Evidence map›Paper›PMID 36151126›Full record

ArticleScientific reports2022

Quantification of ovarian lesion and fallopian tube vasculature using optical-resolution photoacoustic microscopy.

Xiandong Leng, Sitai Kou, Yixiao Lin, Andrea R Hagemann, Ian S Hagemann, Premal H Thaker, Lindsay M Kuroki, Carolyn K McCourt, David G Mutch, Cary Siegel and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

8 citing papers in PubMed, 6 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

12 authors at 1 institution in 1 country.

Xiandong Leng *Biomedical Engineering, Washington University, St. Louis, MO, 63130, USA.
Sitai Kou *Biomedical Engineering, Washington University, St. Louis, MO, 63130, USA.
Yixiao Lin *Biomedical Engineering, Washington University, St. Louis, MO, 63130, USA.
Andrea R HagemannDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Ian S HagemannDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Premal H ThakerDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Lindsay M KurokiDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Carolyn K McCourtDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
David G MutchDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Cary SiegelDepartment of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Matthew A PowellDepartment of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
Quing ZhuBiomedical Engineering, Washington University, St. Louis, MO, 63130, USA. zhu.q@wustl.edu.
Washington University in St. Louis · US

Funding

Coregistered Photoacoustic and Ultrasound Imaging for Ovarian Cancer Diagnosis and Risk ManagementR01CA237664 · NCI · WASHINGTON UNIVERSITY · PI POWELL, MATTHEW A, SIEGEL, CARY L · 2020 to 2024
$2.6M
NCI NIH HHS R01 CA237664NCI NIH HHS R01CA237664
6 · The paper itself

Abstract

The heterogeneity in the pathological and clinical manifestations of ovarian cancer is a major hurdle impeding early and accurate diagnosis. A host of imaging modalities, including Doppler ultrasound, MRI, and CT, have been investigated to improve the assessment of ovarian lesions. We hypothesized that pathologic conditions might affect the ovarian vasculature and that these changes might be detectable by optical-resolution photoacoustic microscopy (OR-PAM). In our previous work, we developed a benchtop OR-PAM and demonstrated it on a limited set of ovarian and fallopian tube specimens. In this study, we collected data from over 50 patients, supporting a more robust statistical analysis. We then developed an efficient custom analysis pipeline for characterizing the vascular features of the samples, including the mean vessel diameter, vascular density, global vascular directionality, local vascular definition, and local vascular tortuosity/branchedness. Phantom studies using carbon fibers showed that our algorithm was accurate within an acceptable error range. Between normal ovaries and normal fallopian tubes, we observed significant differences in five of six extracted vascular features. Further, we showed that distinct subsets of vascular features could distinguish normal ovaries from cystic, fibrous, and malignant ovarian lesions. In addition, a statistically significant difference was found in the mean vascular tortuosity/branchedness values of normal and abnormal tubes. The findings support the proposition that OR-PAM can help distinguish the severity of tubal and ovarian pathologies.

Indexed as

Ovarian CystsOvarian NeoplasmsCarbon FiberFallopian TubesFemaleHumansMicroscopyCarbon Fiber

Identifiers

PMID36151126
PMCPMC9508221
OpenAlexW4297021432

What OpenQuestion holds

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LicenceCC BY
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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.