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Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine

Molecular/genomic profiling is the most accurate method to assess prognosis of endometrial cancer patients. Radiomic profiling allows for the extraction of mineable high-dimensional data from clinical radiological images, thus providing noteworthy information regarding tumor tissues. Interestingly,...

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Autores principales: Bogani, Giorgio, Chiappa, Valentina, Lopez, Salvatore, Salvatore, Christian, Interlenghi, Matteo, D’Oria, Ottavia, Giannini, Andrea, Leone Roberti Maggiore, Umberto, Chiarello, Giulia, Palladino, Simona, Bascio, Ludovica Spano’, Castiglioni, Isabella, Raspagliesi, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778151/
https://www.ncbi.nlm.nih.gov/pubmed/36553988
http://dx.doi.org/10.3390/healthcare10122464
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author Bogani, Giorgio
Chiappa, Valentina
Lopez, Salvatore
Salvatore, Christian
Interlenghi, Matteo
D’Oria, Ottavia
Giannini, Andrea
Leone Roberti Maggiore, Umberto
Chiarello, Giulia
Palladino, Simona
Bascio, Ludovica Spano’
Castiglioni, Isabella
Raspagliesi, Francesco
author_facet Bogani, Giorgio
Chiappa, Valentina
Lopez, Salvatore
Salvatore, Christian
Interlenghi, Matteo
D’Oria, Ottavia
Giannini, Andrea
Leone Roberti Maggiore, Umberto
Chiarello, Giulia
Palladino, Simona
Bascio, Ludovica Spano’
Castiglioni, Isabella
Raspagliesi, Francesco
author_sort Bogani, Giorgio
collection PubMed
description Molecular/genomic profiling is the most accurate method to assess prognosis of endometrial cancer patients. Radiomic profiling allows for the extraction of mineable high-dimensional data from clinical radiological images, thus providing noteworthy information regarding tumor tissues. Interestingly, the adoption of radiomics shows important results for screening, diagnosis and prognosis, across various radiological systems and oncologic specialties. The central hypothesis of the prospective trial is that combining radiomic features with molecular features might allow for the identification of various classes of risks for endometrial cancer, e.g., predicting unfavorable molecular/genomic profiling. The rationale for the proposed research is that once validated, radiomics applied to ultrasonographic images would be an effective, innovative and inexpensive method for tailoring operative and postoperative treatment modalities in endometrial cancer. Patients with newly diagnosed endometrial cancer will have ultrasonographic evaluation and radiomic analysis of the ultrasonographic images. We will correlate radiomic features with molecular/genomic profiling to classify prognosis.
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spelling pubmed-97781512022-12-23 Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine Bogani, Giorgio Chiappa, Valentina Lopez, Salvatore Salvatore, Christian Interlenghi, Matteo D’Oria, Ottavia Giannini, Andrea Leone Roberti Maggiore, Umberto Chiarello, Giulia Palladino, Simona Bascio, Ludovica Spano’ Castiglioni, Isabella Raspagliesi, Francesco Healthcare (Basel) Communication Molecular/genomic profiling is the most accurate method to assess prognosis of endometrial cancer patients. Radiomic profiling allows for the extraction of mineable high-dimensional data from clinical radiological images, thus providing noteworthy information regarding tumor tissues. Interestingly, the adoption of radiomics shows important results for screening, diagnosis and prognosis, across various radiological systems and oncologic specialties. The central hypothesis of the prospective trial is that combining radiomic features with molecular features might allow for the identification of various classes of risks for endometrial cancer, e.g., predicting unfavorable molecular/genomic profiling. The rationale for the proposed research is that once validated, radiomics applied to ultrasonographic images would be an effective, innovative and inexpensive method for tailoring operative and postoperative treatment modalities in endometrial cancer. Patients with newly diagnosed endometrial cancer will have ultrasonographic evaluation and radiomic analysis of the ultrasonographic images. We will correlate radiomic features with molecular/genomic profiling to classify prognosis. MDPI 2022-12-07 /pmc/articles/PMC9778151/ /pubmed/36553988 http://dx.doi.org/10.3390/healthcare10122464 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Bogani, Giorgio
Chiappa, Valentina
Lopez, Salvatore
Salvatore, Christian
Interlenghi, Matteo
D’Oria, Ottavia
Giannini, Andrea
Leone Roberti Maggiore, Umberto
Chiarello, Giulia
Palladino, Simona
Bascio, Ludovica Spano’
Castiglioni, Isabella
Raspagliesi, Francesco
Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine
title Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine
title_full Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine
title_fullStr Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine
title_full_unstemmed Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine
title_short Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine
title_sort radiomics and molecular classification in endometrial cancer (the rome study): a step forward to a simplified precision medicine
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778151/
https://www.ncbi.nlm.nih.gov/pubmed/36553988
http://dx.doi.org/10.3390/healthcare10122464
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