Literature DB >> 34797688

Overview of radiomics in prostate imaging and future directions.

Hwan-Ho Cho1,2, Chan Kyo Kim3, Hyunjin Park2,4.   

Abstract

Recent advancements in imaging technology and analysis methods have led to an analytic framework known as radiomics. This framework extracts comprehensive high-dimensional features from imaging data and performs data mining to build analytical models for improved decision-support. Its features include many categories spanning texture and shape; thus, it can provide abundant information for precision medicine. Many studies of prostate radiomics have shown promising results in the assessment of pathological features, prediction of treatment response, and stratification of risk groups. Herein, we aimed to provide a general overview of radiomics procedures, discuss technical issues, explain various clinical applications, and suggest future research directions, especially for prostate imaging.

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Year:  2021        PMID: 34797688      PMCID: PMC8978251          DOI: 10.1259/bjr.20210539

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  91 in total

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2.  Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.

Authors:  Prateek Prasanna; Jay Patel; Sasan Partovi; Anant Madabhushi; Pallavi Tiwari
Journal:  Eur Radiol       Date:  2016-10-24       Impact factor: 5.315

Review 3.  Inflammation in prostate carcinogenesis.

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Journal:  Nat Rev Cancer       Date:  2007-04       Impact factor: 60.716

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Authors:  Maciej A Mazurowski
Journal:  J Am Coll Radiol       Date:  2015-08       Impact factor: 5.532

5.  MRI phenotype of the prostate: Transition zone radiomics analysis improves explanation of prostate-specific antigen (PSA) serum level compared to volume measurement alone.

Authors:  Tobias Krauss; Hannes Engel; Cordula A Jilg; Christian Gratzke; Fabian Bamberg; Matthias Benndorf
Journal:  Eur J Radiol       Date:  2020-05-12       Impact factor: 3.528

6.  Codifying collegiality: recent developments in data sharing policy in the life sciences.

Authors:  Genevieve Pham-Kanter; Darren E Zinner; Eric G Campbell
Journal:  PLoS One       Date:  2014-09-26       Impact factor: 3.240

7.  Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.

Authors:  Mehdi Alilou; Mahdi Orooji; Niha Beig; Prateek Prasanna; Prabhakar Rajiah; Christopher Donatelli; Vamsidhar Velcheti; Sagar Rakshit; Michael Yang; Frank Jacono; Robert Gilkeson; Philip Linden; Anant Madabhushi
Journal:  Sci Rep       Date:  2018-10-16       Impact factor: 4.379

8.  Deep Learning to Assess Long-term Mortality From Chest Radiographs.

Authors:  Michael T Lu; Alexander Ivanov; Thomas Mayrhofer; Ahmed Hosny; Hugo J W L Aerts; Udo Hoffmann
Journal:  JAMA Netw Open       Date:  2019-07-03

9.  Integrative Radiogenomics Approach for Risk Assessment of Post-Operative Metastasis in Pathological T1 Renal Cell Carcinoma: A Pilot Retrospective Cohort Study.

Authors:  Hye Won Lee; Hwan-Ho Cho; Je-Gun Joung; Hwang Gyun Jeon; Byong Chang Jeong; Seong Soo Jeon; Hyun Moo Lee; Do-Hyun Nam; Woong-Yang Park; Chan Kyo Kim; Seong Il Seo; Hyunjin Park
Journal:  Cancers (Basel)       Date:  2020-04-02       Impact factor: 6.639

10.  A systematic review reporting quality of radiomics research in neuro-oncology: toward clinical utility and quality improvement using high-dimensional imaging features.

Authors:  Ji Eun Park; Ho Sung Kim; Donghyun Kim; Seo Young Park; Jung Youn Kim; Se Jin Cho; Jeong Hoon Kim
Journal:  BMC Cancer       Date:  2020-01-10       Impact factor: 4.430

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  1 in total

1.  Innovations in prostate cancer: introductory editorial.

Authors:  Jurgen J Fütterer; Chan Kyo Kim; Daniel J Margolis
Journal:  Br J Radiol       Date:  2022-03       Impact factor: 3.039

  1 in total

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