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Haragan A, Nekolla K, Kapil A, Brieu N, Widmaier M, Budco A, Kanchev I, Testori M, Chan J, Schneider K, Hidalgo Sastre A, Baehner M, Schmidt G, Field J, Davies M, Gosney J. FP07.02 Deep Learning Based Analysis of Multiplex IHC Accurately Interprets PD-L1 and Provides Prognostic Information in NSCLC. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.01.102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Groher M, Zimmermann J, Musa H, Ackermann A, Surace M, Rodriguez-Canales J, Rebelatto M, Steele K, Kapil A, Brieu N, Rognoni L, Segerer F, Spitzmüller A, Tan TH, Schäpe A, Schmidt G. Insights into the tumour immune microenvironment using tissue phenomics to drive cancer immunotherapy. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz253.062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Nekolla K, Brieu N, Gavriel C, Widmaier M, Budco A, Medrikova D, Kanchev I, Testori M, Chan J, Dundee P, Anderson P, Lawrentschuk N, Wong LM, Phan P, Gibbs P, Harrison D, Baehner M, Caie P, Tran B, Schmidt G. Prognostic immunoprofiling of muscle invasive bladder cancer (MIBC) patients in a multicentre setting. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz239.067] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Brieu N, Gavriel C, Harrison D, Schmidt G, Caie P. Augmenting TNM staging with machine learning-based immune profiling for improved prognosis prediction in muscle-invasive bladder cancer patients. Ann Oncol 2018. [DOI: 10.1093/annonc/mdy269.091] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Andres C, Andres-Belloni B, Hein R, Biedermann T, Schäpe A, Brieu N, Schönmeyer R, Yigitsoy M, Ring J, Schmidt G, Harder N. iDermatoPath - a novel software tool for mitosis detection in H&E-stained tissue sections of malignant melanoma. J Eur Acad Dermatol Venereol 2017; 31:1137-1147. [PMID: 28107565 DOI: 10.1111/jdv.14126] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 12/12/2016] [Indexed: 11/29/2022]
Abstract
BACKGROUND Malignant Melanoma (MM) is characterized by a growing incidence and a high malignant potential. Besides well-defined prognostic factors such as tumour thickness and ulceration, the Mitotic Rate (MR) was included in the AJCC recommendations for diagnosis and treatment of MM. In daily routine, the identification of a single mitosis can be difficult on haematoxylin and eosin slides alone. Several studies showed a big inter- and intra-individual variability in detecting the MR in MM even by very experienced investigators, thus raising the question for a computer-assisted method. OBJECTIVE The objective was to develop a software system for mitosis detection in MM on H&E slides based on machine learning for diagnostic support. METHODS We developed a computer-aided staging support system based on image analysis and machine learning on the basis of 59 MM specimens. Our approach automatically detects tumour regions, identifies mitotic nuclei and classifies them with respect to their diagnostic relevance. A convenient user interface enables the investigator to browse through the proposed mitoses for fast and efficient diagnosing. RESULTS A quantitative evaluation on manually labelled ground truth data revealed that the tumour region detection yields a medium spatial overlap index (dice coefficient) of 0.72. For the mitosis detection, we obtained high accuracies of above 83%. CONCLUSION On the technical side, the developed iDermatoPath software tool provides a novel approach for mitosis detection in MM, which can be further improved using more training data such as dermatopathologist annotations. On the practical side, a first evaluation of the clinical utility was positive, albeit this approach provides most benefit for difficult cases in a research setting. Assuming all slides to be digitally processed and reported in the near future, this method could become a helpful additional tool for the pathologist.
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Affiliation(s)
- C Andres
- Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany.,Labor für Dermatohistologie, Munich, Germany
| | - B Andres-Belloni
- Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | - R Hein
- Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | - T Biedermann
- Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | | | - N Brieu
- Definiens AG, Munich, Germany
| | | | | | - J Ring
- Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
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Robert J, Pantel A, Merens A, Lavigne JP, Nicolas-Chanoine MH, Brieu N, Vrain A, Scanvic A, Porcheret H, Garnier P, Bertrand X, Descamps D, Hombrouck C, Soullie B, Heym B, de Montclos H, Garrec H, Levast M, Mendes-Martins L, Decousser JW, Huet C, Bert F, Herzig V, Klein JP, Nebbad B, Hendricx S, Verhaeghe A, Lafaurie C, Lanselle C, Elsayed F, Carrer A, Drieux-Rouzet L, Evreux F, Varache C, Wallet F, Martin C, Le-Bris JM, Moulhade MC, Deville E, Menouni O, Jean-Pierre H, Pierrot P, Delarbre JM, Coude B, Foca M, Degand N, Prots L, Pantel A, Adam MN, Laurens E, Raskine L, Laouira S, Arlet G, Sanchez R, Peuchant O, Grau V, Laurent C, De-Champs C, Vachee A, Harriau P, Merens A, Belmonte O, Michel G, Henry C, Picot S, Glatz I, Gueudet T, Honderlick P, Cavalie L, Galinier JL, Patoz P, van-der-Mee-Marquet N, Haguenoer E, Canis F, Kassis-Chikhany N, Le-Garrec Y. Incidence rates of carbapenemase-producing Enterobacteriaceae clinical isolates in France: a prospective nationwide study in 2011-12. J Antimicrob Chemother 2014; 69:2706-12. [DOI: 10.1093/jac/dku208] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
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Foulongne V, Brieu N, Gay B, Segondy M. [Human bocavirus (HBoV): from discovery through molecular screening to observation by electron microscopy]. Virologie (Montrouge) 2008; 12:219-221. [PMID: 36131458 DOI: 10.1684/12-3.2011.11046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- V Foulongne
- Laboratoire de virologie, pôle d'infectiologie, hôpital Saint-Éloi, centre hospitalier universitaire de Montpellier, 34295 Montpellier Cedex 5
| | - N Brieu
- Laboratoire de virologie, pôle d'infectiologie, hôpital Saint-Éloi, centre hospitalier universitaire de Montpellier, 34295 Montpellier Cedex 5
| | - B Gay
- Laboratoire de virologie, pôle d'infectiologie, hôpital Saint-Éloi, centre hospitalier universitaire de Montpellier, 34295 Montpellier Cedex 5
| | - M Segondy
- Laboratoire de virologie, pôle d'infectiologie, hôpital Saint-Éloi, centre hospitalier universitaire de Montpellier, 34295 Montpellier Cedex 5
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