Structured illumination microscopy for cancer identification in diagnostic breast biopsies.

Breast cancer is the second most common cancer diagnosed in women in the US with almost 280,000 new cases anticipated in 2023. Currently, on-site pathology for location guidance is not available during the collection of breast biopsies or during surgical intervention procedures. This shortcoming contributes to repeat biopsy and re-excision procedures, increasing the cost and patient discomfort during the cancer management process. Both procedures could benefit from on-site feedback, but current clinical on-site evaluation techniques are not commonly used on breast tissue because they are destructive and inaccurate. Ex-vivo microscopy is an emerging field aimed at creating histology-analogous images from non- or minimally-processed tissues, and is a promising tool for addressing this pain point in clinical cancer management. We investigated the ability structured illumination microscopy (SIM) to generate images from freshly-obtained breast tissues for structure identification and cancer identification at a speed compatible with potential on-site clinical implementation. We imaged 47 biopsies from patients undergoing a guided breast biopsy procedure using a customized SIM system and a dual-color fluorescent hematoxylin & eosin (H&E) analog. These biopsies had an average size of 0.92 cm2 (minimum 0.1, maximum 4.2) and had an average imaging time of 7:29 (minimum 0:22, maximum 37:44). After imaging, breast biopsies were submitted for standard histopathological processing and review. A board-certified pathologist returned a binary diagnostic accuracy of 96% when compared to diagnoses from gold-standard histology slides, and key tissue features including stroma, vessels, ducts, and lobules were identified from the resulting images.

From ultrasound to microscopy: Actualities in thyroid investigation in cattle.

Thyroid ultrasonography examination is widely used in human and small animal medicine. However, it has rarely been applied in cattle. The aim of this study was to determine whether the measurements of the thyroid gland by ultrasound examination correlate to those taken during post-mortem examination. A sample of 22 cows and 23 calves was selected for thyroid gland evaluation. An ultrasound scan was performed ante-mortem, followed by euthanasia (for medical reasons) or slaughtered in the food chain and the dissection of the thyroid gland was therefore performed. Post-mortem, the gland was weighed and its dimensions and volume measured. The volume and weight measurements were compared with the predicted ones on US using the formulas available in the literature. Finally, histological examination was performed on thyroid glands. The dimensions of the thyroid gland measured by ultrasonography were significantly different (p<0.05) from those observed post-mortem, except for lobe lengths in calves (p>0.1). However, in calves, there was no systematic bias between the ultrasound and post-mortem examination of the thyroid gland, which were concordant (with an average error of 18%). Cystic lesions were observed on ultrasound in 9/22 cows and could be found on histological examination in 7 of these. Other lesions, such as follicular hypoplasia and hyperplasia, were seen on histological examination but not on ultrasound. Although the ultrasound measurements did not significantly correlate with those taken post-mortem, this examination may allow to differentiate non-standard thyroids in the case of hyperplastic goiter, as demonstrated in other species. This study also describes and illustrates interesting lesions of the thyroid gland in cattle. These findings are innovative in the description of the use of thyroid ultrasound in cattle, although further studies are needed to allow deeper conclusions.

Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.

Significance: Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful detection and classification of various tissue types, including carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries. Aim: We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples. Approach: Breast tissues excised during breast-conserving surgeries were imaged by the HSDFM and analyzed. The performance of the HSDFM is evaluated by comparing the backscattering intensity spectra of polystyrene microbead solutions with the Monte Carlo simulation of the experimental data. For classification algorithms, two analysis approaches, a supervised technique based on the spectral angle mapper (SAM) algorithm and an unsupervised technique based on the K-means algorithm are applied to classify various tissue types including carcinoma subtypes. In the supervised technique, the SAM algorithm with manually extracted endmembers guided by H&E annotations is used as reference spectra, allowing for segmentation maps with classified tissue types including carcinoma subtypes. Results: The manually extracted endmembers of known tissue types and their corresponding threshold spectral correlation angles for classification make a good reference library that validates endmembers computed by the unsupervised K-means algorithm. The unsupervised K-means algorithm, with no a priori information, produces abundance maps with dominant endmembers of various tissue types, including carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma. The two carcinomas' unique endmembers produced by the two methods agree with each other within <2% residual error margin. Conclusions: Our report demonstrates a robust procedure for the validation of an unsupervised algorithm with the essential set of parameters based on the ground truth, histopathological information. We have demonstrated that a trained library of the histopathology-guided endmembers and associated threshold spectral correlation angles computed against well-defined reference data cubes serve such parameters. Two classification algorithms, supervised and unsupervised algorithms, are employed to identify regions with carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma present in the tissues. The two carcinomas' unique endmembers used by the two methods agree to <2% residual error margin. This library of high quality and collected under an environment with no ambient background may be instrumental to develop or validate more advanced unsupervised data cube analysis algorithms, such as effective neural networks for efficient subtype classification.

Laser speckle rheological microscopy reveals wideband viscoelastic spectra of biological tissues.

Viscoelastic transformation of tissue drives aberrant cellular functions and is an early biomarker of disease pathogenesis. Tissues scale a range of viscoelastic moduli, from biofluids to bone. Moreover, viscoelastic behavior is governed by the frequency at which tissue is probed, yielding distinct viscous and elastic responses modulated over a wide frequency band. Existing tools do not quantify wideband viscoelastic spectra in tissues, leaving a vast knowledge gap. We present wideband laser speckle rheological microscopy (WB-SHEAR) that reveals elastic and viscous response over sub-megahertz frequencies previously not investigated in tissue. WB-SHEAR uses an optical, noncontact approach to quantify wideband viscoelastic spectra in specimens spanning a range of moduli from low-viscosity fibrin to highly elastic bone. Via laser scanning, micromechanical imaging is enabled to access wideband viscoelastic spectra in heterogeneous tumor specimens with high spatial resolution (25 micrometers). The ability to interrogate the viscoelastic landscape of diverse biospecimens could transform our understanding of mechanobiological processes in various diseases.

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.

Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of diseases such as malaria, leukemia, AIDS, and other viral infections. WBCs detection and classification in blood smears offers insights to pathologists, aiding diagnosis across medical conditions. Traditional techniques, including manual counting, detection, classification, and visual inspection of microscopic images by medical professionals, pose challenges due to their labor-intensive nature. However, traditional methods are time consuming and sometimes susceptible to errors. Here, we propose a high-performance convolutional neural network (CNN) coupled with a dual-attention network that efficiently detects and classifies WBCs in microscopic thick smear images. The main aim of this study was to enhance clinical hematology systems and expedite medical diagnostic processes. In the proposed technique, we utilized a deep convolutional generative adversarial network (DCGAN) to overcome the limitations imposed by limited training data and employed a dual attention mechanism to improve accuracy, efficiency, and generalization. The proposed technique achieved overall accuracy rates of 99.83%, 99.35%, and 99.60% for the peripheral blood cell (PBC), leukocyte images for segmentation and classification (LISC), and Raabin-WBC benchmark datasets, respectively. Our proposed approach outperforms state-of-the-art methods in terms of accuracy, highlighting the effectiveness of the strategies employed and their potential to enhance diagnostic capabilities and advance real-world healthcare practices and diagnostic systems.

Reproducibility and prognostic ability of chronicity parameters in kidney biopsy - Comprehensive evaluation comparing microscopy and artificial intelligence in digital pathology.

INTRODUCTION: Semi-quantitative scoring of various parameters in renal biopsy is accepted as an important tool to assess disease activity and prognostication. There are concerns on the impact of interobserver variability in its prognostic utility, generating a need for computerized quantification. METHODS: We studied 94 patients with renal biopsies, 45 with native diseases and 49 transplant patients with index biopsies for Polyomavirus nephropathy. Chronicity scores were evaluated using two methods. A standard definition diagram was agreed after international consultation and four renal pathologists scored each parameter in a double-blinded manner. Interstitial fibrosis (IF) score was assessed with five different computerized and AI-based algorithms on trichrome and PAS stains. RESULTS: There was strong prognostic correlation with renal function and graft outcome at a median follow-up ranging from 24 to 42 months respectively, independent of moderate concordance for pathologists scores. IF scores with two of the computerized algorithms showed significant correlation with estimated glomerular filtration rate (eGFR) at biopsy but not at the end of follow-up. There was poor concordance for AI based platforms. CONCLUSION: Chronicity scores are robust prognostic tools despite interobserver reproducibility. AI-algorithms have absolute precision but are limited by significant variation when different hardware and software algorithms are used for quantification.

Non-invasive methods of monitoring Fe3O4 magnetic nanoparticle toxicity in human liver HepaRG cells using impedance biosensing and Coherent anti-Stokes Raman spectroscopic (CARS) microscopy.

Functionalized nanoparticles have been developed for use in nanomedicines for treating life threatening diseases including various cancers. To ensure safe use of these new nanoscale reagents, various assays for biocompatibility or cytotoxicity in vitro using cell lines often serve as preliminary assessments prior to in vivo animal testing. However, many of these assays were designed for soluble, colourless materials and may not be suitable for coloured, non-transparent nanoparticles. Moreover, cell lines are not always representative of mammalian organs in vivo. In this work, we use non-invasive impedance sensing methods with organotypic human liver HepaRG cells as a model to test the toxicity of PEG-Fe3O4 magnetic nanoparticles. We also use Coherent anti-Stokes Raman Spectroscopic (CARS) microscopy to monitor the formation of lipid droplets as a parameter to the adverse effect on the HepaRG cell model. The results were also compared with two commercial testing kits (PrestoBlue and ATP) for cytotoxicity. The results suggested that the HepaRG cell model can be a more realistic model than commercial cell lines while use of impedance monitoring of Fe3O4 nanoparticles circumventing the uncertainties due to colour assays. These methods can play important roles for scientists driving towards the 3Rs principle - Replacement, Reduction and Refinement.

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology.

Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

On-the-fly Raman microscopy guaranteeing the accuracy of discrimination.

Accelerating the measurement for discrimination of samples, such as classification of cell phenotype, is crucial when faced with significant time and cost constraints. Spontaneous Raman microscopy offers label-free, rich chemical information but suffers from long acquisition time due to extremely small scattering cross-sections. One possible approach to accelerate the measurement is by measuring necessary parts with a suitable number of illumination points. However, how to design these points during measurement remains a challenge. To address this, we developed an imaging technique based on a reinforcement learning in machine learning (ML). This ML approach adaptively feeds back "optimal" illumination pattern during the measurement to detect the existence of specific characteristics of interest, allowing faster measurements while guaranteeing discrimination accuracy. Using a set of Raman images of human follicular thyroid and follicular thyroid carcinoma cells, we showed that our technique requires 3,333 to 31,683 times smaller number of illuminations for discriminating the phenotypes than raster scanning. To quantitatively evaluate the number of illuminations depending on the requisite discrimination accuracy, we prepared a set of polymer bead mixture samples to model anomalous and normal tissues. We then applied a home-built programmable-illumination microscope equipped with our algorithm, and confirmed that the system can discriminate the sample conditions with 104 to 4,350 times smaller number of illuminations compared to standard point illumination Raman microscopy. The proposed algorithm can be applied to other types of microscopy that can control measurement condition on the fly, offering an approach for the acceleration of accurate measurements in various applications including medical diagnosis.

Photoacoustic microscopy for real-time monitoring of near-infrared optical absorbers inside biological tissue.

Significance: We developed a high-speed optical-resolution photoacoustic microscopy (OR-PAM) system using a high-repetition-rate supercontinuum (SC) light source and a two-axes Galvano scanner. The OR-PAM system enabled real-time imaging of optical absorbers inside biological tissues with excellent excitation wavelength tunability. Aim: In the near-infrared (NIR) wavelength range, high-speed OR-PAM faces limitations due to the lack of wavelength-tunable light sources. Our study aimed to enable high-speed OR-PAM imaging of various optical absorbers, including NIR contrast agents, and validate the performance of high-speed OR-PAM in the detection of circulating tumor cells (CTCs). Approach: A high-repetition nanosecond pulsed SC light source was used for OR-PAM. The excitation wavelength was adjusted by bandpass filtering of broadband light pulses produced by an SC light source. Phantom and in vivo experiments were performed to detect tumor cells stained with an NIR contrast agent within flowing blood samples. Results: The newly developed high-speed OR-PAM successfully detected stained cells both in the phantom and in vivo. The phantom experiment confirmed the correlation between the tumor cell detection rate and tumor cell concentration in the blood sample. Conclusions: The high-speed OR-PAM effectively detected stained tumor cells. Combining high-speed OR-PAM with molecular probes that stain tumor cells in vivo enables in vivo CTC detection.

Endoscopic 5-Aminolevulinic Acid-Induced Fluorescence-Guided Intraparenchymal Brain Tumor Resection-Can the Endoscope Detect More Fluorescence Than the Microscope?

OBJECTIVES: Using a laboratory-based optical setup, we show that 5-aminolevulinic acid (5ALA) fluorescence is better detected using the endoscope than the microscope. Furthermore, we present our case series of fully endoscopic 5ALA-guided resection of intraparenchymal tumors. METHODS: A Zeiss Pentero microscope was compared with the Karl Storz Hopkins endoscope. The spectra and intensity of each blue light source were measured. Quantitative fluorescence detection thresholds were measured using a spectrometer. Subjective fluorescence detection thresholds were measured by 6 blinded neuro-oncology surgeons. Clinical data were prospectively collected for all consecutive cases of fully endoscopic 5ALA-guided resection of intraparenchymal tumors between 2012 and 2023. RESULTS: The intensity of blue light on the sample was greater for the endoscope than the microscope at working distances less than 20 mm. The quantitative fluorescence detection thresholds were lower for the endoscope than the microscope at both 30-/10-mm working distances. Fluorescence detection threshold was 0.65%-0.80% relative 4-dicyanomethylene-2-methyl-6-p-dimethylaminostyryl-4H-pyranthe concentration (3.20 × 10-7 to 3.94 × 10-7mol/dm-3) for the microscope, 0.40%-0.55% relative concentrations (1.97 × 10-7 to 2.71 × 10-7mol/dm-3) for the endoscope at 30 mm, and 0.15%-0.30% relative concentrations (7.40 × 10-8 to 1.48 × 10-7mol/dm-3) for the endoscope at 10 mm. In total, 49 5ALA endoscope-assisted brain tumor resections were carried out on 45 patients (mean age = 41 years, male = 28). Greater than 95% resection was achieved in 80% of cases and gross total resection in 42%. Gross total resection was achieved in 100% of tumors in noneloquent locations. There was 1 new neurologic deficit. CONCLUSIONS: The endoscope provides enhanced visualization/detection of 5ALA-induced fluorescence compared with the microscope. 5ALA endoscopic-assisted resection of intraparenchymal tumors is safe and feasible.

Digital morphology compared to the optical microscope: A validation study on reporting bone marrow aspirates.

INTRODUCTION: This study aims to evaluate the effectiveness and reliability of the utilization for clinical reporting of the evaluation of digital images of bone marrow aspirates by morphologists and their comparability with the classic microscopic morphological evaluation. METHODS: We scanned 180 consecutive bone marrow needle aspirates smears using the "Metafer4 VSlide" whole slide imaging (WSI) digital scanning system. We evaluated the statistical comparability and the risk of bias of the microscopic readings with those performed on the screen on the digitized medullary images. RESULTS: The evaluation of cellularity on the screen was equivalent, with a higher frequency of "normal" than the analysis of digital preparations. The means and medians of the percentage values obtained on the different cell populations with the microscopic and digital reading were comparable as the main categories are concerned, with an average difference equal to 0 for the neutrophilic and eosinophilic granulocytic series, at -0.2% for the total myeloid cells, at 1.2% for the erythroid series, at -0.4% for the lymphocytes and at -0.4% for the blasts. Dysplastic features were consistently identified in 69/71 cell lineages. CONCLUSION: Our study demonstrated that screen evaluation of digitized bone marrow needle aspirates provides quantitative and qualitative results comparable to traditional microscopic analysis of the corresponding slide smears. Digital images offer significant benefits in reducing the workload of experienced operators, reproducibility and sharing of observations, and image preservation. Even in routine diagnostic activities, their use does not alter the quality of the results obtained in evaluating bone marrow needle aspirates.

Stochastic Optical Reconstruction Microscopy Imaging of Multiple System Atrophy Inclusions Suggests Stepwise α-Synuclein Aggregation.

BACKGROUND: The architecture and composition of glial (GCI) and neuronal (NCI) α-synuclein inclusions observed in multiple system atrophy (MSA) remain to be precisely defined to better understand the disease. METHODS: Here, we used stochastic optical reconstruction microscopy (STORM) to characterize the nanoscale organization of glial (GCI) and neuronal (NCI) α-synuclein inclusions in cryopreserved brain sections from MSA patients. RESULTS: STORM revealed a dense cross-linked internal structure of α-synuclein in all GCI and NCI. The internal architecture of hyperphosphorylated α-synuclein (p-αSyn) inclusions was similar in glial and neuronal cells, suggesting a common aggregation mechanism. A similar sequence of p-αSyn stepwise intracellular aggregation was defined in oligodendrocytes and neurons, starting from the perinuclear area and growing inside the cells. Consistent with this hypothesis, we found a higher mitochondrial density in GCI and NCI compared to oligodendrocytes and neurons from unaffected donors (P < 0.01), suggesting an active recruitment of the organelles during the aggregation process. CONCLUSIONS: These first STORM images of GCI and NCI suggest stepwise α-synuclein aggregation in MSA. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fast cancer imaging in pancreatic biopsies using infrared imaging.

Pancreatic cancer, particularly Pancreatic ductal adenocarcinoma, remains a highly lethal form of cancer with limited early diagnosis and treatment options. Infrared (IR) spectroscopy, combined with machine learning, has demonstrated great potential in detecting various cancers. This study explores the translation of a diagnostic model from Fourier Transform Infrared to Quantum Cascade Laser (QCL) microscopy for pancreatic cancer classification. Furthermore, QCL microscopy offers faster measurements with selected frequencies, improving clinical feasibility. Thus, the goals of the study include establishing a QCL-based model for pancreatic cancer classification and creating a fast surgical margin detection model using reduced spectral information. The research involves preprocessing QCL data, training Random Forest (RF) classifiers, and optimizing the selection of spectral features for the models. Results demonstrate successful translation of the diagnostic model to QCL microscopy, achieving high predictive power (AUC = 98%) in detecting cancerous tissues. Moreover, a model for rapid surgical margin recognition, based on only a few spectral frequencies, is developed with promising differentiation between benign and cancerous regions. The findings highlight the potential of QCL microscopy for efficient pancreatic cancer diagnosis and surgical margin detection within clinical timeframes of minutes per surgical resection tissue.

Photoacoustic expansion microscopy of melanosomes.

Optical resolution photoacoustic microscopy (OR-PAM) is a hybrid imaging method for visualizing organelles due to the high spatial resolution and abundant optical contrast. Usually, OR-PAM employs high numerical aperture (NA) objectives and high-frequency ultrasonic detectors to resolve three-dimensional (3D) microstructures of cells. Expansion microscopy (ExM) provides a nanoscale resolution by isotropically enlarging cells instead of utilizing ultrahigh NA objectives. In this Letter, we report the development of photoacoustic expansion microscopy (PA-ExM) that combines the advantages of OR-PAM and ExM for 3D organelle imaging using near-infrared light. We evaluate the performance of PA-ExM using label-free melanoma cells, where the image quality of melanosome distributions in expanded cells using a 40× objective is comparable to that of unexpanded cells using an oil-immersed 100× objective. The results suggest that PA-ExM possesses the great potential to study organelles.

Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma.

Significance: Polarized hyperspectral microscopes with the capability of full Stokes vector imaging have potential for many biological and medical applications. Aim: The aim of this study is to investigate polarized hyperspectral imaging (PHSI) for improving the visualization of collagen fibers, which is an important biomarker related to tumor development, and improving the differentiation of normal and tumor cells on pathologic slides. Approach: We customized a polarized hyperspectral microscopic imaging system comprising an upright microscope with a motorized stage, two linear polarizers, two liquid crystal variable retarders (LCVRs), and a compact SnapScan hyperspectral camera. The polarizers and LCVRs worked in tandem with the hyperspectral camera to acquire polarized hyperspectral images, which were further used to calculate four Stokes vectors: S0, S1, S2, and S3. Synthetic RGB images of the Stokes vectors were generated for the visualization of cellular components in PHSI images. Regions of interest of collagen, normal cells, and tumor cells in the synthetic RGB images were selected, and spectral signatures of the selected components were extracted for comparison. Specifically, we qualitatively and quantitatively investigated the enhanced visualization and spectral characteristics of dense fibers and sparse fibers in normal stroma tissue, fibers accumulated within tumors, and fibers accumulated around tumors. Results: By employing our customized polarized hyperspectral microscope, we extract the spectral signatures of Stokes vector parameters of collagen as well as of tumor and normal cells. The measurement of Stokes vector parameters increased the image contrast of collagen fibers and cells in the slides. Conclusions: With the spatial and spectral information from the Stokes vector data cubes (S0, S1, S2, and S3), our PHSI microscope system enhances the visualization of tumor cells and tumor microenvironment components, thus being beneficial for pathology and oncology.

Exploring the future of regenerative medicine: Unveiling the potential of optical microscopy for structural and functional imaging of stem cells.

Regenerative medicine, which utilizes stem cells for tissue and organ repair, holds immense promise in healthcare. A comprehensive understanding of stem cell characteristics is crucial to unlock their potential. This study explores the pivotal role of optical microscopy in advancing regenerative medicine as a potent tool for stem cell research. Advanced optical microscopy techniques enable an in-depth examination of stem cell behavior, morphology, and functionality. The review encompasses current optical microscopy, elucidating its capabilities and constraints in stem cell imaging, while also shedding light on emerging technologies for improved stem cell visualization. Optical microscopy, complemented by techniques like fluorescence and multiphoton imaging, enhances our comprehension of stem cell dynamics. The introduction of label-free imaging facilitates noninvasive, real-time stem cell monitoring without external dyes or markers. By pushing the boundaries of optical microscopy, researchers reveal the intricate cellular mechanisms underpinning regenerative processes, thereby advancing more effective therapeutic strategies. The current study not only outlines the future of regenerative medicine but also underscores the pivotal role of optical microscopy in both structural and functional stem cell imaging.

Digital pathology for reporting histopathology samples, including cancer screening samples - definitive evidence from a multisite study.

AIMS: To conduct a definitive multicentre comparison of digital pathology (DP) with light microscopy (LM) for reporting histopathology slides including breast and bowel cancer screening samples. METHODS: A total of 2024 cases (608 breast, 607 GI, 609 skin, 200 renal) were studied, including 207 breast and 250 bowel cancer screening samples. Cases were examined by four pathologists (16 study pathologists across the four speciality groups), using both LM and DP, with the order randomly assigned and 6 weeks between viewings. Reports were compared for clinical management concordance (CMC), meaning identical diagnoses plus differences which do not affect patient management. Percentage CMCs were computed using logistic regression models with crossed random-effects terms for case and pathologist. The obtained percentage CMCs were referenced to 98.3% calculated from previous studies. RESULTS: For all cases LM versus DP comparisons showed the CMC rates were 99.95% [95% confidence interval (CI) = 99.90-99.97] and 98.96 (95% CI = 98.42-99.32) for cancer screening samples. In speciality groups CMC for LM versus DP showed: breast 99.40% (99.06-99.62) overall and 96.27% (94.63-97.43) for cancer screening samples; [gastrointestinal (GI) = 99.96% (99.89-99.99)] overall and 99.93% (99.68-99.98) for bowel cancer screening samples; skin 99.99% (99.92-100.0); renal 99.99% (99.57-100.0). Analysis of clinically significant differences revealed discrepancies in areas where interobserver variability is known to be high, in reads performed with both modalities and without apparent trends to either. CONCLUSIONS: Comparing LM and DP CMC, overall rates exceed the reference 98.3%, providing compelling evidence that pathologists provide equivalent results for both routine and cancer screening samples irrespective of the modality used.

Improvements in digital pathology equipment for renal biopsies: updating the standard model.

INTRODUCTION: Digital pathology can improve the technical and interpretative workflows in nephropathology by creating hub-spoke networks and virtuous collaboration projects among centers in different geographical regions. New high-resolution fast-scanning instruments combined with currently existing equipment were tested in a nephropathology hub to evaluate possible upgrading in the routine processing phases. METHODS: The scanning performance of two different instruments (Aperio vs hybrid MIDI II) was evaluated and a comparative quality control check was performed on obtained whole slide images. RESULTS: Both with default and custom settings for light microscopy, MIDI II proved to be faster, with only slightly more time required to prepare the scan and larger final file size as compared to Aperio (p < 0.001). No differences were noted in the number of out-of-focus slides per case (p = 0.75). Regarding immunofluorescence, the new scanner required longer preparation time (p = 0.001) with comparable scanning times and final file size (p = 0.169 and p = 0.177, respectively). Quality control showed differences in 3 quality features related to white background and blurriness (p < 0.001). No major discordances in the final diagnosis were recorded after comparing the report obtained with slides scanned using the two instruments, with only one case (4%) showing minor disagreement. CONCLUSION: The present report describes the experience of a hub nephropathology center adopting next generation digital pathology tools for the routine assessment of renal biopsies, highlighting the need for a complementary approach towards a philosophy of interoperability.