Measuring response to treatment in axial spondyloarthritis using quantitative imaging biomarkers: a prospective observational cohort study.

OBJECTIVE: Objective assessments of disease activity and response to treatment in axial spondyloarthritis (axSpA) remain a challenge; quantitative imaging biomarkers (QIBs) of inflammation could enhance assessments of disease activity and therapeutic response. We aimed to determine the responsiveness of QIBs obtained from diffusion-weighted imaging (DW-MRI) and chemical shift-encoded MRI (CSE-MRI) using the partially automated Bone Edema and Adiposity Characterisation with Histograms (BEACH) software tool in axSpA patients undergoing biologic therapy. METHODS: We conducted a prospective longitudinal cohort study, including 30 patients with axSpA undergoing biologic therapy. Patients were scanned before and after biologic therapy using conventional MRI, DWI and CSE-MRI at 3T. Apparent diffusion coefficient (ADC) and proton density fat fraction (PDFF) were assessed using the BEACH tool (https://github.com/TJPBray/BEACH), and conventional MR images were assessed using established visual scoring methods by expert radiologists. Responsiveness - the ability of the MRI measurements to capture changes in disease occurring as a result of biologic therapy - was assessed using the standardized response mean (SRM). Inter-reader reliability of the ADC and PDFF maps was assessed using Bland-Altman limits of agreement analysis and the intraclass correlation coefficient. RESULTS: Responsiveness to therapy was moderate for ADC-based parameters (SRM 0.50) and comparable to established visual scoring methods for bone marrow oedema (SRM 0.53). Interobserver variability was lower for QIBs compared with conventional visual scores methods. CONCLUSIONS: QIBs measured using the BEACH tool are sensitive to changes in inflammation in axSpA following biologic therapy, with similar responsiveness and lower interobserver variability to visual scoring by expert radiologists. ADVANCES IN KNOWLEDGE: QIBs measured using the partially automated BEACH tool offer an objective measure of response to biologic therapy in axSpA.

Assessment of body composition and association with clinical outcomes in patients with lung and colorectal cancer.

Objectives: To assess body composition in patients with non-small cell lung cancer (NSCLC) and colorectal cancer using whole-body MRI and relate this to clinical outcomes. Methods: 53 patients with NSCLC (28 males, 25 females; mean age 66.9) and 74 patients with colorectal cancer (42 males, 32 females; mean age 62.9) underwent staging whole-body MRI scans, which were post-processed to derive fat mass (FM), fat free mass (FFM) and skeletal muscle (SM) indices and SM fat fraction (FF). These were compared between the two cancer cohorts using two-sided t-tests and the chi-squared test. Measurements of body composition were correlated with outcomes including length of hospital stay, metastatic status and mortality. Results: Patients with NSCLC had significantly lower FFM (p = 0.0071) and SM (p = 0.0084) indices. Mean SM FF was greater in patients with NSCLC (p = 0.0124) and was associated with longer hospital stay (p = 0.035). There was no significant relationship between FM, FFM and SM indices and length of hospital stay, metastatic status or mortality. Conclusions: Patients with NSCLC had lower FFM and SM indices than patients with colorectal cancer and greater SMFF, indicating lower SM mass with fatty infiltration. These findings reflect differences in the phenotype of the two groups and suggest patients with lung cancer are more likely to require additional nutritional support. Advances in knowledge: Body composition differs between NSCLC and colorectal cancer. Patients with NSCLC have both a reduced SM mass and greater SM FF suggesting that they are more nutritionally deplete than patients with colorectal cancer.

Fat fraction mapping using magnetic resonance imaging: insight into pathophysiology.

Adipose cells have traditionally been viewed as a simple, passive energy storage depot for triglycerides. However, in recent years it has become clear that adipose cells are highly physiologically active and have a multitude of endocrine, metabolic, haematological and immune functions. Changes in the number or size of adipose cells may be directly implicated in disease (e.g. in the metabolic syndrome), but may also be linked to other pathological processes such as inflammation, malignant infiltration or infarction. MRI is ideally suited to the quantification of fat, since most of the acquired signal comes from water and fat protons. Fat fraction (FF, the proportion of the acquired signal derived from fat protons) has, therefore, emerged as an objective, image-based biomarker of disease. Methods for FF quantification are becoming increasingly available in both research and clinical settings, but these methods vary depending on the scanner, manufacturer, imaging sequence and reconstruction software being used. Careful selection of the imaging method-and correct interpretation-can improve the accuracy of FF measurements, minimize potential confounding factors and maximize clinical utility. Here, we review methods for fat quantification and their strengths and weaknesses, before considering how they can be tailored to specific applications, particularly in the gastrointestinal and musculoskeletal systems. FF quantification is becoming established as a clinical and research tool, and understanding the underlying principles will be helpful to both imaging scientists and clinicians.