Evidence map›Paper›PMID 36894753›Full record

ArticleEuropean radiology2023

Exploratory analysis of mesenteric-portal axis CT radiomic features for survival prediction of patients with pancreatic ductal adenocarcinoma.

Francesca Rigiroli, Jocelyn Hoye, Reginald Lerebours, Peijie Lyu, Kyle J Lafata, Anru R Zhang, Alaattin Erkanli, Niharika B Mettu, Desiree E Morgan, Ehsan Samei and 1 more

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Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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

11 authors at 6 institutions in 2 countries.

Francesca RigiroliDepartment of Radiology, Duke University Health System, 2301 Erwin Road, Box 3808, Durham, NC, 27710, USA. f.rigiroli@gmail.com.ORCID http://orcid.org/0000-0002-5262-5585
Jocelyn HoyeCarl E. Ravin Advanced Imaging Laboratories, Durham, NC, USA.
Reginald LereboursDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Peijie LyuDepartment of Radiology, Duke University Health System, 2301 Erwin Road, Box 3808, Durham, NC, 27710, USA.
Kyle J LafataCarl E. Ravin Advanced Imaging Laboratories, Durham, NC, USA.
Anru R ZhangDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Alaattin ErkanliDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Niharika B MettuDuke University Health System, Durham, NC, USA.
Desiree E MorganDepartment of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Ehsan SameiCarl E. Ravin Advanced Imaging Laboratories, Durham, NC, USA.
Daniele MarinDepartment of Radiology, Duke University Health System, 2301 Erwin Road, Box 3808, Durham, NC, 27710, USA.
Duke University · USDuke University Health System · USAdvanced Imaging Research (United States) · USBeth Israel Deaconess Medical Center · USDuke Medical Center · USUniversity of Alabama at Birmingham · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and evaluate task-based radiomic features extracted from the mesenteric-portal axis for prediction of survival and response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC).

methodsConsecutive patients with PDAC who underwent surgery after neoadjuvant therapy from two academic hospitals between December 2012 and June 2018 were retrospectively included. Two radiologists performed a volumetric segmentation of PDAC and mesenteric-portal axis (MPA) using a segmentation software on CT scans before (CTtp0) and after (CTtp1) neoadjuvant therapy. Segmentation masks were resampled into uniform 0.625-mm voxels to develop task-based morphologic features (n = 57). These features aimed to assess MPA shape, MPA narrowing, changes in shape and diameter between CTtp0 and CTtp1, and length of MPA segment affected by the tumor. A Kaplan-Meier curve was generated to estimate the survival function. To identify reliable radiomic features associated with survival, a Cox proportional hazards model was used. Features with an ICC  ≥ 0.80 were used as candidate variables, with clinical features included a priori.

resultsIn total, 107 patients (60 men) were included. The median survival time was 895 days (95% CI: 717, 1061). Three task-based shape radiomic features (Eccentricity mean tp0, Area minimum value tp1, and Ratio 2 minor tp1) were selected. The model showed an integrated AUC of 0.72 for prediction of survival. The hazard ratio for the Area minimum value tp1 feature was 1.78 (p = 0.02) and 0.48 for the Ratio 2 minor tp1 feature (p = 0.002).

conclusionPreliminary results suggest that task-based shape radiomic features can predict survival in PDAC patients. KEY POINTS: • In a retrospective study of 107 patients who underwent neoadjuvant therapy followed by surgery for PDAC, task-based shape radiomic features were extracted and analyzed from the mesenteric-portal axis. • A Cox proportional hazards model that included three selected radiomic features plus clinical information showed an integrated AUC of 0.72 for prediction of survival, and a better fit compared to the model with only clinical information.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsHumansMaleRetrospective StudiesTomography, X-Ray ComputedAdenocarcinomaMesenteric veinsPancreasPancreatic neoplasmsPortal vein

Identifiers

PMID36894753
OpenAlexW4323812767

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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.