Evidence map›Paper›PMID 35407528›Full record

ReviewJournal of clinical medicine2022

Diffusion-Weighted MRI in the Genitourinary System.

Thomas De Perrot, Christine Sadjo Zoua, Carl G Glessgen, Diomidis Botsikas, Lena Berchtold, Rares Salomir, Sophie De Seigneux, Harriet C Thoeny, Jean-Paul Vallée

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 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

9 authors at 3 institutions in 1 country.

Thomas De PerrotDivision of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland.
Christine Sadjo ZouaDivision of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland.
Carl G GlessgenDivision of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland.ORCID 0000-0002-9836-7139
Diomidis BotsikasDivision of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland.ORCID 0000-0002-0543-0742
Lena BerchtoldDivision of Nephrology, Geneva University Hospitals, 1205 Geneva, Switzerland.ORCID 0000-0001-8815-4263
Rares SalomirDivision of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland.
Sophie De SeigneuxDivision of Nephrology, Geneva University Hospitals, 1205 Geneva, Switzerland.
Harriet C ThoenyDivision of Radiology, Hôpital Cantonal Fribourgois, 1752 Villars-sur-Glâne, Switzerland.
Jean-Paul ValléeDivision of Radiology, Geneva University Hospitals and University of Geneva, 1205 Geneva, Switzerland.
University of Geneva · CHUniversity Hospital of Geneva · CHFribourg Development Agency · CH

Funding

Swiss National Science Foundation IZCOZ0_177140/1 (JPV, HCT), 320038_159714 (JPV) and PP00P3_127454 (SDS)
6 · The paper itself

Abstract

Diffusion weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence's usage in female pelvis, prostate, bladder, penis, testis and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging-Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors has significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or in the bladder and testicular mpMRI.

Indexed as

cancerdiffusionfemale pelvisgenitourinary MRIkidneyprostate

Identifiers

PMID35407528
PMCPMC9000195
OpenAlexW4220966714

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.