Evidence map›Paper›PMID 27766627›Full record

ArticleBritish journal of haematology2017

Whole body magnetic resonance imaging in newly diagnosed multiple myeloma: early changes in lesional signal fat fraction predict disease response.

Arash Latifoltojar, Margaret Hall-Craggs, Neil Rabin, Rakesh Popat, Alan Bainbridge, Nikolaos Dikaios, Magdalena Sokolska, Ali Rismani, Shirley D'Sa, Shonit Punwani and 1 more

Open access · hybridAbstract read
In one paragraph

Article in British journal of haematology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

35 citing papers in PubMed, 66 citations in OpenAlex.

  1. Article
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  4. Application and assessment of deep learning to routine 2D T2 FLEX spine imaging at 1.5T.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
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  11. [Minimal residual disease assessment and progress in multiple myeloma].Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi · 2024
    Article
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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

11 authors at 4 institutions in 1 country.

Arash LatifoltojarCentre for Medical Imaging, University College London, London, UK.ORCID http://orcid.org/0000-0002-5143-746X
Margaret Hall-CraggsCentre for Medical Imaging, University College London, London, UK.
Neil RabinDepartment of Haematology, University College London Hospitals, London, UK.
Rakesh PopatDepartment of Haematology, University College London Hospitals, London, UK.
Alan BainbridgeDepartment of Medical Physics, University College London Hospitals, London, UK.
Nikolaos DikaiosCentre for Medical Imaging, University College London, London, UK.
Magdalena SokolskaDepartment of Medical Physics, University College London Hospitals, London, UK.
Ali RismaniDepartment of Haematology, University College London Hospitals, London, UK.
Shirley D'SaDepartment of Haematology, University College London Hospitals, London, UK.
Shonit PunwaniCentre for Medical Imaging, University College London, London, UK.
Kwee YongUCL Cancer Institute, Haematology, University College London, London, UK.
University College Hospital · GBUniversity College London Hospitals NHS Foundation Trust · GBUniversity College London · GBCRUK Lung Cancer Centre of Excellence · GB

Funding

Cancer Research UK 16463
6 · The paper itself

Abstract

Cross-sectional imaging techniques are being increasingly used for disease evaluation in patients with multiple myeloma. Whole body magnetic resonance imaging (WB-MRI) scanning is superior to plain radiography in baseline assessment of patients but changes following treatment have not been systematically explored. We carried out paired WB-MRI scans in 21 newly diagnosed patients prior to, and 8-weeks after, starting chemotherapy, and analysed stringently selected focal lesions (FLs) for parametric changes. A total of 323 FLs were evaluated, median 20 per patient. At 8 weeks, there was a reduction in estimated tumour volume (eTV), and an increase in signal fat fraction (sFF) and apparent diffusion coefficient (ADC) in the group as a whole (P < 0·001). Patients who achieved complete/very good partial response (CR/VGPR) to induction had a significantly greater increase in sFF compared to those achieving ≤ partial response (PR; P = 0·001). When analysed on a per-patient basis, all patients achieving CR/VGPR had a significant sFF increase in their FL's, in contrast to patients achieving ≤PR. sFF changes in patients reaching maximal response within 100 days (fast responders) were greater compared to slow responders (P = 0·001). Receiver Operator Characteristic analysis indicated that sFF changes at 8 weeks were the best biomarker (area under the Curve 0·95) for an inferior response (≤PR). We conclude that early lesional sFF changes may provide important information on depth of response, and are worthy of further prospective study.

Indexed as

Predictive Value of TestsAdipose TissueAdultAgedBiomarkersFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMultiple MyelomaRemission InductionTime FactorsTreatment OutcomeTumor BurdenWhole Body ImagingBiomarkersbortezomibmagnetic resonance imagingmultiple myelomatreatment responsewhole body

Identifiers

PMID27766627
PMCPMC5244686
OpenAlexW2537996207

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.