Image Analysis of the Tumor Microenvironment

Abstract

In the field of pathology it is clear that molecular genomics and digital imaging represent two promising future directions, and both are as relevant to the tumor microenvironment as they are to the tumor itself (Beck AH et al. Sci Transl Med 3(108):108ra113-08ra113, 2011). Digital imaging, or whole slide imaging (WSI), of glass histology slides facilitates a number of value-added competencies which were not previously possible with the traditional analog review of these slides under a microscope by a pathologist. As an important tool for investigational research, digital pathology can leverage the quantification and reproducibility offered by image analysis to add value to the pathology field. This chapter will focus on the application of image analysis to investigate the tumor microenvironment and how quantitative investigation can provide deeper insight into our understanding of the tumor to tumor microenvironment relationship.

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

“…Current advances include protocols to reconstruct the spatial 3D architectures of DCIS from 2D histology images stained with haematoxylin and eosin (H&E) [139] and multi-tiered content-based image algorithms for classification of tumour grades [140]. Histology samples and digital microscopy analyses were also used to evaluate the differences between distinct regions of interest within the same tumour [141]. Such approaches allow for the assessment of tumour phenotypic features and tumour microenvironment landscapes at different levels of resolution [142].…”

Analysis of digital histopathology images for breast cancer diagnosis

“…Malignant tumors (Tridosaja) are very harmful, because they can affect all three major body systems, i.e. the nervous system (Vata or air), the venous system (Pitta or fire), and the arterial system (Kapha or water) lose mutual coordination and thus cannot prevent tissue damage, resulting in a deadly morbid condition [12,13]. In modern medical point of view, the cancer is defined as abnormal cell division due to a number of conditions.…”

“…Breast cancer is the common problem of not only in developed nations but also in developing countries [11]. It has been found that breast cancer is common to a large part of women [12]. In India, the death toll due to breast cancer is increasing at a rapid pace [13].…”

“…The widespread application of CAD can be found after the emergence of digital mammography in the early 1990s [14]. Recently, CAD has become a part of routine clinical detection of breast cancer on mammograms at many mass screening programs and hospitals [12] in the United States. Now the recent introduction of slide digital scanners, histopathology biopsy slides can also be digitized and kept in digital image format.…”

Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma

“…This combination meets the standards of high definition, high speed, and high throughput screening [11], which could lay a good foundation for the development and application of digital pathology. Using whole slide imaging (WSI) as the basis, combined with a series of technical equipment including (i) a image analysis system and (ii) an information management system, via deep learning of the computer, AI can effectively simulate a pathologist's brain for effective thinking and further assist in broader applications in the medical and health areas, such as disease intelligence analysis, tumour-assisted diagnosis, gene data detection, and disease drug development [12][13][14][15]. Generally, WSIs are gigapixel images stored in a multi-resolution pyramid structure where the highest resolution is × 40.…”