Preface to 2017 focused issue: Translational Imaging in Cancer Patient Care
Preface on Focused Issue on Translational Imaging in Cancer Patient Care

Preface to 2017 focused issue: Translational Imaging in Cancer Patient Care

Medical imaging is involved in almost every aspect of clinical care for cancer patients, ranging from early detection and grading of cancers, risk assessment, therapeutic monitoring, as well as image-guided treatment. The importance of objective, reproducible, and quantifiable imaging is particularly motivated by the growing need for individualized precision medicine (1,2).

Application of morphological imaging to the evaluation of tumor response to treatment has led to the emergence of response criteria such as those proposed by the Response Evaluation Criteria in Solid Tumors (RECIST) working group (3,4). However, there is increasing awareness that anatomical approaches based on measurements of tumor size have significant limitations including the presence of tumors that cannot be measured and mass lesions that persist following effective therapy (5-9). Functional imaging techniques are increasingly being used to monitor response to therapies with novel mechanisms of action, often predicting the success of therapy before conventional measurements of size have changed. The consequences of altered angiogenesis, glucose metabolism and cell death can be imaged in patients using techniques such as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), fluorine-18 positron emission tomography, diffusion-weighted magnetic resonance imaging (DW-MRI), Chemical Exchange Saturation Transfer (CEST) (5-18). However, the ever-expanding number of potential imaging and molecular biomarkers that seemingly correlate with the pathologic processes in question has the potential to produce random statistical parameters, waste scientific efforts, and drive up the cost of health care (11). A deep understanding and validation of the pathophysiologic basis of the correlation between a biomarker and the underlying condition is vitally important (6).

This focused issue of Translational Imaging in Cancer Patient Care highlights current topics in the field of imaging addressing many common and debilitating oncological conditions. The authors have succeeded in covering a wide range of quantitative morphometric and compositional methods, particularly DW-MRI and ultrasound (US) imaging. Among the various functional imaging techniques, diffusion weighted imaging has the particular appeal that this method is widely available and completely non-invasive (without the injection of a contrast agent or a radioisotope). Water motion in tissues is not random but instead is modified by flows within conduits (for example, blood vessels, glandular ducts) and by interactions with cellular components such as hydrophobic phospholipid-containing cellular membranes, intracellular organelles. DW-MRI provides information on tissue cellularity, extracellular space tortuosity, and the integrity of cellular membranes by measuring the random motion of the water molecules in tissue. With increasing cell density, the confining effect of membranes increases and growing tumors typically have lower signal on apparent diffusion constant (ADC) maps than healthy cells due to restricted water diffusion (19-21). Intravoxel incoherent motion (IVIM) analysis allows for the separation of diffusion and perfusion parameters from diffusion weighted imaging with multi b values by compartmentalizing fast and slow moving spins (22-24). US is advantageous in a variety of scenarios of cancer management because it is of low cost and is widely available. US can reach both superficial and deep tissues depending on the frequency utilized for imaging, and microbubble agents provide tissue blood flow information (25-29). US contrast agents can also be targeted and used as carriers for local gene or drug delivery (30-32). US is also convenient for guided biopsy and guided minimally invasive therapy (27,33-38). In this special issue, serum blood biomarkers, such as HIF-1α, VEGF, and tryptase in assessing image-guided interventional treatment are also explored in two articles; a CT scan protocol is explored for gastrointestinal tumor post-surgery surveillance to reduce radiation exposure to patients.

We hope readers find the progress on Translational Imaging reported in this special issue interesting and stimulating. We would like to extend our sincere gratitude to all authors who devoted their time and expertise in putting together excellent contributions to this work. We also thank the Editorial Board of Translational Cancer Research for the opportunity to serve as the guest editor for this issue.




  1. Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 2017;14:749-62. [Crossref] [PubMed]
  2. Basu S. Personalized versus evidence-based medicine with PET-based imaging. Nat Rev Clin Oncol 2010;7:665-8. [Crossref] [PubMed]
  3. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009;45:228-47. [Crossref] [PubMed]
  4. Litière S, Collette S, de Vries EG, et al. RECIST - learning from the past to build the future. Nat Rev Clin Oncol 2017;14:187-92. [Crossref] [PubMed]
  5. Lin G, Keshari KR, Park JM. Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy. Contrast Media Mol Imaging 2017;2017:6053879. [Crossref]
  6. Wang YX. Medical imaging in pharmaceutical clinical trials: what radiologists should know. Clin Radiol 2005;60:1051-7. [Crossref] [PubMed]
  7. Padhani AR, Khan AA. Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy. Target Oncol 2010;5:39-52. [Crossref] [PubMed]
  8. Wáng YX, Choi Y, Chen Z, et al. Molecular imaging: from bench to clinic. Biomed Res Int 2014;2014:357258. [Crossref]
  9. Kang H, Lee HY, Lee KS, et al. Imaging based tumor treatment response evaluation: review of conventional, new, and emerging concepts. Korean J Radiol 2012;13:371-90. [Crossref] [PubMed]
  10. Yuan J, Lo G, King AD. Functional magnetic resonance imaging techniques and their development for radiation therapy planning and monitoring in the head and neck cancers. Quant Imaging Med Surg 2016;6:430-48. [Crossref] [PubMed]
  11. Weaver O, Leung JWT. Biomarkers and Imaging of Breast Cancer. AJR Am J Roentgenol 2017.1-8. [Epub ahead of print]. [Crossref] [PubMed]
  12. Li LZ. A pre-tracer approach for improving the accuracy of metabolic measurements by hyperpolarized nuclear magnetic resonance. Quant Imaging Med Surg 2016;6:612-4. [Crossref] [PubMed]
  13. van Elmpt W, Zegers CM, Reymen B, et al. Multiparametric imaging of patient and tumour heterogeneity in non-small-cell lung cancer: quantification of tumour hypoxia, metabolism and perfusion. Eur J Nucl Med Mol Imaging 2016;43:240-8. [Crossref] [PubMed]
  14. Mehrabian H, Desmond KL, Soliman H, et al. Differentiation between Radiation Necrosis and Tumor Progression Using Chemical Exchange Saturation Transfer. Clin Cancer Res 2017;23:3667-75. [Crossref] [PubMed]
  15. Salzillo TC, Hu J, Nguyen L, et al. Interrogating Metabolism in Brain Cancer. Magn Reson Imaging Clin N Am 2016;24:687-703. [Crossref] [PubMed]
  16. Ziai P, Hayeri MR, Salei A, et al. Role of Optimal Quantification of FDG PET Imaging in the Clinical Practice of Radiology. Radiographics 2016;36:481-96. [Crossref] [PubMed]
  17. Wang YX, Gong JS, Suzuki K, et al. Evidence based imaging strategies for solitary pulmonary nodule. J Thorac Dis 2014;6:872-87. [PubMed]
  18. Grootjans W, de Geus-Oei LF, Troost EG, et al. PET in the management of locally advanced and metastatic NSCLC. Nat Rev Clin Oncol 2015;12:395-407. [Crossref] [PubMed]
  19. Chilla GS, Tan CH, Xu C, et al. Diffusion weighted magnetic resonance imaging and its recent trend-a survey. Quant Imaging Med Surg 2015;5:407-22. [PubMed]
  20. Jafar MM, Parsai A, Miquel ME. Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility. World J Radiol 2016;8:21-49. [Crossref] [PubMed]
  21. Tamada T, Prabhu V, Li J, et al. Prostate Cancer: Diffusion-weighted MR Imaging for Detection and Assessment of Aggressiveness-Comparison between Conventional and Kurtosis Models. Radiology 2017;284:100-8. [Crossref] [PubMed]
  22. Le Bihan D, Turner R. The capillary network: a link between IVIM and classical perfusion. Magn Reson Med 1992;27:171-8. [Crossref] [PubMed]
  23. Yuan J, Wong OL, Lo GG, et al. Statistical assessment of bi-exponential diffusion weighted imaging signal characteristics induced by intravoxel incoherent motion in malignant breast tumors. Quant Imaging Med Surg 2016;6:418-29. [Crossref] [PubMed]
  24. Li YT, Cercueil JP, Yuan J, et al. Liver intravoxel incoherent motion (IVIM) magnetic resonance imaging: a comprehensive review of published data on normal values and applications for fibrosis and tumor evaluation. Quant Imaging Med Surg 2017;7:59-78. [Crossref] [PubMed]
  25. Oyen WJ, van der Graaf WT. Molecular imaging of solid tumors: exploiting the potential. Nat Rev Clin Oncol 2009;6:609-11. [Crossref] [PubMed]
  26. Wang Y, Li L, Wang YX, et al. Ultrasound findings of papillary thyroid microcarcinoma: a review of 113 consecutive cases with histopathologic correlation. Ultrasound Med Biol 2012;38:1681-8. [Crossref] [PubMed]
  27. Xu X, Luo L, Chen J, et al. Acoustic radiation force impulse elastography for efficacy evaluation after hepatocellular carcinoma radiofrequency ablation: a comparative study with contrast-enhanced ultrasound. Biomed Res Int 2014;2014:901642. [Crossref]
  28. Wang Y, Li L, Wang YX, et al. Time-intensity curve parameters in rectal cancer measured using endorectal ultrasonography with sterile coupling gels filling the rectum: correlations with tumor angiogenesis and clinicopathological features. Biomed Res Int 2014;2014:587806.
  29. Sudoł-Szopińska I, Schueller-Weidekamm C, Plagou A, et al. Ultrasound in Arthritis. Radiol Clin North Am 2017;55:985-96. [Crossref] [PubMed]
  30. Unger EC, Porter T, Culp W, et al. Therapeutic applications of lipid-coated microbubbles. Adv Drug Deliv Rev 2004;56:1291-314. [Crossref] [PubMed]
  31. Kaneko OF, Willmann JK. Ultrasound for molecular imaging and therapy in cancer. Quant Imaging Med Surg 2012;2:87-97. [PubMed]
  32. Willmann JK, Bonomo L, Carla Testa A, et al. Ultrasound Molecular Imaging With BR55 in Patients With Breast and Ovarian Lesions: First-in-Human Results. J Clin Oncol 2017;35:2133-40. [Crossref] [PubMed]
  33. Cui NY, Liu JY, Wang Y, et al. Contrast enhanced ultrasound guided biopsy shows higher positive sampling rate than conventional ultrasound guided biopsy for gastrointestinal stromal tumors diagnosis. Transl Cancer Res 2016;5:152-9. [Crossref]
  34. Wang Y, Zhao H, Wang YX, et al. Improvement in the Detection of Cystic Metastatic Papillary Thyroid Carcinoma by Measurement of Thyroglobulin in Aspirated Fluid. Biomed Res Int 2016;2016:8905916.
  35. Zhang J, Hao X, Yang Y, et al. Evaluation of supplementary diagnostic value of contrast-enhanced ultrasound for lymph node puncture biopsy. J Thorac Dis 2017;9:4791-7. [Crossref] [PubMed]
  36. He W, Wang W, Zhou P, et al. Enhanced ablation of high intensity focused ultrasound with microbubbles: an experimental study on rabbit hepatic VX2 tumors. Cardiovasc Intervent Radiol 2011;34:1050-7. [Crossref] [PubMed]
  37. Zhang W, Li JM, He W, et al. Ultrasound-guided percutaneous microwave ablation for benign breast lesions: evaluated by contrast-enhanced ultrasound combined with magnetic resonance imaging. J Thorac Dis 2017;9:4767-73. [Crossref] [PubMed]
  38. She WH, Cheung TT, Jenkins CR, et al. Clinical applications of high-intensity focused ultrasound. Hong Kong Med J 2016;22:382-92. [PubMed]
Prof. Yì-Xiáng J. Wáng
Prof. Yong Wang

Yì-Xiáng J. Wáng

Faculty of Medicine, the Chinese University of Hong Kong, Hong Kong SAR, China.

Yong Wang

Department of Ultrasound, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100006, China.

doi: 10.21037/tcr.2017.12.14

Conflicts of Interest: The authors have no conflicts of interest to declare.

Cite this article as: Wáng YJ, Wang Y. Preface to 2017 focused issue: Translational Imaging in Cancer Patient Care. Transl Cancer Res 2017;6(6):1028-1031. doi: 10.21037/tcr.2017.12.14