Michael Boss, PhD, Director of ACR Imaging Core Lab, along with his colleague, Dr. Madeline E. Carr, recently published Conformance of a 3T radiotherapy MRG Scanner to the QIBA Diffusion Profile in Medical Physics. The purpose of this peer reviewed article is to highlight the feasibility of conformance, particularly the QA requirements.

Diffusion-Weighted Imaging (DWI) is a Quantitative Magnetic Resonance Imaging (qmRI) technique that is often used to study a patient’s tissue cellularity via the water Apparent Diffusion Coefficient (ADC). While this could have a positive impact on disease diagnosis and treatment, there are various technical performance uncertainties in measuring ADC that limit its clinical implementation. The Quantitative Imaging Biomarker Alliance (QIBA) released the QIBA Diffusion Profile in order to list methods and specifications that need to be met for a site to ensure reproducible ADC in multicenter trials. Several phantoms have been produced to meet the Profile’s requirement to perform testing on a pure water ADC sample. However, there is not enough literature describing long-term system stability measurements, nor are there enough studies focusing on imaging dependencies on ADC reliability. Therefore, the objective of this study was to assess the long-term technical performance of ADC on a 3T radiotherapy dedicated MRI scanner.

The National Institute of Standards and Technology (NIST) diffusion phantom used in this study was periodically imaged every month for a year with a 3T MRI scanner. The phantom was manually repositioned from its axial orientation to coronal and then sagittal within the Head/Neck coil. During each rotation, the slice-encoding (and phase-encoding for coronal) direction was changed to match its respective rotation. Each long-term (LT) monthly acquisition included repeating the short-term (ST) measurements in each phantom orientation. The central pixel location was manually identified for each of the vials by using the first repetition ADC map measured for each imaging direction. These locations were imported, along with all four repetitions of trace-DWI and ADC maps, into an in-house developed Python analysis script. In order to investigate the analysis software used for testing Profile conformance, computer-generated DICOM data sets known as digital reference objects (DROs), with b-values of 0, 500, 8000, and 2000 s/mm2 were imported into the offline DWI-fit Python script.

Profile tolerance limits for repeatability, reproducibility, and precision were met for all vials with concentrations 0-30% PVP. The average axial %bias (+ 0.05%) and repeatability (CVST = 0.1%) for the central water vial (at isocenter) were well within Profile tolerance range and were comparable to measurements reported in the literature. A strong and positive linear correlation was found between measured and reference ADC values for all direction acquisitions. Long-term system stability of deriving the ADC (axial CVLT = 0.9%) was also found, displaying similar results as previous studies using this phantom. These results showed that there is minimal imaging directional dependence on ADC performance. Generally, vials with lower diffusivities (40% and 50% PVP) had inferior performance metrics. This could be due to several factors such as eddy currents, gradient nonlinearities, or insufficient contrast to noise ratio (CNR) or SNR to correctly assess the ADC in the highly concentrated vials.

“This study shows that clinical sites should be able to conform to the Profile fairly easily, which means they should be able to obtain quantitative MRI diffusion data within the "claim" of the Profile. When a site uses and conforms to the Profile, they can have high confidence that a measured change in diffusion is a true change (not due to measurement noise/randomness) within the limits the claim describes (e.g., an 11% change in diffusion of a brain lesion is 95% likely to be a true change). Dr. Carr really went above and beyond because she wanted to see how stable her system was, and no one had performed this type of work as diligently as she did,” as stated by Michael A. Boss, PhD, Director of ACR Imaging Core Lab, Editor of the QIBA DWI Profile, Founder of QIBA DWI Biomarker Committee, and Inventor of the phantom.

To access the full article, click here: http://doi.org/10.1002/mp.15645

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Director of ACR CRI’s Imaging Core Lab Publishes QIBA Diffusion Profile Conformance Article