Abstract
Radiation therapy is one of the most effective tools for cancer treatment. In recent years, intensity-modulated radiation therapy has become increasingly popular in that target dose-escalation can be done while sparing adjacent normal tissues. For this reason, the development of measures to pave the way for accurate target delineation is of great interest. With the integration of functional information obtained by biological imaging with radiotherapy, strategies using advanced biological imaging to visualize metabolic pathways and to improve therapeutic index and predict treatment response are discussed in this article.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Radiation therapy (RT) is commonly used as a part of multiple modality treatments for cancer. In RT, staging, target delineation, treatment planning, and evaluation of response are typically based on computed tomography (CT) and magnetic resonance imaging (MRI) as measures of “anatomical imaging.” Recently, the treatment planning paradigm in radiation oncology is beginning to shift toward a more biological and molecular approach as advances in biochemistry, molecular biology, and technology have made functional imaging [positron emission tomography (PET), nuclear magnetic resonance spectroscopy (MRS), optical imaging] of physiological processes in tumors more feasible and practical [1]. This mini-review provides an overview of the role of current imaging strategies in radiation oncology, including functional CT, MRI, and several PET tracers in (1) target delineation, (2) treatment response prediction, and (3) resistant tumor targeting for dose-escalation in radiotherapy.
Target delineation
For several decades, along with the development of three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) techniques [2, 3], CT has been the foundation of RT target delineation and dose calculation.
A special technique called dual-energy CT (DECT) provides information beyond morphological CT, and functional imaging [4, 5]. Physically, DECT is found on different X-ray attenuation coefficients of all materials naturally abundant in humans. The measurement of two different X-ray spectra therefore allows the data to be decomposed into a desired pair of images. The advantages of DECT include (1) fast, robust, quantitative and functional imaging; (2) better tumor detection and more detailed tissue differentiations; and (3) less radiation dose exposure [6]. In the RT planning process, DECT may reduce metal artifacts, thus benefiting target delineation [7, 8].
Dynamic contrast-enhanced CT (DCE-CT) first acquires a baseline image without contrast enhancement followed by a series of images over time after an intravenous bolus of contrast agent. The temporal changes in contrast enhancement can be analyzed to quantify a range of physiological parameters that indicate the functional characteristics, such as blood volume, tissue perfusion, and vascular permeability, within tumors and adjacent tissues [9, 10]. DCE-CT may improve the accuracy of RT target volume delineation in liver, lung, and prostate cancer [11, 12]. For example, Jensen et al. [12] successfully used DCE-CT to aid gross tumor volume (GTV) delineation of liver tumors and reduced interobserver variability.
Diffusion-weighted MRI (DWI) takes advantage of the random thermal movement of molecules that is often referred to as Brownian motion. Water movement in the extracellular space is restricted by the surrounding cells, and therefore the diffusion constant (ADC) is an apparent value that is estimated from the slope of relative signal intensity (on a logarithmic scale) against a series of b values [13]. RT target volume delineation by DWI has been investigated for various cancers. There is an excellent review of target volume delineation for radical radiotherapy planning for glioma by Whitfield et al. [14]. DWI coupled with CT images is shown to improve accuracy and/or consistency to delineate GTV in esophageal or rectal cancer [15, 16].
Most of the fundamentals of molecular imaging akin to tumor detection are built on an urgent demand for sources to sustain aberrant proliferation of a neoplasm. Glucose, a direct material of cellular energy, is desperately needed for tumor growth. 18F-Fluorodeoxyglucose (18F-FDG), a glucose derivative with a radio-fluorine substitution at the 2′-position, was used to reveal the difference in glucose metabolism between tumor and normal tissues, which allowed outlining the lesion. FDG PET has gradually become more important in RT planning [17]. For example, the benefit of FDG PET in lung cancer may include (1) increasing feasibility to distinguish tumors from collapsed lung tissue (atelectasis) and (2) increased accuracy in lymph node staging [18]. In lymphoma, FDG PET is essential for involved node or involved site irradiation.
Treatment response prediction
Early prediction of tumor response is instrumental for treatment planning and optimization of cancer treatment. Thus, a noninvasive imaging biomarker providing accurate information in monitoring as well as enhancing the therapy efficacy is of great importance.
DCE-CT is useful in both target delineation and the prediction of treatment response. Abramyuk et al. [19] performed DCE-CT in 15 patients with HNC before and after chemoradiotherapy (CRT). The increment of transfer coefficient (K trans) and relative tumor blood volume (rTBV) under treatment indicates a poor outcome. DCE-CT also has an important role in lung cancer. In a study by Hwang et al. [20], 75 non-small cell lung cancer (NSCLC) tumors in 65 patients with stable disease according to RECIST after chemotherapy or CRT were investigated. The implementation of DCE-CT predicted the hypermetabolic status of residual tumor in patients with NSCLC after concurrent chemoradiotherapy (CCRT).
Dynamic contrast-enhanced MRI (DCE-MRI), similar to DCE-CT, assesses the changes in signal intensity over time. This imaging follows the intravenous injection of a paramagnetic contrast agent that reduces the T1 (spin–lattice or longitudinal relaxation time) value of the blood and thereby increases (enhances) the signal intensity on T1-weighted imaging [10]. Measurements obtained from DCE-MRI before, during, or after RT were related to tumor response or recurrence, mostly in the cervix, head and neck, central nervous system (CNS), and breast [21]. For example, Ng et al. [22] found that the local control could be predicted by pretreatment K trans in oropharyngeal or hypopharyngeal squamous cell carcinoma patients treated with chemoradiation. Furthermore, Shukla-Dave et al. [23] analyzed the significance of pre-treatment DCE-MRI parameters in 74 patients (61 had CCRT and 13 underwent surgery) with squamous cell carcinoma and neck nodal metastases. The result revealed that skewness of K trans was a powerful predictor of progression-free survival (PFS) and overall survival (OS) for stage IV patients. However, in cervical carcinoma, there was no agreement whether the level of signal enhancement in DCE-MRI was crucial in treatment success and survival [24–26]. For example, Donaldson et al. [24] measured the fraction of voxels showing significant signal enhancement and found that high enhancing fraction (EF) at 25 s postcontrast was correlated with poor disease-free survival (DFS). In contrast, Zahra et al. [26] in an analysis found low signal enhancement was related with lower OS and DFS in cervical carcinoma with the utilization of low-enhancing tumor volume (LETV) and low-enhancing tumor fraction (LETF) as input parameters.
Numbers of studies have shown the prognostic potential of the apparent diffusion coefficient (ADC) in predicting treatment outcome after RT among different tumor entities, mostly in prostate, gynecological, head and neck, CNS, and rectal cancer [27]. Liu et al. retrospectively analyzed the pre-RT and post-RT ADC value of patients with prostate cancer receiving RT. The statistical significance in post-IMRT ADC values was noted between patients with and without recurrence (1.27 ± 0.14 × 10−3 versus 49 ± 0.12 × 10−3 mm2 s−1; P < 0.001). The increase in ADC values observed in prostate cancer after RT leads to a good prognosis [28]. In a prospective cohort study conducted by Harry et al. [29], 20 women with advanced cervical cancer receiving CCRT were included. ADC values and the change in ADC after 2 weeks of therapy showed a consequential connection with eventual tumor response as determined both by MR imaging (P = 0.048) and clinical assessment (P = 0.009). The value of ADC, a prediction of treatment response, is consistently utilized for CNS tumors, including primary tumors as well as brain metastases [30, 31]. In metastatic brain lesions treated with RT alone, Farjam et al. [31] reported the diffusion abnormality index (DAI) drastically decreased from pre-RT to 2 weeks after starting RT in the responsive tumors compared with the progressive ones (P < 0.0002). DWI was also capable of evaluating the treatment outcome in head and neck cancer [32–34] and rectal cancer [35–37]. In a study to assess DFS in head and neck squamous cell carcinoma (HNSCC) treated with CRT using the ADC value [33], 78 patients were retrospectively studied and ADC was calculated with two sets of two b values: 0–750 s/mm2 (ADC750) and 0–1000 s/mm2 (ADC1000). The result indicated that tumor volume (sensitivity, 73 %; specificity, 57 %) and lymph node ADC1000 (sensitivity, 71–79 %; specificity, 77–79 %) were significant but independent predictors of DFS. Lambrecht et al. [35] evaluated the ADC value of DWI before, during, and early after initiating preoperative CRT in local advanced rectal cancer. Significantly high values of pathologically complete remission (pCR) were displayed in cases with low ADC pretreatment and higher ADC change during or after RT.
Magnetic resonance spectroscopy shares the same general principles and equipment as its widely used partner, MRI. Nevertheless, MRI builds images using signals from 1H nuclei in tissue water (and sometimes lipid), present at concentrations of approximately 35 M, MRS is used to measure signals from magnetic nuclei (usually 1H, but 31P has also been extensively studied) of tissue metabolites such as choline, creatine, and lactate that are present at much lower concentrations (typically of the order of a few mM) [38]. In RT, MRS serves as a noninvasive predictor for the response of tumors and treatment outcome in glioma and prostate cancer [39–42]. The potential benefit of MRS was reported in a study on 18 patients with glioblastoma who had three-dimensional MR spectroscopic imaging along with T2- and T1-gadolinium-enhanced MR images at simulation and at boost treatment planning after 17–20 fractions of RT. All patients received standard radiotherapy with concurrent temozolomide followed by adjuvant temozolomide. The result showing an increase in mean or median Cho/NAA values at the third-week RT scan stood a great chance of early progression (P < 0.01) [39]. In a prospectively enrolled study conducted by Crehange et al. [42], 24 patients with localized prostate cancer treating with IMRT with or without long-term adjuvant hormonal therapy (LTHT) underwent 3-T MRS and prostate-specific antigen (PSA) assays. It was concluded that low normalized choline in the peripheral zone, 6 months after radiation, predicts which patients attained a PSA ≤0.5 ng/ml at 1 year.
18F-FDG PET is highly sensitive and specific in evaluating the treatment response of various cancers [68]. Among them was lymphoma, being the first type of tumors to be investigated with PET/CT. A recent study conducted by Radford et al. [43] suggested that consolidation of involved-field RT could be omitted in newly diagnosed patients in stage IA or in stage IIA Hodgkin’s lymphoma because of the negative result of FDG PET after three cycles of ABVD. In local advanced rectal cancer, 15–27 % of the patients experience a pCR after neoadjuvant CRT, which raises the concern whether invasive surgery could be avoided in a selected cohort of patients with complete clinical response after preoperative RCT. In addition, the importance of early changes in FDG uptake on the prediction of pCR and the role of 18F-FDG PET/CT over RCT need further research. Regardless, quantitative and qualitative 18F-FDG PET/CT measurements are equally effective in the assessment of pCR after CRT [44].
3′-Deoxy-3′-18F-fluorothymidine (18F-FLT), another radiolabeled nucleoside analogue recently used as a specific radiotracer, has superseded 18F-FDG in describing the status of cell proliferation. It is documented that the level of deoxythymidine triphosphate will be elevated for the formation of the nucleus via salvage pathway during rapid cell division [45–47]. 18F-FLT PET, hence, is extremely useful in the detection, localization, and staging of tumors. For example, the ability of 18F-FLT PET to detect early changes in tumor proliferation after chemoradiotherapy was testified in esophageal carcinoma. With 18F-FLT instead of FDG PET, a higher specificity for depicting early reductions in tumor proliferation that precede tumor size changes after chemoradiotherapy was shown [48].
Several studies reported that the decline in 18F-FLT tumor uptake during RT or CCRT was a reliable determinant of treatment outcome in patients with HNSCC [49–51], NSCLC [52, 53], and glioma [54]. Nyflot et al. [50] observed an apparent reduction of 18F-FLT and 64Cu-ATSM (discussed in the next section) take-up in HNSCC after RT combined with bevacizumab treatment. In NSCLC, a similar drop of 18F-FLT uptake was noted after 1–2 weeks of RT [52]. Everitt et al. [53] found that the level of 18F-FLT had decreased earlier than that of 18F-FDG after chemo-RT on NSCLC patients, making it possible for this concurrent therapy to have more influence on proliferation rather than cellular glucose metabolism.
Resistant tumor targeting for dose escalation
There is still a risk of treatment failure even when treatment planning is well organized. A promising strategy to increase tumor control rate without undesired radiation exposure of normal tissues would be delivery of additive dose to the radio-resistant tumor regions with biological imaging [55]. Noninvasive imaging tools such as functional MRI and PET coupled with tracers such as 18F-fluoroazomycin arabinoside (18F-FAZA) and 62,64Cu-diacetyl-bis [N(4)-methylthiosemicarbazone] (62,64Cu-ATSM) are discussed next.
Functional MRI performs excellent RT dose escalation by brachytherapy or external beam boosting. Mason et al. [56] delivered a boost dose by DCE-MRI-guided high-dose-rate (HDR) brachytherapy without violating urethral and rectal dose constraint. The focal boost treatment plans increased median D90 from 17.6 to 20.9 Gy and median V150 from 27.3 % to 75.9 %. Dyk et al. [57] delineated the GTV and delivered a higher dose by combining MRI/DWI and HDR brachytherapy. Total dose delivery to the GTV from MRI/DWI-guided HDR is strongly correlated with local tumor control. In the study among patients who had GBM, Einstein et al. conducted a prospective phase II trial using selective MRS-targeted functional SRS boost to high-risk tumor volumes. This treatment is feasible, with tolerable toxicity and patient survivals higher than in historical controls [58]. A single blind randomized phase III trial (NCT01168479) was also conducted to investigate the benefit of a focal lesion ablative microboost in prostate cancer with MRS imaging. Patients allocated to the standard arm receive a dose of 77 Gy in 35 fractions to the entire prostate and patients in the experimental arm receive 77 Gy to the entire prostate and an additional integrated microboost to the macroscopic tumor of 95 Gy in 35 fractions. To delineate the macroscopic tumor within the prostate, different MR imaging techniques including MRS were used. This study is still ongoing.
Hypoxia, the state of oxygen deprivation, is a hallmark of cancer. It upregulates the expression of hypoxia-responsive elements and in turn contributes to chemo-radioresistance in tumors. The gold standard to evaluate the level of oxygen is an invasive method using Eppendorf polarographic electrodes; however, practical utilization of this technique is confined to well-defined superficial neoplasms. Unfortunately, it is unable to provide the three-dimensional distribution of an hypoxic area. 18F-FAZA belongs to the class of nitroimidazole derivatives as well as 18F-fluoromisonidazole (18F-FMISO), which is the first studied hypoxia probe in PET. The mechanism with respect to the accumulation of radiolabeled nitroimidazole derivatives in hypoxic cells is grounded on changes in mitochondrial respiratory chain in hypoxic and normoxic cells. Briefly, if O2 is not present, the −NO2 group on the imidazole ring tends to accept an electron released from the mitochondrial respiratory cycle to form −NO2 −, which can be reacted with another electron to produce a 2-electron reduction product and sequentially reduced to −NH2, resulting in cellular retention because of covalent bonding to the macromolecule. Basically, 18F-FAZA has a few advantages over 18F-FMISO, such as better specific activity, specificity, tumor-to-background ratio, and more chemically stability when injected into the living subjects. Trinkaus et al. [59] and Bollineni et al. [60] have reported the application of 18F-FAZA PET in monitoring the hypoxic fraction of tumor growth in NSCLC patients. Servagi-Vernat et al. [61] reached a similar conclusion in a clinical study using 18F-FAZA PET to identify the hypoxic area in HNSCC of patients during the course of radiochemotherapy. These reports suggest that change in the hypoxic volume between pre- and mid-treatment is crucial to dose-escalation protocols.
Another class of PET hypoxia radiotracers, 62,64Cu-ATSM, a prognosis predictor as well as 18F-FAZA, has been demonstrated to accumulate in tumors [62–64]. The apparent retention of 64Cu-ATSM in hypoxic cells may result from the elevated bioreductive enzymes under a low oxygen condition. The lack of oxygen impairs the electron transfer chain, leads to increased presence of cellular NADH and NADPH, and causes the release of radioactive copper from ATSM that is irreversibly trapped within hypoxic cells, but not in cells under normal oxygen supply condition. The in vitro and in vivo therapeutic efficacy of 64Cu-ATSM in eliminating tumor cells and prolonging the survival time of tumor-bearing hamsters have been reported by Obata et al. [65] and Lewis et al. [66], respectively. Recently, Yoshii et al. [67, 68] found remarkable retention of 64Cu-ATSM in CD133+ cells, which are regarded as cancer stem cell-like cells associated with radio-chemoresistance and metastasis. However, the natural high level of accumulation of radioactive copper in liver, a well-known critical organ for RT, raised a concern about harmful effects on the liver [69]. Yoshii and her colleagues [70] developed a method by using penicillamine, a drug for Wilson’s disease, to reduce radiation dose-escalation in liver with no significant effect on tumor uptake. Being tested in phantoms and a tumor model, Cu-ATSM-based dose-painting has proved to be feasible to deliver a higher dose of radiation to the hypoxic tumor subvolume to overcome inherent hypoxia-induced radioresistance without compromising normal tissue sparing [48, 71].
Conclusion
Biological imaging with functional CT/MRI and PET tracers offers a variety of tactics for tumor detection and visualization, as well as describing the biological aspects of tumor pathophysiology and radiation sensitivity. Although thriving and promising, the potential of imaging modalities in treatment outcomes remains unconfirmable [72]. Further studies on dose-painting are essential in this emerging field of RT. It is thrilling to see biological imaging laying bare the individualized RT strategy.
References
Apisarnthanarax S, Chao KS (2005) Current imaging paradigms in radiation oncology. Radiat Res 163(1):1–25
Chao KS, Low DA, Perez CA et al (2000) Intensity-modulated radiation therapy in head and neck cancers: the Mallinckrodt experience. Int J Cancer 90(2):92–103
Verhey LJ (1999) Comparison of three-dimensional conformal radiation therapy and intensity-modulated radiation therapy systems. Semin Radiat Oncol 9(1):78–98
Fornaro J, Leschka S, Hibbeln D et al (2011) Dual- and multi-energy CT: approach to functional imaging. Insights Imaging 2(2):149–159
van Elmpt W, Landry G, Das M et al (2016) Dual-energy CT in radiotherapy: current applications and future outlook. Radiother Oncol 119:137–144
Simons D, Kachelriess M, Schlemmer HP (2014) Recent developments of dual-energy CT in oncology. Eur Radiol 24(4):930–939
Bamberg F, Dierks A, Nikolaou K et al (2011) Metal artifact reduction by dual energy computed tomography using monoenergetic extrapolation. Eur Radiol 21(7):1424–1429
Guggenberger R, Winklhofer S, Osterhoff G et al (2012) Metallic artefact reduction with monoenergetic dual-energy CT: systematic ex vivo evaluation of posterior spinal fusion implants from various vendors and different spine levels. Eur Radiol 22(11):2357–2364
O’Connor JP, Tofts PS, Miles KA et al (2011) Dynamic contrast-enhanced imaging techniques: CT and MRI. Br J Radiol 84(Spec No 2):S112–S120
Cao Y (2011) The promise of dynamic contrast-enhanced imaging in radiation therapy. Semin Radiat Oncol 21(2):147–156
van Elmpt W, Zegers CM, Das M et al (2014) Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities. J Thorac Dis 6(4):319–327
Jensen NK, Mulder D, Lock M et al (2014) Dynamic contrast enhanced CT aiding gross tumor volume delineation of liver tumors: an interobserver variability study. Radiother Oncol 111(1):153–157
Gallagher FA (2010) An introduction to functional and molecular imaging with MRI. Clin Radiol 65(7):557–566
Whitfield GA, Kennedy SR, Djoukhadar IK et al (2014) Imaging and target volume delineation in glioma. Clin Oncol 26(7):364–376
Hou DL, Shi GF, Gao XS et al (2013) Improved longitudinal length accuracy of gross tumor volume delineation with diffusion weighted magnetic resonance imaging for esophageal squamous cell carcinoma. Radiat Oncol 8:169
Burbach JP, Kleijnen JP, Reerink O et al (2016) Inter-observer agreement of MRI-based tumor delineation for preoperative radiotherapy boost in locally advanced rectal cancer. Radiother Oncol 118(2):399–407
Lammering G, De Ruysscher D, van Baardwijk A et al (2010) The use of FDG-PET to target tumors by radiotherapy. Strahlenther Onkol 186(9):471–481
Konert T, Vogel W, MacManus MP et al (2015) PET/CT imaging for target volume delineation in curative intent radiotherapy of non-small cell lung cancer: IAEA consensus report 2014. Radiother Oncol 116(1):27–34
Abramyuk A, Hietschold V, Appold S et al (2015) Radiochemotherapy-induced changes of tumour vascularity and blood supply estimated by dynamic contrast-enhanced CT and fractal analysis in malignant head and neck tumours. Br J Radiol 88(1045):20140412
Hwang SH, Yoo MR, Park CH et al (2013) Dynamic contrast-enhanced CT to assess metabolic response in patients with advanced non-small cell lung cancer and stable disease after chemotherapy or chemoradiotherapy. Eur Radiol 23(6):1573–1581
Zahra MA, Hollingsworth KG, Sala E et al (2007) Dynamic contrast-enhanced MRI as a predictor of tumour response to radiotherapy. Lancet Oncol 8(1):63–74
Ng SH, Lin CY, Chan SC et al (2013) Dynamic contrast-enhanced MR imaging predicts local control in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiotherapy. PLoS One 8(8):e72230
Shukla-Dave A, Lee NY, Jansen JF et al (2012) Dynamic contrast-enhanced magnetic resonance imaging as a predictor of outcome in head-and-neck squamous cell carcinoma patients with nodal metastases. Int J Radiat Oncol Biol Phys 82(5):1837–1844
Donaldson SB, Buckley DL, O’Connor JP et al (2010) Enhancing fraction measured using dynamic contrast-enhanced MRI predicts disease-free survival in patients with carcinoma of the cervix. Br J Cancer 102(1):23–26
Mayr NA, Huang Z, Wang JZ et al (2012) Characterizing tumor heterogeneity with functional imaging and quantifying high-risk tumor volume for early prediction of treatment outcome: cervical cancer as a model. Int J Radiat Oncol Biol Phys 83(3):972–979
Zahra MA, Tan LT, Priest AN et al (2009) Semiquantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging measurements predict radiation response in cervix cancer. Int J Radiat Oncol Biol Phys 74(3):766–773
Tsien C, Cao Y, Chenevert T (2014) Clinical applications for diffusion magnetic resonance imaging in radiotherapy. Semin Radiat Oncol 24(3):218–226
Liu L, Wu N, Ouyang H et al (2014) Diffusion-weighted MRI in early assessment of tumour response to radiotherapy in high-risk prostate cancer. Br J Radiol 87(1043):20140359
Harry VN, Semple SI, Gilbert FJ et al (2008) Diffusion-weighted magnetic resonance imaging in the early detection of response to chemoradiation in cervical cancer. Gynecol Oncol 111(2):213–220
Galban S, Lemasson B, Williams TM et al (2012) DW-MRI as a biomarker to compare therapeutic outcomes in radiotherapy regimens incorporating temozolomide or gemcitabine in glioblastoma. PLoS One 7(4):e35857
Farjam R, Tsien CI, Feng FY et al (2014) Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy. Neuro-oncology 16(1):131–139
Vandecaveye V, De Keyzer F, Nuyts S et al (2007) Detection of head and neck squamous cell carcinoma with diffusion weighted MRI after (chemo)radiotherapy: correlation between radiologic and histopathologic findings. Int J Radiat Oncol Biol Phys 67(4):960–971
Noij DP, Pouwels PJ, Ljumanovic R et al (2015) Predictive value of diffusion-weighted imaging without and with including contrast-enhanced magnetic resonance imaging in image analysis of head and neck squamous cell carcinoma. Eur J Radiol 84(1):108–116
Tyagi N, Riaz N, Hunt M et al (2016) Weekly response assessment of involved lymph nodes to radiotherapy using diffusion-weighted MRI in oropharynx squamous cell carcinoma. Med Phys 43(1):137
Lambrecht M, Vandecaveye V, De Keyzer F et al (2012) Value of diffusion-weighted magnetic resonance imaging for prediction and early assessment of response to neoadjuvant radiochemotherapy in rectal cancer: preliminary results. Int J Radiat Oncol Biol Phys 82(2):863–870
Curvo-Semedo L, Lambregts DM, Maas M et al (2011) Rectal cancer: assessment of complete response to preoperative combined radiation therapy with chemotherapy: conventional MR volumetry versus diffusion-weighted MR imaging. Radiology 260(3):734–743
Lambregts DM, Vandecaveye V, Barbaro B et al (2011) Diffusion-weighted MRI for selection of complete responders after chemoradiation for locally advanced rectal cancer: a multicenter study. Ann Surg Oncol 18(8):2224–2231
Payne GS, Leach MO (2006) Applications of magnetic resonance spectroscopy in radiotherapy treatment planning. Br J Radiol 79(Spec No 1):S16–S26
Muruganandham M, Clerkin PP, Smith BJ et al (2014) 3-Dimensional magnetic resonance spectroscopic imaging at 3 Tesla for early response assessment of glioblastoma patients during external beam radiation therapy. Int J Radiat Oncol Biol Phys 90(1):181–189
Deviers A, Ken S, Filleron T et al (2014) Evaluation of the lactate-to-N-acetyl-aspartate ratio defined with magnetic resonance spectroscopic imaging before radiation therapy as a new predictive marker of the site of relapse in patients with glioblastoma multiforme. Int J Radiat Oncol Biol Phys 90(2):385–393
Zapotoczna A, Sasso G, Simpson J et al (2007) Current role and future perspectives of magnetic resonance spectroscopy in radiation oncology for prostate cancer. Neoplasia 9(6):455–463
Crehange G, Maingon P, Gauthier M et al (2011) Early choline levels from 3-tesla MR spectroscopy after exclusive radiation therapy in patients with clinically localized prostate cancer are predictive of plasmatic levels of PSA at 1 year. Int J Radiat Oncol Biol Phys 81(4):e407–e413
Radford J, Illidge T, Counsell N et al (2015) Results of a trial of PET-directed therapy for early-stage Hodgkin’s lymphoma. N Engl J Med 372(17):1598–1607
Joye I, Deroose CM, Vandecaveye V et al (2014) The role of diffusion-weighted MRI and (18)F-FDG PET/CT in the prediction of pathologic complete response after radiochemotherapy for rectal cancer: a systematic review. Radiother Oncol 113(2):158–165
Wu CY, Wang HE, Lin MH et al (2012) Radiolabeled nucleosides for predicting and monitoring the cancer therapeutic efficacy of chemodrugs. Curr Med Chem 19(20):3315–3324
Soloviev D, Lewis D, Honess D et al (2012) [(18)F]FLT: an imaging biomarker of tumour proliferation for assessment of tumour response to treatment. Eur J Cancer 48(4):416–424
Apisarnthanarax S, Alauddin MM, Mourtada F et al (2006) Early detection of chemoradioresponse in esophageal carcinoma by 3′-deoxy-3′-3H-fluorothymidine using preclinical tumor models. Clin Cancer Res 12(15):4590–4597
Chao KS, Bosch WR, Mutic S et al (2001) A novel approach to overcome hypoxic tumor resistance: Cu-ATSM-guided intensity-modulated radiation therapy. Int J Radiat Oncol Biol Phys 49(4):1171–1182
Bradshaw TJ, Bowen SR, Deveau MA et al (2015) Molecular imaging biomarkers of resistance to radiation therapy for spontaneous nasal tumors in canines. Int J Radiat Oncol Biol Phys 91(4):787–795
Nyflot MJ, Kruser TJ, Traynor AM et al (2015) Phase 1 trial of bevacizumab with concurrent chemoradiation therapy for squamous cell carcinoma of the head and neck with exploratory functional imaging of tumor hypoxia, proliferation, and perfusion. Int J Radiat Oncol Biol Phys 91(5):942–951
Arens AI, Troost EG, Hoeben BA et al (2014) Semiautomatic methods for segmentation of the proliferative tumour volume on sequential FLT PET/CT images in head and neck carcinomas and their relation to clinical outcome. Eur J Nucl Med Mol Imaging 41(5):915–924
Trigonis I, Koh PK, Taylor B et al (2014) Early reduction in tumour [18F]fluorothymidine (FLT) uptake in patients with non-small cell lung cancer (NSCLC) treated with radiotherapy alone. Eur J Nucl Med Mol Imaging 41(4):682–693
Everitt SJ, Ball DL, Hicks RJ et al (2014) Differential (18)F-FDG and (18)F-FLT uptake on serial PET/CT imaging before and during definitive chemoradiation for non-small cell lung cancer. J Nucl Med 55(7):1069–1074
Zhao F, Li M, Wang Z et al (2015) (18)F-Fluorothymidine PET-CT for resected malignant gliomas before radiotherapy: tumor extent according to proliferative activity compared with MRI. PLoS One 10(3):e0118769
Sovik A, Malinen E, Olsen DR (2009) Strategies for biologic image-guided dose escalation: a review. Int J Radiat Oncol Biol Phys 73(3):650–658
Mason J, Al-Qaisieh B, Bownes P et al (2014) Multi-parametric MRI-guided focal tumor boost using HDR prostate brachytherapy: a feasibility study. Brachytherapy 13(2):137–145
Dyk P, Jiang N, Sun B et al (2014) Cervical gross tumor volume dose predicts local control using magnetic resonance imaging/diffusion-weighted imaging-guided high-dose-rate and positron emission tomography/computed tomography-guided intensity-modulated radiation therapy. Int J Radiat Oncol Biol Phys 90(4):794–801
Einstein DB, Wessels B, Bangert B et al (2012) Phase II trial of radiosurgery to magnetic resonance spectroscopy-defined high-risk tumor volumes in patients with glioblastoma multiforme. Int J Radiat Oncol Biol Phys 84(3):668–674
Trinkaus ME, Blum R, Rischin D et al (2013) Imaging of hypoxia with 18F-FAZA PET in patients with locally advanced non-small cell lung cancer treated with definitive chemoradiotherapy. J Med Imaging Radiat Oncol 57(4):475–481
Bollineni VR, Kerner GS, Pruim J et al (2013) PET imaging of tumor hypoxia using 18F-fluoroazomycin arabinoside in stage III–IV non-small cell lung cancer patients. J Nucl Med 54(8):1175–1180
Servagi-Vernat S, Differding S, Hanin FX et al (2014) A prospective clinical study of 18F-FAZA PET-CT hypoxia imaging in head and neck squamous cell carcinoma before and during radiation therapy. Eur J Nucl Med Mol Imaging 41(8):1544–1552
Dehdashti F, Grigsby PW, Lewis JS et al (2008) Assessing tumor hypoxia in cervical cancer by PET with 60Cu-labeled diacetyl-bis(N4-methylthiosemicarbazone). J Nucl Med 49(2):201–205
Fleming IN, Manavaki R, Blower PJ et al (2015) Imaging tumour hypoxia with positron emission tomography. Br J Cancer 112(2):238–250
Mortensen LS, Johansen J, Kallehauge J et al (2012) FAZA PET/CT hypoxia imaging in patients with squamous cell carcinoma of the head and neck treated with radiotherapy: results from the DAHANCA 24 trial. Radiother Oncol 105(1):14–20
Obata A, Kasamatsu S, Lewis JS et al (2005) Basic characterization of 64Cu-ATSM as a radiotherapy agent. Nucl Med Biol 32(1):21–28
Lewis J, Laforest R, Buettner T et al (2001) Copper-64-diacetyl-bis(N4-methylthiosemicarbazone): an agent for radiotherapy. Proc Natl Acad Sci USA 98(3):1206–1211
Yoshii Y, Furukawa T, Kiyono Y et al (2010) Copper-64-diacetyl-bis (N4-methylthiosemicarbazone) accumulates in rich regions of CD133+ highly tumorigenic cells in mouse colon carcinoma. Nucl Med Biol 37(4):395–404
Yoshii Y, Furukawa T, Kiyono Y et al (2011) Internal radiotherapy with copper-64-diacetyl-bis (N4-methylthiosemicarbazone) reduces CD133+ highly tumorigenic cells and metastatic ability of mouse colon carcinoma. Nucl Med Biol 38(2):151–157
Laforest R, Dehdashti F, Lewis JS et al (2005) Dosimetry of 60/61/62/64Cu-ATSM: a hypoxia imaging agent for PET. Eur J Nucl Med Mol Imaging 32(7):764–770
Yoshii Y, Matsumoto H, Yoshimoto M et al (2014) Controlled administration of penicillamine reduces radiation exposure in critical organs during 64Cu-ATSM internal radiotherapy: a novel strategy for liver protection. PLoS One 9(1):e86996
Clausen MM, Hansen AE, Lundemann M et al (2014) Dose painting based on tumor uptake of Cu-ATSM and FDG: a comparative study. Radiat Oncol 9:228
Groenendaal G, van den Berg CA, Korporaal JG et al (2010) Simultaneous MRI diffusion and perfusion imaging for tumor delineation in prostate cancer patients. Radiother Oncol 95(2):185–190
Acknowledgments
The authors acknowledge the help of Vivian Wu and Vicky C. Lin in manuscript preparation and editing.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
About this article
Cite this article
Lai, YL., Wu, CY. & Chao, K.S.C. Biological imaging in clinical oncology: radiation therapy based on functional imaging. Int J Clin Oncol 21, 626–632 (2016). https://doi.org/10.1007/s10147-016-1000-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10147-016-1000-2