Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 2nd International Conference on Digital Pathology & Image Analysis San Antonio, USA | Hilton San Antonio Airport .

Day 1 :

Keynote Forum

Daniel Racoceanu

Pontifical Catholic University of Peru, Peru

Keynote: Integrative computational pathology and beyond

Time : 10:00-10:45

Conference Series Digital Pathology 2017 International Conference Keynote Speaker Daniel Racoceanu photo
Biography:

Daniel Racoceanu is a Professor in Biomedical Imaging and Data Computing at the Pontifical Catholic University of Peru. Since 2016, he has a tenured Professor position at Sorbonne Université since 2011. His areas of competency are Medical Image Analysis, Pattern Recognition, and Machine Learning with his present research being mainly focused on Digital Pathology and its Integrative aspects. He has completed Dr.Habil. (2006) and PhD (1997) at University of Franche-Comté, France. He was Project Manager at General Electric Energy Products - Europe, before joining, in 1999, as a Associate Professor at the University of Franche-Comté and Research Fellow at FEMTO-ST Institute (French National Research Center - CNRS), Besancon, France. Between 2014 and 2016, he was a member of the Executive Board of the University Institute of Health Engineering of the Sorbonne Université, Paris. During the same period, he lead the Cancer Theranostics research team at the Bioimaging Lab, a joint research unit created between Sorbonne Université, CNRS and INSERM (French National Institute of Health and Medical Research). He participated in the creation of International Joint Research Unit (UMI CNRS) in Singapore, being the Director (from 2008 to 2014) of this joint research venture between the Sorbonne Université (SU), the French National Center for Scientific Research (CNRS), the National University of Singapore (NUS), the Agency for Science, Technology and Research (A*STAR), and the Univ. Grenoble Alpes (UGA), in Singapore. From 2009 to 2015, he was Full Professor (adj.) at the School of Computing, National University of Singapore (NUS).

Abstract:

Histopathology examination represents a milestone of the diagnostic and therapeutic decision. Concretized by the pathology report, essential to the multidisciplinary team (MDT) meetings in hospitals. It relies on professional observation and judgment, integrating: morphological criteria (tumor morphological identity) issued from standard and complementary (histochemistry, enzymology, hybridation in situ, scores) preparations’ observations, consolidated by clinical, radiological and biological contexts - among which, molecular. The future of histopathology is obviously digital (data and images). The challenge is to conciliate, in the framework of the healthcare, various usual missions as: doing the diagnosis for the patient in the present moment, warehousing the medical data for the patient record, and also feeding and structuring the research strategy - particularly in oncology. Due to it's important legal role, the pathology has a key position in the medical diagnostic. At the junction of medical imaging modalities and the omics, this medical exam represents the bottleneck enabling us to go to building a representative local database. We are initiating a program of care monitoring for which the milestones and the impact will be: the production of digital histopathology tools, the modeling of the pathway and the conceptualization of the associated massive database in Peru, with a strong wish to extend it to Andean and Latin American countries. This initiative will allow us to bring in and structure a database (whole slide images, omics, clinical data and metadata) corresponding to a very diverse population (mestizos, amerindians, european, asian-peruvian, afro-peruvians ...) coming from very different regions (coast, rainforest, highlands), with difficult access and difficult to reach, representative to Peru/Andean/Latin American regions.

Keynote Forum

Tomoo Itoh

Kobe University Hospital, Japan

Keynote: `A validation study of WSI-based primary diagnosis for malignant lymphoma

Time : 10:45-11:30

Conference Series Digital Pathology 2017 International Conference Keynote Speaker Tomoo Itoh photo
Biography:

Tomoo Itoh has completed his PhD at Hokkaido University Graduate School of Medicine and presently he is a Professor and Deputy Director of Diagnostic Pathology at Kobe University Hospital, Japan. He is a Board Certified Member of the Japanese Society of Pathology and Board Certified Member of the Japanese Society of Clinical Cytology. He was President of 15th Annual Meeting of Japanese Society of Digital Pathology held in Kobe in 2016, and now one of the core members of the Society.

Abstract:

Background: The digital pathology is an emerging technology, and its usage on routine practices is spreading worldwide rapidly. Very recently, FDA allowed marketing of first whole slide imaging (WSI) system for digital pathology, which enables us use the system even for primary diagnosis. This epoch-making achievement owes a lot to scientific evidences indicated that WSI is eligible for making accurate pathological diagnoses. However, those studies typically targeting small specimens alone and the cases requiring immunohistochemistry or special staining, such as malignant lymphoma, were excluded in many studies.

Objective: To provide an evidence of usability of WSI diagnosis for primary diagnosis of malignant lymphoma compared to conventional glass slide diagnosis and optical microscope.

Design: The cases of malignant lymphoma were retrieved from our case collection. The all slide glasses, including H&E and immunohistochemistry were digitized using a WSI scanner, NanoZoomer RS (Hamamatsu), with x40 magnification, and a well-trained pathologist for lymphoma diagnosis had reviewed and made diagnosis for the digitized cases with more than 2 months of washout time interval. Discrepancies between microscope slide and WSI diagnosis were classified into three categories; concordance, major discrepancy (defined as ones associated with significant difference in clinical treatment), and minor discrepancy (defined as ones associated with no significant difference in clinical treatment).

Result: At the time of writing this abstract, the study was still ongoing. Tentative data showed excellent concordance rate, over than 95%, and which was much better than we expected.

Conclusion: WSI is applicable for primary diagnosis of malignant lymphoma, if we make diagnoses with combination of adequate clinical information, H&E morphology, and immunohistochemistries.

 

  • Digital Pathology

Session Introduction

Ichiro Mori

International University of Health and Welfare School of Medicine, Japan

Title: Glass slide preparation and digital pathology

Time : 11:50-12:25

Speaker
Biography:

Ichiro Mori has completed his PhD from Gunma University, and Post-doctoral studies from Tokai University School of Medicine. He is Professor of Department of Pathology, International University of Health and Welfare, School of Medicine. He has published more than 25 papers in reputed journals.

Abstract:

Digital Pathology is now spreading rapidly. One of the key event is slide scanning because good digital image is crucial for Digital Pathology. WSI (Whole Slide Imaging) scanner is not an all-mighty machine but requires real good glass slide for scan. This time, I’d like to list-up several key-points in glass slide preparation and make proposal for solution. Many steps in glass slide preparation may cause trouble in WSI scanning like quality of thin slicing, mounting slices on glass, embedding, drying, pasting slide label, cover slipping, writing on cover slip, type of cover slip, wiping before scanning, and tissue fixation. WSI scanners are always required to achieve fast scanning speed and good focus. Good quality of thin slicing and slide preparation is exclusive for this purpose. If there are folding, waving, or scratch of slices, embedding dust, bubble, too-much embedding materials, protruded slide label or cover slip, letters or lines on cover slip, they all may mislead autofocus. Moreover, because image analysis is highly expected in Digital Pathology, specimen fixation will become big issue. In Japan, there is no standardization in fixing solution except for recommendation that is buffered 10% formalin. Even using the same fixative, there are wide range of fixing conditions like the size of fixing tissues, fixing temparature, fixing time, stirring fixatives, etc. To get good results in image analysis that will surely reflect patient therapy, we should stand against fixation issues.

Speaker
Biography:

Renu Ethirajan has completed her MBBS and DNB Pathology from Father Muller Medical College, Mangalore, India. She is currently working as Director Pathology for SigTuple, an organization that provides healthcare solutions driven by artificial intelligence and image processing. She has worked as a Consultant Hemato-Oncopathologist and has reported flowcytometry for more than 8 years at HCG Cancer Hospital, Bangalore. She is also trained in molecular diagnosis like fluoroscent in-situ hybradization and immuno-hematology. She has presented multiple papers in reputed CMEs and conferences. She has participated at the National Indian Conclave as a panelist on AI.

 

Abstract:

In this study, we evaluate SHONIT, a cloud based artificial intelligence (AI) system for automated analysis of images captured from peripheral blood smears. SHONIT’s performance in classification of WBCs was evaluated by comparing SHONIT’s results with hematology analyzers and manual microscopy for manually stained smears. The study was carried out over 100 samples. The cases included both normal and abnormal samples, wherein the abnormal cases were from patients with one or more quantitative or qualitative flagging. All the smears were created using Hemaprep auto-smearer and stained using May Grunwald Geimsa stain. They were scanned and analyzed by SHONIT for WBC differentials under 40X magnification. WBC morphological classification by SHONIT was verified by an experienced hematopathologist. Quantitative parameters were analysed by computing the mean absolute error of the WBC DC values between SHONIT and Sysmex XN3000 and between SHONIT and manual microscopy. The mean absolute error between WBC differential values of manual microscopy and SHONIT were 7.67%, 5.93%, 4.58%, 2.69%, 0.44% for neutrophil, lymphocyte, monocyte, eosinophil and basophil respectively. The mean absolute error between WBC differential values values of Sysmex XN3000 and SHONIT were 8.73%, 5.55%, 3.63%, 2.12%, 0.45% for neutrophil, lymphocyte, monocyte, eosinophil and basophil respectively. SHONIT has proven to be effective in locating and examining WBCs. It saves time, accelerates the turnaround-time and and increases productivity of pathologists. It has helped to overcome the time-consuming effort associated with traditional microscopy.

Speaker
Biography:

Anila Chughtai has completed her Bachelor of Medicine & Bachelor of Surgery degrees (MBBS) from Services Institute of Medical Sciences, Lahore. Currently, she is working as a second year Post-graduate trainee at Chughtai lab Lahore.

Abstract:

Collision tumor is a phenomenon in which two histologically different tumors exist as distinct lesions within same organ. Renal tumors represent 3% of adult malignancies and 2% of childhood malignancies but their synchronous occurrence is very rare. We present a case of synchronous tumors of kidney comprising clear cell renal cell carcinoma (CCRCC) and chromophobe renal cell carcinoma (CRCC). Grossly, two separate tumor nodules were identified with unremarkable intervening area. Microscopic examination from both tumor nodules revealed two different epithelial malignancies. Sections from larger nodules revealed nests of cells with distinct cell borders, hyperchromatic nuclei, perinuclear halos and eosinophilic granular cytoplasm while sections from smaller nodule revealed sheets and nests of cell with hyperchromatic nuclei, prominent nucleoli and clear to eosinophilic cytoplasm. Sections from intervening area showed renal parenchyma without any tumor infiltration. Larger tumor was positive for CK-7 and CD-117 immunohistochemical (IHC) stains while negative for CD-10 IHC stain confirming the diagnosis of CRCC. However smaller tumor was positive for CD-10 IHC stain and negative for CK-7 IHC stain confirming the diagnosis of CCRCC. Prognosis in such cases is determined by the more aggressive of the two tumors as in our case CCRCC is more aggressive with a 5 year survival rate of 50-60% as compared to CRCC with a 5 year survival rate of 80-90%.

Speaker
Biography:

Walaa Fikry Elbossaty is a PhD Post Research Fellow, Department of Chemistry, Faculty of Science-Damietta, Egypt. She received BSc (Chemistry/Biochemistry), MSc in Biochemistry from Mansoura University and PhD in Biochemistry/Molecular Biology from Damietta University.

Abstract:

Introduction & Aim: Antigen surface markers represent as the new prognostic tool for detection of acute leukemia. To aim of this study is to investigate the prevalence expression of lymphoid and myeloid antigen lineage in acute leukemias.

Material & Methods: This study included 100 acute leukemias patients. Specimens were selected from consecutive patients who had sufficient material available. Among the 100 patients in which a detailed history, hematological, clinical and immunophenotyping analysis were performed. This study showed distribution of immunophenotyping characters between studied AML and ALL cases.

Results: The most abundant immunophenotyping features in acute myeloid leukemia were cMPO, CD33, CD117, CD13, CD14 and CD64, while the most abundant immunophenotyping features in acute lymphoblastic leukemia were CD19, CD79a, TdT, CD20, CD10 and CD34.

Conclusion: cMPO which act as independent prognostic factor for AML, CD10 and TdT can be used as independent prognostic factor to differentiate between ALL and AML.

Speaker
Biography:

Faith I Onditi is a Senior Research Scientist at the Institute of Primate Research, Department of Tropical and Infectious Diseases, Malaria program. She holds a PhD in Biochemistry (Reproductive Immunology) from University of Nairobi and a Master’s degree in Molecular Medicine. Her research interest is in the development of baboon (Papio anubis)-Plasmodium knowlesi animal model for placental malaria, validating and utilizing the model in testing potential vaccines and drug candidates against malaria in pregnancy. She has published 6 papers in peer reviewed journals and has presented her work in 12 conferences.

Abstract:

Placental malaria (PM) causes adverse pregnancy outcomes in the mother and her foetus. It is difficult to study PM directly in humans due to ethical challenges. This study set out to bridge this gap by determining the outcome of PM in non-immune baboons in order to develop a non-human primate model for the disease.Ten pregnant baboons were acquired late in their third trimester (day 150) and randomly grouped as seven infected and three non-infected. Another group of four nulligravidae (non-pregnant) infected was also included in the analysis of clinical outcome. Malaria infection was intravenously initiated by Plasmodium knowlesi blood-stage parasites through the femoral vein on 160th day of gestation (for pregnant baboons). Peripheral smear, placental smear, haematological samples, and histological samples were collected during the study period. Findings in this study demonstrates the pathophysiology of placental malaria in non-immune baboons. Gross patholog presented similar features to human placentas. Placental parasitaemia was on average 19-fold higher than peripheral parasitaemia in the same animal. Placental damage and infiltration of immune cells was directly associated with P. knowlesi infection and subsequent sequestration in the baboon placenta. Therefore, our findings compare with key feature of placental falciparum malaria in humans. This presents the baboon as a new model for the characterization of malaria during pregnancy.