Pathology and Forensic Medicine, Artificial Intelligence, Oncology, Urology
90
Scopus Publications
Scopus Publications
Development of a deep learning-based tool for coronary artery stenosis evaluation in forensic autopsies using whole slide imaging Nicola Pigaiani, Shakiba Sharifi, Marianna Garavello, Francesco Setti, Francesco Ausania, Federica Bortolotti, Alberto Chighine, Ernesto D’Aloja, Pamela Rodegher, Serena Ammendola, Matteo Brunelli, Marco Cristani, Stefano Gobbo International Journal of Legal Medicine, 2026 BACKGROUND: Cardiovascular disease is a leading cause of mortality, with coronary artery disease accounting for over 60% of cases in adults. Accurate quantification of coronary stenosis in forensic autopsies is crucial for determining causality between pathological findings and death, but is hindered by subjective visual assessments and inter-observer variability. This study aimed to develop an AI-driven tool using whole-slide images for objective stenosis measurement in forensic investigations. MATERIALS AND METHODS: From 98 anonymized H&E-stained autopsy slides (234 coronary sections), 103 high-quality regions of interest were selected and split into training (n = 82), validation (n = 14), and test (n = 7) datasets. Annotations delineated lumen, internal elastic lamina, and external elastic lamina using QuPath. A SegFormer-B0 transformer model was trained with data augmentation, weighted cross-entropy loss, and AdamW optimization. Post-processing enforced anatomical structural hierarchy and generated hybrid confidence maps. RESULTS: On validation dataset, agreement with ground truth was excellent (MAE 3.22% points; RMSE 4.00; MAPE 6.07%; r = 0.986; ICC = 0.986), with slight underestimation. Bland–Altman bias was − 1.36 pp (95% LoA − 9.01 to 6.28 pp), indicating performance across severities. On the test set, accuracy improved (MAE 1.01 pp; RMSE 1.50; MAPE 2.11%; r = 0.998; ICC = 0.995) and outperformed three pathologists’ visual estimates (MAE 16.11, 8.18, 4.79 pp). Bland–Altman bias for the model was − 0.82 pp with tight limits of agreement (− 3.48 to 1.83 pp). Total inference time was 199.08 s for seven cases (28.44 s/image). CONCLUSIONS: WSI-based transformer pipeline enables rapid, auditable, and reproducible coronary stenosis measurement, reducing inter-observer variability and supporting standardized interpretation in forensic investigations.
AIDA: AI-Driven Intelligent Diagnostics and Analytics Zanxi Ruan, Stefano Gobbo, Luca Cima, Mattia Mondo, Shakiba Sharifi, Enrico Munari, Aldo Scarpa, Omar Shahbaz Khan, Stefán Ólafsson, Andrea Giachetti, Francesco Setti, Yiming Wang, Björn Þór Jónsson, Marco Cristani Lecture Notes in Computer Science, 2026
Galileo—an Artificial Intelligence tool for evaluating pre-implantation kidney biopsies Albino Eccher, Vincenzo L’Imperio, Liron Pantanowitz, Giorgio Cazzaniga, Fabio Del Carro, Stefano Marletta, Giovanni Gambaro, Antonella Barreca, Jan Ulrich Becker, Stefano Gobbo, Vincenzo Della Mea, Federico Alberici, Fabio Pagni, Angelo Paolo Dei Tos Journal of Nephrology, 2025 Background Pre-transplant procurement biopsy interpretation is challenging, also because of the low number of renal pathology experts. Artificial intelligence (AI) can assist by aiding pathologists with kidney donor biopsy assessment. Herein we present the “Galileo” AI tool, designed specifically to assist the on-call pathologist with interpreting pre-implantation kidney biopsies. Methods A multicenter cohort of whole slide images acquired from core-needle and wedge biopsies of the kidney was collected. A deep learning algorithm was trained to detect the main findings evaluated in the pre-implantation setting (normal glomeruli, globally sclerosed glomeruli, ischemic glomeruli, arterioles and arteries). The model obtained on the Aiforia Create platform was validated on an external dataset by three independent pathologists to evaluate the performance of the algorithm. Results Galileo demonstrated a precision, sensitivity, F1 score and total area error of 81.96%, 94.39%, 87.74%, 2.81% and 74.05%, 71.03%, 72.5%, 2% in the training and validation sets, respectively. Galileo was significantly faster than pathologists, requiring 2 min overall in the validation phase (vs 25, 22 and 31 min by 3 separate human readers, p < 0.001). Galileo-assisted detection of renal structures and quantitative information was directly integrated in the final report. Conclusions The Galileo AI-assisted tool shows promise in speeding up pre-implantation kidney biopsy interpretation, as well as in reducing inter-observer variability. This tool may represent a starting point for further improvements based on hard endpoints such as graft survival. Graphical Abstract
iForensic, multicentric validation of digital whole slide images (WSI) in forensic histopathology setting according to the College of American Pathologists guidelines Nicola Pigaiani, Antonio Oliva, Vito Cirielli, Simone Grassi, Vincenzo Arena, Luca-Maria Solari, Naomi Tatriele, Dario Raniero, Matteo Brunelli, Stefano Gobbo, Aldo Scarpa, Liron Pantanowitz, Pamela Rodegher, Federica Bortolotti, Francesco Ausania International Journal of Legal Medicine, 2025 Pathology has benefited from the rapid progress of image-digitizing technology during the last decade. However, the application of digital whole slide images (WSI) in forensic pathology still needs to be improved. WSI validation is crucial to ensure diagnostic performance, at least equivalent to glass slides and light microscopy. The College of American Pathologists Pathology and Laboratory Quality Center recently updated internal digital pathology system validation recommendations. Following these guidelines, this pilot study aimed to validate the performance of a digital approach for forensic histopathological diagnosis. Six independent skilled forensic pathologists from different forensic medicine institutes evaluated 100 glass slides of forensic interest (80 stained with standard hematoxylin and eosin, 20 with special staining), including different organs and tissues, with light microscopy (Olympus BX51, Tokyo, Japan). Glass slides were scanned using the Aperio GT 450 DX Digital Slides Scanner (Leica Biosystems, Nussloch, Germany). After two wash-out weeks, forensic pathologists evaluated WSIs in front of a widescreen using computer devices with dedicated software (O3 viewer, O3 Enterprise, Zucchetti, Trieste, Italy). Side-by-side comparisons between diagnoses performed on tissue glass slides versus WSIs were above the threshold stated in the validation guidelines (mean concordance of 97.8%). CSUQ Version 3 questionnaire showed high satisfaction for all pathologists (mean result: 6.6/7). Our institutional digital forensic pathology system has been validated for practical casework application. This approach opens new scenarios in practical forensic casework investigations, such as sharing live histological ex-glass slides online, as well as educational and research perspectives, with improving impacts on the whole daily workflow.
Forensic value of soft tissue detachments from the hyoid bone in death due to strangulation asphyxia Giovanna Del Balzo, Guido Pelletti, Dario Raniero, Alessia Farinelli, Andrea Uberti, Elisa Vermiglio, Gabriele Molteni, Riccardo Nocini, Stefano Gobbo, Francesco Taus, Albino Eccher, Claudio Lucchini, Matteo Brunelli Advances in Clinical and Experimental Medicine, 2025 BACKGROUND There are no unequivocal histopathological findings for the diagnosis of fatal asphyxia due to neck compression. From the observation of a series of asphyxiation cases, we noted, during microscopic analysis, a high frequency of "detachment" of soft tissues from the hyoid bone. This specifically refers to the presence of an optical space between the surface of the hyoid bone and soft tissues. OBJECTIVES We aimed to evaluate the detachment of soft tissues from the hyoid bone as specific histological evidence of death due to strangulation asphyxia. MATERIAL AND METHODS Ten blocks were taken from deaths due to external mechanical compression of the neck (strangulation asphyxia, group A), 22 blocks were taken from deaths for other causes without trauma to the neck (group B), and 38 blocks were obtained from living subjects that have undergone laryngectomies (group C). The presence/absence of detachments were compared between the 3 groups (A, B and C) using Fisher's exact test. RESULTS The detachment of soft tissues from the hyoid bone was observed in 5 cases (50%) in group A, 6 cases (27.2%) in group B, and 17 cases (44.3%) in group C. The sensitivity and specificity of the presence of the detachment in group A were 0.5 (95% confidence interval (95% CI): 0.38-0.62) and 0.57 (95% CI: 0.45-0.69), respectively. The comparison between the 3 groups and the presence/absence of soft tissue detachment showed no statistically significant differences between the groups (p = 0.329), clarifying that soft tissue detachment is a nonspecific variable for all 3 situations. CONCLUSIONS Detachment of soft tissues has poor value as a single element to favor the diagnosis of asphyxia due to violent compression of the neck and should be interpreted as an artifactual finding, unrelated to the neck injury or injury vitality.
Artificial intelligence-based algorithms for the diagnosis of prostate cancer: A systematic review Stefano Marletta, Albino Eccher, Filippo Maria Martelli, Nicola Santonicco, Ilaria Girolami, Aldo Scarpa, Fabio Pagni, Vincenzo L’Imperio, Liron Pantanowitz, Stefano Gobbo, Davide Seminati, Angelo Paolo Dei Tos, Anil Parwani American Journal of Clinical Pathology, 2024 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.
Characterization of two transcriptomic subtypes of marker-null large cell carcinoma of the lung suggests different origin and potential new therapeutic perspectives Michele Simbolo, Giovanni Centonze, Anastasios Gkountakos, Valentina Monti, Patrick Maisonneuve, Stela Golovco, Giovanna Sabella, Alessandro Del Gobbo, Stefano Gobbo, Stefano Ferrero, Alessandra Fabbri, Carlotta Pardo, Giovanna Garzone, Natalie Prinzi, Sara Pusceddu, Adele Testi, Luigi Rolli, Alessandro Mangogna, Luisa Bercich, Mauro Roberto Benvenuti, Emilio Bria, Sara Pilotto, Alfredo Berruti, Ugo Pastorino, Carlo Capella, Maurizio Infante, Michele Milella, Aldo Scarpa, Massimo Milione Virchows Archiv, 2024 Pulmonary large cell carcinoma (LCC) is an undifferentiated neoplasm lacking morphological, histochemical, and immunohistochemical features of small cell lung cancer, adenocarcinoma (ADC), or squamous cell carcinoma (SCC). The available molecular information on this rare disease is limited. This study aimed to provide an integrated molecular overview of 16 cases evaluating the mutational asset of 409 genes and the transcriptomic profiles of 20,815 genes. Our data showed that TP53 was the most frequently inactivated gene (15/16; 93.7%) followed by RB1 (5/16; 31.3%) and KEAP1 (4/16; 25%), while CRKL and MYB genes were each amplified in 4/16 (25%) cases and MYC in 3/16 (18.8%) cases; transcriptomic analysis identified two molecular subtypes including a Pure-LCC and an adenocarcinoma like-LCC (ADLike-LCC) characterized by different activated pathways and cell of origin. In the Pure-LCC group, POU2F3 and FOXI1 were distinctive overexpressed markers. A tuft cell-like profile and the enrichment of a replication stress signature, particularly involving ATR, was related to this profile. Differently, the ADLike-LCC were characterized by an alveolar-cell transcriptomic profile and association with AIM2 inflammasome complex signature. In conclusion, our study split the histological marker-null LCC into two different transcriptomic entities, with POU2F3, FOXI1, and AIM2 genes as differential expression markers that might be probed by immunohistochemistry for the differential diagnosis between Pure-LCC and ADLike-LCC. Finally, the identification of several signatures linked to replication stress in Pure-LCC and inflammasome complex in ADLike-LCC could be useful for designing new potential therapeutic approaches for these subtypes.
TROP-2, NECTIN-4 and predictive biomarkers in sarcomatoid and rhabdoid bladder urothelial carcinoma Matteo Brunelli, Stefano Gobbo, Giorgio Malpeli, Grazia Sirgiovanni, Claudia Caserta, Enrico Munari, Simona Francesconi, Anna Caliò, Guido Martignoni, Alessia Cimadamore, Alessandro Veccia, Alessandro Antonelli, Marcello Tucci, Francesco Pierconti, Isabelle Malak Hattab, Albino Eccher, Stefano Ascani, Michele Milella, Lucio Buffoni, Liang Cheng, Sergio Bracarda Pathologica, 2024
Minimally invasive versus open distal pancreatectomy for resectable pancreatic cancer (DIPLOMA): an international randomised non-inferiority trial Maarten Korrel, Leia R. Jones, Jony van Hilst, Gianpaolo Balzano, Bergthor Björnsson, Ugo Boggi, Svein Olav Bratlie, Olivier R. Busch, Giovanni Butturini, Giovanni Capretti, Riccardo Casadei, Bjørn Edwin, Anouk M.L.H. Emmen, Alessandro Esposito, Massimo Falconi, Bas Groot Koerkamp, Tobias Keck, Ruben H.J. de Kleine, Dyre B. Kleive, Arto Kokkola, Daan J. Lips, Sanne Lof, Misha D.P. Luyer, Alberto Manzoni, Ravi Marudanayagam, Matteo de Pastena, Nicolò Pecorelli, John N. Primrose, Claudio Ricci, Roberto Salvia, Per Sandström, Frederique L.I.M. Vissers, Ulrich F. Wellner, Alessandro Zerbi, Marcel G.W. Dijkgraaf, Marc G. Besselink, Mohammad Abu Hilal, Adnan Alseidi, Constanza Aquilano, Johanna Arola, Denise Bianchi, Rachel Brown, Daniela Campani, Joanne ChinAleong, Jerome Cros, Lyubomira Dimitrova, Claudio Doglioni, Safi Dokmak, Russell Dorer, Michael Doukas, Jean Michel Fabre, Giovanni Ferrari, Viacheslay Grinevich, Stefano Gobbo, Thilo Hackert, Marius van den Heuvel, Clement Huijsentruijt, Mar Iglesias, Casper Jansen, Igor Khatkov, David Kooby, Marco Lena, Claudio Luchini, Krishna Menon, Patrick Michenet, Quintus Molenaar, Anna Nedkova, Andrea Pietrabissa, Mihaela Raicu, Rushda Rajak, Branislava Rankovic, Aniko Rendek, Benjamin Riviere, Antonio Sa Cunha, Olivier Saint Marc, Patricia Sanchez Velazquez, Donatella Santini, Aldo Scarpa, Mylene Sebagh, Donald Sears, Mihir Shah, Zahir Soonawalla, Paola Spaggiari, Lars Tharun, Tore Tholfsen, Ales Tomazic, Alessandro Vanoli, Caroline Verbeke, Joanne Verheij, Moritz Von Winterfeld, Roeland de Wilde, Vincent Yip, Yoh Zen Lancet Regional Health Europe, 2023
Digital pathology world tour Paola Chiara Rizzo, Alessandro Caputo, Eddy Maddalena, Nicolò Caldonazzi, Ilaria Girolami, Angelo Paolo Dei Tos, Aldo Scarpa, Marta Sbaraglia, Matteo Brunelli, Stefano Gobbo, Stefano Marletta, Liron Pantanowitz, Vincenzo Della Mea, Albino Eccher Digital Health, 2023
Serous Neoplasms Paola Capelli, Paolo Tinazzi Martini, Giovanni Morana, Riccardo de Robertis, Claudio Luchini, Stefano Gobbo, Mirko D’Onofrio Imaging and Pathology of Pancreatic Neoplasms A Pictorial Atlas Second Edition, 2022
Neuroendocrine Neoplasms Riccardo De Robertis, Mirko D’Onofrio, Paolo Tinazzi Martini, Stefano Gobbo, Maria Gaia Mastrosimini, Lavinia Stefanizzi, Alessandro Beleù, Luca Geraci, Aldo Scarpa, Paola Capelli Imaging and Pathology of Pancreatic Neoplasms A Pictorial Atlas Second Edition, 2022
Role of next-generation genomic sequencing in targeted agents repositioning for pancreaticoduodenal cancer patients Davide Melisi, Alessandro Cavaliere, Stefano Gobbo, Giulia Fasoli, Valentina Allegrini, Francesca Simionato, Marina Gaule, Simona Casalino, Camilla Pesoni, Camilla Zecchetto, Valeria Merz, Andrea Mambrini, Emilio Barbi, Roberto Girelli, Alessandro Giardino, Isabella Frigerio, Roberto Scalamogna, Arianna Avitabile, Silvia Castellani, Michele Milella, Giovanni Butturini Pancreatology, 2021
Genetic Analysis of Small Well-differentiated Pancreatic Neuroendocrine Tumors Identifies Subgroups with Differing Risks of Liver Metastases Antonio Pea, Jun Yu, Luigi Marchionni, Michael Noe, Claudio Luchini, Alessandra Pulvirenti, Roeland F. de Wilde, Lodewijk A. Brosens, Neda Rezaee, Ammar Javed, Peter Chianchiano, Stefano Gobbo, Paolo Regi, Roberto Salvia, Claudio Bassi, Jin He, Matthew J. Weiss, John L. Cameron, G. Johan A. Offerhaus, Ralph H. Hruban, Rita T. Lawlor, Aldo Scarpa, Christopher M. Heaphy, Laura D. Wood, Christopher L. Wolfgang Annals of Surgery, 2020
A phase II study of liposomal irinotecan with 5-fluorouracil, leucovorin and oxaliplatin in patients with resectable pancreatic cancer: the nITRO trial Francesca Simionato, Camilla Zecchetto, Valeria Merz, Alessandro Cavaliere, Simona Casalino, Marina Gaule, Mirko D’Onofrio, Giuseppe Malleo, Luca Landoni, Alessandro Esposito, Giovanni Marchegiani, Luca Casetti, Massimiliano Tuveri, Salvatore Paiella, Filippo Scopelliti, Alessandro Giardino, Isabella Frigerio, Paolo Regi, Paola Capelli, Stefano Gobbo, Armando Gabbrielli, Laura Bernardoni, Vita Fedele, Irene Rossi, Cristiana Piazzola, Serena Giacomazzi, Martina Pasquato, Morena Gianfortone, Stefano Milleri, Michele Milella, Giovanni Butturini, Roberto Salvia, Claudio Bassi, Davide Melisi Therapeutic Advances in Medical Oncology, 2020
Downstaging in Stage IV Pancreatic Cancer: A New Population Eligible for Surgery? Isabella Frigerio, Paolo Regi, Alessandro Giardino, Filippo Scopelliti, Roberto Girelli, Claudio Bassi, Stefano Gobbo, Paolo Tinazzi Martini, Paola Capelli, Mirko D’Onofrio, Giuseppe Malleo, Laura Maggino, Elena Viviani, Giovanni Butturini Annals of Surgical Oncology, 2017
Renal cell carcinoma with smooth muscle stroma lacks chromosome 3p and VHL alterations Guido Martignoni, Matteo Brunelli, Diego Segala, Stefano Gobbo, Ioana Borze, Lilit Atanesyan, Suvi Savola, Luisa Barzon, Giulia Masi, Regina Tardanico, Shaobo Zhang, John N Eble, Marco Chilosi, Tom Böhling, Liang Cheng, Brett Delahunt, Sakari Knuutila Modern Pathology, 2014
FISH scoring on paraffin sections versus single-cell suspension for chromophobe renal carcinoma and renal oncocytoma Anticancer Research, 2011
Many facets of chromosome 3p cytogenetic findings in clear cell renal carcinoma: The need for agreement in assessment FISH analysis to avoid diagnostic errors Histology and Histopathology, 2011
Utility of tissue microarrays for assessment of chromosomal abnormalities in chromophobe renal cell carcinoma Analytical and Quantitative Cytology and Histology, 2009
Fluorescent cytogenetics of renal cell neoplasms Pathologica, 2008
Renal cell carcinomas with papillary architecture and clear cell components: The utility of immunohistochemical and cytogenetical analyses in differential diagnosis: Editorial comment International Braz J Urol, 2008
Schwannoma of the kidney Stefano Gobbo, John N Eble, Jiaoti Huang, David J Grignon, Mingsheng Wang, Guido Martignoni, Matteo Brunelli, Liang Cheng Modern Pathology, 2008
Renal tumors: Epidemiology, etiology, and clinical history: Pathology: Tumor genetics: Differential diagnosis and use of ancillary methods for diagnosis: Principles of staging and grading: Pediatric tumors Clinical Pathology of Urological Tumours, 2007
Chondroid syringoma with extensive ossification Albino Eccher, Matteo Brunelli, Stefano Gobbo, Daniela Dalfior, Gordan Dvornik, Mattia Barbareschi, Claudia Parolini, Fabio Menestrina, Guido Martignoni International Journal of Surgical Pathology, 2007