Evidence map›Paper›PMID 35150315›Full record

ReviewAbdominal radiology (New York)2022

Contrast-enhanced ultrasound of the kidneys: principles and potential applications.

Ankita Aggarwal, Sneha Goswami, Chandan J Das

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Imaging in Renal Cell Carcinoma Detection.Diagnostics (Basel, Switzerland) · 2024
    Review
  4. Review
  5. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Ankita AggarwalDepartment of Radiology, VMMC & Safdarjung Hospital, New Delhi, India.
Sneha GoswamiDepartment of Radiodiagnosis and Interventional Radiology, AIIMS, New Delhi, India.
Chandan J DasDepartment of Radiodiagnosis and Interventional Radiology, AIIMS, New Delhi, India. dascj@yahoo.com.
All India Institute of Medical Sciences · INAll India Institute of Medical Sciences Raipur · INSafdarjang Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contrast-enhanced ultrasound (CEUS) is an extension and an enhanced form of ultrasound that allows real-time evaluation of the various structures in different vascular phases. The last decade has witnessed a widespread expansion of CEUS applications beyond the liver. It has shown fair potential in kidneys and its diagnostic efficacy is comparable to CT and MRI. Ultrasound is the well-accepted screening modality for renal pathologies, however, it underperforms in the characterization of the renal masses. CEUS can be beneficial in such cases as it can help in the characterization of such incidental masses in the same sitting. It has an excellent safety profile with no risk of radiation or contract-related nephropathy. It can aid in the correct categorization of renal cysts into one of the Bosniak classes and has proven its worth especially in complex cysts or indeterminate renal masses (especially Bosniak Category IIF and III). Few studies also describe its potential role in solid masses and in differentiating benign from malignant masses. Other areas of interest include infections, infarctions, trauma, follow-up of local ablative procedures, and VUR. Through this review, the readers shall get an insight into the various applications of CEUS in kidneys, with imaging examples.

Indexed as

Contrast MediaKidney NeoplasmsHumansKidneyTomography, X-Ray ComputedUltrasonographyContrast MediaBosniak categoryCEUSContrast-enhanced ultrasoundRenal

Identifiers

PMID35150315
OpenAlexW4211167476

What OpenQuestion holds

Textmetadata
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.