Evidence map›Paper›PMID 30383459›Full record

ArticleThe British journal of radiology2019

Quantitative assessment of dynamic

Noam Tau, Alejandro Berlin, Ivan Yeung, Jaydeep Halankar, Grainne Murphy, Kartik S Jhaveri, Sangeet Ghai, Ur Metser

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 82% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 4 institutions in 1 country.

Noam Tau1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada.
Alejandro Berlin2 Department of Radiation Oncology, University of Toronto and Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network , Toronto, ON , Canada.
Ivan Yeung2 Department of Radiation Oncology, University of Toronto and Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network , Toronto, ON , Canada.
Jaydeep Halankar1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada.
Grainne Murphy1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada.
Kartik S Jhaveri1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada.
Sangeet Ghai1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada.
Ur Metser1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada.
Princess Margaret Cancer Centre · CAUniversity of Toronto · CAUniversity Health Network · CAWomen's College Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objective: To describe dynamic

methods: 41 consenting patients who underwent prostate DCE MR and dPET were included in this institutionally approved study. Intraprostatic lesions on MR were assigned a PI-RADS v2 score, and focal lesions on PET were documented. All lesions were correlated with pathology. Quantitative and semi-quantitative DCE MR and two-tissue compartmental model dPET parameters were determined and tumor-to-normal gland ratios (T/N) for these parameters were calculated. Finally, dPET and DCE MR correlation was estimated using Spearman correlation coefficients.

results: There were 46 malignant lesions per standard of reference. On dPET, peripheral zone (PZ) tumors had higher K1 (p < 0.001), and a T/N ratio ≥2 was significant (p < 0.001). On DCE MR, the parameters in, kep, Ktrans and quantitative iAUC were higher for PZ and non-PZ tumors than corresponding normal tissue (p < 0.001); for PZ tumors, a T/N ratio ≥ 1.5 for Ktrans and pei was significant (p = 0.0019 and 0.0026, respectively). Moderate Spearman correlation (0.40 < ρ < 0.59) was found between dPET K1 and DCE MR Ktrans and pei.

conclusion: In patients with high-risk PCa, quantitative dPET and DCE-MR parameters in primary tumors differ from normal tissue. Only moderate correlation exists between K1 (dPET) and Ktrans and pei (DCE MR). The incremental value of any of these parameters to PI-RADS v2 warrants further investigation. ADVANCES IN KNOWLEDGE:: Unique quantitative and semi-quantitative FCH PET/MR parameters in PCa differ from normal gland, and should be further investigated to determine their potential contribution to PI-RADS v2 in the detection of clinically significant PCa.

Indexed as

Magnetic Resonance ImagingPositron-Emission TomographyRadiopharmaceuticalsAgedAged, 80 and overContrast MediaFluorine RadioisotopesHumansImage Processing, Computer-AssistedMaleMiddle AgedProstateProstatic NeoplasmsRisk FactorsContrast MediaFluorine-18Fluorine RadioisotopesRadiopharmaceuticals

Identifiers

PMID30383459
PMCPMC6404848
OpenAlexW2898743105

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.