Systemic vasculitis involving the kidney: the nephropathologist's point of view.

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.

Economic assessment of NGS testing workflow for NSCLC in a healthcare setting.

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.

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.

The biomarkers ATLAS: An audit on 1100 non-small cell lung cancer from an Italian knowledge-based database.

AIMS: To date, precision medicine has revolutionized the clinical management of Non-Small Cell Lung Cancer (NSCLC). International societies approved a rapidly improved mandatory testing biomarkers panel for the clinical stratification of NSCLC patients, but harmonized procedures are required to optimize the diagnostic workflow. In this context a knowledge-based database (Biomarkers ATLAS, https://biomarkersatlas.com/) was developed by a supervising group of expert pathologists and thoracic oncologists collecting updated clinical and molecular records from about 80 referral Italian institutions. Here, we audit molecular and clinical data from n = 1100 NSCLC patients collected from January 2019 to December 2020. METHODS: Clinical and molecular records from NSCLC patients were retrospectively collected from the two coordinating institutions (University of Turin and University of Naples). Molecular biomarkers (KRAS, EGFR, BRAF, ROS1, ALK, RET, NTRK, MET) and clinical data (sex, age, histological type, smoker status, PD-L1 expression, therapy) were collected and harmonized. RESULTS: Clinical and molecular data from 1100 (n = 552 mutated and n = 548 wild-type) NSCLC patients were systematized and annotated in the ATLAS knowledge-database. Molecular records from biomarkers testing were matched with main patients' clinical variables. CONCLUSIONS: Biomarkers ATLAS (https://biomarkersatlas.com/) represents a unique, easily managing, and reliable diagnostic tool aiming to integrate clinical records with molecular alterations of NSCLC patients in the real-word Italian scenario.

Germinal Center Dark Zone harbors ATR-dependent determinants of T-cell exclusion that are also identified in aggressive lymphoma.

The germinal center (GC) dark zone (DZ) and light zone (LZ) regions spatially separate expansion and diversification from selection of antigen-specific B-cells to ensure antibody affinity maturation and B cell memory. The DZ and LZ differ significantly in their immune composition despite the lack of a physical barrier, yet the determinants of this polarization are poorly understood. This study provides novel insights into signals controlling asymmetric T-cell distribution between DZ and LZ regions. We identify spatially-resolved DNA damage response and chromatin compaction molecular features that underlie DZ T-cell exclusion. The DZ spatial transcriptional signature linked to T-cell immune evasion clustered aggressive Diffuse Large B-cell Lymphomas (DLBCL) for differential T cell infiltration. We reveal the dependence of the DZ transcriptional core signature on the ATR kinase and dissect its role in restraining inflammatory responses contributing to establishing an immune-repulsive imprint in DLBCL. These insights may guide ATR-focused treatment strategies bolstering immunotherapy in tumors marked by DZ transcriptional and chromatin-associated features.

New pan-ALK inhibitor-resistant EML4::ALK mutations detected by liquid biopsy in lung cancer patients.

ALK and ROS1 fusions are effectively targeted by tyrosine kinase inhibitors (TKIs), however patients inevitably relapse after an initial response, often due to kinase domain mutations. We investigated circulating DNA from TKI-relapsed NSCLC patients by deep-sequencing. New EML4::ALK substitutions, L1198R, C1237Y and L1196P, were identified in the plasma of NSCLC ALK patients and characterized in a Ba/F3 cell model. Variants C1237Y and L1196P demonstrated pan-inhibitor resistance across 5 clinical and 2 investigational TKIs.

PIK3CA testing in hormone receptor-positive/HER2-negative metastatic breast cancer: real-world data from Italian molecular pathology laboratories.

Introduction: PIK3CA gene mutations occur in approximately 40% of hormone receptor-positive/HER2-negative (HR+/HER2-) metastatic breast cancers (MBCs), electing them to targeted therapy. Testing PIK3CA status is complex due to selection of biological specimen and testing method. Materials & methods: This work investigates real-life experience on PIK3CA testing in HR+/HER2- MBC. Clinical, technical and molecular data on PIK3CA testing were collected from two referral laboratories. Additionally, the results of a nationwide PIK3CA survey involving 116 institutions were assessed. Results: Overall, n = 35 MBCs were PIK3CA-mutated, with mutations mostly occurring in exons 9 (n = 19; 51.4%) and 20 (n = 15; 40.5%). The nationwide survey revealed significant variability across laboratories in terms of sampling methodology, technical assessment and clinical report signing healthcare figures for PIK3CA molecular testing in diagnostic routine practice. Conclusion: This study provides insights into the real-world routine of PIK3CA testing in HR+/HER2- MBC and highlights the need for standardization and networking in predictive pathology.

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.

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.

Management of patients with extensive small-cell lung cancer in the immunotherapy era: an Italian consensus through a Delphi approach.

BACKGROUND: Immunotherapy represented a turning point for treating extensive small-cell lung cancer (ES-SCLC). Although, many issues remain debated. METHODS: A group of Italian medical and radiation oncologists with expertise in managing patients with ES-SCLC developed a list of statements divided in six areas of interest. The Delphi method was used to assess the consensus on the defined list of statements. RESULTS: 32 statements were included in the final list to be voted by the Delphi panel, and 26 reached a consensus on the agreement. A prompt involvement of a multidisciplinary team is a priority to provide an integrated treatment strategy. First-line recommended treatment is immunotherapy in combination with platinum-based chemotherapy and etoposide for four cycles followed by maintenance immunotherapy. CONCLUSIONS: While awaiting new data from clinical trials and real-world studies, these recommendations can represent a useful tool to guide the management of ES-SCLC patients in daily practice.

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.

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.

First-hit SETBP1 mutations cause a myeloproliferative disorder with bone marrow fibrosis.

ABSTRACT: SETBP1 mutations are found in various clonal myeloid disorders. However, it is unclear whether they can initiate leukemia, because SETBP1 mutations typically appear as later events during oncogenesis. To answer this question, we generated a mouse model expressing mutated SETBP1 in hematopoietic tissue: this model showed profound alterations in the differentiation program of hematopoietic progenitors and developed a myeloid neoplasm with megakaryocytic dysplasia, splenomegaly, and bone marrow fibrosis, prompting us to investigate SETBP1 mutations in a cohort of 36 triple-negative primary myelofibrosis (TN-PMF) cases. We identified 2 distinct subgroups, one carrying SETBP1 mutations and the other completely devoid of somatic variants. Clinically, a striking difference in disease aggressiveness was noted, with patients with SETBP1 mutation showing a much worse clinical course. In contrast to myelodysplastic/myeloproliferative neoplasms, in which SETBP1 mutations are mostly found as a late clonal event, single-cell clonal hierarchy reconstruction in 3 patients with TN-PMF from our cohort revealed SETBP1 to be a very early event, suggesting that the phenotype of the different SETBP1+ disorders may be shaped by the opposite hierarchy of the same clonal SETBP1 variants.

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.

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.

Standardized and simplified reporting of next-generation sequencing results in advanced non-small-cell lung cancer: Practical indications from an Italian multidisciplinary group.

Molecular biomarker testing is increasingly becoming standard of care for advanced non-small cell lung cancer (NSCLC). Tissue and liquid biopsy-based next-generation sequencing (NGS) is now highly recommended and has become an integral part of the routine management of advanced NSCLC patients. This highly sensitive approach can simultaneously and efficiently detect multiple biomarkers even in scant samples. However full optimization of NGS in clinical practice requires accurate reporting and interpretation of NGS findings. Indeed, as the number of NSCLC biomarkers continues to grow, clinical reporting of NGS data is becoming increasingly complex. In this scenario, achieving standardization, simplification, and improved readability of NGS reports is key to ensuring timely and appropriate treatment decisions. In an effort to address the complexity and lengthy reporting of NGS mutation results, an Italian group of 14 healthcare professionals involved in NSCLC management convened in 2023 to address the content, structure, and ease-of-use of NGS reporting practices and proposed a standard report template for clinical use This article presents the key discussion points addressed by the Italian working group and describes the essential elements of the report template.

The usual Interstitial pneumonia pattern in autoimmune rheumatic diseases.

Usual Interstitial Pneumonia (UIP) is characterized by progression of lung parenchyma that may be observed in various autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis and connective tissue diseases. From a diagnostic point of view, a UIP pattern related to ARDs may display imaging and pathological features able to distinguish it from that related to IPF, such as the "straight-edge" sign at HRCT and lymphoplasmacytic infiltrates at histologic specimens. Multidisciplinary approach (MDD), involving at least pulmonologist, rheumatologist and radiologist, is fundamental in the differential diagnosis process, but MDD is also required in the evaluation of severity, progression and response to treatment, that is based on the combination of changes in symptoms, pulmonary function trends, and, in selected patients, serial CT evaluation. Differently from IPF, in patients with ARDs both functional evaluation and patient-reported outcomes may be affected by systemic involvement and comorbidities, including musculoskeletal manifestations of disease. Finally, in regards to pharmacological treatment, immunosuppressants have been considered the cornerstone of therapy, despite the lack of solid evidence in most cases; recently, antifibrotic drugs were also proposed for the treatment of progressive fibrosing ILDs other than IPF. In ARD-ILD, the therapeutic choice should balance the need for the control of systemic and lung involvements with the risk of adverse events from multi-morbidities and -therapies. Purpose of this review is to summarize the definition, the radiological and morphological features of the UIP pattern in ARDs, together with risk factors, diagnostic criteria, prognostic evaluation, monitoring and management approaches of the UIP-ARDs.

Perspective of a Pathologist on Benchmark Strategies for Artificial Intelligence Development in Organ Transplantation.

Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles. In transplant pathology histology is still the gold standard for diagnosis dictating the subsequent decisions and course of clinical care. Digital pathology has played an important role in accelerating healthcare progression and nowadays artificial intelligence powered computational pathology can effectively improve diagnostic needs, supporting the quality and safety of the process. Mapping the shape of the journey would suggest a progressive approach from supervised to semi/unsupervised models, which would involve training these models directly for clinical endpoints. In machine learning, this generally delivers better performance, compensating for a potential lack in interpretability. With planning and enough confidence in the performance of learning-based methods from digital pathology and artificial intelligence, there is great potential to augment the diagnostic quality and correlation with clinical endpoints. This may improve the donor pool and vastly reduce diagnostic and prognostic errors that are known but currently are unavoidable in transplant donor pathology.