Sectioning Artifacts Research Articles

Development of an automated combined positive score prediction pipeline using artificial intelligence on multiplexed immunofluorescence images

Immunotherapy targeting immune checkpoint proteins, such as programmed cell death ligand 1 (PD-L1), has shown impressive outcomes in many clinical trials but only 20%–40% of patients benefit from it. Utilizing Combined Positive Score (CPS) to evaluate PD-L1 expression in tumour biopsies to identify patients with the highest likelihood of responsiveness to anti-PD-1/PD-L1 therapy has been approved by the Food and Drug Administration for several solid tumour types. Current CPS workflow requires a pathologist to manually score the two-colour PD-L1 chromogenic immunohistochemistry image. Multiplex immunofluorescence (mIF) imaging reveals the expression of an increased number of immune markers in tumour biopsies and has been used extensively in immunotherapy research. Recent rapid progress of Artificial Intelligence (AI)-based imaging analysis, particularly Deep Learning, provides cost effective and high-quality solutions to healthcare. In this article, we propose an imaging pipeline that utilizes three-colour mIF images (DAPI, PD-L1, and Pan-cytokeratin) as input and predicts the CPS using AI techniques. Our novel pipeline is composed of three modules employing algorithms of image processing, machine learning, and deep learning techniques. The first module of quality check (QC) detects and removes the image regions contaminated with sectioning and staining artefacts. The QC module ensures that only image regions free of the three common artefacts are used for downstream analysis. The second module of nuclear segmentation uses deep learning to segment and count nuclei in the DAPI images wherein our specialized method can accurately separate touching nuclei. The third module of cell phenotyping calculates CPS by identifying and counting PD-L1 positive cells and tumour cells. These modules are data-efficient and require only few manual annotations for training purposes. Using tumour biopsies from a clinical trial, we found that the CPS from the AI-based models shows a high Spearman correlation (78%, p = 0.003) to the pathologist-scored CPS.

Vascular smooth muscle cell contractile proteins as universal markers of vessels of microcirculatory bed

Highlights. The use of vascular smooth muscle cell markers, e.g. smooth muscle myosin heavy chain (SM-MHC) and alpha smooth muscle actin (α-SMA) for immunodetection of adventitial and perivascular microvessels (vasa vasorum) is preferrable over endothelial markers (CD31 and VE-cadherin) as it allows to define vascular geometry regardless of sectioning artifacts and provides ideal signal-to-noise ratio.Aside from elastic laminae which discriminate arterioles from venules and capillaries, we were unable to confirm any specific markers of arterial, venous, and capillary differentiation, although KLF2 and PROX1 transcription factors indicated venous specification and HEY1 suggested capillary identity in rat aortas.Aim. To develop an optimal approach to detection of microvessels and to evaluate the techniques for the differential immunostaining of arterioles, venules, and capillaries in human saphenous veins and rat aortas.Methods. Saphenous veins excised during the coronary artery bypass graft surgery were used for the study. Serial cryosections were analyzed by means of haematoxylin and eosin and Russell-Movat’s pentachrome stainings and by immunofluorescent staining for endothelial cell markers (CD31 and VE-cadherin), vascular smooth muscle cell markers (SM-MHC and α-SMA), mechanosensitive transcription factors (KLF2 and KLF4), transcription factors of arterial specification (HES1, HEY1, ERG), transcription factors and markers of venous identity (NR2F2, NRP2), and transcription factors and markers of lymphatic lineage (PROX1, LYVE1, VEGFR3). Samples were visualized by light and confocal microscopy.Results. In comparison with endothelial cell markers (CD31 and VE-cadherin), vascular smooth muscle cell markers (SM-MHC and α-SMA) permitted objective evaluation of vascular geometry and maximized signal-to-noise ratio irrespective of specific marker, microvessel specification or antibody used. Autofluorescence and specific histological pattern of elastic membranes at Russell-Movat’s pentachrome staining allowed to discriminate arterioles from venules and capillaries. Albeit immunostaining of rat aortas found specific markers of venous endothelial cells (KLF2 and PROX1) and capillary endothelial cells (HEY1), these findings have not been confirmed in saphenous veins. We were unable to find specific markers of human venules and capillaries among the saphenous vein vasa vasorum despite an extensive screening of multiple markers.Conclusion. Immunodetection of microvessels (e.g., vasa vasorum) should be performed by using vascular smooth muscle cell markers (SM-MHC and α-SMA) rather than endothelial cell markers (CD31 and VE-cadherin). Lack of specific markers to discern microvessels of different lineages suggests Russell-Movat’s pentachrome staining as an optimal option for the machine learning of neural networks to analyse the microvessels including vasa vasorum.

Too bright for 2 dimensions: recent progress in advanced 3-dimensional microscopy of the kidney

The kidney is a structurally and functionally complex organ responsible for the control of water, ion, and other solute homeostasis. Moreover, the kidneys excrete metabolic waste products and produce hormones, such as renin and erythropoietin. The functional unit of the kidney is the nephron, which is composed by a serial arrangement of a filter unit called the renal corpuscle and several tubular segments that modulate the filtered fluid by reabsorption and secretion. Within each kidney, thousands of nephrons are closely intermingled and surrounded by an intricate network of blood vessels and various interstitial cell types, including fibroblasts and immune cells. This complex tissue architecture is essential for proper kidney function. In fact, kidney disease is often reflected or even caused by a derangement of the histologic structures. Frequently, kidney histology is studied using microscopic analysis of 2-dimensional tissue sections, which, however, misses important 3-dimensional spatial information. Reconstruction of serial sections tries to overcome this limitation, but is technically challenging, time-consuming, and often inherently linked to sectioning artifacts. In recent years, advances in tissue preparation (e.g., optical clearing) and new light- and electron-microscopic methods have provided novel avenues for 3-dimensional kidney imaging. Combined with novel machine-learning algorithms, these approaches offer unprecedented options for large-scale and automated analysis of kidney structure and function. This review provides a brief overview of these emerging imaging technologies and presents key examples of how these approaches are already used to study the normal and the diseased kidney.

3D Imaging of PDL Collagen Fibers during Orthodontic Tooth Movement in Mandibular Murine Model.

Orthodontic tooth movement is a complex biological process of altered soft and hard tissue remodeling as a result of external forces. In order to understand these complex remodeling processes, it is critical to study the tooth and periodontal tissues within their 3D context and therefore minimize any sectioning and tissue artefacts. Mouse models are often utilized in developmental and structural biology, as well as in biomechanics due to their small size, high metabolic rate, genetics and ease of handling. In principle this also makes them excellent models for dental related studies. However, a major impediment is their small tooth size, the molars in particular. This paper is aimed at providing a step by step protocol for generating orthodontic tooth movement and two methods for 3D imaging of the periodontal ligament fibrous component of a mouse mandibular molar. The first method presented is based on a micro-CT setup enabling phase enhancementimaging of fresh collagen tissues. The second method is a bone clearing method using ethyl cinnamate that enables imaging through the bone without sectioning and preserves endogenous fluorescence. Combining this clearing method with reporter mice like Flk1-Cre;TdTomato provided a first of its kind opportunity to image the 3D vasculature in the PDL and alveolar bone.

Practical Approaches for Cryo-FIB Milling and Applications for Cellular Cryo-Electron Tomography.

Cryo-electron tomography (cryo-ET) is a powerful technique to examine cellular structures as they exist in situ. However, direct imaging by TEM for cryo-ET is limited to specimens up to ∼400nm in thickness, narrowing its applicability to areas such as cellular projections or small bacteria and viruses. Cryo-focused ion beam (cryo-FIB) milling has emerged in recent years as a method to generate thin specimens from cellular samples in preparation for cryo-ET. In this technique, specimens are thinned with a beam of gallium ions to gradually ablate cellular material in order to leave a thin, electron-transparent section (a lamella) through the bulk material. The lamella can be used for high-resolution cryo-ET to visualize cells in 3D in a near-native state. This approach has proved to be robust and relatively simple for new users and exhibits minimal sectioning artifacts. In this chapter, we describe a general approach to cryo-FIB milling for users with prior cryo-EM experience, with extensive notes on operation and troubleshooting.

Deep learning quantification of percent steatosis in donor liver biopsy frozen sections.

BackgroundPathologist evaluation of donor liver biopsies provides information for accepting or discarding potential donor livers. Due to the urgent nature of the decision process, this is regularly performed using frozen sectioning at the time of biopsy. The percent steatosis in a donor liver biopsy correlates with transplant outcome, however there is significant inter- and intra-observer variability in quantifying steatosis, compounded by frozen section artifact. We hypothesized that a deep learning model could identify and quantify steatosis in donor liver biopsies.MethodsWe developed a deep learning convolutional neural network that generates a steatosis probability map from an input whole slide image (WSI) of a hematoxylin and eosin-stained frozen section, and subsequently calculates the percent steatosis. Ninety-six WSI of frozen donor liver sections from our transplant pathology service were annotated for steatosis and used to train (n = 30 WSI) and test (n = 66 WSI) the deep learning model.FindingsThe model had good correlation and agreement with the annotation in both the training set (r of 0.88, intraclass correlation coefficient [ICC] of 0.88) and novel input test sets (r = 0.85 and ICC=0.85). These measurements were superior to the estimates of the on-service pathologist at the time of initial evaluation (r = 0.52 and ICC=0.52 for the training set, and r = 0.74 and ICC=0.72 for the test set).InterpretationUse of this deep learning algorithm could be incorporated into routine pathology workflows for fast, accurate, and reproducible donor liver evaluation.FundingMid-America Transplant Society

False-Negative Histopathologic Diagnosis of Prostatic Adenocarcinoma.

Histopathologic diagnosis of adenocarcinoma of the prostate is based on light-microscopic examination of hematoxylin-eosin-stained tissue sections. Multiple factors, including preanalytic and analytic elements, affect the ability of the pathologist to accurately diagnose prostatic adenocarcinoma. False-negative diagnosis, that is, failure to diagnose prostatic adenocarcinoma, may have serious clinical consequences. It is important to delineate and understand those factors that may affect and cause histopathologic false-negative diagnoses of prostatic adenocarcinoma. To review common factors involved in histopathologic underdiagnosis of prostatic adenocarcinoma, including the following: (1) tissue processing and sectioning artifacts, (2) minimal adenocarcinoma, (3) deceptively benign appearing variants of acinar adenocarcinoma, (4) single cell adenocarcinoma, and (5) treatment effects. Data sources included published, peer-reviewed literature and personal experiences of the senior author. Knowledge of the reasons for histopathologic false-negative diagnosis of adenocarcinoma of the prostate is an important component in the diagnostic assessment of prostate tissue sections. Diagnostic awareness of the histomorphologic presentations of small (minimal) adenocarcinoma; deceptively benign appearing variants including atrophic, foamy gland, microcystic, and pseudohyperplastic variants; single cell carcinoma; and treatment effects is critical for establishment of a definitive diagnosis of adenocarcinoma and the prevention of false-negative diagnoses of prostate cancer.

Correlative 3D Imaging and Microfluidic Modelling of Human Pulmonary Lymphatics using Immunohistochemistry and High-resolution \u03bcCT

Lung lymphatics maintain fluid homoeostasis by providing a drainage system that returns fluid, cells and metabolites to the circulatory system. The 3D structure of the human pulmonary lymphatic network is essential to lung function, but it is poorly characterised. Image-based 3D mathematical modelling of pulmonary lymphatic microfluidics has been limited by the lack of accurate and representative image geometries. This is due to the microstructural similarity of the lymphatics to the blood vessel network, the lack of lymphatic-specific biomarkers, the technical limitations associated with image resolution in 3D, and sectioning artefacts present in 2D techniques. We present a method that combines lymphatic specific (D240 antibody) immunohistochemistry (IHC), optimised high-resolution X-ray microfocus computed tomography (μCT) and finite-element mathematical modelling to assess the function of human peripheral lung tissue. The initial results identify lymphatic heterogeneity within and between lung tissue. Lymphatic vessel volume fraction and fractal dimension significantly decreases away from the lung pleural surface (p < 0.001, n = 25 and p < 0.01, n = 20, respectively). Microfluidic modelling successfully shows that in lung tissue the fluid derived from the blood vessels drains through the interstitium into the lymphatic vessel network and this drainage is different in the subpleural space compared to the intralobular space. When comparing lung tissue from health and disease, human pulmonary lymphatics were significantly different across five morphometric measures used in this study (p ≤ 0.0001). This proof of principle study establishes a new engineering technology and workflow for further studies of pulmonary lymphatics and demonstrates for the first time the combination of correlative μCT and IHC to enable 3D mathematical modelling of human lung microfluidics at micrometre resolution.

Histological Image Analysis of Scaffold‐Based Cell Products to Estimate Percent Viability

IntroductionRegulatory agencies have an expectation that cell‐based products in clinical development be characterized for their percent (%) viability. However, many new cell‐based products do not readily lend themselves to determining this metric through classical methods such as enzymatic dissociation and cell enumeration. Vital Therapies, Inc. (VTL) uses four metabolically active cartridges containing VTL C3A cells in its investigational (phase 3) ELAD® System, an extracorporeal human allogeneic cellular treatment being evaluated for severe alcoholic hepatitis. This study objective was to develop and verify new image processing methods for automatically characterizing the % viability of ELAD C3A cell cartridge histological samples.MethodsELAD C3A cell cartridges were clinically manufactured by introducing VTL C3A cells into the extracapillary space and perfusing growth medium through the lumens of the porous polysulfone hollow fibers. At maturity, cartridges were fixed for histology by recirculating 10% neutral buffered formalin through the hollow fiber lumens for approximately 24 hr. Cross‐sectional discs (~2‐cm thick) were cut using a saw and further cut into 16‐grid samples prior to paraffin embedding. Thin (4‐mm) sections were sliced from the grid blocks, stained with hematoxylin and eosin, and imaged using a high‐resolution scanner (Olympus VS120 or Hamamatsu NanoZoomer 2.0). MATLAB software was utilized to develop a custom algorithm to automatically isolate, count, and mask the hollow fiber cross‐sections through image processing techniques (e.g., color thresholding and object feature segmentation). Grayscale histogram analysis of the differently stained cells in the remaining space was utilized to separate viable from non‐viable areas. The % viability for an entire histology grid image could then be reported as the integrated ratio of viable tissue area to total tissue area. This method was compared to blinded, independent mass measurements of printed and hand‐cut images to separate hollow fiber, viable tissue, and non‐viable tissue areas. Additional comparisons were made against blinded visual assessment.ResultsThis methodology demonstrated that reliable % viability estimates could be estimated from histological images despite fixation and/or sectioning artifacts (e.g., tissue separating from the hollow fibers). The automated image‐processing method was able to complete the analysis very rapidly (e.g., an 8000×8000 pixel image containing over 600 fibers is analyzed in a couple minutes), such that a large library of histological samples could be completed quickly and the results tallied for inter‐grid, intra‐ and inter‐cartridge, and intra‐ and inter‐lot comparisons.ConclusionsNew cell‐based products require creative approaches to address regulatory expectations. The image processing algorithm developed herein was shown to be in agreement with, and more reproducible and rapid than, visual or manual assessments. It was further recognized that this method could be extended to other types of histological stains (e.g., trichrome) or to other types of biomaterial/scaffold‐based tissue‐engineered products.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Label-free automated three-dimensional imaging of whole organs by microtomy-assisted photoacoustic microscopy

Three-dimensional (3D) optical imaging of whole biological organs with microscopic resolution has remained a challenge. Most versions of such imaging techniques require special preparation of the tissue specimen. Here we demonstrate microtomy-assisted photoacoustic microscopy (mPAM) of mouse brains and other organs, which automatically acquires serial distortion-free and registration-free images with endogenous absorption contrasts. Without tissue staining or clearing, mPAM generates micrometer-resolution 3D images of paraffin- or agarose-embedded whole organs with high fidelity, achieved by label-free simultaneous sensing of DNA/RNA, hemoglobins, and lipids. mPAM provides histology-like imaging of cell nuclei, blood vessels, axons, and other anatomical structures, enabling the application of histopathological interpretation at the organelle level to analyze a whole organ. Its deep tissue imaging capability leads to less sectioning, resulting in negligible sectioning artifact. mPAM offers a new way to better understand complex biological organs.

Postnatal Development of the Murine Notochord Remnants Quantified by High-resolution Contrast-enhanced MicroCT

The notochord gives rise to spinal segments during development, and it becomes embedded within the nucleus pulposus of the intervertebral disc (IVD) during maturation. The disruption of the notochord band has been observed with IVD degeneration. Since the mechanical competence of the IVD relies on its structural constituents, defining the structure of the notochord during aging is critical for investigations relating to IVD function and homeostasis. The assessment and imaging of the notochord has classically relied on histological techniques, which introduces sectioning artifacts during preparation and spatial biases. Magnetic resonance imaging (MRI) does not offer sufficient resolution to discriminate the notochord from the surrounding the nucleus pulposus, especially in murine models. Current X-ray based computed tomography systems provide imaging resolutions down to the single- and sub- micron scales, and when coupled with contrast-enhancing agents, enable the high-resolution three-dimensional imaging of relatively small features. Utilizing phosphomolybdic acid to preferentially bind to collagen cationic domains, we describe the structure of the notochord remnants with aging in the lumbar IVDs of BALB/c mice. These results provide a highly quantitative and sensitive approach to monitoring the IVD during postnatal development.

Calcaneal Tendon Collagen Fiber Morphometry and Aging.

Fibrillar collagen in tendons and its natural development in rabbits are discussed in this paper. Achilles tendons from newborn (~7 days) to elderly (~38 months) rabbits were monitored in intact (n tendons=24) and microtome sectioned (n tendons=11) states with label-free second harmonic generation microscopy. After sectioning, the collagen fiber pattern was irregular for the younger animals and remained oriented parallel to the load axis of the tendon for the older animals. In contrast, the collagen fiber pattern in the intact samples followed the load axis for all the age groups. However, there was a significant difference in the tendon crimp pattern appearance between the age groups. The crimp amplitude (A) and wavelength (Λ) started at very low values (A=2.0±0.6 µm, Λ=19±4 µm) for the newborn animals. Both parameters increased for the sexually mature animals (>5 months old). When the animals were fully mature the amplitude decreased but the wavelength kept increasing. The results revealed that the microtome sectioning artifacts depend on the age of animals and that the collagen crimp pattern reflects the physical growth and development.

The Quantitative Structural and Compositional Analyses of Degenerating Intervertebral Discs Using Magnetic Resonance Imaging and Contrast-Enhanced Micro-Computed Tomography.

The intervertebral disc (IVD) is susceptible to degenerative changes that are associated with low back pain. Murine models are often used to investigate the mechanistic changes in the development, aging, and diseased states of the IVD, yet the detection of early degenerative changes in structure is challenging because of the minute size of the murine IVDs. Histology is the gold standard for examining the IVD structure, but it is susceptible to sectioning artifacts, spatial biases, and requires the destructive preparation of the sample. We have previously demonstrated the feasibility of using Ioversol for the contrast-enhanced micro-computed tomography (microCT) to visualize and quantitate the intact healthy murine IVD. In this work, we demonstrate utility of this approach to monitor the longitudinal changes of in vitro nucleolytic- and mechanical injury- degeneration models of the murine discs and introduce novel quantitative metrics to characterize the structure and composition of the IVD. Moreover, we compared the imaging quality and quantitation of these in vitro models to magnetic resonance imaging (MRI) and histology. Stab puncture, trypsin injection, and collagenase injection all induced detectable and significant changes in structure and composition of the discs overtime. Compared to MRI and histology, contrast-enhanced microCT produced superior images that capture the degenerative progression in these models. Contrast-enhanced microCT was also capable of monitoring the structural deteriorations via the changes in disc height and volume, and novelthe nucleus pulposus intensity/disc intensity (NI/DI) parameter provides a surrogate measure of proteoglycan composition (R=0.96). Overall, this approach allows for the nondestructive monitoring of the structure and composition of the IVD at very high resolutions.

Extending two-dimensional histology into the third dimension through conventional micro computed tomography

Histological examination achieves sub-micrometer resolution laterally. In the third dimension, however, resolution is limited to section thickness. In addition, histological sectioning and mounting sections on glass slides introduce tissue-dependent stress and strain. In contrast, state-of-the-art hard X-ray micro computed tomography (μCT) systems provide isotropic sub-micrometer resolution and avoid sectioning artefacts. The drawback of μCT in the absorption contrast mode for visualising physically soft tissue is a low attenuation difference between anatomical features. In this communication, we demonstrate that formalin-fixed paraffin-embedded human cerebellum yields appropriate absorption contrast in laboratory-based μCT data, comparable to conventional histological sections. Purkinje cells, for example, are readily visible. In order to investigate the pros and cons of complementary approaches, two- and three-dimensional data were manually and automatically registered. The joint histogram of histology and the related μCT slice allows for a detailed discussion on how to integrate two-dimensional information from histology into a three-dimensional tomography dataset. This methodology is not only rewarding for the analysis of the human cerebellum, but it also has relevance for investigations of tissue biopsies and post-mortem applications. Our data indicate that laboratory-based μCT as a modality can fill the gap between synchrotron radiation-based μCT and histology for a variety of tissues. As the information from haematoxylin and eosin (H&E) stained sections and μCT data is related, one can colourise local X-ray absorption values according to the H&E stain. Hence, μCT data can correlate and virtually extend two-dimensional (2D) histology data into the third dimension.

Development of a database system and image viewer to assist in the correlation of histopathologic features and digital image analysis with clinical and molecular genetic information.

Pathologists are required to integrate data from multiple sources when making a diagnosis. Furthermore, whole slide imaging (WSI) and next generation sequencing will escalate data size and complexity. Development of well-designed databases that can allow efficient navigation between multiple data types is necessary for both clinical and research purposes. We developed and evaluated an interactive, web-based database that integrates clinical, histologic, immunohistochemical and genetic information to aid in pathologic diagnosis and interpretation with nine lung adenocarcinoma cases. To minimize sectioning artifacts, representative blocks were serially sectioned using automated tissue sectioning (Kurabo Industries, Osaka Japan) and selected slides were stained by multiple techniques, (hematoxylin and eosin [H&E], immunohistochemistry [IHC] or fluorescence in situ hybridization [FISH]). Slides were digitized by WSI scanners. An interactive relational database was designed based on a list of proposed fields covering a variety of clinical, pathologic and molecular parameters. By focusing on the three main tasks of 1.) efficient management of textual information, 2.) effective viewing of all varieties of stained whole slide images (WSI), and 3.) assistance in evaluating WSI with computer-aided diagnosis, this database prototype shows great promise for multi-modality research and diagnosis.

Overdiagnosis of high-grade dysplasia in Barrett's esophagus: a multicenter, international study

Numerous histological mimics of high-grade dysplasia in Barrett's esophagus predispose to overdiagnosis and potential serious mismanagement, including unnecessary esophagectomy. This study investigates the prevalence and sources of this problem. Biopsies from 485 patients diagnosed with Barrett's high-grade dysplasia were screened for a multi-institutional, international Barrett's endoscopic ablation trial. Screening included review of the original diagnostic slides and an additional protocol endoscopy with an extensive biopsy sampling. Observer variability by the study pathologists was assessed through two blinded diagnostic rounds on 437 biopsies from 26 random study endoscopies. Study diagnostic reassessments revealed significantly lower rates of high-grade dysplasia. Only 248 patients (51%) were confirmed to have high-grade dysplasia. The remaining patients had inflamed gastric cardia without Barrett's (n=18; 7%), Barrett's without dysplasia (n=35; 15%), indefinite change (n=61; 26%), low-grade dysplasia (n=79; 33%), adenocarcinoma (n=43; 18%), and other (n=1; <1%), yielding an alarming total of 194 or 40% of patients who were overdiagnosed with Barrett's high-grade dysplasia. Study pathologists achieved a high-level agreement (90% three-way inter-observer agreement per biopsy, Kappa value 0.77) for high-grade dysplasia. Confounding factors promoting overdiagnosis included Barrett's inflammatory atypia (n=182), atypia limited to the basal metaplastic glands (n=147), imprecise criteria for low grade neoplasia (n=102), tangential sectioning artifact (n=59), and reactive gastric cardiac mucosa (n=38). A total of 194 patients (40%) were overdiagnosed with Barrett's high-grade dysplasia, as affirmed by the extensive screening process and high-level study pathologist agreement. The multiple diagnostic pitfalls uncovered should help raise pathologists' awareness of this problem and improve diagnostic accuracy.

Experimental determination of the nucleation rate of melt in a solid solution

An experimental method for measuring the nucleation rate of liquid in a solid solution using partially melted and resolidified samples is presented. The size distributions of liquid droplets that formed in the grain interior during annealing in a temperature gradient are determined from the size distribution of secondary-phase particles resulting from resolidification of the droplets. Quantitative microstructural analysis considering correcting sectioning artifacts is used. In combination with numerical simulations that calculate the droplet growth on the basis of the experimental temperature history, the nucleation rate of liquid is determined as a function of time. Depending on the location in the temperature gradient, both the size distributions and the nucleation rates exhibit either one or two maxima. The transition from monomodal to bimodal distributions at a temperature less than 10K above the solidus temperature indicates the existence of two different types of nucleation sites for melting in the grain interior. The transferability of the time-dependent nucleation rate of liquid on the nucleation rate of solid is discussed in view of the differences from the established concepts of athermal, thermal and instantaneous nucleation.

Numerical and structural genomic aberrations are reliably detectable in tissue microarrays of formalin-fixed paraffin-embedded tumor samples by fluorescence in-situ hybridization.

Few data are available regarding the reliability of fluorescence in-situ hybridization (FISH), especially for chromosomal deletions, in high-throughput settings using tissue microarrays (TMAs). We performed a comprehensive FISH study for the detection of chromosomal translocations and deletions in formalin-fixed and paraffin-embedded (FFPE) tumor specimens arranged in TMA format. We analyzed 46 B-cell lymphoma (B-NHL) specimens with known karyotypes for translocations of IGH-, BCL2-, BCL6- and MYC-genes. Locus-specific DNA probes were used for the detection of deletions in chromosome bands 6q21 and 9p21 in 62 follicular lymphomas (FL) and six malignant mesothelioma (MM) samples, respectively. To test for aberrant signals generated by truncation of nuclei following sectioning of FFPE tissue samples, cell line dilutions with 9p21-deletions were embedded into paraffin blocks. The overall TMA hybridization efficiency was 94%. FISH results regarding translocations matched karyotyping data in 93%. As for chromosomal deletions, sectioning artefacts occurred in 17% to 25% of cells, suggesting that the proportion of cells showing deletions should exceed 25% to be reliably detectable. In conclusion, FISH represents a robust tool for the detection of structural as well as numerical aberrations in FFPE tissue samples in a TMA-based high-throughput setting, when rigorous cut-off values and appropriate controls are maintained, and, of note, was superior to quantitative PCR approaches.

Images in Endocrine Pathology: Parathyroid Adenoma with Frozen Section Artifact Mimics Thyroid Papillary Carcinoma

An 80-year-old female presented with osteopenia. Laboratory investigation revealed calcium was 11.0 mg/dL (normal, 8.9– 10.3) with a parathyroid hormone (PTH) of 10.8 pmol/L (normal range of 1.3 to 9.3). Sestamibi scan revealed a nodule in the region of the middle right lobe of the thyroid consistent with a parathyroid adenoma. During the operation, the right upper parathyroid was identified at the typical position measuring 1.8×1.3×0.9 cm andweighing 1.0496 g. The specimen was bisected to reveal a tan homogeneous cut surface, and one representative section was submitted for frozen section.

A Novel Quantitative Approach for Eliminating Sample-To-Sample Variation Using a Hue Saturation Value Analysis Program

ObjectivesAs computing technology and image analysis techniques have advanced, the practice of histology has grown from a purely qualitative method to one that is highly quantified. Current image analysis software is imprecise and prone to wide variation due to common artifacts and histological limitations. In order to minimize the impact of these artifacts, a more robust method for quantitative image analysis is required.Methods and ResultsHere we present a novel image analysis software, based on the hue saturation value color space, to be applied to a wide variety of histological stains and tissue types. By using hue, saturation, and value variables instead of the more common red, green, and blue variables, our software offers some distinct advantages over other commercially available programs. We tested the program by analyzing several common histological stains, performed on tissue sections that ranged from 4 µm to 10 µm in thickness, using both a red green blue color space and a hue saturation value color space.ConclusionWe demonstrated that our new software is a simple method for quantitative analysis of histological sections, which is highly robust to variations in section thickness, sectioning artifacts, and stain quality, eliminating sample-to-sample variation.