Literature DB >> 28346329

Cardiac Computed Tomography Radiomics: A Comprehensive Review on Radiomic Techniques.

Márton Kolossváry1, Miklós Kellermayer2, Béla Merkely1, Pál Maurovich-Horvat1.   

Abstract

Radiologic images are vast three-dimensional data sets in which each voxel of the underlying volume represents distinct physical measurements of a tissue-dependent characteristic. Advances in technology allow radiologists to image pathologies with unforeseen detail, thereby further increasing the amount of information to be processed. Even though the imaging modalities have advanced greatly, our interpretation of the images has remained essentially unchanged for decades. We have arrived in the era of precision medicine where even slight differences in disease manifestation are seen as potential target points for new intervention strategies. There is a pressing need to improve and expand the interpretation of radiologic images if we wish to keep up with the progress in other diagnostic areas. Radiomics is the process of extracting numerous quantitative features from a given region of interest to create large data sets in which each abnormality is described by hundreds of parameters. From these parameters datamining is used to explore and establish new, meaningful correlations between the variables and the clinical data. Predictive models can be built on the basis of the results, which may broaden our knowledge of diseases and assist clinical decision making. Radiomics is a complex subject that involves the interaction of different disciplines; our objective is to explain commonly used radiomic techniques and review current applications in cardiac computed tomography imaging.

Mesh:

Year:  2018        PMID: 28346329     DOI: 10.1097/RTI.0000000000000268

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  52 in total

Review 1.  Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future.

Authors:  Muhammad Javed Iqbal; Zeeshan Javed; Haleema Sadia; Ijaz A Qureshi; Asma Irshad; Rais Ahmed; Kausar Malik; Shahid Raza; Asif Abbas; Raffaele Pezzani; Javad Sharifi-Rad
Journal:  Cancer Cell Int       Date:  2021-05-21       Impact factor: 5.722

2.  Correlation of texture analysis of paraspinal musculature on MRI with different clinical endpoints: Lumbar Stenosis Outcome Study (LSOS).

Authors:  Manoj Mannil; Jakob M Burgstaller; Ulrike Held; Mazda Farshad; Roman Guggenberger
Journal:  Eur Radiol       Date:  2018-06-14       Impact factor: 5.315

Review 3.  Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

Authors:  Faiq Shaikh; Benjamin Franc; Erastus Allen; Evis Sala; Omer Awan; Kenneth Hendrata; Safwan Halabi; Sohaib Mohiuddin; Sana Malik; Dexter Hadley; Rasu Shrestha
Journal:  J Am Coll Radiol       Date:  2018-02-01       Impact factor: 5.532

4.  Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease.

Authors:  Evangelos K Oikonomou; Musib Siddique; Charalambos Antoniades
Journal:  Cardiovasc Res       Date:  2020-11-01       Impact factor: 10.787

Review 5.  Plaque imaging with CT-a comprehensive review on coronary CT angiography based risk assessment.

Authors:  Márton Kolossváry; Bálint Szilveszter; Béla Merkely; Pál Maurovich-Horvat
Journal:  Cardiovasc Diagn Ther       Date:  2017-10

Review 6.  Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease.

Authors:  Andrew Lin; Márton Kolossváry; Manish Motwani; Ivana Išgum; Pál Maurovich-Horvat; Piotr J Slomka; Damini Dey
Journal:  Radiol Cardiothorac Imaging       Date:  2021-02-25

7.  Identification of High-Risk Left Ventricular Hypertrophy on Calcium Scoring Cardiac Computed Tomography Scans: Validation in the DHS.

Authors:  Fernando U Kay; Suhny Abbara; Parag H Joshi; Sonia Garg; Amit Khera; Ronald M Peshock
Journal:  Circ Cardiovasc Imaging       Date:  2020-02-18       Impact factor: 7.792

8.  Myocardial Infarction Associates With a Distinct Pericoronary Adipose Tissue Radiomic Phenotype: A Prospective Case-Control Study.

Authors:  Andrew Lin; Márton Kolossváry; Jeremy Yuvaraj; Sebastien Cadet; Priscilla A McElhinney; Cathy Jiang; Nitesh Nerlekar; Stephen J Nicholls; Piotr J Slomka; Pál Maurovich-Horvat; Dennis T L Wong; Damini Dey
Journal:  JACC Cardiovasc Imaging       Date:  2020-08-26

Review 9.  Artificial intelligence in radiology.

Authors:  Ahmed Hosny; Chintan Parmar; John Quackenbush; Lawrence H Schwartz; Hugo J W L Aerts
Journal:  Nat Rev Cancer       Date:  2018-08       Impact factor: 60.716

Review 10.  Data Analysis Strategies in Medical Imaging.

Authors:  Chintan Parmar; Joseph D Barry; Ahmed Hosny; John Quackenbush; Hugo J W L Aerts
Journal:  Clin Cancer Res       Date:  2018-03-26       Impact factor: 12.531

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