AI Diagnostic Tool Analyzes CT Scans to Spot Prostate Cancer Before Patients Have Symptoms
|
By MedImaging International staff writers Posted on 13 Jul 2021 |

Image: AI Diagnostic Tool Analyzes CT Scans to Spot Prostate Cancer Before Patients Have Symptoms (Photo courtesy of RMIT University)
Researchers have developed a diagnostic tool that can spot prostate cancer before patients have any symptoms, using artificial intelligence to analyze Computed Tomography (CT) scans in just seconds.
Researchers at RMIT University (Melbourne, Australia), in collaboration with clinicians at St Vincent’s Hospital Melbourne (Australia), have developed an artificial intelligence (AI) program that could catch the prostate cancer earlier, allowing for incidental detection through routine CT scans. The technology works by analyzing CT scans for tell-tale signs of prostate cancer, something even a well-trained human eye struggles to do.
Prostate cancer is the most diagnosed cancer and is slow growing, usually detected incidentally due to which it can go undiagnosed for years. It was responsible for an estimated 12% of male cancer deaths in 2020. Early detection is the key to successful treatment but men often dodge the doctor, avoiding diagnosis tests until it’s too late. CT imaging is not suitable for regular cancer screening because of the high radiation doses involved. CT scans were great for detecting bone and joint problems but even radiologists struggled to spot prostate cancers on the images. The new AI solution can be used to run a cancer check whenever men have their abdomen or pelvis scanned for other issues.
For the study, the researchers studied CT scans of asymptomatic patients, with and without prostate cancer. The team trained the AI software to look for features of disease in a variety of scans and where exactly to look for them, avoiding the need to manually crop the images. The AI performed better than radiologists who viewed the same images, detecting cancerous growths in just seconds. What’s more, the AI improved with each scan, learning and adapting to read images from different machines to spot even the smallest irregularities. The technology can be applied at scale, potentially integrating with a variety of diagnostic imaging equipment like MRI and DEXA machines - pending further research.
“We’ve trained our software to see what the human eye can’t, with the aim of spotting prostate cancer through incidental detection,” said RMIT’s Dr. Ruwan Tennakoon. “It’s like training a sniffer dog – we can teach the AI to see things that we can't with our own eyes, in the same way a dog can smell things human noses can’t.”
Related Links:
RMIT University
St Vincent’s Hospital Melbourne
Researchers at RMIT University (Melbourne, Australia), in collaboration with clinicians at St Vincent’s Hospital Melbourne (Australia), have developed an artificial intelligence (AI) program that could catch the prostate cancer earlier, allowing for incidental detection through routine CT scans. The technology works by analyzing CT scans for tell-tale signs of prostate cancer, something even a well-trained human eye struggles to do.
Prostate cancer is the most diagnosed cancer and is slow growing, usually detected incidentally due to which it can go undiagnosed for years. It was responsible for an estimated 12% of male cancer deaths in 2020. Early detection is the key to successful treatment but men often dodge the doctor, avoiding diagnosis tests until it’s too late. CT imaging is not suitable for regular cancer screening because of the high radiation doses involved. CT scans were great for detecting bone and joint problems but even radiologists struggled to spot prostate cancers on the images. The new AI solution can be used to run a cancer check whenever men have their abdomen or pelvis scanned for other issues.
For the study, the researchers studied CT scans of asymptomatic patients, with and without prostate cancer. The team trained the AI software to look for features of disease in a variety of scans and where exactly to look for them, avoiding the need to manually crop the images. The AI performed better than radiologists who viewed the same images, detecting cancerous growths in just seconds. What’s more, the AI improved with each scan, learning and adapting to read images from different machines to spot even the smallest irregularities. The technology can be applied at scale, potentially integrating with a variety of diagnostic imaging equipment like MRI and DEXA machines - pending further research.
“We’ve trained our software to see what the human eye can’t, with the aim of spotting prostate cancer through incidental detection,” said RMIT’s Dr. Ruwan Tennakoon. “It’s like training a sniffer dog – we can teach the AI to see things that we can't with our own eyes, in the same way a dog can smell things human noses can’t.”
Related Links:
RMIT University
St Vincent’s Hospital Melbourne
Latest Industry News News
- Nuclear Medicine Set for Continued Growth Driven by Demand for Precision Diagnostics
- GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
- Patient-Specific 3D-Printed Phantoms Transform CT Imaging
- Siemens and Sectra Collaborate on Enhancing Radiology Workflows
- Bracco Diagnostics and ColoWatch Partner to Expand Availability CRC Screening Tests Using Virtual Colonoscopy
- Mindray Partners with TeleRay to Streamline Ultrasound Delivery
- Philips and Medtronic Partner on Stroke Care
- Siemens and Medtronic Enter into Global Partnership for Advancing Spine Care Imaging Technologies
- RSNA 2024 Technical Exhibits to Showcase Latest Advances in Radiology
- Bracco Collaborates with Arrayus on Microbubble-Assisted Focused Ultrasound Therapy for Pancreatic Cancer
- Innovative Collaboration to Enhance Ischemic Stroke Detection and Elevate Standards in Diagnostic Imaging
- RSNA 2024 Registration Opens
- Microsoft collaborates with Leading Academic Medical Systems to Advance AI in Medical Imaging
- GE HealthCare Acquires Intelligent Ultrasound Group’s Clinical Artificial Intelligence Business
- Bayer and Rad AI Collaborate on Expanding Use of Cutting Edge AI Radiology Operational Solutions
- Polish Med-Tech Company BrainScan to Expand Extensively into Foreign Markets
Channels
Radiography
view channel
Routine Mammograms Could Predict Future Cardiovascular Disease in Women
Mammograms are widely used to screen for breast cancer, but they may also contain overlooked clues about cardiovascular health. Calcium deposits in the arteries of the breast signal stiffening blood vessels,... Read more
AI Detects Early Signs of Aging from Chest X-Rays
Chronological age does not always reflect how fast the body is truly aging, and current biological age tests often rely on DNA-based markers that may miss early organ-level decline. Detecting subtle, age-related... Read moreMRI
view channel
MRI Scan Breakthrough to Help Avoid Risky Invasive Tests for Heart Patients
Heart failure patients often require right heart catheterization to assess how severely their heart is struggling to pump blood, a procedure that involves inserting a tube into the heart to measure blood... Read more
MRI Scans Reveal Signature Patterns of Brain Activity to Predict Recovery from TBI
Recovery after traumatic brain injury (TBI) varies widely, with some patients regaining full function while others are left with lasting disabilities. Prognosis is especially difficult to assess in patients... Read moreUltrasound
view channel
Portable Ultrasound Sensor to Enable Earlier Breast Cancer Detection
Breast cancer screening relies heavily on annual mammograms, but aggressive tumors can develop between scans, accounting for up to 30 percent of cases. These interval cancers are often diagnosed later,... Read more
Portable Imaging Scanner to Diagnose Lymphatic Disease in Real Time
Lymphatic disorders affect hundreds of millions of people worldwide and are linked to conditions ranging from limb swelling and organ dysfunction to birth defects and cancer-related complications.... Read more
Imaging Technique Generates Simultaneous 3D Color Images of Soft-Tissue Structure and Vasculature
Medical imaging tools often force clinicians to choose between speed, structural detail, and functional insight. Ultrasound is fast and affordable but typically limited to two-dimensional anatomy, while... Read moreNuclear Medicine
view channel
Radiopharmaceutical Molecule Marker to Improve Choice of Bladder Cancer Therapies
Targeted cancer therapies only work when tumor cells express the specific molecular structures they are designed to attack. In urothelial carcinoma, a common form of bladder cancer, the cell surface protein... Read more
Cancer “Flashlight” Shows Who Can Benefit from Targeted Treatments
Targeted cancer therapies can be highly effective, but only when a patient’s tumor expresses the specific protein the treatment is designed to attack. Determining this usually requires biopsies or advanced... Read moreGeneral/Advanced Imaging
view channel
AI Tool Offers Prognosis for Patients with Head and Neck Cancer
Oropharyngeal cancer is a form of head and neck cancer that can spread through lymph nodes, significantly affecting survival and treatment decisions. Current therapies often involve combinations of surgery,... Read more
New 3D Imaging System Addresses MRI, CT and Ultrasound Limitations
Medical imaging is central to diagnosing and managing injuries, cancer, infections, and chronic diseases, yet existing tools each come with trade-offs. Ultrasound, X-ray, CT, and MRI can be costly, time-consuming,... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more







