Evidence map›Paper›PMID 41706122›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Lesion-level dual-tracer PET biomarkers predict prognosis in multiple myeloma treated with CXCR4-directed radiopharmaceutical therapy.

Song Xue, Sabrina Kraus, Johanna S Enke, Kerstin Michalski, Marcus Hacker, Hermann Einsele, Andreas K Buck, Constantin Lapa, Xiang Li, Niklas Dreher

Abstract read
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

1 citing paper in PubMed.

  1. 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

10 authors.

Song XueDivision of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Vienna General Hospital, Medical University of Vienna, Vienna, Austria.
Sabrina KrausDepartment of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany.
Johanna S EnkeNuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Kerstin MichalskiDepartment of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany.
Marcus HackerDivision of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Vienna General Hospital, Medical University of Vienna, Vienna, Austria.
Hermann EinseleDepartment of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany.
Andreas K BuckDepartment of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany.
Constantin LapaNuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Xiang LiDivision of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Vienna General Hospital, Medical University of Vienna, Vienna, Austria. Xiang.li@meduniwien.ac.at.ORCID 0000-0002-0016-6233
Niklas DreherNuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundC-X-C motif chemokine receptor 4 (CXCR4)-directed radiopharmaceutical therapy (RPT) represents a promising option for hematologic malignancies. Nevertheless, responses in relapsed and refractory (r/r) multiple myeloma (MM) are heterogenous, emphasizing the need for optimized patient selection before RPT. Current approaches mostly rely on qualitative assessments, confirming relevant CXCR4-expression by CXCR4-directed PET in vital myeloma burden, the latter usually being determined by additional [ PURPOSE: To evaluate whether quantitative imaging biomarkers derived from dual-tracer PET/CT can enhance patient stratification and predict therapeutic response and survival following CXCR4-RPT. MATERIALS AND

methods22 patients with r/r MM who underwent CXCR4-directed [⁶⁸Ga]Ga-PentixaFor-PET/CT and [¹⁸F]FDG-PET/CT imaging prior to CXCR4-RPT were retrospectively analyzed. A fully automated pipeline performed deep-learning-based lesion segmentation and dual-tracer fusion; batch quality control and correction ensured segmentation accuracy and concordant-lesion adjudication (> 10% volumetric overlap) prior to lesion-level feature extraction. Features included demographics, laboratory/genetic variables, and imaging metrics from FDG- and CXCR4-PET, stratified by anatomic site (medullary vs. extramedullary) and concordance (concordant vs. discordant as defined by comparing FDG- and CXCR4-positive myeloma lesions). Surface-standardized maximum inter-lesion distances (sDmax) were additionally computed. Endpoints were therapy response (responder vs. non-responder as defined by serological response assessment based on IMWG-criteria or PET/MRI based response assessment) and overall survival (OS). Group comparisons were performed using Welch's t-test/Chi-square; survival analysis was conducted applying Kaplan-Meier estimates and log-rank tests. Decision-tree models were interpreted with SHapley Additive exPlanations (SHAP).

resultsResponders to RPT showed lower [

conclusionsIn our exploratory analysis, [¹⁸F]FDG-uptake within medullary concordant lesions was linked to both response and survival, while CXCR4-expressing medullary volume and sDmax added survival information. Concordance-aware, lesion-level quantification from dual-tracer PET/CT might present as a promising approach to aid risk stratification for CXCR4-directed RPT. However, initial findings of our hypothesis generating analysis warrant prospective validation in larger cohorts.

Indexed as

Biomarkers, TumorMultiple MyelomaPositron Emission Tomography Computed TomographyRadiopharmaceuticalsReceptors, CXCR4AgedAged, 80 and overCoordination ComplexesFemaleFluorodeoxyglucose F18HumansMaleMiddle AgedPeptides, CyclicPrognosisRetrospective Studies68Ga-pentixaforBiomarkers, TumorCoordination ComplexesCXCR4 protein, humanFluorodeoxyglucose F18Peptides, CyclicRadiopharmaceuticalsReceptors, CXCR4CXCR4-RPTDual-tracer PETLesion-level quantificationPrognosis biomarker

Identifiers

PMID41706122
PMCPMC13197444

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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.