AI Shows Promising Results for Cancer Detection with Mammographic Screening
By MedImaging International staff writers Posted on 30 Mar 2022 |
Mammograms acquired through population-based breast cancer screening programs produce a significant workload for radiologists. Artificial intelligence (AI) has been proposed as an automated second reader for mammograms that could help reduce this workload. The technology has shown encouraging results for cancer detection, but evidence related to its use in real screening settings is limited. Now, a major new study has shown that AI is a promising tool for breast cancer detection in screening mammography programs.
The new study - the largest of its kind to date, led by researchers at the Cancer Registry of Norway (Oslo, Norway), compared the performance of a commercially available AI system with routine independent double reading as performed in a population-based screening program. The study drew from almost 123,000 examinations performed on more than 47,000 women at four facilities in BreastScreen Norway, the nation’s population-based screening program. The dataset included 752 cancers detected at screening and 205 interval cancers, or cancers detected between screening rounds. The AI system predicted the risk of cancer on a scale from 1 to 10, with 1 representing the lowest risk and 10 the highest risk. A total of 87.6% (653 of 752) of screen-detected and 44.9% (92 of 205) of interval cancers had the highest AI score of 10.
The researchers created three thresholds to assess the performance of the AI system as a decision-making tool. Using a threshold that mirrors the average individual radiologist rate of positive interpretation, the proportion of screen-detected cancers not selected by the AI system was less than 20%. While the AI system performed well, the study’s reliance on retrospective data means that more research is needed. The results showed favorable histopathologic characteristics associated with a better prognosis for screening-detected cancers with low versus high AI scores. Opposite results were observed for interval cancers. This may indicate that interval cancers with low AI scores are true interval cancers not visible on the screening mammograms.
The high percentage of true negative examinations classified with a low AI score has the potential of substantially reducing the interpretive volume, while allowing only a small proportion of cancers to go undetected. By using AI as one of the two readers in a double reading setting, the radiologist could still identify these cancers, the researchers said. Although more study is needed before clinical implementation of AI in breast cancer screening, the results of the study help establish a basis for future research, including prospective studies, according to the researchers.
“In our study, we assumed that all cancer cases selected by the AI system were detected,” said Solveig Hofvind, Ph.D., from the Section for Breast Cancer Screening, Cancer Registry of Norway. “This might not be true in a real screening setting. However, given that assumption, AI will probably be of great value in interpretation of screening mammograms in the future.”
“Based on our results, we expect AI to be of great value in the interpretation of screening mammograms in the future,” Dr. Hofvind added. “We expect the greatest potential to be in reducing the reading volume by selecting negative examinations.”
Related Links:
Cancer Registry of Norway
Latest General/Advanced Imaging News
- PET Scans Reveal Hidden Inflammation in Multiple Sclerosis Patients
- Artificial Intelligence Evaluates Cardiovascular Risk from CT Scans
- 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