2017 AAPM Annual Meeting
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Session Title: Radiomics for Lung Cancer
Question 1: Which of following is not a radiomics feature? 
Reference:Sarah A. Mattonen et al, Detection of Local Cancer Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer: Physician Performance Versus Radiomic Assessment. Int J Radiation Oncol Biol Phys, Vol. 94, No. 5, pp. 1121-1128, 2016 http://dx.doi.org/10.1016/j.ijrobp.2015.12.369
Choice A:Grey-level co-occurrence matrix correlation.
Choice B:Grey-level co-occurrence matrix energy.
Choice C:Grey-level co-occurrence matrix homogeneity.
Choice D:Morphology.
Choice E:Mean Dose.
Question 2: Which of the following clinical applications can radiomics potentially lead to improvements in:
Reference:Aerts, H.J., The potential of radiomic-based phenotyping in precision medicine: a review. JAMA Oncology, 2016. 2(12):1636-1642.
Choice A:Diagnosis.
Choice B:Prediction of prognosis.
Choice C:Assessment of treatment response.
Choice D:All of the above.
Choice E:None of the above.
Question 3: Which of the following are NOT the advantages of imaging compared with tissue biopsy-based pathologic or molecular analysis:
Reference:Gillies, R.J., Kinahan, P.E., and Hricak, H., Radiomics: images are more than pictures, they are data. Radiology, 2016. 278(2):563-577.
Choice A:Noninvasive.
Choice B:Provides definitive diagnosis of cancer.
Choice C:Allows visualization of the whole tumor.
Choice D:Allows characterization of in vivo pathophysiology.
Choice E:None of the above.
Question 4: A radiogenomic association study may be designed to answer the following scientific questions EXCEPT:
Reference:Kuo, Michael D., and Neema Jamshidi. "Behind the numbers: decoding molecular phenotypes with radiogenomics—guiding principles and technical considerations." Radiology 270.2 (2014): 320-325
Choice A:Understanding the genomic features correlated with certain image phenotypes.
Choice B:Understanding how a certain biological process is reflected at imaging.
Choice C:Defining imaging surrogates of tissue-based molecular markers.
Choice D:Defining causal relations between imaging and molecular markers.
Question 5: Which of the following is not characteristic of an ideal quantitative imaging metric?
Reference:Characterization of PET/CT images using texture analysis.: the past, the present . . . any future? Mathiew Hatt, et al., Eur. J. Nucl. Med. Mol. Imaging, 44:151 – 165, (2016)
Choice A:Robust.
Choice B:Repeatable.
Choice C:Correlated with clinical prognostic factors.
Choice D:Correlated with clinical end-point.
Question 6: Which of the following statistics is appropriate for measuring the volume correlation of a quantitative imaging feature?
Reference:Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer, Xenia Fave, et al., Scientific Reports, 7:588, (2017); Characterization of PET/CT images using texture analysis.: the past, the present . . . any future? Mathiew Hatt, et al., Eur. J. Nucl. Med. Mol. Imaging, 44:151 – 165, (2016)
Choice A:Concordance correlation coefficient.
Choice B:Overall concordance correlation coefficient.
Choice C:Pearson correlation coefficient.
Choice D:Spearman correlation coefficient.
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