Evidence map›Paper›PMID 33130917›Full record

ArticleCancer immunology, immunotherapy : CII2021

Noninvasive, longitudinal imaging-based analysis of body adipose tissue and water composition in a melanoma mouse model and in immune checkpoint inhibitor-treated metastatic melanoma patients.

Wolfgang M Thaiss, Sergios Gatidis, Tina Sartorius, Jürgen Machann, Andreas Peter, Thomas K Eigentler, Konstantin Nikolaou, Bernd J Pichler, Manfred Kneilling

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

Article in Cancer immunology, immunotherapy : CII, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.8field-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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
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 4 institutions in 1 country.

Wolfgang M ThaissDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard Karls University, 72076, Tübingen, Germany.ORCID http://orcid.org/0000-0002-0796-780X
Sergios GatidisDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University, 72076, Tübingen, Germany.
Tina SartoriusGerman Center for Diabetes Research (DZD E.V.), Neuherberg, Germany.
Jürgen MachannGerman Center for Diabetes Research (DZD E.V.), Neuherberg, Germany.
Andreas PeterGerman Center for Diabetes Research (DZD E.V.), Neuherberg, Germany.
Thomas K EigentlerDepartment of Dermatology, University Hospital Tübingen, Liebermeisterstreet 20, 72076, Tübingen, Germany.
Konstantin NikolaouDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University, 72076, Tübingen, Germany.
Bernd J PichlerDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard Karls University, 72076, Tübingen, Germany.
Manfred KneillingDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard Karls University, 72076, Tübingen, Germany. manfred.kneilling@med.uni-tuebingen.de.ORCID http://orcid.org/0000-0001-9119-1970
Deutsches Diabetes-Zentrum e.V. · DESiemens (Germany) · DEUniversity Children's Hospital Tübingen · DEUniversity of Tübingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs cancer cachexia (CC) is associated with cancer progression, early identification would be beneficial. The aim of this study was to establish a workflow for automated MRI-based segmentation of visceral (VAT) and subcutaneous adipose tissue (SCAT) and lean tissue water (LTW) in a B16 melanoma animal model, monitor diseases progression and transfer the protocol to human melanoma patients for therapy assessment.

methodsFor in vivo monitoring of CC B16 melanoma-bearing and healthy mice underwent longitudinal three-point DIXON MRI (days 3, 12, 17 after subcutaneous tumor inoculation). In a prospective clinical study, 18 metastatic melanoma patients underwent MRI before, 2 and 12 weeks after onset of checkpoint inhibitor therapy (CIT; n = 16). We employed an in-house MATLAB script for automated whole-body segmentation for detection of VAT, SCAT and LTW.

resultsB16 mice exhibited a CC phenotype and developed a reduced VAT volume compared to baseline (B16 - 249.8 µl, - 25%; controls + 85.3 µl, + 10%, p = 0.003) and to healthy controls. LTW was increased in controls compared to melanoma mice. Five melanoma patients responded to CIT, 7 progressed, and 6 displayed a mixed response. Responding patients exhibited a very limited variability in VAT and SCAT in contrast to others. Interestingly, the LTW was decreased in CIT responding patients (- 3.02% ± 2.67%; p = 0.0034) but increased in patients with progressive disease (+ 1.97% ± 2.19%) and mixed response (+ 4.59% ± 3.71%).

conclusionMRI-based segmentation of fat and water contents adds essential additional information for monitoring the development of CC in mice and metastatic melanoma patients during CIT or other treatment approaches.

Indexed as

Adipose TissueAgedAnimalsCachexiaDisease Models, AnimalFemaleHumansImmune Checkpoint InhibitorsMagnetic Resonance ImagingMaleMelanomaMelanoma, ExperimentalMiceMice, Inbred C57BLMiddle AgedMonitoring, PhysiologicImmune Checkpoint InhibitorsWaterCancer cachexiaImmune checkpoint inhibitor therapyMelanomaMRISegmentationTherapy monitoring

Identifiers

PMID33130917
PMCPMC8053172
OpenAlexW3096401754

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.