Evidence map›Paper›PMID 38229839›Full record

ReviewGland surgery2023

Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer.

Pierpaolo Palumbo, Andrea Martinese, Maria Rosaria Antenucci, Vincenza Granata, Roberta Fusco, Federica De Muzio, Maria Chiara Brunese, Eleonora Bicci, Alessandra Bruno, Federico Bruno and 5 more

Open access · diamondAbstract readReview
In one paragraph

Review in Gland surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
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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

15 authors at 7 institutions in 1 country.

Pierpaolo PalumboDepartment of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, L'Aquila, Italy.
Andrea Martinese *Department of Applied Clinical Sciences and Biotechnology, University of L'Aquila, L'Aquila, Italy.
Maria Rosaria Antenucci *Department of Applied Clinical Sciences and Biotechnology, University of L'Aquila, L'Aquila, Italy.
Vincenza GranataDivision of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli", Naples, Italy.
Roberta FuscoMedical Oncology Division, Igea SpA, Napoli, Italy.
Federica De MuzioDiagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, Campobasso, Italy.
Maria Chiara BruneseDiagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, Campobasso, Italy.
Eleonora BicciDepartment of Emergency Radiology, University Hospital Careggi, Florence, Italy.
Alessandra BrunoDepartment of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Ancona, Italy.
Federico BrunoDepartment of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, L'Aquila, Italy.
Andrea GiovagnoniDepartment of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Ancona, Italy.
Nicoletta GandolfoDiagnostic Imaging Department, Villa Scassi Hospital-ASL 3, Genoa, Italy.
Vittorio MieleDepartment of Emergency Radiology, University Hospital Careggi, Florence, Italy.
Ernesto Di Cesare *Department of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Rosa Manetta *Radiology Unit, San Salvatore Hospital, Abruzzo Health Unit 1, L'Aquila, Italy.
University of L'Aquila · ITAzienda Ospedaliero-Universitaria Careggi · ITMarche Polytechnic University · ITUniversity of Molise · ITIGEA Clinical Biophysics (Italy) · ITIstituto Nazionale Tumori IRCCS "Fondazione G. Pascale" · ITSocietà Italiana di Reumatologia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI. Methods: This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed. Key Content and Findings: DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (D Conclusions: DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what K

Indexed as

Diffusion kurtosis imaging (DKI)diffusion-weighted imaging (DWI)prostate cancer (PCa)

Identifiers

PMID38229839
PMCPMC10788566
OpenAlexW4390245517

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.