Evidence map›Paper›PMID 36900085›Full record

ArticleDiagnostics (Basel, Switzerland)2023

Can Imaging Using Radiomics and Fat Fraction Analysis Detect Early Tissue Changes on Historical CT Scans in the Regions of the Pancreas Gland That Subsequently Develop Adenocarcinoma?

Ronald Lee Korn, Andre Burkett, Jeff Geschwind, Dominic Zygadlo, Taylor Brodie, Derek Cridebring, Daniel D Von Hoff, Michael J Demeure

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Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Ronald Lee KornImaging Endpoints Research Laboratory, 7150 E Camelback Road Suite 120, Scottsdale, AZ 85251, USA.
Andre BurkettImaging Endpoints Research Laboratory, 7150 E Camelback Road Suite 120, Scottsdale, AZ 85251, USA.
Jeff GeschwindImaging Endpoints Research Laboratory, 7150 E Camelback Road Suite 120, Scottsdale, AZ 85251, USA.
Dominic ZygadloImaging Endpoints Research Laboratory, 7150 E Camelback Road Suite 120, Scottsdale, AZ 85251, USA.
Taylor BrodieHoag Family Cancer Institute, 1 Hoag Drive, Newport Beach, CA 92663, USA.
Derek CridebringTranslational Genomics Research Institute, 445 N. Fifth Street, Phoenix, AZ 85004, USA.ORCID 0000-0001-5630-0350
Daniel D Von HoffTranslational Genomics Research Institute, 445 N. Fifth Street, Phoenix, AZ 85004, USA.ORCID 0000-0003-4723-7681
Michael J DemeureHoag Family Cancer Institute, 1 Hoag Drive, Newport Beach, CA 92663, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite a growing number of effective therapeutic options for patients with pancreatic adenocarcinoma, the prognosis remains dismal mostly due to the late-stage presentation and spread of the cancer to other organs. Because a genomic analysis of pancreas tissue revealed that it may take years, if not decades, for pancreatic cancer to develop, we performed radiomics and fat fraction analysis on contrast-enhanced CT (CECT) scans of patients with historical scans showing no evidence of cancer but who subsequently went on to develop pancreas cancer years later, in an attempt to identify specific imaging features of the normal pancreas that may portend the subsequent development of the cancer. In this IRB-exempt, retrospective, single institution study, CECT chest, abdomen, and pelvis (CAP) scans of 22 patients who had evaluable historical imaging data were analyzed. The images from the "healthy" pancreas were obtained between 3.8 and 13.9 years before the diagnosis of pancreas cancer was established. Afterwards, the images were used to divide and draw seven regions of interest (ROIs) around the pancreas (uncinate, head, neck-genu, body (proximal, middle, and distal) and tail). Radiomic analysis on these pancreatic ROIs consisted of first order quantitative texture analysis features such as kurtosis, skewness, and fat quantification. Of all the variables tested, fat fraction in the pancreas tail (

Indexed as

pancreas cancerradiomicsscreening

Identifiers

PMID36900085
PMCPMC10001321

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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.