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Artificial intelligence (AI) is of considerable interest in the healthcare community including its diagnostic applications for thyroid nodules in assisting both radiology and FNA assessment. Fine-needle aspiration (FNA) helps distinguishing benign from malignant thyroid nodules and is a crucial step in the initial diagnosis of cancer. The classification of some lesions can be challenging, and the use of AI in some cases may become essential in order not to give an indeterminate result to the lesion. In this review, we summarize the available evidence regarding the application of AI in thyroid imaging and cytopathology. There are now considerable applications in digital waiting to be approved that will save time and cut costs. The published literature to date has shown promising results. However, future work is required to better define how this technology can be exploited in routine cytopathology practice.

Introduction: This retrospective study on patients with biopsy-proven lupus nephritis (LN) aimed to assess the probability of sustained clinical remission (sCR) and to investigate sCR effects on disease flares and impaired kidney function (IKF). Methods: sCR was defined as clinical-Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) = 0 and estimated glomerular filtration rate (eGFR) >60 ml/min per 1.73 m2 lasting ≥1 year; IKF: eGFR <60 ml/min per 1.73 m2 for >3 months. We analyzed the probability of achieving and maintaining sCR, and the yearly risk of flare. Cox models were used to identify predictors of sCR and IKF with variables analyzed as time-dependent covariates when appropriate. Results: Of 303 patients followed-up with for 14.8 (interquartile range: 9.8–22) years, 257 (84.8%) achieved sCR. The probability of achieving sCR progressively increased over time reaching 90% at 15 years. Baseline age (hazard ratio [HR]: 1.017; 95% confidence interval [CI]: 0.005–1.029; P = 0.004), hydroxychloroquine intake (HR: 1.385; 95% CI: 1.051–1.825; P = 0.021), and absence of arterial hypertension (HR: 0.699; 95% CI: 0.532–0.921; P = 0.011) were independent predictors of sCR. Among patients who achieved sCR, 142 (55.3%) developed a lupus flare after a median time of 3.6 (2.3–5.9) years. In the remaining 115 patients, sCR persisted for 9.5 (5.8–14.5) years. The probability of sCR to persist at 15 years was 38%. SLE flare risk decreased to 10%, 5%, and 2% in patients with sCR lasting <5, 5 to 10, and >10 years, respectively. At the last observation, 57 patients (18.81%) had IKF. sCR achievement (HR: 0.18, P < 0.001) and its duration (HR: 0.83, P < 0.001) were protective against IKF. Conclusion: sCR is an achievable target in LN management and protects against IKF. The longer the sCR, the higher the chance of its persistence and the lower the risk of SLE flares.

The application of innovative spatial proteomics techniques, such as those based upon matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology, has the potential to impact research in the field of nephropathology. Notwithstanding, the possibility to apply this technology in more routine diagnostic contexts remains limited by the alternative fixatives employed by this ultraspecialized diagnostic field, where most nephropathology laboratories worldwide use bouin-fixed paraffin-embedded (BFPE) samples. Here, the feasibility of performing MALDI-MSI on BFPE renal tissue is explored, evaluating variability within the trypsin-digested proteome as a result of different preanalytical conditions and comparing them with the more standardized formalin-fixed paraffin-embedded (FFPE) counterparts. A large proportion of the features (270, 68.9%) was detected in both BFPE and FFPE renal samples, demonstrating only limited variability in signal intensity (10.22-10.06%). Samples processed with either fixative were able to discriminate the principal parenchyma regions along with diverse renal substructures, such as glomeruli, tubules, and vessels. This was observed when performing an additional "stress test", showing comparable results in both BFPE and FFPE samples when the distribution of several amyloid fingerprint proteins was mapped. These results suggest the utility of BFPE tissue specimens in MSI-based nephropathology research, further widening their application in this field.

Recent advancements in computer-assisted diagnosis (CAD) have catalysed significant progress in pathology, particularly in the realm of urine cytopathology. This review synthesizes the latest developments and challenges in CAD for diagnosing urothelial carcinomas, addressing the limitations of traditional urinary cytology. Through a literature review, we identify and analyse CAD models and algorithms developed for urine cytopathology, highlighting their methodologies and performance metrics. We discuss the potential of CAD to improve diagnostic accuracy, efficiency and patient outcomes, emphasizing its role in streamlining workflow and reducing errors. Furthermore, CAD tools have shown potential in exploring pathological conditions, uncovering novel biomarkers and prognostic/predictive features previously unknown or unseen. Finally, we examine the practical issues surrounding the integration of CAD into clinical practice, including regulatory approval, validation and training for pathologists. Despite the promising results, challenges remain, necessitating further research and validation efforts. Overall, CAD presents a transformative opportunity to revolutionize diagnostic practices in urine cytopathology, paving the way for enhanced patient care and outcomes.

Background. Three different histological scores—histopathologic classification (Berden), Renal Risk Score (RRS) and the Mayo Clinic Chronicity Score (MCCS)—for anti-neutrophil cytoplasmic antibody (ANCA)-associated glomerulonephritis (ANCA-GN) were compared to evaluate their association with patient and kidney prognosis of ANCA-GN. Methods. Patients aged >18 years with at least 1 year of follow-up and biopsy-proven ANCA-GN entered this retrospective study. Renal biopsies were classified according to Berden’s classification, RRS and MCCS. The first endpoint was end-stage kidney disease (ESKD), defined as chronic dialysis or estimated glomerular filtration rate <15 mL/min/1.73 m2. The second endpoint was ESKD or death. Results. Of 152 patients 84 were males, with median age of 63.8 years and followed for 46.9 (interquartile range 12.8–119) months, 59 (38.8%) reached the first endpoint and 20 died. The Kaplan–Meier curves showed that Berden and RRS were associated with first (Berden: P = .004, RRS: P < .001) and second (Berden: P = .001, RRS: P < .001) endpoint, MCCS with the first endpoint only when minimal + mild vs moderate + severe groups were compared (P = .017), and with the second endpoint (P < .001). Among the clinical/histological presentation features, arterial hypertension [odds ratio (OR) = 2.75, confidence interval (95% CI) 1.50–5.06; P = .0011], serum creatinine (OR = 1.17, 95% CI 1.09–1.25; P < .0001), and the percentage of normal glomeruli (OR = 0.97, 95% CI 0.96–0.99; P = .009) were the independent predictors of ESKD at multivariate analysis. When the three scores were included in multivariate analysis, RRS (OR = 2.21, 95% CI 1.15–4.24; P = .017) and MCCS (OR = 2.03, 95% CI 1.04–3.95; P = .037) remained predictive of ESKD, but Berden (OR = 1.17, 95% CI 0.62–2.22; P = .691) did not. Conclusion. RRS and MCCS scores were independent predictors of kidney survival together with high serum creatinine and arterial hypertension at diagnosis

Kidneys are often targets of systemic vasculitis (SVs), being affected in many different forms and representing a possible sentinel of an underlying multi-organ condition. Renal biopsy still remains the gold standard for the identification, characterization and classification of these diseases, solving complex differential diagnosis thanks to the combined application of light microscopy (LM), immunofluorescence (IF) and electron microscopy (EM). Due to the progressively increasing complexity of renal vasculitis classification systems (e.g. pauci-immune vs immune complex related forms), a clinico-pathological approach is mandatory and adequate technical and interpretative expertise in nephropathology is required to ensure the best standard of care for our patients. In this complex background, the present review aims at summarising the current knowledge and challenges in the world of renal vasculitis, unveiling the potential role of the introduction of digital pathology in this setting, from the creation of hub-spoke networks to the future application of artificial intelligence (AI) tools to aid in the diagnostic and scoring/classification process.

The diagnostic assessment of thyroid nodules is hampered by the persistence of uncertainty in borderline cases, and further complicated by the inclusion of non-invasive follicular tumor with papillary-like nuclear features (NIFTP) as a less aggressive alternative to papillary thyroid carcinoma (PTC). In this setting, computational methods might facilitate the diagnostic process by unmasking key nuclear characteristics of NIFTPs. The main aims of this work were to (1) identify morphometric features of NIFTP and PTC that are interpretable for the human eye, and (2) develop a deep learning model for multi-class segmentation as a support tool to reduce diagnostic variability. Our findings confirmed that nuclei in NIFTP and PTC share multiple characteristics, setting them apart from hyperplastic nodules (HP). The morphometric analysis identified 15 features that can be translated into nuclear alterations readily understandable by pathologists, such as a remarkable inter-nuclear homogeneity for HP in contrast to a major complexity in the chromatin texture of NIFTP, and to the peculiar pattern of nuclear texture variability of PTC. A few NIFTP cases with available NGS data were also analyzed to initially explore the impact of RAS-related mutations on nuclear morphometry. Finally, a pixel-based deep learning model was trained and tested on whole slide images (WSIs) of NIFTP, PTC, and HP cases. The model, named NUTSHELL (NUclei from Thyroid tumors Segmentation to Highlight Encapsulated Low-malignant Lesions), successfully detected and classified the majority of nuclei in all WSIs' tiles, showing comparable results with already well-established pathology nuclear scores. NUTSHELL provides an immediate overview of NIFTP areas and can be used to detect microfoci of PTC within extensive glandular samples or identify lymph node metastases. NUTSHELL can be run inside WSInfer with an easy rendering in QuPath, thus facilitating the democratization of digital pathology.

Objectives: The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine. Methods: A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer. Results: Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival. Conclusions: The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.

Kidney transplantation is the best treatment for end-stage renal disease since it offers the greatest survival benefit compared to dialysis. The gap between the number of renal transplants performed and the number of patients awaiting renal transplants leads to a steadily increasing pressure on the scientific community. Kidney preimplantation biopsy is used as a component of the evaluation of organ quality before acceptance for transplantation. However, the reliability and predictive value of biopsy data are controversial. Most of the previously proposed predictive models were not associated with graft survival, but what has to be reaffirmed is that histologic examination of kidney tissue can provide an objective window on the state of the organ that cannot be deduced from clinical records and renal functional studies. The balance of evidence indicates that reliable decisions about donor suitability must be made based on the overall picture. This work discusses recent trends that can reduce diagnostic timing and variability among players in the decision-making process that lead to kidney transplants, from the pathologist’s perspective.

Background: The molecular diagnostic and therapeutic pathway of Non-Small Cell Lung Cancer (NSCLC) stands as a successful example of precision medicine. The scarcity of material and the increasing number of biomarkers to be tested have prompted the routine application of next-generation-sequencing (NGS) techniques. Despite its undeniable advantages, NGS involves high costs that may impede its broad adoption in laboratories. This study aims to assess the detailed costs linked to the integration of NGS diagnostics in NSCLC to comprehend their financial impact. Materials and methods: The retrospective analysis encompasses 210 cases of early and advanced stages NSCLC, analyzed with NGS and collected at the IRCCS San Gerardo dei Tintori Foundation (Monza, Italy). Molecular analyses were conducted on FFPE samples, with an hotspot panel capable of detecting DNA and RNA variants in 50 clinically relevant genes. The economic analysis employed a full-cost approach, encompassing direct and indirect costs, overheads, VAT (Value Added Tax). Results: We estimate a comprehensive cost for each sample of €1048.32. This cost represents a crucial investment in terms of NSCLC patients survival, despite constituting only around 1% of the expenses incurred in their molecular diagnostic and therapeutic pathway. Conclusions: The cost comparison between NGS test and the notably higher therapeutic costs highlights that the diagnostic phase is not the limiting economic factor. Developing NGS facilities structured in pathology networks may ensure appropriate technical expertise and efficient workflows.

The assessment of programmed death-ligand 1 (PD-L1) combined positive scoring (CPS) in head and neck squamous cell carcinoma (HNSCC) is challenged by pre-analytical and inter-observer variabilities. An educational program to compare the diagnostic performances between local pathologists and a board of pathologists on 11 challenging cases from different Italian pathology centers stained with PD-L1 immunohistochemistry on a digital pathology platform is reported. A laboratory-developed test (LDT) using both 22C3 (Dako) and SP263 (Ventana) clones on Dako or Ventana platforms was compared with the companion diagnostic (CDx) Dako 22C3 pharm Dx assay. A computational approach was performed to assess possible correlations between stain features and pathologists’ visual assessments. Technical discordances were noted in five cases (LDT vs. CDx, 45%), due to an abnormal nuclear/cytoplasmic diaminobenzidine (DAB) stain in LDT (n = 2, 18%) and due to variation in terms of intensity, dirty background, and DAB droplets (n = 3, 27%). Interpretative discordances were noted in six cases (LDT vs. CDx, 54%). CPS remained unchanged, increased, or decreased from LDT to CDx in three (27%) cases, two (18%) cases, and one (9%) case, respectively, around relevant cutoffs (1 and 20, k = 0.63). Differences noted in DAB intensity/distribution using computational pathology partly explained the LDT vs. CDx differences in two cases (18%). Digital pathology may help in PD-L1 scoring, serving as a second opinion consultation platform in challenging cases. Computational and artificial intelligence tools will improve clinical decision-making and patient outcomes.

In the molecular era, proper archival conditions within pathology laboratories are crucial, especially for formalin-fixed paraffin-embedded (FFPE) tissue specimens retrieved years after the original diagnosis. Indeed, improper preservation can impact the integrity of nucleic acids and protein antigens. This study evaluates the quality status of stored FFPE blocks using multilevel omics approaches. FFPE blocks from 45 Non-Small Cell Lung Carcinoma (NSCLC) cases were analyzed. The blocks were collected from six different pathology archives across Italy with distinct environmental characteristics. Nucleic acids’ quantity and quality, as well as protein antigens, were assessed using various techniques, including MALDI-MSI. RNA was quantitatively higher, but more fragmented, compared to DNA. DNA quantity and quality were suitable for molecular analyses in 94.4% and 62.3% of samples, respectively. RNA quantity was adequate across all samples, but it was optimal only in 22.3% of cases. DNA quality started to deteriorate after 6–8 years, whereas RNA quality diminished only after 10 years of storage. These data might suggest a particular DNA susceptibility to FFPE blocks conservation. Immunohistochemical intensity decreased significantly after 6–8 years of storage, and MALDI-MSI analysis revealed that younger tissue blocks contained more unique proteomic signals than the older ones. This study emphasizes the importance of proper FFPE archiving conditions for molecular analyses. Governance should prioritize attention to pathology archives to ensure quality preservation and optimize predictive testing. By elucidating the nuances of FFPE block storage, this research paves the way for enhanced molecular diagnostics and therapeutic insights regarding oncology and beyond.

Cytopathology represents a well established diagnostic approach because of its limited cost, reliability, and minimal invasiveness with respect to other methodologies. The evolving complexity of the different classifications systems and the implementation of ancillary techniques to refine the diagnosis is progressively helping in the risk of malignancy stratification, and the adoption of next-generation sequencing techniques contributes to enrich this valuable tool with predictive information, which is always more essential in the tailored medicine era. The recent introduction of digital and computational pathology is further boosting the potentialities of cytopathology, aiding in the interpretation of samples to improve the cost effectiveness of large screening programs and the diagnostic efficiency within intermediate/atypical categories. Moreover, the adoption of artificial intelligence tools is promising to complement molecular investigations, representing a stimulating perspective in the cytopathology field. In this work, the authors tried to summarize the multifaceted nature of this complex and evolving field of pathology, synthesizing the most recent advances and providing the young pathologists’ perspective on this fascinating world.

The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, − 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

In this article we describe a case of acute kidney injury caused by ethylene glycol intoxication which partially reversed after temporary hemodialysis treatment. The diagnosis was obtained after the patient’s clinical history and the finding of ethylene glycol in the blood, numerous intratubular crystals at renal biopsy, and the presence of large amounts of atypical – spindle-like and needle-like – calcium oxalate crystals in the urinary sediment.

Introduction: Diagnosis and management of microscopic polyangiitis (MPA) have evolved considerably over the past decades, but it is unknown whether clinical and histological presentation and patient and renal outcomes have changed accordingly. Methods: We compared clinical and histopathological characteristic at diagnosis, risk of death, end-stage kidney disease (ESKD), and relapse rate in patients diagnosed with MPA between 1980 and 2022, after grouping them in 2 periods (p): p1980-2001 and p2002-2022. We compared the mortality rate between the 2 periods using Kaplan-Meier estimator and Cox-regression, and competing risks of ESKD and death using the Aalen-Johansen estimator, Fine-Gray multiple regression, and multistate models. Results: Out of 187 patients, 77 were in p1980-2001 and 110 in p2002 to 2022. Patients in p2002 to 2022 were older (66.2 ± 14.0 SD vs. 57.7 ± 15.8; P < 0.001), had a better kidney function (estimated glomerular filtration rate [eGFR] 25.9 ± 24.8 vs. 21.5 ± 28.2 ml/min per 1.73 m2; P = 0.011) and a lower prevalence of the Berden sclerotic class (5.9 vs. 20.9%; P = 0.011). Despite a similar crude and adjusted patient survival, the risk of ESKD decreased during p2002 to 2022 (subdistribution hazard ratio [HR] 0.30, 95% confidence interval [CI]: 0.16-0.57; P < 0.001). The results remained significant after accounting for death after ESKD and after adjusting for potential confounders (HR 0.33 [95% CI: 0.18-0.63; P < 0.001]). The risk of relapse was numerically higher during p2002 to 2022 (subdistribution-HR 1.64 [95% CI: 0.95-2.83; P = 0.075]). Conclusion: MPA kidney involvement has become less severe over the past decades, leading to a reduced risk of ESKD and a higher relapse rate, despite a comparable risk of death.

Eosinophilic granulomatosis with polyangiitis (EGPA) is a necrotizing vasculitis, which typically affects small-to medium-sized blood vessels. It is characterized by the presence of tissue infiltrates rich in eosinophils, along with the formation of granulomatous lesions. About 40% of cases have positive anti-neutrophil cytoplasm antibodies (ANCA), with predominant perinuclear staining, and anti-myeloperoxidase (anti-MPO) specificity in about 65% of cases. Typical manifestations of EGPA include the late onset of asthma, nasal and sinus-related symptoms, peripheral neuropathy, and significant eosinophilia observed in the peripheral blood. In contrast to granulomatosis with polyangiitis and microscopic polyangiitis, renal involvement in EGPA is less frequent (about 25%) and poorly studied. Necrotizing pauci-immune crescentic glomerulonephritis is the most common renal presentation in patients with ANCA-positive EGPA. Although rarely, other forms of renal involvement may also be observed, such as eosinophilic interstitial nephritis, mesangial glomerulonephritis, membranous nephropathy, or focal sclerosis. A standardized treatment for EGPA with renal involvement has not been defined, however the survival and the renal outcomes are usually better than in the other ANCA-associated vasculitides. Nonetheless, kidney disease is an adverse prognostic factor for EGPA patients. Larger studies are required to better describe the renal involvement, in particular for patterns different from crescentic glomerulonephritis, and to favor the development of a consensual therapeutic approach. In this article, in addition to personal data, we will review recent findings on patient clinical phenotypes based on ANCA, genetics and the impact of biological drugs on disease management.

Introduction: Artificial intelligence (AI) integration in nephropathology has been growing rapidly in recent years, facing several challenges including the wide range of histological techniques used, the low occurrence of certain diseases, and the need for data sharing. This narrative review retraces the history of AI in nephropathology and provides insights into potential future developments. Methods: Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about automated image analysis or the application of an AI algorithm on non-neoplastic kidney histological samples were included and analyzed to extract information such as publication year, AI task, and learning type. Prepublication servers and reviews were not included. Results: Seventy-six (76) original research articles were selected. Most of the studies were conducted in the United States in the last 7 years. To date, research has been mainly conducted on relatively easy tasks, like single-stain glomerular segmentation. However, there is a trend towards developing more complex tasks such as glomerular multi-stain classification. Conclusion: Deep learning has been used to identify patterns in complex histopathology data and looks promising for the comprehensive assessment of renal biopsy, through the use of multiple stains and virtual staining techniques. Hybrid and collaborative learning approaches have also been explored to utilize large amounts of unlabeled data. A diverse team of experts, including nephropathologists, computer scientists, and clinicians, is crucial for the development of AI systems for nephropathology. Collaborative efforts among multidisciplinary experts result in clinically relevant and effective AI tools.

Introduction: Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions. Areas covered: This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions. Expert commentary: Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

AA amyloidosis may complicate several chronic inflammatory conditions. From a clinical point of view, causality between inflammatory pathology and AA amyloidosis can be assumed because of the data described in the literature; some of the best known include rheumatoid arthritis, ankylosing spondylitis, inflammatory bowel disease, and chronic infections. Singles cases of inflammatory diseases have been found at AA amyloidosis. Causality becomes more plausible if at least two different cases with AA amyloidosis are both found to have the same rare inflammatory disease. We describe the case of a patient with primary sclerosing cholangitis (PSC) with development of AA amyloidosis conditioning a nephrotic syndrome, likely secondary to failure to control the chronic inflammatory process. Only two cases in the literature describe the association of this rare disease and the appearance of AA amyloidosis. The treatment of AA amyloidosis consists in treating the underlying inflammatory disorder; to date, few effective treatments are available for PSC. Therefore, and in view of the limited data in the literature, we believe it is important to describe its association.

Introduction: Freehand renal biopsy represents a valid alternative to the most widespread ultrasonography-guided technique, although some concerns can derive from the possible increased complication rate and lower adequacy rate. Objectives: In the present audit study, efficacy of freehand method have been established through the analysis of 328 consecutive renal biopsies in 322 patients, instead the safety of the procedure was assessed in 196 patients. Patients and Methods: We retrospectively reviewed hospital databases of all patients who underwent a percutaneous renal biopsy over an 18 years’ period at Santa Marta and Santa Venera hospital in Acireale. Results: The procedure led to a definitive diagnosis in the majority of cases (98.48%), being uninformative only in 5 out of 328 cases (1.52%). Comparing these results against a Proforma, resulting from analysis of best literature reports for the items studied, adverse event rates were similar. Conclusion: Freehand renal biopsy resulted a good option to obtain renal tissue, without serious side effects. We argue about safety and we prefer to reserve this invasive procedure to selected cases, avoiding renal biopsy if biochemical and instrumental data allow a definitive diagnosis as well as in high risk patients. Our policy protects patients from the adverse effects that can result from kidney biopsy.

Background and Objective: Digital pathology represents an invaluable source of information and a long-term investment with high returns, with the possible deployment of artificial intelligence (AI) tools for both the clinical and research activity. Moreover, the rising nosological complexity of the oncologic diseases, e.g., lung cancer, is stressing the need of integration among different subspecialities (e.g., radiology, molecular biology, and immuno-oncology) for the final characterization of cancer. In this setting, digital pathology can play a pivotal role in the "integration" of these different competencies, and the application of AI for prognostic/predictive purposes can represent a further "third" revolution in pathology. The objective of the present review is to provide an updated overview of the possible role of digital and integrative pathology in detecting gene mutations and, especially, translocations in different types of tumors, focusing on the promising implications that this advancement can have in lung cancer characterization. Methods: A systematic literature search was conducted on different research engines (PubMed, IEEE Xplore, dblp, ACM digital library, Inspec) over a 15-year interval from January 1, 2006 to October 31, 2021 selecting only English-language articles to highlight the possible diagnostic and prognostic role of digital pathology tools in detecting gene mutations and, especially, translocations in different types of tumors. Key Content and Findings: Digital pathology tools already demonstrated a role in the detection of specific mutations and translocations in different types of cancer, both in a targeted (e.g., liver/thyroid carcinoma) and in an agnostic (e.g., MSI) setting. In lung cancer, AI showed the capability of highlighting specific subset of mutations (STK11, EGFR, FAT1, SETBP1, KRAS, and TP53) from whole slide imaging (WSI), with the translocation field representing a promising frontier, with some gene rearrangement (e.g.

Fine-needle aspiration biopsies (FNA) represent the gold standard to exclude the malignant nature of thyroid nodules. After cytomorphology, 20–30% of cases are deemed “indeterminate for malignancy” and undergo surgery. However, after thyroidectomy, 70–80% of these nodules are benign. The identification of tools for improving FNA’s diagnostic performances is explored by matrix-assisted laser-desorption ionization mass spectrometry imaging (MALDI-MSI). A clinical study was conducted in order to build a classification model for the characterization of thyroid nodules on a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/malignant cells. The model had optimal performances in the internal validation set (n = 70), with 100.0% (95% CI = 83.2–100.0%) sensitivity and 96.0% (95% CI = 86.3–99.5%) specificity. The external validation (n = 170) showed a specificity of 82.9% (95% CI = 74.3–89.5%) and a sensitivity of 43.1% (95% CI = 30.9–56.0%). The performance of the model was hampered in the presence of poor and/or noisy spectra. Consequently, restricting the evaluation to the subset of FNAs with adequate cellularity, sensitivity improved up to 76.5% (95% CI = 58.8–89.3). Results also suggest the putative role of MALDI-MSI in routine clinical triage, with a three levels diagnostic classification that accounts for an indeterminate gray zone of nodules requiring a strict follow-up.

Importance: Identifying new prognostic features in colon cancer has the potential to refine histopathologic review and inform patient care. Although prognostic artificial intelligence systems have recently demonstrated significant risk stratification for several cancer types, studies have not yet shown that the machine learning-derived features associated with these prognostic artificial intelligence systems are both interpretable and usable by pathologists. Objective: To evaluate whether pathologist scoring of a histopathologic feature previously identified by machine learning is associated with survival among patients with colon cancer. Design, Setting, and Participants: This prognostic study used deidentified, archived colorectal cancer cases from January 2013 to December 2015 from the University of Milano-Bicocca. All available histologic slides from 258 consecutive colon adenocarcinoma cases were reviewed from December 2021 to February 2022 by 2 pathologists, who conducted semiquantitative scoring for tumor adipose feature (TAF), which was previously identified via a prognostic deep learning model developed with an independent colorectal cancer cohort. Main Outcomes and Measures: Prognostic value of TAF for overall survival and disease-specific survival as measured by univariable and multivariable regression analyses. Interpathologist agreement in TAF scoring was also evaluated. Results: A total of 258 colon adenocarcinoma histopathologic cases from 258 patients (138 men [53%]; median age, 67 years [IQR, 65-81 years]) with stage II (n = 119) or stage III (n = 139) cancer were included. Tumor adipose feature was identified in 120 cases (widespread in 63 cases, multifocal in 31, and unifocal in 26). For overall survival analysis after adjustment for tumor stage, TAF was independently prognostic in 2 ways: TAF as a binary feature (presence vs absence: hazard ratio [HR] for presence of TAF, 1.55 [95% CI, 1.07-2.25]; P = .02) and TAF as a semiquantitative categorica

Objective. The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department. Methods. Two NLP-based automatic coding systems (support vector machine, SVM, and long-short term memory, LSTM) were trained and applied to a series of narrative reports. Results. The 1163 cases were tested with both algorithms, showing good performances in terms of accuracy, precision, recall, and F1 score, with SVM showing slightly better performances as compared to LSTM (0.84, 0.87, 0.83, 0.82 vs 0.83, 0.85, 0.83, 0.82, respectively). The integration of an explainability allowed identification of terms and groups of words of importance, enabling fine-tuning, balancing semantic meaning and model performance. Conclusions. AI tools allow the automatic SNOMED-CT labeling of the pathology archives, providing a retrospective fix to the large lack of organization of narrative reports.

The number of patients awaiting a kidney transplant is constantly rising but lack of organs leads kidneys from extended criteria donors (ECD) to be used to increase the donor pool. Pre-transplant biopsies are routinely evaluated through the Karpinski-Remuzzi score but consensus on its correlation with graft survival is controversial. This study aims to test a new diagnostic model relying on digital pathology to evaluate pre-transplant biopsies and to correlate it with graft outcomes. Pre-transplant biopsies from 78 ECD utilized as single kidney transplantation were scanned, converted to whole-slide images (WSIs), and reassessed by two expert nephropathologists using the Remuzzi-Karpinski score. The correlation between graft survival at 36 months median follow-up and parameters assigned by either WSI or glass slide score (GSL) by on-call pathologists was evaluated, as well as the agreement between the GSL and the WSIs score. No relation was found between the GSL assessed by on-call pathologists and graft survival (P = 0.413). Conversely, the WSI score assigned by the two nephropathologists strongly correlated with graft loss probability, as confirmed by the ROC curves analysis (DeLong test P = 0.046). Digital pathology allows to share expertise in the transplant urgent setting, ensuring higher accuracy and favoring standardization of the process. Its employment may significantly increase the predictive capability of the pre-transplant biopsy evaluation for ECD, improving the quality of allocation and patient safety.

Renal amyloidosis is a rare condition caused by the progressive accumulation of misfolded proteins within glomeruli, vessels, and interstitium, causing functional decline and requiring prompt treatment due to its significant morbidity and mortality. Congo red (CR) stain on renal biopsy samples is the gold standard for diagnosis, but the need for polarized light is limiting the digitization of this nephropathology field. This study explores the feasibility and reliability of CR fluorescence on virtual slides (CRFvs) in evaluating the diagnostic accuracy and proposing an automated digital pipeline for its assessment. Whole-slide images from 154 renal biopsies with CR were scanned through a Texas red fluorescence filter (NanoZoomer S60, Hamamatsu) at the digital Nephropathology Center of the Istituto di Ricovero e Cura a Carattere Scientifico San Gerardo, Monza, Italy, and evaluated double-blinded for the detection and quantification through the amyloid score and a custom ImageJ pipeline was built to automatically detect amyloid-containing regions. Interobserver agreement for CRFvs was optimal (k = 0.90; 95% CI, 0.81-0.98), with even better concordance when consensus-based CRFvs evaluation was compared to the standard CR birefringence (BR) (k = 0.98; 95% CI, 0.93-1). Excellent performance was achieved in the assessment of amyloid score overall by CRFvs (weighted k = 0.70; 95% CI, 0.08-1), especially within the interstitium (weighted k = 0.60; 95% CI, 0.35-0.84), overcoming the misinterpretation of interstitial and capsular collagen BR. The application of an automated digital pathology pipeline (Streamlined Pipeline for Amyloid detection through CR fluorescence Digital Analysis, SPADA) further increased the performance of pathologists, leading to a complete concordance with the standard BR. This study represents an initial step in the validation of CRFvs, demonstrating its general reliability in a digital nephropathology center. The computational method used in this stu

Context Despite the reluctance to invest and the challenging estimation of necessary supporting costs, optimising the archives seems to be one of the hottest topics in the future management of the pathology laboratories. Historically, archives were only partially designed to securely store and organise tissue specimens, and tracking systems were often flawed, posing significant risks to patients' health and legal ramifications for pathologists. Objective The current review explores the available data from the literature on archives' management in pathology, including comprehensive business plans, structure setup, outfit, inventories, ongoing conservation and functional charges. Data sources Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about the archiving process and storage were included and analysed to extract information. Prepublication servers were ignored. Italian Institutional Regional databases for public competitive bidding processes were queried too. Conclusions A new emergent feeling in the pathology laboratory is growing for archives management; the digital pathology era is a great opportunity to apply innovation to tracking systems and samples preservation. The main aim is a critical evaluation of the return of investment in developing automatic and tracked archiving processes for improving not only quality, efficacy and efficiency of the labs but also patients' healthcare.

Objective: The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered. Methods: On 21 July 2022, an initial conference call was held on Zoom to identify the main issues to be discussed during the face-to-face meeting. The final summit was divided into four different sessions: (I) the definition of DP, (II) practical applications of DP, (III) the use of AI in DP, (IV) DP and education. Results: Essential requirements for the implementation of DP are a fully tracked and automated workflow, selection of the appropriate scanner based on the specific needs of each department, and a strong commitment combined with coordinated teamwork (pathologists, technicians, biologists, IT service and industries). This could reduce human error, leading to the application of AI tools for diagnosis, prognosis and prediction. Open challenges are the lack of specific regulations for virtual slide storage and the optimal storage solution for large volumes of slides. Conclusion: Teamwork is key to DP transition, including close collaboration with industry. This will ease the transition and help bridge the gap that currently exists between many labs and full digitisation. The ultimate goal is to improve patient care.

Aims: Diabetic nephropathy is a major consequence of inflammation developing in type 1 diabetes, with interleukin-8 (IL-8)-CXCR1/2 axis playing a key role in kidney disease progression. In this study, we investigated the therapeutic potential of a CXCR1/2 non-competitive allosteric antagonist (Ladarixin) in preventing high glucose-mediated injury in human podocytes and epithelial cells differentiated from renal stem/progenitor cells (RSC) cultured as nephrospheres. Materials and Methods: We used human RSCs cultured as nephrospheres through a sphere-forming functional assay to investigate hyperglycemia-mediated effects on IL-8 signalling in human podocytes and tubular epithelial cells. Results: High glucose impairs RSC self-renewal, induces an increase in IL-8 transcript expression and protein secretion and induces DNA damage in RSC-differentiated podocytes, while exerting no effect on RSC-differentiated epithelial cells. Accordingly, the supernatant from epithelial cells or podocytes cultured in high glucose was able to differentially activate leucocyte-mediated secretion of pro-inflammatory cytokines, suggesting that the crosstalk between immune and non-immune cells may be involved in disease progression in vivo. Conclusions: Treatment with Ladarixin during RSC differentiation prevented high glucose-mediated effects on podocytes and modulated either podocyte or epithelial cell-dependent leucocyte secretion of pro-inflammatory cytokines, suggesting CXCR1/2 antagonists as possible pharmacological approaches for the treatment of diabetic nephropathy.

Thyroid fine-needle aspiration (FNA) is a commonly used diagnostic cytological procedure in pediatric patients for the evaluation of thyroid nodules, triaging them for the detection of thyroid cancer. In recent years, greater attention has been paid to thyroid FNA in this setting, including the use of updated ultrasound score algorithms to improve accuracy and yield, especially considering the theoretically higher risk of malignancy of these lesions compared with the adult population, as well as to minimize patient discomfort. Moreover, molecular genetic testing for thyroid disease is an expanding field of research that could aid in distinguishing benign from cancerous nodules and assist in determining their clinical management. Finally, artificial intelligence tools can help in this task by performing a comprehensive analysis of all the obtained data. These advancements have led to greater reliance on FNA as a first-line diagnostic tool for pediatric thyroid disease. This review article provides an overview of these recent developments and their impact on the diagnosis and management of thyroid nodules in children.

Background: Programmed death-ligand 1 (PD-L1) checkpoint inhibitors represent a mainstay of therapy in head and neck squamous cell cancer (HNSCC). However, little is known about the influence of combined therapy on PD-L1 expression. The study aims to gather evidence on this topic. Methods: A systematic search was carried out in electronic databases Pubmed-MEDLINE and Embase to retrieve studies on the comparison of PD-L1 expression before and after conventional therapy. Data were extracted and a quantitative analysis with pooled odds ratios (ORs) was performed when applicable. Results: Of 5688 items, 15 were finally included. Only a minority of studies assessed PD-L1 with the recommended combined positive score (CPS). The results are highly heterogeneous, with some studies reporting an increase in PD-L1 expression and others reporting a decrease. Three studies allowed for quantitative analysis and showed a pooled OR of 0.49 (CI 0.27–0.90). Conclusions: From the present evidence, a clear conclusion towards an increase or decrease in PD-L1 expression after combined therapy cannot be drawn, but even with few studies available, a trend towards an increase in expression in tumor cells at a cutoff of 1% can be noted in patients undergoing platinum-based therapy. Future studies will provide more robust data on the effect of combined therapy on PD-L1 expression.

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.

Anti-glomerular basement membrane (anti-GBM) disease is a rare life-threatening small vessel vasculitis that typically affects the capillaries of kidneys and lungs, with most of patients developing rapidly progressive crescentic glomerulonephritis, and 40%-60% concomitant alveolar haemorrhage. It is caused by the deposition in alveolar and glomerular basement membrane of circulating autoantibodies directed against antigens intrinsic to the basement membrane. The exact mechanism that induces the formation of autoantibodies is unknown, but probably environmental factors, infections or direct damage to kidneys and lungs may trigger the autoimmune response in genetically susceptible individuals. Initial therapy includes corticosteroids and cyclophosphamide to prevent autoantibodies production, and plasmapheresis to remove the circulating autoantibodies. Good renal outcomes may be achieved by a prompt treatment initiation. However, when patients present with severe renal failure requiring dialysis or with a high proportion of glomerular crescents at biopsy, renal outcomes are bad. Relapses are rare and when renal involvement is present, the suspect of concomitant diseases, such as ANCA-associated vasculitis and membranous nephropathy, should be raised. Imlifidase is showing promising results, which if confirmed will cause a paradigm shift in the treatment of this disease.

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic examination, a time-consuming process requiring skilled staff. Thus, artificial intelligence (AI) has been exploited for identification of microorganisms. A systematic search was carried out using electronic databases looking for studies dealing with the application of AI to pathology microbiology specimens. Of 4596 retrieved articles, 110 were included. The main applications of AI regarded malaria (54 studies), bacteria (28), nematodes (14), and other protozoa (11). Most publications examined cytological material (95, 86%), mainly analyzing images acquired through microscope cameras (65, 59%) or coupled with smartphones (16, 15%). Various deep-learning strategies were used for the analysis of digital images, achieving highly satisfactory results. The published evidence suggests that AI can be reliably utilized for assisting pathologists in the detection of microorganisms. Further technologic improvement and availability of datasets for training AI-based algorithms would help expand this field and widen its adoption, especially for developing countries.

Aims: Identification and characterisation of monoclonal gammopathies of renal significance (MGRS) is critical for therapeutic purposes. Amyloidosis represents one of the most common forms of MGRS, and renal biopsy remains the gold standard for their classification, although mass spectrometry has shown greater sensitivity in this area. Methods: In the present study, a new in situ proteomic technique, matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), is investigated as an alternative to conventional laser capture microdissection MS for the characterisation of amyloids. MALDI-MSI was performed on 16 cases (3 lambda light chain amyloidosis (AL), 3 AL kappa, 3 serum amyloid A amyloidosis (SAA), 2 lambda light chain deposition disease (LCDD), 2 challenging amyloid cases and 3 controls). Analysis began with regions of interest labelled by the pathologist, and then automatic segmentation was performed. Results: MALDI-MSI correctly identified and typed cases with known amyloid type (AL kappa, AL lambda and SAA). A 'restricted fingerprint' for amyloid detection composed of apolipoprotein E, serum amyloid protein and apolipoprotein A1 showed the best automatic segmentation performance (area under the curve >0.7). Conclusions: MALDI-MSI correctly assigned minimal/challenging cases of amyloidosis to the correct type (AL lambda) and identified lambda light chains in LCDD cases, highlighting the promising role of MALDI-MSI for amyloid typing.

Noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) are low-risk thyroid lesions most often characterised by RAS-type mutations. The histological diagnosis may be challenging, and even immunohistochemistry and molecular approaches have not yet provided conclusive solutions. This study characterises a set of NIFTPs by Matrix-Assisted Laser Desorption/Ionisation (MALDI)-Mass Spectrometry Imaging (MSI) to highlight the proteomic signatures capable of overcoming histological challenges. Archived formalin-fixed paraffin-embedded samples from 10 NIFTPs (n = 6 RAS-mutated and n = 4 RAS-wild type) were trypsin-digested and analysed by MALDI-MSI, comparing their profiles to normal tissue and synchronous benign nodules. This allowed the definition of a four-peptide signature able to distinguish RAS-mutant from wild-type cases, the latter showing proteomic similarities to hyperplastic nodules. Moreover, among the differentially expressed signals, Peptidylprolyl Isomerase A (PPIA, 1505.8 m/z), which has already demonstrated a role in the development of cancer, was found overexpressed in NIFTP RAS-mutated nodules compared to wild-type lesions. These results underlined that high-throughput proteomic approaches may add a further level of biological comprehension for NIFTPs. In the future, thanks to the powerful single-cell detail achieved by new instruments, the complementary NGS-MALDI imaging sequence might be the correct methodological approach to confirm that the current NIFTP definition encompasses heterogeneous lesions that must be further characterised.

Background: The implementation of a fully digital workflow in any anatomic pathology department requires a complete conversion to a tracked system. Ensuring the strict correspondence of the material submitted for the analysis, from the accessioning to the reporting phase, is mandatory in the anatomic pathology laboratory, especially when implementing the digital pathology for primary histological diagnosis. The proposed solutions, up to now, rely on the verification that all the materials present in the glass slide are also present in the whole slide images (WSIs). Although different methods have already been implemented for this purpose (e.g., the 'macroimage' of the digital slide, representing the overview of the glass slide), the recent introduction of a device to capture the cut surface of paraffin blocks put the quality control of the digital workflow a step forward, allowing to match the digitized slide with the corresponding block. This system may represent a reliable, easy-to-use alternative to further reduce tissue inconsistencies between material sent to the lab and the final glass slides or WSIs. Methods: The Anatomic Pathology of the Gravina Hospital in Caltagirone, Sicily, Italy, has implemented the application of the BlocDoc devices (SPOT Imaging, Sterling Heights, USA) in its digital workflow. The instruments were positioned next to every microtome/sectioning station, with the possibility to capture the 'normal' and the polarized image of the cut surface of the blocks directly by the technician. The presence of a monitor in the BlocDoc device allowed the technician to check the concordance between the cut surface of the block and the material on the corresponding slide. The link between BlocDoc and the laboratory information system, through the presence of the 2D barcode, allowed the pathologists to access the captured image of the cut surface of the block at the pathologist workstation, thus enabling the direct comparison between this image and the W

Digital pathology for the routine assessment of cases for primary diagnosis has been implemented by few laboratories worldwide. The Gravina Hospital in Caltagirone (Sicily, Italy), which collects cases from 7 different hospitals distributed in the Catania area, converted the entire workflow to digital starting from 2019. Before the transition, the Caltagirone pathology laboratory was characterized by a non-tracked workflow, based on paper requests, hand-written blocks and slides, as well as manual assembling and delivering of the cases and glass slides to the pathologists. Moreover, the arrangement of the spaces and offices in the department was illogical and under-productive for the linearity of the workflow. For these reasons, an adequate 2D barcode system for tracking purposes, the redistribution of the spaces inside the laboratory and the implementation of the whole-slide imaging (WSI) technology based on a laboratory information system (LIS)-centric approach were adopted as a needed prerequisite to switch to a digital workflow. The adoption of a dedicated connection for transfer of clinical and administrative data between different software and interfaces using an internationally recognised standard (Health Level 7, HL7) in the pathology department further facilitated the transition, helping in the integration of the LIS with WSI scanners. As per previous reports, the components and devices chosen for the pathologists’ workstations did not significantly impact on the WSI-based reporting phase in primary histological diagnosis. An analysis of all the steps of this transition has been made retrospectively to provide a useful “handy” guide to lead the digital transition of “analog”, non-tracked pathology laboratories following the experience of the Caltagirone pathology department. Following the step-by-step instructions, the implementation of a paperless routine with more standardized and safe processes, the possibility to manage the priority of the cases and to

The interest in implementing digital pathology (DP) workflows to obtain whole slide image (WSI) files for diagnostic purposes has increased in the last few years. The increasing performance of technical components and the Food and Drug Administration (FDA) approval of systems for primary diagnosis led to increased interest in applying DP workflows. However, despite this revolutionary transition, real world data suggest that a fully digital approach to the histological workflow has been implemented in only a minority of pathology laboratories. The objective of this study is to facilitate the implementation of DP workflows in pathology laboratories, helping those involved in this process of transformation to identify: a) the scope and the boundaries of the DP transformation; b) how to introduce automation to reduce errors; c) how to introduce appropriate quality control to guarantee the safety of the process and d) the hardware and software needed to implement DP systems inside the pathology laboratory. The European Society of Digital and Integrative Pathology (ESDIP) provided consensus-based recommendations developed through discussion among members of the Scientific Committee. The recommendations are thus based on the expertise of the panel members and on the agreement obtained after virtual meetings. Prior to publication, the recommendations were reviewed by members of the ESDIP Board. The recommendations comprehensively cover every step of the implementation of the digital workflow in the anatomic pathology department, emphasizing the importance of interoperability, automation and tracking of the entire process before the introduction of a scanning facility. Compared to the available national and international guidelines, the present document represents a practical, handy reference for the correct implementation of the digital workflow in Europe.

Objective: The American College of Radiology (ACR) and the European Thyroid Association (EU) have proposed two scoring systems for thyroid nodule classification. Here, we compared the ability of the two systems in triaging thyroid nodules for fine-needle aspiration (FNA) and tested the putative role of an approach that combines ultrasound features and cytology for the detection of malignant nodules. Design and Methods: The scores obtained with the ACR and EU Thyroid Imaging Reporting and Data Systems (TIRADS) from a prospective series of 480 thyroid nodules acquired from 435 subjects were compared to assess their performances in FNA triaging on the final cytological diagnosis. The US features that showed the highest contribution in discriminating benign nodules from malignancies were combined with cytology to improve its diagnostic performance. Results: FNA was recommended on 46.5% and 51.9% of the nodules using the ACR and EU-TIRADS scores, respectively. The ACR system demonstrated a higher specificity as compared to the EU-TIRADS (59.0% vs. 52.4%, p = 0.0012) in predicting >TIR3A/III (SIAPEC/Bethesda) nodules. Moreover, specific radiological features (i.e., echogenic foci and margins), combined with the cytological classes improved the specificity (97.5% vs. 91%, p < 0.0001) and positive predictive values (77.5% vs. 50.7%, p < 0.0001) compared to cytology alone, especially in the setting of indeterminate nodules (TIR3A/III and TIR3B/IV), maintaining an excellent sensitivity and negative predictive value. Conclusions: The ACR-TIRADS system showed a higher specificity compared to the EUTIRADS in triaging thyroid nodules. The use of specific radiological features improved the diagnostic ability of cytology.

Ultrasound scores are used to determine whether thyroid nodules should undergo Fine Needle Aspiration (FNA) or simple clinical follow-up. Different scores have been proposed for this task, with the American College of Radiology (ACR) TIRADS system being one of the most widely used. This study evaluates its ability in triaging thyroid nodules deserving FNA on a large prospective monocentric Italian case series of 493 thyroid nodules from 448 subjects. In ACR 1–2, cytology never prompted a surgical indication. In 59% of cases classified as TIR1c-TIR2, the FNA procedure could be ancillary, according to the ACR-TIRADS score. A subset (37.9%) of cases classified as TIR4-5 would not undergo FNA, according to the dimensional thresholds used by the ACR-TIRADS. Applying the ACR score, a total of 46.5% thyroid nodules should be studied with FNA. The ACR system demonstrated a sensitivity and specificity of 58.9% and 59% in the identification of patients with cytology ≥TIR3A, with a particularly high false negative rate for ACR classes ≥3 (44.8%, 43/96), which would dramatically decrease (7.3%, 7/96) if the dimensional criteria were not taken into account. In ACR 3–4–5, a correspondence with the follow-up occurred in 60.3%, 50.2% and 51.9% of cases. The ACR-TIRADS is a useful risk stratification tool for thyroid nodules, although the current dimensional thresholds could lead to an underestimation of malignant lesions. Their update might be considered in future studies to increase the screening performances of the system.

Nephropathy represents a major complication of Fabry Disease and its accurate characterization is of paramount importance in predicting the disease progression and assessing the therapeutic responses. The diagnostic process still relies on performing renal biopsy, nevertheless many efforts have been made to discover early reliable biomarkers allowing us to avoid invasive procedures. In this field, proteomics offers a sensitive and fast method leading to an accurate detection of specific pathological proteins and the discovery of diagnostic and prognostic biomarkers that reflect disease progression and facilitate the evaluation of therapeutic responses. Here, we report a review of selected literature focusing on the investigation of several proteomic techniques highlighting their advantages, limitations and future perspectives in their application in the routine study of Fabry Nephropathy.

Whole-slide imaging and virtual microscopy are useful tools implemented in the routine pathology workflow in the last 10 years, allowing primary diagnosis or second-opinions (telepathology) and demonstrating a substantial role in multidisciplinary meetings and education. The regulatory approval of this technology led to the progressive digitalization of routine pathological practice. Previous experiences on renal biopsies stressed the need to create integrate networks to share cases for diagnostic and research purposes. In the current paper, we described a virtual lab studying the routine renal biopsies that have been collected from 14 different Italian Nephrology centers between January 2014 and December 2019. For each case, light microscopy (LM) and immunofluorescence (IF) have been processed, analysed and scanned. Additional pictures (eg. electron micrographs) along with the final encrypted report were uploaded on the web-based platform. The number and type of specimens processed for every technique, the provisional and final diagnosis, and the turnaround-time (TAT) have been recorded. Among 826 cases, 4.5% were second opinion biopsies and only 4% were suboptimal/inadequate for the diagnosis. Transmission electron microscopy (TEM) has been performed on 41% of cases, in 22% changing the final diagnosis, in the remaining 78% contributed to the better definition of the disease. For light microscopy and IF the median TAT was of 2 working days, with only 8.6% with a TAT longer than 5 days. For TEM, the average TAT was 26 days (IQR 6–64). In summary, we systematically reviewed the 6-years long nephropathological experience of an Italian renal pathology service, where digital pathology is a definitive standard of care for the routine diagnosis of glomerulonephritides.

Lymphomatous infiltration of kidney parenchyma is a frequent complication of systemic hematologic malignancies and often shows subtle clinical presentation. Diffuse large B-cell lymphoma represents the most frequent form involving the kidney, with advanced stage at diagnosis, poor outcome, and risk for central nervous system relapse if not adequately treated. Kidney biopsy can provide specific and early detection of these cases, helping in the differential diagnosis with more frequent entities. Finally, further hematologic workup (bone marrow biopsy, complete blood cell count, and positron emission tomography) can distinguish secondary involvement of the kidney from the rarer kidney-limited forms, especially in patients without a previous diagnosis of lymphoma. Making a prompt and correct diagnosis directs the management of these cases and may improve the outcome, as described in the present report.