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Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study

Background: Liver metastases are a leading cause of cancer-associated deaths in patients affected by colorectal cancer (CRC). The multidisciplinary strategy to treat CRC is more effective when the radiological diagnosis is accurate and early. Despite the evolving technologies in radiological accurac...

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Autores principales: Rocca, Aldo, Brunese, Maria Chiara, Santone, Antonella, Avella, Pasquale, Bianco, Paolo, Scacchi, Andrea, Scaglione, Mariano, Bellifemine, Fabio, Danzi, Roberta, Varriano, Giulia, Vallone, Gianfranco, Calise, Fulvio, Brunese, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8745238/
https://www.ncbi.nlm.nih.gov/pubmed/35011771
http://dx.doi.org/10.3390/jcm11010031
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author Rocca, Aldo
Brunese, Maria Chiara
Santone, Antonella
Avella, Pasquale
Bianco, Paolo
Scacchi, Andrea
Scaglione, Mariano
Bellifemine, Fabio
Danzi, Roberta
Varriano, Giulia
Vallone, Gianfranco
Calise, Fulvio
Brunese, Luca
author_facet Rocca, Aldo
Brunese, Maria Chiara
Santone, Antonella
Avella, Pasquale
Bianco, Paolo
Scacchi, Andrea
Scaglione, Mariano
Bellifemine, Fabio
Danzi, Roberta
Varriano, Giulia
Vallone, Gianfranco
Calise, Fulvio
Brunese, Luca
author_sort Rocca, Aldo
collection PubMed
description Background: Liver metastases are a leading cause of cancer-associated deaths in patients affected by colorectal cancer (CRC). The multidisciplinary strategy to treat CRC is more effective when the radiological diagnosis is accurate and early. Despite the evolving technologies in radiological accuracy, the radiological diagnosis of Colorectal Cancer Liver Metastases (CRCLM) is still a key point. The aim of our study was to define a new patient representation different by Artificial Intelligence models, using Formal Methods (FMs), to help clinicians to predict the presence of liver metastasis when still undetectable using the standard protocols. Methods: We retrospectively reviewed from 2013 to 2020 the CT scan of nine patients affected by CRC who would develop liver lesions within 4 months and 8 years. Seven patients developed liver metastases after primary staging before any liver surgery, and two patients were enrolled after R0 liver resection. Twenty-one patients were enrolled as the case control group (CCG). Regions of Interest (ROIs) were identified through manual segmentation on the medical images including only liver parenchyma and eventual benign lesions, avoiding major vessels and biliary ducts. Our predictive model was built based on formally verified radiomic features. Results: The precision of our methods is 100%, scheduling patients as positive only if they will be affected by CRCLM, showing a 93.3% overall accuracy. Recall was 77.8%. Conclusion: FMs can provide an effective early detection of CRCLM before clinical diagnosis only through non-invasive radiomic features even in very heterogeneous and small clinical samples.
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spelling pubmed-87452382022-01-11 Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study Rocca, Aldo Brunese, Maria Chiara Santone, Antonella Avella, Pasquale Bianco, Paolo Scacchi, Andrea Scaglione, Mariano Bellifemine, Fabio Danzi, Roberta Varriano, Giulia Vallone, Gianfranco Calise, Fulvio Brunese, Luca J Clin Med Article Background: Liver metastases are a leading cause of cancer-associated deaths in patients affected by colorectal cancer (CRC). The multidisciplinary strategy to treat CRC is more effective when the radiological diagnosis is accurate and early. Despite the evolving technologies in radiological accuracy, the radiological diagnosis of Colorectal Cancer Liver Metastases (CRCLM) is still a key point. The aim of our study was to define a new patient representation different by Artificial Intelligence models, using Formal Methods (FMs), to help clinicians to predict the presence of liver metastasis when still undetectable using the standard protocols. Methods: We retrospectively reviewed from 2013 to 2020 the CT scan of nine patients affected by CRC who would develop liver lesions within 4 months and 8 years. Seven patients developed liver metastases after primary staging before any liver surgery, and two patients were enrolled after R0 liver resection. Twenty-one patients were enrolled as the case control group (CCG). Regions of Interest (ROIs) were identified through manual segmentation on the medical images including only liver parenchyma and eventual benign lesions, avoiding major vessels and biliary ducts. Our predictive model was built based on formally verified radiomic features. Results: The precision of our methods is 100%, scheduling patients as positive only if they will be affected by CRCLM, showing a 93.3% overall accuracy. Recall was 77.8%. Conclusion: FMs can provide an effective early detection of CRCLM before clinical diagnosis only through non-invasive radiomic features even in very heterogeneous and small clinical samples. MDPI 2021-12-22 /pmc/articles/PMC8745238/ /pubmed/35011771 http://dx.doi.org/10.3390/jcm11010031 Text en © 2021 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 Article
Rocca, Aldo
Brunese, Maria Chiara
Santone, Antonella
Avella, Pasquale
Bianco, Paolo
Scacchi, Andrea
Scaglione, Mariano
Bellifemine, Fabio
Danzi, Roberta
Varriano, Giulia
Vallone, Gianfranco
Calise, Fulvio
Brunese, Luca
Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study
title Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study
title_full Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study
title_fullStr Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study
title_full_unstemmed Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study
title_short Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study
title_sort early diagnosis of liver metastases from colorectal cancer through ct radiomics and formal methods: a pilot study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8745238/
https://www.ncbi.nlm.nih.gov/pubmed/35011771
http://dx.doi.org/10.3390/jcm11010031
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