Identification of focal lesion characteristics in MRI which indicate presence of corresponding osteolytic lesion in CT in patients with multiple myeloma

The presence of bone marrow focal lesions and osteolytic lesions in patients with multiple myeloma (MM) is of high prognostic significance for their individual outcome. It is not known yet why some focal lesions seen in MRI, reflecting localized bone marrow infiltration of myeloma cells, remain non-lytic, whereas others are associated with destruction of mineralized bone. In this study, we analyzed MRI characteristics of manually segmented focal lesions in MM patients to identify possible features that might discriminate lytic and non-lytic lesions. The initial cohort included a total of 140 patients with different stages of MM who had undergone both whole-body MRI and whole-body low-dose CT within 30 days, and of which 29 satisfied the inclusion criteria for this study. Focal lesions in MRI and corresponding osteolytic areas in CT were segmented manually. Analysis of the lesions included volume, location and first order texture features analysis. There were significantly more lytic lesions in the axial skeleton than in the appendicular skeleton (p = 0.037). Out of 926 focal lesions in the axial skeleton seen on MRI, 544 (59.3 %) were osteolytic. Analysis of volume and first order texture features showed differences in texture and volume between focal lesions in MRI with and without local bone destruction in CT, but these findings were not statistically significant. Neither morphological imaging characteristics like size and location nor first order texture features could predict whether focal lesions seen in MRI would exhibit corresponding bone destruction in CT. Studies performing biopsies of such lesions are ongoing. •Consideration of radiological markers in MRI to predict bone destruction in CT.•Higher odds of a focal lesion being osteolytic in the axial skeleton vs. appendicular skeleton•Volume of osteolytic focal lesions in MRI is higher than in non-osteolytic lesions.•Automatic detection and segmentation of lesions in the future could be possible.