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).
Highlights
Multiple myeloma (MM) and its precursor conditions smoldering myeloma and monoclonal gammopathy of unknown significance (MGUS) outline a continuous spectrum of monoclonal plasma cell disorders
The patient with smoldering myeloma was included in the MM subgroup, since bone marrow (BM) Infiltration was above the MGUS threshold (≥ 10%)
BM biopsy and dual-energy computed tomography (DECT) scan were separated by a median of 4.5 days [interquartile range 1.0–12.5 days]
Summary
Multiple myeloma (MM) and its precursor conditions smoldering myeloma and monoclonal gammopathy of unknown significance (MGUS) outline a continuous spectrum of monoclonal plasma cell disorders. Most cases of MM are preceded by the asymptomatic, premalignant disorders smoldering myeloma or MGUS, which are commonly diagnosed incidentally in patients presenting with other conditions [1]. Standard work-up for diagnosis of plasma cell disorders includes laboratory testing, bone marrow (BM) biopsy of the iliac crest, and whole body imaging [3]. BM biopsy is required to evaluate the degree of plasma cell infiltration, while diagnostic imaging is employed to detect myeloma defining bone lesions [3]. Despite IMWG recommendations, a recent large-scale clinical analysis challenged the obligation of regular invasive BM diagnostic for patients with evidence of monoclonal antibody, since in most cases it did not contribute to the diagnosis [5]
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