Evidence map›Paper›PMID 36717575›Full record

ArticleScientific reports2023

Characterization of spatially mapped volumetric molecular ultrasound signals for predicting response to anti-vascular therapy.

Cody A Keller, Shaya Zarkesh, Jianhua Zhou, Amelie M Lutz, Dimitre Hristov, Aya Kamaya, Ahmed El Kaffas

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 55% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Cody A KellerDepartment of Radiology, School of Medicine, Stanford University, Stanford, CA, USA.
Shaya ZarkeshDepartment of Radiology, School of Medicine, Stanford University, Stanford, CA, USA.
Jianhua ZhouDepartment of Radiology, School of Medicine, Stanford University, Stanford, CA, USA.
Amelie M LutzDepartment of Radiology, School of Medicine, Stanford University, Stanford, CA, USA.
Dimitre HristovDepartment of Radiation Oncology, Stanford University, Stanford, CA, USA.
Aya KamayaDepartment of Radiology, School of Medicine, Stanford University, Stanford, CA, USA.
Ahmed El KaffasDepartment of Radiology, School of Medicine, Stanford University, Stanford, CA, USA. elkaffas@stanford.edu.
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative three-dimensional molecular ultrasound is a promising technology for longitudinal imaging applications such as therapy monitoring; the risk profile is favorable compared to positron emission tomography and computed tomography. However, clinical translation of quantitative methods for this technology are limited in that they assume that tumor tissues are homogeneous, and often depend on contrast-destruction events that can produce unintended bioeffects. Here, we develop quantitative features (henceforth image features) that capture tumor spatial information, and that are extracted without contrast destruction. We compare these techniques with the contrast-destruction derived differential targeted enhancement parameter (dTE) in predicting response to therapy. We found thirty-three reproducible image features that predict response to antiangiogenic therapy, without the need for a contrast agent disruption pulse. Multiparametric analysis shows that several of these image features can differentiate treated versus control animals with comparable performance to post-destruction measurements, suggesting that these can potentially replace parameters such as the dTE. The highest performing pre-destruction image features showed strong linear correlations with conventional dTE parameters with less overall variance. Thus, our study suggests that image features obtained during the wash in of the molecular agent, pre-destruction, may replace conventional post-destruction image features or the dTE parameter.

Indexed as

Contrast MediaNeoplasmsAnimalsPositron-Emission TomographyTomography, X-Ray ComputedUltrasonographyContrast Media

Identifiers

PMID36717575
PMCPMC9886917
OpenAlexW4318482079

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.