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September 2019: Radiomics – solutions for better diagnosis, treatment and prognosis

Featuring Pallavi Tiwari, MS,PhD.

01 September, 2019


Artificial Intelligence is presenting healthcare with unprecedented solutions for better diagnosis, treatment options and prognosis.Dr. Pallavi Tiwari , Assistant Professor of Biomedical Engineering ,director of Brain Image Computing laboratory at Case Western Reserve University. and an associate member of the Case Comprehensive Cancer Center presented her lab’s work focused on developing radiomic (extracting computerized sub-visual features from radiologic imaging), radiogenomic (identifying radiologic features associated with molecular phenotypes), and radiopathomic (radiologic features associated with pathologic phenotypes) techniques to capture insights into the underlying tumor biology as observed on non-invasive routine imaging.

She discussed clinical applications of this work for predicting disease outcome, recurrence, progression and response to therapy specifically in the context of brain tumors. She also discussed current efforts in developing new radiomic features for post-treatment evaluation and predicting response to chemo-radiation treatment.

She also presented her work which includes machine learning solutions to differentiate between tumors and non-tumor areas, developing new features to characterize tumors better and novel multimodal approaches to strengthen the accuracy of diagnosis and prognosis.

These new innovative techniques are now presenting our clinicians and patients with less invasive, more accurate and cheaper treatment options.From avoidance of brain biopsy to radiomics guided biopsies, better decision support for clinicians is likely to result in better treatment outcomes.

She concluded with a discussion on her lab’s recent findings in AI + experts, in the context of a clinically challenging problem of distinguishing benign radiation effects from tumor recurrence on routine MRI scans.


Dr. Tiwari got her PhD from Rutgers University in 2012.In 2016, she founded the Brain Image Computing lab at Case Western Reserve University. Her research interests lie in pattern recognition, data mining, and image analysis for automated personalized medicine solutions using radiological imaging in brain tumors and neurological disorders. 

Over the last 13 years, her research has been focused on developing novel image analysis methods for diagnosis, prognosis, and evaluating treatment response of different types of cancers (prostate, breast, lung) and neuro-imaging applications including brain tumors, epilepsy, and cancer pain. Her research has so far evolved into over 30 peer-reviewed publications, 35 peer-reviewed abstracts, and 7 patents (2 issued, 5 pending). 

In 2017, her work was recognized by Case Western as one of the most notable research works in the university. Her research has also been covered by various news outlets including Crains Cleveland, NSF Science Now, and Science Daily. She has received certification of commendation from the General Assembly of the State of Ohio and from Ohio Secretary of State for her work in brain tumors.  She has been a recipient of several scientific awards, most notably being named as one of 100 women achievers by Government of India for making a positive impact in the field of Science and Innovation.  In 2018, she was selected as one of Crain’s Business Cleveland Forty under 40.

Dr. Tiwari is currently leading a team of researchers on multiple projects using novel radiomics and image informatics for prognosis and treatment evaluation in adult and pediatric brain tumors, autism, as well as other neurological disorders. She has been an invited and plenary speaker on topics relating to radiomics and radiogenomics at forums including MICCAI, Society of Neuro-Oncology, SPIE, and radiology workshops throughout the country.  Her research is funded through the Department of Defense, Dana Foundation, state of Ohio, and Case Comprehensive Cancer Center. She also serves on various leadership capacities (i.e. associate editor, committee member, scientific reviewer) in the medical image informatics community.