mpMRIs, according to Health Imaging.
“Mdprostate is intended to support radiologists by automating time-consuming processes and improving the objectivity of diagnosis through data quantification,” said Tonia Michaely, chief of staff at mediaire, in a news release.
“By providing objective assessments and standardizing lesion detection and classification, AI has the potential to augment radiologists’ performance throughout the PCa [prostate cancer] diagnostic pathway,” Nadine Bayerl, Dr. med., a radiologist with the Institute of Radiology at University Hospital Erlangen and corresponding author of the mediaire study, told Health Imaging. (Photo copyright: University Hospital Erlangen.)
Scoring Cancer Risk
To perform the comparison, a team of researchers applied the AI tool to 123 prostate MRI exams followed by systematic and targeted biopsies. The software was instructed to automatically segment the prostrate, calculate prostate volume, and classify lesions per the Prostate Imaging Reporting and Data System (PI-RADS).
PI-RADS, according to the America College of Radiology, is a reporting method that indicates how likely a lesion is to be clinically significant cancer on a score of one to five:
PI-RADS 1: very low (clinically significant cancer is highly unlikely to be present).
PI-RADS 2: low (clinically significant cancer is unlikely to be present).
PI-RADS 3: intermediate (the presence of clinically significant cancer is equivocal).
PI-RADS 4: high (clinically significant cancer is likely to be present).
PI-RADS 5: very high (clinically significant cancer is highly likely to be present).
For PI-RADS scores greater than two, mdprostate generated 100% sensitivity and dismissed all cancers for lesions that were below that threshold. For PI-RADS scores of four or higher, the AI tool yielded 85.5% sensitivity and specificity of 63.2% for clinically significant cancers.
Deep Learning in Diagnostic Pathway
“In practical terms, these results indicate that when a case falls below the PI-RADS ≥ 2 cutoff, clinicians can rule out malignancy with a high degree of confidence,” the authors explained in the European Journal of Radiology. “This capability is particularly valuable in clinical decision-making, as it allows for the safe avoidance of unnecessary biopsies or further invasive procedures in these patients.”
“Recent advances in deep learning algorithms, facilitated by larger labeled datasets, improved computing hardware, and refined training techniques, have led to several studies highlighting the diagnostic value of deep learning algorithms in prostate imaging,” radiologist Nadine Bayerl, Dr. med., Institute of Radiology at University Hospital Erlangen and corresponding author of the study, told Health Imaging.
The software “demonstrated high diagnostic performance in identifying and grading prostate lesions, with results comparable to those reported in meta-analyses of expert readers using PI-RADS,” the researchers noted in their published study.
“Its ability to standardize evaluations and potentially reduce variability underscores its potential as a valuable adjunct in the prostate cancer diagnostic pathway. The high accuracy of mdprostate, particularly in ruling out prostate cancers, highlights its clinical utility by reducing workload and enhancing patient outcomes,” they concluded.
AI in Clinical Laboratories and Pathology
Dark Daily has frequently covered AI’s expanding role in clinical laboratory testing and pathology diagnostics. At the recent Executive War College, a dozen sessions explored its growth in the industry. During one session, Sam Terese, CEO and president at Alverno Laboratories said, “AI is allowing us to drive our business. It is really resonating that we need to use AI in the future.”
Members who could not attend the 2025 Executive War College can order audio recordings of these valuable sessions by clicking here.
Clinical laboratory data was key in identifying antibiotic-resistant bacteria responsible for surge in BSIs in hospitals and other healthcare facilities in 2020 and 2021
Clinical laboratory data compiled by the European Antimicrobial Resistance Surveillance Network (EARS-Net) shows that a massive increase in bloodstream infections (BSIs) occurred among EU nations during the first two years of the COVID-19 pandemic. The study found that BSIs caused by certain antimicrobial-resistant (AMR) pathogens, known as superbugs, more than doubled in EU hospitals and healthcare facilities in 2020 and 2021.
Microbiologists and clinical laboratory managers in the US may find it valuable to examine this peer-reviewed study into AMR involved in blood stream infections. It could contain useful insights for diagnosing patients suspected of BSIs in US hospitals where sepsis prevention and antibiotic stewardship programs are major priorities.
“Antimicrobial resistance undermines modern medicine and puts millions of lives at risk,” said Tedros Adhanom Ghebreyesus, PhD, Director-General, World Health Organization, in a WHO press release. “To truly understand the extent of the global threat and mount an effective public health response to [antimicrobial resistance], we must scale up microbiology testing and provide quality-assured data across all countries, not just wealthier ones.” Clinical laboratories in the US may be called upon to submit data on bloodstream infections in this country. (Photo copyright: WHO.)
Clinical Laboratories in EU Report Huge Increase in Carbapenem Resistance
To perform their study, researchers measured the increase in Acinetobacter BSIs between 2020 and 2021, the first two years of the COVID-19 pandemic. Their data originated from qualitative regular antimicrobial susceptibility testing (AST) from blood samples collected by local clinical laboratories in the European Union/European economic area (EU/EEA) nations.
The researchers limited their dataset to Acinetobacter BSI information from the European medical laboratories that documented results of carbapenem susceptibility testing for the bacterial species.
Carbapenems are a class of very powerful antibiotics that are typically used to treat severe bacterial infections. A total of 255 EU/EEA clinical laboratories reported their data for the study. The scientists found that the percentages of Acinetobacter resistance varied considerably between EU/EEA nations, so they separated the countries into three different groups:
Nations in Group One—The Netherlands, Belgium, Austria, Estonia, Denmark, Germany, Iceland, Finland, Luxembourg, Ireland, Norway, Sweden, and Malta—experienced less than 10% resistance to carbapenems.
Nations in Group Two—Slovenia, Czech Republic, and Portugal—had carbapenem resistance between 10% and 50%.
Nations in Group Three—Croatia, Bulgaria, Greece, Cyprus, Italy, Hungary, Lithuania, Latvia, Romania, Poland, Spain, and Slovakia—demonstrated carbapenem resistance equal or greater than 50%.
The study also found that Acinetobacter BSIs rose by 57% and case counts increased by 114% in 2020 and 2021 when compared to 2018 and 2019. The percentage of resistance to carbapenems rose to 66% in 2020 and 2021, up from 48% in 2018 and 2019.
Antimicrobial Resistance Especially High in Hospital Settings
The researchers further arranged the data into three hospital ward types: intensive care unit (ICU), non-ICU, and unknown. The increase in BSIs caused by Acinetobacter species resistant to carbapenems was greater in ICU-admitted individuals (144%) than non-ICU-admitted individuals (41%).
There are more than 50 species of Acinetobacter bacteria and various strains are often resistant to many types of commonly-used antibiotics. Symptoms of an Acinetobacter infection usually appear within 12 days after a person comes into contact with the bacteria. These symptoms may include:
Blood infections,
Urinary tract infections,
Pneumonia, and
Wound infections.
Healthy people have a low risk of contracting an Acinetobacter infection with the highest number of these infections occurring in hospitals and other healthcare settings. Acinetobacter bacteria can survive for a long time on surfaces and equipment, and those working in healthcare or receiving treatment are in the highest risk category.
The prevalence of this type of bacteria increases in relation to the use of medical equipment, such as ventilators and catheters, as well as antibiotic treatments.
WHO Report Validates EARS-Net Research
In December of 2022, the World Health Organization (WHO) issued a Global Antimicrobial Resistance and Use Surveillance System (GLASS) report that revealed the presence of an increasing resistance to antibiotics in some bacterial infections. That report showed high levels (above 50%) of resistance in bacteria that frequently caused bloodstream infections in hospitals, such as Klebsiella pneumonia and Acinetobacter.
The WHO report examined data collected during 2020 from 87 different countries and found that common bacterial infections are becoming increasingly resistant to treatments. Both Klebsiella pneumoniae and Acinetobacter can be life threatening and often require treatment with strong antibiotics, such as carbapenems.
More research is needed to determine the reasons behind increases in Acinetobacter infections as reported in European hospitals and other healthcare settings, and to ascertain the extent to which they are related to hospitalizations and the upsurge in antimicrobial resistance during the COVID-19 pandemic.
Microbiologists and clinical laboratory managers in the US may want to learn more about the fIndings of this European study involving AMR and use those insights to plan accordingly for any future increase in bloodstream infections in this country.
