Radiomics and radiomic features
Radiomics is a method that aims to extract a large number of features from medical images, using data-characterisation algorithms.
The set of features can be divided into a number of families, such as intensity-based statistical, intensity histogram-based, intensity-volume histogram-based, morphological features, local intensity, texture matrix-based features, etc. To calculate features, it is assumed that an image segmentation mask exists, which identifies the voxels located within a region of interest (ROI).
The image biomarker standardisation initiative (IBSI, [Zwanenburg 2020]) is an independent international collaboration which works towards standardising the extraction of image biomarkers (image features) from acquired imaging for the purpose of high-throughput quantitative image analysis (radiomics).
Example
Segmentation process (data from ACRIN-FLT-Breast. The Cancer Imaging Archive, [Kinahan, 2017]), using Slicer 3D software [Fedorov, 2012]:
Image type | Feature Class | Feature Name | Segmentation_segment_Segment_1 | Segmentation_segment_Segment_2 |
---|---|---|---|---|
diagnostics | Versions | PyRadiomics | v3.0.1.post4+gad5b2de | v3.0.1.post4+gad5b2de |
diagnostics | Versions | Numpy | 1.19.2 | 1.19.2 |
diagnostics | Versions | SimpleITK | 2.0.2 | 2.0.2 |
diagnostics | Versions | PyWavelet | 1.1.1 | 1.1.1 |
diagnostics | Versions | Python | 3.6.7 | 3.6.7 |
diagnostics | Configuration | Settings | {’minimumROIDimensions’: 2, 'minimumROISize’: None, 'normalize’: False, 'normalizeScale’: 1, 'removeOutliers’: None, 'resampledPixelSpacing’: None, 'interpolator’: 'sitkBSpline’, 'preCrop’: False, 'padDistance’: 5, 'distances’: [1], 'force2D’: False, 'force2Ddimension’: 0, 'resegmentRange’: None, 'label’: 1, 'additionalInfo’: True, 'binWidth’: 25.0, 'symmetricalGLCM’: True, 'correctMask’: True} | {’minimumROIDimensions’: 2, 'minimumROISize’: None, 'normalize’: False, 'normalizeScale’: 1, 'removeOutliers’: None, 'resampledPixelSpacing’: None, 'interpolator’: 'sitkBSpline’, 'preCrop’: False, 'padDistance’: 5, 'distances’: [1], 'force2D’: False, 'force2Ddimension’: 0, 'resegmentRange’: None, 'label’: 1, 'additionalInfo’: True, 'binWidth’: 25.0, 'symmetricalGLCM’: True, 'correctMask’: True} |
diagnostics | Configuration | EnabledImageTypes | {’Original’: {}} | {’Original’: {}} |
diagnostics | Image-original | Hash | 533a438effd3030eeb0cea7ca74e9f5887af4945 | 533a438effd3030eeb0cea7ca74e9f5887af4945 |
diagnostics | Image-original | Dimensionality | 3D | 3D |
diagnostics | Image-original | Spacing | (3.90625, 3.90625, 4.25) | (3.90625, 3.90625, 4.25) |
diagnostics | Image-original | Size | (128, 128, 239) | (128, 128, 239) |
diagnostics | Image-original | Mean | 22.01189889 | 22.01189889 |
diagnostics | Image-original | Minimum | 0 | 0 |
diagnostics | Image-original | Maximum | 2486.789208 | 2486.789208 |
diagnostics | Mask-original | Hash | 233cb5136e729a3e4f21362aca4475c2ce7026e1 | c3c38c72291849f4c9fd08f3f2350db65cd702d3 |
diagnostics | Mask-original | Spacing | (3.90625, 3.90625, 4.25) | (3.90625, 3.90625, 4.25) |
diagnostics | Mask-original | Size | (128, 128, 239) | (128, 128, 239) |
diagnostics | Mask-original | BoundingBox | (72, 72, 94, 8, 15, 11) | (39, 71, 93, 10, 12, 10) |
diagnostics | Mask-original | VoxelNum | 541 | 443 |
diagnostics | Mask-original | VolumeNum | 1 | 1 |
diagnostics | Mask-original | CenterOfMassIndex | (75.80406654343808, 78.79112754158965, 98.68022181146026) | (43.63205417607224, 76.4334085778781, 97.2686230248307) |
diagnostics | Mask-original | CenterOfMass | (46.109634935304996, 57.77784195933458, -601.1090573012939) | (-79.56228837471781, 48.56800225733633, -607.1083521444696) |
original | shape | Elongation | 0.718428907 | 0.844158396 |
original | shape | Flatness | 0.520675964 | 0.600962385 |
original | shape | LeastAxisLength | 26.82559939 | 26.77934631 |
original | shape | MajorAxisLength | 51.52071776 | 44.56076951 |
original | shape | Maximum2DDiameterColumn | 45.28123922 | 48.53417771 |
original | shape | Maximum2DDiameterRow | 59.20707339 | 41.31831464 |
original | shape | Maximum2DDiameterSlice | 59.75413492 | 48.94517221 |
original | shape | Maximum3DDiameter | 59.90508443 | 50.13637651 |
original | shape | MeshVolume | 34381.23067 | 27977.30764 |
original | shape | MinorAxisLength | 37.01397296 | 37.61634771 |
original | shape | Sphericity | 0.81721643 | 0.792830881 |
original | shape | SurfaceArea | 6256.930251 | 5621.35284 |
original | shape | SurfaceVolumeRatio | 0.181986803 | 0.20092544 |
original | shape | VoxelVolume | 35083.77075 | 28728.48511 |
original | firstorder | 10Percentile | 296.780922 | 196.64847 |
original | firstorder | 90Percentile | 1729.293089 | 1081.286734 |
original | firstorder | Energy | 550714072.8 | 173841865.9 |
original | firstorder | Entropy | 5.880349771 | 5.144364146 |
original | firstorder | InterquartileRange | 826.7166258 | 456.6205522 |
original | firstorder | Kurtosis | 2.749790628 | 4.095834657 |
original | firstorder | Maximum | 2486.789208 | 1871.7509 |
original | firstorder | MeanAbsoluteDeviation | 468.9773551 | 281.3159101 |
original | firstorder | Mean | 839.3567999 | 517.6909538 |
original | firstorder | Median | 628.6984404 | 387.1992456 |
original | firstorder | Minimum | 190.4121598 | 147.7359567 |
original | firstorder | Range | 2296.377048 | 1724.014944 |
original | firstorder | RobustMeanAbsoluteDeviation | 352.5233463 | 195.2900155 |
original | firstorder | RootMeanSquared | 1008.937943 | 626.4340044 |
original | firstorder | Skewness | 0.940244297 | 1.300753755 |
original | firstorder | TotalEnergy | 35713726953 | 11273619540 |
original | firstorder | Uniformity | 0.022348564 | 0.039179817 |
original | firstorder | Variance | 313435.9349 | 124415.6382 |
original | glcm | Autocorrelation | 1337.177605 | 490.8682935 |
original | glcm | ClusterProminence | 7067328.506 | 1486133.703 |
original | glcm | ClusterShade | 46339.60226 | 16679.47707 |
original | glcm | ClusterTendency | 1713.395114 | 672.7994778 |
original | glcm | Contrast | 434.092444 | 205.4518274 |
original | glcm | Correlation | 0.599616154 | 0.537346338 |
original | glcm | DifferenceAverage | 15.79439971 | 10.98590189 |
original | glcm | DifferenceEntropy | 5.25598161 | 4.770647602 |
original | glcm | DifferenceVariance | 175.1626669 | 80.70159972 |
original | glcm | Id | 0.143851838 | 0.186220415 |
original | glcm | Idm | 0.07537084 | 0.110098784 |
original | glcm | Idmn | 0.956825044 | 0.962847097 |
original | glcm | Idn | 0.866847358 | 0.874617615 |
original | glcm | Imc1 | -0.456304457 | -0.371594794 |
original | glcm | Imc2 | 0.998000784 | 0.990742836 |
original | glcm | InverseVariance | 0.079726888 | 0.10876887 |
original | glcm | JointAverage | 31.88255748 | 19.33349937 |
original | glcm | JointEnergy | 0.001693794 | 0.002769738 |
original | glcm | JointEntropy | 9.356114223 | 8.757717212 |
original | glcm | MCC | 0.712991455 | 0.66080859 |
original | glcm | MaximumProbability | 0.006333344 | 0.010531668 |
original | glcm | SumAverage | 63.76511495 | 38.66699874 |
original | glcm | SumEntropy | 6.818176686 | 6.143977009 |
original | glcm | SumSquares | 536.8718896 | 219.5628263 |
original | gldm | DependenceEntropy | 6.843322445 | 6.415485289 |
original | gldm | DependenceNonUniformity | 261.3770795 | 152.4266366 |
original | gldm | DependenceNonUniformityNormalized | 0.483136931 | 0.344078186 |
original | gldm | DependenceVariance | 0.634472344 | 0.853955944 |
original | gldm | GrayLevelNonUniformity | 12.09057301 | 17.35665914 |
original | gldm | GrayLevelVariance | 501.8990368 | 198.4882776 |
original | gldm | HighGrayLevelEmphasis | 1235.898336 | 461.1038375 |
original | gldm | LargeDependenceEmphasis | 2.881700555 | 4.205417607 |
original | gldm | LargeDependenceHighGrayLevelEmphasis | 2880.072089 | 1383.89842 |
original | gldm | LargeDependenceLowGrayLevelEmphasis | 0.049963494 | 0.146062888 |
original | gldm | LowGrayLevelEmphasis | 0.014439637 | 0.030611278 |
original | gldm | SmallDependenceEmphasis | 0.713459129 | 0.551884249 |
original | gldm | SmallDependenceHighGrayLevelEmphasis | 941.3063273 | 300.2885403 |
original | gldm | SmallDependenceLowGrayLevelEmphasis | 0.009915324 | 0.014809438 |
original | glrlm | GrayLevelNonUniformity | 11.70994981 | 16.51195929 |
original | glrlm | GrayLevelNonUniformityNormalized | 0.022068484 | 0.03850109 |
original | glrlm | GrayLevelVariance | 501.3122804 | 199.2892289 |
original | glrlm | HighGrayLevelRunEmphasis | 1241.486747 | 465.9229893 |
original | glrlm | LongRunEmphasis | 1.059378422 | 1.10049669 |
original | glrlm | LongRunHighGrayLevelEmphasis | 1298.7777 | 497.3345847 |
original | glrlm | LongRunLowGrayLevelEmphasis | 0.015422869 | 0.034045554 |
original | glrlm | LowGrayLevelRunEmphasis | 0.014378364 | 0.030441998 |
original | glrlm | RunEntropy | 5.976110053 | 5.310844322 |
original | glrlm | RunLengthNonUniformity | 510.5775347 | 402.0003095 |
original | glrlm | RunLengthNonUniformityNormalized | 0.962181014 | 0.937159747 |
original | glrlm | RunPercentage | 0.980804777 | 0.968050009 |
original | glrlm | RunVariance | 0.019765585 | 0.032984177 |
original | glrlm | ShortRunEmphasis | 0.985477316 | 0.975477745 |
original | glrlm | ShortRunHighGrayLevelEmphasis | 1227.934367 | 458.0863265 |
original | glrlm | ShortRunLowGrayLevelEmphasis | 0.01412371 | 0.029570304 |
original | glszm | GrayLevelNonUniformity | 8.225653207 | 8.724381625 |
original | glszm | GrayLevelNonUniformityNormalized | 0.019538369 | 0.030828204 |
original | glszm | GrayLevelVariance | 496.6355866 | 204.9185281 |
original | glszm | HighGrayLevelZoneEmphasis | 1312.477435 | 529.4275618 |
original | glszm | LargeAreaEmphasis | 2.315914489 | 3.643109541 |
original | glszm | LargeAreaHighGrayLevelEmphasis | 2311.304038 | 1293.833922 |
original | glszm | LargeAreaLowGrayLevelEmphasis | 0.0399263 | 0.134434019 |
original | glszm | LowGrayLevelZoneEmphasis | 0.013797431 | 0.027308059 |
original | glszm | SizeZoneNonUniformity | 290.2684086 | 147.3745583 |
original | glszm | SizeZoneNonUniformityNormalized | 0.689473655 | 0.520758157 |
original | glszm | SmallAreaEmphasis | 0.856105631 | 0.749508706 |
original | glszm | SmallAreaHighGrayLevelEmphasis | 1148.741358 | 426.7926749 |
original | glszm | SmallAreaLowGrayLevelEmphasis | 0.011822282 | 0.019085154 |
original | glszm | ZoneEntropy | 6.607326679 | 6.315456586 |
original | glszm | ZonePercentage | 0.77818854 | 0.638826185 |
original | glszm | ZoneVariance | 0.66459792 | 1.192723096 |
original | ngtdm | Busyness | 0.095294279 | 0.244693066 |
original | ngtdm | Coarseness | 0.00917816 | 0.010024537 |
original | ngtdm | Complexity | 30438.04282 | 9770.860363 |
original | ngtdm | Contrast | 1.363559647 | 0.788477366 |
original | ngtdm | Strength | 45.03347974 | 28.76248158 |
References
Zwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J., Andrearczyk, V., Apte, A., … & Löck, S. (2020). The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology, 295(2), 328-338., https://doi.org/10.1148/radiol.2020191145
Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F.M., Sonka M., Buatti J., Aylward S.R., Miller J.V., Pieper S., Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. PMCID: PMC3466397. https://doi.org/10.1016/j.mri.2012.05.001
Kinahan, Paul; Muzi, Mark; Bialecki, Brian; Coombs, Laura. (2017). Data from ACRIN-FLT-Breast. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2017.ol20zmxg