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Aditya Apte
Researcher at Memorial Sloan Kettering Cancer Center
Publications - 103
Citations - 4250
Aditya Apte is an academic researcher from Memorial Sloan Kettering Cancer Center. The author has contributed to research in topics: Radiation therapy & Medicine. The author has an hindex of 24, co-authored 89 publications receiving 2845 citations. Previous affiliations of Aditya Apte include Aarhus University Hospital & Kettering University.
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Journal ArticleDOI
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping
Alex Zwanenburg,Alex Zwanenburg,Martin Vallières,Mahmoud A. Abdalah,Hugo J.W.L. Aerts,Hugo J.W.L. Aerts,Vincent Andrearczyk,Aditya Apte,Saeed Ashrafinia,Spyridon Bakas,Roelof J. Beukinga,Ronald Boellaard,Marta Bogowicz,Luca Boldrini,Irène Buvat,Gary Cook,Christos Davatzikos,Adrien Depeursinge,Marie-Charlotte Desseroit,Nicola Dinapoli,Cuong V. Dinh,Sebastian Echegaray,Issam El Naqa,Issam El Naqa,Andriy Fedorov,Roberto Gatta,Robert J. Gillies,Vicky Goh,Michael Götz,Matthias Guckenberger,Sung Min Ha,Mathieu Hatt,Fabian Isensee,Philippe Lambin,Stefan Leger,Stefan Leger,Ralph T.H. Leijenaar,Jacopo Lenkowicz,Fiona Lippert,Are Losnegård,Klaus H. Maier-Hein,Olivier Morin,Henning Müller,Sandy Napel,Christophe Nioche,Fanny Orlhac,Sarthak Pati,Elisabeth Pfaehler,Arman Rahmim,Arman Rahmim,Arvind Rao,Jonas Scherer,Muhammad Siddique,Nanna M. Sijtsema,Jairo Socarras Fernandez,Emiliano Spezi,Roel J H M Steenbakkers,Stephanie Tanadini-Lang,Daniela Thorwarth,Esther G.C. Troost,Esther G.C. Troost,Taman Upadhaya,Vincenzo Valentini,Lisanne V. van Dijk,Joost J. M. van Griethuysen,Floris H. P. van Velden,Philip Whybra,Christian Richter,Christian Richter,Steffen Löck,Steffen Löck +70 more
TL;DR: A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software and could be excellently reproduced.
Journal ArticleDOI
Exploring feature-based approaches in PET images for predicting cancer treatment outcomes
I. El Naqa,Perry W. Grigsby,Aditya Apte,Elizabeth A. Kidd,Eric D. Donnelly,D. Khullar,S Chaudhari,Deshan Yang,M. Schmitt,Richard Laforest,Wade L. Thorstad,Joseph O. Deasy +11 more
TL;DR: Investigation of intensity-volume histogram metrics and shape and texture features extracted from PET images to predict patient's response to treatment suggests proposed approaches could potentially provide better tools and discriminant power for utilizing functional imaging in clinical prognosis.
Journal ArticleDOI
Elective Clinical Target Volumes for Conformal Therapy in Anorectal Cancer: A Radiation Therapy Oncology Group Consensus Panel Contouring Atlas
Robert J. Myerson,Michael C. Garofalo,Issam El Naqa,Ross A. Abrams,Aditya Apte,Walter R. Bosch,Prajnan Das,Leonard L. Gunderson,Theodore S. Hong,J.J. John Kim,Christopher G. Willett,Lisa A. Kachnic +11 more
TL;DR: This report serves as a template for the definition of the elective CTVs to be used in IMRT planning for anal and rectal cancers, as part of prospective RTOG trials.
Journal ArticleDOI
A Nomogram to Predict Radiation Pneumonitis, Derived from a Combined Analysis of RTOG 9311 and Institutional Data
Jeffrey D. Bradley,A. Hope,Issam El Naqa,Aditya Apte,P. Lindsay,Walter Bosch,John W. Matthews,William T. Sause,Mary V. Graham,Joseph O. Deasy +9 more
TL;DR: In this article, the authors used the Washington University (WU) patient dataset to test the superior-to-inferior tumor position, maximum dose, and D35 (minimum dose to the hottest 35% of the lung volume) were valuable to predict radiation pneumonitis (RP), against the patient database from Radiation Therapy Oncology Group (RTOG) trial 9311.
Journal ArticleDOI
Breast cancer subtype intertumor heterogeneity: MRI‐based features predict results of a genomic assay
Elizabeth J. Sutton,Jung Hun Oh,Brittany Z. Dashevsky,Brittany Z. Dashevsky,Harini Veeraraghavan,Aditya Apte,Sunitha B. Thakur,Joseph O. Deasy,Elizabeth A. Morris +8 more
TL;DR: To investigate the association between a validated, gene‐expression‐based, aggressiveness assay, Oncotype Dx RS, and morphological and texture‐based image features extracted from magnetic resonance imaging (MRI).