Evidence map›Paper›PMID 32113936›Full record

ArticlePancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]2020

Comparison of imaging modalities for measuring the diameter of intraductal papillary mucinous neoplasms of the pancreas.

Tri Huynh, Karla Ali, Shraddha Vyas, Kaleena Dezsi, Destiny Strickland, Toni Basinski, Dung-Tsa Chen, Kun Jiang, Barbara Centeno, Mokenge Malafa and 4 more

Abstract readComparative Study
In one paragraph

Article in Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.], 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

14 authors.

Tri HuynhCollege of Medicine, University of Florida, Gainesville, FL, USA.
Karla AliDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
Shraddha VyasDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
Kaleena DezsiDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
Destiny StricklandDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
Toni BasinskiDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
Dung-Tsa ChenDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA.
Kun JiangDepartment of Pathology, Moffitt Cancer Center, Tampa, FL, USA.
Barbara CentenoDepartment of Pathology, Moffitt Cancer Center, Tampa, FL, USA.
Mokenge MalafaDepartment of Gastrointestinal Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Jason B KlapmanDepartment of Gastrointestinal Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Pamela J HodulDepartment of Gastrointestinal Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Daniel JeongDepartment of Diagnostic Radiology, Moffitt Cancer Center, Tampa, FL, USA.
Jennifer B PermuthDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA; Department of Gastrointestinal Oncology, Moffitt Cancer Center, Tampa, FL, USA. Electronic address: jenny.permuth@moffitt.org.

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI KENNETH Lynn WRIGHT · 1998 to 2026
$93.5M
Using Radiogenomics to Noninvasively Predict the Malignant Potential of Intraductal Papillary Mucinous Neoplasms of the Pancreas and Uncover Hidden BiologyR37CA229810 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI JEONG, DANIEL, PERMUTH, JENNIFER B · 2019 to 2025
$5.0M
NCI NIH HHS P30 CA076292NCI NIH HHS R37 CA229810
6 · The paper itself

Abstract

backgroundIntraductal papillary mucinous neoplasms (IPMNs) are pre-malignant pancreatic cysts detected by imaging. Cyst size is one of many features evaluated on computed tomography (CT), magnetic resonance imaging (MRI), or endoscopic ultrasonography (EUS) to help guide IPMN management. Our objective was to determine which imaging modality best predicts pathological cyst size.

methodsWe analyzed records for 57 IPMN cases surgically treated at Moffitt Cancer Center from 2008 to 2016 for whom pre-operative CT, MRI, and EUS IPMN cyst size and post-operative pathological cyst size values were available. Long axis cyst diameter measurements were compared to each other and corresponding pathological cyst measurements using within-subjects ANOVA, Bland-Altman analysis, and linear regression. Consensus measurements were also performed on CT and MRI images.

resultsCyst size measured via CT and MRI overestimated pathological size by 0.33 cm and 0.27 cm, respectively, whereas EUS underestimated pathological size by 0.05 cm and had the narrowest 95% limit of agreement (LOA). Among pathologically-confirmed cysts <3 cm, MRI overestimated pathological size by 0.30 cm (P = 0.049) and had the widest LOA, followed by EUS and CT. Among cysts ≥3 cm, EUS underestimated pathological size by 0.35 cm (P = 0.059) and MRI and CT overestimated pathological size by 0.23 cm and 0.51 cm, respectively.

conclusionsIn this small retrospective study, EUS cyst size measurements correlated best with pathologic specimens compared to CT and MRI, especially for cysts < 3 cm. Larger prospective studies are needed to determine which imaging modalities are best to risk-stratify IPMNs and guide surgical versus. Non-surgical management.

Indexed as

AgedAged, 80 and overEndoscopic Ultrasound-Guided Fine Needle AspirationEndosonographyFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPancreatic CystPancreatic DuctsPancreatic Intraductal NeoplasmsPancreatic NeoplasmsReproducibility of ResultsTomography, X-Ray ComputedImagingIPMNMeasurementPancreatic cyst

Identifiers

PMID32113936
PMCPMC7346718

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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.