Source: University of Texas M. D. Anderson Cancer Center From: news-medical.net Researchers at The University of Texas MD Anderson Cancer Center have developed a new computational approach designed to better account for changes in gene expression within tumors relative to their unique microenvironments. This approach outperformed current methods for predicting chemotherapy response in patients with triple-negative breast cancer (TNBC). The …
Multiomic Real-World Data Predict Outcomes in Metastatic Breast Cancer
By: Sabrina Serani From: targetedonc.com Key Takeaways Multiomic profiling, including whole exome and transcriptome sequencing, offers prognostic value beyond standard HER2 immunohistochemistry. HER2 and ABCC1 are identified as significant transcriptomic predictors of overall survival in patients treated with T-DXd. Elevated ABCC1 expression is associated with poorer outcomes, indicating its role in resistance to T-DXd. Integrating multiomic data into clinical practice …
RSNA: AI Model Tops Breast Density for Predicting Risk for Breast Cancer
Source: HealthDay From: cancertherapyadvisor.com An image-only artificial intelligence (AI) model is more precise than breast density for predicting the five-year risk for breast cancer, according to a study presented at the annual meeting of the Radiological Society of North America, held from Nov. 30 to Dec. 4 in Chicago. Constance D. Lehman, M.D., Ph.D., from Harvard Medical School in Boston, …
MRI model predicts breast tumor shrinkage patterns
By: Amerigo Allegretto From: auntminnie.com An MRI model that analyzes breast tumor microbiomes improved the prediction of tumor shrinkage patterns in a study published August 26 in Radiology. A team led by Yuhong Huang, MD, from Southern Medical University in Guangzhou, China, reported high accuracy and overall performance for the model, which incorporates the intratumoral microbiome count, habitat radiomic features, …
MRI predicts treatment response for triple-negative breast cancer
By: Amerigo Allegretto From: auntminnie.com Post-treatment MRI can accurately predict treatment response for early triple-negative breast cancer, according to research published July 1 in Radiology. A team led by Toulsie Ramtohul, MD, from the Curie Institute in Paris, France, found that their logistic regression model, which used radiologic complete response, nodal involvement, and Ki-67 indexing, achieved high predictive value for complete …
FDA authorizes first AI platform for breast cancer prediction
By: Stephanie Brown From: medicalxpress.com The U.S. Food and Drug Administration has granted de novo authorization to CLAIRITY BREAST, a first-in-class, image-based platform that can help predict a woman’s risk for breast cancer. CLAIRITY BREAST is designed as a prognostic tool that can predict the five-year risk of developing breast cancer by analyzing subtle imaging features on routine mammograms, making …
FDA Authorizes AI Platform for Breast Cancer Prediction
From: itnonline.com Clairity, Inc., a digital health innovator advancing AI-driven healthcare solutions, has received U.S. Food and Drug Administration (FDA) De Novo authorization for Clairity Breast, a novel, image-based prognostic platform designed to predict five-year breast cancer risk from a routine screening mammogram. With this authorization, Clairity is planning to launch among leading health systems through 2025 – propelling a new era …
Breast Texture Patterns May Aid Risk Prediction from Mammography
By: Laura Cowen From: insideprecisionmedicine.com In one of the largest studies of its kind, researchers have used radiomics analysis to identify six distinct breast tissue patterns, beyond breast density, that are associated with breast cancer risk. “We expect these phenotypes to improve future risk prediction to better identify women at high risk for breast cancer for risk-reduction strategies and tailored …
UC San Diego Team Develops New Dose Prediction Model for Breast Cancer Radiotherapy
From: ucsd.edu Researchers at UC San Diego have developed advanced deep learning techniques that could revolutionize treatment planning for breast cancer radiotherapy – making it faster and improving its quality. The team sought to reduce inconsistencies in treatment plans and improve patient outcomes by leveraging artificial intelligence (AI) using the Expanse system at the San Diego Supercomputer Center (SDSC), which …
New biomarker can accurately predict outcomes in meningiomas and breast cancers
Source : University of Texas M. D. Anderson Cancer Center From: news-medical.net Using a new technology and computational method, researchers from Fred Hutch Cancer Center and The University of Texas MD Anderson Cancer Center have uncovered a biomarker capable of accurately predicting outcomes in meningioma brain tumors and breast cancers. In the study, published today in Science, the researchers discovered …