Evidence map›Paper›PMID 35626304›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Development of "Mathematical Technology for Cytopathology," an Image Analysis Algorithm for Pancreatic Cancer.

Reiko Yamada, Kazuaki Nakane, Noriyuki Kadoya, Chise Matsuda, Hiroshi Imai, Junya Tsuboi, Yasuhiko Hamada, Kyosuke Tanaka, Isao Tawara, Hayato Nakagawa

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Review
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

10 authors.

Reiko YamadaDepartment of Gastroenterology and Hepatology, School of Medicine, Mie University, Tsu 514-8507, Japan.ORCID 0000-0003-2318-073X
Kazuaki NakaneDepartment of Molecular Pathology, Osaka University, Osaka 565-0871, Japan.
Noriyuki KadoyaDepartment of Radiation Oncology, School of Medicine, Tohoku University, Sendai 980-8577, Japan.
Chise MatsudaDepartment of Pathology, Mie University Hospital, Tsu 514-8507, Japan.
Hiroshi ImaiDepartment of Pathology, Mie University Hospital, Tsu 514-8507, Japan.
Junya TsuboiDepartment of Endoscopic Medicine, Mie University Hospital, Tsu 514-8507, Japan.
Yasuhiko HamadaDepartment of Gastroenterology and Hepatology, School of Medicine, Mie University, Tsu 514-8507, Japan.ORCID 0000-0001-5564-184X
Kyosuke TanakaDepartment of Endoscopic Medicine, Mie University Hospital, Tsu 514-8507, Japan.ORCID 0000-0002-1402-7832
Isao TawaraDepartment of Hematology and Oncology, School of Medicine, Mie University, Tsu 514-8507, Japan.ORCID 0000-0002-5426-9422
Hayato NakagawaDepartment of Gastroenterology and Hepatology, School of Medicine, Mie University, Tsu 514-8507, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related death worldwide. The accuracy of a PDAC diagnosis based on endoscopic ultrasonography-guided fine-needle aspiration cytology can be strengthened by performing a rapid on-site evaluation (ROSE). However, ROSE can only be performed in a limited number of facilities, due to a relative lack of available resources or cytologists with sufficient training. Therefore, we developed the Mathematical Technology for Cytopathology (MTC) algorithm, which does not require teaching data or large-scale computing. We applied the MTC algorithm to support the cytological diagnosis of pancreatic cancer tissues, by converting medical images into structured data, which rendered them suitable for artificial intelligence (AI) analysis. Using this approach, we successfully clarified ambiguous cell boundaries by solving a reaction-diffusion system and quantitating the cell nucleus status. A diffusion coefficient (

Indexed as

artificial intelligencebenign tissuediffusion coefficientMathematical Technology for Cytopathologymedical imagemultivariate analysisnuclear boundarypancreatic ductal adenocarcinomarapid on-site evaluationreaction–diffusion system

Identifiers

PMID35626304
PMCPMC9139930

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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.