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.

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.

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.

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.

Differential Expression of NOTCH-1 and Its Molecular Targets in Response to Metronomic Followed by Conventional Therapy in a Patient with Advanced Triple-Negative Breast Cancer.

A group of 27 patients diagnosed with metastatic triple-negative breast cancer (mTNBC) was randomly distributed into two groups and underwent different lines of metronomic treatment (mCHT). The former group (N 14) received first-line mCHT and showed a higher overall survival rate than the second group (N 13), which underwent second-line mCHT. Analysis of one patient still alive from the first group, diagnosed with mTNBC in 2019, showed a complete metabolic response (CMR) after a composite approach implicating first-line mCHT followed by second-line epirubicin and third-line nab-paclitaxel, and was chosen for subsequent molecular characterization. We found altered expression in the cancer stemness-associated gene NOTCH-1 and its corresponding protein. Additionally, we found changes in the expression of oncogenes, such as MYC and AKT, along with their respective proteins. Overall, our data suggest that a first-line treatment with mCHT followed by MTD might be effective by negatively regulating stemness traits usually associated with the emergence of drug resistance.

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.

Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions.

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.

Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital Analysis.

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 study has the potential to facilitate the integration of spatial omics and artificial intelligence tools for the diagnosis of amyloidosis, streamlining its detection process.

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

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

Spatial resolution of renal amyloid deposits through MALDI-MSI: a combined digital and molecular approach to monoclonal gammopathies.

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.

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.

Lights on HBME-1: the elusive biomarker in thyroid cancer pathology.

Among the different ancillary immunohistochemical tools that pathologists may employ in thyroid nodules, the so-called Hector Battifora's 'MEsothelioma' 1 (HBME-1) staining is one of the most fascinating, since its real identity is currently unknown. In the present review, the different clinical applications of HBME-1 are analysed, with main emphasis on its role in thyroid pathology with overview on less impactful fields, such as haematopathology or mesothelial lesions. Different acceptable or good diagnostic performances were recorded for HBME-1 in thyroid pathology, being used in routine practice as one of the best tools to screen thyroid malignancy both in terms of sensitivity and specificity. From a speculative point of view, after many attempts to hunt the cryptic target antigen of this antibody, its identity still remains elusive. In this setting, the application of high-throughput technologies (mainly in situ proteomics) may be the exact route to improve the knowledge about the pathophysiology of HBME-1 and to finally unveil its true identity.

Monoclonal Gammopathy of Renal Significance: A Molecular Middle Earth between Oncology, Nephrology, and Pathology.

Background: The renal biopsy represents a cornerstone in the definition of monoclonal gammopathy of renal significance (MGRS), helping in identifying patients with sub-detectable neoplastic clones (MGUS) that would deserve aggressive chemotherapies. However, the rising complexity of this onco-nephrology field is significantly challenging the daily work of nephrologists and nephropathologists, leading to the formation of ultra-specialized international centers with dedicated personnel/instrumentation and stressing the need for a better understanding of the underlying molecular landscape of these entities. Summary: In this setting, the application of proteomic techniques, some with in situ capabilities (e.g., MALDI-MS imaging), for the investigation of the most challenging MGRS is progressively shedding light on the pathobiology of these diseases, providing new insights in the diagnosis and prognosis of these cases. This transformation is further enhanced by the application of next-generation digital pathology platforms, leading to a significant improvement of the cultural background for physicians thanks to second opinions, database and atlas creation, enhancement of diagnostic reports, with obvious repercussions for patients both in terms of turnaround time and appropriateness. Key Messages: The present review is aimed at bridging the gap between clinical questions (i.e., a better characterization of MGRS) and the molecular landscape of onco-nephrology entities.

Digital pathology for the routine diagnosis of renal diseases: a standard model.

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.

The spectrum of the cytopathological features of primary effusion lymphoma and human herpes virus 8-related lymphoproliferative disorders.

INTRODUCTION: Human herpes virus 8-related lymphoproliferative disorders are a complex and heterogeneous group of entities and some of them are eminently diagnosed by cytopathology. In a routine laboratory, these lesions account for less than 1% of the effusion fluids samples. However, they represent up to 30% of all the lymphoma diagnosis from effusion cytological samples and their consideration in the diagnostic flow chart is mandatory, especially in human immunodeficiency virus-positive patients. METHODS: A retrospective series of cytological specimens from cavity effusions (n = 605) were analysed. Five human herpes virus 8-related lymphoproliferative processes were recruited. A combination of morphological criteria (enhanced with May-Grünwald Giemsa staining), cell block-based immunocytochemistry and flow cytometry were undertaken for final characterisation. RESULTS: The identification of malignant cells may be difficult. Some specimens are particularly rich, easily leading to suspect a lymphoproliferative process, whereas in other cases, the presence of abundant reactive mesothelial cells, histiocytes, neutrophils, small reactive T and B lymphocytes may obscure the neoplastic process. The biological behaviour may be very heterogeneous and a standardised therapy for these cases is still lacking, although some patients may benefit from antiretroviral therapy in a human immunodeficiency virus setting. CONCLUSIONS: The present case series highlights some characteristic findings of these entities to reaffirm useful cytopathological diagnostic criteria, stressing the crucial role of the appropriate technical processing of effusion fluids to obtain the best performances.

Robot-assisted removal of a lymphocyst causing severe neuralgic pain and adductor atrophy.

Following a robot-assisted radical hysterectomy and pelvic lymphadenectomy for early-stage cervical cancer, a 53-year-old woman was diagnosed with a 50-mm right-sided pelvic lymphocyst by the use of vaginal ultrasonography. She gradually developed intermittent increasingly severe neuralgic pain mimicking a meralgia paresthetica. A neurolysis was proposed by the neurosurgeons. Awaiting this intervention, a pelvic MRI revealed a partial atrophy of the ipsilateral adductor muscles and a probable entrapment of the obturator nerve by the lymphocyst as an alternative cause of the pain. Using a four-arm da Vinci-S-HD robot the lymphocyst, located deep in the right obturator fossa and surrounding the obturator nerve, was completely removed, sparing the partially atrophic obturator nerve. No bleeding occurred. The surgery time was 95 min. At 10 months' follow-up the patient was relieved of her pain with no signs of a new lymphocyst.