AI Accurately Predicts Who Will Develop Pancreatic Cancer Based on CT Scans
By MedImaging International staff writers Posted on 27 Apr 2022 |

Pancreatic ductal adenocarcinoma is not only the most common type of pancreatic cancer, but is also the most deadly. Less than 10% of people diagnosed with the disease live more than five years after being diagnosed or starting treatment. But recent studies have reported that finding the cancer early can increase survival rates by as much as 50%. There currently is no easy way to find pancreatic cancer early, however. People with this type of cancer may experience symptoms such as general abdominal pain or unexplained weight loss, but these symptoms are often ignored or overlooked as signs of the cancer since they are common in many health conditions. Now, an artificial intelligence (AI) tool can accurately predict who would develop pancreatic cancer based on what their CT scan images looked like years prior to being diagnosed with the disease. The findings may help prevent death through early detection of pancreatic cancer which is one of the most challenging cancers to treat.
Investigators at Cedars-Sinai (Los Angeles, CA, USA) reviewed electronic medical records to identify people who were diagnosed with the cancer within the last 15 years and who underwent CT scans six months to three years prior to their diagnosis. These CT images were considered normal at the time they were taken. The team identified 36 patients who met these criteria, the majority of whom had CT scans done in the ER because of abdominal pain. The AI tool was trained to analyze these pre-diagnostic CT images from people with pancreatic cancer and compare them with CT images from 36 people who didn’t develop the cancer. The investigators reported that the model was 86% accurate in identifying people who would eventually be found to have pancreatic cancer and those who would not develop the cancer.
The AI model picked up on variations on the surface of the pancreas between people with cancer and healthy controls. These textural differences could be the result of molecular changes that occur during the development of pancreatic cancer. The investigators are currently collecting data from thousands of patients at healthcare sites throughout the U.S. to continue to study the AI tool’s prediction capability.
“This AI tool was able to capture and quantify very subtle, early signs of pancreatic ductal adenocarcinoma in CT scans years before occurrence of the disease. These are signs that the human eye would never be able to discern,” said Debiao Li, PhD, director of the Biomedical Imaging Research Institute, professor of Biomedical Sciences and Imaging at Cedars-Sinai, and senior and corresponding author of the study.
“There are no unique symptoms that can provide an early diagnosis for pancreatic ductal adenocarcinoma,” said Stephen J. Pandol, MD, director of Basic and Translational Pancreas Research and program director of the Gastroenterology Fellowship Program at Cedars-Sinai, and another author of the study. “This AI tool may eventually be used to detect early disease in people undergoing CT scans for abdominal pain or other issues.”
“Our hope is this tool could catch the cancer early enough to make it possible for more people to have their tumor completely removed through surgery,” said Touseef Ahmad Qureshi, PhD, a scientist at Cedars-Sinai and first author of the study.
Related Links:
Cedars-Sinai
Latest General/Advanced Imaging News
- New AI Method Captures Uncertainty in Medical Images
- CT Coronary Angiography Reduces Need for Invasive Tests to Diagnose Coronary Artery Disease
- Novel Blood Test Could Reduce Need for PET Imaging of Patients with Alzheimer’s
- CT-Based Deep Learning Algorithm Accurately Differentiates Benign From Malignant Vertebral Fractures
- Minimally Invasive Procedure Could Help Patients Avoid Thyroid Surgery
- Self-Driving Mobile C-Arm Reduces Imaging Time during Surgery
- AR Application Turns Medical Scans Into Holograms for Assistance in Surgical Planning
- Imaging Technology Provides Ground-Breaking New Approach for Diagnosing and Treating Bowel Cancer
- CT Coronary Calcium Scoring Predicts Heart Attacks and Strokes
- AI Model Detects 90% of Lymphatic Cancer Cases from PET and CT Images
- Breakthrough Technology Revolutionizes Breast Imaging
- State-Of-The-Art System Enhances Accuracy of Image-Guided Diagnostic and Interventional Procedures
- Catheter-Based Device with New Cardiovascular Imaging Approach Offers Unprecedented View of Dangerous Plaques
- AI Model Draws Maps to Accurately Identify Tumors and Diseases in Medical Images
- AI-Enabled CT System Provides More Accurate and Reliable Imaging Results
- Routine Chest CT Exams Can Identify Patients at Risk for Cardiovascular Disease
Channels
Radiography
view channel
Novel Breast Imaging System Proves As Effective As Mammography
Breast cancer remains the most frequently diagnosed cancer among women. It is projected that one in eight women will be diagnosed with breast cancer during her lifetime, and one in 42 women who turn 50... Read more
AI Assistance Improves Breast-Cancer Screening by Reducing False Positives
Radiologists typically detect one case of cancer for every 200 mammograms reviewed. However, these evaluations often result in false positives, leading to unnecessary patient recalls for additional testing,... Read moreMRI
view channel
PET/MRI Improves Diagnostic Accuracy for Prostate Cancer Patients
The Prostate Imaging Reporting and Data System (PI-RADS) is a five-point scale to assess potential prostate cancer in MR images. PI-RADS category 3 which offers an unclear suggestion of clinically significant... Read more
Next Generation MR-Guided Focused Ultrasound Ushers In Future of Incisionless Neurosurgery
Essential tremor, often called familial, idiopathic, or benign tremor, leads to uncontrollable shaking that significantly affects a person’s life. When traditional medications do not alleviate symptoms,... Read more
Two-Part MRI Scan Detects Prostate Cancer More Quickly without Compromising Diagnostic Quality
Prostate cancer ranks as the most prevalent cancer among men. Over the last decade, the introduction of MRI scans has significantly transformed the diagnosis process, marking the most substantial advancement... Read moreUltrasound
view channel
Deep Learning Advances Super-Resolution Ultrasound Imaging
Ultrasound localization microscopy (ULM) is an advanced imaging technique that offers high-resolution visualization of microvascular structures. It employs microbubbles, FDA-approved contrast agents, injected... Read more
Novel Ultrasound-Launched Targeted Nanoparticle Eliminates Biofilm and Bacterial Infection
Biofilms, formed by bacteria aggregating into dense communities for protection against harsh environmental conditions, are a significant contributor to various infectious diseases. Biofilms frequently... Read moreNuclear Medicine
view channel
New SPECT/CT Technique Could Change Imaging Practices and Increase Patient Access
The development of lead-212 (212Pb)-PSMA–based targeted alpha therapy (TAT) is garnering significant interest in treating patients with metastatic castration-resistant prostate cancer. The imaging of 212Pb,... Read more
New Radiotheranostic System Detects and Treats Ovarian Cancer Noninvasively
Ovarian cancer is the most lethal gynecological cancer, with less than a 30% five-year survival rate for those diagnosed in late stages. Despite surgery and platinum-based chemotherapy being the standard... Read more
AI System Automatically and Reliably Detects Cardiac Amyloidosis Using Scintigraphy Imaging
Cardiac amyloidosis, a condition characterized by the buildup of abnormal protein deposits (amyloids) in the heart muscle, severely affects heart function and can lead to heart failure or death without... 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
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
Bayer and Google Partner on New AI Product for Radiologists
Medical imaging data comprises around 90% of all healthcare data, and it is a highly complex and rich clinical data modality and serves as a vital tool for diagnosing patients. Each year, billions of medical... Read more