Evidence map›Paper›PMID 36650440›Full record

ArticleBMC cancer2023

Detection of pancreatic cancer with two- and three-dimensional radiomic analysis in a nationwide population-based real-world dataset.

Dawei Chang, Po-Ting Chen, Pochuan Wang, Tinghui Wu, Andre Yanchen Yeh, Po-Chang Lee, Yi-Hui Sung, Kao-Lang Liu, Ming-Shiang Wu, Dong Yang and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 8% of its field
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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. 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

13 authors at 5 institutions in 2 countries.

Dawei ChangData Science Degree Program, National Taiwan University and Academia Sinica, Taipei, Taiwan.
Po-Ting ChenDepartment of Medical Imaging, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan.
Pochuan WangDepartment of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Tinghui WuInstitute of Applied Mathematical Sciences, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei, 10617, Taiwan.
Andre Yanchen YehSchool of Medicine, National Taiwan University, Taipei, Taiwan.
Po-Chang LeeNational Health Insurance Administration, Ministry of Health and Welfare, Taipei, Taiwan.
Yi-Hui SungNational Health Insurance Administration, Ministry of Health and Welfare, Taipei, Taiwan.
Kao-Lang LiuDepartment of Medical Imaging, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan.
Ming-Shiang WuDepartment of Internal Medicine, Division of Gastroenterology and Hepatology, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan.
Dong YangNVIDIA, Bethesda, MD, 20814, USA.
Holger RothNVIDIA, Bethesda, MD, 20814, USA.
Wei-Chih Liao *Department of Internal Medicine, Division of Gastroenterology and Hepatology, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan. david.ntuh@gmail.com.
Weichung Wang *Institute of Applied Mathematical Sciences, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei, 10617, Taiwan. wwang@ntu.edu.tw.
National Taiwan University · TWNational Taiwan University Hospital · TWMinistry of Health and Welfare · TWNvidia (United States) · USAcademia Sinica · TW

Funding

Ministry of Science and Technology, Taiwan MOST 107-2634-F-002-014-, MOST 107-2634-F-002-016-, MOST 108-2634-F-002-011-, MOST 108-2634-F-002-013-, MOST 109-2634-F-002-028-, and MOST 110-2634-F-002-030
6 · The paper itself

Abstract

backgroundCT is the major detection tool for pancreatic cancer (PC). However, approximately 40% of PCs < 2 cm are missed on CT, underscoring a pressing need for tools to supplement radiologist interpretation.

methodsContrast-enhanced CT studies of 546 patients with pancreatic adenocarcinoma diagnosed by histology/cytology between January 2005 and December 2019 and 733 CT studies of controls with normal pancreas obtained between the same period in a tertiary referral center were retrospectively collected for developing an automatic end-to-end computer-aided detection (CAD) tool for PC using two-dimensional (2D) and three-dimensional (3D) radiomic analysis with machine learning. The CAD tool was tested in a nationwide dataset comprising 1,477 CT studies (671 PCs, 806 controls) obtained from institutions throughout Taiwan.

resultsThe CAD tool achieved 0.918 (95% CI, 0.895-0.938) sensitivity and 0.822 (95% CI, 0.794-0.848) specificity in differentiating between studies with and without PC (area under curve 0.947, 95% CI, 0.936-0.958), with 0.707 (95% CI, 0.602-0.797) sensitivity for tumors < 2 cm. The positive and negative likelihood ratios of PC were 5.17 (95% CI, 4.45-6.01) and 0.10 (95% CI, 0.08-0.13), respectively. Where high specificity is needed, using 2D and 3D analyses in series yielded 0.952 (95% CI, 0.934-0.965) specificity with a sensitivity of 0.742 (95% CI, 0.707-0.775), whereas using 2D and 3D analyses in parallel to maximize sensitivity yielded 0.915 (95% CI, 0.891-0.935) sensitivity at a specificity of 0.791 (95% CI, 0.762-0.819).

conclusionsThe high accuracy and robustness of the CAD tool supported its potential for enhancing the detection of PC.

Indexed as

AdenocarcinomaPancreatic NeoplasmsHumansRetrospective StudiesSensitivity and SpecificityTaiwanComputer-aided detectionMachine learningPancreatic cancerPancreatic ductal adenocarcinomaRadiomics

Identifiers

PMID36650440
PMCPMC9843893
OpenAlexW4317103315

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.