4.1 Article

CT-based morphologic and radiomics features for the classification of MYCN gene amplification status in pediatric neuroblastoma

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer

Rasheed Omobolaji Alabi et al.

Summary: This study compared the performance of a nomogram and a machine learning model in predicting overall survival in tongue cancer patients, with the machine learning model outperforming the nomogram. Patient age, T stage, radiotherapy, and surgical resection were identified as significant features influencing the machine learning model's performance.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2021)

Article Oncology

Cancer Statistics, 2021

Rebecca L. Siegel et al.

Summary: Every year, the American Cancer Society projects the numbers of new cancer cases and deaths in the United States, with the latest data showing a significant decline in lung cancer mortality, while prostate cancer mortality has plateaued and breast and colorectal cancer mortality have slowed. Improvements in treatment have accelerated progress against lung cancer, leading to a record drop in overall cancer mortality.

CA-A CANCER JOURNAL FOR CLINICIANS (2021)

Article Oncology

A nomogram of clinical and biologic factors to predict survival in children newly diagnosed with high-risk neuroblastoma: An International Neuroblastoma Risk Group project

Lucas Moreno et al.

Summary: A novel nomogram using prognostic biomarkers has been developed to identify the subgroup of ultra-high-risk neuroblastoma patients for whom novel frontline therapy is urgently needed. The nomogram has been validated and can provide individual prognosis information at diagnosis while identifying patients predicted to have poor outcomes. This tool has the potential to facilitate testing of new treatment options to improve outcomes for high-risk neuroblastoma patients.

PEDIATRIC BLOOD & CANCER (2021)

Review Oncology

MYCN Function in Neuroblastoma Development

Jorg Otte et al.

Summary: Dysregulated expression of the transcription factor MYCN is frequently detected in nervous system tumors such as childhood neuroblastoma and is a strong predictor of poor prognosis. Increased MYCN expression is an early event in these cancers, leading to a peculiar dysregulation of cells that exhibit embryonal or cancer stem-like qualities.

FRONTIERS IN ONCOLOGY (2021)

Article Oncology

Radiogenomics prediction for MYCN amplification in neuroblastoma: A hypothesis generating study

Angela Di Giannatale et al.

Summary: This study established a radiogenomics model by correlating CT radiomics analysis with MYCN status in NB patients. The logistic regression model successfully predicted MYCN amplification status in NB patients with high accuracy. Radiomics showed high accuracy in predicting MYCN amplification status in NB.

PEDIATRIC BLOOD & CANCER (2021)

Article Biology

Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature

Zahra Khodabakhshi et al.

Summary: This study aimed to identify important features for classifying NSCLC subtypes using CT radiomics, with a focus on the gray level size zone matrix features (GLSZM). Results showed that these texture features were significant indicators for distinguishing between NSCLC subtypes, leading to an optimized classifier with high precision, recall, F1-score, and accuracy. This demonstrates the potential of CT radiomics in precision medicine and treatment planning for NSCLC patients.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Oncology

Revised Neuroblastoma Risk Classification System: A Report From the Children's Oncology Group

Meredith S. Irwin et al.

Summary: A revised neuroblastoma risk classifier incorporating INRGSS and SCAs has been validated, which may impact clinical trial eligibility and treatment assignment.

JOURNAL OF CLINICAL ONCOLOGY (2021)

Article Oncology

CT-Based Radiomics Signature With Machine Learning Predicts MYCN Amplification in Pediatric Abdominal Neuroblastoma

Xin Chen et al.

Summary: This study aimed to develop and validate CT-based machine learning models for predicting MYCN amplification in pediatric abdominal neuroblastoma. By analyzing radiographic features and radiomics signature, accurate prediction of MYCN amplification was achieved, with Logistic, SVM, and Random Forest classifiers performing well, while the Bayes classifier showed lower predictive performance. Combining clinical and radiographic qualitative features can improve the predictive performance of MYCN amplification.

FRONTIERS IN ONCOLOGY (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Radiogenomics of neuroblastoma in pediatric patients: CT-based radiomics signature in predicting MYCN amplification

Haoting Wu et al.

Summary: A CT-based radiomics signature was constructed and showed great performance in predicting MYCN amplification in pediatric patients with neuroblastoma. The clinical radiomics nomogram, incorporating radiomics signature and clinical factors, outperformed the clinical model alone for predicting MNA.

EUROPEAN RADIOLOGY (2021)

Article Statistics & Probability

Visualizing the effects of predictor variables in black box supervised learning models

Daniel W. Apley et al.

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2020)

Article Multidisciplinary Sciences

Assessing robustness of radiomic features by image perturbation

Alex Zwanenburg et al.

SCIENTIFIC REPORTS (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Radiogenomics: bridging imaging and genomics

Zuhir Bodalal et al.

ABDOMINAL RADIOLOGY (2019)

Article Pediatrics

Diagnostic ultrasound-guided cutting needle biopsies in neuroblastoma: A safe and efficient procedure

Kleopatra Georgantzi et al.

JOURNAL OF PEDIATRIC SURGERY (2019)

Review Oncology

The challenge of defining ultra-high-risk neuroblastoma

Daniel A. Morgenstern et al.

PEDIATRIC BLOOD & CANCER (2019)

Review Oncology

Repeatability and Reproducibility of Radiomic Features: A Systematic Review

Alberto Traverso et al.

INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2018)

Article Pediatrics

Evolving biopsy techniques for the diagnosis of neuroblastoma in children

Giovanni Campagna et al.

JOURNAL OF PEDIATRIC SURGERY (2018)

Article Oncology

Risk stratification of high-risk metastatic neuroblastoma: A report from the HR-NBL-1/SIOPEN study

Daniel A. Morgenstern et al.

PEDIATRIC BLOOD & CANCER (2018)

Article Radiology, Nuclear Medicine & Medical Imaging

Updates in Diagnosis, Management, and Treatment of Neuroblastoma

Caroline C. Swift et al.

RADIOGRAPHICS (2018)

Article Oncology

Computational Radiomics System to Decode the Radiographic Phenotype

Joost J. M. van Griethuysen et al.

CANCER RESEARCH (2017)

Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics: Images Are More than Pictures, They Are Data

Robert J. Gillies et al.

RADIOLOGY (2016)

Article Biochemical Research Methods

mRMRe: an R package for parallelized mRMR ensemble feature selection

Nicolas De Jay et al.

BIOINFORMATICS (2013)

Article Multidisciplinary Sciences

Signatures of mutational processes in human cancer

Ludmil B. Alexandrov et al.

NATURE (2013)

Article Pediatrics

Needle core vs open biopsy for diagnosis of intermediate- and high-risk neuroblastoma in children

Saif F. Hassan et al.

JOURNAL OF PEDIATRIC SURGERY (2012)

Article Radiology, Nuclear Medicine & Medical Imaging

3D Slicer as an image computing platform for the Quantitative Imaging Network

Andriy Fedorov et al.

MAGNETIC RESONANCE IMAGING (2012)

Article Medicine, General & Internal

Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Marco Gerlinger et al.

NEW ENGLAND JOURNAL OF MEDICINE (2012)

Article Computer Science, Interdisciplinary Applications

Anatomical Global Spatial Normalization

Jack L. Lancaster et al.

NEUROINFORMATICS (2010)

Article Oncology

The International Neuroblastoma Risk Group (INRG) Staging System: An INRG Task Force Report

Tom Monclair et al.

JOURNAL OF CLINICAL ONCOLOGY (2009)

Article Computer Science, Interdisciplinary Applications

Building Predictive Models in R Using the caret Package

Max Kuhn

JOURNAL OF STATISTICAL SOFTWARE (2008)