Radiomics Analysis for Multiple Myeloma: A Systematic Review with Radiomics Quality Scoring

Abstract

Multiple myeloma (MM) is one of the most common hematological malignancies affecting the bone marrow. Radiomics analysis has been employed in the literature in an attempt to evaluate the bone marrow of MM patients. This manuscript aimed to systematically review radiomics research on MM while employing a radiomics quality score (RQS) to accurately assess research quality in the field. A systematic search was performed on Web of Science, PubMed, and Scopus. The selected manuscripts were evaluated (data extraction and RQS scoring) by three independent readers (R1, R2, and R3) with experience in radiomics analysis. A total of 23 studies with 2682 patients were included, and the median RQS was 10 for R1 (IQR 5.5–12) and R3 (IQR 8.3–12) and 11 (IQR 7.5–12.5) for R2. RQS was not significantly correlated with any of the assessed bibliometric data (impact factor, quartile, year of publication, and imaging modality) (p > 0.05). Our results demonstrated the low quality of published radiomics research in MM, similarly to other fields of radiomics research, highlighting the need to tighten publication standards.

The promise and limitations of artificial intelligence in musculoskeletal imaging

“…In one retrospective study, Gitto et al assessed the diagnostic performance of ML-enhanced radiomics-based MRI for the classification and differentiation of atypical lipomatous tumors of the extremities from other benign lipomas, reporting a sensitivity of 92%, a specificity of 33%, and no statistically significant difference when compared to qualitative image assessment performed by a radiologist with 7 years of experience ( 89 ). Research into the field is ongoing, and although radiomics has shown promise as a powerful and innovative tool that can help with the evaluation of different types of cancers, more research is needed to fully explore the full scope of its applications ( 115 ).…”