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

Automated 3D scoring of fluorescence in situ hybridization (FISH) using a confocal whole slide imaging scanner

Fluorescence in situ hybridization (FISH) is a technique to visualize specific DNA/RNA sequences within the cell nuclei and provide the presence, location and structural integrity of genes on chromosomes. A confocal Whole Slide Imaging (WSI) scanner technology has superior depth resolution compared to wide-field fluorescence imaging. Confocal WSI has the ability to perform serial optical sections with specimen imaging, which is critical for 3D tissue reconstruction for volumetric spatial analysis. The standard clinical manual scoring for FISH is labor-intensive, time-consuming and subjective. Application of multi-gene FISH analysis alongside 3D imaging, significantly increase the level of complexity required for an accurate 3D analysis. Therefore, the purpose of this study is to establish automated 3D FISH scoring for z-stack images from confocal WSI scanner. The algorithm and the application we developed, SHIMARIS PAFQ, successfully employs 3D calculations for clear individual cell nuclei segmentation, gene signals detection and distribution of break-apart probes signal patterns, including standard break-apart, and variant patterns due to truncation, and deletion, etc. The analysis was accurate and precise when compared with ground truth clinical manual counting and scoring reported in ten lymphoma and solid tumors cases. The algorithm and the application we developed, SHIMARIS PAFQ, is objective and more efficient than the conventional procedure. It enables the automated counting of more nuclei, precisely detecting additional abnormal signal variations in nuclei patterns and analyzes gigabyte multi-layer stacking imaging data of tissue samples from patients. Currently, we are developing a deep learning algorithm for automated tumor area detection to be integrated with SHIMARIS PAFQ.

Automated density-based counting of FISH amplification signals for HER2 status assessment

BACKGROUND

Automated image analysis can make quantification of FISH signals in histological sections more efficient and reproducible. Current detection-based methods, however, often fail to accurately quantify densely clustered FISH signals.

METHODS

We propose a novel density-based approach to quantifying FISH signals. Instead of detecting individual signals, this approach quantifies FISH signals in terms of the integral over a density map predicted by Deep Learning. We apply the density-based approach to the task of counting and determining ratios of ERBB2 and CEN17 signals and compare it to common detection-based and area-based approaches.

RESULTS

The ratios determined by our approach were strongly correlated with results obtained by manual annotation of individual FISH signals (Pearson's r = 0.907). In addition, they were highly consistent with cutoff-scores determined by a pathologist (balanced concordance = 0.971). The density-based approach generally outperformed the other approaches. Its superiority was particularly evident in the presence of dense signal clusters.

CONCLUSIONS

The presented approach enables accurate and efficient automated quantification of FISH signals. Since signals in clusters can hardly be detected individually even by human observers, the density-based quantification performs better than detection-based approaches.

Calibration of interphase fluorescence in situ hybridization cutoff by mathematical models

Fluorescence in situ hybridization (FISH) continues to play an important role in clinical investigations. Laboratories may create their own cutoff, a percentage of positive nuclei to determine whether a specimen is positive or negative, to eliminate false positives that are created by signal overlap in most cases. In some cases, it is difficult to determine the cutoff value because of differences in both the area of nuclei and the number of signals. To address these problems, we established two mathematical models using probability theory. To verify these two models, normal disomy cells from healthy individuals were used to simulate cells with different numbers of signals by hybridization with different probes. We used an X/Y probe to obtain the average distance between two signals and the probability of signal overlap in different nuclei area. Frequencies of all signal patterns were scored and compared with theoretical frequencies, and models were assessed using a goodness of fit test. We used five BCR/ABL1-positive samples, 20 BCR/ABL1-negative samples and two samples with ambiguous results to verify the cutoff calibrated by these two models. The models were in agreement with experimental results. The dynamic cutoff can classify cases in routine analysis correctly, and it can also correct for influences from nuclei area and the number of signals in some ambiguous cases. The probability models can be used to assess the effect of signal overlap and calibrate the cutoff.

Investigation of CPD and HMDS sample preparation techniques for cervical cells in developing computer-aided screening system based on FE-SEM/EDX

This paper investigated the effects of critical-point drying (CPD) and hexamethyldisilazane (HMDS) sample preparation techniques for cervical cells on field emission scanning electron microscopy and energy dispersive X-ray (FE-SEM/EDX). We investigated the visualization of cervical cell image and elemental distribution on the cervical cell for two techniques of sample preparation. Using FE-SEM/EDX, the cervical cell images are captured and the cell element compositions are extracted for both sample preparation techniques. Cervical cell image quality, elemental composition, and processing time are considered for comparison of performances. Qualitatively, FE-SEM image based on HMDS preparation technique has better image quality than CPD technique in terms of degree of spread cell on the specimen and morphologic signs of cell deteriorations (i.e., existence of plate and pellet drying artifacts and membrane blebs). Quantitatively, with mapping and line scanning EDX analysis, carbon and oxygen element compositions in HMDS technique were higher than the CPD technique in terms of weight percentages. The HMDS technique has shorter processing time than the CPD technique. The results indicate that FE-SEM imaging, elemental composition, and processing time for sample preparation with the HMDS technique were better than CPD technique for cervical cell preparation technique for developing computer-aided screening system.

Feature selection for the automated detection of metaphase chromosomes: performance comparison using a receiver operating characteristic method

BACKGROUND

The purpose of this study is to identify a set of features for optimizing the performance of metaphase chromosome detection under high throughput scanning microscopy. In the development of computer-aided detection (CAD) scheme, feature selection is critically important, as it directly determines the accuracy of the scheme. Although many features have been examined previously, selecting optimal features is often application oriented.

METHODS

In this experiment, 200 bone marrow cells were first acquired by a high throughput scanning microscope. Then 9 different features were applied individually to group captured images into the clinically analyzable and unanalyzable classes. The performance of these different methods was assessed by a receiving operating characteristic (ROC) method.

RESULTS

The results show that using the number of labeled regions on each acquired image is suitable for the first on-line CAD scheme. For the second off-line CAD scheme, it would be suggested to combine four feature extraction methods including the number of labeled regions, average regions area, average region pixel value, and the standard deviation of either region distance or circularity.

CONCLUSION

This study demonstrates an effective method of feature selection and comparison to facilitate the optimization of the CAD schemes for high throughput scanning microscope in the future.

Intelligent screening systems for cervical cancer

Advent of medical image digitalization leads to image processing and computer-aided diagnosis systems in numerous clinical applications. These technologies could be used to automatically diagnose patient or serve as second opinion to pathologists. This paper briefly reviews cervical screening techniques, advantages, and disadvantages. The digital data of the screening techniques are used as data for the computer screening system as replaced in the expert analysis. Four stages of the computer system are enhancement, features extraction, feature selection, and classification reviewed in detail. The computer system based on cytology data and electromagnetic spectra data achieved better accuracy than other data.

Fluorescence in situ hybridization (FISH): an increasingly demanded tool for biomarker research and personalized medicine

Extensive studies of the genetic aberrations related to human diseases conducted over the last two decades have identified recurrent genomic abnormalities as potential driving factors underlying a variety of cancers. Over the time, a series of cutting-edge high-throughput genetic tests, such as microarrays and next-generation sequencing, have been developed and incorporated into routine clinical practice. Although it is a classical low-throughput cytogenetic test, fluorescence in situ hybridization (FISH) does not show signs of fading; on the contrary, it plays an increasingly important role in detecting specific biomarkers in solid and hematologic neoplasms and has therefore become an indispensable part of the rapidly developing field of personalized medicine. In this article, we have summarized the recent advances in FISH application for both de novo discovery and routine detection of chromosomal rearrangements, amplifications, and deletions that are associated with the pathogenesis of various hematopoietic and non-hematopoietic malignancies. In addition, we have reviewed the recent developments in FISH methodology as well.

State-of-the-art FISHing: automated analysis of cytogenetic aberrations in interphase nuclei

Interphase fluorescence in situ hybridization (i-FISH) is a powerful tool for visualizing various molecular targets in non-dividing cells. Manual scoring of i-FISH signals is a labor intensive, time-consuming, and error-prone process liable to subjective interpretation. Automated evaluation of signal patterns provides the opportunity to overcome these difficulties. The first report on automated i-FISH analysis has been published 20 years ago and since then several applications have been introduced in the fields of oncology, and prenatal and fertility screening. In this article, we provide an insight into the automated i-FISH analysis including its course, brief history, clinical applications, and advantages and challenges. The lack of guidelines for describing new automated i-FISH methods hampers the precise comparison of performance of various applications published, thus, we make a proposal for a panel of parameters essential to introduce and standardize new applications and reproduce previously described technologies.

Chromosomal rearrangements in post-Chernobyl papillary thyroid carcinomas: evaluation by spectral karyotyping and automated interphase FISH

Structural genomic rearrangements are frequent findings in human cancers. Therefore, papillary thyroid carcinomas (PTCs) were investigated for chromosomal aberrations and rearrangements of the RET proto-oncogene. For this purpose, primary cultures from 23 PTC have been established and metaphase preparations were analysed by spectral karyotyping (SKY). In addition, interphase cell preparations of the same cases were investigated by fluorescence in situ hybridisation (FISH) for the presence of RET/PTC rearrangements using RET-specific DNA probes. SKY analysis of PTC revealed structural aberrations of chromosome 11 and several numerical aberrations with frequent loss of chromosomes 20, 21, and 22. FISH analysis for RET/PTC rearrangements showed prevalence of this rearrangement in 72% (16 out of 22) of cases. However, only subpopulations of tumour cells exhibited this rearrangement indicating genetic heterogeneity. The comparison of visual and automated scoring of FISH signals revealed concordant results in 19 out of 22 cases (87%) indicating reliable scoring results using the optimised scoring parameter for RET/PTC with the automated Metafer4 system. It can be concluded from this study that genomic rearrangements are frequent in PTC and therefore important events in thyroid carcinogenesis.

Clonal heterogeneity and chromosomal instability at disease presentation in high hyperdiploid acute lymphoblastic leukemia

Although aneuploidy has many possible causes, it often results from underlying chromosomal instability (CIN) leading to an unstable karyotype with cell-to-cell variation and multiple subclones. To test for the presence of CIN in high hyperdiploid acute lymphoblastic leukemia (HeH ALL) at diagnosis, we investigated 20 patients (10 HeH ALL and 10 non-HeH ALL), using automated four-color interphase fluorescence in situ hybridization (I-FISH) with centromeric probes for chromosomes 4, 6, 10, and 17. In HeH ALL, the proportion of abnormal cells ranged from 36.3% to 92.4%, and a variety of aneuploid populations were identified. Compared with conventional cytogenetics, I-FISH revealed numerous additional clones, some of them very small. To investigate the nature and origin of this clonal heterogeneity, we determined average numerical CIN values for all four chromosomes together and for each chromosome and patient group. The CIN values in HeH ALL were relatively high (range, 22.2-44.7%), compared with those in non-HeH ALL (3.2-6.4%), thus accounting for the presence of numerical CIN in HeH ALL at diagnosis. We conclude that numerical CIN may be at the origin of the high level of clonal heterogeneity revealed by I-FISH in HeH ALL at presentation, which would corroborate the potential role of CIN in tumor pathogenesis.

Automated analysis of fluorescent in situ hybridization (FISH) labeled genetic biomarkers in assisting cervical cancer diagnosis

The numerical and/or structural deviation of some chromosomes (i.e., monosomy and _polysomy of chromosomes 3 and X) are routinely used as positive genetic biomarkers to diagnose cervical cancer and predict the disease progression. Among the available diagnostic methods to analyze the aneusomy of chromosomes 3 and X, fluorescence in situ hybridization (FISH) technology has demonstrated significant advantages in assisting clinicians to more accurately detect and diagnose cervical carcinoma at an early stage, in particular for the women at a high risk for progression of low-grade and high-grade squamous intra-epithelium lesions (LSIL and HSIL). In order to increase the diagnostic accuracy, consistency, and efficiency from that of manual FISH analysis, this study aims to develop and test an automated FISH analysis method that includes a two-stage scheme. In the first stage, an interactive multiple-threshold algorithm is utilized to segment potential interphase nuclei candidates distributed in different intensity levels and a rule-based classifier is implemented to identify analyzable interphase cells. In the second stage, FISH labeled biomarker spots of chromosomes 3 and X are segmented by a top-hat transform. The independent FISH spots are then detected by a knowledge-based classifier, which enables recognition of the splitting and stringy FISH signals. Finally, the ratio of abnormal interphase cells with numerical changes of chromosomes 3 and X is calculated to detect positive cases. The experimental results of four test cases showed high agreement of FISH analysis results between the automated scheme and the cytogeneticist's analysis including 92.7% to 98.7% agreement in cell segmentation and 4.4% to 11.0% difference in cell classification. This preliminary study demonstrates the feasibility of potentially applying the automatic FISH analysis method to expedite the screening and detecting cervical cancer at an early stage.

Detection of early precursors of t(12;21) positive pediatric acute lymphoblastic leukemia during follow-up

DNA-, RNA-, and cell-based methods provide different biologic information for determining the presence of minimal residual disease (MRD). We monitored the responses of patients with pediatric acute lymphoblastic leukemia (pALL) using DNA markers, TEL/AML1 expression, and scanning fluorescence microscopy (SFM). Using SFM, 36% of patients exhibited 1.5-3.1 log and 2.9-4.2 log higher MRD levels compared with those based on DNA and RNA markers, respectively. CD10+ ancestor cells with germline antigen receptors, but silent TEL/AML1 expression, may reside in the lymphoid stem cell compartment of treated t(12;21)-positive patients and might act as a potential source of cells for late relapses.

Automated detection of residual cells after sex-mismatched stem-cell transplantation - evidence for presence of disease-marker negative residual cells

BACKGROUND

A new chimerism analysis based on automated interphase fluorescence in situ hybridization (FISH) evaluation was established to detect residual cells after allogene sex-mismatched bone marrow or blood stem-cell transplantation.Cells of 58 patients were characterized as disease-associated due to presence of a bcr/abl-gene-fusion or a trisomy 8 and/or a simultaneous hybridization of gonosome-specific centromeric probes. The automatic slide scanning platform Metafer with its module MetaCyte was used to analyse 3,000 cells per sample.

RESULTS

Overall 454 assays of 58 patients were analyzed. 13 of 58 patients showed residual recipient cells at one stage of more than 4% and 12 of 58 showed residual recipient cells less than 4%, respectively. As to be expected, patients of the latter group were associated with a higher survival rate (48 vs. 34 month). In only two of seven patients with disease-marker positive residual cells between 0.1-1.3% a relapse was observed. Besides, disease-marker negative residual cells were found in two patients without relapse at a rate of 2.8% and 3.3%, respectively.

CONCLUSION

The definite origin and meaning of disease-marker negative residual cells is still unclear. Overall, with the presented automatic chimerism analysis of interphase FISH slides, a sensitive method for detection of disease-marker positive residual cells is on hand.

Automated detection and analysis of fluorescent in situ hybridization spots depicted in digital microscopic images of Pap-smear specimens

Fluorescence in situ hybridization (FISH) technology has been widely recognized as a promising molecular and biomedical optical imaging tool to screen and diagnose cervical cancer. However, manual FISH analysis is time-consuming and may introduce large inter-reader variability. In this study, a computerized scheme is developed and tested. It automatically detects and analyzes FISH spots depicted on microscopic fluorescence images. The scheme includes two stages: (1) a feature-based classification rule to detect useful interphase cells, and (2) a knowledge-based expert classifier to identify splitting FISH spots and improve the accuracy of counting independent FISH spots. The scheme then classifies detected analyzable cells as normal or abnormal. In this study, 150 FISH images were acquired from Pap-smear specimens and examined by both an experienced cytogeneticist and the scheme. The results showed that (1) the agreement between the cytogeneticist and the scheme was 96.9% in classifying between analyzable and unanalyzable cells (Kappa=0.917), and (2) agreements in detecting normal and abnormal cells based on FISH spots were 90.5% and 95.8% with Kappa=0.867. This study demonstrated the feasibility of automated FISH analysis, which may potentially improve detection efficiency and produce more accurate and consistent results than manual FISH analysis.

Automated four-color interphase fluorescence in situ hybridization approach for the simultaneous detection of specific aneuploidies of diagnostic and prognostic significance in high hyperdiploid acute lymphoblastic leukemia

In high hyperdiploid acute lymphoblastic leukemia (ALL), the concurrence of specific trisomies confers a more favorable outcome than hyperdiploidy alone. Interphase fluorescence in situ hybridization (FISH) complements conventional cytogenetics (CC) through its sensitivity and ability to detect chromosome aberrations in nondividing cells. To overcome the limits of manual I-FISH, we developed an automated four-color I-FISH approach and assessed its ability to detect concurrent aneuploidies in ALL. I-FISH was performed using centromeric probes for chromosomes 4, 6, 10, and 17. Parameters established for nucleus selection and signal detection were evaluated. Cutoff values were determined. Combinations of aneuploidies were considered relevant when each aneuploidy was individually significant. Results obtained in 10 patient samples were compared with those obtained with CC. Various combinations of aneuploidies were identified. All clones detected by CC were observed also by I-FISH, and I-FISH revealed numerous additional abnormal clones in all patients, ranging from < or =1% to 31.6% of cells analyzed. We conclude that four-color automated I-FISH permits the identification of concurrent aneuploidies of potential prognostic significance. Large numbers of cells can be analyzed rapidly. The large number of nuclei scored revealed a high level of chromosome variability both at diagnosis and relapse, the prognostic significance of which is of considerable clinical interest and merits further evaluation.

Automated FISH analysis using dual-fusion and break-apart probes on paraffin-embedded tissue sections

Detecting balanced translocations using tissue sections plays an important diagnostic role in cases of hematological malignancies. Manual scoring is often problematic due to truncation and overlapping of nuclei. Reports have described automated analysis using primarily tile sampling. The aim of this study was to investigate an automated fluorescent in situ hybridization analysis method using grid sampling on tissue sections, and compare the performance of dual-fusion (DF) and break-apart (BA) probes in this setting. Ten follicular, 10 mantle cell lymphoma, and 10 translocation-negative samples were used to set the threshold of false positivity using IGH/CCND1, IGH/BCL-2 DF, and IGH BA probes. The cut-off distances of red and green signals to define fusion signals were 0.5, 1.0, and 1.2 mum for the IGH/CCND1, IGH/BCL-2 DF, and IGH BA probes, respectively. The mean false positivity of grid units was 5.3, 11.4, and 28.1%, respectively. Ten to 14 additional samples analyzed blindly and were correctly classified using each probe. Discriminating positive and negative samples using automated analysis and grid sampling was possible with each probe, although different definitions of fusion signals were required due to the different physical distances between the DNA probes. Using the DF probes resulted in lower false positivity, which was less affected by signal numbers per grid units.

Automated Duet spot counting system and manual technologist scoring using dual-fusion fluorescence in situ hybridization (D-FISH) strategy: comparison and application to FISH minimal residual disease testing in patients with chronic myeloid leukemia

The automated BioView Duet system was compared with manual technologist scoring (MTS) using a BCR/ABL dual-fusion FISH (D-FISH) probe strategy for chronic myeloid leukemia (CML) specimens. In the first study, 500 nuclei were evaluated for 10 distinct signal patterns in various abnormal cell percentages from each of 89 specimens. The Duet system correctly identified all 27 normal specimens and the abnormal signal pattern of all 63 abnormal specimens. The percentage of abnormal nuclei detected was also concordant, with an average difference between MTS and the Duet system of only 2.7%. However, achievement of accurate quantitative results required reclassification by a technologist for nearly 50% of nuclei per specimen. Next, the Duet system was used to evaluate BCR/ABL D-FISH for FISH minimal residual disease (MRD) detection in CML patients. Up to 6,000 nuclei were evaluated for four signal pattern categories for each of 60 CML MRD samples. Excluding four abnormal specimens with insufficient samples, the Duet system correctly identified all of the abnormal specimens and identified four additional abnormal specimens previously diagnosed as normal by MTS. The technologist time required for evaluation and reclassification of the Duet system data for the FISH MRD samples averaged only 1 minute per case, saving significant technologist effort. We conclude that the Duet system appears to be more sensitive and cost-effective than MTS for CML FISH MRD testing.

Automated detection of residual leukemic cells by consecutive immunolabeling for CD10 and fluorescence in situ hybridization for ETV6/RUNX1 rearrangement in childhood acute lymphoblastic leukemia

Among the various methods available for analyzing minimal residual disease, a new procedure for the cell-based approaches using consecutive phenotypic and genotypic analysis as revealed by immunofluorescent labeling and subsequent fluorescent in situ hybridization (FISH) has been developed. We are introducing a fluorescent microscopy-based technique by which not only cellular targets and immunological marker positivity, but also the FISH pattern was identified by automated scanning. For the latter one translocation-specific FISH pattern recognition was accomplished by using an automated scanning mode for the 3D determination of valid distances between FISH signals, to define the cutoff value for the shortest green-red spot distance differentiating positive cells from negative ones. The procedure was tested with CD10(+) acute lymphoblastic leukemia cell line harboring the t(12;21)(p13;q22) resulting in the ETV6/RUNX1 rearrangement (formerly TEL/AML1), as well as peripheral blood lymphocytes of healthy individuals. Using the combined, automated method, a sensitivity of 98.67% and a specificity of 99.97% were obtained. The mean false positivity + 2 standard deviations cutoff level (0.09%) allows detection of leukemic cells with high accuracy, even a bit below the tumor load dilution of 10(-3), a value reported to be critical in clinical decision making.

Automated analysis of FISH and immunohistochemistry images: A review

Fluorescent in-situ hybridization (FISH) and immunohistochemistry (IHC) constitute a pair of complimentary techniques for detecting gene amplification and overexpression, respectively. The advantages of IHC include relatively cheap materials and high sample durability, while FISH is the more accurate and reproducible method. Evaluation of FISH and IHC images is still largely performed manually, with automated or semiautomated techniques increasing in popularity. Here, we provide a comprehensive review of a number of (semi-) automated FISH and IHC image processing systems, focusing on the algorithmic aspects of each technique. Our review verifies the increasingly important role of such methods in FISH and IHC; however, manual intervention is still necessary in order to resolve particularly challenging or ambiguous cases. In addition, large-scale validation is required in order for these systems to enter standard clinical practice.