PMID- 30335753
OWN - NLM
STAT- MEDLINE
DCOM- 20190306
LR  - 20190306
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 13
IP  - 10
DP  - 2018
TI  - Visual assessment versus computer-assisted gray scale analysis in the ultrasound 
      evaluation of neonatal respiratory status.
PG  - e0202397
LID - 10.1371/journal.pone.0202397 [doi]
AB  - BACKGROUND AND AIM: Lung ultrasound has been used to describe common respiratory 
      diseases both by visual and computer-assisted gray scale analysis. In the present
      paper, we compare both methods in assessing neonatal respiratory status keeping
      two oxygenation indexes as standards. PATIENTS AND METHODS: Neonates admitted to 
      the NICU for respiratory distress were enrolled. Two neonatologists not attending
      the patients performed a lung scan, built a single frame database and rated the
      images with a standardized score. The same dataset was processed using the gray
      scale analysis implemented with textural features and machine learning analysis. 
      Both the oxygenation ratio (PaO2/FiO2) and the alveolar arterial oxygen gradient 
      (A-a) were kept as reference standards. RESULTS: Seventy-five neonates with
      different respiratory status were enrolled in the study and a dataset of 600
      ultrasound frames was built. Visual assessment of respiratory status correlated
      significantly with PaO2/FiO2 (r = -0.55; p<0.0001) and the A-a (r = 0.59;
      p<0.0001) with a strong interobserver agreement (K = 0.91). A significant
      correlation was also found between both oxygenation indexes and the gray scale
      analysis of lung ultrasound scans using regions of interest corresponding to 50K 
      (r = -0.42; p<0.002 for PaO2/FiO2; r = 0.46 p<0.001 for A-a) and 100K (r = -0.35 
      p<0.01 for PaO2/FiO2; r = 0.58 p<0.0001 for A-a) pixels regions of interest.
      CONCLUSIONS: A semi quantitative estimate of the degree of neonatal respiratory
      distress was demonstrated both by a validated scoring system and by computer
      assisted analysis of the ultrasound scan. This data may help to implement point
      of care ultrasound diagnostics in the NICU.
FAU - Raimondi, Francesco
AU  - Raimondi F
AUID- ORCID: 0000-0003-3250-1582
AD  - Division of Neonatology, Section of Pediatrics, Department of Translational
      Medical Sciences, Universita "Federico II", Naples, Italy.
FAU - Migliaro, Fiorella
AU  - Migliaro F
AD  - Division of Neonatology, Section of Pediatrics, Department of Translational
      Medical Sciences, Universita "Federico II", Naples, Italy.
FAU - Verdoliva, Luisa
AU  - Verdoliva L
AD  - Department of Electrical Engineering and Information Technology, Universita
      "Federico II", Naples, Italy.
FAU - Gragnaniello, Diego
AU  - Gragnaniello D
AD  - Department of Electrical Engineering and Information Technology, Universita
      "Federico II", Naples, Italy.
FAU - Poggi, Giovanni
AU  - Poggi G
AD  - Department of Electrical Engineering and Information Technology, Universita
      "Federico II", Naples, Italy.
FAU - Kosova, Roberta
AU  - Kosova R
AD  - Division of Neonatology, Section of Pediatrics, Department of Translational
      Medical Sciences, Universita "Federico II", Naples, Italy.
FAU - Sansone, Carlo
AU  - Sansone C
AD  - Department of Electrical Engineering and Information Technology, Universita
      "Federico II", Naples, Italy.
FAU - Vallone, Gianfranco
AU  - Vallone G
AD  - Department of Advanced Biomedical Sciences, Universita "Federico II", Naples,
      Italy.
FAU - Capasso, Letizia
AU  - Capasso L
AD  - Division of Neonatology, Section of Pediatrics, Department of Translational
      Medical Sciences, Universita "Federico II", Naples, Italy.
LA  - eng
PT  - Journal Article
DEP - 20181018
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
RN  - S88TT14065 (Oxygen)
SB  - IM
MH  - Blood Gas Analysis
MH  - Female
MH  - Humans
MH  - Infant, Newborn
MH  - Lung/*diagnostic imaging/physiopathology
MH  - Male
MH  - Oxygen/metabolism
MH  - Respiratory Distress Syndrome, Newborn/*diagnosis/diagnostic
      imaging/physiopathology
MH  - *Ultrasonography
PMC - PMC6193620
COIS- The authors declare that no competing interests exists.
EDAT- 2018/10/20 06:00
MHDA- 2019/03/07 06:00
CRDT- 2018/10/19 06:00
PHST- 2017/07/13 00:00 [received]
PHST- 2018/08/02 00:00 [accepted]
PHST- 2018/10/19 06:00 [entrez]
PHST- 2018/10/20 06:00 [pubmed]
PHST- 2019/03/07 06:00 [medline]
AID - 10.1371/journal.pone.0202397 [doi]
AID - PONE-D-17-26076 [pii]
PST - epublish
SO  - PLoS One. 2018 Oct 18;13(10):e0202397. doi: 10.1371/journal.pone.0202397.
      eCollection 2018.