Spectral morphometric characterization of breast carcinoma cells

Nuclear image analysis study of neuroendocrine tumors

BACKGROUND

There is a subjective disagreement about nuclear chromatin in the field of pathology. Objective values of red, green, and blue (RGB) light intensities for nuclear chromatin can be obtained through a quantitative analysis using digital images.

METHODS

We examined 10 cases of well differentiated neuroendocrine tumors of the rectum, small cell lung carcinomas, and moderately differentiated squamous cell lung carcinomas respectively. For each case, we selected 30 representative cells and captured typical microscopic findings. Using an image analyzer, we determined the longest nuclear line profiles and obtained graph files and Excel data on RGB light intensities. We assessed the meaningful differences in graph files and Excel data among the three different tumors.

RESULTS

The nucleus of hematoxylin and eosin-stained tumor cells was expressed as a combination of RGB light sources. The highest intensity was from blue, whereas the lowest intensity was from green. According to the graph files, green showed the most noticeable change in the light intensity, which is consistent with the difference in standard deviations.

CONCLUSIONS

The change in the light intensity for green has an important implication for differentiating between tumors. Specific features of the nucleus can be expressed in specific values of RGB light intensities.

Spectrally encoded spectral imaging

Spectral imaging, i.e. the acquisition of the spectrum emitted from each sample location, is a powerful tool for a wide variety of applications in science and technology. For biomedical applications, spectral imaging is important for accurate analysis of a biological specimen and for assisting clinical diagnosis, however it could be challenging mainly due to the typically low damage thresholds and strict time constraints. Here, we present a fiber-based technique termed spectrally encoded spectral imaging (SESI), in which a fully emitted spectrum is captured from each resolvable point of a specimen using an additional lateral scanning of the spectrally encoded line. The technique is demonstrated by capturing spectral data cubes of a color print and of a green leaf, and its potential advantage in signal-to-noise ratio is theoretically discussed. Using a miniaturized grating-lens configuration, SESI could be conducted endoscopically, allowing minimally invasive color and spectral imaging in remote locations of the body.

Novel round-robin tabu search algorithm for prostate cancer classification and diagnosis using multispectral imagery

Quantitative cell imagery in cancer pathology has progressed greatly in the last 25 years. The application areas are mainly those in which the diagnosis is still critically reliant upon the analysis of biopsy samples, which remains the only conclusive method for making an accurate diagnosis of the disease. Biopsies are usually analyzed by a trained pathologist who, by analyzing the biopsies under a microscope, assesses the normality or malignancy of the samples submitted. Different grades of malignancy correspond to different structural patterns as well as to apparent textures. In the case of prostate cancer, four major groups have to be recognized: stroma, benign prostatic hyperplasia, prostatic intraepithelial neoplasia, and prostatic carcinoma. Recently, multispectral imagery has been used to solve this multiclass problem. Unlike conventional RGB color space, multispectral images allow the acquisition of a large number of spectral bands within the visible spectrum, resulting in a large feature vector size. For such a high dimensionality, pattern recognition techniques suffer from the well-known "curse-of-dimensionality" problem. This paper proposes a novel round-robin tabu search (RR-TS) algorithm to address the curse-of-dimensionality for this multiclass problem. The experiments have been carried out on a number of prostate cancer textured multispectral images, and the results obtained have been assessed and compared with previously reported works. The system achieved 98%-100% classification accuracy when testing on two datasets. It outperformed principal component/linear discriminant classifier (PCA-LDA), tabu search/nearest neighbor classifier (TS-1NN), and bagging/boosting with decision tree (C4.5) classifier.

Spectral imaging perspective on cytomics

BACKGROUND

Cytomics involves the analysis of cellular morphology and molecular phenotypes, with reference to tissue architecture and to additional metadata. To this end, a variety of imaging and nonimaging technologies need to be integrated. Spectral imaging is proposed as a tool that can simplify and enrich the extraction of morphological and molecular information. Simple-to-use instrumentation is available that mounts on standard microscopes and can generate spectral image datasets with excellent spatial and spectral resolution; these can be exploited by sophisticated analysis tools.

METHODS

This report focuses on brightfield microscopy-based approaches. Cytological and histological samples were stained using nonspecific standard stains (Giemsa; hematoxylin and eosin (H&E)) or immunohistochemical (IHC) techniques employing three chromogens plus a hematoxylin counterstain. The samples were imaged using the Nuance system, a commercially available, liquid-crystal tunable-filter-based multispectral imaging platform. The resulting data sets were analyzed using spectral unmixing algorithms and/or learn-by-example classification tools.

RESULTS

Spectral unmixing of Giemsa-stained guinea-pig blood films readily classified the major blood elements. Machine-learning classifiers were also successful at the same task, as well in distinguishing normal from malignant regions in a colon-cancer example, and in delineating regions of inflammation in an H&E-stained kidney sample. In an example of a multiplexed ICH sample, brown, red, and blue chromogens were isolated into separate images without crosstalk or interference from the (also blue) hematoxylin counterstain.

CONCLUSION

Cytomics requires both accurate architectural segmentation as well as multiplexed molecular imaging to associate molecular phenotypes with relevant cellular and tissue compartments. Multispectral imaging can assist in both these tasks, and conveys new utility to brightfield-based microscopy approaches.

Spectral characteristics of acute lymphoblastic leukemia in childhood

Although the differentiation and classification of acute leukemia are based upon cytochemical features as well as immunologic, cytogenetic, and molecular characteristics, in many cases the morphological distinction of normal lymphocytes from lymphoblasts of acute lymphoblastic leukemia (ALL) is difficult using light microscopy. In this study the distinction between normal lymphocytes and lymphoblasts of childhood ALL is proposed using their spectral characteristics. The method has been based upon the analysis and classification of optical absorption characteristics of the bone marrow cells. Spectral microscopy system is capable of capturing a great number of narrow-band images, in the wide spectral range of the optical spectrum. The analysis showed statistically significant difference (P < 0.0001) between normal lymphocytes and lymphoblasts as far as it concerns the detection, identification and mapping of their spectral absorption characteristics. Our results suggest the potential of spectral imaging as a new method for the distinction of lymphocytes from lymphoblasts in cases that with the light microscope, the morphologic differences are not visible in the bone marrow smears at diagnosis or the follow up of the children with ALL.

Lobular carcinoma with cytoplasmic granules

We report on a case of invasive lobular carcinoma of the breast with a previously undescribed cytologic feature. Diff-Quik-stained cytologic preparations showed uniform single cells with prominent coarse cytoplasmic granules. Ultrastructurally, the granules showed features suggestive of autophagosomes and/or degenerative mitochondria. The cytologic differential diagnosis included granulocytic sarcoma, metastatic melanoma, extramedullary hematopoiesis, large granulocytic leukemia/lymphoma, and mast-cell tumor. Adjunctive studies were helpful in the diagnosis of carcinoma. Histologic study of the mastectomy specimen showed classic type of invasive lobular carcinoma.

Structural characterization of erythroid and megakaryocytic differentiation in Friend erythroleukemia cells

OBJECTIVE

The aim of this study was to examine the structural characterization of erythroid and megakaryocytic cell differentiation in Friend erythroleukemic cells using spectral imaging and electron microscopy.

MATERIALS AND METHODS

Two variants of Friend erythroleukemia cells were treated with hexamethylene bisacetamide (HMBA) to induce differentiation: 1) MEL, which exhibit the normal phenotype and are susceptible to differentiation; and 2) the resistant R1 cells. The cells were analyzed by spectral imaging along with transmission and scanning electron microscopy. The expression of cell cycle regulatory proteins was analyzed by Western blotting.

RESULTS

Spectral imaging of HMBA-treated MEL and R1 cells stained by May-Grünwald-Giemsa and subjected to spectral similarity mapping revealed five morphologic cell types: proerythroblast-like cells, normoblast-like cells, reticulocyte-like cells, megakaryocytes, and apoptotic cells. In MEL cells, both megakaryocytic differentiation characterized by nuclear lobes and erythroid differentiation characterized by accumulation of hemoglobin were detected; R1 cells were not committed to terminal differentiation. HMBA-induced cell cycle arrest at G(1) affected the expression of regulatory proteins in a similar manner in both types of cells. Expression of cyclin-dependent kinase 4 decreased and expression of p21(WAF1) increased. The level of the underphosphorylated form of phosphorylated retinoblastoma protein increased, inducing a decrease in the level of c-myc. In addition, we detected a decrease in the expression of the anti-apoptotic regulator, Bcl-2, and an increased expression of the pro-apoptotic regulator, Bax.

CONCLUSIONS

Spectral imaging provides new insight for the morphologic characterization of erythroid and megakaryocytic cell differentiation as well as apoptosis. Image analysis was well correlated to cell cycle arrest and the expression of regulatory proteins.