ECP 2022 Abstract Book

Virchows Archiv (2022) 481 (Suppl 1):S1–S364 13 M. Riefolo*, M. Sabatino, C. Baldovini, C. Marcelli, L. Potena, O. Leone *Pathology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Italy Background & objectives: Acute Myocarditis (AM) has been much discussed as one of the most frequent cardiac complications of COVID-19. Despite serious clinical suspicion, however, there is no substantial EMB histological series. Methods: At the S.Orsola Bologna Centre, cardiologic referral Centre for Emilia-Romagna region, we retrospectively analysed and compared two groups of patients who underwent EMB for clinical suspicion of myocarditis in the 5 years pre-pandemic (2015-2019, Group 1) and in the initial 15 months of the pandemic (April 2020- June 2021, Group 2), before the vaccine became generally available in our region. Results: In group 1, of 65 patients who underwent EMB, 31 (47.7%) had a histological diagnosis of AM, with histotype: lymphocytic in 24 cases, giant cell in 1, toxic in 1, mixed in 1. Extension of inflammation was focal in 19 and multifocal/diffuse in 12. Month ratio in suspected cases was 1.1; in histological confirmed cases 0.5. In group 2, of 23 patients 13 had EMB positive for AM (56.5%), with histotype: lymphocytic in 8 cases, giant cell in 1, eosinophilic in 2, mixed in 2. Extension of inflammation: was focal in 7 and multifocal/diffuse in 6. Month ratio in suspected cases was 1.5, in histological confirmed AM, 0.9. Conclusion: In this study we analysed the frequency, clinical presentation and histological parameters of suspected AM before and during the pandemic. During the pandemic there was an increase in number of cases, in terms of both clinical suspicion and of histologic confirmation at EMB. The cases were generally more severe and showed a different range of histotypes, but there was no real correlation with SARS-CoV-2. OFP-11-004 From conventional congenital cardiac surgery to molecular car- diac surgery: between darkness and light. New paradigms for investigations and treatments during pregnancy A. Capuani* *Private Organization Carrara, Italy Background & objectives: We advocate new biological models and protocols for investigation and treatment of severe CHD on the light of nowadays spectacular progresses of the Molecular Biology with the Next Generation Sequency (NGS), Microarray Technolo- gies and CRISPR-Cass9 Technique. Methods: We reconsidered the embryogenesis and the morphol- ogy of the most severe forms of CHD, from TF to Transpositions and Univentricular Hearts, considering the diagnostic potentiality of maternal liquid biopsies in pregnancy and with emphasis on the CHD embryogenetic patterns. (Capuani et al. Ann Thorac Surg 1995, J Cardiothorac Surg 2014, Virchow’s Archives 2015, 2016, 2020). Results: We found a common morphological denominator encom- passing all pathological cardiac settings: the Trabecula Septomar- ginalis (Leonardo’s Cord) sequential counterclockwise malrota- tion. Several genes are involved in the process with over and under expression and network interactions. Microarray and NGS analysis applied early in pregnancy and to each single step of the malrota- tion may lead to a very early diagnosis and possible treatments. We present our research protocol. Conclusion : Each malformed cardiac phenotype has a specific molecular profile. The TSM malrotation protocol encompass all cardiac pathological phenotypes and is proposed as a model for investigation and treatment of CHD early in pregnancy by NGS, Microarray and CRISPR-Cass9 technique, what we refer as Molec- ular Cardiac Surgery. OFP-11-005 Reporting guidelines for pathology AI research – a review C. Mcgenity*, D. Treanor *Leeds Teaching Hospitals NHS Trust, United Kingdom Background & objectives: An explosion of interest into applications of artificial intelligence (AI) is transforming pathology research. Complete reporting of research is essential for avoiding research waste and benefitting patients. The objective of this work was identifying reporting guidelines for pathology AI research. Methods: The Equator Network library of 499 reporting guidelines and extensions was systematically searched to identify those applicable to pathology AI research. Inclusion and exclusion criteria were used and guidance was screened for utility at different stages of research and for a range of study types. Items were compiled to create a summary for easy identification of useful guidance and templates. Results: 70 reporting guidelines and extensions applicable to stages of pathology AI research were identified. These were categorised into 5 groups: Literature & Research Priorities, Discovery, Clinical Trial, Implementation and Post-Implementation & Guidelines. A summary resource was developed for pathology AI researchers, with links to guidelines for these 5 groups, to assist in complete reporting of research. Guidelines currently in development and those useful at multiple stages of research were also highlighted. Our group recently published a study demonstrating that essential information is underreported in pathology AI studies, making replication difficult. Therefore, this summary will be shared publicly to highlight the availability of reporting guidance to the pathology AI research community. Conclusion: Replication and research waste are recognised to be problematic in AI research. Reporting guidelines can be used as templates to ensure the essential information needed to replicate research is included within journal articles and abstracts. Reporting guidelines are available and useful for many study types, but greater awareness is needed to encourage researchers to utilise them and for journals to adopt them. This review and summary resource highlights guidance to pathology AI researchers, aiming to improve completeness of reporting. Funding: Dr McGenity is funded by Leeds Hospitals Charity and the National Institute for Health Research (NIHR). Prof. Treanor is funded by National Pathology Imaging Co-operative (NPIC). NPIC (project no. 104687) is supported by a £50m investment from the Data to Early Diagnosis and Precision Medicine strand of the Government’s Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI). OFP-11-006 A holistic evaluation of three-dimensional biomarker expres- sion and genetic alterations in non-small cell lung cancer using tissue clearing technology L. Wang*, Y. Hsieh, Y. Hung, Y. Chen, Y. Lin, Y. Lin, T. Chou *Taipei Veterans General Hospital, Taiwan Background & objectives: The common practice of assessing programmed death-ligand 1 (PD-L1) expression based on a single section may not be representative. To overcome this problem, we developed a novel protocol that can make formalin-fixed, paraf- fin-embedded tissue translucent, allowing three-dimensional (3D) imaging. S45