Fully automated fluorescent in situ hybridization (FISH) staining and digital analysis of HER2 in breast cancer: a validation study

Quantitative Imaging Analysis Fluorescence In Situ Hybridization Validation for Clinical HER2 Testing in Breast Cancer

CONTEXT.—

Quantitative imaging is a promising tool that is gaining wide use across several areas of pathology. Although there has been increasing adoption of morphologic and immunohistochemical analysis, the adoption of evaluation of fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded tissue has been limited because of complexity and lack of practice guidelines.

OBJECTIVE.—

To perform human epidermal growth factor receptor 2 (HER2) FISH validation in breast carcinoma in accordance with the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) 2018 guideline.

DESIGN.—

Clinical validation of HER2 FISH was performed using the US Food and Drug Administration-approved dual-probe HER2 IQFISH (Dako, Carpinteria, California) with digital scanning performed on a PathFusion (Applied Spectral Imaging, Carlsbad, California) system. Validation parameters evaluated included z-stacking, classifier, accuracy, precision, software, and hardware settings. Finally, we evaluated the performance of digital enumeration on clinical samples in a real-world setting.

RESULTS.—

The accuracy samples showed a final concordance of 95.3% to 100% across HER2 groups 1 to 5. During clinical implementation for HER2 groups 2, 3, and 4, we achieved a final concordance of 76% (95 of 125). Of these cases, only 8% (10 of 125) had discordances with clinical impact that could be identified algorithmically and triaged for manual review.

CONCLUSIONS.—

Digital FISH enumeration is a useful tool to improve the efficacy of HER2 FISH enumeration and capture genetic heterogeneity across HER2 signals. Excluding cases with high background or poor image quality and manual review of cases with ASCO/CAP group discordances can further improve the efficiency of digital HER2 FISH enumeration.

Future Practices of Breast Pathology Using Digital and Computational Pathology

Pathology clinical practice has evolved by adopting technological advancements initially regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and genomic sequencing. Breast pathology has a critical role as a medical domain, where the patient's pathology diagnosis has significant implications for prognostication and treatment of diseases. The advent of digital and computational pathology has brought about significant advancements in the field, offering new possibilities for enhancing diagnostic accuracy and improving patient care. Digital slide scanning enables to conversion of glass slides into high-fidelity digital images, supporting the review of cases in a digital workflow. Digitization offers the capability to render specimen diagnoses, digital archival of patient specimens, collaboration, and telepathology. Integration of image analysis and machine learning-based systems layered atop the high-resolution digital images offers novel workflows to assist breast pathologists in their clinical, educational, and research endeavors. Decision support tools may improve the detection and classification of breast lesions and the quantification of immunohistochemical studies. Computational biomarkers may help to contribute to patient management or outcomes. Furthermore, using digital and computational pathology may increase standardization and quality assurance, especially in areas with high interobserver variability. This review explores the current landscape and possible future applications of digital and computational techniques in the field of breast pathology.

Region of interest (ROI) selection using vision transformer for automatic analysis using whole slide images

Selecting regions of interest (ROI) is a common step in medical image analysis across all imaging modalities. An ROI is a subset of an image appropriate for the intended analysis and identified manually by experts. In modern pathology, the analysis involves processing multidimensional and high resolution whole slide image (WSI) tiles automatically with an overwhelming quantity of structural and functional information. Despite recent improvements in computing capacity, analyzing such a plethora of data is challenging but vital to accurate analysis. Automatic ROI detection can significantly reduce the number of pixels to be processed, speed the analysis, improve accuracy and reduce dependency on pathologists. In this paper, we present an ROI detection method for WSI and demonstrated it for human epidermal growth factor receptor 2 (HER2) grading for breast cancer patients. Existing HER2 grading relies on manual ROI selection, which is tedious, time-consuming and suffers from inter-observer and intra-observer variability. This study found that the HER2 grade changes with ROI selection. We proposed an ROI detection method using Vision Transformer and investigated the role of image magnification for ROI detection. This method yielded an accuracy of 99% using 20 × WSI and 97% using 10 × WSI for the ROI detection. In the demonstration, the proposed method increased the diagnostic agreement to 99.3% with the clinical scores and reduced the time to 15 seconds for automated HER2 grading.

Status and Prospects of Fluorescence In Situ Hybridization Automation—A Survey among Laboratory Directors and Their Designates

As a clinical diagnostic technique, fluorescence in situ hybridization (FISH) is simple, reliable, cost-effective and widely applicable. Due to technology advances, automation systems are adapted in FISH in different ways, involving all and/or some of the following procedural steps: sample processing, probe distribution, hybridization, post-wash, result analysis and/or final report preparation. To better understand the status and prospective of FISH automation, a survey has been recently performed among Cytogenetic Laboratory Directors and/or their designated Laboratory Managers, Supervisors or certified Cytogenetic Technologists. We present here the preliminary analysis of this survey, to advocate more discussion about standardization of the FISH automation as well as implementation of FISH automation as part of educational programs for Cytogenetic Technologists.

Development of a high-sensitivity and short-duration fluorescence in situ hybridization method for viral mRNA detection in HEK 293T cells

Coronavirus disease 2019 (COVID-19) is an extremely contagious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early disease recognition of COVID-19 is crucial not only for prompt diagnosis and treatment of the patients, but also for effective public health surveillance and response. The reverse transcription-polymerase chain reaction (RT-PCR) is the most common method for the detection of SARS-CoV-2 viral mRNA and is regarded as the gold standard test for COVID-19. However, this test and those for antibodies (IgM and IgG) and antigens have certain limitations (e.g., by yielding false-negative and false-positive results). We have developed an RNA fluorescence in situ hybridization (FISH) method for high-sensitivity detection of SARS-CoV-2 mRNAs in HEK 293T cell cultures as a model. After transfection of HEK 293T cells with plasmids, Spike (S)/envelope (E) proteins and their mRNAs were clearly detected inside the cells. In addition, hybridization time could be reduced to 2 hours for faster detection when probe concentration was increased. Our approach might thus significantly improve the sensitivity and specificity of SARS-CoV-2 detection and be widely applied for the high-sensitivity single-molecular detection of other RNA viruses (e.g., Middle East respiratory syndrome coronavirus (MERS-CoV), Hepatitis A virus, all influenza viruses, and human immunodeficiency virus (HIV)) in various types of samples including tissue, body fluid, blood, and water. RNA FISH can also be utilized for the detection of DNA viruses (e.g., Monkeypox virus, human papillomavirus (HPV), and cytomegalovirus (CMV)) by detection of their mRNAs inside cells or body fluid.

Singular Nuclei Segmentation for Automatic HER2 Quantification Using CISH Whole Slide Images

Human epidermal growth factor receptor 2 (HER2) quantification is performed routinely for all breast cancer patients to determine their suitability for HER2-targeted therapy. Fluorescence in situ hybridization (FISH) and chromogenic in situ hybridization (CISH) are the US Food and Drug Administration (FDA) approved tests for HER2 quantification in which at least 20 cancer-affected singular nuclei are quantified for HER2 grading. CISH is more advantageous than FISH for cost, time and practical usability. In clinical practice, nuclei suitable for HER2 quantification are selected manually by pathologists which is time-consuming and laborious. Previously, a method was proposed for automatic HER2 quantification using a support vector machine (SVM) to detect suitable singular nuclei from CISH slides. However, the SVM-based method occasionally failed to detect singular nuclei resulting in inaccurate results. Therefore, it is necessary to develop a robust nuclei detection method for reliable automatic HER2 quantification. In this paper, we propose a robust U-net-based singular nuclei detection method with complementary color correction and deconvolution adapted for accurate HER2 grading using CISH whole slide images (WSIs). The efficacy of the proposed method was demonstrated for automatic HER2 quantification during a comparison with the SVM-based approach.

Computer-Aided Scoring Of () Gene Amplification Status In Breast Cancer

Background

Identification of HER2 protein overexpression and/or amplification of the HER2 gene are required to qualify breast cancer patients for HER2 targeted therapies. In situ hybridization (ISH) assays that identify HER2 gene amplification function as a stand-alone test for determination of HER2 status and rely on the manual quantification of the number of HER2 genes and copies of chromosome 17 to determine HER2 amplification.

Methods

To assist pathologists, we have developed the uPath HER2 Dual ISH Image Analysis for Breast (uPath HER2 DISH IA) algorithm, as an adjunctive aid in the determination of HER2 gene status in breast cancer specimens. The objective of this study was to compare uPath HER2 DISH image analysis vs manual read scoring of VENTANA HER2 DISH-stained breast carcinoma specimens with ground truth (GT) gene status as the reference. Three reader pathologists reviewed 220, formalin-fixed, paraffin-embedded (FFPE) breast cancer cases by both manual and uPath HER2 DISH IA methods. Scoring results from manual read (MR) and computer-assisted scores (image analysis, IA) were compared against the GT gene status generated by consensus of a panel of pathologists. The differences in agreement rates of HER2 gene status between manual, computer-assisted, and GT gene status were determined.

Results

The positive percent agreement (PPA) and negative percent agreement (NPA) rates for image analysis (IA) vs GT were 97.2% (95% confidence interval [CI]: 95.0, 99.3) and 94.3% (95% CI: 90.8, 97.3) respectively. Comparison of agreement rates showed that the lower bounds of the 95% CIs for the difference of PPA and NPA for IA vs MR were –0.9% and –6.2%, respectively. Further, inter- and intra-reader agreement rates in the IA method were observed with point estimates of at least 96.7%.

Conclusions

Overall, our data show that the uPath HER2 DISH IA is non-inferior to manual scoring and supports its use as an aid for pathologists in routine diagnosis of breast cancer.

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Image analysis algorithm for HER2 amplification using Bright-field ISH in Breast.

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Automated tumor cell selection and quantitation within pathologist defined ROI.

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The image analysis algorithm is non-inferior to manual scoring.

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Integrated solution to support pathologists in determining HER2 gene status.

Analysis of human chromosomes by imaging flow cytometry

Chromosomal analysis is traditionally performed by karyotyping on metaphase spreads, or by fluorescent in situ hybridization (FISH) on interphase cells or metaphase spreads. Flow cytometry was introduced as a new method to analyze chromosomes number (ploidy) and structure (telomere length) in the 1970s with data interpretation largely based on fluorescence intensity. This technology has had little uptake for human cytogenetic applications primarily due to analytical challenges. The introduction of imaging flow cytometry, with the addition of digital images to standard multi-parametric flow cytometry quantitative tools, has added a new dimension. The ability to visualize the chromosomes and FISH signals overcomes the inherent difficulties when the data is restricted to fluorescence intensity. This field is now moving forward with methods being developed to assess chromosome number and structure in whole cells (normal and malignant) in suspension. A recent advance has been the inclusion of immunophenotyping such that antigen expression can be used to identify specific cells of interest for specific chromosomes and their abnormalities. This capability has been illustrated in blood cancers, such as chronic lymphocytic leukemia and plasma cell myeloma. The high sensitivity and specificity achievable highlights the potential imaging flow cytometry has for cytogenomic applications (i.e., diagnosis and disease monitoring). This review introduces and describes the development, current status, and applications of imaging flow cytometry for chromosomal analysis of human chromosomes.

HER2 fluorescent in situ hybridization signal degradation: a 10-year retrospective study

CONTEXT

Fluorescence in situ hybridization (FISH) analysis is recommended for invasive breast carcinomas with equivocal (2+) immunohistochemical expression of human epidermal growth factor receptor 2 (HER2). However, existing guidelines for the retention and storage requirements for HER2 FISH slides vary widely among countries and laboratories.

OBJECTIVE

To determine the degradation rate of HER2 FISH signals, and the optimal retention time and storage conditions for HER2 FISH slides.

DESIGN

Dual-probe HER2 FISH slides from March 2009 to June 2019 were retrieved from the archive to assess the presence, intensity and quantity of the green chromosome enumeration probe 17 (CEP 17) and orange HER2 signals. Per the institutional policy, FISH slides are placed in slide boxes and stored in - 80 °C freezers for up to 4 years, whereas older slides are stored at room temperature.

RESULTS

After excluding HER2 FISH slides that were deemed uninterpretable due to technical issues, a total of 6255 slides were assessed. Slides from 2009 to 2014 were stored at room temperature, while slides from 2015 to 2019 were stored in - 80 °C freezers. Slides stored in freezers showed retention of both the green and the orange signals. Slide stored at room temperature demonstrated significant decrease in the signal retention rate and the loss of signal did not progress in a linear fashion. The CEP17 signal was quenched much faster than the HER2 signal.

CONCLUSION

Our study is the first to demonstrate HER2 FISH signal degradation with time and slide storage conditions. Storing HER2 FISH slides in a -80 °C freezer allows for retention of both HER2 and CEP17 signals. At room temperature, the signals start to degrade with CEP17 signals lost at a faster rate. The results of the study may be used in official guidelines for storage conditions and retention time for HER2 FISH slides.

Review of the current state of digital image analysis in breast pathology

Advances in digital image analysis have the potential to transform the practice of breast pathology. In the near future, a move to a digital workflow offers improvements in efficiency. Coupled with artificial intelligence (AI), digital pathology can assist pathologist interpretation, automate time-consuming tasks, and discover novel morphologic patterns. Opportunities for digital enhancements abound in breast pathology, from increasing reproducibility in grading and biomarker interpretation, to discovering features that correlate with patient outcome and treatment. Our objective is to review the most recent developments in digital pathology with clear impact to breast pathology practice. Although breast pathologists currently undertake limited adoption of digital methods, the field is rapidly evolving. Care is needed to validate emerging technologies for effective patient care.

Fast fluorescence in situ hybridisation for the enhanced detection of MET in non-small cell lung cancer

The c-Met/hepatocyte growth factor receptor pathway is frequently dysregulated in multiple cancer types, including non-small cell lung cancer (NSCLC). MET amplification has been shown to develop as a resistance mechanism to treatment in NSCLC. The identification of increased MET copy number within tumour cells is increasingly important to stratify those tumours and patients which are susceptible to treatment targetting MET kinase inhibition. Fluorescence in situ hybridisation (FISH) has been successfully employed to identify patients with abnormal MET gene copy number with numerous probes available for use. Here we report a FISH protocol that reduces probe hybridisation time in NSCLC tissue to 1 hour and compare the results with other protocols. MET gene copy number was determined in 20 NSCLC cases using 3 FISH probes: 1. Kreatech FISH, MET (7q31) SE 7 ready to use probes, hybridised using an overnight protocol; 2. Dako MET IQFISH probe with CEP7 ready to use probe, hybridised for 2 hours; 3. Kreatech MET (7q31) SE 7 XL FISH probe, prepared in SwiftFISH buffer and hybridised for 1 hour. The MET gene copy number and MET: centromere 7 gene ratio were determined for each tissue and cases categorised as having MET high or MET low status. All three FISH probes were shown to demonstrate good agreement with each other. Overall percentage agreement between probes was ≥90%. Intraclass correlation showed good agreement (ICC ≥0.80) between all three assays for MET gene copy number and MET: centromere 7 gene ratio. These FISH protocols provide evidence that rapid laboratory developed FISH assays with short turnaround time perform consistently with standard protocols, potentially enabling faster treatment decisions.

Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists

CONTEXT.—

Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing.

OBJECTIVE.—

To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) for breast cancer where QIA is used.

DESIGN.—

The College of American Pathologists (CAP) convened a panel of pathologists, histotechnologists, and computer scientists with expertise in image analysis, immunohistochemistry, quality management, and breast pathology to develop recommendations for QIA of HER2 IHC in breast cancer. A systematic review of the literature was conducted to address 5 key questions. Final recommendations were derived from strength of evidence, open comment feedback, expert panel consensus, and advisory panel review.

RESULTS.—

Eleven recommendations were drafted: 7 based on CAP laboratory accreditation requirements and 4 based on expert consensus opinions. A 3-week open comment period received 180 comments from more than 150 participants.

CONCLUSIONS.—

To improve accurate, precise, and reproducible interpretation of HER2 IHC results for breast cancer, QIA and procedures must be validated before implementation, followed by regular maintenance and ongoing evaluation of quality control and quality assurance. HER2 QIA performance, interpretation, and reporting should be supervised by pathologists with expertise in QIA.

Automatic quantification of HER2 gene amplification in invasive breast cancer from chromogenic in situ hybridization whole slide images

Human epidermal growth factor receptor 2 (HER2), a transmembrane tyrosine kinase receptor encoded by the ERBB2 gene on chromosome 17q12, is a predictive and prognostic biomarker in invasive breast cancer (BC). Approximately 20% of BC are HER2-positive as a result of ERBB2 gene amplification and overexpression of the HER2 protein. Quantification of HER2 is performed routinely on all invasive BCs, to assist in clinical decision making for prognosis and treatment for HER2-positive BC patients by manually counting gene signals. We propose an automated system to quantify the HER2 gene status from chromogenic in situ hybridization (CISH) whole slide images (WSI) in invasive BC. The proposed method selects untruncated and nonoverlapped singular nuclei from the cancer regions using color unmixing and machine learning techniques. Then, HER2 and chromosome enumeration probe 17 (CEP17) signals are detected based on the RGB intensity and counted per nucleus. Finally, the HER2-to-CEP17 signal ratio is calculated to determine the HER2 amplification status following the ASCO/CAP 2018 guidelines. The proposed method reduced the labor and time for the quantification. In the experiment, the correlation coefficient between the proposed automatic CISH quantification method and pathologist manual enumeration was 0.98. The p -values larger than 0.05 from the one-sided paired t -test ensured that the proposed method yields statistically indifferent results to the reference method. The method was established on WSI scanned by two different scanners. Through the experiments, the capability of the proposed system has been demonstrated.

Automated detection of the HER2 gene amplification status in Fluorescence in situ hybridization images for the diagnostics of cancer tissues

The human epidermal growth factor receptor 2 (HER2) gene amplification status is a crucial marker for evaluating clinical therapies of breast or gastric cancer. We propose a deep learning-based pipeline for the detection, localization and classification of interphase nuclei depending on their HER2 gene amplification state in Fluorescence in situ hybridization (FISH) images. Our pipeline combines two RetinaNet-based object localization networks which are trained (1) to detect and classify interphase nuclei into distinct classes normal, low-grade and high-grade and (2) to detect and classify FISH signals into distinct classes HER2 or centromere of chromosome 17 (CEN17). By independently classifying each nucleus twice, the two-step pipeline provides both robustness and interpretability for the automated detection of the HER2 amplification status. The accuracy of our deep learning-based pipeline is on par with that of three pathologists and a set of 57 validation images containing several hundreds of nuclei are accurately classified. The automatic pipeline is a first step towards assisting pathologists in evaluating the HER2 status of tumors using FISH images, for analyzing FISH images in retrospective studies, and for optimizing the documentation of each tumor sample by automatically annotating and reporting of the HER2 gene amplification specificities.

High-content, cell-by-cell assessment of HER2 overexpression and amplification: a tool for intratumoral heterogeneity detection in breast cancer

Immunohistochemistry and fluorescence in situ hybridization are the two standard methods for human epidermal growth factor receptor 2 (HER2) assessment. However, they have severe limitations to assess quantitatively intratumoral heterogeneity (ITH) when multiple subclones of tumor cells co-exist. We develop here a high-content, quantitative analysis of breast cancer tissues based on microfluidic experimentation and image processing, to characterize both HER2 protein overexpression and HER2 gene amplification at the cellular level. The technique consists of performing sequential steps on the same tissue slide: an immunofluorescence (IF) assay using a microfluidic protocol, an elution step for removing the IF staining agents, a standard FISH staining protocol, followed by automated quantitative cell-by-cell image processing. Moreover, ITH is accurately detected in both cluster and mosaic form using an analysis of spatial association and a mathematical model that allows discriminating true heterogeneity from artifacts due to the use of thin tissue sections. This study paves the way to evaluate ITH with high accuracy and content while requiring standard staining methods.

Assessment of HER2 amplification status in breast cancer using a new automated HER2 IQFISH pharmDx™ (Dako Omnis) assay

In breast cancer the human epidermal growth factor receptor 2 (HER2) is an important target for a number of different HER2 inhibitors. Different slide-based assays are available for assessment of treatment eligibility, which include fluorescence in situ hybridization (FISH) or other in situ hybridization (ISH) methods for assessment of the HER2 gene status. Here we report a summary of the validation data on HER2 IQFISH pharmDx™ (Dako Omnis), a newly developed assay for the automated staining platform Dako Omnis. The assay uses a non-toxic buffer that significantly reduces the hybridization time, which results in a total turnaround time of 3½ to 4h from deparaffinization to counting of the gene and centromere signals. The data reported in the current summary covers method comparison, assessment of staining quality, observer-to-observer reproducibility as well as reproducibility within and between laboratories. Based on data from the different studies it was concluded that HER2 IQFISH pharmDx (Dako Omnis) is a reliable and robust assay with a high precision that is at least comparable to the manual HER2 IQFISH pharmDx™ assay and the PathVysion(®)HER-2 DNA Probe Kit.

Validation of break-apart and fusion MYC probes using a digital fluorescence in situ hybridization capture and imaging system

INTRODUCTION

Detection of MYC translocations using fluorescence in situ hybridization (FISH) is important in the evaluation of lymphomas, in particular, Burkitt lymphoma and diffuse large B-cell lymphoma. Our aim was to validate a digital FISH capture and imaging system for the detection of MYC 8q24 translocations using LSI-MYC (a break-apart probe) and MYC 8;14 translocation using IGH-MYC (a fusion probe).

MATERIALS AND METHODS

LSI-MYC probe was evaluated using tissue sections from 35 patients. IGH-MYC probe was evaluated using tissue sections from forty patients. Sections were processed for FISH and analyzed using traditional methods. FISH slides were then analyzed using the GenASIs capture and analysis system.

RESULTS

Results for LSI-MYC had a high degree of correlation between traditional method of FISH analysis and digital FISH analysis. Results for IGH-MYC had a 100% concordance between traditional method of FISH analysis and digital FISH analysis.

CONCLUSION

Annotated whole slide images of H and E and FISH sections can be digitally aligned, so that areas of tumor within a section can be matched and evaluated with a greater degree of accuracy. Images can be archived permanently, providing a means for examining the results retrospectively. Digital FISH imaging of the MYC translocations provides a better diagnostic tool compared to traditional methods for evaluating lymphomas.