Diagnostic Pathology
SCIE-ISI SCOPUS (2006-2023)
1746-1596
Cơ quản chủ quản: BioMed Central Ltd. , BMC
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Immunohistochemical (IHC) assays performed on formalin-fixed paraffin-embedded (FFPE) tissue sections traditionally have been semi-quantified by pathologist visual scoring of staining. IHC is useful for validating biomarkers discovered through genomics methods as large clinical repositories of FFPE specimens support the construction of tissue microarrays (TMAs) for high throughput studies. Due to the ubiquitous availability of IHC techniques in clinical laboratories, validated IHC biomarkers may be translated readily into clinical use. However, the method of pathologist semi-quantification is costly, inherently subjective, and produces ordinal rather than continuous variable data. Computer-aided analysis of digitized whole slide images may overcome these limitations. Using TMAs representing 215 ovarian serous carcinoma specimens stained for S100A1, we assessed the degree to which data obtained using computer-aided methods correlated with data obtained by pathologist visual scoring. To evaluate computer-aided image classification, IHC staining within pathologist annotated and software-classified areas of carcinoma were compared for each case. Two metrics for IHC staining were used: the percentage of carcinoma with S100A1 staining (%Pos), and the product of the staining intensity (optical density [OD] of staining) multiplied by the percentage of carcinoma with S100A1 staining (OD*%Pos). A comparison of the IHC staining data obtained from manual annotations and software-derived annotations showed strong agreement, indicating that software efficiently classifies carcinomatous areas within IHC slide images. Comparisons of IHC intensity data derived using pixel analysis software versus pathologist visual scoring demonstrated high Spearman correlations of 0.88 for %Pos (p < 0.0001) and 0.90 for OD*%Pos (p < 0.0001). This study demonstrated that computer-aided methods to classify image areas of interest (e.g., carcinomatous areas of tissue specimens) and quantify IHC staining intensity within those areas can produce highly similar data to visual evaluation by a pathologist.
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The subtype distribution of lymphoid neoplasms in Southwest China was analyzed according to WHO classifications. This study aims to analyze subtype distribution of lymphomas in southwest China.
Lymphoid neoplasms diagnosed within 9 years in a single institution in Southwest China were analyzed according to the WHO classification.
From January 2000 to December 2008, a total number of 6,382 patients with lymphoma were established, of which mature B-cell neoplasms accounted for 56%, mature T- and NK-cell neoplasms occupied 26%, and precursor lymphoid neoplasms and Hodgkin lymphomas were 5% and 13%, respectively. Mixed cellularity (76%) was the major subtype of classical Hodgkin lymphoma; and the bimodal age distribution was not observed. The top six subtypes of non-Hodgkin lymphoma were as follows: diffuse large B-cell lymphoma, extranodal NK/T-cell lymphoma, nasal type, extranodal marginal zone lymphoma of mucosa associated lymphoid tissue, follicular lymphoma, precursor lymphoid neoplasms, and chronic lymphocytic leukemia/small lymphocytic lymphoma. Extranodal lymphomas comprised about half of all cases, and most frequently involved Waldeyer's ring, gastrointestinal tract, sinonasal region and skin.
The lymphoid neoplasms of Southwest China displayed some epidemiologic features similar to those reported in literature from western and Asian countries, as well as other regions of China, whereas some subtypes showed distinct features. The high frequency of mature T/NK cell neoplasms and extranodal lymphomas, especially for extranodal NK/T-cell lymphoma, nasal type, is the most outstanding characteristic of this series.
Metastatic adenocarcinoma from an unknown primary site is a common clinical problem. Determining the cytokeratin (CK) 7/CK20 pattern of tumors is one of the most helpful procedures for this purpose since the CK7-/CK20+ pattern is typical of colorectal adenocarcinomas. CDX2, a critical nuclear transcription factor for intestinal development, is expressed in intestinal epithelium and adenocarcinomas. In the present study, we compared the sensitivity and specificity of CDX2 expression and the CK7-/CK20+ phenotype in differentiating colorectal adenocarcinomas from pancreatic and gastric adenocarcinomas.
CK7/CK20 staining pattern and CDX2 expression were evaluated in 118 cases of colorectal, 59 cases of gastric, and 32 cases of pancreatic adenocarcinomas. The sensitivity, specificity, and positive and negative predictive values of the CK7-/CK20+ phenotype and of CDX2 expression were analyzed.
The CK7-/CK20+ immunophenotype was expressed by 75 of 118 (64%) colorectal and 3 of 59 (5%) gastric tumors and was not observed in any pancreatic adenocarcinomas. The CK7+/CK20+ immunophenotype was expressed in 24/118 (20%) of colon, 28/59 (48%) of gastric and 7/32 (22%) of pancreatic adenocarcinomas. The CK7+/CK20- expression pattern was observed in only 2% (2 of 118) of colorectal carcinomas. CDX2 was expressed in 114 of 118 (97%) colorectal, 36 of 59 (61%) gastric, and 5 of 32(16%) pancreatic adenocarcinomas. There was no significant association between CDX2 expression and tumor differentiation in colorectal carcinomas. In gastric carcinomas, CDX2 expression was more common in intestinal type tumors than in diffuse type carcinomas. The CK7-/CK20+ phenotype showed a specificity of 96.7% in predicting colorectal adenocarcinomas, which was superior to that of CDX2 expression. CDX2 expression at both cut-off levels (> 5% and > 50%) had a higher sensitivity (96.6% and 78%) than the CK phenotype.
Both the CK7-/CK20+ phenotype and expression of the antibody CDX2 are highly specific and sensitive markers of colorectal origin. CDX2 expression should be a useful adjunct for the diagnosis of intestinal adenocarcinomas, particularly when better established markers such as CK7 and CK20 yield equivocal results. The CK7-/CK20+ phenotype is superior in its specificity and positive predictive value and might be preferred.
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Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases.
We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections.
The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies.
The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity.
The world is currently witnessing a major devastating pandemic of Coronavirus disease-2019 (COVID-19). This disease is caused by a novel coronavirus named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). It primarily affects the respiratory tract and particularly the lungs. The virus enters the cell by attaching its spike-like surface projections to the angiotensin-converting enzyme-2 (ACE-2) expressed in various tissues. Though the majority of symptomatic patients have mild flu-like symptoms, a significant minority develop severe lung injury with acute respiratory distress syndrome (ARDS), leading to considerable morbidity and mortality. Elderly patients with previous cardiovascular comorbidities are particularly susceptible to severe clinical manifestations.
Currently, our limited knowledge of the pathologic findings is based on post-mortem biopsies, a few limited autopsies, and very few complete autopsies. From these reports, we know that the virus can be found in various organs but the most striking tissue damage involves the lungs resulting almost always in diffuse alveolar damage with interstitial edema, capillary congestion, and occasional interstitial lymphocytosis, causing hypoxia, multiorgan failure, and death. A few pathology studies have also reported intravascular microthrombi and pulmonary thrombembolism. Although the clinical presentation of this disease is fairly well characterized, knowledge of the pathologic aspects remains comparatively limited.
In this review, we discuss clinical, pathologic, and genomic features of COVID-19, review current hypotheses regarding the pathogenesis, and briefly discuss the clinical characteristics. We also compare the salient features of COVID-19 with other coronavirus-related illnesses that have posed significant public health issues in the past, including SARS and the Middle East Respiratory Syndrome (MERS).