1. Kumar V, Abbas AK, Fausto N, Robbins SL. Robbins and Cotran Pathologic Basis of Disease: Elsevier Saunders; 2005.
2. Fink KR, Fink JR. Imaging of brain metastases. Surg Neurol Int. 2013;4(Suppl 4):S209-19.
3. Boroughs LK, DeBerardinis RJ. Metabolic pathways promoting cancer cell survival and growth. Nat Cell Biol. 2015;17(4):351-9.
4. Robertson-Tessi M, Gillies RJ, Gatenby RA, Anderson AR. Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes. Cancer Res. 2015;75(8):1567-79.
5. Ganeshan B, Miles KA, Young RC, Chatwin CR. Hepatic entropy and uniformity: additional parameters that can potentially increase the effectiveness of contrast enhancement during abdominal CT. Clin Radiol. 2007;62(8):761-8.
6. Ganeshan B, Abaleke S, Young RC, Chatwin CR, Miles KA. Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging. 2010;10(1):137-43.
7. Miles KA, Ganeshan B, Griffiths MR, Young RC, Chatwin CR. Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology. 2009;250(2):444-52.
8. Alic L, Niessen WJ, Veenland JF. Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review. PLoS One. 2014;9(10):e110300.
9. Stein D, Goldberg N, Domachevsky L, Bernstine H, Nidam M, Abadi-Korek I, et al. Quantitative biomarkers for liver metastases: comparison of MRI diffusion-weighted imaging heterogeneity index and fluorine-18-fluoro-deoxyglucose standardised uptake value in hybrid PET/MR. Clin Radiol. 2018;73(9):832.e17-.e22.
10. Dong X, Wu P, Sun X, Li W, Wan H, Yu J, et al. Intra-tumour 18F-FDG uptake heterogeneity decreases the reliability on target volume definition with positron emission tomography/computed tomography imaging. J Med Imaging Radiat Oncol. 2015;59(3):338-45.
11. Yoon HJ, Kim Y, Kim BS. Intratumoral metabolic heterogeneity predicts invasive components in breast ductal carcinoma in situ. Eur Radiol. 2015;25(12):3648-58.
12. Bundschuh RA, Dinges J, Neumann L, Seyfried M, Zsótér N, Papp L, et al. Textural Parameters of Tumor Heterogeneity in ¹⁸F-FDG PET/CT for Therapy Response Assessment and Prognosis in Patients with Locally Advanced Rectal Cancer. J Nucl Med. 2014;55(6):891-7.
13. Yankeelov TE, Peterson TE, Abramson RG, Izquierdo-Garcia D, Arlinghaus LR, Li X, et al. Simultaneous PET-MRI in oncology: a solution looking for a problem? Magn Reson Imaging. 2012;30(9):1342-56.
14. Punwani S, Taylor SA, Saad ZZ, Bainbridge A, Groves A, Daw S, et al. Diffusion-weighted MRI of lymphoma: prognostic utility and implications for PET/MRI? Eur J Nucl Med Mol Imaging. 2013;40(3):373-85.
15. Rohren EM, Provenzale JM, Barboriak DP, Coleman RE. Screening for cerebral metastases with FDG PET in patients undergoing whole-body staging of non-central nervous system malignancy. Radiology. 2003;226(1):181-7.
16. Wong CS, Gong N, Chu Y-C, Anthony M-P, Chan Q, Lee HF, et al. Correlation of measurements from diffusion weighted MR imaging and FDG PET/CT in GIST patients: ADC versus SUV. European Journal of Radiology. 2012;81(9):2122-6.
17. van Rijswijk CSP, Geirnaerdt MJA, Hogendoorn PCW, Peterse JL, van Coevorden F, Taminiau AHM, et al. Dynamic contrast-enhanced MR imaging in monitoring response to isolated limb perfusion in high-grade soft tissue sarcoma: initial results. European radiology. 2003;13(8):1849-58.
18. Kong E, Chun KA, Cho IH. Quantitative assessment of simultaneous F-18 FDG PET/MRI in patients with various types of hepatic tumors: Correlation between glucose metabolism and apparent diffusion coefficient. PloS one. 2017;12(7):e0180184-e.
19. Just N. Improving tumour heterogeneity MRI assessment with histograms. Br J Cancer. 2014;111(12):2205-13.
20. Dalili D, Padhani A, Grimm R. Quantitative WB-MRI with ADC Histogram Analysis for Response Assessment in Diffuse Bone Disease. 2017.
21. Rosenkrantz AB, Sigmund EE, Winnick A, Niver BE, Spieler B, Morgan GR, et al. Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants. Magn Reson Imaging. 2012;30(10):1534-40.
22. Rakheja R, Makis W, Skamene S, Nahal A, Brimo F, Azoulay L, et al. Correlating metabolic activity on 18F-FDG PET/CT with histopathologic characteristics of osseous and soft-tissue sarcomas: a retrospective review of 136 patients. AJR Am J Roentgenol. 2012;198(6):1409-16.
23. Nakajo M, Kajiya Y, Kaneko T, Kaneko Y, Takasaki T, Tani A, et al. FDG PET/CT and diffusion-weighted imaging for breast cancer: prognostic value of maximum standardized uptake values and apparent diffusion coefficient values of the primary lesion. Eur J Nucl Med Mol Imaging. 2010;37(11):2011-20.
24. Marusyk A, Polyak K. Tumor heterogeneity: causes and consequences. Biochim Biophys Acta. 2010;1805(1):105-17.