Automated topographical cell proliferation analysis

BACKGROUND: Cell proliferation is often studied using the incorporation of bromodeoxyuridine (BrdU). Immunohistochemical staining is then used to detect BrdU in the nucleus. To circumvent the observer bias and labor-intensive nature of manually counting BrdU-labeled nuclei, an automated topographical cell proliferation analysis method is developed. METHODS: Sections stained with fluorescein-labeled anti-BrdU and counterstained with To-Pro-3 are scanned using confocal laser scanning microscopy (CLSM). For every point in the image, the nucleus density of BrdU-labeled nuclei and the total nucleus density of the neighborhood of that point are calculated from the BrdU and the To-Pro-3 signal, respectively. The ratio of these densities gives an indication of the amount of cell proliferation at that point. The automated measure is validated by comparing it with the ratio of BrdU-stained nuclei to the total number of nuclei obtained from a manual count. RESULTS: A positive correlation is found between the automated measure and the ratios calculated from the manual counting (r = 0.86, P < 0.001). Calculating the topographical cell proliferation using the automated method is faster and does not suffer from interobserver variability. CONCLUSIONS: Automated topographical cell proliferation analysis is a fast method to objectively find differences in cell proliferation within a tissue. This can be visualized by a topographical map that corresponds to the tissue under study.     

Well Differentiated Follicular Neoplasms of the Thyroid: Reproducibility and Validity of A''Decision Tree''Classification Based On Nucleolar and Karyometric Features

This study was conducted on fine-needle aspirates of well differentiated follicular neoplasms of the thyroid. A 'decision tree' classification based on the percentage of nucleolated nuclei, percentage of nuclei with two or more nucleoli and mean major nuclear diameter was adopted. We observed that the reproducibility and the validity of the follicular adenoma vs follicular carcinoma discrimination are greater than in the subjective evaluation. Moreover, similar classification results were obtained when measurements were performed either with a fully automated image analysis system or with semiautomatic or manual instrumentation. As for reproducibility of the inter-instrument comparisons, the k statistic values ranged from 0.85 to 1.00 (mean value 0.90, that is, an 'almost perfect' degree of agreement); in the subjective evaluations, the inter-observer comparisons showed values ranging from 0.20 to 0.56 (mean value 0.37, that is, 'fair'). In the decision tree classification, feature value thresholds were selected in order to have specificity of 100% and the predictive value of a positive result (carcinoma) of 100%; accuracy was 87% (range 86-89%), sensitivity 74% (71-79%), the predictive value of a negative result (adenoma) 79% (78-82%). In the subjective evaluation the values were as follows: accuracy 67% (64-71%), sensitivity 57% (50-64%), specificity 77% (71-79%), predictive value of a negative result (adenoma) 64% (61-69%), predictive value of a positive result (carcinoma) 71% (67-75%). The conclusion is that, by using a routine microscope equipped with a micrometer, the preoperative diagnosis of follicular carcinoma from smears can be formulated with a high degree of certainty.     

Quantitative study of KI-67 antibody staining in non-Hodgkin's lymphomas using image analysis.

In sections from 32 B malignant lymphomas (ML), the total KI-67 stained area was compared to the number of KI-67 positive cells in order to demonstrate the reliability of using image analysis to quantify the proliferative activity. The total KI-67 area percentage correlated highly with the number of KI-67 positive cellular profiles (r = .93). Significant differences were found between low- and high-grade ML according to the Kiel classification (mean values +/- SD, respectively, of 7.7 +/- 3.81% and 16.6 +/- 6.23%), and between low-, or intermediate- and high-grade ML only, according to the International Working Formulation. Within the Working Formulation, the statistical analysis grouped the diffuse large cell subtype of intermediate grade with the immunoblastic high-grade subtype. A wide range of KI-67 area percentage values was noted, particularly in follicular ML; for these follicular ML, considering follicular areas only, values were comparable to high-grade ML (14.8 +/- 6.60%). In conclusion, the KI-67 area percentage is a reliable alternative method to manual cell counting, and image analysis allows quicker measurements appropriate to large and strictly lymphomatous areas, using a greater number of cells than in manual cell counting.     

High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays.     

Mathematical morphologic segmentation dedicated to quantitative immunohistochemistry

OBJECTIVE: To develop automatic segmentation sequences for fully automated quantitative immunohistochemistry of cancer cell nuclei by image analysis. STUDY DESIGN: The study focused on the automated delineation of cancer cell lobules and nuclei, taking breast carcinoma as an example. A hierarchic segmentation was developed, employing mainly the chaining of mathematical morphology operators. The proposed sequence was tested on 22 images of various situations, collected from 18 different cases of breast carcinoma. A quality control procedure was applied, comparing the automated method with manual outlining of cancer cell foci and with manual pricking of cancer cell nuclei. RESULTS: Good concordance was found between automated and manual segmentation procedures (90% for cancer cell clumps, 97% for cancer cell nuclei on average), but the rate of false positive nuclei (small regions labeled as nuclei by the segmentation procedure) could be relatively high (11% on average, with a maximum of 35%) and can result in underestimation of the immunostaining ratio. CONCLUSION: This study examined a preliminary approach to automated immunoquantification, limited to automated segmentation without any color characterization. The automated hierarchic segmentation presented here leads to good discrimination of cancer cell nuclei at the chosen magnification.     

Automated fluorescent in situ hybridization (FISH) analysis of t(9;22)(q34;q11) in interphase nuclei.

BACKGROUND: For chronic myeloid leukemia, the FISH detection of t(9;22)(q34;q11) in interphase nuclei of peripheral leukocytes is an alternative method to bone marrow karyotyping for monitoring treatment. With automation, several drawbacks of manual analysis may be circumvented. In this article, the capabilities of a commercially available automated image acquisition and analysis system were determined by detecting t(9;22)(q34;q11) in interphase nuclei of peripheral leukocytes. METHODS: Three peripheral blood samples of normal adults, 21 samples of CML patients, and one sample of a t(9;22)(q34;q11) positive cell-line were used. RESULTS: Single nuclei with correctly detected signals amounted to 99.6% of nuclei analyzed after exclusion of overlapping nuclei and nuclei with incorrect signal detection. A cut-off value of 0.84 mum was defined to discriminate between translocation positive and negative nuclei based on the shortest distance between signals. Using this value, the false positive rate of the automated analysis for negative samples was 7.0%, whereas that of the manual analysis was 5.8%. Automated and manual results showed strong correlation (R(2) = 0.985), the mean difference of results was only 3.7%. CONCLUSIONS: A reliable and objective automated analysis of large numbers of cells is possible, avoiding interobserver variability and producing statistically more accurate results than manual evaluation.     

ENUMERATING 3MTM PETRIFILMTM AEROBIC COUNT PLATES USING THE PETRISCAN® AUTOMATED COLONY COUNTER

In the food and dairy industries, aerobic plate counts are determined by a time-consuming and laborious hand-counting method. The PetriScan ® automated colony counter was developed to improve efficiency in the microbiology laboratory. In this study, colony counts of food, dairy, and milk products plated on 3M^TM Petrifilm^TM Aerobic Count Plates were compared using both automated and manual count plate methods. For sample variation, 16 different food, dairy, and milk products were used. Samples were prepared and serially diluted using Butterfield's diluent according to approved AOAC methods and APHA's Standard Methods. Plates were inoculated, incubated, and counted according to AOAC methods. For data collection, plates with counts between 5 and 300 colonies were included. A total of 55 low (5–30), 29 medium (31–100), and 23 high (101–300) count plates were used. Duplicate results were recorded for both methods; hand counts were tallied by two scientists. The duplicates of the mean log values for manual counts varied by 0.0005 and 0.0007, and the duplicates for the automated counts varied by 0.0011. The mean log value difference between the automated and manual counts for pooled data was 0.035. The correlation coefficient for the regression line comparing the automated and manual count methods for pooled data was 0.98. The regression equation was y = 0.9257x + 0.0781. These results demonstrate that the PetriScan® automated colony counter is a comparable and practical alternative to the standard method of manually counting plates.     

MIB-1 counting methods in meningiomas and agreement among pathologists

OBJECTIVE: To evaluate the correlation of MIB-1 labeling index (LI) obtained by 2 counting methods with histologic grade and investigate interobserver variability between these methods. STUDY DESIGN: A total of 65 meningiomas were analyzed for proliferation with 2 counting methods by 2 pathologists using MIB-1 antibody. In the first method, the most densely staining areas were counted (HL method). In the second method, randomly selected areas were counted (RS method). RESULTS: MIB-1 values correlated well with histologic grade in both methods. As expected, the tumors with recurrence had significantly higher LIs than the nonrecurrent tumors in each method. However, there was a statistically significant difference in the mean MIB-1 values of between the HL and RS methods. When MIB-1 LI was compared between 2 pathologists, perfect agreement in the HL method and substantial agreement in the RS method were achieved. CONCLUSION: Our results showed that values of MIB LIs differ with different counting methods. Nonetheless, both methods showed good correlation with World Health Organization grades. Therefore standardization of 1 counting method is of great importance for determining a reliable and specific cutoff value in assessing the risk of recurrence in meningiomas.     

Comparison of manual and automated methods for identifying target sounds in audio recordings of Pileated, Pale-billed, and putative Ivory-billed woodpeckers

ABSTRACT.   Although offering many benefits over manual recording and survey techniques for avian field studies, automated sound recording systems produce large datasets that must be carefully examined to locate sounds of interest. We compared two methods for locating target sounds in continuous sound recordings: (1) a manual method using computer software to provide a visual representation of the recording as a sound spectrogram and (2) an automated method using sound analysis software preprogrammed to identify specific target sounds. For both methods, we examined the time required to process a 24-h recording, scanning accuracy, and scanning comprehensiveness using four different target sounds of Pileated Woodpeckers ( Dryocopus pileatus ), Pale-billed Woodpeckers ( Campephilus guatemalensis ), and putative Ivory-billed Woodpeckers ( Campehilus principalis ). We collected recordings from the bottomland forests of Florida and the Neotropical dry forests of Costa Rica, and compared manual versus automated cross-correlation scanning techniques. The automated scanning method required less time to process sound recordings, but made more false positive identifications and was less comprehensive than the manual method, identifying significantly fewer target sounds. Although the automated scanning method offers a fast and economic alternative to traditional manual efforts, our results indicate that manual scanning is best for studies requiring an accurate account of temporal patterns in call frequency and for those involving birds with low vocalization rates.     

Development and validation of a computerized cytomorphometric method to assess the maturation of vaginal epithelial cells

BACKGROUND: After menopause, declining levels of estrogens may cause vaginal discomfort, or so-called "vaginal atrophy." Evaluation of therapies for vaginal atrophy may be performed using the so-called "maturation index." The maturation index is expressed as the percentage of (para)-basal, intermediate, and superficial epithelial cells in a vaginal smear. Manual assessment of the maturation index is subject to inter- and intraobserver variations. In this study, assessment of the maturation of cells in vaginal smears using automated image analysis was investigated. MATERIALS AND METHODS: Automated assessment, using a commercially available image analysis system, was performed on hematoxylin-eosin-stained cytospin specimens. A training set was constructed by an experienced cytotechnologist, based upon visual classification of stored grey value images. From this, two discriminant functions (DFs) were calculated capable of classifying cells in one of the three types. These cell classifiers were capable of classifying 97% of the cells correctly. Data from automated assessment were compared with those of classical manual counting. Specimens of 13 mature and 6 atrophic vaginal specimens were assessed in duplicate, both manually and by image analysis, using the DFs. RESULTS: No significant interobserver effect was found for image analysis, whereas a significant effect was found for manual counting. Both methods were able to distinguish between matured and atrophic specimens. CONCLUSIONS: It was concluded that for assessment of vaginal maturation, the use of automated image analysis systems is recommended. Besides increased reproducibility, image analysis systems yield additional data describing the size and shape of the cytoplasm and nucleus of cells, which might increase discriminating power.     

A comparative study in morphometric grading of transitional cell carcinoma of the urinary bladder

To overcome the considerable observer inconsistency in the histologic grading of transitional cell carcinomas, the value of four different morphometric grading methods was investigated in 61 tumors of the bladder. Only two methods showed satisfactory reproducibility. Both methods, one based on random nuclear sampling and the other on selective nuclear sampling, showed an increase in the mean and standard deviation of the nuclear area with higher tumor grades (P less than .00001). Morphometric classification of the learning set (44 cases) was in agreement with the unequivocally assessed histologic grade in 35 cases (79.5%) using random sampling and in 38 cases (86.4%) using selective sampling. By reducing the grading classes to "low" (grades 1 and 2) and "high" (grade 3) and by introducing a classification probability threshold (0.80), an accurate morphometric classification was achieved in 38 cases (86.4%) using random sampling and in 41 cases (93.2%) using selective sampling. Of the 17 cases with histologic grading discrepancies, all 10 low-grade tumors (with discrepancies of grade 1 versus grade 2) were correctly classified as low-grade carcinomas by both of the morphometric methods; in the remaining 7 cases, with low-versus-high discrepancies (grade 2 versus grade 3), the selective method yielded better correlation with the tumor stage and clinical follow-up. It is concluded that morphometric classification is an acceptable alternative for histologic grading by pathologists, provided that the reproducibility of the method is confirmed. Although both random and selective sampling yielded satisfactory classifications, the selective method gave more reliable results as confirmed by the clinical behavior.     

Cellular quantitative analysis of neuroblastoma tumor and splitting overlapping cells

Background

Neuroblastoma Tumor (NT) is one of the most aggressive types of infant cancer. Essential to accurate diagnosis and prognosis is cellular quantitative analysis of the tumor. Counting enormous numbers of cells under an optical microscope is error-prone. There is therefore an urgent demand from pathologists for robust and automated cell counting systems. However, the main challenge in developing these systems is the inability of them to distinguish between overlapping cells and single cells, and to split the overlapping cells. We address this challenge in two stages by: 1) distinguishing overlapping cells from single cells using the morphological differences between them such as area, uniformity of diameters and cell concavity; and 2) splitting overlapping cells into single cells. We propose a novel approach by using the dominant concave regions of cells as markers to identify the overlap region. We then find the initial splitting points at the critical points of the concave regions by decomposing the concave regions into their components such as arcs, chords and edges, and the distance between the components is analyzed using the developed seed growing technique. Lastly, a shortest path determination approach is developed to determine the optimum splitting route between two candidate initial splitting points.

Results

We compare the cell counting results of our system with those of a pathologist as the ground-truth. We also compare the system with three state-of-the-art methods, and the results of statistical tests show a significant improvement in the performance of our system compared to state-of-the-art methods. The F-measure obtained by our system is 88.70%. To evaluate the generalizability of our algorithm, we apply it to images of follicular lymphoma, which has similar histological regions to NT. Of the algorithms tested, our algorithm obtains the highest F-measure of 92.79%.

Conclusion

We develop a novel overlapping cell splitting algorithm to enhance the cellular quantitative analysis of infant neuroblastoma. The performance of the proposed algorithm promises a reliable automated cell counting system for pathology laboratories. Moreover, the high performance obtained by our algorithm for images of follicular lymphoma demonstrates the generalization of the proposed algorithm for cancers with similar histological regions and histological structures.     

Use of automated microscopy for the detection of disseminated tumor cells in bone marrow samples

The use of automated microscopy has reached the maturity necessary for its routine use in the clinical pathology laboratory. In the following study we compared the performance of an automated microscope system (MDS) with manual method for the detection and analysis of disseminated tumor cells present in bone marrow preparations from breast carcinoma patients. The MDS System detected rare disseminated tumor cells among bone marrow mononuclear cells with higher sensitivity than standard manual microscopy. Automated microscopy also proved to be a method of high reproducibility and precision, the advantage of which was clearly illustrated by problems of variability in manual screening. Accumulated results from two pathologists who had screened 120 clinical slides from breast cancer patients both by manual microscopy and by use of the MDS System revealed only two (3.8%) missed by the automatic procedure, whereas as many as 20 out of 52 positive samples (38%) were missed by manual screening.     

Accuracy of a remote quantitative image analysis in the whole slide images

The rationale for choosing a remote quantitative method supporting a diagnostic decision requires some empirical studies and knowledge on scenarios including valid telepathology standards. The tumours of the central nervous system [CNS] are graded on the base of the morphological features and the Ki-67 labelling Index [Ki-67 LI]. Various methods have been applied for Ki-67 LI estimation. Recently we have introduced the Computerized Analysis of Medical Images [CAMI] software for an automated Ki-67 LI counting in the digital images. Aims of our study was to explore the accuracy and reliability of a remote assessment of Ki-67 LI with CAMI software applied to the whole slide images [WSI]. The WSI representing CNS tumours: 18 meningiomas and 10 oligodendrogliomas were stored on the server of the Warsaw University of Technology. The digital copies of entire glass slides were created automatically by the Aperio ScanScope CS with objective 20x or 40x. Aperio's Image Scope software provided functionality for a remote viewing of WSI. The Ki-67 LI assessment was carried on within 2 out of 20 selected fields of view (objective 40x) representing the highest labelling areas in each WSI. The Ki-67 LI counting was performed by 3 various methods: 1) the manual reading in the light microscope - LM, 2) the automated counting with CAMI software on the digital images - DI , and 3) the remote quantitation on the WSIs - as WSI method. The quality of WSIs and technical efficiency of the on-line system were analysed. The comparative statistical analysis was performed for the results obtained by 3 methods of Ki-67 LI counting. The preliminary analysis showed that in 18% of WSI the results of Ki-67 LI differed from those obtained in other 2 methods of counting when the quality of the glass slides was below the standard range. The results of our investigations indicate that the remote automated Ki-67 LI analysis performed with the CAMI algorithm on the whole slide images of meningiomas and oligodendrogliomas could be successfully used as an alternative method to the manual reading as well as to the digital images quantitation with CAMI software. According to our observation a need of a remote supervision/consultation and training for the effective use of remote quantitative analysis of WSI is necessary.     

Determination of amphetamine and methamphetamine enantiomers by chiral derivatization and gas chromatography–mass spectrometry as a test case for an automated sample preparation system

An automated sample preparation system has been applied to the chiral analysis of amphetamine and methamphetamine using derivatization with trifluoracetyl-L -prolyl chloride (L -TPC) and subsequent separation on a gas chromatography–mass spectrometry (GC-MS) system. Tasks automated were the dilution of standards and the off-line preparation of the diastereoisomer derivatives. Chromatographic performance, sensitivity, and reproducibility of the automated procedure were compared to the equivalent values obtained with two existing assays methods which employ manual derivatiation, either on-column or off-line. Chromatographic performance was unaffected by the derivatization procedure and sensitivity was better for both automated and manual off-line derivatization. Qualitative reproducibility as based on enantiomeric composition was equivalent for all three approaches, while quantitative reproducibility as based on peak areas was best for the automated procedure. Considering the fact that the diastereoisomer derivatives are unstable over time, automated sample preparation with “just-in-time” derivatization can increase the overall precision of the analytical method. The procedures described here are general enough in nature that they could be applied to other chiral or even achiral analytes. © 1994 Wiley-Liss, Inc.     

Assessment of automated disease detection in diabetic retinopathy screening using two-field photography

Aim

To assess the performance of automated disease detection in diabetic retinopathy screening using two field mydriatic photography.

Methods

Images from 8,271 sequential patient screening episodes from a South London diabetic retinopathy screening service were processed by the Medalytix iGrading™ automated grading system. For each screening episode macular-centred and disc-centred images of both eyes were acquired and independently graded according to the English national grading scheme. Where discrepancies were found between the automated result and original manual grade, internal and external arbitration was used to determine the final study grades. Two versions of the software were used: one that detected microaneurysms alone, and one that detected blot haemorrhages and exudates in addition to microaneurysms. Results for each version were calculated once using both fields and once using the macula-centred field alone.

Results

Of the 8,271 episodes, 346 (4.2%) were considered unassessable. Referable disease was detected in 587 episodes (7.1%). The sensitivity of the automated system for detecting unassessable images ranged from 97.4% to 99.1% depending on configuration. The sensitivity of the automated system for referable episodes ranged from 98.3% to 99.3%. All the episodes that included proliferative or pre-proliferative retinopathy were detected by the automated system regardless of configuration (192/192, 95% confidence interval 98.0% to 100%). If implemented as the first step in grading, the automated system would have reduced the manual grading effort by between 2,183 and 3,147 patient episodes (26.4% to 38.1%).

Conclusion

Automated grading can safely reduce the workload of manual grading using two field, mydriatic photography in a routine screening service.     

Automated image analysis for quantitative fluorescence in situ hybridization with environmental samples

When fluorescence in situ hybridization (FISH) analyses are performed with complex environmental samples, difficulties related to the presence of microbial cell aggregates and nonuniform background fluorescence are often encountered. The objective of this study was to develop a robust and automated quantitative FISH method for complex environmental samples, such as manure and soil. The method and duration of sample dispersion were optimized to reduce the interference of cell aggregates. An automated image analysis program that detects cells from 4',6'-diamidino-2-phenylindole (DAPI) micrographs and extracts the maximum and mean fluorescence intensities for each cell from corresponding FISH images was developed with the software Visilog. Intensity thresholds were not consistent even for duplicate analyses, so alternative ways of classifying signals were investigated. In the resulting method, the intensity data were divided into clusters using fuzzy c-means clustering, and the resulting clusters were classified as target (positive) or nontarget (negative). A manual quality control confirmed this classification. With this method, 50.4, 72.1, and 64.9% of the cells in two swine manure samples and one soil sample, respectively, were positive as determined with a 16S rRNA-targeted bacterial probe (S-D-Bact-0338-a-A-18). Manual counting resulted in corresponding values of 52.3, 70.6, and 61.5%, respectively. In two swine manure samples and one soil sample 21.6, 12.3, and 2.5% of the cells were positive with an archaeal probe (S-D-Arch-0915-a-A-20), respectively. Manual counting resulted in corresponding values of 22.4, 14.0, and 2.9%, respectively. This automated method should facilitate quantitative analysis of FISH images for a variety of complex environmental samples.     

Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method

The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.     

Analysis of proliferating cell fraction determined by monoclonal antibody to M1-subunit ribonucleotide reductase and Ki-67 in relation to p53 protein expression in fine-needle aspirates from non-Hodgkin's lymphomas

The purpose of this study was to analyse the proliferative fraction with the monoclonal antibody M1-R-R to M1-subunit ribonucleotide reductase and with MIB-1 to Ki-67 antigen in relation to p53 protein expression in fine needle aspirates from B-cell non-Hodgkin's lymphomas. One hundred and thirty-seven cases, previously diagnosed and sub-typed according to the Kiel classification and characterized by immunophenotyping, were included in the study. The M-1 subunit ribonucleotide reductase (M1-R-R), Ki-67 and p53 antigens were detected using monoclonal antibodies on stored cytospin preparations. There was a good correlation (r = 0.72) between Ki-67 and M1-R-R positive cell fraction in both high and low grade lymphomas. High-grade lymphomas had a median percentage of M1-R-R/MIB-1 positive cells of 53.0/73.0 for lymphoblastic, 61.0/52.0 for immunoblastic and 33.5/41.0 for centroblastic lymphomas, respectively. In low grade lymphomas figures of median percentage of M1-R-R/MIB-1 were 9.0/15.0 for centroblastic/centrocytic, 11.0/9.5 for chronic lymphocytic leukaemia, 16.0/27.0 for centrocytic and 12.0/9.0 for immunocytomas, respectively. The median percentages of M1-R-R/MIB-1 for high and low grade lymphomas were 37.0/50.5 and 11.0/12.0, respectively. In the p53 positive cases the proliferation rate as measured by staining for M1-R-R and MIB-1 was higher than in p53 negative cases, but the difference was not statistically significant. The results show that cytospin material obtained by fine needle aspiration and stored at -70 degrees C for years can be used reliably for both peroxidase-avidin-biotin and three-step alkaline phosphatase immunocytochemical staining. In addition, proliferation fraction determined by M1-R-R monoclonal antibody staining correlates well with that measured by an established marker for cell proliferation, the Ki-67 antibody. However, the proliferation fraction as measured by the two antibodies differs in the various subtypes of non-Hodgkin's lymphoma which indicates that they may contribute different prognostic information.