Retrospective validation of MetaSystems' deep-learning-based digital microscopy platform with assistance compared to manual fluorescence microscopy for detection of mycobacteria.

This study aimed to validate Metasystems' automated acid-fast bacilli (AFB) smear microscopy scanning and deep-learning-based image analysis module (Neon Metafer) with assistance on respiratory and pleural samples, compared to conventional manual fluorescence microscopy (MM). Analytical parameters were assessed first, followed by a retrospective validation study. In all, 320 archived auramine-O-stained slides selected non-consecutively [85 originally reported as AFB-smear-positive, 235 AFB-smear-negative slides; with an overall mycobacterial culture positivity rate of 24.1% (77/320)] underwent whole-slide imaging and were analyzed by the Metafer Neon AFB Module (version 4.3.130) using a predetermined probability threshold (PT) for AFB detection of 96%. Digital slides were then examined by a trained reviewer blinded to previous AFB smear and culture results, for the final interpretation of assisted digital microscopy (a-DM). Paired results from both microscopic methods were compared to mycobacterial culture. A scanning failure rate of 10.6% (34/320) was observed, leaving 286 slides for analysis. After discrepant analysis, concordance, positive and negative agreements were 95.5% (95%CI, 92.4%-97.6%), 96.2% (95%CI, 89.2%-99.2%), and 95.2% (95%CI, 91.3%-97.7%), respectively. Using mycobacterial culture as reference standard, a-DM and MM had comparable sensitivities: 90.7% (95%CI, 81.7%-96.2%) versus 92.0% (95%CI, 83.4%-97.0%) (P-value = 1.00); while their specificities differed 91.9% (95%CI, 87.4%-95.2%) versus 95.7% (95%CI, 92.1%-98.0%), respectively (P-value = 0.03). Using a PT of 96%, MetaSystems' platform shows acceptable performance. With a national laboratory staff shortage and a local low mycobacterial infection rate, this instrument when combined with culture, can reliably triage-negative AFB-smear respiratory slides and identify positive slides requiring manual confirmation and semi-quantification. IMPORTANCE: This manuscript presents a full validation of MetaSystems' automated acid-fast bacilli (AFB) smear microscopy scanning and deep-learning-based image analysis module using a probability threshold of 96% including accuracy, precision studies, and evaluation of limit of AFB detection on respiratory samples when the technology is used with assistance. This study is complementary to the conversation started by Tomasello et al. on the use of image analysis artificial intelligence software in routine mycobacterial diagnostic activities within the context of high-throughput laboratories with low incidence of tuberculosis.

Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.

Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.

Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning.

BACKGROUND: Microscopic examination of Giemsa-stained blood films remains the reference standard for malaria parasite detection and quantification, but is undermined by difficulties in ensuring high-quality manual reading and inter-reader reliability. Automated parasite detection and quantification may address this issue. METHODS: A multi-centre, observational study was conducted during 2018 and 2019 at 11 sites to assess the performance of the EasyScan Go, a microscopy device employing machine-learning-based image analysis. Sensitivity, specificity, accuracy of species detection and parasite density estimation were assessed with expert microscopy as the reference. Intra- and inter-device reliability of the device was also evaluated by comparing results from repeat reads on the same and two different devices. This study has been reported in accordance with the Standards for Reporting Diagnostic accuracy studies (STARD) checklist. RESULTS: In total, 2250 Giemsa-stained blood films were prepared and read independently by expert microscopists and the EasyScan Go device. The diagnostic sensitivity of EasyScan Go was 91.1% (95% CI 88.9-92.7), and specificity 75.6% (95% CI 73.1-78.0). With good quality slides sensitivity was similar (89.1%, 95%CI 86.2-91.5), but specificity increased to 85.1% (95%CI 82.6-87.4). Sensitivity increased with parasitaemia rising from 57% at < 200 parasite/µL, to ≥ 90% at > 200-200,000 parasite/µL. Species were identified accurately in 93% of Plasmodium falciparum samples (kappa = 0.76, 95% CI 0.69-0.83), and in 92% of Plasmodium vivax samples (kappa = 0.73, 95% CI 0.66-0.80). Parasite density estimates by the EasyScan Go were within ± 25% of the microscopic reference counts in 23% of slides. CONCLUSIONS: The performance of the EasyScan Go in parasite detection and species identification accuracy fulfil WHO-TDR Research Malaria Microscopy competence level 2 criteria. In terms of parasite quantification and false positive rate, it meets the level 4 WHO-TDR Research Malaria Microscopy criteria. All performance parameters were significantly affected by slide quality. Further software improvement is required to improve sensitivity at low parasitaemia and parasite density estimations. Trial registration ClinicalTrials.gov number NCT03512678.

Testing Precision Limits of Neural Network-Based Quality Control Metrics in High-Throughput Digital Microscopy.

OBJECTIVE: Digital microscopy is used to monitor particulates such as protein aggregates within biopharmaceutical products. The images that result encode a wealth of information that is underutilized in pharmaceutical process monitoring. For example, images of particles in protein drug products typically are analyzed only to obtain particle counts and size distributions, even though the images also reflect particle characteristics such as shape and refractive index. Multiple groups have demonstrated that convolutional neural networks (CNNs) can extract information from images of protein aggregates allowing assignment of the likely stress at the "root-cause" of aggregation. A practical limitation of previous CNN-based approaches is that the potential aggregation-inducing stresses must be known a priori, disallowing identification of particles produced by unknown stresses. METHODS: We demonstrate an expanded CNN analysis of flow imaging microscopy (FIM) images incorporating judiciously chosen particle standards within a recently proposed "fingerprinting algorithm" (Biotechnol. & Bioeng. (2020) 117:3322) that allows detection of particles formed by unknown root-causes. We focus on ethylene tetrafluoroethylene (ETFE) microparticles as standard surrogates for protein aggregates. We quantify the sensitivity of the new algorithm to experimental parameters such as microscope focus and solution refractive index changes, and explore how FIM sample noise affects statistical testing procedures. RESULTS & CONCLUSIONS: Applied to real-world microscopy images of protein aggregates, the algorithm reproducibly detects complex, distinguishing "textural features" of particles that are not easily described by standard morphological measurements. This offers promise for quality control applications and for detecting shifts in protein aggregate populations due to stresses resulting from unknown process upsets.

Validation of digital microscopy: Review of validation methods and sources of bias.

Digital microscopy (DM) is increasingly replacing traditional light microscopy (LM) for performing routine diagnostic and research work in human and veterinary pathology. The DM workflow encompasses specimen preparation, whole-slide image acquisition, slide retrieval, and the workstation, each of which has the potential (depending on the technical parameters) to introduce limitations and artifacts into microscopic examination by pathologists. Performing validation studies according to guidelines established in human pathology ensures that the best-practice approaches for patient care are not deteriorated by implementing DM. Whereas current publications on validation studies suggest an overall high reliability of DM, each laboratory is encouraged to perform an individual validation study to ensure that the DM workflow performs as expected in the respective clinical or research environment. With the exception of validation guidelines developed by the College of American Pathologists in 2013 and its update in 2021, there is no current review of the application of methods fundamental to validation. We highlight that there is high methodological variation between published validation studies, each having advantages and limitations. The diagnostic concordance rate between DM and LM is the most relevant outcome measure, which is influenced (regardless of the viewing modality used) by different sources of bias including complexity of the cases examined, diagnostic experience of the study pathologists, and case recall. Here, we review 3 general study designs used for previous publications on DM validation as well as different approaches for avoiding bias.

Investigation of the efficiency and stability of a novel visualized lattice CO2 laser-based gynecological therapeutic apparatus for the treatment of cervical diseases in rhesus monkeys.

The fractional CO2 laser is a type of ablative laser. In this study, a novel fractional CO2 laser therapeutic apparatus was developed for cervical diseases. To compare the depth and diameter of penetration as well as the stability of a novel laser against a control laser emitting at the same wavelength, we tested this using a rhesus monkey model. The cervixes of rhesus monkeys were irradiated with the novel CO2 laser. The effects of irradiation were assessed by measuring the depths and diameters of the holes created by the laser. In addition, the depths and diameters of the holes were compared between the novel CO2 laser-based gynecological therapeutic apparatus and the conventional CO2 laser-based therapeutic apparatus. When operated under the single spot mode and at the same energy level, the novel CO2 laser-based gynecological therapeutic apparatus created holes that could reach the greater depth. In addition, the laser spot size of the new apparatus was more constant. Moreover, there were no significant differences in the side effects between the new apparatus and the conventional apparatus. The results indicate that the novel CO2 laser-based gynecological therapeutic apparatus exhibits better stability in comparison to the conventional CO2 laser-based therapeutic apparatus.

Longitudinal craze line propagation in human root dentin after instrumentation with NiTi rotary files of different instrument tapers after long-term chewing simulation.

OBJECTIVES: The aim of this study was to investigate whether file design and taper significantly influence microcrack initiation during machine preparation. MATERIALS AND METHODS: Sixty extracted teeth with straight single canals were selected. The teeth were randomly assigned to four groups based on their root canal anatomy and the corresponding NiTi rotary file system (I, Mtwo; II, ProTaper Universal; III, F6 SkyTaper; control, no preparation and filling). The root canals of the experimental groups were filled using the single-cone technique. The tested teeth were all subjected to a mechanical chewing simulation with flat lead loading over a period of 3 years (corresponding to 150,000 cycles). The teeth were checked for dentinal defects (accumulative crack growth in length) under the digital microscope (Keyence VHX-5000) at time 0 (baseline prior to chewing simulation) and after 3, 6, 12, 24, and 36 months of loading. The cumulative crack increase was statistically analyzed using the Kruskal-Wallis test, Jonckheere-Terpstra test, and the Wilcoxon rank-sum test. The significance was set at p < 0.05. RESULTS: In contrast to preparation with greater-tapered instruments, ProTaper Universal (group II) and F6 SkyTaper (group III) instrumentation with the smaller tapered Mtwo files (group I) showed less accumulative propagation of craze lines (p < 0.05) at all time points. CONCLUSION: Instruments with greater taper for root canal instrumentation should be used with care to avoid negative long-term effects in the form of propagation of dentinal defects over time. A positive cutting-edge angle and a smaller taper have a positive effect on a lower craze line development. CLINICAL RELEVANCE: Instruments with a positive cutting-edge angle and a smaller taper are beneficial for the long-term preservation of dentinal tooth structure.

Digital 3D Topographic Microscopy: Bridging the Gaps Between Macroscopy, Microscopy and Scanning Electron Microscopy.

Re-endothelialization of vascular lumen after endovascular procedures is a critical healing milestone and is subjected to routine pathological evaluation during preclinical safety assessment of new cardiovascular devices. Gross evaluation, microscopic evaluation, and scanning electron microscopy (SEM) are the methods of choice for evaluation of vascular surfaces. In this article, we present a new digital imaging approach of surface topography herein referred to as topographical digital microscopy (TDM) that is able to meet the objectives of endovascular healing assessment in a single instrumental platform combined with the same sample preparation techniques as for histology or SEM. This platform is taking advantage of digitally managed illumination, X-Y stitching, and Z-stacking to enable direct optical imaging of tissue surfaces at levels of details ranging from the macroscopic to the cellular level. This technique is enabled by advances in digital optical microscopy and provides images in color and 3 dimensions that can help in the analysis, especially in distinguishing biologically meaningful observations from technical preparation artifacts and in visualizing surface topography.

Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network.

Intestinal protozoa are responsible for relatively few infections in the developed world, but the testing volume is disproportionately high. Manual light microscopy of stool remains the gold standard but can be insensitive, time-consuming, and difficult to maintain competency. Artificial intelligence and digital slide scanning show promise for revolutionizing the clinical parasitology laboratory by augmenting the detection of parasites and slide interpretation using a convolutional neural network (CNN) model. The goal of this study was to develop a sensitive model that could screen out negative trichrome slides, while flagging potential parasites for manual confirmation. Conventional protozoa were trained as "classes" in a deep CNN. Between 1,394 and 23,566 exemplars per class were used for training, based on specimen availability, from a minimum of 10 unique slides per class. Scanning was performed using a 40× dry lens objective automated slide scanner. Data labeling was performed using a proprietary Web interface. Clinical validation of the model was performed using 10 unique positive slides per class and 125 negative slides. Accuracy was calculated as slide-level agreement (e.g., parasite present or absent) with microscopy. Positive agreement was 98.88% (95% confidence interval [CI], 93.76% to 99.98%), and negative agreement was 98.11% (95% CI, 93.35% to 99.77%). The model showed excellent reproducibility using slides containing multiple classes, a single class, or no parasites. The limit of detection of the model and scanner using serially diluted stool was 5-fold more sensitive than manual examinations by multiple parasitologists using 4 unique slide sets. Digital slide scanning and a CNN model are robust tools for augmenting the conventional detection of intestinal protozoa.

Automatic Fiber Length Measurements with a Multi-Stencil Fast Marching Method on Microscopy Images.

Fiber length has a strong impact on the mechanical properties of composite materials. It is one of the most important quantitative features in characterizing microstructures for understanding the material performance. Studies conducted to determine fiber length distribution have primarily focused on sample preparation and fiber dispersion. However, the subsequent image analysis is frequently performed manually or semi-automatically, which either requires careful sample preparation or manual intervention in the image analysis and processing. In this article, an image processing and analysis method has been developed based on medial axis transformation via the multi-stencil fast marching method for fiber length measurements on acquired microscopy images. The developed method can be implemented fully automatically and without any user induced delays. This method offers high efficiency, sub-pixel accuracy, and excellent statistical representativity.

Application of reflectance confocal microscopy to investigate the non-ablative, micro-ablative, and ablative effects of CO2 fractional laser irradiation on skin.

CO2 fractional laser, as an ablative fractional laser, is commonly used in cosmetic treatment. We applied CO2 fractional laser irradiation to skin in vitro and used reflectance confocal microscopy (RCM) to image and detect the presence of any non-ablative, micro-ablative and ablative effects, in order to better understand the features of a CO2 fractional laser. In vitro irradiation of foreskin was performed using a CO2 fractional laser. Foreskin specimens were divided into 4 groups that received different amounts of irradiation energy, based on the number of irradiation passes they received: 5, 10, 15, and 20 passes, respectively. This corresponds to fluence energy of 16.3, 32.6, 48.9, 65.3 J/cm2. Immediately after irradiation, digital microscopy (DM), RCM, and histopathology were performed to observe whether the non-ablative, micro-ablative, and ablative phenomenon occurred, and the injury features of MTZs. Immediately after CO2 fractional laser irradiation, RCM and DM showed that when the numbers of passes were 5 and 10, a micro-ablative column (MAC) could not be observed or was very small. We mainly observed a thicker thermal coagulation zone (TCZ), representing non-ablative or micro-ablative effects. When the number of passes were increased to 15 and 20, the MAC was significantly enlarged and surrounded by a TCZ of medium thickness, representing ablative effects. For the first time, this study used RCM and DM to demonstrate that a CO2 fractional laser could achieve non-ablative, micro-ablative, and ablative effects on irradiated skin via different energy levels.

Virtual Microscopy Is More Effective Than Conventional Microscopy for Teaching Cytology to Veterinary Students: A Randomized Controlled Trial.

Virtual microscopy (VM) using scanned slides and imaging software is increasingly used in medical curricula alongside instruction in conventional microscopy (CM). Limited reports suggest that VM is useful in the veterinary education setting, and generally well-received by students. Whether students can apply knowledge gained through VM to practical use is unknown. Our objective was to determine whether instruction using VM, compared to CM, is a successful method of training veterinary students for the application of cytology in practice (i.e., using light microscopes). Seventy-one veterinary students from Colorado State University who attended a voluntary 3-hour cytology workshop were randomized to receive the same instruction with either VM (n = 35) or CM (n = 36). We compared these students to a control group (n = 22) of students who did not attend a workshop. All students took a post-workshop assessment involving the interpretation of four cases on glass slides with CM, designed to simulate the use of cytology in general practice. Students also took an 18-question survey related to the effectiveness of the workshop, providing their opinions on cytology instruction in the curriculum and their learning preference (VM or CM). The mean assessment score of the VM group (14.18 points) was significantly higher than the control group (11.33 points, p = .003), whereas the mean of the CM group (12.77 points) was not statistically significantly different from controls (p = .170). Not only is VM an effective method of teaching cytology to veterinary students that can be translated to a real-world case scenario, but it outperformed CM instruction in this study.

A three-dimensional digital microscopic investigation of entheseal changes as skeletal activity markers.

OBJECTIVES: The current article explores the effectiveness of entheseal changes (EC) as skeletal activity markers by testing the correlation between such changes and cross-sectional geometric (CSG) properties while controlling for the effect of age and body size. MATERIALS AND METHODS: The originality of the article lies in capturing EC in a continuous quantitative manner using three-dimensional microscopy. Roughness and bone resorption were recorded on Zones 1 and 2 of three humeral entheses (subscapularis, supraspinatus, and infraspinatus) in a documented sample of 29 male skeletons. RESULTS: Our analysis found that merely 5.91% of the partial correlations between EC and CSG properties were statistically significant. In addition, two unexpected patterns were identified, namely a higher number of significant correlations on the left side entheses compared to the right side ones, and a higher number of correlations between minimum roughness and CSG properties compared to mean and maximum roughness. DISCUSSION: These patterns are the inverse of what we would expect if activity had exerted an important effect on EC expression. Therefore, they support the lack of association between EC and habitual activity, even though various factors potentially affecting the above results are discussed.

Evaluation of Region of Interest Digital Cytology Compared to Light Microscopy for Veterinary Medicine.

Digital microscopy (DM) has been employed for primary diagnosis in human medicine and for research and teaching applications in veterinary medicine, but there are few veterinary DM validation studies. Region of interest (ROI) digital cytology is a subset of DM that uses image-stitching software to create a low-magnification image of a slide, then selected ROI at higher magnification, and stitches the images into a relatively small file of the embedded magnifications. This study evaluated the concordance of ROI-DM compared to traditional light microscopy (LM) between 2 blinded clinical pathologists. Sixty canine and feline cytology samples from a variety of anatomic sites, including 31 cases of malignant neoplasia, 15 cases of hyperplastic or benign neoplastic lesions, and 14 infectious/inflammatory lesions, were evaluated. Two separate nonblinded adjudicating clinical pathologists evaluated the reports and diagnoses and scored each paired case as fully concordant, partially concordant, or discordant. The average overall concordance (full and partial concordance) for both pathologists was 92%. Full concordance was significantly higher for malignant lesions than benign. For the 40 neoplastic lesions, ROI-DM and LM agreed on general category of tumor type in 78 of 80 cases (98%). ROI-DM cytology showed robust concordance with the current gold standard of LM cytology and is potentially a viable alternative to current LM cytology techniques.

Diagnostic Validation of a Whole-Slide Imaging Scanner in Cytological Samples: Diagnostic Accuracy and Comparison With Light Microscopy.

Digital slides created by whole-slide imaging scanners can be evaluated by pathologists located in remote sites, but the process must be validated before this technology can be applied to routine cytological diagnosis. The aim of this study was to validate a whole-slide imaging scanner for cytological samples. Sixty cytological samples, whose diagnoses were confirmed by gold-standard examinations (histology or flow cytometry), were digitalized using a whole-slide imaging scanner. Digital slides and glass slides were examined by 3 observers with different levels of cytopathological expertise. No significant differences were noted between digital and glass slides in regard to the number of cases correctly diagnosed, or the sensitivity, specificity, or diagnostic accuracy, irrespective of the observers' expertise. The agreements between the digital slides and the gold-standard examinations were moderate to substantial, while the agreements between the glass slides and the gold-standard examinations were substantial for all 3 observers. The intraobserver agreements between digital and glass slides were substantial to almost perfect. The interobserver agreements when evaluating digital slides were moderate between observers 1 and 2 and between observers 1 and 3 while they were substantial between observers 2 and 3. In conclusion, our study demonstrated that the digital slides produced by the whole-slide imaging scanner are adequate to diagnose cytological samples and are similar among clinical pathologists with differing levels of expertise.

Automated microscopy for routine malaria diagnosis: a field comparison on Giemsa-stained blood films in Peru.

BACKGROUND: Microscopic examination of Giemsa-stained blood films remains a major form of diagnosis in malaria case management, and is a reference standard for research. However, as with other visualization-based diagnoses, accuracy depends on individual technician performance, making standardization difficult and reliability poor. Automated image recognition based on machine-learning, utilizing convolutional neural networks, offers potential to overcome these drawbacks. A prototype digital microscope device employing an algorithm based on machine-learning, the Autoscope, was assessed for its potential in malaria microscopy. Autoscope was tested in the Iquitos region of Peru in 2016 at two peripheral health facilities, with routine microscopy and PCR as reference standards. The main outcome measures include sensitivity and specificity of diagnosis of malaria from Giemsa-stained blood films, using PCR as reference. METHODS: A cross-sectional, observational trial was conducted at two peripheral primary health facilities in Peru. 700 participants were enrolled with the criteria: (1) age between 5 and 75 years, (2) history of fever in the last 3 days or elevated temperature on admission, (3) informed consent. The main outcome measures included sensitivity and specificity of diagnosis of malaria from Giemsa-stained blood films, using PCR as reference. RESULTS: At the San Juan clinic, sensitivity of Autoscope for diagnosing malaria was 72% (95% CI 64-80%), and specificity was 85% (95% CI 79-90%). Microscopy performance was similar to Autoscope, with sensitivity 68% (95% CI 59-76%) and specificity 100% (95% CI 98-100%). At San Juan, 85% of prepared slides had a minimum of 600 WBCs imaged, thus meeting Autoscope's design assumptions. At the second clinic, Santa Clara, the sensitivity of Autoscope was 52% (95% CI 44-60%) and specificity was 70% (95% CI 64-76%). Microscopy performance at Santa Clara was 42% (95% CI 34-51) and specificity was 97% (95% CI 94-99). Only 39% of slides from Santa Clara met Autoscope's design assumptions regarding WBCs imaged. CONCLUSIONS: Autoscope's diagnostic performance was on par with routine microscopy when slides had adequate blood volume to meet its design assumptions, as represented by results from the San Juan clinic. Autoscope's diagnostic performance was poorer than routine microscopy on slides from the Santa Clara clinic, which generated slides with lower blood volumes. Results of the study reflect both the potential for artificial intelligence to perform tasks currently conducted by highly-trained experts, and the challenges of replicating the adaptiveness of human thought processes.

Digital vs traditional: Are diagnostic accuracy rates similar for glass slides vs whole slide images in a non-gynaecological external quality assurance setting?

INTRODUCTION: The Royal College of Pathologists of Australasia Quality Assurance Programs introduced virtual microscopy cases into its cytopathology non-gynaecological programme after a short pilot phase, to address the challenges of providing a purely glass slide-based external quality assurance programme to multiple participants both locally and internationally. The use of whole slide image (WSI) cases has facilitated a more robust programme in relation to standardised material and statistical analysis, with access to a wider variety of specimen types and diagnostic entities. METHOD: Diagnostic accuracy rates on 56 WSI were assessed against the reference diagnosis. A portion (12) of these WSI slides had been used in glass slide format in previous external quality assurance surveys, and the results of these were compared to the responses received as glass slide cases. RESULTS: Overall diagnostic accuracy for the 56 WSI cases was acceptable in comparison to the reference diagnosis. When these 12 cases were analysed individually, for seven of the 12 cases, virtual format was found to be not inferior to glass slides for diagnostic accuracy. For one case, accuracy using WSI for diagnosis was superior to glass format. CONCLUSION: Diagnostic accuracy, using WSI for cases in our external quality assurance programme is acceptable. As the use of digital microscopy in a large scale external quality assurance programme offers extensive advantages over a glass slide-based format, our results encourage future comparison of diagnostic accuracy for virtual compared to glass slide format at a point in time where pathologists are becoming increasingly familiar with virtual microscopy in everyday practice.

The Pathologist 2.0: An Update on Digital Pathology in Veterinary Medicine.

Using light microscopy to describe the microarchitecture of normal and diseased tissues has changed very little since the middle of the 19th century. While the premise of histologic analysis remains intact, our relationship with the microscope is changing dramatically. Digital pathology offers new forms of visualization, and delivery of images is facilitated in unprecedented ways. This new technology can untether us entirely from our light microscopes, with many pathologists already performing their jobs using virtual microscopy. Several veterinary colleges have integrated virtual microscopy in their curriculum, and some diagnostic histopathology labs are switching to virtual microscopy as their main tool for the assessment of histologic specimens. Considering recent technical advancements of slide scanner and viewing software, digital pathology should now be considered a serious alternative to traditional light microscopy. This review therefore intends to give an overview of the current digital pathology technologies and their potential in all fields of veterinary pathology (ie, research, diagnostic service, and education). A future integration of digital pathology in the veterinary pathologist's workflow seems to be inevitable, and therefore it is proposed that trainees should be taught in digital pathology to keep up with the unavoidable digitization of the profession.

Early Alzheimer's disease neuropathology detected by proton MR spectroscopy.

Proton magnetic resonance spectroscopy ((1)H-MRS) is sensitive to early neurodegenerative processes associated with Alzheimer's disease (AD). Although (1)H-MRS metabolite ratios of N-acetyl aspartate (NAA)/creatine (Cr), NAA/myoinositol (mI), and mI/Cr measured in the posterior cingulate gyrus reveal evidence of disease progression in AD, pathologic underpinnings of the (1)H-MRS metabolite changes in AD are unknown. Pathologically diagnosed human cases ranging from no likelihood to high likelihood AD (n = 41, 16 females and 25 males) who underwent antemortem (1)H-MRS of the posterior cingulate gyrus at 3 tesla were included in this study. Immunohistochemical evaluation was performed on the posterior cingulate gyrus using antibodies to synaptic vesicles, hyperphosphorylated tau (pTau), neurofibrillary tangle conformational-epitope (cNFT), amyloid-ß, astrocytes, and microglia. The slides were digitally analyzed using Aperio software, which allows neuropathologic quantification in the posterior cingulate gray matter. MRS and pathology associations were adjusted for time from scan to death. Significant associations across AD and control subjects were found between reduced synaptic immunoreactivity and both NAA/Cr and NAA/mI in the posterior cingulate gyrus. Higher pTau burden was associated with lower NAA/Cr and NAA/mI. Higher amyloid-ß burden was associated with elevated mI/Cr and lower NAA/mI ratios, but not with NAA/Cr. (1)H-MRS metabolite levels reveal early neurodegenerative changes associated with AD pathology. Our findings support the hypothesis that a decrease in NAA/Cr is associated with loss of synapses and early pTau pathology, but not with amyloid-ß or later accumulation of cNFT pathology in the posterior cingulate gyrus. In addition, elevation of mI/Cr is associated with the occurrence of amyloid-ß plaques in AD.