Observational studyEuropean radiology2022
Feasibility of artificial intelligence-supported assessment of bone marrow infiltration using dual-energy computed tomography in patients with evidence of monoclonal protein - a retrospective observational study.
Observational study in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Identification of Bone Marrow and Peripheral Blood Plasma Extracellular Vesicle Protein Biomarker Signatures for Multiple Myeloma Diagnosis and Staging.International journal of nanomedicine · 2026Article
- Clinical utility of artificial intelligence models in radiology: a systemic scoping review of diagnostic and endovascular applications.CVIR endovascular · 2025Review
- Dual-energy CT-derived virtual noncalcium imaging to assess bone marrow lesions in patients with knee osteoarthritis.Scientific reports · 2025Article
- Diagnosis of newly developed multiple myeloma without bone disease detectable on conventional computed tomography (CT) scan by using dual-energy CT.Journal of bone oncology · 2024Article
- The Challenging Approach to Multiple Myeloma: From Disease Diagnosis and Monitoring to Complications Management.Cancers · 2024Review
- Correlation between vertebral bone mineral density and multi-level virtual non-calcium imaging parameters from dual-layer spectral detector computed tomography.Quantitative imaging in medicine and surgery · 2024Article
- Updates on the Applications of Spectral Computed Tomography for Musculoskeletal Imaging.Diagnostics (Basel, Switzerland) · 2024Review
- Quantitative assessment of bone marrow infiltration and characterization of tumor burden using dual-layer spectral CT in patients with multiple myeloma.Radiology and oncology · 2024Article
- Current Status and Future of Artificial Intelligence in MM Imaging: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Correlation between whole skeleton dual energy CT calcium-subtracted attenuation and bone marrow infiltration in multiple myeloma.European journal of radiology · 2022Article
- Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
objectivesTo demonstrate the feasibility of an automated, non-invasive approach to estimate bone marrow (BM) infiltration of multiple myeloma (MM) by dual-energy computed tomography (DECT) after virtual non-calcium (VNCa) post-processing.
methodsIndividuals with MM and monoclonal gammopathy of unknown significance (MGUS) with concurrent DECT and BM biopsy between May 2018 and July 2020 were included in this retrospective observational study. Two pathologists and three radiologists reported BM infiltration and presence of osteolytic bone lesions, respectively. Bone mineral density (BMD) was quantified CT-based by a CE-certified software. Automated spine segmentation was implemented by a pre-trained convolutional neural network. The non-fatty portion of BM was defined as voxels > 0 HU in VNCa. For statistical assessment, multivariate regression and receiver operating characteristic (ROC) were conducted.
resultsThirty-five patients (mean age 65 ± 12 years; 18 female) were evaluated. The non-fatty portion of BM significantly predicted BM infiltration after adjusting for the covariable BMD (p = 0.007, r = 0.46). A non-fatty portion of BM > 0.93% could anticipate osteolytic lesions and the clinical diagnosis of MM with an area under the ROC curve of 0.70 [0.49-0.90] and 0.71 [0.54-0.89], respectively. Our approach identified MM-patients without osteolytic lesions on conventional CT with a sensitivity and specificity of 0.63 and 0.71, respectively.
conclusionsAutomated, AI-supported attenuation assessment of the spine in DECT VNCa is feasible to predict BM infiltration in MM. Further, the proposed method might allow for pre-selecting patients with higher pre-test probability of osteolytic bone lesions and support the clinical diagnosis of MM without pathognomonic lesions on conventional CT. KEY POINTS: • The retrospective study provides an automated approach for quantification of the non-fatty portion of bone marrow, based on AI-supported spine segmentation and virtual non-calcium dual-energy CT data. • An increasing non-fatty portion of bone marrow is associated with a higher infiltration determined by invasive biopsy after adjusting for bone mineral density as a control variable (p = 0.007, r = 0.46). • The non-fatty portion of bone marrow might support the clinical diagnosis of multiple myeloma when conventional CT images are negative (sensitivity 0.63, specificity 0.71).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.