Arterial spin labeling (ASL) is a completely noninvasive vascular MR method, which exploits arterial water as an endogenous tracer. It is therefore very desired for the longitudinal patient follow-up. Importantly, ASL yields absolute measurements of blood flow at high spatial and temporal resolution [19]. In ASL, the proton spins of the arterial water are magnetically labeled, i.e., undergo either saturation or inversion, prior to reaching the imaged volume. Blood flowing into the imaging slice exchanges with tissue water, altering the tissue magnetization. A perfusion-weighted image can be generated by the subtraction of a “labeled” image from a control image, in which spin labeling has not been performed. ASL has been clinically applied in the assessment of cerebral blood flow in various pathological states, including cerebrovascular disease, neurodegenerative disease, and epilepsy. In oncology, the ASL application has been mainly limited to brain tumors [20, 21]. In extracranial tumors, however, technical challenges limit the ability to label the supplying vessels of the tumor [22]. Moreover, it is sometimes difficult to differentiate the tumor-feeding artery. Nevertheless, some preclinical and clinical studies have shown potential of ASL for cancer diagnosis and therapy evaluation at peripheral locations [23, 24].

Computed tomography (CT) is currently one of the most commonly used imaging modalities because of widespread availability, reasonable costs, fast image acquisition, whole-body 3D coverage, and high spatial resolution. On the other hand, CT has several important disadvantages, including the use of ionizing radiation, poor soft tissue contrast, and limited functional information. In clinical oncology, contrast-enhanced CT plays an important role, being the imaging method of choice for monitoring of pulmonary, hepatic, mediastinal, and retroperitoneal lymph node metastases [25]. Perfusion CT, a dynamic contrast-enhanced CT method, also aspires for the position in cancer diagnostics, by generating (patho)physiologically relevant hemodynamic parameters. Although perfusion CT can be readily incorporated into existing CT protocols, clinical experience has largely comprised preliminary studies and few large-scale clinical trials have been performed [26].

A perfusion CT measurement consists of a dynamic series of images acquired before, during, and after an intravenous bolus of iodinated contrast material. The first pass of contrast agent through the vascular system typically comprises the first 45–60 s post-contrast. Over time, increasing amounts of contrast material pass into the extravascular space until equilibrium is reached at approximately 2 min post-contrast. The resulting temporal changes in contrast enhancement can be used to assess a range of parameters that reflect the functional status of the tissue vasculature. As a consequence of the two-compartment kinetics of a contrast agent, there are two categories of (patho)physiological data that are obtained from perfusion CT data. The intravascular phase of enhancement provides estimation of the perfusion, i.e., blood flow per unit volume or mass of tissue, and the relative blood volume. The extravascular phase can be used to evaluate vascular permeability exploiting the fact that tumor blood vessels are abnormally permeable to circulating molecules [27].

Vascular function of the imaged tissue can be expressed by means of semiquantitative and quantitative parameters. Semiquantitative parameters, such as the enhancement peak or enhancement rate, are obtained from tumor time–attenuation curves and have been shown to correlate with MVD in lung and renal cancer [28, 29]. Compartmental analysis and deconvolution represent the two most widely used quantitative analysis methods for determination of perfusion and other vascular parameters from dynamic CT data. Compartmental analysis for first-pass studies considers the intravascular and extravascular spaces as a single compartment, which can be done prior to the moment when contrast medium appears in the draining veins of the tissue of interest. Perfusion is calculated either from the maximal slope of the tissue concentration–time curve or from its peak height, normalized to the arterial input function. A two-compartment model is used for measurements of capillary permeability and blood volume [27]. Deconvolution method uses arterial and tissue time–attenuation curves to calculate the impulse residue function (IRF) for the tissue of interest, where the IRF is a theoretical tissue curve that would be obtained from an instantaneous arterial input [27]. Compartmental analysis and deconvolution methods have both been validated against other reference standards both in animals and humans, showing high accuracy and reproducibility [30–32].

Contrast-enhanced ultrasonography (CEUS) imaging emerges as the most popular medical imaging modality, which can be attributed to the low cost per examination and high safety profile. Due to poor scattering of ultrasonic waves by blood, the US contrast agents have been developed to assess the functional tissue status. The US contrast agents consist of micron-sized gas bubbles encapsulated in biodegradable shells. In contrast to both CT- and MRI-based methods, CEUS enables the visualization of tissue capillary network. This unique feature is due to a high sensitivity of US to very small amounts of contrast agent, even to a single bubble. Furthermore, because sonography is a dynamic method that is performed in real time, the tissue perfusion properties can be deduced from both the influx and washout of the contrast media. In addition, signals from the microbubbles enable the visualization of slow flow in microscopic vessels. CEUS is now routinely used for diagnosis, particularly for the detection and characterization of various liver tumors [33]. More detailed description of the methodological principles of CEUS and its clinical applicability can be found in the recent review by Postema and Gilja [34]. In addition to conventional CEUS, double contrast-enhanced ultrasound (DCUS) has been recently developed to improve the assessment of gastric cancer [35]. In clinical application of this methodology, the use of an oral US contrast agent reveals the three-layered structure of the gastric wall, while the application of an intravenous contrast reveals the dynamic features of tumor vascularity. DCUS is considered as superior to the traditional staging methods for gastric cancer since it can assess the depth of tumor penetration and the presence of lymph node metastases. In addition, a few research groups proposed blood flow measurements by Doppler ultrasonography for therapy monitoring in different malignancies [36–38].

Diffusion-weighted MR imaging (DWI) is a technique that is increasingly gaining ground within the field of oncology. The contrast in DWI is derived from differences in the microscopic movement (“diffusion”) of water protons between different tissues. The degree of water diffusion is mainly dependent on a tissue’s cellular density, the presence of intact cell membranes, and the viscosity of fluids. In tissues with a dense cellular structure, with many intact cell membranes, or within fluids with a highly viscous content, the movement of water protons is restricted. In contrast, the loss of cellularity, e.g., as a result of chemotherapy, is associated with an increase in the water diffusion and can be measured by DWI (Fig. 13.3) [39]. Diffusion weighting is typically obtained by applying two bipolar diffusion sensitizing gradients to a T2-weighted spin echo sequence. The gradient duration, the amplitude, and the interval between the two gradients together determine the degree of diffusion weighting (referred to as the “b-value”). On high b-value (e.g., b800–1000) diffusion images, the signal from most soft tissues is suppressed, and the only signal that remains is that of high cellular structures, such as malignant tumors, but also some normal anatomical structures such as nerves and lymphoid tissues. Traditionally, DWI was mainly used in neurologic imaging to detect areas of brain ischemia, an indication for which DWI has proven itself invaluable. In the early years, body DWI was not deemed feasible due to artifacts caused by limitations in the scan technique, the presence of air-filled spaces (lungs, bowels), and respiratory motion. Nowadays, however, these limitations have been largely overcome, and extracranial applications of DWI are rapidly emerging. One of the current cornerstones of DWI is the evaluation of malignancies. Numerous studies have shown the value of diffusion for the detection of malignant tumors within specific organs such as the liver and prostate [40, 41] but also in the whole-body setting to assess the extent of disease in patients with lymphoma or to screen for metastases from, for example, prostate and breast cancer [42, 43]. One of the main strengths of DWI is that it not only allows for a visual assessment but also enables the acquisition of quantitative data. When plotting the degree of signal attenuation obtained at two or more b-values logarithmically, the slope of this line can be used as a quantitative measure of diffusion: the “apparent diffusion coefficient” (ADC). ADC has been shown a useful parameter to help distinguish between benign and malignant lesions. For example, in the liver study, it has been shown that the ADC of metastatic lesions (1.05 × 10⁻³ mm²/s) and hepatocellular carcinoma (1.22 × 10⁻³ mm²/s) was significantly lower compared to benign lesions such as focal nodular hyperplasia (1.40 × 10⁻³ mm²/s), hemangiomas (1.92 × 10⁻³ mm²/s), and cysts (3.02 × 10⁻³ mm²/s) [44]. Moreover, ADC has been suggested as a potential imaging biomarker to assess and monitor the behavior of tumors after onset of cancer treatment. When a tumor responds to treatment, this is reflected by a change in its cellular microstructure, which can readily be detected as a change in its diffusion characteristics (Fig. 13.4). The use of ADC as an imaging biomarker is an appealing option; because DWI is a noninvasive technique, acquisition is relatively fast and can easily be incorporated into any clinical MRI protocol. Moreover, DWI does not require the use of exogenous contrast agents or ionizing radiation. Hence, the use of ADC as a noninvasive tumor biomarker is now frequently being explored, and successful results have been reported in various types of malignancies such as colorectal cancer, primary and metastatic liver tumors, bone tumors, and lymphoma [45–48].