Ultrasound-Guided Musculoskeletal Injections.

Musculoskeletal injections serve a variety of diagnostic and therapeutic purposes, with ultrasonography (US) guidance having many advantages: no ionizing radiation, real-time guidance, high spatial resolution, excellent soft tissue contrast, and the ability to identify and avoid critical structures. Sonography can be cost effective and afford flexibility in resource-constrained settings. This article describes US-guided musculoskeletal injections relevant to many radiology practices and provides experience-based suggestions. Structures covered include multiple joints (shoulder, hip), bursae (iliopsoas, subacromial-subdeltoid, greater trochanteric), peripheral nerves (sciatic, radial), and tendon sheaths (posterior tibial, peroneal, flexor hallucis longus, Achilles, long head of the biceps). Trigger point and similar targeted steroid injections, as well as calcific tendinopathy barbotage, are also described.

Automated Volumetric Assessment of Hepatocellular Carcinoma Response to Sorafenib: A Pilot Study.

PURPOSE: This pilot study evaluates the feasibility of automated volumetric quantification of hepatocellular carcinoma (HCC) as an imaging biomarker to assess treatment response for sorafenib. METHODS: In this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study, a training database of manually labeled background liver, enhancing and nonenhancing tumor tissue was established using pretherapy and first posttherapy multiphasic computed tomography images from a registry of 13 HCC patients. For each patient, Hounsfield density and geometry-based feature images were generated from registered multiphasic computed tomography data sets and used as the input for a random forest-based classifier of enhancing and nonenhancing tumor tissue. Leave-one-out cross-validation of the dice similarity measure was applied to quantify the classifier accuracy. A Cox regression model was used to confirm volume changes as predictors of time to progression (TTP) of target lesions for both manual and automatic methods. RESULTS: When compared with manual labels, an overall classification accuracy of dice similarity coefficient of 0.71 for pretherapy and 0.66 posttherapy enhancing tumor labels and 0.45 for pretherapy and 0.59 for posttherapy nonenhancing tumor labels was observed. Automated methods for quantifying volumetric changes in the enhancing lesion agreed with manual methods and were observed as a significant predictor of TTP. CONCLUSIONS: Automated volumetric analysis was determined to be feasible for monitoring HCC response to treatment. The information extracted using automated volumetrics is likely to reproduce labor-intensive manual data and provide a good predictor for TTP. Further work will extend these studies to additional treatment modalities and larger patient populations.

Rectus femoris knee muscle moment arms measured in vivo during dynamic motion with real-time magnetic resonance imaging.

Moment arms represent a muscle's ability to generate a moment about a joint for a given muscle force. The goal of this study was to develop a method to measure muscle moment arms in vivo over a large range of motion using real-time magnetic resonance (MR) imaging. Rectus femoris muscle-tendon lengths and knee joint angles of healthy subjects (N = 4) were measured during dynamic knee joint flexion and extension in a large-bore magnetic resonance imaging (MRI) scanner. Muscle-tendon moment arms were determined at the knee using the tendon-excursion method by differentiating measured muscle-tendon length with respect to joint angle. Rectus femoris moment arms were averaged across a group of healthy subjects and were found to vary similarly during knee joint flexion (mean: 3.0 (SD 0.5) cm, maximum: 3.5 cm) and extension (mean: 2.8 (SD 0.4) cm, maximum: 3.6 cm). These moment arms compare favorably with previously published dynamic tendon-excursion measurements in cadaveric specimens but were relatively smaller than moment arms from center-of-rotation studies. The method presented here provides a new approach to measure muscle-tendon moment arms in vivo and has the potential to be a powerful resource for characterizing musculoskeletal geometry during dynamic joint motion.

Spatial Distance Correlates With Genetic Distance in Diffuse Glioma.

Background: Treatment effectiveness and overall prognosis for glioma patients depend heavily on the genetic and epigenetic factors in each individual tumor. However, intra-tumoral genetic heterogeneity is known to exist and needs to be managed. Currently, evidence for genetic changes varying spatially within the tumor is qualitative, and quantitative data is lacking. We hypothesized that a greater genetic diversity or "genetic distance" would be observed for distinct tumor samples taken with larger physical distances between them. Methods: Stereotactic biopsies were obtained from untreated primary glioma patients as part of a clinical trial between 2011 and 2016, with at least one biopsy pair collected in each case. The physical (Euclidean) distance between biopsy sites was determined using coordinates from imaging studies. The tissue samples underwent whole exome DNA sequencing and epigenetic methylation profiling and genomic distances were defined in three separate ways derived from differences in number of genes, copy number variations (CNV), and methylation profiles. Results: Of the 31 patients recruited to the trial, 23 were included in DNA methylation analysis, for a total of 71 tissue samples (14 female, 9 male patients, age range 21-80). Samples from an 8 patient subset of the 23 evaluated patients were further included in whole exome and copy number variation analysis. Physical and genomic distances were found to be independently and positively correlated for each of the three genomic distance measures. The correlation coefficients were 0.63, 0.65, and 0.35, respectively for (a) gene level mutations, (b) copy number variation, and (c) methylation status. We also derived quantitative linear relationships between physical and genomic distances. Conclusion: Primary brain tumors are genetically heterogeneous, and the physical distance within a given glioma correlates to genomic distance using multiple orthogonal genomic assessments. These data should be helpful in the clinical diagnostic and therapeutic management of glioma, for example by: managing sampling error, and estimating genetic heterogeneity using simple imaging inputs.

Guiding the first biopsy in glioma patients using estimated Ki-67 maps derived from MRI: conventional versus advanced imaging.

BACKGROUND: Undersampling of gliomas at first biopsy is a major clinical problem, as accurate grading determines all subsequent treatment. We submit a technological solution to reduce the problem of undersampling by estimating a marker of tumor proliferation (Ki-67) using MR imaging data as inputs, against a stereotactic histopathology gold standard. METHODS: MR imaging was performed with anatomic, diffusion, permeability, and perfusion sequences, in untreated glioma patients in a prospective clinical trial. Stereotactic biopsies were harvested from each patient immediately prior to surgical resection. For each biopsy, an imaging description (23 parameters) was developed, and the Ki-67 index was recorded. Machine learning models were built to estimate Ki-67 from imaging inputs, and cross validation was undertaken to determine the error in estimates. The best model was used to generate graphical maps of Ki-67 estimates across the whole brain. RESULTS: Fifty-two image-guided biopsies were collected from 23 evaluable patients. The random forest algorithm best modeled Ki-67 with 4 imaging inputs (T2-weighted, fractional anisotropy, cerebral blood flow, Ktrans). It predicted the Ki-67 expression levels with a root mean square (RMS) error of 3.5% (R2 = 0.75). A less accurate predictive result (RMS error 5.4%, R2 = 0.50) was found using conventional imaging only. CONCLUSION: Ki-67 can be predicted to clinically useful accuracies using clinical imaging data. Advanced imaging (diffusion, perfusion, and permeability) improves predictive accuracy over conventional imaging alone. Ki-67 predictions, displayed as graphical maps, could be used to guide biopsy, resection, and/or radiation in the care of glioma patients.

Multiparametric fat-water separation method for fast chemical-shift imaging guidance of thermal therapies.

PURPOSE: A k-means-based classification algorithm is investigated to assess suitability for rapidly separating and classifying fat/water spectral peaks from a fast chemical shift imaging technique for magnetic resonance temperature imaging. Algorithm testing is performed in simulated mathematical phantoms and agar gel phantoms containing mixed fat/water regions. METHODS: Proton resonance frequencies (PRFs), apparent spin-spin relaxation (T2*) times, and T1-weighted (T1-W) amplitude values were calculated for each voxel using a single-peak autoregressive moving average (ARMA) signal model. These parameters were then used as criteria for k-means sorting, with the results used to determine PRF ranges of each chemical species cluster for further classification. To detect the presence of secondary chemical species, spectral parameters were recalculated when needed using a two-peak ARMA signal model during the subsequent classification steps. Mathematical phantom simulations involved the modulation of signal-to-noise ratios (SNR), maximum PRF shift (MPS) values, analysis window sizes, and frequency expansion factor sizes in order to characterize the algorithm performance across a variety of conditions. In agar, images were collected on a 1.5T clinical MR scanner using acquisition parameters close to simulation, and algorithm performance was assessed by comparing classification results to manually segmented maps of the fat/water regions. RESULTS: Performance was characterized quantitatively using the Dice Similarity Coefficient (DSC), sensitivity, and specificity. The simulated mathematical phantom experiments demonstrated good fat/water separation depending on conditions, specifically high SNR, moderate MPS value, small analysis window size, and low but nonzero frequency expansion factor size. Physical phantom results demonstrated good identification for both water (0.997 ± 0.001, 0.999 ± 0.001, and 0.986 ± 0.001 for DSC, sensitivity, and specificity, respectively) and fat (0.763 ± 0.006, 0.980 ± 0.004, and 0.941 ± 0.002 for DSC, sensitivity, and specificity, respectively). Temperature uncertainties, based on PRF uncertainties from a 5 × 5-voxel ROI, were 0.342 and 0.351°C for pure and mixed fat/water regions, respectively. Algorithm speed was tested using 25 × 25-voxel and whole image ROIs containing both fat and water, resulting in average processing times per acquisition of 2.00 ± 0.07 s and 146 ± 1 s, respectively, using uncompiled MATLAB scripts running on a shared CPU server with eight Intel Xeon(TM) E5640 quad-core processors (2.66 GHz, 12 MB cache) and 12 GB RAM. CONCLUSIONS: Results from both the mathematical and physical phantom suggest the k-means-based classification algorithm could be useful for rapid, dynamic imaging in an ROI for thermal interventions. Successful separation of fat/water information would aid in reducing errors from the nontemperature sensitive fat PRF, as well as potentially facilitate using fat as an internal reference for PRF shift thermometry when appropriate. Additionally, the T1-W or R2* signals may be used for monitoring temperature in surrounding adipose tissue.

Effects of hemoglobin glutamer-250 (bovine) (HBOC-201, Hemopure) on coagulation testing.

Polymerized bovine hemoglobin is currently under investigation as an alternative to blood-banked human red blood cells. Because of the dark red hemolyzed appearance of hemoglobin-based oxygen carrier (HBOC)-201, we sought to describe the effects of HBOC-201 on coagulation analyzers that perform prothrombin times, activated partial thromboplastin times, fibrinogen, and antithrombin. Pooled normal plasma was combined with HBOC-201 to achieve plasma hemoglobin levels of 1.4, 2.6, 3.8, 4.8, and 6.2 g/dL. Results for each test using HBOC-201-prepared plasma were compared with results using saline-matched controls. Two consecutive absolute result differences of >10% between saline controls and HBOC-201 samples were used for determining interference in test accuracy by the concentration of HBOC-201. Mechanical detection methods (fibrometer, STA, CS-190) and the MDA-180 method were less affected by increasing levels of HBOC-201 than optical detection devices for all test parameters.