Ms. Sukanya Raj Iyer Profile

Sukanya Raj Iyer

Graduate Research Assistant at Case Western Reserve Univ

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Publications (3)

SPIE Journal Paper | 18 March 2019 Open Access

Molecular imaging and validation of margins in surgically excised nonmelanoma skin cancer specimens

Yiqiao Liu, Ethan Walker, Sukanya Raj Iyer, Mark Biro, InYoung Kim, Bo Zhou, Brian Straight, Matthew Bogyo, James P. Basilion, Daniel L. Popkin, David L. Wilson

JMI, Vol. 6, Issue 01, 016001, (March 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.1.016001

KEYWORDS: Tissues, Luminescence, Cancer, Imaging systems, Skin cancer, Skin, Image registration, Molecular imaging, Image processing, Image segmentation

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Proceedings Article | 13 March 2019 Paper

Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI

Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma, Ramon Correa, Prateek Prasanna, Niha Beig, Kaustav Bera, Volodymyr Statsevych, Alexander Judkins, Anant Madabhushi, Pallavi Tiwari

Proceedings Volume 10950, 109501E (2019) https://doi.org/10.1117/12.2513567

KEYWORDS: Tumors, Magnetic resonance imaging, Brain, Tissues, Gadolinium, Cancer, Medical research, Lung cancer, Radiotherapy, Genomics

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Medulloblastoma (MB) is the most common malignant brain tumor in children. Currently, "one-size-fits-all" radiation and chemotherapy treatment regimen is employed for treating MB patient, causing at least some children to undergo highly aggressive and in some cases, inadequate radiation therapy. Consequently, there is a need for prognostic and predictive tools for identifying disease aggressiveness and ultimately which patients with MB may be able to benefit from de-escalation of therapy. Genomic characterization of MB has recently identified 4 distinct molecular subgroups: Sonic Hedgehog (SHH) , Wingless (WNT) , Group 3, Group 4 each exhibiting different clinical behavior. The molecular sub-types have unique risk-profiles and outcomes, and patients could potentially benefit from sub-group specific treatments. However, the transition of these molecular MB subtypes into clinical practice has been limited due to challenges in availability of molecular profiling in most hospitals, as well as variability in clinical assessment. In this work, we present a radiomic feature that captures subtle tissue deformations caused due to the impact of tumor growth on the normal-appearing brain around tumor (BAT), to distinguish molecular sub-types of MB. First, we obtain voxel-wise deformation magnitude from the deformation orientations, after registering Gadolinium (Gd)-enhanced T1-w MRI scan for every study to a normal age-specific T1w MRI template. Deformation statistics are then computed within every 5mm annular BAT region, 0 < d < 60mm, where d is the distance from the tumor infiltrating edge, to capture subtle localized deformation changes around the tumor. Our results using multi-class comparison via one-way ANOVA and post-hoc comparison showed significant differences across deformation magnitudes obtained for Group 3, Group 4, and SHH molecular sub-types, observed up to 15-mm outside the infiltrating edge. Our feasibility results suggest that the subtle deformation features in BAT observed on routine Gd-T1w MRI may potentially serve as surrogate markers to non-invasively characterize molecular sub-types of pediatric MB.

Proceedings Article | 6 March 2018 Presentation + Paper

Molecular imaging and validation of non-melanoma skin cancer margins

Yiqiao Liu, Ethan Walker, InYoung Kim, Mark Biro, Sukanya Raj Iyer, Bo Zhou, Matthew Bogyo, James Basilion, Daniel Popkin, David Wilson

Proceedings Volume 10579, 105790Y (2018) https://doi.org/10.1117/12.2293847

KEYWORDS: Skin cancer, Imaging systems, Image registration, Surgery, Image segmentation

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