Abstract PS4-43: Prediction of breast ductal carcinoma in situ recurrence using histomics analysis of stromal features from hematoxylin and eosin stain-based images

Autor: Olivier Morin, Catherine C. Park, Taman Upadhaya, Ronald Balassanian

Publikováno v: Cancer Research. 81:PS4-43

OBJECTIVE It remains a challenge to predict individual risk for recurrence after primary treatment of ductal carcinoma in situ (DCIS). While DCIS is contained within the duct, prior studies have pointed to the importance of stromal collagen in cancer

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7670c91cbc4c939996b06db15061c9a5
https://doi.org/10.1158/1538-7445.sabcs20-ps4-43

Abstract P1-02-16: Prediction of breast ductal carcinoma in situ recurrence using histomics analysis of stromal collagen from second-harmonic generation and hematoxylin and eosin stain-based images

Autor: Taman Upadhaya, Mary-Kate Hayward, Mi-Ok Kim, Ronald Balassanian, Valerie Weaver, Olivier Morin, Catherine Park

Publikováno v: Cancer Research. 82:P1-02

OBJECTIVE. A clinical challenge of ductal carcinoma in situ (DCIS) is to accurately predict individual risk for recurrence. Prior studies have highlighted the importance of stromal collagen surrounding breast ducts in breast cancer aggression. We stu

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https://doi.org/10.1158/1538-7445.sabcs21-p1-02-16

Comparison and Fusion of Machine Learning Algorithms for Prospective Validation of PET/CT Radiomic Features Prognostic Value in Stage II-III Non-Small Cell Lung Cancer

Autor: Taman Upadhaya, Dimitris Visvikis, Catherine Cheze Le Rest, Mathieu Hatt, Olena Tankyevych, Shima Sepehri

Publikováno v: Diagnostics
Volume 11
Issue 4
Diagnostics, Vol 11, Iss 675, p 675 (2021)

Machine learning (ML) algorithms for selecting and combining radiomic features into multiparametric prediction models have become popular
however, it has been shown that large variations in performance can be obtained by relying on different app

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::131a8102402270d428b9e26b7a08811b
https://pubmed.ncbi.nlm.nih.gov/33918681

Qualitative and quantitative reproducibility of [18]fluoromethycholine PET/computed tomography in prostate cancer

Autor: Christelle Gallais, R. Perdrisot, Catherine Cheze Le Rest, Florent Tixier, Taman Upadhaya, Thomas Pinto-Leite

Publikováno v: Nuclear medicine communications. 41(2)

Background Recurrence occurs in more than 50% of prostate cancer. To be effective, treatments require precise localization of tumor cells. [F]fluoromethylcholine ([18F]FCH) PET/computed tomography (CT) is currently used to restage disease in cases of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::745c340d629aab95f8039d1372e60c4f
https://pubmed.ncbi.nlm.nih.gov/31939917

The Image Biomarker Standardization Initiative: standardized quantitative radiomics for highthroughput image-based phenotyping

Autor: Olivier Morin, Mahmoud A. Abdalah, Steffen Löck, Sandy Napel, Lisanne V. van Dijk, Arvind Rao, Muhammad Siddique, Jacopo Lenkowicz, Ronald Boellaard, Issam El Naqa, Jairo Socarras Fernandez, Marta Bogowicz, Spyridon Bakas, Jonas Scherer, Are Losnegård, Marie-Charlotte Desseroit, Robert J. Gillies, Gary Cook, Martin Vallières, Vincenzo Valentini, Alex Zwanenburg, Philip Whybra, Sarthak Pati, Sebastian Echegaray, Matthias Guckenberger, Christos Davatzikos, Emiliano Spezi, Roberto Gatta, Nicola Dinapoli, Daniela Thorwarth, Luca Boldrini, Roel J H M Steenbakkers, Esther G.C. Troost, Joost J. M. van Griethuysen, Irène Buvat, Sung Min Ha, Fiona Lippert, Hugo J.W.L. Aerts, Klaus H. Maier-Hein, Fanny Orlhac, Cuong V. Dinh, Stefan Leger, Philippe Lambin, Ralph T.H. Leijenaar, Fabian Isensee, Mathieu Hatt, Vicky Goh, Christian Richter, Roelof J. Beukinga, Henning Müller, Elisabeth Pfaehler, Nanna M. Sijtsema, Floris H. P. van Velden, Aditya Apte, Michael Götz, Arman Rahmim, Vincent Andrearczyk, Stephanie Tanadini-Lang, Adrien Depeursinge, Christophe Nioche, Andriy Fedorov, Saeed Ashrafinia, Taman Upadhaya

Publikováno v: Radiology 295(2020)2, 328-338
Radiology
Radiology, Radiological Society of North America, 2020, 295 (2), pp.328-338. ⟨10.1148/radiol.2020191145⟩
Radiology, 295(2), 328-338. RADIOLOGICAL SOC NORTH AMERICA
Zwanenburg, A, Vallières, M, Abdalah, M A, Aerts, H J W L, Andrearczyk, V, Apte, A, Ashrafinia, S, Bakas, S, Beukinga, R J, Boellaard, R, Bogowicz, M, Boldrini, L, Buvat, I, Cook, G J R, Davatzikos, C, Depeursinge, A, Desseroit, M C, Dinapoli, N, Dinh, C V & Echegaray, S 2020, ' The image biomarker standardization initiative : Standardized quantitative radiomics for high-throughput image-based phenotyping ', Radiology, vol. 295, no. 2, pp. 328-338 . https://doi.org/10.1148/radiol.2020191145
Radiology, vol 295, iss 2
Radiology, 295(2), 328-338. Radiological Society of North America, Inc.
Radiology, 2020, 295 (2), pp.328-338. ⟨10.1148/radiol.2020191145⟩
Radiology, 295(2), 328-338. Radiological Society of North America Inc.

International audience; Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a07c005740a02571d8d74ebfc9433efe
https://www.hzdr.de/publications/Publ-30321-1