Evidence map›Paper›PMID 30003330›Full record

ArticlePediatric surgery international2018

Reliability of sonoelastography in predicting pediatric cervical lymph node malignancy.

Ossama M Zakaria, Ahmed Mousa, Reema AlSadhan, Tamer A Sultan, Ahmed F Eid, Mohamed Y Daoud, Asmaa Al-Taher, Hazem M Zakaria, Krishna Swaroop, Amr M El-Gibaly and 2 more

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Article in Pediatric surgery international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
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  3. Review
  4. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Ossama M ZakariaDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia. ossamaz2004@gmail.com.
Ahmed MousaDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Reema AlSadhanDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Tamer A SultanDivision of Pediatric Surgery, Faculty of Medicine, Menoufia University, Menoufia, Egypt.
Ahmed F EidMedical Imaging Department, King Abdul-Aziz Hospital, Health Affairs of the Ministry of National Guard, Al-Ahsa, Saudi Arabia.
Mohamed Y DaoudDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Asmaa Al-TaherDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Hazem M ZakariaDepartment of Surgery, Imam Abdulrahman Bin Faisal University, College of Medicine, Dammam, Saudi Arabia.
Krishna SwaroopDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Amr M El-GibalyDepartment of General, Visceral, Thoracic and Vascular Surgery, Hanse Klinikum Stralsund, University Medicine of Greifswald, Greifswald, Germany.
Haytham Al-ArfajDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Essam M AbdelbaryDepartments of Pediatric Surgery, Surgery, Radiology, Pathology, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeControversy exists as regards the best non-invasive diagnostic tool for pediatric cervical lymphadenopathy. The current work aimed to evaluate the reliability, sensitivity, specificity, and accuracy of sonoelastography in diagnosing benign and/or malignant pediatric cervical lymphadenopathy.

methodsProspective study took place over a period of 4 years from January 2013 to December 2016. A total of 177 lymph nodes (LNs) in 128 children with an age ranging from 11 months to 12 years were recruited in this study. Patients were 77 males and 51 females with a ratio of 3:2. All patients underwent a thorough history taking and clinical examination of the neck focusing on the cervical lymph nodes. After that, a B-mode sonography, Color Doppler ultrasound, and Sonoelastography were performed. Elastographic patterns of 1-5 were evaluated, whereas patterns of 3-5 (firm to hard) were suspected to have a malignant nature. Sonographic-guided aspiration cytology took place in 107 lymph nodes and excisional biopsy in 102 lymph nodes, whereas 13 lymph nodes responded adequately to conservative treatment. They proved to be benign reactive hyperplasia.

resultsThe majority of LNs (87%) were of the malignant type that showed an elastographic pattern of 3-5. The same patterns were observed in only 6 (3.4%) of the benign LNs. Sonoelastography showed a sensitivity of 85.9%, specificity of 100%, PPV of 100%, NPV of 75.96%, and overall accuracy of 90.23% in distinguishing benign from malignant lymph nodes. Using the B-Mode ultrasound, an abnormal hilum was seen in 75%. The accuracy of color Doppler US reached 82.7%.

conclusionsSonoelastography may be superior to other US modalities in elucidating different cervical lymph node biopsy helping to distinguish benign from malignant lesions. This may replace the lymph node biopsies in the future. Moreover, its use in the follow-up of patients with cervical malignancies may reduce the number of future biopsies. Further studies with more patients may be needed for a better assessment of results.

Indexed as

Elasticity Imaging TechniquesBiopsy, Fine-NeedleChildChild, PreschoolFemaleHumansInfantLymphadenopathyLymph NodesMaleProspective StudiesReproducibility of ResultsSensitivity and SpecificityUltrasonography, InterventionalFNACLymph nodeLymphomaMalignancySonoelastography

Identifiers

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.