Adjustable-tip needles versus fixed-tip needles in radiofrequency ablation of symptomatic benign thyroid nodules: a single-center Italian experience.

PURPOSE: In this retrospective, observational study we aim to compare the outcomes of the RFA treatment of benign thyroid nodules, carried out respectively with the standard fixed-needle approach (FTN) and the adjustable-tip needle technique (ATN), considered a more tailored, quicker and easier technical approach. METHODS: We enrolled 36 patients who underwent RFA treatment of symptomatic, benign, thyroid nodule, 18 with the ATN and 18 with the FTN approach, respectively. Data about absolute volume reduction, volume reduction rate (VRR) and success rate (defined as VRR ≥ 50%), after 1, 3 and 6 months of follow-up were compared. RESULTS: Our study suggested no substantial difference between the approaches, up to 6 months of follow-up, both in terms of absolute reduction (p = 0.27) and VRR (p = 0.14). These results were confirmed when the success rates, both in terms of 50%-reduction (p = 0.12) and absolute reduction (p = 0.42), was considered. Only at the 6-month evaluation, the FTN procedure showed a better success rate, yet without statistical significance (88.9% vs. 61.1%, p = 0.12). No difference emerged both in terms of patients' satisfaction and safety. CONCLUSION: Our small experience suggested no substantial difference between ATN and FTN, in terms of outcomes. On the other hand, ATN was considered to be more straightforward and could consequently allow for a shorter operator learning curve.

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.

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.

Eicosapentaenoic Acid: between Cardiovascular Benefits and the Risk of Atrial Fibrillation.

In recent years, scientific research has increasingly focused on the cardiovascular benefits of omega-3 polyunsaturated fatty acids (n-3 PUFAs) supplements. The most promising results emerged from the new trials on a high-dose eicosapentaenoic acid (EPA)-only approach, instead of the previously prescribed therapy with EPA + docosahexaenoic acid (DHA). The evidence of the reduction of cardiovascular events in patients at high cardiovascular risk with EPA is intriguing. However, physicians have expressed concern about the potential high risk of atrial fibrillation (AF) occurrence due to such an approach. This study aims to investigate the current evidence on the cardiovascular benefits of EPA and its association with atrial arrhythmogenesis. Current guidelines consider EPA (as IPE) treatment for selected patients but with no specific indication regarding AF risk evaluation. We propose a flowchart that could be a starting point for the future development of an algorithm to help clinicians to prescribe EPA safely and effectively, especially in patients at high risk of incipient AF.

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.

A Prospective Multicenter Study Examining the Relationship Between Thyroid Cancer Treatment Outcomes and the Presence of Autoimmune Thyroiditis.

Background: There is some controversy on the potential relationship between autoimmune processes and clinicopathologic features as well as prognosis of differentiated thyroid cancer (DTC), and the evidence is limited by its largely retrospective nature. We examined the relationship between the presence of autoimmune thyroiditis (AT) and 1-year thyroid cancer treatment outcomes in a large multicenter study using prospectively collected data. Methods: We included data from consecutive DTC patients enrolled in the Italian Thyroid Cancer Observatory (ITCO) database (NCT04031339). We divided the groups according to the presence (AT) or absence (no autoimmune thyroiditis [noAT]) of associated AT. We used propensity score matching to compare the clinical features and outcomes between the two groups at 1-year follow-up. Results: We included data from 4233 DTC patients, including 3172 (75%) females. The American Thyroid Association (ATA) risk levels were as follows: 51% (2160/4233) low risk, 41.3% (1750/4233) intermediate risk, and 7.6% (323/4233) high risk. There were 1552 patients (36.7%) who had AT. Before propensity score matching, AT patients were significantly younger and had a smaller and bilateral tumor (p < 0.0001). Patients with AT more frequently fell into the low- and intermediate-risk categories, while the ATA high risk was more frequent among noAT patients (p = 0.004). After propensity score matching, patients with AT more frequently showed evidence of disease (structural/biochemical incomplete response) versus excellent/indeterminate response, compared with patients without AT (7.3% vs. 4.5%, p = 0.001), with an odds ratio of 1.86 ([confidence interval: 1.3-2.6], p = 0.0001). However, when considering only structural persistence as the outcome, no statistically significant differences were observed between patients with or without AT (3.4% vs. 2.7%, p = 0.35). The elevated risk associated with the ATA intermediate and high risk at diagnosis remained consistently statistically significant. Conclusions: In this large prospective series, biochemical persistence was more frequent, at 1-year follow-up, in AT patients. However, there was no significant association between the presence of AT and structural persistence of disease. These findings may be explained by the presence of a residual thyroid tissue.

Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy.

BACKGROUND AND OBJECTIVE: The Oxford Classification for IgA nephropathy is the most successful example of an evidence-based nephropathology classification system. The aim of our study was to replicate the glomerular components of Oxford scoring with an end-to-end deep learning pipeline that involves automatic glomerular segmentation followed by classification for mesangial hypercellularity (M), endocapillary hypercellularity (E), segmental sclerosis (S) and active crescents (C). METHODS: A total number of 1056 periodic acid-Schiff (PAS) whole slide images (WSIs), coming from 386 kidney biopsies, were annotated. Several detection models for glomeruli, based on the Mask R-CNN architecture, were trained on 587 WSIs, validated on 161 WSIs, and tested on 127 WSIs. For the development of segmentation models, 20,529 glomeruli were annotated, of which 16,571 as training and 3958 as validation set. The test set of the segmentation module comprised of 2948 glomeruli. For the Oxford classification, 6206 expert-annotated glomeruli from 308 PAS WSIs were labelled for M, E, S, C and split into a training set of 4298 glomeruli from 207 WSIs, and a test set of 1908 glomeruli. We chose the best-performing models to construct an end-to-end pipeline, which we named MESCnn (MESC classification by neural network), for the glomerular Oxford classification of WSIs. RESULTS: Instance segmentation yielded excellent results with an AP50 ranging between 78.2-80.1 % (79.4 ± 0.7 %) on the validation and 75.1-77.7 % (76.5 ± 0.9 %) on the test set. The aggregated Jaccard Index was between 73.4-75.9 % (75.0 ± 0.8 %) on the validation and 69.1-73.4 % (72.2 ± 1.4 %) on the test set. At granular glomerular level, Oxford Classification was best replicated for M with EfficientNetV2-L with a mean ROC-AUC of 90.2 % and a mean precision/recall area under the curve (PR-AUC) of 81.8 %, best for E with MobileNetV2 (ROC-AUC 94.7 %) and ResNet50 (PR-AUC 75.8 %), best for S with EfficientNetV2-M (mean ROC-AUC 92.7 %, mean PR-AUC 87.7 %), best for C with EfficientNetV2-L (ROC-AUC 92.3 %) and EfficientNetV2-S (PR-AUC 54.7 %). At biopsy-level, correlation between expert and deep learning labels fulfilled the demands of the Oxford Classification. CONCLUSION: We designed an end-to-end pipeline for glomerular Oxford Classification on both a granular glomerular and an entire biopsy level. Both the glomerular segmentation and the classification modules are freely available for further development to the renal medicine community.

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.

Post-Surgical Indications to Radioiodine Treatment and Potential Risk Factors for Post-Treatment Recurrence in Patients with Intermediate-Risk Differentiated Thyroid Carcinoma.

In this multicentric retrospective observational study, we investigated the potential risk factors for radioiodine (RAI) indication and the post-treatment recurrence of intermediate-risk differentiated thyroid cancer (DTC) 1 and 3 years from diagnosis. We included 121 patients who underwent thyroidectomy for intermediate-risk DTC. The 92 patients (76.0%) who underwent RAI treatment had a higher prevalence of extra-thyroid micro-extension (mETE) (p = 0.03), pT3 staging (p = 0.03) and recourse to therapeutic central (p = 0.04) and lateral (p = 0.01) neck dissection, as well as higher numbers (p = 0.02) and greater dimensions (p = 0.01) of lymph node metastases, compared with untreated patients. Relapse was observed in 18.1% and 20.7% of cases 1 and 3 years from diagnosis, respectively, with no significant differences between groups. A lower age at diagnosis (p = 0.03) and higher levels of stimulated thyroglobulin (Tg) (p = 0.04) emerged as the only independent risk factors for tumour relapse at 1 year. Tumour relapse at 3 years was only independently predicted by the presence of tumour relapse at 1 year (p = 0.04). In conclusion, mETE, pT3 and the presence of large, multiple or clinically evident lymph node metastases represent the main indicators for referring patients to RAI treatment. Early recurrence may be considered the most relevant factor when planning further surveillance.

What has vaccination against COVID-19 in CKD patients taught us?

Effective vaccination strategies are of crucial importance to protecting patients who are vulnerable to infections, such as patients with chronic kidney disease. This is because the decreased efficiency of the immune system in chronic kidney disease impairs vaccine-induced immunisation. COVID-19 has prompted investigation of the immune response to SARS-CoV-2 vaccines in chronic kidney disease and in kidney transplant recipients in an effort to improve efficacy. The seroconversion rate after two vaccine doses is reduced, especially in kidney transplant recipients. Furthermore, although the seroconversion rate in chronic kidney disease patients is as high as in healthy subjects, anti-spike antibody titres are lower than in healthy vaccinated individuals, and these titres decrease rapidly. Although the vaccine-induced anti-spike antibody titre correlates with neutralising antibody levels and with protection against COVID-19, the protective prognostic significance of their titre is decreased due to the emergence of SARS-CoV-2 variants other than the Wuhan index virus against which the original vaccines were produced. Cellular immunity is also relevant, and because of cross-reactivity to the spike protein, epitopes of different viral variants confer protection against newly emerging variants of SARS-CoV-2. A multi-dose vaccination strategy is the most effective way to obtain a sufficient serological response. In kidney transplant recipients, a 5-week discontinuation period from antimetabolite drugs in concomitance with vaccine administration may also increase the vaccine's efficacy. The newly acquired knowledge obtained from COVID-19 vaccination is of general interest for the success of other vaccinations in chronic kidney disease patients.

Differences between κ and λ light chain amyloidosis analyzed by a pathologic scoring system.

OBJECTIVES: Amyloid light chain (AL)-κ and AL-λ share common histopathologic changes; however, the potential difference in clinical manifestations, histologic findings, and clinical significance between the 2 subtypes remain unclear. METHODS: In a retrospective study, 94 kidney biopsies for AL amyloidosis were evaluated using the composite scarring injury score (CSIS) and amyloid score (AS). Results were then compared between AL-κ and AL-λ. RESULTS: Comparing AS and CSIS between AL-κ and AL-λ, the AS was significantly higher in AL-κ than in AL-λ, with 2 components of AS (capillary wall and vascular amyloid) scoring higher in AL-κ than in AL-λ, while mesangial and interstitial ASs were similar in the 2 cohorts. In addition, the proportion of periodic acid-Schiff strong-staining amyloid in AL-κ was markedly higher than in AL-λ. There was no significant difference in CSIS and its components between the 2 subtypes of AL amyloidosis. CONCLUSIONS: Overall, AL-κ presents with higher serum creatinine and a higher AS score than AL-λ at biopsy, which may indicate a worse prognosis and be an important reference for clinical management.

["New antigens" in membranous glomerulonephritis: let's take a closer look].

Membranous Nephropathy (MN) is characterized by the presence of subepithelial deposits. MN has been traditionally classified as primary if it is not associated with other pathologies, or secondary if it is associated with autoimmune diseases, infections or malignancies. The identification of target podocyte antigen was a critical point in the understanding of the disease: firstly in 2009 with M-type phospholipase A2 receptor (PLA2R) and then in 2014 with Thrombospondin Type 1 Domain Containing 7A (THSD7A). In the last years using an innovative approach based on laser microdissection and tandem mass spectrometry (MS/MS) has allowed the identification of new target antigen/protein as EXT1/2, NELL-1, NCAM1, SEMA3B, PCHD7, HTRA1, TGFBR3. Some of these proteins have been found in both primary and secondary MN, blurring the line between the two forms. Further studies are necessary to define and understand the clinical features of different antigen associated diseases. The aim of this review is to take a closer look at the new antigens and to evaluate how their discovery can change MN classification.

Endocrine disrupting chemicals: effects on pituitary, thyroid and adrenal glands.

BACKGROUND: In recent years, scientific research has increasingly focused on Endocrine Disrupting Chemicals (EDCs) and demonstrated their relevant role in the functional impairment of endocrine glands. This induced regulatory authorities to ban some of these compounds and to carefully investigate others in order to prevent EDCs-related conditions. As a result, we witnessed a growing awareness and interest on this topic. AIMS: This paper aims to summarize current evidence regarding the detrimental effects of EDCs on pivotal endocrine glands like pituitary, thyroid and adrenal ones. Particularly, we directed our attention on the known and the hypothesized mechanisms of endocrine dysfunction brought by EDCs. We also gave a glimpse on recent findings from pioneering studies that could in the future shed a light on the pathophysiology of well-known, but poorly understood, endocrine diseases like hormone-producing adenomas. CONCLUSIONS: Although intriguing, studies on endocrine dysfunctions brought by EDCs are challenging, in particular when investigating long-term effects of EDCs on humans. However, undoubtedly, it represents a new intriguing field of science research.

Isotope partitioning between cow milk and farm water: A tool for verification of milk provenance.

RATIONALE: The oxygen and hydrogen isotope compositions of the water component of the milk from nine Italian dairy farms were studied together with the farm water for one year. The aim was to verify the importance of farm water and seasonal temperature variation on milk isotope values and propose mathematical relations as new tools to identify the milk origin. METHODS: Milk was centrifuged to separate the solids and then distilled under vacuum to separate water. δ(18 O/16 O) and δ(2 H/1 H) analyses of the water molecules were carried out using a water equilibrator online with a mass spectrometer. For oxygen and hydrogen isotope determination, water was equilibrated with pure CO2 for 7.5 h and with pure H2 for 5 h, respectively. The isotope ratio value is indicated with δ (expressed on the VSMOW/SLAP scale) as defined by IUPAC. RESULTS: The average annual isotope value of milk at the different cattle sheds is mostly related to the farm water suggesting that the drinking water is the most important factor influencing the isotopic values of the milk water. The milk/water fractionation factor correlates with the milking time and, thus, the seasonal temperature is best described by a 4th order polynomial regression line. A two-level check model was used to verify the milking provenance. CONCLUSIONS: This study shows that it is essential to analyze both milk and farm water to indicate provenance. A two-step verification tool, based on the difference between the measured and calculated δ(18 O/16 O)M values, and the difference between the calculated and estimated milk-water fractionation factors, allowed the source determination of milk. Both conditions must be met if the milk is considered to be from the Parmigiano-Reggiano production region. Although this approach was developed for this region, it can easily be tested and adapted to other dairy production areas.

Lymphoma and the Kidney: A Kidney Biopsy Teaching Case.

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.

Geometry-Consistent Light Field Super-Resolution via Graph-Based Regularization.

Light field cameras capture the 3D information in a scene with a single exposure. This special feature makes light field cameras very appealing for a variety of applications: from post-capture refocus to depth estimation and image-based rendering. However, light field cameras suffer by design from strong limitations in their spatial resolution. Off-the-shelf super-resolution algorithms are not ideal for light field data, as they do not consider its structure. On the other hand, the few super-resolution algorithms explicitly tailored for light field data exhibit significant limitations, such as the need to carry out a costly disparity estimation procedure with sub-pixel precision. We propose a new light field super-resolution algorithm meant to address these limitations. We use the complementary information in the different light field views to augment the spatial resolution of the whole light field at once. In particular, we show that coupling the multi-view approach with a graph-based regularizer, which enforces the light field geometric structure, permits to avoid the need of a precise and costly disparity estimation step. Extensive experiments show that the new algorithm compares favorably to the state-of-the-art methods for light field super-resolution, both in terms of visual quality and in terms of reconstruction error.