1.

Introduction

The promise of novel biomedical imaging methods, such as optical imaging, is not only to increase the frequency and accuracy with which disease can be detected but also to improve the prediction and monitoring of disease progression or regression during treatment. A critical component of research seeking to develop new imaging concepts is validation of the image signal itself. This requires establishing the biological basis for image contrast and depends critically on achievable signal-to-background ratios. Over and above correlation of optical images with tissue morphology, there must also be validation of parametric variables obtained through optical methodologies, and validation of exogenously applied biomarkers with regards to their tissue specificity and molecular targets. In each of these instances, pathology provides the validation.

Optical imaging research groups need to develop associations between image data and standardized biophysical markers (histopathologic, morphometric, proteomic, genomic) to identify the pathologic measures that represent the most promising and appropriate surrogates for new image indices. Use of parametric indices derived from pathologic analysis of tissue specimens will ensure a standardized approach for image interpretation and spectral analysis. Such standardization will be a critical foundation for the future multicenter imaging trials that are essential for adoption of novel imaging techniques into medical practice, because tissue analysis will be performed by a broader set of collaborating pathologists.

The Network for Translational Research in Optical Imaging (NTROI), funded by the National Institutes of Health (NIH) [through the National Cancer Institute (NCI)], is a national initiative composed of networks of researchers seeking to translate new optical imaging technologies in useful modalities for different organ sites (breast, esophagus, colon). NTROI includes the Pathology Working Group (the authors of this paper), which is composed of named collaborating pathologists with input from the National Institutes of Standards and Technology (NIST). The mission of the Pathology Working Group is to develop the pathology standards necessary for support of the optical imaging research being performed within NTROI. The current NTROI utilization of pathology is given in Table 1 . The following review highlights the approach used by the Pathology Working Group to validate optical imaging standards for NTROI.

Table 1

Utilization of pathology “standards” by NTROI principals.

Table 2

Tissue correlates of optical imaging parameters.

2.

Current Approaches to Selecting Validating Biomarkers

One of the key applications of optical imaging is to identify the salient properties of human tissue that mark the presence of disease (usually neoplasia) and exhibit optical contrast. In the simplest sense, these tissue parameters constitute “biomarkers” of disease. The selection of potential biomarkers that signify tissue disease should be driven by the molecular basis of emerging technologies.¹ For example, near-infrared (NIR) spectroscopy quantifies hemoglobin and deoxyhemoglobin concentrations and provides information on tissue vascularity, oxygenation, and optical scatter.^{2, 3, 4} Magnetic resonance elastography (MRE) images tissue elasticity and hardness,^{5, 6, 7} which are properties based on the tissue stroma and long associated with breast malignancy as exploited in clinical breast exams. Other electromagnetic imaging methods^{8, 9} are believed to be sensitive to tissue cellularity, cell membrane integrity, bound water content, and ionic concentrations, which, for example, have been hypothesized to be signatures of breast malignancy.^{10, 11, 12, 13, 14, 15}

One conceptual approach to developing relevant pathological correlates of imaged tissue characteristics is to focus on the properties of the tissue compartments that change with disease progression such as (a) epithelial cells, (b) supporting stromal matrix, and (c) blood vessels. The operative concept is that, while the initiating event in disease pathogenesis (e.g., neoplastic transformation) may not be optically visible, the growth and progression of the disease process will become optically detectable. In the first instance of epithelial cell proliferation, alterations in cellular density are characteristic optical and histopathological signatures of cancer. Indeed, pathologists are trained to observe, compare, and contrast subtle changes in cell morphology (such as nuclear size, shape, and chromatin pattern; nuclear membrane irregularity; and nucleolar number and shape) and cellular density when making a clinically relevant diagnosis, be it benign, hyperplastic, dysplastic, or malignant. Optical techniques are now being developed to recapitulate these subcellular morphologic changes. Using scattering-based methods, point probe systems can now measure microscopic features, such as nuclear size and subcellular particle size, in sites such as the cervix and esophagus.^{16, 17, 18, 19}

In both the first and second instances (epithelial versus stromal changes), optical scattering, electrical current flow, and capacitance are dramatically influenced by changes in extra- and intracellular densities of macromolecules such as proteins and nucleic acids. Collagen is known to be mechanically stiff and, hence, elasticity is a key parameter for fibrous tissue stroma. Lastly, assessment of angiogenic activity in relation to collagen content may provide an indication of the presence of provisional versus mature stroma; the former being strongly associated with elevated water content. Water is an important contributor to electrical permittivity and conductivity as well as optical absorption and mechanical compressibility (or incompressibility). Blood strongly affects optical absorption as well as electrical conductivity and, to a lesser extent, electrical permittivity. Another approach to validating the image findings may be to use mathematical models to statistically compare the content of multiple independent microscopic biomedical images based on multinomial distribution. Such a model has already been used to demonstrate the synergistic effect of combination treatments (chemotherapy or radiation or both) on cancer.²⁰

An important finding of these various studies is that the discriminating tissue findings are not necessarily the cancerous tissues. The supporting stroma, vasculature, and influx of inflammatory cells may be just as important or more so as optical “signatures” for noninvasive optical imaging.

Postulated pathology correlates can be categorized according to the properties being validated (Table 2 ). Physical properties in imaged tissues (hardness and compressibility) might be assessed by comparing the different tissue-type volumes (fat versus epithelium versus stroma) at both light and electron microscopic levels. Measures of vascularity, reflecting both angiogenesis per se and vasculogenesis in general, might include vessel density, area, orientation, and tissue hypoxia or necrosis. Protein expression, analyzed by immunohistochemistry, immunofluorescence, or serum or tissue proteomics, can define angiogenesis (stimulatory or inhibitory), tissue oxygenation, stromal components, cell-cycle regulators, cytokine production, proliferation correlates, proteolytic enzymes degrading the extracellular matrix to facilitate tumor stromal invasion, and metastasis suppressors or enhancers.²¹ Autofluorescence spectroscopy in the ultraviolet-to-visible range may detect differentiating endogenous fluorophores in the epithelial and extracellular matrix.^{22, 23} Phase-contrast signals in frozen tissue may reflect optical scatter. Gene expression profiles can be used to define morphologic phenotypes, cellular adhesion, extracellular matrix, angiogenesis, and therapeutic targets. We may not yet have a clear understanding of which molecular alterations correlate with imaging findings (cancer initiation and progression versus cell-cycle regulatory proteins versus tumor-suppressor genes versus treatment response), but interinstitutional research groups should develop standardized ways of archiving tissue so that it is available for future collaborative gene array studies. Limitations encountered in NTROI studies to date include precision of sampling of the lesional tissue analyzed by optical methods in vivo;²⁴ the accuracy of the parametric morphologic measurements ex vivo; and the reliability of pathology diagnosis (to be discussed).

Perhaps most important of all, we need to ensure that standardized interinstitutional data is weighted according to its relevance in clinical outcome versus its utility in validating the imaging technology. The chosen pathology correlates must be able to differentiate a range of clinically relevant differential diagnoses: normal; benign; hyperplastic; dysplastic; malignant, noninvasive; malignant, invasive. The validation methodologies must be applied to different biopsy types depending on the organ site (biopsies, cores, excisions). Moreover, it is not a safe assumption that optical imaging or spectroscopic parameters operate on a monotonic continuum as disease progresses. The possibility must be allowed that optical signatures change in a discontinuous fashion as disease progresses. Only experimental evidence can establish whether “parametric thresholds” or optical signatures are the appropriate basis for clinical decision making. These efforts are ongoing within NTROI (Table 3 ).

Table 3

Technologic correlates of optical imaging versus pathology.

Wherever possible, the tissue must be oriented in relation to the patient and the three-dimensional orientation of the imaging method, so that direct morphologic correlations can be obtained. The need for orientation applies to both macroscopic (gross) and microscopic analysis. This is mandatory in examination of excised surgical specimens. In the case of biopsy specimens, orientation to the relevant tissue planes (e.g., mucosa and submucosa) optimizes the likelihood of meaningful correlation with the optical findings obtained prior to tissue harvest. An excellent example of such successful correlation is the recent implementation of confocal laser endomicroscopy, which utilizes the superior spatial resolution of confocal microscopy at the time of endoscopy to better understand the in vivo microarchitecture of the bowel. Used in conjunction with chromoendoscopy, the analysis of mucosal surface details is beginning to resemble a histologic examination. This technique has been applied to the in vivo diagnosis of Barrett’s epithelium and associated neoplasia, intraepithelial neoplasia in ulcerative colitis, microscopic colitis, and Helicobacter pylori.^{25, 26} Studies have already reported excellent predictions of Barrett’s esophagus (sensitivity of 98.1% and specificity of 94.1%) and associated neoplasia (sensitivity of 92.9% and specificity of 98.4%) using this technology.²⁷ Kappa statistics for inter- and intraobserver agreement for the prediction of the histopathological diagnosis are 0.843 and 0.892, respectively, raising the question of whether repeated screening gastrointestinal biopsies interpreted by a pathologist will be needed.²⁷ Whether these optical images will be interpreted at the time of endoscopy by the gastrointestinal physicians or will be sent (as images) to a pathologist for a definitive interpretation remains to be seen and raises important questions as to the future training of new medical specialists.

3.

Pathology Standardization and Validation

4.

Quantitative Reference Standards and Data Sharing

Currently, quantitative reference standards are often derived from single studies of small sample size. There is an urgent need to share standardized data across institutional research groups rather than developing local standards. The NCI-funded CaBIG (Cancer Biomedical Informatics Grid) project is creating the tools and awareness for how intra- and interinstitutional systems can communicate to share medical data, but their success depends on universal access to standardized common data elements of information such as the pathology details, tissue availability, laboratory tests, and clinical outcome data.⁴⁶ The exchange of a wide variety of data on the Web can be achieved using simple, flexible text-format-derived languages such as the Extensible Markup Language (XML). For example, this would enable universal access to the digitized images of multiple paraffin-embedded tissue samples in tissue microarrays (TMAs) with the central database providing both patient clinical information with outcomes and molecular analytical data (immunohistochemistry, in situ hybridization, etc.).⁴⁷

The ideals of standardized data exchange are shared by the Pathology Working Group within the NCI-funded NTROI, and the Laboratory Digital Imaging Project (LDIP) of the NIST. NIST is currently working with CAP to develop standardized check samples for Her2/Neu well as standards for verifying performance of optical imaging devices. The ability to image and quantitate fluorescently labeled markers in vivo has generally been limited by the autofluorescence of formalin-fixed tissue specimens. Now, with the advent of increased capabilities in existing fluorescence and brightfield microscopes, fast, accurate, and affordable multispectral analysis can be obtained. As in vivo imaging technology evolves, the need to validate in vivo images with pathology correlates will further increase. These efforts are ongoing (Table 4 ).

Table 4

Ongoing tasks for pathology support of optical imaging.

5.

Recruitment of the Pathology Community

A final activity of the Pathology Working Group is to publicize to the academic pathology community the importance of expanding the technologies practiced in pathology, especially those relevant to optical imaging. Accordingly, efforts involving automated analysis of cytometric images⁴⁸ and fast-Fourier analysis of nuclear morphometry⁴⁹ and collagen structure⁵⁰ are to be commended. In each instance, the sensorium of pathology is being expanded and in ways that may be relevant to the practice of optical imaging. Efforts to map histologic tissue sections to optical images⁵¹ also will be of value. This includes using tissue autofluorescence of NADH and flavoproteins to assess myocardial apoptosis,⁵² bioluminescence measurement of cancer to predict radiosensivity of individual malignancies,⁵³ and uptake of fluorescent biomarkers to predict tumor aggressiveness.⁵⁴ Moreover, a shift of pathology immunodiagnostics from immunohistochemistry to rigorous immunofluorescence⁵⁵ may have direct relevance to the field of optical imaging. Regardless of modality, integration of molecular diagnostics into the routine algorithms of diagnostic pathology may routinely require rigorous quantitative approaches to immunodiagnostics.^{56, 57, 58, 59}

6.

Summary

The validation of an image signal with a biological basis for image contrast, using biomarkers derived from pathology gold standards, is essential for the adoption of novel imaging techniques into medical practice. For a predictive or prognostic disease biomarker to be useful, it must be clinically important, independent, significant, and standardized with regard to methods, interpretation, and data reporting.⁶⁰ The same must apply to image-correlating biomarkers. Rigorous validation of such biomarkers must be performed with the goal of a standardized, reproducible, efficient format for clinical diagnostic implementation.⁶¹ The pathologist, by providing diagnostic reproducibility, access to correlating biopsy material, and molecular expertise, should be an integral part of any team that is validating novel imaging modalities.