Automatic microscopic detection of mycobacteria in sputum: a proof-of-concept

被引:0
|
作者
D. Zingue
P. Weber
F. Soltani
D. Raoult
M. Drancourt
机构
[1] MEPHI,
[2] Aix Marseille Université,undefined
[3] IRD,undefined
[4] IHU Méditerranée Infection,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
The laboratory diagnosis of lung mycobacterioses including tuberculosis comprises the microscopic examination of sputum smear after appropriate staining such as Ziehl-Neelsen staining to observe acid-fast bacilli. This standard procedure is operator-dependant and its sensitivity depends on the duration of observation. We developed and evaluated an operator-independent microscopic examination of sputum smears for the automated detection and enumeration of acid-fast bacilli using a ZEISS Axio Scan.Z1 microscope. The sensitivity, specificity, positive predictive value, negative predictive values and accuracy were calculated using standard formulations by comparison with standard microscopic examination. After in-house parameterization of the automatic microscope and counting software, the limit of detection evaluated by seeding negative sputa with Mycobacterium bovis BCG or Mycobacterium tuberculosis H37Rv (100–105 bacilli/mL) was of 102 bacilli/mL of sputum with a 100% positivity rate. Then, the evaluation of 93 sputum specimens including 34 smear-positive and 59 smear-negative specimens yielded a sensitivity of 97.06% [84.67–99.93%], a specificity of 86.44% [73.01–92.78%]. Up to 100 smear slides could be stocked for reading in the microscope magazine and results are exportable into the laboratory information system. Based on these preliminary results, we are implanting this automatic protocol in the routine workflow so that only smears detected positive by automatic microscopy are confirmed by standard microscopic examination.
引用
收藏
相关论文
共 50 条
  • [1] Automatic microscopic detection of mycobacteria in sputum: a proof-of-concept
    Zingue, D.
    Weber, P.
    Soltani, F.
    Raoult, D.
    Drancourt, M.
    SCIENTIFIC REPORTS, 2018, 8
  • [2] HYPERNETWORKS FOR SOUND EVENT DETECTION: A PROOF-OF-CONCEPT
    Singh, Shubhr
    Huy Phan
    Benetos, Emmanouil
    2022 30TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2022), 2022, : 429 - 433
  • [3] "Proof-Of-Concept" Evaluation of an Automated Sputum Smear Microscopy System for Tuberculosis Diagnosis
    Lewis, James J.
    Chihota, Violet N.
    van der Meulen, Minty
    Fourie, P. Bernard
    Fielding, Katherine L.
    Grant, Alison D.
    Dorman, Susan E.
    Churchyard, Gavin J.
    PLOS ONE, 2012, 7 (11):
  • [4] Secure Automatic Identification System (SecAIS): Proof-of-Concept Implementation
    Goudosis, Athanasios
    Katsikas, Sokratis
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2022, 10 (06)
  • [5] Blockgraph Proof-of-Concept
    Cordova, David A. M.
    Velloso, Pedro B.
    Guerre, Alexandre
    Nguyen, Thi-Mai-Trang
    Pujolle, Guy
    Alagha, Khaldoun
    Dua, Guillaume
    PROCEEDINGS OF THE 2021 SIGCOMM 2021 POSTER AND DEMO SESSIONS, SIGCOMM 2021 DEMOS AND POSTERS, 2024, : 82 - 84
  • [6] SemFuzz: Semantics-based Automatic Generation of Proof-of-Concept Exploits
    You, Wei
    Zong, Peiyuan
    Chen, Kai
    Wang, XiaoFeng
    Liao, Xiaojing
    Bian, Pan
    Liang, Bin
    CCS'17: PROCEEDINGS OF THE 2017 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, 2017, : 2139 - 2154
  • [7] The accuracy of an automatic free flap temperature monitor: a proof-of-concept study
    Marco Aurelio Rendón-Medina
    Marco Antonio Rendón-Pimentel
    Julio Palacios-Juárez
    European Journal of Plastic Surgery, 2020, 43 : 185 - 188
  • [8] The accuracy of an automatic free flap temperature monitor: a proof-of-concept study
    Aurelio Rendon-Medina, Marco
    Antonio Rendon-Pimentel, Marco
    Palacios-Juarez, Julio
    EUROPEAN JOURNAL OF PLASTIC SURGERY, 2020, 43 (02) : 185 - 188
  • [9] Anomalous state detection in radio access networks: A proof-of-concept
    Frey, Michael
    Evans, Thomas
    Folz, Angela
    Gregg, Mary
    Quimby, Jeanne
    Rezac, Jacob D.
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2024, 231
  • [10] Support vector machines for automated snoring detection: proof-of-concept
    Samuelsson, Laura B.
    Rangarajan, Anusha A.
    Shimada, Kenji
    Krafty, Robert T.
    Buysse, Daniel J.
    Strollo, Patrick J.
    Kravitz, Howard M.
    Zheng, Huiyong
    Hall, Martica H.
    SLEEP AND BREATHING, 2017, 21 (01) : 119 - 133