Imaging as an early biomarker to predict sensitivity to everolimus for progressive NF2-related vestibular schwannoma.

PURPOSE: NF2-related schwannomatosis (NF2) is characterized by bilateral vestibular schwannomas (VS) often causing hearing and neurologic deficits, with currently no FDA-approved drug treatment. Pre-clinical studies highlighted the potential of mTORC1 inhibition in delaying schwannoma progression. We conducted a prospective open-label, phase II study of everolimus for progressive VS in NF2 patients and investigated imaging as a potential biomarker predicting effects on growth trajectory. METHODS: The trial enrolled 12 NF2 patients with progressive VS. Participants received oral everolimus daily for 52 weeks. Brain imaging was obtained quarterly. As primary endpoint, radiographic response (RR) was defined as ≥ 20% decrease in target VS volume. Secondary endpoints included other tumors RR, hearing outcomes, drug safety and quality of life (QOL). RESULTS: Eight participants completed the trial and four discontinued the drug early due to significant volumetric VS progression. After 52 weeks of treatment, the median annual VS growth rate decreased from 77.2% at baseline to 29.4%. There was no VS RR and 3 of 8 (37.5%) participants had stable disease. Decreased or unchanged VS volume after 3 months of treatment was predictive of stabilization at 12 months. Seven of eight participants had stable hearing during treatment except one with a decline in word recognition score. Ten of twelve participants reported only minimal changes to their QOL scores. CONCLUSIONS: Volumetric imaging at 3 months can serve as an early biomarker to predict long-term sensitivity to everolimus treatment. Everolimus may represent a safe treatment option to decrease the growth of NF2-related VS in patients who have stable hearing and neurological condition. TRN: NCT01345136 (April 29, 2011).

Evaluation of Non-Compressive Transvaginal Cervical Elastography as a Quantitative Imaging Biomarker in Pregnancy: A Repeatability and Reliability Analysis.

OBJECTIVES: Non-compressive strain elastography has been proposed as a novel quantitative imaging biomarker for assessing the structure and function of the cervix. The current study aims to assess the repeatability, and intra- and inter-observer reliability of transvaginal non-compressive cervical strain elastography in a clinical setting. METHODS: We conducted a dual-phase single-center prospective feasibility study of singleton gestations >16-weeks gestation that required a clinically-indicated transvaginal ultrasound. Each study participant, n = 43 in phase 1 and n = 13 in phase 2, had elastography performed by two trained observers that each performed multiple image acquisitions. We performed a multivariable regression to adjust for changes in clinical characteristics between study phases and calculated the repeatability coefficients, limits of agreement, and intraclass correlations for each quantitative elastography parameter. We compared quantitative elastography parameters to cervical length measurements, acquired from the same images. RESULTS: The repeatability coefficients and percent limits of agreement were wide for all of the quantitative elastography parameters, demonstrating poor repeatability. Intraclass correlation coefficients were poor-moderate for both intra-observer (0.31-0.77) and inter-observer reliability (0.35-0.77) in both study phases, while cervical length showed excellent reliability with intraclass correlations consistently >0.90. CONCLUSIONS: Non-compressive transvaginal strain cervical elastography did not demonstrate adequate repeatability or reliability. Our results highlight the importance of rigorously assessing novel quantitative imaging biomarkers before clinical application.

Five multivariate Duchenne muscular dystrophy progression models bridging six-minute walk distance and MRI relaxometry of leg muscles.

The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 model variables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials.

High-frequency Quantitative Ultrasound Imaging of Human Rotator Cuff Muscles: Assessment of Repeatability and Reproducibility.

This study evaluated the repeatability and reproducibility of using high-frequency quantitative ultrasound (QUS) measurement of backscatter coefficient (BSC), grayscale analysis, and gray-level co-occurrence matrix (GLCM) textural analysis, to characterize human rotator cuff muscles. The effects of varying scanner settings across two different operators and two US systems were investigated in a healthy volunteer with normal rotator cuff muscles and a patient with chronic massive rotator cuff injury and substantial muscle degeneration. The results suggest that BSC is a promising method for assessing rotator cuff muscles in both control and pathological subjects, even when operators were free to adjust system settings (depth, level of focus, and time-gain compensation). Measurements were repeatable and reproducible across the different operators and ultrasound imaging platforms. In contrast, grayscale and GLCM analyses were found to be less reliable in this setting, with significant measurement variability. Overall, the repeatability and reproducibility measurements of BSC indicate its potential as a diagnostic tool for rotator cuff muscle evaluation.

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.

Comparison of inversion methods in MR elastography: An open-access pipeline for processing multifrequency shear-wave data and demonstration in a phantom, human kidneys, and brain.

PURPOSE: Magnetic resonance elastography (MRE) maps the viscoelastic properties of soft tissues for diagnostic purposes. However, different MRE inversion methods yield different results, which hinder comparison of values, standardization, and establishment of quantitative MRE markers. Here, we introduce an expandable, open-access, webserver-based platform that offers multiple inversion techniques for multifrequency, 3D MRE data. METHODS: The platform comprises a data repository and standard MRE inversion methods including local frequency estimation (LFE), direct-inversion based multifrequency dual elasto-visco (MDEV) inversion, and wavenumber-based (k-) MDEV. The use of the platform is demonstrated in phantom data and in vivo multifrequency MRE data of the kidneys and brains of healthy volunteers. RESULTS: Detailed maps of stiffness were generated by all inversion methods showing similar detail of anatomy. Specifically, the inner renal cortex had higher shear wave speed (SWS) than renal medulla and outer cortex without lateral differences. k-MDEV yielded higher SWS values than MDEV or LFE (full kidney/brain k-MDEV: 2.71 ± 0.19/1.45 ± 0.14 m/s, MDEV: 2.14 ± 0.16/0.99 ± 0.11 m/s, LFE: 2.12 ± 0.15/0.89 ± 0.06 m/s). CONCLUSION: The freely accessible platform supports the comparison of MRE results obtained with different inversion methods, filter thresholds, or excitation frequencies, promoting reproducibility in MRE across community-developed methods.

Quantitative imaging biomarkers of immune-related adverse events in immune-checkpoint blockade-treated metastatic melanoma patients: a pilot study.

PURPOSE: To develop quantitative molecular imaging biomarkers of immune-related adverse event (irAE) development in malignant melanoma (MM) patients receiving immune-checkpoint inhibitors (ICI) imaged with 18F-FDG PET/CT. METHODS: 18F-FDG PET/CT images of 58 MM patients treated with anti-PD-1 or anti-CTLA-4 ICI were retrospectively analyzed for indication of irAE. Three target organs, most commonly affected by irAE, were considered: bowel, lung, and thyroid. Patient charts were reviewed to identify which patients experienced irAE, irAE grade, and time to irAE diagnosis. Target organs were segmented using a convolutional neural network (CNN), and novel quantitative imaging biomarkers - SUV percentiles (SUVX%) of 18F-FDG uptake within the target organs - were correlated with the clinical irAE status. Area under the receiver-operating characteristic curve (AUROC) was used to quantify irAE detection performance. Patients who did not experience irAE were used to establish normal ranges for target organ 18F-FDG uptake. RESULTS: A total of 31% (18/58) patients experienced irAE in the three target organs: bowel (n=6), lung (n=5), and thyroid (n=9). Optimal percentiles for identifying irAE were bowel (SUV95%, AUROC=0.79), lung (SUV95%, AUROC=0.98), and thyroid (SUV75%, AUROC=0.88). Optimal cut-offs for irAE detection were bowel (SUV95%>2.7 g/mL), lung (SUV95%>1.7 g/mL), and thyroid (SUV75%>2.1 g/mL). Normal ranges (95% confidence interval) for the SUV percentiles in patients without irAE were bowel [1.74, 2.86 g/mL], lung [0.73, 1.46 g/mL], and thyroid [0.86, 1.99 g/mL]. CONCLUSIONS: Increased 18F-FDG uptake within irAE-affected organs provides predictive information about the development of irAE in MM patients receiving ICI and represents a potential quantitative imaging biomarker for irAE. Some irAE can be detected on 18F-FDG PET/CT well before clinical symptoms appear.

B0 and B1 inhomogeneities in the liver at 1.5 T and 3.0 T.

PURPOSE: The purpose of this work is to characterize the magnitude and variability of B0 and B1 inhomogeneities in the liver in large cohorts of patients at both 1.5 T and 3.0 T. METHODS: Volumetric B0 and B1 maps were acquired over the liver of patients presenting for routine abdominal MRI. Regions of interest were drawn in the nine Couinaud segments of the liver, and the average value was recorded. Magnitude and variation of measured averages in each segment were reported across all patients. RESULTS: A total of 316 B0 maps and 314 B1 maps, acquired at 1.5 T and 3.0 T on a variety of GE Healthcare MRI systems in 630 unique exams, were identified, analyzed, and, in the interest of reproducible research, de-identified and made public. Measured B0 inhomogeneities ranged (5th-95th percentiles) from -31.7 Hz to 164.0 Hz for 3.0 T (-14.5 Hz to 81.3 Hz at 1.5 T), while measured B1 inhomogeneities (ratio of actual over prescribed flip angle) ranged from 0.59 to 1.13 for 3.0 T (0.83 to 1.11 at 1.5 T). CONCLUSION: This study provides robust characterization of B0 and B1 inhomogeneities in the liver to guide the development of imaging applications and protocols. Field strength, bore diameter, and sex were determined to be statistically significant effects for both B0 and B1 uniformity. Typical clinical liver imaging at 3.0 T should expect B0 inhomogeneities ranging from approximately -100 Hz to 250 Hz (-50 Hz to 150 Hz at 1.5 T) and B1 inhomogeneities ranging from approximately 0.4 to 1.3 (0.7 to 1.2 at 1.5 T).

Design and evaluation of quantitative MRI phantoms to mimic the simultaneous presence of fat, iron, and fibrosis in the liver.

PURPOSE: To design, construct, and evaluate quantitative MR phantoms that mimic MRI signals from the liver with simultaneous control of three parameters: proton-density fat fraction (PDFF), R2∗ , and T1 . These parameters are established biomarkers of hepatic steatosis, iron overload, and fibrosis/inflammation, respectively, which can occur simultaneously in the liver. METHODS: Phantoms including multiple vials were constructed. Peanut oil was used to modulate PDFF, MnCl2 and iron microspheres were used to modulate R2∗ , and NiCl2 was used to modulate the T1 of water (T1,water ). Phantoms were evaluated at both 1.5 T and 3 T using stimulated-echo acquisition-mode MRS and chemical shift-encoded MRI. Stimulated-echo acquisition-mode MRS data were processed to estimate T1,water , T1,fat , R2,water∗ , and R2,fat∗ for each vial. Chemical shift-encoded MRI data were processed to generate PDFF and R2∗ maps, and measurements were obtained in each vial. Measurements were evaluated using linear regression and Bland-Altman analysis. RESULTS: High-quality PDFF and R2∗ maps were obtained with homogeneous values throughout each vial. High correlation was observed between imaging PDFF with target PDFF (slope = 0.94-0.97, R2 = 0.994-0.997) and imaging R2∗ with target R2∗ (slope = 0.84-0.88, R2 = 0.935-0.943) at both 1.5 T and 3 T. The values of R2,fat∗ and R2,water∗ were highly correlated with slope close to 1.0 at both 1.5 T (slope = 0.90, R2 = 0.988) and 3 T (slope = 0.99, R2 = 0.959), similar to the behavior observed in vivo. The value of T1,water (500-1200 ms) was controlled with varying NiCl2 concentration, while T1,fat (300 ms) was independent of NiCl2 concentration. CONCLUSION: Novel quantitative MRI phantoms that mimic the simultaneous presence of fat, iron, and fibrosis in the liver were successfully developed and validated.

An update in musculoskeletal tumors: from quantitative imaging to radiomics.

In the last two decades, relevant progress has been made in the diagnosis of musculoskeletal tumors due to the development of new imaging tools, such as diffusion-weighted imaging, diffusion kurtosis imaging, magnetic resonance spectroscopy, and diffusion tensor imaging. Another important role has been played by the development of artificial intelligence software based on complex algorithms, which employ computing power in the detection of specific tumor types. The aim of this article is to report the most advanced imaging techniques focusing on their advantages in clinical practice.

Normal range for MR elastography measured liver stiffness in children without liver disease.

BACKGROUND: Magnetic resonance elastography (MRE) can determine the presence and stage of liver fibrosis. Data on normative MRE values, while reported in adults, are limited in children. PURPOSE: To determine the distribution of MRE-measured liver stiffness in children without liver disease. STUDY TYPE: Prospective, observational. POPULATION: Eighty-one healthy children (mean 12.6 ± 2.6 years, range 8-17 years). FIELD STRENGTH/SEQUENCE: 3.0T Signa HDxt, General Electric MR Scanner; 2D GRE MRE sequence. ASSESSMENT: History, examination, laboratory evaluation, and (MR) exams (proton density fat fraction, PDFF, and MRE) were performed. MR elastograms were analyzed manually at two reading centers and compared with each other for agreement and with published values in healthy adults and thresholds for fibrosis in adult and pediatric patients. STATISTICAL TESTS: Descriptive statistics, Bland-Altman analysis, t-test to compare hepatic stiffness values with reference standards. RESULTS: Stiffness values obtained at both reading centers were similar, without significant bias (P = 0.362) and with excellent correlation (intraclass correlation coefficient [ICC] = 0.782). Mean hepatic stiffness value for the study population was 2.45 ± 0.35 kPa (95th percentile 3.19 kPa), which was significantly higher than reported values for healthy adult subjects (2.10 ± 0.23 kPa, P < 0.001). In all, 74-85% of subjects had stiffness measurements suggestive of no fibrosis. DATA CONCLUSION: Mean liver stiffness measured with MRE in this cohort was significantly higher than that reported in healthy adults. Despite rigorous screening, some healthy children had stiffness measurements suggestive of liver fibrosis using current published thresholds. Although MRE has the potential to provide noninvasive assessment in patients with suspected hepatic disease, further refinement of this technology will help advance its use as a diagnostic tool for evidence of fibrosis in pediatric populations. LEVEL OF EVIDENCE: 1 Technical Efficacy: 5 J. Magn. Reson. Imaging 2020;51:919-927.

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials.

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.

Intrasubject repeatability of in vivo intervertebral motion parameters using quantitative fluoroscopy.

PURPOSE: In vivo quantification of intervertebral motion through imaging has progressed to a point where biomarkers for low back pain are emerging. This makes possible deeper study of the condition's biometrics. However, the measurement of change over time involves error. The purpose of this prospective investigation is to determine the intrasubject repeatability of six in vivo intervertebral motion parameters using quantitative fluoroscopy. METHODS: Intrasubject reliability (ICC) and minimal detectable change (MDC) of baseline to 6-week follow-up measurements were calculated for six lumbar spine intervertebral motion parameters in 109 healthy volunteers. A standardised quantitative fluoroscopy (QF) protocol was used to provide measurements in the coronal and sagittal planes using both passive recumbent and active weight-bearing motion. Parameters were: intervertebral range of motion (IV-RoM), laxity, motion sharing inequality (MSI), motion sharing variability (MSV), flexion translation and anterior disc height change during flexion. RESULTS: The best overall intrasubject reliability (ICC) and agreement (MDC) were for disc height (ICC 0.89, MDC 43%) and IV-RoM (ICC 0.96, MDC 60%), and the worst for MSV (ICC 0.04, MDC 408%). Laxity, MSI and translation had acceptable reliability (most ICCs > 0.60), but not agreement (MDC > 85%). CONCLUSION: Disc height and IV-RoM measurement using QF could be considered for randomised trials, while laxity, MSI and translation could be considered for moderators, correlates or mediators of patient-reported outcomes. MSV had both poor reliability and agreement over 6 weeks. These slides can be retrieved under Electronic Supplementary Material.

Quantitative determination of pancreas size using anatomical landmarks and its clinical relevance: A systematic literature review.

There have been many reports of altered pancreas size in diseases of the endocrine and exocrine pancreas, but few attempts to quantify such changes. The aim of this study was to conduct a systematic literature review, documenting the methodology, and quantitative data in studies reporting on pancreas size. Three electronic databases (Embase, Scopus, and MEDLINE) were searched by two reviewers independently. Studies of humans were included if they compared pancreas size (reported as pancreas diameters, areas, and/or lengths) between diseased populations and controls. A total of 28 studies with 3,810 individuals were included. Among these, 22 measured pancreas diameters, seven measured pancreas areas, and one measured pancreas lengths. The most common landmark for the head of the pancreas was the confluence of the superior mesenteric and splenic veins (three out of nine studies, 33.3%); for the body it was the superior mesenteric artery (seven out of nine, 77.8%); for the tail it was the internal border of the left kidney (two out of six, 33.3%). Pancreas diameters and areas tended to be smaller in diabetes mellitus, the extent of reduction being greater in individuals with type 1 than type 2 diabetes. Pancreas diameters tended to be greater in acute pancreatitis and pancreatic cancer but not in chronic pancreatitis. Pancreas diameters are a clinically relevant measure for diseases of the endocrine and exocrine pancreas. Consensus guidelines need to be developed to standardize their measurements. Clin. Anat. 31:913-926, 2018. © 2018 Wiley Periodicals, Inc.

Liver histology and diffusion-weighted MRI in children with nonalcoholic fatty liver disease: A MAGNET study.

PURPOSE: To determine potential associations between histologic features of pediatric nonalcoholic fatty liver disease (NAFLD) and estimated quantitative magnetic resonance diffusion-weighted imaging (DWI) parameters. MATERIALS AND METHODS: This prospective, cross-sectional study was performed as part of the Magnetic Resonance Assessment Guiding NAFLD Evaluation and Treatment (MAGNET) ancillary study to the Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN). Sixty-four children underwent a 3T DWI scan (b-values: 0, 100, and 500 s/mm2 ) within 180 days of a clinical liver biopsy of the right hepatic lobe. Three parameters were estimated in the right hepatic lobe: apparent diffusion coefficient (ADC), diffusivity (D), and perfusion fraction (F); the first assuming exponential decay and the latter two assuming biexponential intravoxel incoherent motion. Grading and staging of liver histology were done using the NASH CRN scoring system. Associations between histologic scores and DWI-estimated parameters were tested using multivariate linear regression. RESULTS: Estimated means ± standard deviations were: ADC: 1.3 (0.94-1.8) × 10-3 mm2 /s; D: 0.82 (0.56-1.0) × 10-3 mm2 /s; and F: 17 (6.0-28)%. Multivariate analyses showed ADC and D decreased with steatosis and F decreased with fibrosis (P < 0.05). Associations between DWI-estimated parameters and other histologic features were not significant: ADC: fibrosis (P = 0.12), lobular inflammation (P = 0.20), portal inflammation (P = 0.27), hepatocellular inflammation (P = 0.29), NASH (P = 0.30); D: fibrosis (P = 0.34), lobular inflammation (P = 0.84), portal inflammation (P = 0.76), hepatocellular inflammation (P = 0.38), NASH (P = 0.81); F: steatosis (P = 0.57), lobular inflammation (P = 0.22), portal inflammation (P = 0.42), hepatocellular inflammation (P = 0.59), NASH (P = 0.07). CONCLUSION: In children with NAFLD, steatosis and fibrosis have independent effects on DWI-estimated parameters ADC, D, and F. Further research is needed to determine the underlying mechanisms and clinical implications of these effects. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1149-1158.

A Pilot Comparative Study of Quantitative Ultrasound, Conventional Ultrasound, and MRI for Predicting Histology-Determined Steatosis Grade in Adult Nonalcoholic Fatty Liver Disease.

OBJECTIVE: The purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD). SUBJECTS AND METHODS: In this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift-based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed. RESULTS: CUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all). CONCLUSION: Preliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD.

Big data in oncologic imaging.

Cancer is a complex disease and unfortunately understanding how the components of the cancer system work does not help understand the behavior of the system as a whole. In the words of the Greek philosopher Aristotle "the whole is greater than the sum of parts." To date, thanks to improved information technology infrastructures, it is possible to store data from each single cancer patient, including clinical data, medical images, laboratory tests, and pathological and genomic information. Indeed, medical archive storage constitutes approximately one-third of total global storage demand and a large part of the data are in the form of medical images. The opportunity is now to draw insight on the whole to the benefit of each individual patient. In the oncologic patient, big data analysis is at the beginning but several useful applications can be envisaged including development of imaging biomarkers to predict disease outcome, assessing the risk of X-ray dose exposure or of renal damage following the administration of contrast agents, and tracking and optimizing patient workflow. The aim of this review is to present current evidence of how big data derived from medical images may impact on the diagnostic pathway of the oncologic patient.

Intra- and inter-examination repeatability of magnetic resonance spectroscopy, magnitude-based MRI, and complex-based MRI for estimation of hepatic proton density fat fraction in overweight and obese children and adults.

PURPOSE: Determine intra- and inter-examination repeatability of magnitude-based magnetic resonance imaging (MRI-M), complex-based magnetic resonance imaging (MRI-C), and magnetic resonance spectroscopy (MRS) at 3T for estimating hepatic proton density fat fraction (PDFF), and using MRS as a reference, confirm MRI-M and MRI-C accuracy. METHODS: Twenty-nine overweight and obese pediatric (n = 20) and adult (n = 9) subjects (23 male, 6 female) underwent three same-day 3T MR examinations. In each examination MRI-M, MRI-C, and single-voxel MRS were acquired three times. For each MRI acquisition, hepatic PDFF was estimated at the MRS voxel location. Intra- and inter-examination repeatability were assessed by computing standard deviations (SDs) and intra-class correlation coefficients (ICCs). Aggregate SD was computed for each method as the square root of the average of first repeat variances. MRI-M and MRI-C PDFF estimation accuracy was assessed using linear regression with MRS as a reference. RESULTS: For MRI-M, MRI-C, and MRS acquisitions, respectively, mean intra-examination SDs were 0.25%, 0.42%, and 0.49%; mean intra-examination ICCs were 0.999, 0.997, and 0.995; mean inter-examination SDs were 0.42%, 0.45%, and 0.46%; and inter-examination ICCs were 0.995, 0.992, and 0.990. Aggregate SD for each method was <0.9%. Using MRS as a reference, regression slope, intercept, average bias, and R (2), respectively, for MRI-M were 0.99%, 1.73%, 1.61%, and 0.986, and for MRI-C were 0.96%, 0.43%, 0.40%, and 0.991. CONCLUSION: MRI-M, MRI-C, and MRS showed high intra- and inter-examination hepatic PDFF estimation repeatability in overweight and obese subjects. Longitudinal hepatic PDFF change >1.8% (twice the maximum aggregate SD) may represent real change rather than measurement imprecision. Further research is needed to assess whether examinations performed on different days or with different MR technologists affect repeatability of MRS voxel placement and MRS-based PDFF measurements.

Special Report on the Consensus QIBA Profile for Objective Analytical Validation of Non-calcified and High-risk Plaque and Other Biomarkers using Computed Tomography Angiography.

RATIONALE AND OBJECTIVES: Evidence is building in support of the clinical utility of atherosclerotic plaque imaging by computed tomography angiography (CTA). There is increasing organized activity to embrace non-calcified plaque (NCP) as a formally defined biomarker for clinical trials, and high-risk plaque (HRP) for clinical care, as the most relevant measures for the field to advance and worthy of community efforts to validate. Yet the ability to assess the quantitative performance of any given specific solution to make these measurements or classifications is not available. Vendors use differing definitions, assessment metrics, and validation data sets to describe their offerings without clinician users having the capability to make objective assessments of accuracy and precision and how this affects diagnostic confidence. MATERIALS AND METHODS: The QIBA Profile for Atherosclerosis Biomarkers by CTA was created by the Quantitative Imaging Biomarkers Alliance (QIBA) to improve objectivity and decrease the variability of noninvasive plaque phenotyping. The Profile provides claims on the accuracy and precision of plaque measures individually and when combined. RESULTS: Individual plaque morphology measurements are evaluated in terms of bias (accuracy), slope (consistency of the bias across the measurement range, needed for measurements of change), and variability. The multiparametric plaque stability phenotype is evaluated in terms of agreement with expert pathologists. The Profile is intended for a broad audience, including those engaged in discovery science, clinical trials, and patient care. CONCLUSION: This report provides a rationale and overview of the Profile claims and how to comply with the Profile in research and clinical practice. SUMMARY STATEMENT: This article summarizes objective means to validate the analytical performance of non-calcified plaque (NCP), other emerging plaque morphology measurements, and multiparametric histology-defined high-risk plaque (HRP), as outlined in the QIBA Profile for Atherosclerosis Biomarkers by CTA.

Multipeak fat-corrected complex R2* relaxometry: theory, optimization, and clinical validation.

PURPOSE: To develop R2* mapping techniques corrected for confounding factors and optimized for noise performance. THEORY AND METHODS: Conventional R2* mapping is affected by two key confounding factors: noise-related bias and the presence of fat in tissue. Noise floor effects introduce bias in magnitude-based reconstructions, particularly at high R2* values. The presence of fat, if uncorrected, introduces severe protocol-dependent bias. In this work, the bias/noise properties of different R2* mapping reconstructions (magnitude- and complex-fitting, fat-uncorrected, and fat-corrected) are characterized using Cramer-Rao Bound analysis, simulations, and in vivo data. A framework for optimizing the choice of echo times is provided. Finally, the robustness of liver R2* mapping in the presence of fat is evaluated in 28 subjects. RESULTS: Fat-corrected R2* mapping removes fat-related bias without noise penalty over a wide range of R2* values. Complex nonlinear least-squares fitted and fat-corrected R2* reconstructions that account for the spectral complexity of fat provide robust R2* estimates with low bias and optimized noise performance over a wide range of echo times combinations and R2* values. CONCLUSION: The use of complex fitting and fat-correction improves the robustness, noise performance, and accuracy of R2* measurements, and are necessary to establish R2* as quantitative imaging biomarker in the liver.