Evidence map›Paper›PMID 24967287›Full record

ArticleISRN radiology2013

Whole Body MRI at 3T with Quantitative Diffusion Weighted Imaging and Contrast-Enhanced Sequences for the Characterization of Peripheral Lesions in Patients with Neurofibromatosis Type 2 and Schwannomatosis.

Laura M Fayad, Jaishri Blakeley, Scott Plotkin, Brigitte Widemann, Michael A Jacobs

Open access · diamondAbstract read
In one paragraph

Article in ISRN radiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 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

5 authors at 4 institutions in 1 country.

Laura M FayadThe Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA ; Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA ; Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Jaishri BlakeleySidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA ; The Johns Hopkins Hospital Comprehensive Neurofibromatosis Center, Department of Neurology, The Johns Hopkins Hospital, CRB II, Suite 1M16, 1550 Orleans Street, Baltimore, MD 21231, USA.
Scott PlotkinDepartment of Neurology and Cancer Center, Massachusetts General Hospital, Boston, MA, USA ; Neurofibromatosis Clinic, Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, YAW 9, Boston, MA 02114, USA.
Brigitte WidemannCenter for Cancer Research, National Cancer Institute, Bethesda, MD, USA ; Pharmacology & Experimental Therapeutics Section, Pediatric Oncology Branch, NCI, CCR, Room 1-5750, 10 Center Drive, 10-CRC, MSC 1101, Bethesda, MD 20892, USA.
Michael A JacobsThe Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA ; Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Sidney Kimmel Comprehensive Cancer Center · USCenter for Neuro-Oncology · USJohns Hopkins Hospital · USNational Cancer Institute · US

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rosalie Wollett · 1985 to 2026
$208.6M
Theranostic Imaging of Metastatic Prostate CancerP50CA103175 · NCI · JOHNS HOPKINS UNIVERSITY · PI BARKER, PETER B · 2003 to 2015
$17.9M
PHASE I TRIALS OF ANTICANCER AGENTSU01CA070095 · NCI · JOHNS HOPKINS UNIVERSITY · PI CARDUCCI, MICHAEL A · 1995 to 2013
$8.6M
Multi-Modality Quantitiative Imaging for Evaluation of Response to Cancer TherapyU01CA140204 · NCI · JOHNS HOPKINS UNIVERSITY · PI DU, YONG, SOLNES, LILJA · 2011 to 2022
$6.1M
NCI NIH HHS P30 CA006973NCI NIH HHS P50 CA103175NCI NIH HHS U01 CA070095NCI NIH HHS U01 CA140204
6 · The paper itself

Abstract

Purpose. WB-MRI is mainly used for tumor detection and surveillance. The purpose of this study is to establish the feasibility of WB-MRI at 3T for lesion characterization, with DWI/ADC-mapping and contrast-enhanced sequences, in patients with neurofibromatosis type 2 (NF-2) and schwannomatosis. Materials and Methods. At 3T, WB-MRI was performed in 11 subjects (10 NF-2 and 1 schwannomatosis) with STIR, T1, contrast-enhanced T1, and DWI/ADC mapping (b = 50, 400, 800 s/mm(2)). Two readers reviewed imaging for the presence and character of peripheral lesions. Lesion size and features (signal intensity, heterogeneity, enhancement characteristics, and ADC values) were recorded. Descriptive statistics were reported. Results. Twenty-three lesions were identified, with average size of 4.6 ± 2.8 cm. Lesions were characterized as tumors (21/23) or cysts (2/23) by contrast-enhancement properties (enhancement in tumors, no enhancement in cysts). On T1, tumors were homogeneously isointense (5/21) or hypointense (16/21); on STIR, tumors were hyperintense and homogeneous (10/21) or heterogeneous (11/21); on postcontrast T1, tumors enhanced homogeneously (14/21) or heterogeneously (7/21); on DWI, tumor ADC values were variable (range 0.8-2.7), suggesting variability in intrinsic tumor properties. Conclusion. WB-MRI with quantitative DWI and contrast-enhanced sequences at 3T is feasible and advances the utility of WB-MRI not only to include detection, but also to provide additional metrics for lesion characterization.

Identifiers

PMID24967287
PMCPMC4045550
OpenAlexW2095849839

What OpenQuestion holds

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Registered trials

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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.