Evidence map›Paper›PMID 38733421›Full record

ReviewFamilial cancer2024

Screening for pancreatic cancer in high-risk individuals using MRI: optimization of scan techniques to detect small lesions.

Bas Boekestijn, Shirin Feshtali, Hans Vasen, Monique E van Leerdam, Bert A Bonsing, J Sven D Mieog, Martin N Wasser

Abstract readReview
In one paragraph

Review in Familial cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Artificial intelligence in pancreatic cancer: applications in early detection, tumor staging, and survival prediction-a comprehensive review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  2. Review
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  4. Article
  5. Catching pancreatic cancer early: Are we there yet?Journal of the National Cancer Center · 2026
    Review
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  7. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Bas BoekestijnDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands. b.boekestijn@lumc.nl.
Shirin FeshtaliDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Hans VasenDepartment of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands.
Monique E van LeerdamDepartment of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands.
Bert A BonsingDepartment of Surgery, Leiden University Medical Center, Leiden, The Netherlands.
J Sven D MieogDepartment of Surgery, Leiden University Medical Center, Leiden, The Netherlands.
Martin N WasserDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer has a dismal prognosis in the general population. However, early detection and treatment of disease in high-risk individuals can improve survival, as patients with localized disease and especially patients with lesions smaller than 10 mm show greatly improved 5-year survival rates. To achieve early detection through MRI surveillance programs, optimization of imaging is required. Advances in MRI technologies in both hardware and software over the years have enabled reliable detection of pancreatic cancer at a small size and early stage. Standardization of dedicated imaging protocols for the pancreas are still lacking. In this review we discuss state of the art scan techniques, sequences, reduction of artifacts and imaging strategies that enable early detection of lesions. Furthermore, we present the imaging features of small pancreatic cancers from a large cohort of high-risk individuals. Refinement of MRI techniques, increased scan quality and the use of artificial intelligence may further improve early detection and the prognosis of pancreatic cancer in a screening setting.

Indexed as

Early Detection of CancerMagnetic Resonance ImagingPancreatic NeoplasmsHumansEarly detectionHigh-risk individualsMRIPancreatic cancerScreening

Identifiers

PMID38733421
PMCPMC11254973

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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.