AI Predicts which Pre-Malignant Breast Lesions will Progress to Advanced Cancer

New research at Case Western Reserve University could help better determine which patients diagnosed with the pre-malignant breast cancer commonly as stage 0 are likely to progress to invasive breast cancer and therefore might benefit from additional therapy over and above surgery alone.

Once a lumpectomy of breast tissue reveals this pre-cancerous tumor, most women have surgery to remove the remainder of the affected tissue and some are given radiation therapy as well, said Anant Madabhushi, the F. Alex Nason Professor II of Biomedical Engineering at the Case School of Engineering.

"Current testing places patients in high risk, low risk and indeterminate risk - but then treats those 'indeterminates' with radiation, anyway," said Madabhushi, whose Center for Computational Imaging and Personalized Diagnostics (CCIPD) conducted the new research. "They err on the side of caution, but we're saying that it appears that it should go the other way - the middle should be classified with the lower risk.

"In short, we're probably over-treating patients," Madabhushi continued. "That goes against prevailing wisdom, but that's what our analysis is finding."

The most common breast cancer

Stage 0 breast cancer is the most common type and known clinically as ductal carcinoma in situ (DCIS), indicating that the cancer cell growth starts in the milk ducts.

About 60,000 cases of DCIS are diagnosed in the United States each year, accounting for about one of every five new breast cancer cases, according to the American Cancer Society. People with a type of breast cancer that has not spread beyond the breast tissue live at least five years after diagnosis, according to the cancer society.

Lead researcher Haojia Li, a graduate student in the CCIPD, used a computer program analyze the spatial architecture, texture and orientation of the individual cells and nuclei from scanned and digitized lumpectomy tissue samples from 62 DCIS patients.

The result: Both the size and orientation of the tumors characterized as "indeterminate" were actually much closer to those confirmed as low risk for recurrence by an expensive genetic test called Oncotype DX.

Li then validated the features that distinguished the low and high risk Oncotype groups in being able to predict the likelihood of progression from DCIS to invasive ductal carcinoma in an independent set of 30 patients.

"This could be a tool for determining who really needs the radiation, or who needs the gene test, which is also very expensive," she said.

The research led by Li was published Oct. 17 in the journal Breast Cancer Research.

Madabhushi established the CCIPD at Case Western Reserve in 2012. The lab now includes nearly 60 researchers. The lab has become a global leader in the detection, diagnosis and characterization of various cancers and other diseases, including breast cancer, by meshing medical imaging, machine learning and artificial intelligence (AI).

Some of the lab's most recent work, in collaboration with New York University and Yale University, has used AI to predict which lung cancer patients would benefit from adjuvant chemotherapy based on tissue slide images.

That advancement was named by Prevention Magazine as one of the top 10 medical breakthroughs of 2018.

Li H, Whitney J, Bera K, Gilmore H, Thorat MA, Badve S, Madabhushi A.
Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings.
Breast Cancer Res 21, 114 (2019). doi: 10.1186/s13058-019-1200-6.

Most Popular Now

Research Shows AI Technology Improves Pa…

Existing research indicates that the accuracy of a Parkinson's disease diagnosis hovers between 55% and 78% in the first five years of assessment. That's partly because Parkinson's sibling movement disorders...

Who's to Blame When AI Makes a Medi…

Assistive artificial intelligence technologies hold significant promise for transforming health care by aiding physicians in diagnosing, managing, and treating patients. However, the current trend of assistive AI implementation could actually...

First Therapy Chatbot Trial Shows AI can…

Dartmouth researchers conducted the first clinical trial of a therapy chatbot powered by generative AI and found that the software resulted in significant improvements in participants' symptoms, according to results...

DMEA sparks: The Future of Digital Healt…

8 - 10 April 2025, Berlin, Germany. Digitalization is considered one of the key strategies for addressing the shortage of skilled workers - but the digital health sector also needs qualified...

DeepSeek: The "Watson" to Doct…

DeepSeek is an artificial intelligence (AI) platform built on deep learning and natural language processing (NLP) technologies. Its core products include the DeepSeek-R1 and DeepSeek-V3 models. Leveraging an efficient Mixture...

Stepping Hill Hospital Announced as SPAR…

Stepping Hill Hospital, part of Stockport NHS Foundation Trust, has replaced its bedside units with state-of-the art devices running a full range of information, engagement, communications and productivity apps, to...

DMEA 2025: Digital Health Worldwide in B…

8 - 10 April 2025, Berlin, Germany. From the AI Act, to the potential of the European Health Data Space, to the power of patient data in Scandinavia - DMEA 2025...