Evidence map›Paper›PMID 22081252›Full record

ReviewCurrent urology reports2012

Advanced renal mass imaging: diffusion and perfusion MRI.

Anthony G Gilet, Stella K Kang, Danny Kim, Hersh Chandarana

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current urology reports, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Trial
  2. Review
  3. Review
  4. Review
  5. Mono, bi- and tri-exponential diffusion MRI modelling for renal solid masses and comparison with histopathological findings.Cancer imaging : the official publication of the International Cancer Imaging Society · 2018
    Article
  6. World journal of radiology · 2018
    Article
  7. Article
  8. Review
  9. Article
  10. MRI phenotype in renal cancer: is it clinically relevant?Topics in magnetic resonance imaging : TMRI · 2014
    Review
  11. Article
  12. Article
  13. Diffusion-weighted magnetic resonance imaging in cystic renal masses.Canadian Urological Association journal = Journal de l'Association des urologues du Canada
    Article
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

4 authors.

Anthony G GiletDepartment of Radiology, NYU Langone Medical Center, New York, NY, USA.
Stella K Kang
Danny Kim
Hersh Chandarana

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computed tomography (CT) is considered the imaging modality of choice in evaluation of renal lesions. The advantages of magnetic resonance imaging (MRI) compared to CT include superior soft tissue contrast, avoidance of ionizing radiation and iodinated contrast media, and the possibility of performing functional and advanced imaging techniques such as diffusion-weighted (DWI) and perfusion-weighted imaging (PWI). Although the traditional role of MRI in the evaluation of renal mass is primarily that of a problem-solving tool, DWI and PWI are expanding the role of MRI in management of renal cell cancers. DWI and PWI have shown considerable promise not only in renal lesion detection and characterization as benign or malignant, but also in assessment of renal cell cancer subtype and nuclear grade. Furthermore, these techniques have the potential to assist with tailoring patient- and disease-specific management by providing surgical planning in patients with localized renal cell cancer and assessing treatment response in patients with advanced renal cell cancer undergoing targeted chemotherapy.

Indexed as

Diffusion Magnetic Resonance ImagingHumansKidney NeoplasmsMagnetic Resonance AngiographyNeoplasm GradingReproducibility of Results

Identifiers

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.