Characterizing primary refractory neuroblastoma: prediction of outcome by microscopic image analysis

M. Khalid Khan Niazi; Daniel A. Weiser M.D.; Bruce R. Pawel M.D.; Metin N. Gurcan

doi:10.1117/12.2082095

19 March 2015 Characterizing primary refractory neuroblastoma: prediction of outcome by microscopic image analysis

M. Khalid Khan Niazi, Daniel A. Weiser M.D., Bruce R. Pawel M.D., Metin N. Gurcan

Proceedings Volume 9420, Medical Imaging 2015: Digital Pathology; 942008 (2015) https://doi.org/10.1117/12.2082095
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Neuroblastoma is a childhood cancer that starts in very early forms of nerve cells found in an embryo or fetus. It is a highly lethal cancer of sympathetic nervous system that commonly affects children of age five or younger. It accounts for a disproportionate number of childhood cancer deaths and remains a difficult cancer to eradicate despite intensive treatment that includes chemotherapy, surgery, hematopoietic stem cell transplantation, radiation therapy and immunotherapy. A poorly characterized group of patients are the 15% with primary refractory neuroblastoma (PRN) which is uniformly lethal due to de novo chemotherapy resistance. The lack of response to therapy is currently assessed after multiple months of cytotoxic therapy, driving the critical need to develop pretreatment clinic-biological biomarkers that can guide precise and effective therapeutic strategies. Therefore, our guiding hypothesis is that PRN has distinct biological features present at diagnosis that can be identified for prediction modeling. During a visual analysis of PRN slides, stained with hematoxylin and eosin, we observed that patients who survived for less than three years contained large eosin-stained structures as compared to those who survived for greater than three years. So, our hypothesis is that the size of eosin stained structures can be used as a differentiating feature to characterize recurrence in neuroblastoma. To test this hypothesis, we developed an image analysis method that performs stain separation, followed by the detection of large structures stained with Eosin. On a set of 21 PRN slides, stained with hematoxylin and eosin, our image analysis method predicted the outcome with 85.7% accuracy.

Citation Download Citation

M. Khalid Khan Niazi, Daniel A. Weiser M.D., Bruce R. Pawel M.D., and Metin N. Gurcan "Characterizing primary refractory neuroblastoma: prediction of outcome by microscopic image analysis", Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 942008 (19 March 2015); https://doi.org/10.1117/12.2082095

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