Evidence map›Paper›PMID 30662795›Full record

ArticleJournal of pathology informatics2018

Comprehensive Study of Telecytology Using Robotic Digital Microscope and Single Z-Stack Digital Scan for Fine-Needle Aspiration-Rapid On-Site Evaluation.

Keluo Yao, Rulong Shen, Anil Parwani, Zaibo Li

Abstract read
In one paragraph

Article in Journal of pathology informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Keluo YaoDepartment of Pathology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Rulong ShenDepartment of Pathology, The Ohio State University, Columbus, Ohio, USA.
Anil ParwaniDepartment of Pathology, The Ohio State University, Columbus, Ohio, USA.
Zaibo LiDepartment of Pathology, The Ohio State University, Columbus, Ohio, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe current technology for remote assessment of fine-needle aspiration-rapid on-site evaluation (FNA-ROSE) is limited. Recent advances may provide solutions. This study compared the performance of VisionTek digital microscope (VDM) (Sakura, Japan) and Hamamatsu NanoZoomer C9600-12 single Z-stack digital scan (SZDS) to conventional light microscopy (CLM) for FNA-ROSE.

methodsWe assembled sixty FNA cases from the thyroid (

resultsFor AA, the Cohen's kappa statistics (CKS) scores of intermodality agreement (IMA) were 0.74-0.94 (CLM vs. VDM) and 0.86-1 (CLM vs. SZDS). The discordant rates of IMA were 3.3% (4/120) for VDM versus CLM, and 1.7% (2/120) for SZDS versus CLM. For PD, the CKS scores of IMA ranged 0.7-0.93. The overall discordant rates of IMA were 15% (18/120) for CLM versus VDM and 10.8% (13/120) for CLM versus SZDS. The discordant rates of IMA with 2 or higher degrees were 5.8% (7/120) for CLM versus VDM and 1.7% (2/120) for CLM versus SZDS. The average time spent per slide was 270 s for VDM, significantly longer than that for CLM (113 s) or for SZDS (122 s).

conclusionsOur data demonstrate that both VDM and SZDS are suitable to provide AA and reasonable PD evaluation. VDM, however, has a significantly longer turnaround time and worse diagnostic performance. The study demonstrates both the potentials and challenges of using VDM and SZDS for FNA-ROSE.

Indexed as

Adequacy assessmentCohen's kappa statisticsconventional light microscopyfine-needle aspiration-rapid on-site evaluationintermodality agreementNanoZoomerpreliminary diagnosissingle Z-stack digital scanTelecytologyVisionTek digital microscope

Identifiers

PMID30662795
PMCPMC6319035

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Registered trials

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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.