Identification and validation of diagnostic cut-offs of the ELISpot assay for the diagnosis of invasive aspergillosis in high-risk patients.

OBJECTIVE: We investigated the performance of enzyme linked immunospot (ELISpot) assay for the diagnosis of invasive aspergillosis (IA) in high-risk patients with hematologic malignancies. METHODS: We prospectively enrolled two cohorts of patients undergoing intensive myelosuppressive or immunosuppressive treatments at high risk for IA. ELISpot was performed to detect Aspergillus-specific T cells producing Interleukin-10. RESULTS: In the discovery cohort, a derived cut-off of 40 spot forming cells (SFCs)/106 PBMCs has shown to correctly classify IA cases with a sensitivity and specificity of 89.5% and 88.6%, respectively. This cut-off is lowered to 25 SFC when considering the subset of possible IA patients, with sensitivity and specificity of 76% and 93%, respectively. The application of the 40 SFCs cut-off to the validation cohort resulted in a positivity rate of 83.3% in proven/probable cases and a negativity rate of 92.5% in possible/non-IA cases. Adopting the 25 SCFs cut-off, the assay resulted positive in 83.3% of proven/probable cases while it resulted negative in 66.7% of possible/non-IA cases. CONCLUSIONS: ELISpot shows promises in the diagnosis of IA and the possibility to use two distinct cut-offs with similar diagnostic performances according to patients' different pre-test probability of infection can widen its use in patients at risk.

Diagnostic Biomarkers in Renal Cell Tumors According to the Latest WHO Classification: A Focus on Selected New Entities.

The fifth edition of the World Health Organization (WHO) classification for urogenital tumors, released in 2022, introduces some novelties in the chapter on renal epithelial tumors compared to the previous 2016 classification. Significant changes include the recognition of new disease entities and adjustments in the nomenclature for certain pathologies. Notably, each tumor entity now includes minimum essential and desirable criteria for reliable diagnosis. This classification highlights the importance of biological and molecular characterization alongside traditional cytological and architectural features. In this view, immunophenotyping through immunohistochemistry (IHC) plays a crucial role in bridging morphology and genetics. This article aims to present and discuss the role of key immunohistochemical markers that support the diagnosis of new entities recognized in the WHO classification, focusing on critical topics associated with single markers, in the context of specific tumors, such as the clear cell capillary renal cell tumor (CCPRCT), eosinophilic solid and cystic renal cell carcinoma (ESC-RCC), and so-called "other oncocytic tumors", namely the eosinophilic vacuolated tumor (EVT) and low-grade oncocytic tumor (LOT). Their distinctive characteristics and immunophenotypic profiles, along with insights regarding diagnostic challenges and the differential diagnosis of these tumors, are provided. This state-of-the-art review offers valuable insights in biomarkers associated with novel renal tumors, as well as a tool to implement diagnostic strategies in routine practice.

Digital pathology structure and deployment in Veneto: a proof-of-concept study.

Nowadays pathology laboratories are worldwide facing a digital revolution, with an increasing number of institutions adopting digital pathology (DP) and whole slide imaging solutions. Despite indeed providing novel and helpful advantages, embracing a whole DP workflow is still challenging, especially for wide healthcare networks. The Azienda Zero of the Veneto Italian region has begun a process of a fully digital transformation of an integrated network of 12 hospitals producing nearly 3 million slides per year. In the present article, we describe the planning stages and the operative phases needed to support such a disruptive transition, along with the initial preliminary results emerging from the project. The ultimate goal of the DP program in the Veneto Italian region is to improve patients' clinical care through a safe and standardized process, encompassing a total digital management of pathology samples, easy file sharing with experienced colleagues, and automatic support by artificial intelligence tools.

2-Step-Scores with optional nephropathology for the prediction of adverse outcomes for brain-dead donor kidneys in Eurotransplant.

BACKGROUND AND HYPOTHESIS: The decision for acceptance or discard of the increasingly rare and marginal brain-dead donor kidneys in Eurotransplant (ET) countries has to be made without solid evidence. Thus, we developed and validated flexible clinicopathological scores called 2-Step Scores for the prognosis of delayed graft function (DGF) and one-year death-censored transplant loss (1y-tl) reflecting the current practice of six ET countries including Croatia and Belgium. METHODS: The training set was n=620 for DGF and n=711 for 1y-tl, with validation sets n=158 and n=162. In step 1, stepwise logistic regression models including only clinical predictors were used to estimate the risks. In step 2, risk estimates were updated for statistically relevant intermediate risk percentiles with nephropathology. RESULTS: Step 1 revealed an increased risk of DGF with increased cold ischaemia time, donor and recipient BMI, dialysis vintage, number of HLA-DR mismatches or recipient CMV IgG positivity. On the training and validation set, c-statistics were 0.672 and 0.704, respectively. At a range between 18% and 36%, accuracy of DGF-prognostication improved with nephropathology including number of glomeruli and Banff cv (updated overall c statistics of 0.696 and 0.701, respectively).Risk of 1y-tl increased in recipients with cold ischaemia time, sum of HLA-A. -B, -DR mismatches and donor age. On training and validation sets, c-statistics were 0.700 and 0.769, respectively. Accuracy of 1y-tl prediction improved (c-statistics = 0.706 and 0.765) with Banff ct. Overall, calibration was good on the training, but moderate on the validation set; discrimination was at least as good as established scores when applied to the validation set. CONCLUSION: Our flexible 2-Step Scores with optional inclusion of time-consuming and often unavailable nephropathology should yield good results for clinical practice in ET, and may be superior to established scores. Our scores are adaptable to donation after cardiac death and perfusion pump use.

Digital Pathology Applications for PD-L1 Scoring in Head and Neck Squamous Cell Carcinoma: A Challenging Series.

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.

Pathology Laboratory Archives: Conservation Quality of Nucleic Acids and Proteins for NSCLC Molecular Testing.

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.

Forensic value of soft tissue detachments from the hyoid bone in death due to strangulation asphyxia.

BACKGROUND: There are no unequivocal histopathological findings for the diagnosis of fatal asphyxia due to neck compression. From the observation of a series of asphyxiation cases, we noted, during microscopic analysis, a high frequency of "detachment" of soft tissues from the hyoid bone. This specifically refers to the presence of an optical space between the surface of the hyoid bone and soft tissues. OBJECTIVES: We aimed to evaluate the detachment of soft tissues from the hyoid bone as specific histological evidence of death due to strangulation asphyxia. MATERIAL AND METHODS: Ten blocks were taken from deaths due to external mechanical compression of the neck (strangulation asphyxia, group A), 22 blocks were taken from deaths for other causes without trauma to the neck (group B), and 38 blocks were obtained from living subjects that have undergone laryngectomies (group C). The presence/absence of detachments were compared between the 3 groups (A, B and C) using Fisher's exact test. RESULTS: The detachment of soft tissues from the hyoid bone was observed in 5 cases (50%) in group A, 6 cases (27.2%) in group B, and 17 cases (44.3%) in group C. The sensitivity and specificity of the presence of the detachment in group A were 0.5 (95% confidence interval (95% CI): 0.38-0.62) and 0.57 (95% CI: 0.45-0.69), respectively. The comparison between the 3 groups and the presence/absence of soft tissue detachment showed no statistically significant differences between the groups (p = 0.329), clarifying that soft tissue detachment is a nonspecific variable for all 3 situations. CONCLUSIONS: Detachment of soft tissues has poor value as a single element to favor the diagnosis of asphyxia due to violent compression of the neck and should be interpreted as an artifactual finding, unrelated to the neck injury or injury vitality.

TROP-2, NECTIN-4 and predictive biomarkers in sarcomatoid and rhabdoid bladder urothelial carcinoma.

Introduction: The surface protein TROP-2/TACSTD2 and the cell adhesion protein NECTIN-4/NECTIN4 are responsible for the efficacy of anticancer therapies based on antibody-drug conjugates (ADC) targeting intracellular microtubules. In contrast with common histologic subtypes of bladder urothelial carcinoma (BUC), little is known of TROP-2 and NECTIN-4 expression in sarcomatoid and rhabdoid BUC. Aims: In this study, we aimed to analyze TROP-2 and NECTIN-4 expression and additional predictive biomarkers by immunohistochemistry and fluorescence in situ hybridization (FISH) on 35 undifferentiated BUC (28 sarcomatoid and 7 rhabdoid). Wide genomic investigation was also performed on 411 BUC cases of the PanCancer Atlas, focusing on genes related to the microtubule pathways. Results: Seven of 35 (20%) undifferentiated BUC showed expression of TROP-2. NECTIN-4 was expressed in 10 cases (29%). Seven cases (20%) co-expressed TROP-2 and NECTIN-4. HER-2 FISH was amplified in 5 cases (14%) while HER-2 immunoexpression was observed in 14 cases (40%). PD-L1 scored positive for combined proportion score (CPS) in 66% of cases and for tumor proportion score (TPS) in 51% of cases. Pan-NTRK1-2/3 was elevated in 9 cases (26%) and FGFR-2/3 was broken in 7 of 35 cases (20%). Of 28 sarcomatoid BUC, 9 (32%) were negative for all (TROP-2, NECTIN-4, PD-L1, HER-2, FGFR and pan-NTRK) biomarkers and 3 (11%) expressed all five biomarkers. Among cases with rhabdoid dedifferentiation, 1 of 7 (14%) showed activation of all biomarkers, whereas 2 of 7 (28%) showed none. The mRNA analysis identified microtubule-related genes and pathways suitable for combined ADC treatments in BUC. Conclusion: Sarcomatoid and rhabdoid BUC do harbor positive expression of the ADC targets TROP-2 or NECTIN-4 in a relatively modest subset of cases, whereas the majority do not. Different combinations of other positive biomarkers may help the choice of medical therapies. Overall, these findings have important clinical implications for targeted therapy for BUC.

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images.

Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability. Multiple papers have presented systems for the automatic quantification of TPS, but none report on the task of determining cell-level PD-L1 expression and often reserve their evaluation to a single PD-L1 monoclonal antibody or clinical center. In this paper, we report on a deep learning algorithm for detecting PD-L1 negative and positive tumor cells at a cellular level and evaluate it on a cell-level reference standard established by six readers on a multi-centric, multi PD-L1 assay dataset. This reference standard also provides for the first time a benchmark for computer vision algorithms. In addition, in line with other papers, we also evaluate our algorithm at slide-level by measuring the agreement between the algorithm and six pathologists on TPS quantification. We find a moderately low interobserver agreement at cell-level level (mean reader-reader F1 score = 0.68) which our algorithm sits slightly under (mean reader-AI F1 score = 0.55), especially for cases from the clinical center not included in the training set. Despite this, we find good AI-pathologist agreement on quantifying TPS compared to the interobserver agreement (mean reader-reader Cohen's kappa = 0.54, 95% CI 0.26-0.81, mean reader-AI kappa = 0.49, 95% CI 0.27-0.72). In conclusion, our deep learning algorithm demonstrates promise in detecting PD-L1 expression at a cellular level and exhibits favorable agreement with pathologists in quantifying the tumor proportion score (TPS). We publicly release our models for use via the Grand-Challenge platform.

Benchmarking digital displays (monitors) for histological diagnoses: the nephropathology use case.

AIM: The digital transformation of the pathology laboratory is being continuously sustained by the introduction of innovative technologies promoting whole slide image (WSI)-based primary diagnosis. Here, we proposed a real-life benchmark of a pathology-dedicated medical monitor for the primary diagnosis of renal biopsies, evaluating the concordance between the 'traditional' microscope and commercial monitors using WSI from different scanners. METHODS: The College of American Pathologists WSI validation guidelines were used on 60 consecutive renal biopsies from three scanners (Aperio, 3DHISTECH and Hamamatsu) using pathology-dedicated medical grade (MG), professional grade (PG) and consumer-off-the-shelf (COTS) monitors, comparing results with the microscope diagnosis after a 2-week washout period. RESULTS: MG monitor was faster (1090 vs 1159 vs 1181 min, delta of 6-8%, p<0.01), with slightly better performances on the detection of concurrent diseases compared with COTS (κ=1 vs 0.96, 95% CI=0.87 to 1), but equal concordance to the commercial monitors on main diagnosis (κ=1). Minor discrepancies were noted on specific scores/classifications, with MG and PG monitors closer to the reference report (r=0.98, 95% CI=0.83 to 1 vs 0.98, 95% CI=0.83 to 1 vs 0.91, 95% CI=0.76 to 1, κ=0.93, 95% CI=077 to 1 vs 0.93, 95% CI=0.77 to 1 vs 0.86, 95% CI=0.64 to 1, κ=1 vs 0.50, 95% CI=0 to 1 vs 0.50, 95% CI=0 to 1, for IgA, antineutrophilic cytoplasmic antibody and lupus nephritis, respectively). Streamlined Pipeline for Amyloid detection through congo red fluorescence Digital Analysis detected amyloidosis on both monitors (4 of 30, 13% cases), allowing detection of minimal interstitial deposits with slight overestimation of the Amyloid Score (average 6 vs 7). CONCLUSIONS: The digital transformation needs careful assessment of the hardware component to support a smart and safe diagnostic process. Choosing the display for WSI is critical in the process and requires adequate planning.

Donors risk assessment in transplantation: From the guidelines to their real-world application.

Transplantation of an organ from a donor carries an unavoidable risk of tumor transmission. The need to extend the donor pool increases the use of organs from donors with malignancies and potential disease transmission is a constant tension influencing donor suitability decisions. Current classification systems for the assessment of donor malignancy transmission risk have evolved from reports of potential transmission events in recipients to national donation and transplant surveillance agencies. Although the risk of malignancy transmission is very low in the general transplant setting it must constantly be balanced with the transplant benefits. Guidelines are mainly based on large registries and sparse case reports of transmission, so they cannot cover all the possible situations. For this reason, in 2004 in Italy, the National Transplant Center gave rise to the Second Opinion Service, charged by the Ministry of Health, by structuring expertise in diagnostic oncology and risk transmission and making it available to the Italian Transplant Centers. In this paper the registry of the Italian Oncological Second Opinion was reviewed, from 2016 to 2018, to detail the most frequent and problematic neoplastic topics addressed, those are separately reported and discussed. Furthermore, a review of the most recent strategies and risk stratification is provided, according to the most recent literature evidence and to the European Guidelines.

The Puzzle of Preimplantation Kidney Biopsy Decision-Making Process: The Pathologist Perspective.

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.

Artificial intelligence-based algorithms for the diagnosis of prostate cancer: A systematic review.

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.

Natural Language Processing to extract SNOMED-CT codes from pathological reports.

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.