Accounting for tissue heterogeneity in infrared spectroscopic imaging for accurate diagnosis of thyroid carcinoma subtypes

Abstract

Fourier transform infrared (FT-IR) microscopy was used to image tissue samples from twenty patients diagnosed with thyroid carcinoma. The spectral data were then used to differentiate between follicular thyroid carcinoma and follicular variant of papillary thyroid carcinoma using principle component analysis coupled with linear discriminant analysis and a Naïve Bayesian classifier operating on a set of computed spectral metrics. Classification of patients’ disease type was accomplished by using average spectra from a wide region containing follicular cells, colloid, and fibrosis; however, classification of disease state at the pixel level was only possible when the extracted spectra were limited to follicular epithelial cells in the samples, excluding the relatively uninformative areas of fibrosis. The results demonstrate the potential of FT-IR microscopy as a tool to assist in the difficult diagnosis of these subtypes of thyroid cancer, and also highlights the importance of selectively and separately analyzing spectral information from different features of a tissue of interest.

Introduction

The thyroid is one of the largest endocrine glands in the body, and is responsible for the production of thyroxine (T4) and triiodothyronine (T3), collectively known as thyroid hormone (TH). Through the secretion of TH, the gland modulates the metabolic activity of a diverse array of tissues, increasing oxygen consumption, glucose catabolism, and breakdown of fatty acids in the liver for the synthesis of cholesterol, and these functions are required for maintaining health. The production of TH in the gland occurs at the level of the follicle, the functional unit of thyroid tissue that consist of a thin layer of epithelial cells, designated as follicular cells, surrounding a colloid-filled lumen. These follicular cells are central to the proper endocrine function of the thyroid, and are also affected in a number of thyroid-specific diseases, including cancer.

Carcinoma of the thyroid is the most common endocrine malignancy, accounting for the majority of endocrine cancer-related deaths, and its incidence is on the rise (perhaps due to improved imaging techniques); in 2016 it is estimated that thyroid cancer will account for 3.8% of all new cancer diagnoses in the United States [1]. As is the case with many cancers, early and accurate diagnosis while avoiding over-diagnosis is critical. Diagnosis includes identification of the carcinoma subtype; the two major classes are papillary thyroid carcinoma (PTC, >85% of cases) and follicular thyroid carcinoma (FTCA, 5%–15% of cases) [2].

Diagnosis is made by cytological analysis of a fine needle aspirate ordered by a clinician when a malignancy is suspected; however, sensitivity depends on the skill of the technician [3], [4]. The presence of thyroid carcinoma is confirmed by a pathologist examining a hematoxylin-and-eosin stained section of a thyroid tissue sample under a light microscope (Fig. 1). The stain allows for distinction of the different components of the diseased tissue, such as follicular cells, fibrosis, and colloid, allowing a trained observer to notice changes in the tissue architecture that may be indicative of disease. In cases where thyroid carcinoma is confirmed, surgical treatment course is either partial (lobectomy) or complete thyroidectomy. Postoperative management varies according to type of carcinoma diagnosed and risk of recurrence estimate.

An important limitation in the current diagnostic approach lies in distinguishing FTCA from a special subtype of thyroid carcinoma known as follicular variant of papillary carcinoma (FVPCA). Since its characterization in 1960, there has been much debate and uncertainty concerning the diagnosis of FVPCA, largely due to its morphological mimicry of FTCA [5], [6], [7]. FVPCA exhibits a predominantly follicular architecture, while lacking many of the keystone nuclear features necessary to make a PTC diagnosis [5]. However, though its histology mimics that of FTCA (Fig. 1), clinically FVPCA behaves similarly to PTC [8], a tumor that has better survival. The challenge in making a definitive FVPCA diagnosis is further exacerbated by poor inter-reader reliability (one study found only 39% concordance between ten experienced pathologists diagnosing FVPCA vs. FTCA) [5]. Thus it is important to find a supportive method which can improve the diagnosis of this challenging entity, especially as it may help avoid unnecessary total thyroidectomy or secondary surgery [4], [8].

Mid-infrared imaging is a promising tool for deriving chemical information from the tissue samples traditionally used in histopathology. Fourier transform infrared (FT-IR) microscopy applied to tissue imaging uses the unique absorption spectra from the biochemical constituents of a sample to detect changes in key tissue components such as nucleic acids, glycogen, collagen, and other proteins that are indicative of disease processes. By combining this spectral information with the spatial information from microscopy, biochemical changes in different tissue features can be selectively analyzed, rather than collecting spectra averaged indeterminately from diverse tissue components. This process allows the technique to provide insight into diagnosis and disease prognosis. Importantly, FT-IR imaging requires no labels or dyes, and fits into the current clinical workflow in pathology laboratories due to its compatibility with traditional frozen and formalin-fixed paraffin-embedded samples. However, the latter class of samples must be dewaxed, which can be readily conducted according to established protocols [9].

This compatibility means that FT-IR microscopy is well suited to study the spectral and structural features of thyroid carcinomas. A number of recent articles have covered using FT-IR imaging for tissue diagnostics in detail, with some preliminary work exploring thyroid tissue [9], [10], [11]. The technique holds promise as an adjunct tool to traditional histopathology for exploring the differences between FTCA and FVPCA. This work investigates the capability of FT-IR to distinguish between these disease types as well as the relative diagnostic value of different components of thyroid tissue in making that distinction.