Search

MRI-based cartilage compositional analysis shows biochemical and microstructural changes at early stages of osteoarthritis before changes become visible with structural MRI sequences and arthroscopy. This could help with early diagnosis, risk assessment, and treatment monitoring of osteoarthritis. Spin-lattice relaxation time constant in rotating frame (T1ρ) and T2 mapping are the MRI techniques best established for assessing cartilage composition. Only T2 mapping is currently commercially available, which is sensitive to water, collagen content, and orientation of collagen fibers, whereas T1ρ is more sensitive to proteoglycan content. Clinical application of cartilage compositional imaging is limited by high variability and suboptimal reproducibility of the biomarkers, which was the motivation for creating the Quantitative Imaging Biomarkers Alliance (QIBA) Profile for cartilage compositional imaging by the Musculoskeletal Biomarkers Committee of the QIBA. The profile aims at providing recommendations to improve reproducibility and to standardize cartilage compositional imaging. The QIBA Profile provides two complementary claims (summary statements of the technical performance of the quantitative imaging biomarkers that are being profiled) regarding the reproducibility of biomarkers. First, cartilage T1ρ and T2 values are measurable at 3.0-T MRI with a within-subject coefficient of variation of 4%-5%. Second, a measured increase or decrease in T1ρ and T2 of 14% or more indicates a minimum detectable change with 95% confidence. If only an increase in T1ρ and T2 values is expected (progressive cartilage degeneration), then an increase of 12% represents a minimum detectable change over time. The QIBA Profile provides recommendations for clinical researchers, clinicians, and industry scientists pertaining to image data acquisition, analysis, and interpretation and assessment procedures for T1ρ and T2 cartilage imaging and test-retest conformance. This special report aims to provide the rationale for the proposed claims, explain the content of the QIBA Profile, and highlight the future needs and developments for MRI-based cartilage compositional imaging for risk prediction, early diagnosis, and treatment monitoring of osteoarthritis.

Background Proton density fat fraction (PDFF) estimated by using chemical shift-encoded (CSE) MRI is an accepted imaging biomarker of hepatic steatosis. This work aims to promote standardized use of CSE MRI to estimate PDFF. Purpose To assess the accuracy of CSE MRI methods for estimating PDFF by determining the linearity and range of bias observed in a phantom. Materials and Methods In this prospective study, a commercial phantom with 12 vials of known PDFF values were shipped across nine U.S. centers. The phantom underwent 160 independent MRI examinations on 27 1.5-T and 3.0-T systems from three vendors. Two three-dimensional CSE MRI protocols with minimal T1 bias were included: vendor and standardized. Each vendor's confounder-corrected complex or hybrid magnitude-complex based reconstruction algorithm was used to generate PDFF maps in both protocols. The Siemens reconstruction required a configuration change to correct for water-fat swaps in the phantom. The MRI PDFF values were compared with the known PDFF values by using linear regression with mixed-effects modeling. The 95% CIs were calculated for the regression slope (ie, proportional bias) and intercept (ie, constant bias) and compared with the null hypothesis (slope = 1, intercept = 0). Results Pooled regression slope for estimated PDFF values versus phantom-derived reference PDFF values was 0.97 (95% CI: 0.96, 0.98) in the biologically relevant 0%-47.5% PDFF range. The corresponding pooled intercept was -0.27% (95% CI: -0.50%, -0.05%). Across vendors, slope ranges were 0.86-1.02 (vendor protocols) and 0.97-1.0 (standardized protocol) at 1.5 T and 0.91-1.01 (vendor protocols) and 0.87-1.01 (standardized protocol) at 3.0 T. The intercept ranges (absolute PDFF percentage) were -0.65% to 0.18% (vendor protocols) and -0.69% to -0.17% (standardized protocol) at 1.5 T and -0.48% to 0.10% (vendor protocols) and -0.78% to -0.21% (standardized protocol) at 3.0 T. Conclusion Proton density fat fraction estimation derived from three-dimensional chemical shift-encoded MRI in a commercial phantom was accurate across vendors, imaging centers, and field strengths, with use of the vendors' product acquisition and reconstruction software. © RSNA, 2021 See also the editorial by Dyke in this issue.

Purpose To determine the linearity, bias, and precision of hepatic proton density fat fraction (PDFF) measurements by using magnetic resonance (MR) imaging across different field strengths, imager manufacturers, and reconstruction methods. Materials and Methods This meta-analysis was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic literature search identified studies that evaluated the linearity and/or bias of hepatic PDFF measurements by using MR imaging (hereafter, MR imaging-PDFF) against PDFF measurements by using colocalized MR spectroscopy (hereafter, MR spectroscopy-PDFF) or the precision of MR imaging-PDFF. The quality of each study was evaluated by using the Quality Assessment of Studies of Diagnostic Accuracy 2 tool. De-identified original data sets from the selected studies were pooled. Linearity was evaluated by using linear regression between MR imaging-PDFF and MR spectroscopy-PDFF measurements. Bias, defined as the mean difference between MR imaging-PDFF and MR spectroscopy-PDFF measurements, was evaluated by using Bland-Altman analysis. Precision, defined as the agreement between repeated MR imaging-PDFF measurements, was evaluated by using a linear mixed-effects model, with field strength, imager manufacturer, reconstruction method, and region of interest as random effects. Results Twenty-three studies (1679 participants) were selected for linearity and bias analyses and 11 studies (425 participants) were selected for precision analyses. MR imaging-PDFF was linear with MR spectroscopy-PDFF (R2 = 0.96). Regression slope (0.97; P < .001) and mean Bland-Altman bias (-0.13%; 95% limits of agreement: -3.95%, 3.40%) indicated minimal underestimation by using MR imaging-PDFF. MR imaging-PDFF was precise at the region-of-interest level, with repeatability and reproducibility coefficients of 2.99% and 4.12%, respectively. Field strength, imager manufacturer, and reconstruction method each had minimal effects on reproducibility. Conclusion MR imaging-PDFF has excellent linearity, bias, and precision across different field strengths, imager manufacturers, and reconstruction methods. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on October 2, 2017.

Purpose To perform a meta-analysis to generate an estimate of the repeatability coefficient (RC) for magnetic resonance (MR) elastography of the liver. Materials and Methods A systematic search of databases was performed for publications on MR elastography during the 10-year period between 2006 and 2015. The identified studies were screened independently and were verified reciprocally by all authors. Two reviewers independently determined the percentage RC and effective sample size from each article. A forest plot was constructed of the percentage RC estimates from the 12 studies. Bootstrap 95% confidence intervals (CIs) were constructed for the summary percentage RCs. Results Twelve studies comprising 274 patients met the eligibility criteria and were included for analysis. A flow diagram of studies included according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was prepared for the inclusion and exclusion criteria. All studies included in the meta-analysis fulfilled four or more of the seven categories of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2. The estimated summary RC was 22% (95% CI: 16.1%, 28.2%). The three main sources for this heterogeneity were the trained versus untrained operator drawing contours to choose regions of interest, the time between two replicate examinations, and, finally, the field strength of the MR imaging unit. The RC estimates tended to be higher for studies that did not use a well-trained operator, those with 1.5-T field strength imaging units, and those with longer time intervals between examinations. Conclusion The meta-analysis results provide the basis for the following draft longitudinal Quantitative Imaging Biomarkers Alliance MR elastography claim: A measured change in hepatic stiffness of 22% or greater, at the same site and with use of the same equipment and acquisition sequence, indicates that a true change in stiffness has occurred with 95% confidence. © RSNA, 2017.

Rationale and objectivesTumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile.Materials and methodsIndustry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers.ResultsIntra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility was determined in three partitions and was found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters greater than 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not ony in overall volume but also in detail.ConclusionsNine of the 12 participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the present study was not designed to explicitly evaluate algorithm profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes greater than 10 mm. No partition of the algorithms was able to meet the QIBA requirements for interchangeability down to 10 mm, although the partition comprising best performing algorithms did meet this requirement for a tumor size of greater than approximately 40 mm.

Background: Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases. Methods: For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment. Results: The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and − 16.3% for SUVmax, and 21.2% and − 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak. Conclusion: In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this investigation was to assess the effect of visceral adipose tissue volume (VA) on reader efficacy in diagnosing and characterizing small bowel Crohn's disease using lower exposure CT enterography (CTE). Secondarily, we investigated the effect of lower exposure and VA on reader diagnostic confidence. Methods: Prospective paired investigation of 256 CTE, 129 with Crohn's disease, were reconstructed at 100% and simulated 50% and 30% exposure. The senior author provided the disease classification for the 129 patients with Crohn's disease. Patient VA was measured, and exams were evaluated by six readers for presence or absence of Crohn's disease and phenotype using a 0–10‐point scale. Logistic regression models assessed the effect of VA on sensitivity and specificity. Results: The effect of VA on sensitivity was significantly reduced at 30% exposure (odds radio [OR]: 1.00) compared to 100% exposure (OR: 1.12) (p = 0.048). There was no statistically significant difference among the exposures with respect to the effect of visceral fat on specificity (p = 0.159). The study readers' probability of agreement with the senior author on disease classification was 60%, 56%, and 53% at 100%, 50%, and 30% exposure, respectively (p = 0.004). When detecting low severity Crohn's disease, readers' mean sensitivity was 83%, 75%, and 74% at 100%, 50%, and 30% exposure, respectively (p = 0.002). In low severity disease, sensitivity also tended to increase as visceral fat increased (ORs per 1000 cm3 increase in visceral fat: 1.32, 1.31, and 1.18, p = 0.010, 0.016, and 0.100, at 100%, 50%, and 30% exposure). Conclusions: While the interaction is complex, VA plays a role in detecting and characterizing small bowel Crohn's disease when exposure is altered, particularly in low severity disease. [ABSTRACT FROM AUTHOR]