Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment

被引：1

作者：

Vincenza Granata

Roberta Fusco

Federica De Muzio

Maria Chiara Brunese

Sergio Venanzio Setola

Alessandro Ottaiano

Claudia Cardone

Antonio Avallone

Renato Patrone

Silvia Pradella

Vittorio Miele

Fabiana Tatangelo

Carmen Cutolo

Nicola Maggialetti

Damiano Caruso

Francesco Izzo

Antonella Petrillo

机构：

[1] Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli,Division of Radiology

[2] Igea SpA,Medical Oncology Division

[3] University of Molise,Department of Medicine and Health Sciences V. Tiberio

[4] IRCCS Fondazione G. Pascale,Clinical Experimental Abdominal Oncology Unit, Istituto Nazionale Tumori

[5] Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli,Division of Hepatobiliary Surgical Oncology

[6] Careggi University Hospital,Department of Radiology

[7] Italian Society of Medical and Interventional Radiology (SIRM),SIRM Foundation

[8] Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli,Division of Pathological Anatomy and Cytopathology

[9] University of Salerno,Department of Medicine, Surgery and Dentistry

[10] University of Bari “Aldo Moro”,Department of Medical Science, Neuroscience and Sensory Organs (DSMBNOS)

[11] Sapienza-University of Rome,Department of Medical Surgical Sciences and Translational Medicine, Radiology Unit

来源：

La radiologia medica | 2023年 / 128卷 / 11期

关键词：

Colorectal liver metastases; Radiomics analysis; Machine learning analysis; Biomarkers; Computed tomography; Magnetic resonance imaging;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

页码：1310 / 1332

页数：22

共 50 条

[1] Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment
Granata, Vincenza
Fusco, Roberta
De Muzio, Federica
Brunese, Maria Chiara
Setola, Sergio Venanzio
Ottaiano, Alessandro
Cardone, Claudia
Avallone, Antonio
Patrone, Renato
Pradella, Silvia
Miele, Vittorio
Tatangelo, Fabiana
Cutolo, Carmen
Maggialetti, Nicola
Caruso, Damiano
Izzo, Francesco
Petrillo, Antonella
RADIOLOGIA MEDICA, 2023, 128 (11): : 1310 - 1332
[2] Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases
Granata, Vincenza
Fusco, Roberta
De Muzio, Federica
Cutolo, Carmen
Setola, Sergio Venanzio
Dell'Aversana, Federica
Grassi, Francesca
Belli, Andrea
Silvestro, Lucrezia
Ottaiano, Alessandro
Nasti, Guglielmo
Avallone, Antonio
Flammia, Federica
Miele, Vittorio
Tatangelo, Fabiana
Izzo, Francesco
Petrillo, Antonella
RADIOLOGIA MEDICA, 2022, 127 (07): : 763 - 772
[3] Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases
Vincenza Granata
Roberta Fusco
Federica De Muzio
Carmen Cutolo
Sergio Venanzio Setola
Federica Dell’Aversana
Francesca Grassi
Andrea Belli
Lucrezia Silvestro
Alessandro Ottaiano
Guglielmo Nasti
Antonio Avallone
Federica Flammia
Vittorio Miele
Fabiana Tatangelo
Francesco Izzo
Antonella Petrillo
La radiologia medica, 2022, 127 : 763 - 772
[4] Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern
Granata, Vincenza
Fusco, Roberta
De Muzio, Federica
Cutolo, Carmen
Raso, Mauro Mattace
Gabelloni, Michela
Avallone, Antonio
Ottaiano, Alessandro
Tatangelo, Fabiana
Brunese, Maria Chiara
Miele, Vittorio
Izzo, Francesco
Petrillo, Antonella
DIAGNOSTICS, 2022, 12 (05)
[5] Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment
Granata, Vincenza
Fusco, Roberta
Brunese, Maria Chiara
Ferrara, Gerardo
Tatangelo, Fabiana
Ottaiano, Alessandro
Avallone, Antonio
Miele, Vittorio
Normanno, Nicola
Izzo, Francesco
Petrillo, Antonella
DIAGNOSTICS, 2024, 14 (02)
[6] Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction
Granata, Vincenza
Fusco, Roberta
Setola, Sergio Venanzio
Brunese, Maria Chiara
Di Mauro, Annabella
Avallone, Antonio
Ottaiano, Alessandro
Normanno, Nicola
Petrillo, Antonella
Izzo, Francesco
RADIOLOGIA MEDICA, 2024, 129 (07): : 957 - 966
[7] Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy
Karagkounis, Georgios
Horvat, Natally
Danilova, Sofia
Chhabra, Salini
Narayan, Raja R.
Barekzai, Ahmad B.
Kleshchelski, Adam
Joanne, Chou
Gonen, Mithat
Balachandran, Vinod
Soares, Kevin C.
Wei, Alice C.
Kingham, T. Peter
Jarnagin, William R.
Shia, Jinru
Chakraborty, Jayasree
D'Angelica, Michael I.
ANNALS OF SURGICAL ONCOLOGY, 2024,
[8] Prospective study of contrast-enhanced computed tomography, computed tomography during arterioportography, and magnetic resonance imaging for staging colorectal liver metastases for liver resection
Bhattacharjya, S
Bhattacharjya, T
Baber, S
Tibballs, JM
Watkinson, AF
Davidson, BR
BRITISH JOURNAL OF SURGERY, 2004, 91 (10) : 1361 - 1369
[9] Exploring tumor heterogeneity in colorectal liver metastases by imaging: Unsupervised machine learning of preoperative CT radiomics features for prognostic stratification
Wang, Qiang
Nilsson, Henrik
Xu, Keyang
Wei, Xufu
Chen, Danyu
Zhao, Dongqin
Hu, Xiaojun
Wang, Anrong
Bai, Guojie
EUROPEAN JOURNAL OF RADIOLOGY, 2024, 175
[10] Interobserver Variability of Gross Tumor Volume Delineation for Colorectal Liver Metastases Using Computed Tomography and Magnetic Resonance Imaging
Marshall, Cora
Thirion, Pierre
Mihai, Alina
Armstrong, John G.
Cournane, Sean
Hickey, Darina
McClean, Brendan
Quinn, John
ADVANCES IN RADIATION ONCOLOGY, 2023, 8 (01)

← 1 2 3 4 5 →