Proton density fat‐fraction: A standardized mr‐based biomarker of tissue fat concentration

Abstract

On February 19–22, the 2012 ISMRM Workshop on Fat–Water Separation was held in Long Beach, California. Over 130 attendees from 13 countries convened to discuss historical aspects of water–fat imaging, as well as technical and clinical developments, and remaining challenges. Among these attendees were new and established investigators. A comprehensive overview of the meeting and presentations from the 25 invited speakers at the workshop was recently published in Magnetic Resonance in Medicine (1). As illustrated in Figure 1 below, scientific interest in fat quantification using MR spectroscopy (MRS) and MR imaging (MRI) has grown steadily in the past decade. Accordingly, many of the invited lectures and scientific abstracts at the meeting focused on emerging MRS- and MRI-based methods to quantify tissue fat concentration. Applications included quantification of tissue fat concentration in organs and tissues such as liver, pancreas, skeletal muscle, heart, thymus, bone marrow, and white and brown adipose tissue, as well as the use of MRI techniques to quantify and characterize fat content for the food industry. During these lectures and ensuing discussions, a theme that emerged multiple times was the need to standardize MR-based biomarkers for assessing tissue fat concentration. The number of citations on fat quantification with magnetic resonance has grown steadily in the past decade. This pubmed.org search, limited to 1998 through 2011, was conducted on April 20, 2012, using key words “fat quantification magnetic resonance”. While many different MR-based biomarkers may be considered for fat quantification, an informal consensus was reached at the meeting that proton-density fat-fraction (PDFF) is currently the most practical and meaningful MR-based biomarker for this purpose. Thus, the goal of this editorial is to provide a formal statement from three of the organizers of the ISMRM workshop on the choice of PDFF as the standardized MR-based biomarker for tissue fat concentration. It is our position that PDFF is the most appropriate standardized biomarker of tissue fat concentration when measured appropriately with quantitative MRS or MRI techniques. In the remainder of this editorial we will define PDFF, justify its use as a standardized MR-based biomarker of tissue fat concentration, explain current technical approaches to measure PDFF correctly, and explain differences of PDFF with tissue-based measures of fat concentration such as biochemical assays of tissue fat. In general, several important metrics of a valid biomarker must be considered when choosing a biomarker for standardization. In addition to measuring a clinically relevant quantity (e.g., liver fat content), the biomarker must be accurate, precise, robust, and reproducible. Accuracy reflects the degree of correlation between the biomarker and an accepted reference standard, i.e., how well does the biomarker predict the quantity being measured? Precision, or repeatability, reflects the variability of the biomarker when repeated measurements are made, including within an examination and between examinations. Precision is particularly important for treatment monitoring and for longitudinal measurements. An imaging biomarker is considered robust if it is insensitive to changes in the scanning parameters that might be encountered in clinical practice or in a clinical trial. Finally, validation studies should be reproducible, with low variability across platform, scanner manufacturer, field strength, reader, reading center, and technologist. As we discuss below, the PDFF is an imaging biomarker that best meets all of these criteria. Standardization of all biomarkers, including PDFF, is critical for research and clinical purposes. This permits pooling of results across multiple centers, including meta-analyses and multi-center studies, as well as implementation into widespread clinical practice and acceptance. Finally, standardization of PDFF as the MR-based biomarker of tissue fat concentration would permit portability of tissue fat concentration measurements for patients being cared for at multiple institutions. Prototype implementations of MR-based measurements of PDFF proposed by multiple groups have also demonstrated a practical strength of PDFF: the ability to record PDFF values directly from PDFF maps (2-4). Fully automated calculation of PDFF maps generated using imaging-based methods or PDFF values measured using automated postprocessing of single-voxel MRS-based methods are highly practical and easily accepted by clinicians (5). While the reconstruction algorithms are advanced and require complex computations, the algorithms can be implemented seamlessly to rapidly generate MRI-based PDFF maps or MRS-based PDFF values online. So long as the underlying complexity is invisible to the practitioner, the use of PDFF algorithms will be easily adopted and accepted in a clinical setting. This practical aspect of PDFF is understated, and is a clear a