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Radiomics and Imaging Genomics in Precision Medicine Precision and Future Medicine 2017;1(1):10-31 REVIEW https://doi.org/10.23838/pfm.2017.00101 ARTICLE pISSN: 2508-7940 · eISSN: 2508-7959 Radiomics and imaging genomics in precision medicine 1,2 1 1 1 Geewon Lee , Ho Yun Lee , Eun Sook Ko , Woo Kyoung Jeong 1 DepartmentofRadiologyandCenterforImagingScience,SamsungMedicalCenter,SungkyunkwanUniversitySchoolof Medicine,Seoul,Korea 2 DepartmentofRadiologyandMedicalResearchInstitute,PusanNationalUniversityHospital,PusanNationalUniversitySchool ofMedicine,Busan,Korea Received: February 3, 2017 Revised: February 18, 2017 Accepted: February 24, 2017 ABSTRACT “Radiomics,”afieldofstudyinwhichhigh-throughputdataisextractedandlargeamo- Corresponding author: Ho Yun Lee untsofadvancedquantitativeimagingfeaturesareanalyzedfrommedicalimages,and Department of Radiology and “imaginggenomics,”thefieldofstudyofhigh-throughputmethodsofassociatingimag- Center for Imaging Science, ingfeatureswithgenomicdata,hasgatheredacademicinterest.However,aradiomics Samsung Medical Center, andimaginggenomicsapproachintheoncologyworldisstillinitsveryearlystages Sungkyunkwan University andmanyproblemsremaintobesolved.Inthisreview,wewilllookthroughthestepsof School of Medicine, 81 Irwon-ro, radiomicsandimaginggenomicsinoncology,specificallyaddressingpotentialapplica- Gangnam-gu, Seoul 06351, Korea tionsineachorganandfocusingontechnicalissues. Tel: +82-2-3410-2502 E-mail: [email protected] Keywords:Imaginggenomics;Neoplasms;Radiomics INTRODUCTION Medicalimagingsuchascomputedtomography(CT),positronemissiontomography(PET),or magneticresonanceimaging(MRI)ismandatoryinthediagnosis,staging,treatmentplanning, postoperativesurveillance,andresponseevaluationintheroutinemanagementofcancer.Al- thoughtheseconventionalmodalitiesprovideimportantinformationoncancerphenotypes, yetagreatdealofgeneticandprognosticinformationremainsunrevealed. Recently,thereisuniversalunderstandingthatgenomicheterogeneityexistsamongand evenwithintumorsandthatthosedifferencescanplayanimportantroleindeterminingthe likelihoodofaclinicalresponsetotreatmentwithparticularagents[1-4].Inotherwords,the successofprecisionmedicinerequiresaclearunderstandingofeachpatient’stumoralhetero- geneityandindividualsituation. This is an Open Access article Here,“radiomics,”afieldofstudyinwhichhigh-throughputdataisextractedandlargeamounts distributed under the terms of the ofadvancedquantitativeimagingfeaturesareanalyzedfrommedicalimages,and“imaging Creative Commons Attribution genomics,”thefieldofstudyofhigh-throughputmethodsofassociatingimagingfeatureswith Non-Commercial License (http:// creativecommons.org/licenses/ genomicdata,hasgatheredacademicinterest.Inotherwords,investigatorshavesuggested by-nc/4.0/). thatthehiddeninformationembeddedinmedicalimagesmaybecomeutilizedthroughthese Copyright © 2017 Sungkyunkwan University School of Medicine 10 GeewonLee,etal. robustapproaches.Indeed,severalrecentstudiesemploying value,suchasthe75thpercentileCTattenuationvaluefrom radiomicsandimaginggenomicshavebeenfoundtobeuse- histograms,hasbeenreportedasasignificantdifferentiation fulinquantifyingoveralltumorspatialcomplexityandiden- factorforinvasiveadenocarcinomas[118].Furthermore,the tifyingthetumorsubregionsthatdrivediseasetransforma- 97.5thpercentileCTattenuationvalueandtheslopeofCT tion,progression,anddrugresistance[5-9].Inthisreview,we attenuationvalueshavebeensuggestedaspredictorsforfu- willlookthroughallstepsofradiomicsandimaginggenom- tureCTattenuationchangesandthegrowthrateofpureGGO icsinoncology,specificallyaddressingpotentialapplications lesions[119].Overall,lungcancer-specific(GGO-related)ra- ineachorganandfocusingontechnicalissues. diomicfeaturescouldprovideadditionalinformationabout tumorinvasivenessandprogressionfromotherindolentor Thorax non-invasivelesionsandevenpredicttumorgrowth(Fig.1). Lung Tworecentinvestigationssupporttheimportanceofintratu- Breast morsubregionalpartitioningusingmultiparametricimages Thispartofthereviewwillbefocusedonradiomicsandim- [7,10].Inonestudy,researcherssuccessfullydividedatumor aginggenomicresearchesinbreastimagingusingMRItex- intonecroticregionsandviableregionsbyincorporating tureanalysis.Radiomicresearchhasbeenappliedtodetect 18F-fluorodeoxyglucose(18F-FDG)PETanddiffusion-weight- microcalcifications[120],differentiatebenignfrommalig- edMRI,whichshowedgoodagreementwithhistology[7].In nantlesions[121-123],anddistinguishbetweenbreastcan- theotherstudy,researchersidentifiedclinicallyrelevant,high- cersubtypes[124,125].Jamesetal.[120]hypothesizedthe risksubregionsinlungcancerusingintratumorpartitioning magneticsusceptibilityofmicrocalcificationsleadstodirec- of18FFDG-PETandCTimages[10]. tionalblurringeffectswhichcanbedetectedbystatistical Overall,manystudieshaveshownthattexturalfeaturesare imageprocessing.Intheirresults,theirmethodcoulddetect associatedwithtumorstage,metastasis,response,survival, localizedblurringwithhighdiagnosticperformance.Regard- andmetagenesinlungcancer[11-16];thereby,providingev- ingthedifferentiationbetweenbenignandmalignancy,sev- idencethattexturalfeaturesshowsubstantialpromiseasprog- eralstudieshavefoundthattexturefeaturesmaydifferbe- nosticindicatorsinthoraciconcology.Tables1,2demonstrate tweenthem.Inthebreasttwo-dimensionalco-occurrence thecurrentliteratureaboutradiomicsandimaginggenomics matrixfeaturesofdynamiccontrast-enhanced(DCE)MRIim- inthefieldofclinicaloncology[16-111]. agesandsignalenhancementratiomaps,three-dimensional Inparallelwiththe2011TheInternationalAssociationfor andfour-dimensionalfeaturesmaybefeasibleindistinguish- theStudyofLungCancer(IASLC)/TheAmericanThoracicSo- ingbetweenbenignandmalignantbreastlesions[121-123]. ciety(ATS)/TheEuropeanRespiratorySociety(ERS)classifi- Hollietal.[124]haveinvestigatedtodifferentiateinvasive cationforlungadenocarcinomas,anextensivevolumeoflit- lobularcarcinoma(ILC)andinvasiveductalcarcinoma(IDC) eraturehascoveredthesubsetofsubsolidnodules,which byusingdifferenttexturemethods.Inthisstudy,co-occur- correlateswiththespectrumoflungadenocarcinoma.Of rencematrixfeaturesweresignificantlydifferentbetween particularimportanceisthesignificanceofthepresenceand ILCandIDC,allowingdifferentiationbetweenthesetwohis- degreeofapathologicallyinvasiveportion,namelythethick- tologicalsubtypes.Further,thesefeaturesweresuperiorto eningofalveolarseptaandincreasedcellularity[112,113]. theothertexturemethodsappliedincludinghistogramanal- Althoughapproximatelyhalfofpureground-glassopacity ysis,run-lengthmatrix,autoregressivemodel,andwavelet (GGO)noduleshavebeenreportedtohaveapathologically transform[124]. invasivecomponent,discriminationbetweentheinvasive RegardingtextureanalysisofbreastMRimages,thistech- andnon-invasiveproportionsremainschallenginginpure niquehasbeenappliedtopredicttreatmentresponse[126]. GGOlesionsbecauseoflimitedvisualperceptionandsubjec- Parikhetal.[126]evaluatedwhetherchangesinMRItexture tiveanalysisofconventionalCTscans[114,115].Severalin- featurescanpredictpathologiccompleteresponse(pCR)to vestigatorshavedemonstratedthatquantificationandfea- neoadjuvantchemotherapy.Intheirstudyconductedin36 tureextractionofGGOlesions(usingnumericalvalues)can consecutiveprimarybreastcancerpatients,anincreasein findsmallpathologicallyinvasivecomponents,whicharere- T2-weightedMRIuniformityandadecreaseinT2-weighted flectedatthemedicalimagingvoxellevelandotherwisenot MRIentropyafterneoadjuvantchemotherapymaybehelp- visuallydetectable[116-118].Entropyorahighattenuation fulinearlierpredictingpCRthantumorsizechange. https://doi.org/10.23838/pfm.2017.00101 11 Radiomicsandimaginggenomics Table 1. Radiomics studies of clinical oncology published in literature No. of Study Cancer type Modality Country patients Pauletal.(2016)[24] 65 Esophagealcancer PET France Huynhetal.(2017)[25] 112 Lungcancer CT USA Luetal.(2016)[26] 32 Lungcancer CT USA Lopezetal.(2017)[27] 17 Braincancer MRI USA Yuetal.(2016)[28] 110 Braincancer MRI China Ginsburgetal.(2016)[29] 80 Prostatecancer MRI USA Yuetal.(2017)[30] 92 Braincancer MRI China Songetal.(2016)[31] 339 Lungcancer CT Korea Corolleretal.(2017)[32] 85 Lungcancer CT USA Bogowiczetal.(2016)[33] 11 Oropharyngealcancer CT Switzerland 11 Lungcancer Baeetal.(2017)[34] 80 Lungcancer CT Korea Prasannaetal.(2016)[35] 42 Braincancer MRI USA 65 Breastcancer MRI 120 Lungcancer CT Lohmannetal.(2016)[36] 47 Braincancer MRI Germany PET Lietal.(2016)[37] 91 Breastcancer MRI USA Shiradkaretal.(2016)[38] 23 Prostatecancer MRI USA Kickingerederetal.(2016)[39] 172 Braincancer MRI Germany Grootjansetal.(2016)[40] 60 Lungcancer PET TheNetherlands Nieetal.(2016)[41] 48 RectalCancer MRI USA Prasannaetal.(2016)[42] 65 Braincancer MRI USA McGarryetal.(2016)[43] 81 Braincancer MRI USA Desseroitetal.(2016)[44] 74 Lungcancer PET France CT Lietal.(2016)[21] 84 Breastcancer MRI USA Yipetal.(2016)[45] 348 Lungcancer PET USA Huetal.(2016)[46] 40 RectalCancer CT China Gieseletal.(2017)[47] 148 Lungcancer PET/CT Germany Malignantmelanoma Gastroenteropancreaticneuroendocrinetumours Prostatecancer Aertsetal.(2016)[48] 47 Lungcancer CT USA Huynhetal.(2016)[49] 219 Breastcancer Mammography USA Choietal.(2016)[50] 89 Lungcancer CT Korea Permuthetal.(2016)[51] 38 Pancreaticcancer CT USA Hananiaetal.(2016)[52] 53 Pancreaticcancer CT USA Flechsigetal.(2016)[53] 122 Lungcancer PET/CT Germany Oliveretal.(2016)[54] 31 Lungcancer PET/CT USA (Continuedtothenextpage) 12 http://pfmjournal.org GeewonLee,etal. Table 1. Continued No. of Study Cancer type Modality Country patients Grossmannetal.(2016)[55] 141 Braincancer MRI USA Hawkinsetal.(2016)[56] 196 Lungcancer CT USA Obeidetal.(2017)[57]
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