Body Composition Factors in Myeloma Spectrum Patients that Predict Morbidity, Mortality, and Progression: Opportunistic Screening Using Whole Body Low Dose CT

• Applicant: Fabian Stefan Bauer
• Subject Area: Nuclear Medicine, Radiotherapy, Radiobiology
• Term: from 2023 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 538209205

The proposed research project aims to establish predictive models for morbidity, mortality, and disease progression in the myeloma spectrum, ranging from monoclonal gammopathy of undetermined significance to (smoldering) multiple myeloma. For this study, body composition measurements will be obtained from whole body low dose CT scans, utilizing approximately 430 CT scans performed at the host institution between July 2017 and the present. The whole body low dose CT scans will be retrospectively analyzed and 2D body composition analysis will be performed on selected thoracic (T3, T5, T7) and lumbar (L4) levels. The body composition measurements comprise the quantification and assessment of the cross sectional area and density of total adipose tissue, subcutaneous and visceral adipose tissue, intermuscular adipose tissue, muscle tissue and vertebral bone. These measurements will be performed using validated segmentation algorithms. Subsequently, measurements will be averaged and indexed as body composition markers based on patient weight, patient height, age, and gender. The patient outcomes, including time to progression, days of hospitalization, chemotherapy response, adverse effects, fractures, progression-free survival, and overall survival, will be documented and correlated with patient and disease characteristics and body composition markers. Multivariate analyses will be conducted to establish predictive models. This proposed study aligns with routine clinical practice as whole body low dose CT is indicated and regularly performed when suspecting myeloma spectrum disease, allowing for opportunistic screening without additional risk to the patients. By utilizing body composition measurements from these scans, the study aims to identify additional body composition markers with predictive value, potentially improving the prediction of disease progression as well as patient outcomes, which may lead to an enhancement of patient management and treatment strategies.

• DFG Programme: WBP Fellowship
• International Connection: USA
• Host: Professorin Dr. Connie Chang