In the preclinical stages of the drug development process, key priorities include target identification and validation, identification of promising drug compound leads, and demonstration of target engagement as proof of concept. This process typically occurs first in in vitro studies of appropriate cell lines and then in preclinical in vivo animal studies and may initially involve high-throughput screening of thousands of candidate compounds to identify a handful of promising leads. The most sought-after imaging biomarkers during the preclinical stage will provide information on activity at the cellular and molecular levels. A comprehensive review of imaging biomarkers for preclinical drug development is beyond the scope of this chapter, which is focused on imaging biomarkers for human clinical trials.

Investigational agents undergo increasingly rigorous clinical testing as they progress along the path toward regulatory approval. Phase 1 and 2 studies are typically smaller trials designed to establish initial safety and dosing data and to demonstrate efficacy in small study populations. Phase 3 studies are typically much larger and more costly multisite trials aimed at collecting the necessary safety and efficacy data to support a marketing application to regulatory authorities. Given the expense involved in proceeding from phase 2 into phase 3 testing, a key objective in early clinical trials is gathering sufficient preliminary efficacy data to inform a “go or no-go” decision on continuing into phase 3 studies.

The most relevant imaging biomarkers during clinical trials will be those that provide evidence of drug efficacy as well as those that select for patient subgroups in whom drug efficacy may be higher [11, 12]. In phase 1 and phase 2 trials, investigators may choose to incorporate biomarker endpoints from a constantly expanding menu of advanced imaging techniques, presumably selecting approaches that report on functional or compositional variables correlated with the mechanism of drug action. It is in this context that the advanced techniques described in this text are currently most relevant for demonstrating the efficacy of novel molecularly targeted agents. In phase 3 trials, the most important biomarkers will be those that are reproducible across large, multisite trials and those that have been rigorously confirmed as acceptable surrogate endpoints for survival. The requirements for imaging biomarkers may be more stringent for late-stage than for early-stage clinical trials because biomarker results from early-stage clinical trials are used primarily by the trial sponsor for internal decision making, while results from late-stage clinical trials will be scrutinized by outside regulatory authorities in the drug approval process.

Imaging-based tumor size measurement assessment guidelines for solid malignancies were first codified in the 1980 World Health Organization criteria [13] and were revised as the Response Evaluation Criteria in Solid Tumors (RECIST) in 2000 [14] and RECIST 1.1 in 2009 [15]. The Macdonald criteria for supratentorial malignant glioma were proposed in 1990 [16]. The International Working Group (IWG) or Cheson criteria for hematologic malignancies were first issued in 1999 [17] and were revised in 2007 [18]. These response assessment tools have enjoyed widespread utilization in the scientific, industrial, and regulatory communities, and new drug approval applications routinely include results using these imaging biomarkers to support efficacy claims.

RECIST was explicitly designed for use in phase 2 clinical trials (although it is used at other stages in drug development and even clinically) and is essentially a guideline for assessing tumor response and progression based on changes in anatomical tumor burden over time. RECIST specifies criteria for categorizing lesions on baseline (i.e., pretreatment) imaging as either “target” or “nontarget” lesions, with the former to be followed with successive quantitative size measurements and the latter to be followed qualitatively. At follow-up imaging (i.e., during treatment), lesion burden is reassessed in standardized fashion, with target lesions reevaluated as the sum of their unidimensional size measurements and nontarget lesions reevaluated subjectively according to changes perceived by the reviewer. At each imaging timepoint (typically a predetermined follow-up interval specified in the study protocol), patients are assigned one of four response categories: complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). These patient-level response categories can then be used to construct summary trial endpoints including objective response rate (ORR, i.e., the percentage of patients achieving either PR or CR), time to progression (TTP, i.e., average time until PD), and progression-free survival (PFS, i.e., average time until PD or death).

As present time, most clinical trial protocols for solid malignancies specify one or more of these RECIST-derived imaging biomarkers as endpoints for assessing efficacy of the investigational agent. Although ORR is still widely utilized, PFS and other “time-to-event” biomarkers are increasingly incorporated as primary efficacy endpoints, especially in late-stage randomized clinical trials [19]. Recent National Cancer Institute (NCI) task force recommendations have specifically encouraged the use of PFS as a primary efficacy endpoint in phase 2 clinical trials [20]. The ascendancy of PFS has paralleled the introduction of cytostatic agents into the therapeutic armamentarium; these agents, in contrast to traditional cytotoxic agents, result in cell cycle arrest rather than cell death and may be less likely to produce gross tumor shrinkage, although patients may benefit from a delay in tumor progression which would be captured in PFS but not in ORR.

How well do tumor size-based biomarkers perform for response assessment? In the phase 2 clinical trial setting, ORR is generally accepted as a valid indicator of antitumor efficacy because objective responses are infrequent in the absence of efficacious treatment [21]. There also exists a small but important literature linking objective tumor response to clinical survival benefit [22, 23], to success in later-stage clinical testing [24], and to future regulatory approval [25]. In general, however, tumor shrinkage is considered an unreliable surrogate for survival, one that may either overestimate or underestimate a drug’s effect on the relevant clinical endpoint [15, 26] and one that may have a different correlation with survival in different tumor types or with different drug agents [25, 27]. PFS, meanwhile, has been correlated with survival only in certain tumor types (particular advanced colorectal and ovarian cancers) [28], and biostatisticians have cautioned against extrapolating survival associations even in these tumor types to novel anticancer therapies [27]. Although tumor size-based endpoints have become an important basis for oncology drug regulatory approval [21, 29], there have been several high-profile examples of authorities having granted accelerated approval to new anticancer drugs based on tumor size measurement data, only to rescind or narrow the approval as postmarketing data failed to show a survival benefit; notable examples include U.S. Food and Drug Administration (FDA) approvals of gefitinib (Iressa) for non-small cell lung cancer and, more recently, bevacizumab (Avastin) for metastatic breast cancer.

The shortcomings of RECIST have been well publicized [30, 31] and fall into two general categories: practical problems with its implementation and more fundamental objections to a size-based approach to response assessment. Practical problems with implementing RECIST include difficulties choosing target lesions representative of total tumor burden, the need to assess many lesions on a qualitative and subjective basis, and high intraobserver and interobserver variability for heterogeneous lesions or lesions with irregular borders [32]. Single-axis measurements as dictated by RECIST may not adequately capture size changes in nonspherical lesions or lesions with asymmetric growth. Lesions along curved surfaces, abutting other organs, or adjacent to other pathology may be difficult to measure by RECIST guidelines. Finally, the use of categorical rather than continuous response variables may sacrifice statistical power.

A more fundamental objection to RECIST is that an exclusive focus on tumor size may exclude other potentially meaningful features, including morphologic, compositional, and functional parameters that may provide a more comprehensive assessment of tumor status. Tumor size change may lag weeks to months behind a tumor biological response or may never occur at all. Size measurement criteria may therefore underestimate or fail to capture antitumor efficacy, especially of newer targeted agents that produce a cytostatic rather than cytotoxic effect.

These considerations are motivating ongoing efforts within the oncologic imaging community to improve upon current tumor size measurement biomarkers. These efforts fall into two general categories: incremental modifications to size-based biomarkers and novel imaging techniques reporting on parameters other than tumor size.

Other important modifications of tumor size measurement techniques under current investigation include three-dimensional volumetric measurement approaches [33] and customized response assessment guidelines tailored to specific tumor types. Examples of the latter include the Choi criteria for gastrointestinal stromal tumors [34], the modified RECIST (mRECIST) criteria for hepatocellular carcinoma [35], and the immune-related response criteria (irRC) for melanoma immune modulator therapies [36].

In addition, the RECIST and IWG criteria themselves are dynamic systems that continue to evolve and incorporate new techniques. The most recent IWG criteria incorporate fluorodeoxyglucose positron emission tomography (FDG-PET) on a variable basis depending on the FDG avidity of the lymphoma subtype [18]. RECIST 1.1 also incorporates FDG-PET, albeit on a limited basis as an indicator of disease progression [15]. In general, despite much enthusiasm for the potential of metabolic imaging, response assessment guidelines have been slow to incorporate FDG-PET, especially for solid malignancies. This is due, at least in part, to the great challenge in optimizing and standardizing techniques to enable comparable results to be obtained by different vendors and institutions.

Perhaps the most basic definition of cancer is that it is a set of diseases characterized by unregulated cell growth and proliferation. Furthermore, since many anticancer drugs have as their ultimate goal destruction of tumor cells, imaging methods sensitive to changes to tissue cellularity are of great importance. The typical application of histology and molecular biology in living systems is somewhat limited as it cannot provide a noninvasive deep tissue visualization of cells and molecules of interest. In particular, the visualization of cellular and molecular activity in animals normally requires the sacrifice and destruction of the organism to allow for analysis by histology and molecular biology. The development of cellular and molecular imaging techniques has begun to bridge this gap.