We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

HospiMedica

Download Mobile App
Recent News AI Critical Care Surgical Techniques Patient Care Health IT Point of Care Business Focus

AI System Detects Prostate Cancer During Routine CT Scans

By HospiMedica International staff writers
Posted on 15 Nov 2021
Print article
Image: CT slices of a patient with prostate cancer (a), and one without (b) (Photo courtesy of SVHM/ RMIT)
Image: CT slices of a patient with prostate cancer (a), and one without (b) (Photo courtesy of SVHM/ RMIT)
A new study describes an artificial intelligence (AI) based framework that can rapidly spot incidental prostate tumors during abdominal or pelvic scans.

Developed at RMIT University (RMIT; Melbourne, Australia) and St. Vincent's Hospital (SVHM; Melbourne, Australia), the new convolutional neural network (CNN) is designed for incidental computer aided detection (CADe) of clinically significant prostate cancer in patients undergoing a computerized tomography (CT) scan of the abdomen or pelvis for other reasons. The dataset used to develop the CNN consisted of 139 clinically significant prostate cancer patients and 432 controls.

The results showed that the proposed CNN pipeline achieved an area under the receiver operating characteristic curve (ROC-AUC) of 0.88 on CT, significantly higher than that of two radiologists (0.61 and 0.70) set on the same task. In addition, the results confirmed that the screening capabilities of CT-based pipelines, when combined with deep learning CNNs, are comparable to those of magnetic resonance imaging (MRI)-based diagnostic pipelines. The study was published in the November 2021 issue of Scientific Reports.

“Australia doesn’t have a screening program for prostate cancer, but armed with this technology, we hope to catch [such] cases early in patients who are scanned for other reasons,” said study co-author radiologist Mark Page, MD, of SVHM. “For example, emergency patients who have CT scans could be simultaneously screened for prostate cancer. If we can detect it earlier and refer them to specialist care faster, this could make a significant difference to their prognosis.”

In Australia, prostate cancer is responsible for approximately 12% of all male cancer deaths, as the slowly-growing tumors often go unnoticed for years. It is typically difficult to spot prostate cancer in CT images, and the radiation doses required make CT unsuitable as a screening modality. However, if men need to undergo an abdominal or pelvic scan for other reasons, CADe could help spot prostate cancer and let clinicians initiate early treatment.

Related Links:
RMIT University
St. Vincent's Hospital


Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Autoclavable Camera System
Precision AC

Print article

Channels

Critical Care

view channel
Image: The stretchable microneedle electrode arrays (Photo courtesy of Zhao Research Group)

Stretchable Microneedles to Help In Accurate Tracking of Abnormalities and Identifying Rapid Treatment

The field of personalized medicine is transforming rapidly, with advancements like wearable devices and home testing kits making it increasingly easy to monitor a wide range of health metrics, from heart... Read more

Patient Care

view channel
Image: The portable, handheld BeamClean technology inactivates pathogens on commonly touched surfaces in seconds (Photo courtesy of Freestyle Partners)

First-Of-Its-Kind Portable Germicidal Light Technology Disinfects High-Touch Clinical Surfaces in Seconds

Reducing healthcare-acquired infections (HAIs) remains a pressing issue within global healthcare systems. In the United States alone, 1.7 million patients contract HAIs annually, leading to approximately... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The Quantra Hemostasis System has received US FDA special 510(k) clearance for use with its Quantra QStat Cartridge (Photo courtesy of HemoSonics)

Critical Bleeding Management System to Help Hospitals Further Standardize Viscoelastic Testing

Surgical procedures are often accompanied by significant blood loss and the subsequent high likelihood of the need for allogeneic blood transfusions. These transfusions, while critical, are linked to various... Read more