Thu, 2019-04-25 14:38
To Chemo or not to Chemo, That is the Question
Thursday, April 25, 2019 - 14:38

Recent research at the Center has unveiled novel quantitative imaging biomarkers from the immediate periphery adjacent to the tumor in both invasive breast cancer and advanced non-small cell lung cancer, from pre-treatment DCE-MRI and CT scans respectively. The breast cancer work was recently reported in JAMA Open, while the lung cancer work was published in Radiology: AI.

Unlike conventional 'radiomics' methods which look inside the tumor, the research here was innovative  at looking not just inside the tumor but also outside the tumor. The clincal end point these features were looking at was response to chemotherapy in both the cancers using only non-invasive imaging done before therapy. 

The work in lung cancer also showed that these novel pre-treamtment imaging features from inside and outside the lung nodule could also predict progression-free survival in these patients.

In the case of the work in HER2+ breast cancer (one of the invasive breast cancer subtypes), not only were the radiomic features predictive of benefit to chemotherapy derived from gold standard pathological analysis, but could also unlock novel molecular subtypes within this clinically defined subtype as well, with differential response to chemotherapy. 

The publication of these two novel research findings with a potential to change current clinical practice received excited coverage in the scientific community. A few of those are linked below

Business Standard, Science DailyScienMag, The Daily, Medical News, World Pharma News

Tue, 2018-05-01 12:41
Man vs Machine
Tuesday, May 1, 2018 - 12:41

Dr. Madabhushi talks about how AI can improve and augment human performance when it comes to diagnostic, therapeutic and treatment planning across a wide spectrum of diseases.

Also it seems the article and the related journal manuscripts are making quite a wave on Reddit. 

Mon, 2017-11-06 13:43
Role of Computational Imaging in Precision Medicine
Monday, November 6, 2017 - 13:43

A talk delivered at the National Cancer Institute on October 11, 2017.


Tue, 2017-06-13 10:29
ML-CDS 2017: Multimodal Learning for Clinical Decision Support
Tuesday, June 13, 2017 - 10:29

NEW deadline for paper submission: June 26, 2017

In conjunction with MICCAI 2017

September 10, 2017,Quebec City, Canada

Now accepting submissions

Papers will be published in a volume of Springer LNCS series (MICCAI 2017 Workshops Volume) 


ML-CDS 2017 builds on the success of the last four events in this series. We are looking for high-quality submissions that address innovative research and development in the learning methods using multimodal medical data. Applications in clinical decision support and treatment planning are of highest interest. Experts in quantitative imaging, text analytics, and decision support systems will present to an audience of scientists and clinicians. Advances in the development and use of deep learning methods with medical imaging and text data are expected to be among major topics of submission and discussion at the event.