Diagnosis Of The Chronic Lymphocytic Leukemia (CLL) Using A Raman-Based Scanner Optimized For Blood Smear Analysis (M3s Project)

Introduction/ Background In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. Aims The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. Methods Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labeling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a microscope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted to immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). Results Currently, a total of 60 patients (CLL and healthy) were included in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (Random Forest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information.

Nouvelles perspectives pour le vidéodisque

Le vidéodisque, associé à des ressources informatiques et à des réseaux de transmission (en bande étroite ou large) offre des possibilités nombreuses de partage de ressources. Nous nous limitons à la présentation de deux services en cours de développement, qui sont une excellente illustration des services exploitables sur les réseaux large bande : 1. La téléconférence (en bande étroite) assistée par vidéodisque (local). 2. Le télémontage, exploité en site central. La téléconférence permet l'établissement d'une communication parlée entre deux utilisateurs, s'appuyant sur des éléments visuels en provenance d'un vidéodisque et d'éléments vidéographiques (dessins, entourages), produits en temps réel par l'utilisateur. Le télémontage permet de sélectionner et de ré-organiser un grand nombre d'images, qui seront ensuite complétées par des sous-titres et des éléments sonores. Les outils fournis à l'utilisateur pouvant être très sophistiqués, le programme permet d'en adapter la complexité à son niveau d'expertise

A cognitive virtual microscopic framework for knowlege-based exploration of large microscopic images in breast cancer histopathology

10.1109/IEMBS.2009.5334739Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 20093697-370

Standards and specifications in pathology: image management, report management and terminology

For making medical decisions, healthcare professionals require that all necessary information is both correct and easily available. Collaborative Digital Anatomic Pathology refers to the use of information technology that supports the creation and sharing or exchange of information, including data and images, during the complex workflow performed in an Anatomic Pathology department from specimen reception to report transmission and exploitation. Collaborative Digital Anatomic Pathology is supported by standardization efforts toward knowledge representation for sharable and computable clinical information. The goal of the international integrating the Healthcare Enterprise (IHE) initiative is precisely specifying how medical informatics standards should be implemented to meet specific health care needs and making systems integration more efficient and less expensive. The IHE Anatomic Pathology initiative was launched to implement the best use of medical informatics standards in order to produce, share and exchange machine-readable structured reports and their evidences (including whole slide images) within hospitals and across healthcare facilities. DICOM supplements 122 and 145 provide flexible object information definitions dedicated respectively to specimen description and WSI acquisition, storage and display. The profiles "Anatomic Pathology Reporting for Public Health" (ARPH) and "Anatomic Pathology Structured Report" (APSR) provide standard templates and transactions for sharing or exchanging structured reports in which textual observations - encoded using PathLex, an international controlled vocabulary currently being mapped to SNOMED CT concepts - may be bound to digital images or regions of interest in images. Current implementations of IHE Anatomic Pathology profiles in North America, France and Spain demonstrate the applicability of recent advances in standards for Collaborative Digital Anatomic Pathology. The use of machine-readable format of Anatomic Pathology information supports the development of computer-based decision support as well as secondary use of Anatomic Pathology information for research or public health

Application Of Raman Microscopy For The Diagnosis Of The Chronic Lymphocytic Leukemia (Cll) : PS01.01 | ePoster Session I

INTRODUCTION / BACKGROUND: In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. AIMS: The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. METHODS: Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labelling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a micro- scope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). RESULTS: Currently, a total of 60 patients (CLL and healthy) were in- cluded in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (RandomForest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information