MSGID: 1:317/3 63e3257a   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    AI can predict the effectiveness of breast cancer chemotherapy    
      
     Date:   
         February 7, 2023   
     Source:   
         University of Waterloo   
     Summary:   
         Engineers have developed artificial intelligence (AI) technology to   
         predict if women with breast cancer would benefit from chemotherapy   
         prior to surgery.   
      
      
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   FULL STORY   
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   Engineers at the University of Waterloo have developed artificial   
   intelligence (AI) technology to predict if women with breast cancer   
   would benefit from chemotherapy prior to surgery.   
      
      
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   The new AI algorithm, part of the open-source Cancer-Net initiative led   
   by Dr.   
      
   Alexander Wong, could help unsuitable candidates avoid the serious side   
   effects of chemotherapy and pave the way for better surgical outcomes   
   for those who are suitable.   
      
   "Determining the right treatment for a given breast cancer patient is   
   very difficult right now, and it is crucial to avoid unnecessary side   
   effects from using treatments that are unlikely to have real benefit   
   for that patient," said Wong, a professor of systems design engineering.   
      
   "An AI system that can help predict if a patient is likely to respond well   
   to a given treatment gives doctors the tool needed to prescribe the best   
   personalized treatment for a patient to improve recovery and survival."   
   In a project led by Amy Tai, a graduate student with the Vision and Image   
   Processing (VIP) Lab, the AI software was trained with images of breast   
   cancer made with a new magnetic image resonance modality, invented by   
   Wong and his team, called synthetic correlated diffusion imaging (CDI).   
      
   With knowledge gleaned from CDI images of old breast cancer cases and   
   information on their outcomes, the AI can predict if pre-operative   
   chemotherapy treatment would benefit new patients based on their CDI   
   images.   
      
   Known as neoadjuvant chemotherapy, the pre-surgical treatment can shrink   
   tumours to make surgery possible or easier and reduce the need for major   
   surgery such as mastectomies.   
      
   "I'm quite optimistic about this technology as deep-learning AI has   
   the potential to see and discover patterns that relate to whether a   
   patient will benefit from a given treatment," said Wong, a director of   
   the VIP Lab and the Canada Research Chair in Artificial Intelligence   
   and Medical Imaging.   
      
   A paper on the project, Cancer-Net BCa: Breast Cancer Pathologic Complete   
   Response Prediction using Volumetric Deep Radiomic Features from Synthetic   
   Correlated Diffusion Imaging, was recently presented at Med-NeurIPS as   
   part of NeurIPS 2022, a major international conference on AI.   
      
   The new AI algorithm and the complete dataset of CDI images of breast   
   cancer have been made publicly available through the Cancer-Net initiative   
   so other researchers can help advance the field.   
      
       * RELATED_TOPICS   
             o Health_&_Medicine   
                   # Breast_Cancer # Colon_Cancer # Lung_Cancer #   
                   Personalized_Medicine   
             o Computers_&_Math   
                   # Artificial_Intelligence # Photography # Robotics #   
                   Software   
       * RELATED_TERMS   
             o Breast_cancer o Mammography o Breast_implant o   
             Breast_reconstruction o Computer_vision o Technology o   
             Cervical_cancer o Esophageal_cancer   
      
   ==========================================================================   
   Story Source: Materials provided by University_of_Waterloo. Note:   
   Content may be edited for style and length.   
      
      
   ==========================================================================   
   Journal Reference:   
      1. Chi-en Amy Tai, Nedim Hodzic, Nic Flanagan, Hayden Gunraj, Alexander   
         Wong. Cancer-Net BCa: Breast Cancer Pathologic Complete Response   
         Prediction using Volumetric Deep Radiomic Features from Synthetic   
         Correlated Diffusion Imaging. Submitted to arXiv, 2023 DOI:   
         10.48550/ arXiv.2211.05308   
   ==========================================================================   
      
   Link to news story:   
   https://www.sciencedaily.com/releases/2023/02/230207144246.htm   
      
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