Deep 3D histology powered by tissue clearing, omics and AI.

To comprehensively understand tissue and organism physiology and pathophysiology, it is essential to create complete three-dimensional (3D) cellular maps. These maps require structural data, such as the 3D configuration and positioning of tissues and cells, and molecular data on the constitution of each cell, spanning from the DNA sequence to protein expression. While single-cell transcriptomics is illuminating the cellular and molecular diversity across species and tissues, the 3D spatial context of these molecular data is often overlooked. Here, I discuss emerging 3D tissue histology techniques that add the missing third spatial dimension to biomedical research. Through innovations in tissue-clearing chemistry, labeling and volumetric imaging that enhance 3D reconstructions and their synergy with molecular techniques, these technologies will provide detailed blueprints of entire organs or organisms at the cellular level. Machine learning, especially deep learning, will be essential for extracting meaningful insights from the vast data. Further development of integrated structural, molecular and computational methods will unlock the full potential of next-generation 3D histology.

A Scalable Histological Method to Embed and Section Multiple Brains Simultaneously.

The preparation and processing of rodent brains for evaluation by immunohistochemistry is time-consuming. A large number of mouse brains are routinely used in experiments in neuroscience laboratories to evaluate several models of human diseases. Thus, methods are needed to reduce the time associated with processing brains for histology. A scalable method was developed to embed, section, and stain multiple mouse brains using supplies found in any common histology laboratory. Section collection schemes can be scaled to provide identical bregma locations between adjacent sections for immunohistochemistry, facilitating comprehensive, high-quality immunohistochemistry. As a result, sectioning and staining times are considerably reduced as sections from multiple blocks are stained simultaneously. This method improves on previous procedures and allows multiple embedding and subsequent immunostaining of brains easily with a dramatically reduced time requirement. Furthermore, we expand this method for use in numerous mouse tissues, rat brain tissue, and post-mortem human brain and arterial tissues. In summary, this procedure allows the processing of many rodent or human tissues from perfusion through microscopy in 10 days or less.

Sliding Window Optimal Transport for Open World Artifact Detection in Histopathology.

Histological images are frequently impaired by local artifacts from scanner malfunctions or iatrogenic processes - caused by preparation - impacting the performance of Deep Learning models. Models often struggle with the slightest out-of-distribution shifts, resulting in compromised performance. Detecting artifacts and failure modes of the models is crucial to ensure open-world applicability to whole slide images for tasks like segmentation or diagnosis. We introduce a novel technique for out-of-distribution detection within whole slide images, compatible with any segmentation or classification model. Our approach tiles multi-layer features into sliding window patches and leverages optimal transport to align them with recognized in-distribution samples. We average the optimal transport costs over tiles and layers to detect out-of-distribution samples. Notably, our method excels in identifying failure modes that would harm downstream performance, surpassing contemporary out-of-distribution detection techniques. We evaluate our method for both natural and synthetic artifacts, considering distribution shifts of various sizes and types. The results confirm that our technique outperforms alternative methods for artifact detection. We assess our method components and the ability to negate the impact of artifacts on the downstream tasks. Finally, we demonstrate that our method can mitigate the risk of performance drops in downstream tasks, enhancing reliability by up to 77%. In testing 7 annotated whole slide images with natural artifacts, our method boosted the Dice score by 68%, highlighting its real open-world utility.

Histopathology Image Classification With Noisy Labels via The Ranking Margins.

Clinically, histopathology images always offer a golden standard for disease diagnosis. With the development of artificial intelligence, digital histopathology significantly improves the efficiency of diagnosis. Nevertheless, noisy labels are inevitable in histopathology images, which lead to poor algorithm efficiency. Curriculum learning is one of the typical methods to solve such problems. However, existing curriculum learning methods either fail to measure the training priority between difficult samples and noisy ones or need an extra clean dataset to establish a valid curriculum scheme. Therefore, a new curriculum learning paradigm is designed based on a proposed ranking function, which is named The Ranking Margins (TRM). The ranking function measures the 'distances' between samples and decision boundaries, which helps distinguish difficult samples and noisy ones. The proposed method includes three stages: the warm-up stage, the main training stage and the fine-tuning stage. In the warm-up stage, the margin of each sample is obtained through the ranking function. In the main training stage, samples are progressively fed into the networks for training, starting from those with larger margins to those with smaller ones. Label correction is also performed in this stage. In the fine-tuning stage, the networks are retrained on the samples with corrected labels. In addition, we provide theoretical analysis to guarantee the feasibility of TRM. The experiments on two representative histopathologies image datasets show that the proposed method achieves substantial improvements over the latest Label Noise Learning (LNL) methods.

CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery.

Prevalencia de cristales de colesterol en granulomas perirradiculares de origen endodóntico / Prevalence of cholesterol crystals in periradicular granulomas of endodontic origin

Objetivos: Identificar y determinar la prevalencia de cristales de colesterol (CRCo) en granulomas perirradiculares de origen endodóntico y el tipo de reacción que provocan en los tejidos circundantes. Material y métodos: Se estudiaron con microscopía óptica 75 preparados histológicos de archivo pertenecientes a lesiones perirradiculares humanas correspondientes a piezas dentarias que habían recibido un tratamiento endodóntico pre- vio y que, según los informes que acompañaban las muestras, habían sido obtenidas mediante una apicectomía. Del total, 68 muestras fueron diagnosticadas como granulomas, mientras que los 7 restantes se diagnosticaron como quistes inflamato- rios y fueron descartadas. Resultados: 39 granulomas pertenecían a pacientes de sexo femenino con presencia de CRCo en el 58,97% de los ca- sos. Los 29 granulomas restantes pertenecían al sexo mascu- lino y presentaron CRCo en un 41,37%. La mayor proporción de CRCo fue hallada en granulomas pertenecientes a pacien- tes mayores de 62 años. Los CRCo se observaron rodeados de macrófagos y células gigantes multinucleadas, provocando una reacción a cuerpo extraño. También se observaron células espumosas en áreas circundantes. Conclusiones: La presencia de CRCo en granulomas perirradiculares de origen endodóntico provoca una reacción a cuerpo extraño que puede interferir con el proceso de re- paración posendodóntico especialmente en pacientes de edad avanzada (AU)

Aim: Identify and determine the prevalence of cholester- ol crystals (CRCo) in periradicular granulomas of endodontic origin and the type of reaction they produce in the surround- ing tissues. Material and methods: 75 archival histological preparations were studied with optical microscopy. They be- longed to human periradicular lesions corresponding to teeth that had received a previous endodontic treatment and that, according to the reports accompanying the samples, had been obtained by an apicoectomy. Of the total, 68 samples were diagnosed as granulomas, while the remaining 7 were diag- nosed as inflammatory cysts and were discarded. Results: 39 granulomas corresponded to female patients in which the presence of CRCo was observed in 58.97% of the cases. The remaining 29 granulomas were from male patients and showed CRCo in 41.37% of the cases. The highest pro- portion of CRCo was found in patients over 62 years of age. The CRCo were surrounded by macrophages and multinucle- ated giant cells causing a foreign body reaction. Foam cells were also observed in the surrounding areas. Conclusions: The presence of CRCo in periradicular granulomas of endodontic origin could be a factor interfering with periapical healing after conventional endodontic thera- py, especially in elderly patients (AU)

Mixed methodology in human brain research: integrating MRI and histology.

Postmortem magnetic resonance imaging (MRI) can provide a bridge between histological observations and the in vivo anatomy of the human brain. Approaches aimed at the co-registration of data derived from the two techniques are gaining interest. Optimal integration of the two research fields requires detailed knowledge of the tissue property requirements for individual research techniques, as well as a detailed understanding of the consequences of tissue fixation steps on the imaging quality outcomes for both MRI and histology. Here, we provide an overview of existing studies that bridge between state-of-the-art imaging modalities, and discuss the background knowledge incorporated into the design, execution and interpretation of postmortem studies. A subset of the discussed challenges transfer to animal studies as well. This insight can contribute to furthering our understanding of the normal and diseased human brain, and to facilitate discussions between researchers from the individual disciplines.

Qualitative Histologic Assessment vs. Geomorphometric Analysis of Nerve Fiber Shape after the Intraneural Application of Liposomal Bupivacaine / Evaluación Histológica Cualitativa Versus Análisis Geomorfométrico de la Forma de la Fibra Nerviosa Después de la Aplicación Intraneural de Bupivacaína Liposomal

SUMMARY: The preserved form of all components of the nerve fiber is a prerequisite for the proper conduction of the nerve impulse. various factors can change the shape of nerve fibers. In everyday practice, qualitative histological analysis is the gold standard for detecting changes in shape. Geometric morphometry is an innovative method that objectively enables the assessment of changes in nerve fibers' shape after local anesthetics action. A total of sixty sciatic nerves were used as material, which was intraneural injected with saline solution in the control group (n=30), and a solution of 1.33 % liposomal bupivacaine (n=30) in the test group. After the animals were sacrificed, nerve samples were taken and histological preparations were made. The preparations were first described and examined using a qualitative histological method, after which digital images were made. The images were entered into the MorphoJ program and processed using the method of geometric morphometry. Qualitative histological examination revealed no differences in nerve fibers after intraneurally applied physiological solution and liposomal bupivacaine. Using the method of geometric morphometry, a statistically significant change in the shape of axons was found after intraneurally applied saline solution and liposomal bupivacaine (p=0.0059). No significant differences in histological changes were found after the qualitative histological analysis of nerve fiber cross-section preparations. A statistically significant change in the shape of nerve fiber axons was observed after geometric morphometric analysis of digital images after intraneural application of saline and liposomal bupivacaine.

La forma conservada de todos los componentes de la fibra nerviosa es un requisito previo para la conducción correcta del impulso nervioso. Varios factores pueden cambiar la forma de las fibras nerviosas. En la práctica diaria, el análisis histológico cualitativo es el estándar de oro para detectar cambios de forma. La morfometría geométrica es un método innovador que permite evaluar objetivamente los cambios en la forma de las fibras nerviosas después de la acción de los anestésicos locales. Se utilizó como material un total de sesenta nervios ciáticos, que se inyectaron intraneuralmente con solución salina en el grupo control (n=30), y una solución de bupivacaína liposomal al 1,33 % (n=30) en el grupo de prueba. Después de sacrificados los animales, se tomaron muestras de nervios y se realizaron preparaciones histológicas. Primero se describieron y examinaron las preparaciones utilizando un método histológico cualitativo, después de lo cual se tomaron imágenes digitales. Las imágenes fueron ingresadas al programa MorphoJ y procesadas mediante el método de morfometría geométrica. El examen histológico cualitativo no reveló diferencias en las fibras nerviosas después de la aplicación intraneural de solución fisiológica y bupivacaína liposomal. Usando el método de morfometría geométrica, se encontró un cambio estadísticamente significativo en la forma de los axones después de la aplicación intraneural de solución salina y bupivacaína liposomal (p = 0,0059). No se encontraron diferencias significativas en los cambios histológicos después del análisis histológico cualitativo de las preparaciones de secciones transversales de fibras nerviosas. Se observó un cambio estadísticamente significativo en la forma de los axones de las fibras nerviosas después del análisis de morfometría geométrica de imágenes digitales después de la aplicación intraneural de solución salina y bupivacaína liposomal.

Methods to expose subsurface objects of interest identified from 3D imaging: The intermediate sample preparation stage in the correlative microscopy workflow.

The correlative imaging workflow is a method of combining information and data across modes (e.g. SEM, X-ray CT, FIB-SEM), scales (cm to nm) and dimensions (2D-3D-4D), providing a more holistic interpretation of the research question. Often, subsurface objects of interest (e.g. inclusions, pores, cracks, defects in multilayered samples) are identified from initial exploratory nondestructive 3D tomographic imaging (e.g. X-ray CT, XRM), and those objects need to be studied using additional techniques to obtain, for example, 2D chemical or crystallographic data. Consequently, an intermediate sample preparation step needs to be completed, where a targeted amount of sample surface material is removed, exposing and revealing the object of interest. At present, there is not one singular technique for removing varied thicknesses at high resolution and on a range of scales from cm to nm. Here, we review the manual and automated options currently available for targeted sample material removal, with a focus on those methods which are readily accessible in most laboratories. We summarise the approaches for manual grinding and polishing, automated grinding and polishing, microtome/ultramicrotome, and broad-beam ion milling (BBIM), with further review of other more specialist techniques including serial block face electron microscopy (SBF-SEM), and ion milling and laser approaches such as FIB-SEM, Xe plasma FIB-SEM, and femtosecond laser/LaserFIB. We also address factors which may influence the decision on a particular technique, including the composition, shape and size of the samples, sample mounting limitations, the amount of surface material to be removed, the accuracy and/or resolution of peripheral parts, the accuracy and/or resolution of the technique/instrumentation, and other more general factors such as accessibility to instrumentation, costs, and the time taken for experimentation. It is hoped that this study will provide researchers with a range of options for removal of specific amounts of sample surface material to reach subsurface objects of interest in both correlative and non-correlative workflows.

Tensor image registration library: Deformable registration of stand-alone histology images to whole-brain post-mortem MRI data.

BACKGROUND: Accurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data. METHODS: Our pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. RESULTS: All 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. CONCLUSIONS: Our open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.

Multi-Scale Investigation of Human Renal Tissue in Three Dimensions.

Histopathology as a diagnostic mainstay for tissue evaluation is strictly a 2D technology. Combining and supplementing this technology with 3D imaging has been proposed as one future avenue towards refining comprehensive tissue analysis. To this end, we have developed a laboratory-based X-ray method allowing for the investigation of tissue samples in three dimensions with isotropic volume information. To assess the potential of our method for micro-morphology evaluation, we selected several kidney regions from three patients with cystic kidney disease, obstructive nephropathy and diabetic glomerulopathy. Tissue specimens were processed using our in-house-developed X-ray eosin stain and investigated with a commercial microCT and our in-house-built NanoCT. The microCT system provided overview scans with voxel sizes of [Formula: see text] and the NanoCT was employed for higher resolutions including voxel sizes from [Formula: see text] to 210 nm. We present a methodology allowing for a precise micro-morphologic investigation in three dimensions which is compatible with conventional histology. Advantages of our methodology are its versatility with respect to multi-scale investigations, being laboratory-based, allowing for non-destructive imaging and providing isotropic volume information. We believe, that after future developmental work this method might contribute to advanced multi-modal tissue diagnostics.

Presencia de lesiones quísticas en sacos pericoronarios de terceros molares mandibulares / Presence of cystic lesions in pericoronary sacs of mandibular third molars

Introducción: a pesar de que un tercer molar no erupcionado repre- senta un riesgo de formación quística, la práctica clínica desestima el análisis histopatológico de los folículos de dichos molares. Objetivo: identificar la frecuencia de lesiones quísticas en los sacos pericoronarios de terceros molares mandibulares. Material y métodos: estudio des- criptivo, transversal, analítico y observacional, en donde se incluyeron sacos pericoronarios de terceros molares mandibulares para su análisis histopatológico, descripción de características clínico-radiográficas y su asociación con la presencia de cambios histológicos o lesiones quís- ticas. Resultados: se incluyeron 48 muestras de sacos pericoronarios, la histopatología de los sacos pericoronarios mostró que 83.3% tenían algún tipo de alteración: 13 quistes paradentales (27.1%), cuatro quistes dentígeros (8.3%), 12 folículos hiperplásicos (25.0%) y 11 folículos inflamados (22.9%). La presencia de lesiones quísticas en la población fue de 35.4%. Se detectó asociación estadísticamente significativa entre el sexo y la presencia de lesiones quísticas (p = 0.039) y entre el nivel de erupción y la presencia de cambios histológicos (p = 0.046). Con- clusiones: la frecuencia de lesiones quísticas o cambios histológicos en folículos de terceros molares mandibulares es alta, principalmente en molares parcialmente erupcionados o submucosos y sin importar la ausencia de sintomatología o alteraciones radiográficas (AU))

Introduction: although a non-erupted third molar represents a risk of cystic formation; clinical practice rejects the histopathological analysis of the follicles of said molars. Objective: identify the frequency of the histopathological changes in pericoronary sacs of mandibular third molars. Material and methods: descriptive cross- sectional, observational and analytic study, where pericoronary sacs of mandibular third molars were included for histopathological analysis, description of clinical-radiographic characteristics and their association with the presence of histological changes or cystic lesions. Results: 48 samples of pericoronary sacs were included, the histopathology of the pericoronary sacs showed 83.3% had some type of alteration: 13 paradental cysts (27.1%), four dentigerous cysts (8.3%), 12 hyperplastic follicles (25.0%) and 11 inflamed follicles (22.9%). The presence of cystic lesions in the population was 35.4%. A statistically significant association was detected between sex and the presence of cystic lesions (p = 0.039); and between the level of eruption and the presence of histological changes (p = 0.046). Conclusions: the frequency of cystic lesions or histological changes in mandibular third molar follicles is high, mainly in partially erupted or submucosal molars and regardless of the absence of symptoms or radiographic alterations (AU)

Protocol to image and analyze the morphology of mouse peripheral nerves using transmission electron microscopy.

Morphological analysis of peripheral nerves in mouse models can be used to characterize the pathophysiology of peripheral nerve disease, but obtaining high-quality electron micrographs can be challenging. Here, we present a protocol to obtain electron micrographs of mouse peripheral nerves. We detail the procedures of sampling, fixation, and embedding of peripheral nerves. We then outline the steps for ultrathin sectioning and transmission electron microscopy imaging. Finally, we describe morphological evaluation of nerve fibers in these images using ImageJ and AxonSeg. For complete details on the use and execution of this protocol, please refer to Nakai-Shimoda et al. (2021).

Definition of a sectioning plane and place for a section containing hoped-for regions using a spare counterpart specimen.

Histological examination of targets in regions of interest in histological sections is one of the most frequently used tools in biomedical research. However, it is a technical challenge to secure a multitarget section for inspection of the structure's mutual relationship of targets or a longitudinally filamentous- or tubular-formed tissue section for visitation of the overall morphological features. We present a method with a specified cutting plane and place, allowing researchers to cut directly at the multitarget centers accurately and quickly. The method is proven to be reliable with high accuracy and reproducibility and a low coefficient of variation, testing on repeat experiments of three target's position-known models. With this method, we successfully yielded single sections containing whole intraorbital optical nerves, three aortic valves, or whole thoracic tracheas in their central positions. The adjoined custom-made tools used in the study, such as various tissue-specific formulated calibrated trimming and embedding guides, an organ-shaped cavity plaster mold, and a two-time embedding technique for optimal and identical trimming or embedding, also bear great potential to become a common supplemental tool for traditional histology and may contribute to the reduction of the labor, and the number of animals needed.

Quantitative Neuroanatomical Phenotyping of the Embryonic Mouse Brain.

Congenital neurodevelopmental anomalies are present from birth and are characterized by an abnormal development of one or more structures of the brain. Brain structural anomalies are highly comorbid with neurodevelopmental and neuropsychiatric disorders such as intellectual disability, autism spectrum disorders, epilepsy, and schizophrenia, and 80% are of genetic origin. We aim to address an important neurobiological question: How many genes regulate the normal anatomy of the brain during development. To do so, we developed a quantitative approach for the assessment of a total of 106 neuroanatomical parameters in mouse mutant embryos at embryonic day 18.5 across two planes commonly used in brain anatomical studies, the coronal and sagittal planes. In this article we describe the techniques we developed and explain why ultrastandardized procedures involving embryonic mouse brains are even more of prime importance for morphological phenotyping than adult mouse brains. We focus our analysis on brain size anomalies and on the most frequently altered brain regions including the cortex, corpus callosum, hippocampus, ventricles, caudate putamen, and cerebellum. Our protocols allow a standardized histology pipeline from embryonic mouse brain preparation to sectioning, staining, and scanning and neuroanatomical analyses at well-defined positions on the coronal and sagittal planes. Together, our protocols will help scientists in deciphering congenital neurodevelopmental anomalies and anatomical changes between groups of mouse embryos in health and genetic diseases. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Fixation and preparation of embryonic mouse brain samples Basic Protocol 2: Sectioning, staining, and scanning of embryonic mouse brain sections Basic Protocol 3: Coronal neuroanatomical measurements of embryonic mouse brain structures Basic Protocol 4: Sagittal neuroanatomical measurements of embryonic mouse brain structures.

A combination of scanning electron microscopy and broad argon ion beam milling provides intact structure of secondary tissues in woody plants.

The secondary tissues of woody plants consist of fragile cells and rigid cell walls. However, the structures are easily damaged during mechanical cross-sectioning for electron microscopy analysis. Broad argon ion beam (BIB) milling is commonly employed for scanning electron microscopy (SEM) of hard materials to generate a large and distortion-free cross-section. However, BIB milling has rarely been used in plant science. In the present study, SEM combined with BIB milling was validated as an accurate tool for structural observation of secondary woody tissues of two samples, living pine (Pinus densiflora) and high-density oak wood (Quercus phillyraeoides), and compared with classical microtome cross-sectioning. The BIB milling method does not require epoxy resin embedding because of prior chemical fixation and critical point drying of the sample, thus producing a three-dimensional image. The results showed that xylem structures were well-preserved in their natural state in the BIB-milled cross-section compared with the microtome cross-section. The observations using SEM combined with BIB milling were useful for wide-area imaging of both hard and soft plant tissues, which are difficult to observe with transmitted electron microscopy because it is difficult to obtain sections of such tissues, particularly those of fragile reaction woods.

Whole-mount immunofluorescent labeling of the adult fly retina.

The adult Drosophila compound eye is an ideal in vivo model for studying biological questions. However, light microscopy of this tissue requires cumbersome embedding and sectioning. Here, we document detailed whole-mount procedures for immunolabeling the adult retina, enabling high-quality studies of fluorescent-tagged targets with straightforward preparations. We describe the steps for visualizing the nuclear lamina, membrane-associated protein, and actin-rich rhabdomere, but this robust protocol can apply to other cellular structures and target proteins. For complete details on the use and execution of this protocol, please refer to Chang et al. (2021).

Histological analysis of an alkaline based tissue clearing technique for fetal musculoskeletal tissue / Análisis histológico de una técnica de limpieza de tejido de base alcalina para tejido musculoesquelético fetal

SUMMARY: Tissue clearing techniques are frequently used in the observation and description of anatomical structures and pathways without altering the three-dimensional layout of the anatomical specimen. Tissue optical clearing promotes preservation of three-dimensional structures, which allows the study of the internal anatomy in its original position and original spatial interaction. Among these techniques, Potassium Hydroxide (KOH) maceration clearing is one of the most widely used. However, the histological changes of tissue after KOH maceration have yet to be fully understood. Our aim is to describe the microscopical differences between macerated and normal tissue. To better understand said changes, two human fetuses with a gestation period of 16 to 28 weeks were cleared and processed for histological analysis. Microtome slides of the fetuses' lower limbs were obtained and stained with Hematoxylin & Eosin, Periodic Acid Schiff (PAS), and Masson's trichrome with the purpose of observing the histological and macromolecule composition changes in cleared tissue. Remarkable differences at a histological level regarding the composition of the cellular structures, since diaphanized tissues showed a predominance of extracellular matrix composed of collagen fibers with the absence of most of the nucleated cellular tissue. Phospholipid's saponification, nucleic acids degradation and a change on proteins structural properties are the main factors inducing clearing. At the same time, molecular stability of collagen in alkaline conditions allows the specimen to maintain its shape after the process.

RESUMEN: Las técnicas de limpieza de tejido se utilizan con frecuencia en la observación y descripción de estructuras y vías anatómicas sin alterar el diseño tridimensional de la muestra anatómica. El aclaramiento óptico de tejidos promueve la preservación de estructuras tridimensionales, lo que permite el estudio de la anatomía interna en su posición original y la interacción espacial original. Entre estas técnicas, el aclarado por maceración con Hidróxido de Potasio (KOH) es una de las más utilizadas. Sin embargo, los cambios histológicos del tejido después de la maceración con KOH aún no se han entendido por completo. Nuestro objetivo es describir las diferencias microscópicas entre el tejido macerado y el normal. Para entender mejor dichos cambios, dos fetos humanos con un período de gestación de 16 a 28 semanas fueron aclarados y procesados para análisis histológicos. Se obtuvieron microtomos de las extremidades inferiores de los fetos y se tiñeron con hematoxilina y eosina, ácido peryódico de Schiff (PAS) y tricrómico de Masson con el fin de observar los cambios histológicos y de composición de macromoléculas en el tejido aclarado. Diferencias notables a nivel histológico en cuanto a la composición de las estructuras celulares, ya que los tejidos diafanizados mostraban un predominio de matriz extracelular compuesta por fibras de colágeno con ausencia de la mayor parte del tejido celular nucleado. La saponificación de los fosfolípidos, la degradación de los ácidos nucleicos y un cambio en las propiedades estructurales de las proteínas son los principales factores que inducen la depuración. Al mismo tiempo, la estabilidad molecular del colágeno en condiciones alcalinas permite que la muestra mantenga su forma después del proceso.

SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology Images.

Automated nuclei segmentation and classification are the keys to analyze and understand the cellular characteristics and functionality, supporting computer-aided digital pathology in disease diagnosis. However, the task still remains challenging due to the intrinsic variations in size, intensity, and morphology of different types of nuclei. Herein, we propose a self-guided ordinal regression neural network for simultaneous nuclear segmentation and classification that can exploit the intrinsic characteristics of nuclei and focus on highly uncertain areas during training. The proposed network formulates nuclei segmentation as an ordinal regression learning by introducing a distance decreasing discretization strategy, which stratifies nuclei in a way that inner regions forming a regular shape of nuclei are separated from outer regions forming an irregular shape. It also adopts a self-guided training strategy to adaptively adjust the weights associated with nuclear pixels, depending on the difficulty of the pixels that is assessed by the network itself. To evaluate the performance of the proposed network, we employ large-scale multi-tissue datasets with 276349 exhaustively annotated nuclei. We show that the proposed network achieves the state-of-the-art performance in both nuclei segmentation and classification in comparison to several methods that are recently developed for segmentation and/or classification.

Artificial double inversion recovery images can substitute conventionally acquired images: an MRI-histology study.

Cortical multiple sclerosis lesions are disease-specific, yet inconspicuous on magnetic resonance images (MRI). Double inversion recovery (DIR) images are sensitive, but often unavailable in clinical routine and clinical trials. Artificially generated images can mitigate this issue, but lack histopathological validation. In this work, artificial DIR images were generated from postmortem 3D-T1 and proton-density (PD)/T2 or 3D-T1 and 3D fluid-inversion recovery (FLAIR) images, using a generative adversarial network. All sequences were scored for cortical lesions, blinded to histopathology. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesions type I-IV (leukocortical, intracortical, subpial and cortex-spanning, respectively). Histopathological scorings were then (unblinded) compared to MRI using linear mixed models. Images from 38 patients (26 female, mean age 64.3 ± 10.7) were included. A total of 142 cortical lesions were detected, predominantly subpial. Histopathology-blinded/unblinded sensitivity was 13.4/35.2% for artificial DIR generated from T1-PD/T2, 14.1/41.5% for artificial DIR from T1-FLAIR, 17.6/49.3% for conventional DIR and 10.6/34.5% for 3D-T1. When blinded to histopathology, there were no differences; with histopathological feedback at hand, conventional DIR and artificial DIR from T1-FLAIR outperformed the other sequences. Differences between histopathology-blinded/unblinded sensitivity could be minified through adjustment of the scoring criteria. In conclusion, artificial DIR images, particularly generated from T1-FLAIR could potentially substitute conventional DIR images when these are unavailable.