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Dive into the research topics where Srishti Abrol is active.

Publication


Featured researches published by Srishti Abrol.


Topics in Magnetic Resonance Imaging | 2017

Radiomic Phenotyping in Brain Cancer to Unravel Hidden Information in Medical Images

Srishti Abrol; Aikaterini Kotrotsou; Ahmed Salem; Pascal O. Zinn; Rivka R. Colen

Abstract Radiomics is a new area of research in the field of imaging with tremendous potential to unravel the hidden information in digital images. The scope of radiology has grown exponentially over the last two decades; since the advent of radiomics, many quantitative imaging features can now be extracted from medical images through high-throughput computing, and these can be converted into mineable data that can help in linking imaging phenotypes with clinical data, genomics, proteomics, and other “omics” information. In cancer, radiomic imaging analysis aims at extracting imaging features embedded in the imaging data, which can act as a guide in the disease or cancer diagnosis, staging and planning interventions for treating patients, monitor patients on therapy, predict treatment response, and determine patient outcomes.


Scientific Reports | 2017

Silent Sentence Completion Shows Superiority Localizing Wernicke's Area and Activation Patterns of Distinct Language Paradigms Correlate with Genomics: Prospective Study

Kamel Salek; Islam Hassan; Aikaterini Kotrotsou; Srishti Abrol; Scott H. Faro; Feroze B. Mohamed; Pascal O. Zinn; Wei Wei; Nan Li; Ashok Kumar; Jeffrey S. Weinberg; Jeffrey S. Wefel; Shelli R. Kesler; Ho Ling Anthony Liu; Ping Hou; R. Jason Stafford; Sujit S. Prabhu; Raymond Sawaya; Rivka R. Colen

Preoperative mapping of language areas using fMRI greatly depends on the paradigms used, as different tasks harness distinct capabilities to activate speech processing areas. In this study, we compared the ability of 3 covert speech paradigms: Silent Sentence Completion (SSC), category naming (CAT) and verbal fluency (FAS), in localizing the Wernicke’s area and studied the association between genomic markers and functional activation. Fifteen right-handed healthy volunteers and 35 mixed-handed patients were included. We focused on the anatomical areas of posterosuperior, middle temporal and angular gyri corresponding to Wernicke’s area. Activity was deemed significant in a region of interest if P < 0.05. Association between fMRI activation and genomic mutation status was obtained. Results demonstrated SSC’s superiority at localizing Wernicke’s area. SSC demonstrated functional activity in 100% of cancer patients and healthy volunteers; which was significantly higher than those for FAS and CAT. Patients with 1p/19q non-co-deleted had higher extent of activation on SSC (P < 0.02). Those with IDH-1 wild-type were more likely to show no activity on CAT (P < 0.05). SSC is a robust paradigm for localizing Wernicke’s area, making it an important clinical tool for function-preserving surgeries. We also found a correlation between tumor genomics and functional activation, which deserves more comprehensive study.


Investigational New Drugs | 2018

Radiomics to predict immunotherapy-induced pneumonitis: proof of concept

Rivka R. Colen; Takeo Fujii; Mehmet Asim Bilen; Aikaterini Kotrotsou; Srishti Abrol; Kenneth R. Hess; Joud Hajjar; Maria E. Suarez-Almazor; Anas Alshawa; David S. Hong; Dunia Giniebra-Camejo; Bettzy Stephen; Vivek Subbiah; Ajay Sheshadri; Tito R. Mendoza; Siqing Fu; Padmanee Sharma; Funda Meric-Bernstam; Aung Naing


Journal of Clinical Oncology | 2017

Radiomic analysis of pseudo-progression compared to true progression in glioblastoma patients: A large-scale multi-institutional study.

Srishti Abrol; Aikaterini Kotrotsou; Ahmed Hassan; Nabil Elshafeey; Islam Hassan; Tagwa Idris; Kamel Salek; Ahmed Elakkad; Kristin Alfaro; Shiao-Pei Weathers; Fanny Moron; Jason T. Huse; Jeffrey S. Weinberg; Amy B. Heimberger; Raymond Sawaya; Ashok Kumar; John F. de Groot; Meng Law; Pascal O. Zinn; Rivka R. Colen


Neurosurgery | 2018

213 Radiomic Machine Learning Algorithms Discriminate Pseudo-Progression From True Progression in Glioblastoma Patients: A Multi-Institutional Study

Pascal O. Zinn; Srishti Abrol; Aikaterini Kotrotsou; Ahmed Hassan; Nabil Elshafeey; Tagwa Idris; Naveen Manohar; Islam Hassan; Kamel Salek; Nikdokht Farid; Carrie R. McDonald; Shiao-Pei Weathers; Naeim Bahrami; Samuel Bergamaschi; Ahmed Elakkad; Kristin Alfaro-Munoz; Fanny Moron; Jason T. Huse; Jeffrey S. Weinberg; Sherise D. Ferguson; Evangelos Kogias; Amy B. Heimberger; Raymond Sawaya; Ashok M Kumar; John F. de Groot; Meng Law; Rivka R. Colen


Journal of Neuro-oncology | 2018

Multi-center study finds postoperative residual non-enhancing component of glioblastoma as a new determinant of patient outcome

Aikaterini Kotrotsou; Ahmed Elakkad; Jia Sun; Ginu Thomas; Dongni Yang; Srishti Abrol; Wei Wei; Jeffrey S. Weinberg; Ali Shojaee Bakhtiari; Moritz F. Kircher; Markus Luedi; John F. de Groot; Raymond Sawaya; Ashok Kumar; Pascal O. Zinn; Rivka R. Colen


Journal of Clinical Oncology | 2018

Interrogating machine learning classifiers and dimensionality reduction techniques for radiomic prediction of glioma tumor grade.

Kareem Wahid; Aikaterini Kotrotsou; Srishti Abrol; Ahmed Hassan; Nabil Elshafeey; Rivka R. Colen


Cancer Research | 2018

Abstract 3040: Radiomics discriminates pseudo-progression from true progression in glioblastoma patients: A large-scale multi-institutional study

Srishti Abrol; Aikaterini Kotrotsou; Ahmed Hassan; Nabil Elshafeey; Tagwa Idris; Naveen Manohar; Anand Agarwal; Islam Hassan; Kamel Salek; Nikdokht Farid; Carrie R. McDonald; Shiao-Pei Weathers; Naeim Bahrami; Samuel Bergamaschi; Ahmed Elakkad; Kristin Alfaro-Munoz; Fanny Moron; Jason T. Huse; Jeffrey S. Weinberg; Sherise D. Ferguson; Evangelos Kogias; Amy B. Heimberger; Raymond Sawaya; Ashok Kumar; John F. de Groot; Meng Law; Pascal O. Zinn; Rivka R. Colen


Neuro-oncology | 2017

NIMG-91. RADIOMIC ANALYSIS OF PSEUDO-PROGRESSION COMPARED TO TRUE PROGRESSION IN GLIOBLASTOMA PATIENTS: A LARGE-SCALE MULTI-INSTITUTIONAL STUDY

Srishti Abrol; Aikaterini Kotrotsou; Ahmed Hassan; Nabil Elshafeey; Anand Agarwal; Islam Hassan; Tagwa Idris; Kamel Salek; Nikdokht Farid; Carrie R. McDonald; Shiao-Pei Weathers; Naeim Bahrami; Samuel Bergamaschi; Ahmed Elakkad; Kristin Alfaro-Munoz; Fanny Moron; Jason T. Huse; Jeffrey S. Weinberg; Amy B. Heimberger; Raymond Sawaya; Ashok Kumar; John F. de Groot; Meng Law; Pascal O. Zinn; Rivka R. Colen


Neuro-oncology | 2017

NIMG-02. MULTI-CENTER STUDY DEMONSTRATES RADIOMIC TEXTURE FEATURES DERIVED FROM MR PERFUSION IMAGES PREDICT PSEUDOPROGRESSION FROM TRUE PROGRESSION IN GLIOBLASTOMA PATIENTS

Nabil Elshafeey; Aikaterini Kotrotsou; Srishti Abrol; Islam Hassan; Ahmed Hassan; Anand Agarwal; Kamel Salek; Samuel Bergamaschi; Fanny Moron; Meng Law; Pascal O. Zinn; Rivka R. Colen

Collaboration


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Aikaterini Kotrotsou

University of Texas MD Anderson Cancer Center

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Rivka R. Colen

University of Texas MD Anderson Cancer Center

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Pascal O. Zinn

Baylor College of Medicine

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Nabil Elshafeey

University of Texas MD Anderson Cancer Center

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Ahmed Hassan

University of Texas MD Anderson Cancer Center

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Kamel Salek

University of Texas MD Anderson Cancer Center

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Ahmed Elakkad

University of Texas MD Anderson Cancer Center

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Ashok Kumar

University of Texas MD Anderson Cancer Center

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Fanny Moron

Baylor College of Medicine

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Jeffrey S. Weinberg

University of Texas MD Anderson Cancer Center

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