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Introduction: To evaluate the detection rate for prostate cancer (PCa) performing multiparametric magnetic resonance imaging (mpMRI) fusion targeted biopsy (TPBx) combined only with ipsilateral systematic prostate biopsy (SPBx). Materials and Methods: From January 2023 to December 2023, 495 men with clinical suspicion of PCa underwent transperineal SPBx plus TPBx in the presence of PI-RADS score lesions ≥ 3. Results: In 250/495 men (50.5%) a PCa was found, while 36/250 (14.4%) men had negative mpMRI. In comparison to TPBx, SPBx diagnosed a higher number of indolent PCa, 38.5 vs. 5.8%, respectively; conversely, SPBx demonstrated a higher detection rate for clinically significant PCa (97.3 vs. 85.4%) in the presence of ISUP Grade Group 2 (GG2). In details, rates were higher in the presence of GG2 (100 vs. 76%), GG3 (85.7 vs. 75.8%) and GG4 (100 vs. 86.4%) tumors. However, in GG5, both SPBx and TPBx diagnosed 100% of csPCa. Furthermore, 89.4% of the cases showed csPCa on the negative mpMRI side. Conclusions: SPBx combined with TPBx maximized csPCa diagnosis; the use of reduced biopsy scheme limited to ipsilateral side of mpMRI lesion plus TPBx missed 11.6% csPCa. Only in the presence of PI-RADS score 5 SPBx and TPBx diagnosed both 100% of csPCa.

Introduction: To evaluate the accuracy of PSMA PET/CT in the diagnosis and clinical staging of prostatic ductal adenocarcinoma (DAC). Materials and methods: Two Caucasian men 58 and 62 years old were admitted to our Department for dysuria: the patients had not familiarity for prostate cancer (PCa), PSA values were 5.6 and 2.8 ng/ml, digital rectal examination was positive, multiparametric magnetic resonance image (mpMRI) showed for both the presence of an index lesion PIRADS score 5. The patients underwent extended transperineal prostate biopsy combined with four mpMRI/TRUS fusion biopsy under sedation and antibiotic prophylaxis; biopsy histology demonstrated the presence of a mixed PCa characterized by DAC and acinar PCa (Grade Group 4/Gleason score 8). The patients underwent clinical staging performing lung and abdominal CT, bone scan and fluoride 18 (18F) PSMA PET/CT. Results: Conventional imaging was negative for distant metastases; 18F-PSMA PET/CT showed in both patients an intraprostatic lesion characterized by a standardized uptake value (SUVmax) equal to 4.6 and 4.9 in the absence of distant lesions suspicious for metastases. Following multidisciplinary evaluation, the patients underwent radical prostatectomy plus extended pelvic lymphadenectomy. Definitive specimen showed the presence in both cases of a mixed pT3bN1 PCa (ductal plus acinar pattern Grade Group 4) with positive surgical margins, neuronal invasion, and nodes metastases (5/20 and 6/24, respectively). Post-operative PSA in the two patients was 0.8 and 0.3 ng/ml, therefore patients underwent adjuvant therapy. Conclusions: Conventional imaging and PSMA PET/CT could result inadequate in clinical staging of DAC, the use of more imaging data (i.e. mpMRI and/or F-18 FDG) could improve overall accuracy.

Abstract In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of characterization and reporting on resected biopsies, including polyps, the numbers of which are increasing as a result of CRC population screening programs ongoing in many countries all around the globe. Here, we present an approach to address two major challenges in the automated assessment of CRC histopathology whole-slide images. We present an AI-based method to segment multiple ( $$n=14$$ n = 14 ) tissue compartments in the H &E-stained whole-slide image, which provides a different, more perceptible picture of tissue morphology and composition. We test and compare a panel of state-of-the-art loss functions available for segmentation models, and provide indications about their use in histopathology image segmentation, based on the analysis of (a) a multi-centric cohort of CRC cases from five medical centers in the Netherlands and Germany, and (b) two publicly available datasets on segmentation in CRC. We used the best performing AI model as the basis for a computer-aided diagnosis system that classifies colon biopsies into four main categories that are relevant pathologically. We report the performance of this system on an independent cohort of more than 1000 patients. The results show that with a good segmentation network as a base, a tool can be developed which can support pathologists in the risk stratification of colorectal cancer patients, among other possible uses. We have made the segmentation model available for research use on https://grand-challenge.org/algorithms/colon-tissue-segmentation/ .

Abstract The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer diagnosis. However, the availability of medical specialists to annotate digitized images and free-text diagnostic reports does not scale with the need for large datasets required to train robust computer-aided diagnosis methods that can target the high variability of clinical cases and data produced. This work proposes and evaluates an approach to eliminate the need for manual annotations to train computer-aided diagnosis tools in digital pathology. The approach includes two components, to automatically extract semantically meaningful concepts from diagnostic reports and use them as weak labels to train convolutional neural networks (CNNs) for histopathology diagnosis. The approach is trained (through 10-fold cross-validation) on 3’769 clinical images and reports, provided by two hospitals and tested on over 11’000 images from private and publicly available datasets. The CNN, trained with automatically generated labels, is compared with the same architecture trained with manual labels. Results show that combining text analysis and end-to-end deep neural networks allows building computer-aided diagnosis tools that reach solid performance (micro-accuracy = 0.908 at image-level) based only on existing clinical data without the need for manual annotations.

Introduction: To evaluate the accuracy of 68Ga-prostate specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) in the diagnosis of clinically significant prostate cancer (csPCa: Grade Group ≥ 2) in men enrolled in Active Surveillance (AS) protocol. Materials and methods: From May 2013 to December 2021 200 men aged between 52 and 74 years (median age 63) with very low risk PCa were enrolled in an AS protocol study. During the follow up 48/200 (24%) men were upgraded and 10/200 (5%) decided to leave the AS protocol. After five years from confirmatory biopsy (range: 48-60 months) 40/142 (28.2%) consecutive patients were submitted to mpMRI and 68Ga-PSMA PET/CT imaging examinations before scheduled repeated biopsy. All the mpMRI (PI-RADS ≥ 3) and 68Ga-PET/TC standardized uptake value (SUVmax) ≥ 5 index lesions underwent targeted cores (mpMRI-TPBx and PSMA-TPBx) combined with transperineal saturation prostate biopsy (SPBx: median 20 cores). Results: Multiparametric MRI and 68Ga-PSMA PET/CT showed 18/40 (45%) and 9/40 (22.5%) lesions suspicious for PCa. In 3/40 (7.5%) men a csPCa (GG2) was found; 68Ga-PSMA-TPBx vs. mpMRI-TPBx vs. SPBx diagnosed 2/3 (66.6%) vs. 2/3 (66.6%) vs. 3/3 (100%) csPCa, respectively. In detail, mpMRI and 68Ga-PSMA PET/TC demonstrated 16/40 (40%) vs. 7/40 (17.5%) false positive and 1 (33.3%) vs. 1 (33.3%) false negative results. Conclusion: Although 68PSMA PET/CT did not improve the detection for csPCa of SPBx (1 false negative result equal to 33.3% of the cases), at the same time, would have spared 31/40 (77.5%) scheduled biopsies showing a better diagnostic accuracy in comparison with mpMRI (83.3% vs. 70.2%).

Summary: Background: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. Methods: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. Findings: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. Interpretation: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implementation. Funding: No specific funding was provided for this study.

Computational pathology can significantly benefit from ontologies to standardize the employed nomenclature and help with knowledge extraction processes for high-quality annotated image datasets. The end goal is to reach a shared model for digital pathology to overcome data variability and integration problems. Indeed, data annotation in such a specific domain is still an unsolved challenge and datasets cannot be steadily reused in diverse contexts due to heterogeneity issues of the adopted labels, multilingualism, and different clinical practices. Material and methods: This paper presents the ExaMode ontology, modeling the histopathology process by considering 3 key cancer diseases (colon, cervical, and lung tumors) and celiac disease. The ExaMode ontology has been designed bottom-up in an iterative fashion with continuous feedback and validation from pathologists and clinicians. The ontology is organized into 5 semantic areas that defines an ontological template to model any disease of interest in histopathology. Results: The ExaMode ontology is currently being used as a common semantic layer in: (i) an entity linking tool for the automatic annotation of medical records; (ii) a web-based collaborative annotation tool for histopathology text reports; and (iii) a software platform for building holistic solutions integrating multimodal histopathology data. Discussion: The ontology ExaMode is a key means to store data in a graph database according to the RDF data model. The creation of an RDF dataset can help develop more accurate algorithms for image analysis, especially in the field of digital pathology. This approach allows for seamless data integration and a unified query access point, from which we can extract relevant clinical insights about the considered diseases using SPARQL queries.

Introduction: To evaluate the diagnostic accuracy of 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomog-raphy (PET/CT) vs. multiparametric magnetic resonance imag-ing (mpMRI) targeted biopsy (TPBx) in the diagnosis of clinical-ly significant prostate cancer (csPCa: Grade Group ≥ 2). Materials and methods: From January 2021 to June 2022, 100 patients (median age: 66 years) with negative digital rectal examination underwent transperineal prostate biopsy for abnor-mal PSA values (median 7.5 ng/ml). Before prostate biopsy, all patients underwent mpMRI and 68Ga-PET/CT examinations and mpMRI (PI-RADS version 2 ≥ 3) or 68Ga-PET/CT index lesions suspicious for cancer (SUVmax > 5 g/ml) underwent cognitive targeted cores (mpMRI-TPBx and PSMA-TPBx: four cores) com-bined with extended systematic prostate biopsy (eSPBx: median 18 cores). The procedure was performed transperineally using a tru-cut 18-gauge needle under sedation and antibiotic prophy-laxis. Results: PCa was found in 58/100 (58.0%) men; in detail, 44/58 (75.9%) were csPCa; mpMRI and 68Ga-PSMA showed 66/100 (66%) and 62/100 (60%) lesions suspicious for PCa, respective-ly. 68Ga-PSMA-TPBx vs. mpMRI-TPBx vs. eSPBx diagnosed 42 (95.4%) vs. 36 (81.8%) vs. 30 (68.2%) csPCa, respectively; mpMRI-TPBx vs. 68Ga-PSMA-TPBx showed a diagnostic accuracy of 76.9% vs. 84.9% in diagnosing csPCa. Conclusions: 68GaPSMA PET/CT TPBx demonstrated good accuracy in the diagnosis of csPCa, which was not inferior to mpMRI TPBx (84.9% vs. 76.9%) improving the detection rate for cancer of systematic biopsy.

Introduction: The reclassification rate for clinically significant prostate cancer (csPCa) in men enrolled in Active Surveillance (AS) as been prospective-ly evaluated. Patients and methods: One hundred patients with very low risk PCa underwent after 8 years a scheduled transperineal prostate biopsy (SPBx = 20 cores) combined with additional mpMRI/TRUS fusion biopsies (4 cores) of lesions PI-RADS scores ≥ 3. All the patients, after initial diagnosis, previously had mpMRI evaluation combined with transperineal saturation prostate biopsy (confirmatory and 3-year scheduled biopsy). Risk reclassification at repeat biopsy triggering the recommen-dation for active treatment was defined as over 3 or more than 10% of positive cores, Gleason score > 6/ISUP Grade Group ≥ 2, greatest percentage of cancer (GPC) > 50%. Results: Multiparametric MRI was suspicious (PI-RADS ≥ 3) in 30 of 100 cases (30.0%); 70 (70.0%) vs. 20 (20.0%) vs. 10 (10.0%) patients had a PI-RADS score ≤ 2 vs. 3 vs. 4, respec-tively. Two (2.0%) patients with PI-RADS score 3 and 4 were upgraded (ISUP Grade Group 2); SPBx and MRI/TRUS fusion biopsy diagnosed 100% and 0% of csPCa, respectively. Conclusions: Transperineal SPBx combined with mpMRI at ini-tial confirmatory biopsy allow to select an high number of men at very low risk of reclassification during the AS follow up (2.0%of the cases at 8 years from diagnosis); these data could be use-ful to reduce the number of scheduled repeated prostate biopsy during the AS follow up.

Pre-eclampsia is a pregnancy complication characterized by defective vascular remodeling in maternal decidua responsible for reduced blood flow leading to functional and structural alterations in the placenta. We have investigated the contribution of the complement system to decidual vascular changes and showed that trophoblasts surrounding unremodeled vessels prevalent in preeclamptic decidua fail to express C1q that are clearly detected in cells around remodeled vessels predominant in control placenta. The critical role of C1q is supported by the finding that decidual trophoblasts of female C1qa-/- pregnant mice mated to C1qa+/+ male mice surrounding remodeled vessels express C1q of paternal origin. Unlike C1qa-/- pregnant mice, heterozygous C1qa+/- and wild type pregnant mice share a high percentage of remodeled vessels. C1q was also found in decidual vessels and stroma of normal placentae and the staining was stronger in preeclamptic placentae. Failure to detect placental deposition of C1r and C1s associated with C1q rules out complement activation through the classical pathway. Conversely, the intense staining of decidual endothelial cells and villous trophoblast for ficolin-3, MASP-1 and MASP-2 supports the activation of the lectin pathway that proceeds with the cleavage of C4 and C3 and the assembly of the terminal complex. These data extend to humans our previous findings of complement activation through the lectin pathway in an animal model of pre-eclampsia and provide evidence for an important contribution of C1q in decidual vascular remodeling.

Endometrial carcinoma (EC) is the most common gynecological malignant disease in high-income countries, such as European countries and the USA. The 2020 edition of the World Health Organization (WHO) Classification of Tumors of the Female Genital Tract underlines the important clinical implications of the proposed new histomolecular classification system for ECs. In view of the substantial genetic and morphological heterogeneity in ECs, both classical pthological parameters and molecular classifiers have to be integrated in the pathology report. This review will focus on the most commonly adopted immunohistochemical and molecular biomarkers in daily clinical characterization of EC, referring to the most recent published recommendations, guidelines, and expert opinions.

Exa-scale volumes of medical data have been produced for decades. In most cases, the diagnosis is reported in free text, encoding medical knowledge that is still largely unexploited. In order to allow decoding medical knowledge included in reports, we propose an unsupervised knowledge extraction system combining a rule-based expert system with pre-trained Machine Learning (ML) models, namely the Semantic Knowledge Extractor Tool (SKET). Combining rule-based techniques and pre-trained ML models provides high accuracy results for knowledge extraction. This work demonstrates the viability of unsupervised Natural Language Processing (NLP) techniques to extract critical information from cancer reports, opening opportunities such as data mining for knowledge extraction purposes, precision medicine applications, structured report creation, and multimodal learning.SKET is a practical and unsupervised approach to extracting knowledge from pathology reports, which opens up unprecedented opportunities to exploit textual and multimodal medical information in clinical practice. We also propose SKET eXplained (SKET X), a web-based system providing visual explanations about the algorithmic decisions taken by SKET.SKET X is designed/developed to support pathologists and domain experts in understanding SKET predictions, possibly driving further improvements to the system.

Introduction: The detection rate for clinically significant prostate cancer (csPCa) in men with mpMRI PI-RADS score 3 diagnosed by affiliated radiology centers vs radiological reference center was evaluated. Materials and methods: From January 2017 to December 2020, 950 men (median age 64 years) underwent mpMRI for abnormal PSA values (median 6.3 ng/ml). Among the 950 patients who underwent mpMRI 500 were evaluated by a reference center and 450 by outpatient radiological affiliated centers. All the mpMRI index lesions characterized by a PI-RADS 3 underwent targeted cores combined with extended prostate biopsy. Two radiologists of the radiological reference center revised all the mpMRI lesions 3. Results: Overall, 361/950 (38%) patients had a mpMRI lesion PI-RADS score 3: 120/500 cases (24%) vs 241/450 cases (53.5%) were diagnosed by reference vs affiliated radiological centers. The detection rate for cT1c csPCa was equal to 26.7% (35/120 cases) vs 16.6% (40/241 cases) in men with PI-RADS 3 lesions diagnosed in the reference vs the affiliated radiological centers (p < 0.05). Among the 241 PI-RADS score 3 lesions diagnosed by affiliated radiological centers 86/241 (35.7%) and 36/241 (15%) were downgraded (PI-RADS scores < 3) and upgraded (PI-RADS score 4) by the dedicated radiologists of the reference center. Conclusions: In our series, about 35% and 15% of PI-RADS score 3 lesions diagnosed by affiliated radiological centers were downgraded and upgraded when revised by experencied radiologists, therefore a second opinion is mandatory especially in men enrolled in active surveillance protocols in whom mpMRI is recommended to reduce the number of scheduled repeated prostate biopsies.

A Caucasian man 84 years old was admitted to our Department for acute renal failure secondary to severe bilateral hydronephrosis; moreover, the patient referred chronic fatigue and was anuric from two days. Serum creatinine and PSA values were equal to 9.6 mg/dl and 4.8 ng/ml and digital rectal examination was highly suspicious for prostate cancer. In emergency, the patient underwent bilateral application of percutaneous renal nephrostomies to restore kidney function and, after three days, was submitted to ultrasound-guided extended transperineal biopsy; the histology showed the presence of a prostatic small cell carcinoma (SCC) fulfilling the World Health Organization criteria. The patient underwent clinical staging including chest and abdominal computed tomography evaluation and total body scan that did not demonstrated distant metastases and/or others primitive tumors; in addition, cystoscopy and urinary cytology were negative. The patient underwent multidisciplinary evaluation, but he died 20 days from the diagnosis for progressive clinical worsening (physical and cognitive impairments) before beginning oncological treatment. In conclusion, primitive SCC represents a very rare cancer provided of poor prognosis; only the execution of prostate biopsy combined with an accurate specimen analysis allow to make the correct diagnosis and therapeutic treatment.

We report a case of giant retrovesical adenoma originating from ectopic prostatic tissue. A 73-year-old man presented with progressive dysuria, increasing PSA values, and acute urinary retention. One year before presentation, the patient had undergone retropubic prostatic adenomectomy for benign prostate hyperplasia. At last admission, PSA value was 23 ng/ml; mpMRI demonstrated a dysomogeneus retrovesical mass of 8 cm in diameter. Biopsy histology demonstrated acute prostatitis of the residual parenchyma and a prostatic adenoma in the retrovesical mass. After antibiotics and restored spontaneous urination, the patient was discharged and refused surgical lesion removal. After three months, the patient remains asymptomatic.

MicroRNAs (miRNAs) are a class of small, non-coding RNAs that act as key regulators in various physiological and pathological processes as prostate cancer (PCa). In this study we describe molecular evaluation of 132 and 212 miRNAs expression, by Real-time reverse-transcription PCR (qRT-PCR), in a Caucasian man 64-year-old with locally advanced PCa (PSA 160 ng/ml, Gleason score 4+3/ISUP Grade Group 3, clinical stage T3NXM0) who underwent radical retropubic prostatectomy plus extended pelvic lymphadenectomy (LAD) as first step of a multimodal therapeutic treatment. A normal prostate of a 67-year-old man removed by post mortem autopsy was used as a control in the study. The mRNA for this study was conducted on paraffined prostatic sections of: a) index case of PCa; b) metastatic lymph node of index case; c) normal prostate. MiRNA-132, miRNA- 212 and Glyceraldehyde 3-phosphate dehydrogenase (as reference gene) assays were obtained. Definitive specimen showed a pT3bN1R1 stage: acinar cells adenocarcinoma with involvement of the seminal vesicles, multifocal positive surgical margins, Gleason score 8 (4+4/ISUP Grade Group 4), metastases in 5/25 iliac lymph nodes. An increased expression of miRNA-132 and miRNA-212 in index case of prostatic adenocarcinoma compared to normal prostate tissue was found; moreover, a lower expression of miR-132 and miR-212 in metastatic lymph node compared to primitive PCa and normal prostate tissue was demonstrated. Although a greater number of patients should be evaluated, these data suggest that the biology of the primary PCa, in our clinical case, was different from metastatic lymph node.

Pancreatic cancer is a most frequent cancer in Europe, and the majority of cases of cancer of the pancreas are diagnosed above the age of 65. Radical surgery is the first curative treatment of pancreatic cancer, and alternative or combined therapeutic options, in particular, consist of adjuvant or neoadjuvant chemotherapy, with or without radiotherapy. Many factors, including diet and genetics, have been implicated in the development of cancer of the pancreas. Poly (ADP-ribose) polymerase 1 (PARP-1) protein is required for translocation of the apoptosis-inducing factor (AIF) from the mitochondria to the nucleus. It is involved in programmed cell death processes. Different PARP-1 gene expression proteins have been observed in various tumors such as lung, ovarian, endometrial, skin, and glioblastoma. We evaluated the expression of PARP-1 protein in pancreatic adenocarcinoma and normal pancreas tissues by immunohistochemistry. Protein PARP-1 in the nucleus was found in all samples (normal pancreas and pancreatic adenocarcinoma tissues). No cytoplasmic staining was observed in any sample. PARP-1-positive cells resulted higher in the normal pancreas compared with the pancreas with adenocarcinoma. PARP-1 overexpression in prostate cancer tissue compared with normal prostate suggests a greater activity of PARP-1 in these tumors. These findings suggest that PARP-1 expression in prostate cancer is an attempt to trigger apoptosis in this type of tumor, similarl to that reported in other cancers. This finding suggests that PARP-1-mediated cell death pathways are inhibited in this cancer.

Abstract Background Inguinal hernia is one of the most common benign pathologies that primarily affects men. Primary gastrointestinal non-Hodgkin’s lymphoma (PGI NHL) is the most common type of extranodal lymphoma. This study reports a rare case in which these two conditions co-exist. Case presentation An 85-year-old male complained of bowel movement pattern change, abdominal distension and loss of weight, without vomiting but with nausea. A computed tomographic scan of the abdomen showed a small bowel obstruction caused by a migration of a small bowel loop in the right inguinal canal, with a clinically non-reducible inguinal hernia. The patient underwent surgery. The histopathological report showed small bowel large B cell non-Hodgkin’s lymphoma. Conclusion When the diagnosis of the contents of an inguinal hernia is not well-established, surgery should be performed as soon as possible to ensure the cure of the disease and the correct diagnosis of the contents.

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

Digital pathology for the routine assessment of cases for primary diagnosis has been implemented by few laboratories worldwide. The Gravina Hospital in Caltagirone (Sicily, Italy), which collects cases from 7 different hospitals distributed in the Catania area, converted the entire workflow to digital starting from 2019. Before the transition, the Caltagirone pathology laboratory was characterized by a non-tracked workflow, based on paper requests, hand-written blocks and slides, as well as manual assembling and delivering of the cases and glass slides to the pathologists. Moreover, the arrangement of the spaces and offices in the department was illogical and under-productive for the linearity of the workflow. For these reasons, an adequate 2D barcode system for tracking purposes, the redistribution of the spaces inside the laboratory and the implementation of the whole-slide imaging (WSI) technology based on a laboratory information system (LIS)-centric approach were adopted as a needed prerequisite to switch to a digital workflow. The adoption of a dedicated connection for transfer of clinical and administrative data between different software and interfaces using an internationally recognised standard (Health Level 7, HL7) in the pathology department further facilitated the transition, helping in the integration of the LIS with WSI scanners. As per previous reports, the components and devices chosen for the pathologists’ workstations did not significantly impact on the WSI-based reporting phase in primary histological diagnosis. An analysis of all the steps of this transition has been made retrospectively to provide a useful “handy” guide to lead the digital transition of “analog”, non-tracked pathology laboratories following the experience of the Caltagirone pathology department. Following the step-by-step instructions, the implementation of a paperless routine with more standardized and safe processes, the possibility to manage the priority of the cases and to implement artificial intelligence (AI) tools are no more an utopia for every “analog” pathology department.

Immunotherapy by immune checkpoint inhibitors has emerged as an effective treatment for a slight proportion of patients with aggressive tumors. Currently, some molecular determinants, such as the expression of the programmed cell death ligand-1 (PD-L1) or the tumor mutational burden (TMB) have been used in the clinical practice as predictive biomarkers, although they fail in consistency, applicability, or reliability to precisely identify the responding patients mainly because of their spatial intratumoral heterogeneity. Therefore, new biomarkers for early prediction of patient response to immunotherapy, that could integrate several approaches, are eagerly sought. Novel methods of quantitative image analysis (such as radiomics or pathomics) might offer a comprehensive approach providing spatial and temporal information from macroscopic imaging features potentially predictive of underlying molecular drivers, tumor-immune microenvironment, tumor-related prognosis, and clinical outcome (in terms of response or toxicity) following immunotherapy. Preliminary results from radiomics and pathomics analysis have demonstrated their ability to correlate image features with PD-L1 tumor expression, high CD3 cell infiltration or CD8 cell expression, or to produce an image signature concordant with gene expression. Furthermore, the predictive power of radiomics and pathomics can be improved by combining information from other modalities, such as blood values or molecular features, leading to increase the accuracy of these models. Thus, “digital biopsy,” which could be defined by non-invasive and non-consuming digital techniques provided by radiomics and pathomics, may have the potential to allow for personalized approach for cancer patients treated with immunotherapy.

Endometrial cancer is the most common gynecologic malignancy in developed countries. Estrogen-dependent tumors (type I, endometrioid) account for 80% of cases and non-estrogen-dependent (type II, non-endometrioid) account for the rest. Endometrial cancer type I is generally thought to develop via precursor lesions along with the increasing accumulation of molecular genetic alterations. Endometrial hyperplasia with atypia/Endometrial Intraepithelial Neoplasia is the least common type of hyperplasia but it is the type most likely to progress to type I cancer, whereas endometrial hyperplasia without atypia rarely progresses to carcinoma. MicroRNAs are a class of small, non-coding, single-stranded RNAs that negatively regulate gene expression mainly binding to 3′-untranslated region of target mRNAs. In the current study, we identified a microRNAs signature (miR-205, miR-146a, miR-1260b) able to discriminate between atypical and typical endometrial hyperplasia in two independent cohorts of patients. The identification of molecular markers that can distinguish between these two distinct pathological conditions is considered to be highly useful for the clinical management of patients because hyperplasia with an atypical change is associated with a higher risk of developing cancer. We show that the combination of miR-205, −146a, and −1260b has the best predictive power in discriminating these two conditions (>90%). With the aim to find a biological role for these three microRNAs, we focused our attention on a common putative target involved in endometrial carcinogenesis: the oncosuppressor gene SMAD4. We showed that miRs-146a,−205, and−1260b directly target SMAD4 and their enforced expression induced proliferation and migration of Endometrioid Cancer derived cell lines, Hec1a cells. These data suggest that microRNAs-mediated impairment of the TGF-β pathway, due to inhibition of its effector molecule SMAD4, is a relevant molecular alteration in endometrial carcinoma development. Our findings show a potential diagnostic role of this microRNAs signature for the accurate diagnosis of Endometrial hyperplasia with atypia/Endometrial Intraepithelial Neoplasia and improve the understanding of their pivotal role in SMAD4 regulation.

Tissue Biomarkers are information written in the tissue and used in Pathology to recognize specific subsets of patients with diagnostic, prognostic or predictive purposes, thus representing the key elements of Personalized Medicine. The advent of Artificial Intelligence (AI) promises to further reinforce the role of Pathology in the scenario of Personalized Medicine: AI-based devices are expected to standardize the evaluation of tissue biomarkers and also to discover novel information, which would otherwise be ignored by human review, and use them to make specific predictions. In this review we will present how AI has been used to support Tissue Biomarkers evaluation in the specific field of Pathology, give an insight to the intriguing field of AI-based biomarkers and discuss possible advantages, risk and perspectives for Pathology.

The European Society for Digital and Integrative Pathology (ESDIP) was formally founded in 2016 in Berlin. After a well-participated annual general meeting, ESDIP members elected a new active structure for the next term of office. The priority goals of this new and highly motivated team will be to support the digital transformation in the pathology laboratories, to build inter-institutional bridges for cooperation, to establish a solid educational program, and to increase the collaboration with industry partners.

ABSTRACT Purpose: Detection rate for anterior prostate cancer (PCa) in men who underwent initial and repeat biopsy has been prospectively evaluated. Materials and Methods: From January 2013 to March 2014, 400 patients all of Caucasian origin (median age 63.5 years) underwent initial (285 cases) and repeat (115 cases) prostate biopsy; all the men had negative digital rectal examination and the indications to biopsy were: PSA values > 10 ng/mL, PSA between 4.1-10 or 2.6-4 ng/mL with free/total PSA≤25% and ≤20%, respectively. A median of 22 (initial biopsy) and 31 cores (repeat biopsy) were transperineally performed including 4 cores of the anterior zone (AZ) and 4 cores of the AZ plus 2 cores of the transition zone (TZ), respectively. Results: Median PSA was 7.9 ng/mL; overall, a PCa was found in 180 (45%) patients: in 135 (47.4%) and 45 (36%) of the men who underwent initial and repeat biopsy, respectively. An exclusive PCa of the anterior zone was found in the 8.9 (initial biopsy) vs 13.3% (repeat biopsy) of the men: a single microfocus of cancer was found in the 61.2% of the cases; moreover, in 7 out 18 AZ PCa the biopsy histology was predictive of significant cancer in 2 (28.5%) and 5 (71.5%) men who underwent initial and repeat biopsy, respectively. Conclusions: However AZ biopsies increased detection rate for PCa (10% of the cases), the majority of AZ PCa with histological findings predictive of clinically significant cancer were found at repeat biopsy (about 70% of the cases).

Introduction. Multiparametric pelvic magnetic resonance imaging (mpMRI) accuracy in prostate cancer (PCa) diagnosis was evaluated. Materials and Methods. From June 2011 to December 2013, 168 patients (median 65 years) with negative digital rectal examination underwent repeat transperineal saturation biopsy (SPBx; median 28 cores) for persistently high or increasing PSA values, PSA >10 ng/ml or PSA values between 4.1-10 o r 2.6-4 ng/ml with free/total PSA < 25% and < 20%, respectively. All patients underwent mpMRI using a 3.0 Tesla scanner equipped with surface 16 channels phased-array coil and lesions suspicious for PCa were submitted to additional targeted biopsies. Results. A T1c PCa was found in 66 (39%) cases; SPBx and mpMRI-suspicious targeted biopsy diagnosed 60 (91%) and 52 (78.8%) cancers missing 6 (all of the anterior zone) and 14 cancers (12 and 2 of the lateral margins and anterior zone), respectively; in detail, mpMRI missed 12 (18.1%) PCa charaterized by microfocal (1 positive core with greatest percentage of cancer and Gleason score equal to 5% and 6, respectively) disease at risk for insignificant cancer. The diameter of the suspicious mpMRI lesion was directly correlated to the diagnosis of PCa with poor Gleason score (p < 0.05); detection rate of cancer for each suspicious mpMRI core was 35.3%. Diagnostic accuracy, sensitivity, specificity, positive and negative predictive value of mpMRI in diagnosing PCa was 75.7%, 82.5%, 71.8%, 78.9%, 87.9%, respectively. Conclusion. Multiparametric pMRI improved SPBx accuracy in diagnosing significant anterior PCa; the diameter of mpMRI suspicious lesion resulted significantly predictive of aggressive cancers.

PURPOSE: To compare PCA3 score cut-off of 35 vs 20 in PCa diagnosis in patients undergoing repeated saturation prostate biopsy (SPBx). MATERIALS AND METHODS: From January 2010 to May 2011, 118 patients (median 62.5 years) with primary negative extended biopsy underwent a transperineal SPBx (median 30 cores) for persistent suspicion of PCa. The indications for repeated biopsy were: persistently high or increasing PSA values; PSA > 10 ng/mL, PSA values between 4.1-10 or 2.6-4 ng/mL with free/total PSA ≤ 25% and ≤ 20%, respectively; moreover, before performing SPBx urinary PCA3 score was evaluated. RESULTS: All patients had negative DRE and median PSA was 8.5 ng/mL (range: 3.7-24 ng/mL). A T1c PCa was found in 32 patients (27.1%): PCA3 score was 59 (median; range: 7-201) in the presence of PCa and 35 (median; range: 3-253) in the absence of cancer (p < 0.05). In the presence of ASAP and HGPIN median PCA3 score was 109 (range: 42-253) and 40 (range: 30-140), respectively. Diagnostic accuracy, sensitivity, specificity, PPV and NPV of PCA3 score cut-off of 20 vs 35 in PCa diagnosis were 44.9 vs 50%, 90.6 vs 71.9%, 27.9 vs 41.8%, 31.9 vs 31.5% and 88.9 vs 80%, respectively. ROC analysis demonstrated an AUC for PCA3 ≥ 20 vs ≥ 35 of 0.678 and 0.634, respectively. CONCLUSIONS: Our data suggest that PCA3 is more useful as an exclusion tool; moreover, setting a PCA3 cut-off at 20 vs 35, would have avoided 22.9 vs 38.1% of biopsies while missing 9.4% and 28% diagnosis of PCa.

Introduction: A whole slide image (WSI) is typically comprised of a macro image (low-power snapshot of the entire glass slide) and stacked tiles in a pyramid structure (with the lowest resolution thumbnail at the top). The macro image shows the label and all pieces of tissue on the slide. Many whole slide scanner vendors do not readily show the macro overview to pathologists. We demonstrate that failure to do so may result in a serious misdiagnosis. Materials and Methods: Various examples of errors were accumulated that occurred during the digitization of glass slides where the virtual slide differed from the macro image of the original glass slide. Such examples were retrieved from pathology laboratories using different types of scanners in the USA, Canada, Europe, and Asia. Results: The reasons for image errors were categorized into technical problems (e.g., automatic tissue finder failure, image mismatches, and poor scan coverage) and human operator mistakes (e.g., improper manual region of interest selection). These errors were all detected because they were highlighted in the macro image. Conclusion: Our experience indicates that WSI can be subject to inadvertent errors related to glitches in scanning slides, corrupt images, or mistakes made by humans when scanning slides. Displaying the macro image that accompanies WSIs is critical from a quality control perspective in digital pathology practice as this can help detect these serious image-related problems and avoid compromised diagnoses.

Introduction: Whole-slide imaging (WSI) technology can be used for primary diagnosis and consultation, including intraoperative (IO) frozen section (FS). We aimed to implement and validate a digital system for the FS evaluation of cancer and transplant specimens following recommendations of the College of American Pathologists. Materials and Methods: FS cases were routinely scanned at ×20 employing the “Navigo” scanner system. IO diagnoses using glass versus digital slides after a 3-week washout period were recorded. Intraobserver concordance was evaluated using accuracy rate and kappa statistics. Feasibility of WSI diagnoses was assessed by the way of sensitivity, specificity, as well as positive and negative predictive values. Participants also completed a survey denoting scan time, time spent viewing cases, preference for glass versus WSI, image quality, interface experience, and any problems encountered. Results: Of the 125 cases submitted, 121 (436 slides) were successfully scanned including 93 oncological and 28 donor-organ FS biopsies. Four cases were excluded because of failed digitalization due to scanning problems or sample preparation artifacts. Full agreement between glass and digital-slide diagnosis was obtained in 90 of 93 (97%, κ = 0.96) oncology and in 24 of 28 (86%, κ = 0.91) transplant cases. There were two major and one minor discrepancy for cancer cases (sensitivity 100%, specificity 96%) and two major and two minor disagreements for transplant cases (sensitivity 96%, specificity 75%). Average scan and viewing/reporting time were 12 and 3 min for cancer cases, compared to 18 and 5 min for transplant cases. A high diagnostic comfort level among pathologists emerged from the survey. Conclusions: These data demonstrate that the “Navigo” digital WSI system can reliably support an IO FS service involving complicated cancer and transplant cases.

Introduction: Successful implementation of whole slide imaging (WSI) for routine clinical practice has been accomplished in only a few pathology laboratories worldwide. We report the transition to an effective and complete digital surgical pathology workflow in the pathology laboratory at Cannizzaro Hospital in Catania, Italy. Methods: All (100%) permanent histopathology glass slides were digitized at ×20 using Aperio AT2 scanners. Compatible stain and scanning slide racks were employed to streamline operations. eSlide Manager software was bidirectionally interfaced with the anatomic pathology laboratory information system. Virtual slide trays connected to the two-dimensional (2D) barcode tracking system allowed pathologists to confirm that they were correctly assigned slides and that all tissues on these glass slides were scanned. Results: Over 115,000 glass slides were digitized with a scan fail rate of around 1%. Drying glass slides before scanning minimized them sticking to scanner racks. Implementation required introduction of a 2D barcode tracking system and modification of histology workflow processes. Conclusion: Our experience indicates that effective adoption of WSI for primary diagnostic use was more dependent on optimizing preimaging variables and integration with the laboratory information system than on information technology infrastructure and ensuring pathologist buy-in. Implementation of digital pathology for routine practice not only leveraged the benefits of digital imaging but also creates an opportunity for establishing standardization of workflow processes in the pathology laboratory.

We report a case of Wegener’s granulomatosis clinically mistaken for carcinoma in a 21-year-old girl presenting with an ulcerated mass of the nasopharynx associated with enlarged laterocervical nodes. The lesion was clinically suspected as malignant on the basis of clinical and radiological findings (namely, computed tomography scan and positron emission tomography). However, multiple biopsies were not conclusive for malignancy showing histological change suggestive of Wegener’s granulomatosis. A serum determination of cANCA supported the diagnosis of Wegener’s granulomatosis. Clinical findings and image studies suggested an erroneous diagnosis of malignancy whereas a definitive diagnosis of Wegener’s granulomatosis was achieved only after repeated biopsies thus leading to a correct therapeutic approach. The Wegener granulomatosis must be added to the list of the differential diagnoses of the masses of the nasopharynx associated with or without enlarged laterocervical nodes.

Ameloblastomas are locally aggressive jaw tumours with a high propensity for recurrence and are believed to arise from remnants of dental lamina or odontogenic epithelium. Extragnathic ameloblastomas are unusual, and primary sinonasal tract origin is very uncommon with few cases reported in the literature. We herein report a case of primary sinonasal ameloblastoma presented in a 74-year-old male with nasal obstruction, rhinorrhoea, and sinusitis. Nasal endoscopy showed the right nasal cavity completely obstructed by a polypoid lesion attached to the lateral nasal wall. A preoperative CT scan was performed showing a solid lesion, measuring 2 cm in the maximum diameter, extending from the nasopharynx area with obstruction of the ostiomeatal unit and sphenoethmoidal recess into the lateral pharyngeal space, laterally to the parotid, without continuity with maxillary alveola and antrum. The tumour was completely excised endoscopically, and a final diagnosis of ameloblastoma was rendered. At the 12-month followup, there was no evidence of recurrence.

Testicular carcinoid tumours (TCT) account for less than 1% of all testicular neoplasms. A 17-year-old male underwent radical orchiectomy for a painful indurated and increased in size right testicle; a mixed echogenic mass, with a central homogeneous area surrounded by a hypoechoic edge with calcifications was found at ultreasound with increased vascularity at color Doppler examination. Biochemical markers were within normal limits. These symptoms are not specific and the majority of TCT are only diagnosed on histopathology. Patients should undergo long-term biochemical and radiological follow-up given potential for delayed metastases, in one case 17 years after primary treatment.