Literature DB >> 29488085

The changing face of cancer diagnosis: From computational image analysis to systems biology.

Fabian Kiessling1.   

Abstract

ᅟ: KEY POINTS: • Radiomics and radiogenomics will merge radiology, nuclear medicine, pathology and laboratory medicine. • Automation of image data analysis will change the daily routine work. • Image-guided therapy and handling complex radiogenomic data will play a major role.

Entities:  

Mesh：

Substances：

Year:  2018        PMID： 29488085     DOI： 10.1007/s00330-018-5347-9

Source DB:  PubMed          Journal:  Eur Radiol        ISSN： 0938-7994            Impact factor:   5.315


  22 in total

1.  Systems biology and new technologies enable predictive and preventative medicine.

Authors:  Leroy Hood; James R Heath; Michael E Phelps; Biaoyang Lin
Journal:  Science       Date:  2004-10-22       Impact factor: 47.728

Review 2.  Imaging features of myeloproliferative neoplasms.

Authors:  I G Murphy; E L Mitchell; L Raso-Barnett; A L Godfrey; E M Godfrey
Journal:  Clin Radiol       Date:  2017-06-12       Impact factor: 2.350

Review 3.  Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

Authors:  Carl A K Borrebaeck
Journal:  Nat Rev Cancer       Date:  2017-02-03       Impact factor: 60.716

Review 4.  Radiomics: the bridge between medical imaging and personalized medicine.

Authors:  Philippe Lambin; Ralph T H Leijenaar; Timo M Deist; Jurgen Peerlings; Evelyn E C de Jong; Janita van Timmeren; Sebastian Sanduleanu; Ruben T H M Larue; Aniek J G Even; Arthur Jochems; Yvonka van Wijk; Henry Woodruff; Johan van Soest; Tim Lustberg; Erik Roelofs; Wouter van Elmpt; Andre Dekker; Felix M Mottaghy; Joachim E Wildberger; Sean Walsh
Journal:  Nat Rev Clin Oncol       Date:  2017-10-04       Impact factor: 66.675

5.  Breast Cancer: Computer-aided Detection with Digital Breast Tomosynthesis.

Authors:  Lia Morra; Daniela Sacchetto; Manuela Durando; Silvano Agliozzo; Luca Alessandro Carbonaro; Silvia Delsanto; Barbara Pesce; Diego Persano; Giovanna Mariscotti; Vincenzo Marra; Paolo Fonio; Alberto Bert
Journal:  Radiology       Date:  2015-05-11       Impact factor: 11.105

Review 6.  Molecular tools for companion diagnostics.

Authors:  Agata Zieba; Karin Grannas; Ola Söderberg; Mats Gullberg; Mats Nilsson; Ulf Landegren
Journal:  N Biotechnol       Date:  2012-05-24       Impact factor: 5.079

7.  Pulmonary subsolid nodules: value of semi-automatic measurement in diagnostic accuracy, diagnostic reproducibility and nodule classification agreement.

Authors:  Hyungjin Kim; Chang Min Park; Eui Jin Hwang; Su Yeon Ahn; Jin Mo Goo
Journal:  Eur Radiol       Date:  2017-12-01       Impact factor: 5.315

Review 8.  Cancer pharmacogenomics, challenges in implementation, and patient-focused perspectives.

Authors:  Jai N Patel
Journal:  Pharmgenomics Pers Med       Date:  2016-07-12

Review 9.  Radiogenomic Analysis of Oncological Data: A Technical Survey.

Authors:  Mariarosaria Incoronato; Marco Aiello; Teresa Infante; Carlo Cavaliere; Anna Maria Grimaldi; Peppino Mirabelli; Serena Monti; Marco Salvatore
Journal:  Int J Mol Sci       Date:  2017-04-12       Impact factor: 5.923

Review 10.  Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

Authors:  Bram van Ginneken
Journal:  Radiol Phys Technol       Date:  2017-02-16
View more
  11 in total

1.  Differentiation of clear cell and non-clear cell renal cell carcinomas by all-relevant radiomics features from multiphase CT: a VHL mutation perspective.

Authors:  Zhi-Cheng Li; Guangtao Zhai; Jinheng Zhang; Zhongqiu Wang; Guiqin Liu; Guang-Yu Wu; Dong Liang; Hairong Zheng
Journal:  Eur Radiol       Date:  2018-12-06       Impact factor: 5.315

2.  Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Authors:  Yanfen Cui; Xiaotang Yang; Zhongqiang Shi; Zhao Yang; Xiaosong Du; Zhikai Zhao; Xintao Cheng
Journal:  Eur Radiol       Date:  2018-08-20       Impact factor: 5.315

3.  MRI-Based Radiomics Models to Discriminate Hepatocellular Carcinoma and Non-Hepatocellular Carcinoma in LR-M According to LI-RADS Version 2018.

Authors:  Haiping Zhang; Dajing Guo; Huan Liu; Xiaojing He; Xiaofeng Qiao; Xinjie Liu; Yangyang Liu; Jun Zhou; Zhiming Zhou; Xi Liu; Zheng Fang
Journal:  Diagnostics (Basel)       Date:  2022-04-21

4.  Clinical-radiomics nomograms for pre-operative differentiation of sacral chordoma and sacral giant cell tumor based on 3D computed tomography and multiparametric magnetic resonance imaging.

Authors:  Ping Yin; Ning Mao; Sicong Wang; Chao Sun; Nan Hong
Journal:  Br J Radiol       Date:  2019-07-09       Impact factor: 3.039

5.  A preclinical micro-computed tomography database including 3D whole body organ segmentations.

Authors:  Stefanie Rosenhain; Zuzanna A Magnuska; Grace G Yamoah; Wa'el Al Rawashdeh; Fabian Kiessling; Felix Gremse
Journal:  Sci Data       Date:  2018-12-18       Impact factor: 6.444

6.  Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer.

Authors:  Yuqiang Li; Wenxue Liu; Qian Pei; Lilan Zhao; Cenap Güngör; Hong Zhu; Xiangping Song; Chenglong Li; Zhongyi Zhou; Yang Xu; Dan Wang; Fengbo Tan; Pei Yang; Haiping Pei
Journal:  Cancer Med       Date:  2019-10-22       Impact factor: 4.452

7.  Preoperative Prediction of Extramural Venous Invasion in Rectal Cancer: Comparison of the Diagnostic Efficacy of Radiomics Models and Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Authors:  Xiangling Yu; Wenlong Song; Dajing Guo; Huan Liu; Haiping Zhang; Xiaojing He; Junjie Song; Jun Zhou; Xinjie Liu
Journal:  Front Oncol       Date:  2020-04-09       Impact factor: 6.244

Review 8.  Role of MRI‑based radiomics in locally advanced rectal cancer (Review).

Authors:  Siyu Zhang; Mingrong Yu; Dan Chen; Peidong Li; Bin Tang; Jie Li
Journal:  Oncol Rep       Date:  2021-12-22       Impact factor: 3.906

9.  Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer.

Authors:  Zhuokai Zhuang; Zongchao Liu; Juan Li; Xiaolin Wang; Peiyi Xie; Fei Xiong; Jiancong Hu; Xiaochun Meng; Meijin Huang; Yanhong Deng; Ping Lan; Huichuan Yu; Yanxin Luo
Journal:  J Transl Med       Date:  2021-06-10       Impact factor: 5.531

10.  Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?

Authors:  Mark Bukowski; Robert Farkas; Oya Beyan; Lorna Moll; Horst Hahn; Fabian Kiessling; Thomas Schmitz-Rode
Journal:  Eur Radiol       Date:  2020-05-06       Impact factor: 5.315
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.