The Immune Response in Nonmetastatic Axillary Lymph Nodes Is Associated with the Presence of Axillary Metastasis and Breast Cancer Patient Outcome.

Tumor cells can modify the immune response in primary tumors and in the axillary lymph nodes with metastasis (ALN+) in breast cancer (BC), influencing patient outcome. We investigated whether patterns of immune cells in the primary tumor and in the axillary lymph nodes without metastasis (ALN-) differed between patients diagnosed without ALN+ (diagnosed-ALN-) and with ALN+ (diagnosed-ALN+) and the implications for clinical outcome. Eleven immune markers were studied using immunohistochemistry, tissue microarray, and digital image analysis in 141 BC patient samples (75 diagnosed-ALN+ and 66 diagnosed-ALN-). Two logistic regression models were derived to identify the clinical, pathologic, and immunologic variables associated with the presence of ALN+ at diagnosis. There are immune patterns in the ALN- associated with the presence of ALN+ at diagnosis. The regression models revealed a small subgroup of diagnosed-ALN+ with ALN- immune patterns that were more similar to those of the ALN- of the diagnosed-ALN-. This small subgroup also showed similar clinical behavior to that of the diagnosed-ALN-. Another small subgroup of diagnosed-ALN- with ALN- immune patterns was found whose members were more similar to those of the ALN- of the diagnosed-ALN+. This small subgroup had similar clinical behavior to the diagnosed-ALN+. These data suggest that the immune response present in ALN- at diagnosis could influence the clinical outcome of BC patients.

Digital image analysis in breast cancer: an example of an automated methodology and the effects of image compression.

In the current practice of pathology, the evaluation of immunohistochemical (IHC) markers represents an essential tool. The manual quantification of these markers is still laborious and subjective, and the use of computerized systems for digital image (DI) analysis has not yet resolved the problems of nuclear aggregates (clusters). Furthermore, the volume of DI storage continues to be an important problem in computer-assisted pathology. In the present study we have developed an automated procedure to quantify IHC nuclear markers in DI with a high level of clusters. Furthermore the effects of JPEG compression in the image analysis were evaluated. The results indicated that there was an agreement with the results of both methods (automated vs. manual) in almost 90% of the analyzed images. On the other hand, automated count differences increase as the compression level increase, but only in images with a high number of stained nuclei (>nuclei/image) or with high area cluster (>25µm2). Some corrector factors were developed in order to correct this count differences. In conclusion, the proposed automated procedure is an objective, faster than manual counting and reproducible method that has more than 90% of similarity with manual count. Moreover, the results demonstrate that with correction factors, it is possible to carry out unbiased automated quantifications on IHC nuclear markers in compressed DIs.

Quantification of diverse subcellular immunohistochemical markers with clinicobiological relevancies: validation of a new computer-assisted image analysis procedure.

Tissue microarray technology and immunohistochemical techniques have become a routine and indispensable tool for current anatomical pathology diagnosis. However, manual quantification by eye is relatively slow and subjective, and the use of digital image analysis software to extract information of immunostained specimens is an area of ongoing research, especially when the immunohistochemical signals have different localization in the cells (nuclear, membrane, cytoplasm). To minimize critical aspects of manual quantitative data acquisition, we generated semi-automated image-processing steps for the quantification of individual stained cells with immunohistochemical staining of different subcellular location. The precision of these macros was evaluated in 196 digital colour images of different Hodgkin lymphoma biopsies stained for different nuclear (Ki67, p53), cytoplasmic (TIA-1, CD68) and membrane markers (CD4, CD8, CD56, HLA-Dr). Semi-automated counts were compared to those obtained manually by three separate observers. Paired t-tests demonstrated significant differences between intra- and inter-observer measurements, with more substantial variability when the cellular density of the digital images was > 100 positive cells/image. Overall, variability was more pronounced for intra-observer than for inter-observer comparisons, especially for cytoplasmic and membrane staining patterns (P < 0.0001 and P = 0.050). The comparison between the semi-automated and manual microscopic measurement methods indicates significantly lower variability in the results yielded by the former method. Our semi-automated computerized method eliminates the major causes of observer variability and may be considered a valid alternative to manual microscopic quantification for diagnostic, prognostic and therapeutic purposes.

Effects of image compression on automatic count of immunohistochemically stained nuclei in digital images.

This study investigates the effects of digital image compression on automatic quantification of immunohistochemical nuclear markers. We examined 188 images with a previously validated computer-assisted analysis system. A first group was composed of 47 images captured in TIFF format, and other three contained the same images converted from TIFF to JPEG format with 3x, 23x and 46x compression. Counts of TIFF format images were compared with the other three groups. Overall, differences in the count of the images increased with the percentage of compression. Low-complexity images (< or =100 cells/field, without clusters or with small-area clusters) had small differences (<5 cells/field in 95-100% of cases) and high-complexity images showed substantial differences (<35-50 cells/field in 95-100% of cases). Compression does not compromise the accuracy of immunohistochemical nuclear marker counts obtained by computer-assisted analysis systems for digital images with low complexity and could be an efficient method for storing these images.

JPEG2000 for automated quantification of immunohistochemically stained cell nuclei: a comparative study with standard JPEG format.

The Joint Photographic Experts Group (JPEG) standard format is one of the most widely used in image compression technologies. More recently, JPEG2000 format has emerged as a state-of-the-art technology that provides substantial improvements in picture quality at higher compression ratios. However, there has been no attempt to date to determine which of the two compression formats produces less variability in the automated evaluation of immunohistochemically stained digital images in agreement with their compression rates and complexity degrees. The evaluation of Ki67 and FOXP3 immunohistochemical nuclear markers was performed in a total of 329 digital images: 47 were captured in uncompressed Tagged Image File Format (TIFF), 141 were converted to three JPEG compressed formats (47 each with 1:3, 1:23 and 1:46 compression) and 141 were converted to three JPEG2000 compressed formats (47 each with 1:3, 1:23 and 1:46 compression). The count differences between images in TIFF versus JPEG formats were compared with those obtained between images in TIFF versus JPEG2000 formats at the three levels of compression. It was found that, using JPEG2000 compression, the results of the stained nuclei count are close enough to the results obtained with uncompressed images, especially in highly complex images at minimum and medium compression. Otherwise, in images of low complexity, JPEG and JPEG2000 had similar count efficiency to that of the original TIFF images at all compression levels. These data suggest that JPEG2000 could give rise to an efficient means of storage, reducing file size and storage capacity, without compromise on the immunohistochemical analytical quality.

Appraisal of immune response in lymphoproliferative syndromes: a systematic review.

In lymphoproliferative syndromes, tumoural-immune cell interactions depend on a number of factors related to tumoural and immune cells. Recent gene expression data tend to confirm the decisive role of the reactive microenvironment in the development and clinical behaviour of lymphoproliferative syndromes, and encourage particular interest in the role of T cells and accessory cells. This systematic review brings together the accumulated knowledge about "immune signatures" in Hodgkin and non-Hodgkin lymphomas. Extracted results revealed that the presence of T lymphocytes, regulatory T cells and non-activated CTL in the reactive microenvironment appear commonly to be related with a favourable outcome in the majority of lymphoproliferative syndromes, whereas the presence of TAM, NK cells and activated CTLs appear more usually related with a poor prognosis. The direct involvement of these "immune signatures" in the histopathological morphology, classification, clinicobiological characteristics and outcome of affected patients stimulates the search for new and more appropriate immunotherapeutic strategies.

Automated quantification of nuclear immunohistochemical markers with different complexity.

Manual quantification of immunohistochemically stained nuclear markers is still laborious and subjective and the use of computerized systems for digital image analysis have not yet resolved the problems of nuclear clustering. In this study, we designed a new automatic procedure for quantifying various immunohistochemical nuclear markers with variable clustering complexity. This procedure consisted of two combined macros. The first, developed with a commercial software, enabled the analysis of the digital images using color and morphological segmentation including a masking process. All information extracted with this first macro was automatically exported to an Excel datasheet, where a second macro composed of four different algorithms analyzed all the information and calculated the definitive number of positive nuclei for each image. One hundred and eighteen images with different levels of clustering complexity was analyzed and compared with the manual quantification obtained by a trained observer. Statistical analysis indicated a great reliability (intra-class correlation coefficient > 0.950) and no significant differences between the two methods. Bland-Altman plot and Kaplan-Meier curves indicated that the results of both methods were concordant around 90% of analyzed images. In conclusion, this new automated procedure is an objective, faster and reproducible method that has an excellent level of accuracy, even with digital images with a high complexity.

Immunohistochemical patterns of reactive microenvironment are associated with clinicobiologic behavior in follicular lymphoma patients.

PURPOSE: Recent molecular data have suggested that non-neoplastic cells are powerful modulators that may confer a selective advantage or disadvantage on the outcome of follicular lymphoma (FL) patients. PATIENTS AND METHODS: The prevalence of the principal inflammatory and immune-infiltrated cells was measured immunohistochemically in the tissue of 211 FL patients, and associations were sought with their traditional clinicobiologic characteristics. RESULTS: Our results confirmed the presence of a large number of T lymphocytes (CD4+ and CD8+) and CD57+ cells and, at a moderate level, the presence of TIA-1+ cytotoxic cells, CD68+ macrophages, CD123+ plasmacytoid cells, and FOXP3+ regulatory T cells among the pool of non-neoplastic cells. In addition to the conventional clinical variables, univariate analysis identified a low level of infiltrated CD8+ T lymphocytes as a significantly negative prognostic factor of overall survival. The following significant differences in the abundance of cells of specific and nonspecific immunity were observed in relation to the clinicobiologic features of FL: (1) a reactive microenvironment mainly made up of T lymphocytes and macrophages was significantly associated with a favorable clinical behavior of FL patients; and (2) a reactive microenvironment infiltrated predominantly by CD57+ T cells was associated with a significantly higher frequency of adverse clinicobiologic manifestations such as "B" symptoms and bone marrow involvement. CONCLUSION: Our results demonstrate the existence of two specific patterns in the reactive microenvironment of FL, an immunosurveillance pattern (T lymphocytes and macrophages) and an immune-escape pattern (CD57+ T cells), that were directly associated with the clinicobiologic features of these patients.